This review of the year should have come out a few weeks earlier. However I was caught up in completing the series of articles on Bowling and Pitch quality and hence this slight delay. Anyhow the year is still fresh in our memory and here we go. I also do not want to hear the words Bowling/Pitch quality for a month or so.

1. A look at performance of teams during 2011

Team	Tests	Home	Neutral	Away	Home	Neutral	Away	Home	Neutral	Away	Performance
		Wins	Wins	Wins	Draws	Draws	Draws	Losses	Losses	Losses	%
England	8	5	0	1	2	0	0	0	0	0	81.2
Pakistan	10	0	1	5	0	2	1	0	0	1	80.5
Australia	9	2	0	2	0	0	2	2	0	1	56.7
New Zealand	5	0	0	2	1	0	0	1	0	1	53.0
South Africa	5	2	0	0	1	0	0	2	0	0	45.0
India	12	2	0	1	1	0	3	0	0	5	41.7
West Indies	10	1	0	1	2	0	2	2	0	2	40.0
Sri Lanka	11	0	0	1	2	2	2	1	1	2	37.3
Zimbabwe	3	1	0	0	0	0	0	2	0	0	18.0
Bangladesh	5	0	0	0	1	0	0	3	0	1	9.0

This is the traditional 2-1-0 method of evaluating team performance. I have analyzed the matches from home-neutral-away points of view. I have used the 2-1-0 values for the neutral matches and weighed the home matches down by 10% and the away matches upwards by 10%. For another website ratings work I do an additional measure of the team rating points (my famous 100 point split between the two teams). However for this I am going limit myself to the traditional 2-1-0 valuation only.

If one forgets the January disaster for England in the desert, they fully deserve the top position. Their overall record of 6-2-0 is outstanding and the best by any team. Pakistan has only a slightly inferior record of 6-3-1 indicating a welcome resurgence, continuing on to 2012. Just for information, the UAE matches are treated as neutral. Australia left the Ashes trauma of 2010 behind and compiled a 4-2-3 record. New Zealand and South Africa played the minimum of five Tests and compiled identical 2-1-2 records. Then comes India, somewhat fortuitously placed at no.6. They had a 3-4-5 record. They are indeed still lower down if one takes the defeat margins. And let us not forget that the next 3 Tests in 2012 have been thumping losses.

2. An alternate look at performance of teams during 2011

Team	Own RpW	Oth RpW	Difference	Own WpT	Oth WpT	Difference
England	59.2	28.5	30.7	18.5	10.9	7.6
Pakistan	41.6	26.4	15.2	19.6	12.4	7.2
South Africa	30	26.5	3.5	18.2	16.4	1.8
Australia	29.4	28.3	1.1	16.4	17.3	-0.9
Zimbabwe	33.8	34.6	-0.8	17	18.3	-1.3
India	30.9	35.6	-4.7	17.0	17.0	0.0
West Indies	27.7	33	-5.3	15.8	18.4	-2.6
New Zealand	25.8	32.2	-6.4	15.2	19.6	-4.4
Sri Lanka	29.7	40.8	-11	12.6	17.3	-4.6
Bangladesh	27.1	48.6	-21.5	12	18.4	-6.4

I can hear that strident caller saying "Cut the crap. This is what my ten-year old son/nephew/sister/cousin/.. does in 15 minutes flat on a Sunday afternoon. Where is this "alternate look"? Ah! that is coming now. Why were the teams successful? Good bowling and batting and fielding is fine. But what are the numbers? In this table I look at two sets of numbers to throw light on the success of certain teams and failures of the others.

First the RpW (Runs per wicket) values. I have compiled the "own RpW" and "other RpW" values and got the difference. This difference will indicate the success or lack of of the teams. England's own figure is 59.2 (amazing number - indicating an average innings of nearly 600) and 28.5. The "other RpW" is less than half of the "own RpW". The difference is a mind-boggling 30.7. Pakistan has a very respectable 41.6 and a tight 26.7, giving them a difference of 15.2. No wonder these two teams are so far up on the top. Then after a lot of daylight comes South Africa with a difference of 3.5. Australia is the only other team with a positive difference, viz., 1.1. Those who are surprised to see Zimbabwe placed above India, please be reminded that, leaving the Napier disaster aside, they have made a determined return to Test cricket. Their scores since their return are 370, 291, 412, 141, 313 and 331. Very creditable indeed. Compare this with India's sequence in England, viz., 286, 261, 288, 158, 224, 244, 300 and 283. No wonder Zimbabwe, have a difference of 0.8 are placed above India, with a difference of -4.7. One could also say India were lucky enough to play six Tests against West Indies.

The other comparison I have made is between "own WpM (wickets per match)" and "other WpM". After all a team has to take 20 wickets to win. Once again England and Pakistan are way up with a differential of 7.6 (18.5 vs 10.9) and 7.2 (19.6 vs 12.4) wickets respectively. South Africa has 1.8. India has a flat 0.0. Surprisingly Australia have a negative value of 0.9. This is no doubt due to their heavy defeat against England, narrow win over Sri Lanka, the 47 and the loss of 20 wickets in Hobart and Melbourne. Sri Lanka have done poorly in both measures. However let us not forget that they won a Test and two ODIs in South Africa.

3. The top team performances

2003 2011 Eng 87.45 vs Ind 12.55 England won by an innings and 242 runs
2022 2011 Pak 85.66 vs Bng 14.34 Pakistan won by an innings and 184 runs
1989 2011 Eng 82.55 vs Aus 17.45 England won by an innings and 83 runs
2023 2011 Saf 82.49 vs Slk 17.51 South Africa won by an innings and 81 runs
2001 2011 Eng 82.18 vs Ind 17.82 England won by 319 runs
2017 2011 Ind 80.46 vs Win 19.54 India won by an innings and 15 runs
1994 2011 Eng 80.43 vs Slk 19.57 England won by an innings and 14 runs
2004 2011 Eng 80.25 vs Ind 19.75 England won by an innings and 8 runs

These are the eight imposing wins during 2011. The criteria for selection is match rating points of 80 and above for the winning team. This is secured by any innings win or huge run-margin wins. Only one such win qualifies. This methodology has been explained in my September 2010 article. India has been at the receiving end quite often during 2011. The heaviest win was recorded by England over India (innings and 242 runs). Two other wins by England also fall in this category. Thus India has lost three matches heavily. India's home win over West Indies was achieved comfortably. In terms of winners, this was, without any question, England's year. 5 of these 8 wins have been achieved by them.

It may be of interest to note that India has started 2012 disastrously. All three of their losses have been worse than 80-20. New Zealand's thumping of Zimbabwe comes out with a 89.2-10.8 rating.

4. The year of the debutant bowler

2016 2011 Philander V.D        Saf Aus  7.0  3  15 5 151.2 Debut
2018 2011 Cummins P.J          Aus Saf 29.0  5  79 6 140.3 Debut
2020 2011 Pattinson J.L        Aus Nzl 11.0  5  27 5 131.4 Debut
2015 2011 Ashwin R             Ind Win 21.3  5  47 6 129.4 Debut
2005 2011 Lyon N.M             Aus Slk 15.0  3  34 5 117.7 Debut
2026 2011 de Lange M           Saf Slk 23.2  3  81 7 116.3 Debut
2010 2011 Elias Sunny          Bng Win 23.0  0  94 6 112.4 Debut
2013 2011 Bracewell D.A.J      Nzl Zim 25.0  2  85 5  99.2 Debut

The selectors only had to select a bowler and he would deliver a five-wicket performance. I have not checked this out but can confidently say that at no time in history would eight bowlers, on debut, have captured five wickets or more within a calendar year. And all these happened during the last four months. The stand-out performance was Philander's match-winning effort, discussed later.

5. The debut centurions

1999 2011 Debut Edwards K.A          Win Ind 110  139.6 Debut
2007 2011 Debut Marsh S.E            Aus Slk 141   94.2 Debut

Two centuries were scored on debut during 2011, Edwards did this during their home series against India. He did reasonably well when West Indies came over to India. Marsh scored a wonderful century against Sri Lanka and then dropped like a brick against India.

6. The top batting performances

2003 2011 Cook A.N             Eng Ind 294  193.0
2004 2011 Dravid R             Ind Eng 146* 186.9
2016 2011 Amla H.M             Saf Aus 112  185.0
1997 2011 Dravid R             Ind Win 112  183.0
2016 2011 Clarke M.J           Aus Saf 151  177.3
...
2021 2011 Warner D.A           Aus Nzl 123* 162.9

These are the top 5 rated batting performances. Dravid essayed two of these, both away. The Oval masterpiece of 146 was the innings people would talk of for years to come. To see him losing his stumps almost every innings over the past month has been painful, to say the least. However for me the two stand-out performances have been by two Australians, both in losing causes. Clarks's 151 was a masterpiece and deserved a win. However their own meltdown prevented that. Warner showed everyone that he is not just an attacking batsman. His unbeaten century would have become Lara/Inzamam/Greenidge-esque if only they had scored seven more runs. This innings was almost similar to Tendulkar's epic of 136 except that Warner remained unconquered.

7. The top bowling performances

1988 2011 Harbhajan Singh      Ind Saf 38.0  1 120 7 180.4
1988 2011 Steyn D.W            Saf Ind 31.0 11  75 5 164.0
2021 2011 Bracewell D.A.J      Nzl Aus 16.4  4  40 6 154.0
2016 2011 Philander V.D        Saf Aus  7.0  3  15 5 151.2
2004 2011 Swann G.P            Eng Ind 38.0  6 106 6 148.1

These were the top rated bowling performances. For me the stand-out performance was that of Philander on his debut. The match was dead and gone with Australia taking a near-200 run lead. Philander, on his debut, bowled the perfect spell, bowling 42 deliveries on the spot. He could probably have taken all 10 wickets, the perfect way he bowled. His spell paved the way for a tough but reasonable task which was achieved quite comfortably. However without Philander, there would have been no Amla/Smith. Only slightly below is Bracewell's match-winning spell at Hobart. He gave the Australians a taste of the medicine they themselves were going to administer the Indian batsmen a few weeks later.

8. A few important measures compared

Measure	2011	2000-10	All-Tests
Runs per wicket	32.5	34.3	31.9
Runs per over	3.15	3.22	2.82
Wickets per match	32.6	30.9	30.7
Result %	69.2	75.3	65.2
Home wins %	33.3	45	38.6
Away wins %	35.9	30.4	26.6
Overs per match	336	329	348
Balls per wicket	61.8	63.9	67.9
% Inns >= 500	5.4	10.2	6.7
% Inns <= 100	2.8	3.4	3.8
Opening Ptshp Avge	30.9	39.6	36.9
% OP >= 100	6.1	9.2	9.2
% OP <= 10	36.1	28.2	28.7
2-5 Ptshp Avge	157.8	160.5	149.6

Now for a look at various measures for 2011, the preceding decade and the 135 year period.

The Runs per wicket values showed a distinct downward trend from the previous decade of over 5%. It is slightly above the all-Tests figure. There were many below-par performances by fancied teams which accounted for this. The Runs per over figure was only marginally lower. The wickets were taken in about 2 balls fewer keeping with the trend of lowering Runs per wicket.

The Wickets per match numbers showed a distinct increase of about 5% from the 2000-10 decade. However the surprising fact is that this did not show a corresponding increase in Result %. On the contrary there was a drop of 6% from the 2000s. Difficult to explain this.

The Home win % showed a huge drop of 25% from the 2000s decade figure. The away wins showed an increase of about 15%. Maybe the sample size of 39 Tests for 2011 is not big enough. It is possible that the slight drop in home performance of Australia and South Africa contributed to this. It is possible that teams, sand India during 2011, also travel better.

Overs per match was only marginally higher at 336 overs. This comprised of 12 draws at an average of 367 overs (quite a few rain-affected draws) and 17 results at an average of 322 overs. Let us convert this at about 14 overs per hour (especially since dawdling India played over 35% of the Tests), this comes to 23 hours. Add to this an hour of wickets falling and innings changes, we come to around 24 hours. This is around 4 days of play. Remember this is on an average. Let me add that the 2012 has started with only 290 overs per match for the 7 conclusive Tests. That is well below 4 days play. Only one Test, the Adelaide one, reached the fifth day: That too, courtesy, Mr. M.J.Clarke.

There is a sharp drop in 500+ innings, just above 50%, the respective figures standing at 5.4 and 10.2% respectively. For that matter the year 2011 was below the all-Tests average. Quite surprisingly, the sub-100 innings also showed a drop from 2000-10 and all-Tests values. Quite inexplicable.

The Opening partnerships failed miserably during 2011. The average runs scored dropped from nearly 40 to just over 30. It was way below the all-Tests figure. Maybe the Indian openers and Strauss and Hughes contributed to this. Similarly there was a significant drop in the 100+ opening partnerships (once in 16 innings as against once in 11 innings) and the sub-10 partnerships showed a sharp increase. Maybe the new crop of exciting pace bowlers contributed to this. Pattinson, Cummins, Philander, Bracewell, Yadav, Broad et al are going to continue in this vein. Ably supported by the resurgence of Siddle, Hilfenhaus, Andersen, et al. Of course Steyn, Morkel, Zaheer are always there. The other significant reason could be the continuing Twenty-20 approach of the openers.

However the middle-order partnerships for the second, third, fourth and fifth wickets have held firm. This value of 158 is quite close to the 2000-10 value of 160.

9. My own abiding memories of 2011

These are strictly my personal selections.

The match of the year was New Zealand's sevn-run win over Australia. Warner batted as he would never have been expected to. Bracewell bowled as Hadlee did 26 years back. Until the last ball bowled by Bracewell to Lyon, the result was in doubt. As Djokovic told a few weeks later at Melbourne, there should have been two winners. Both teams fought hard to the last ball. A close contender was Australia's redeeming series-equalling win over South Africa at Wanderer's.

The innings of the year was Warner's unbeaten 123, referred to quite a few times already. Warner would go through bad patches in his career. He should only rewind the clock back to 13 December 2011 and Hobart, when he almost climbed Everest through the North face. Amazing thing is that Warner's 180 at Perth might very well be the innings of 2012 and it is going to take some beating.

The bowling performance of the year was Philander's 5 for 15 against Australia. The match was dead and gone, but for Philander. I have never seen 42 balls delivered on a coin. That was McGrath-like.

The most forgettable performance of the year was Sehwag's golden pair at Birmingham. He lasted a round 190 overs less than the 7 English batsmen. That symbolized the Indian English debacle as Dravid's loss of his stumps symbolized six months later.

The bravest performance of 2011 was by Zimbabwe on their comeback. They fought hard and four of their six innings exceeded 300. And this was against Pakistan, New Zealand and Bangladesh.

The non-stories of the year were Tendulkar's ton of tons, the various retirement stories circulated, the complete irrelevance of Champions' League (even though, as a contest, it was far superior to IPL) and the millions of words written on India's free fall (all destined to have no effect).

The Indian Test debacles have been chronicled ad nauseam. However the meltdown of the year was Sri Lanka's 24-over capitulation on the last day at Cardiff.

MS Dhoni comes in two situations next. The sporting gesture of the year was Dhoni's recall of Bell. The cop-out of the year was Dhoni's refusal to go for the win at Roseau, against West Indies.

Last month I had embarked on a major project. This had been triggered by a few comments on performance of allrounders in series. Finally after covering the batsmen, bowlers and teams, I have covered the allrounders in Test series, the idea I started with. This concludes the current series of articles but there are some very good follow-up ideas, especially relating to the teams analysis which will be done later.

I am aware that Cricinfo statistics section gives you an insight into the runs scored and wickets captured in Test series. However those are raw numbers and also do not show the results by series types. Even Statsguru might not provide that. What I intend to do is to weight the individual player performances in series with various relevant parameters. It is necessary to recognize where players performed (home or away), how did the performance measure against those of the other bowlers, what were the quality of wickets captured, what was the quality of bowlers, what was the pitch condition, was there a critical series situation et al. That would let us judge performances at their true worth.

The weight basis is the same as has been done in the batting and bowling analyses. The relevant factors considered is given below in summary form. I do not want to repeat the details here.

Batting - Runs scored
1. Where the series was played
2. Series situation
3. Quality of bowling
4. Pitch type
5. Support provided / % of score

Bowling - Wickets captured
1. Where the series was played
2. Series situation
3. Quality of wickets captured
4. Pitch type
5. Bowler's average vs Teams' series average

The key to the all-rounder analysis is in setting the criteria for selection as an all-round performance. Independent bars have to be set up for batting and bowling. These bars cannot be too high: Very few performances would come in. These bars cannot be too close to the ground: Batsmen who can bowl and bowlers who can bat would sneak in. I have arrived at the following criteria after a few trials.

No of Tests  Minimum runs  Minimum wickets
    3             200            10
    4             250            12
    5             300            14
    6             350            16	  

This stiff set of criteria let in only 60 series-level performances making this quite an exclusive and privileged group. That is the purpose behind the exercise also.

Acknowledging the importance of wicketkeepers in a side and the prevailing conviction that wicket-keepers are allrounders, I have done a set of tables for wicketkeepers at the end.

Since we need to consider runs and wickets captured together, I have used 30 runs per wicket as a rough conversion factor to work out a common Run index. The overall 135-year average is just short of 30.0. I debated using the series RpW figure. However this figure has already been used in determining the Pitch type and I did not want double counting of this. Already steps have been taken to see that, if the RpW was high, the runs would discounted and wickets inflated and vice versa. So I have used a standard measure for conversion across. This conversion is necessary to determine the average contribution per match, of players across the series. One table is drawn based on this.

Readers would note that this average is not used in setting up the criteria for selection. These are two different factors. The criteria have been set using ball-park figures and my judgement while the equalization methodology of determining the Run index requires a more objective basis.

This time I have used the actual number of Tests played while determining the average performances. Only series which a player has played a minimum of 3 Tests have been included in this analysis. Also, the three Triangular tournaments, the 1912 one and the two Asian Championships are not included. This is because these are not bi-lateral series.

The tables are shown for 6, 5, 4 and 3 test series. These are ordered on the base information, which is the Run index.

Ser Year Hme-Awy Player          For  #-P RunIdx  Avge   R  W  Wt-R  Wt-W 

232 1981 ENG-Aus Botham I.T     (Eng) 6-6 1397.0 232.8 399 34 457.2 31.33
234 1981 IND-Eng Botham I.T     (Eng) 6-6 1081.4 180.2 440 17 503.7 19.26
190 1974 AUS-Eng Greig A.W      (Eng) 6-6 1063.3 177.2 446 17 532.3 17.70
...
152 1966 ENG-Win Sobers G.St.A  (Win) 5-5 1474.0 294.8 722 20 840.2 21.13
 18 1894 AUS-Eng Giffen G       (Aus) 5-5 1454.6 290.9 475 34 541.3 30.44
185 1974 WIN-Eng Greig A.W      (Eng) 5-5 1319.2 263.8 430 24 476.5 28.09
 33 1910 SAF-Eng Faulkner G.A   (Saf) 5-5 1317.7 263.5 545 29 552.5 25.51
113 1957 SAF-Aus Benaud R       (Aus) 5-5 1268.2 253.6 329 30 408.9 28.64
526 2005 ENG-Aus Flintoff A     (Eng) 5-5 1178.1 235.6 402 24 421.1 25.23
103 1955 WIN-Aus Miller K.R     (Aus) 5-5 1175.8 235.2 439 20 469.6 23.54
161 1968 AUS-Win Sobers G.St.A  (Win) 5-5 1169.7 233.9 497 18 551.9 20.59
 38 1920 AUS-Eng Gregory J.M    (Aus) 5-5 1142.4 228.5 442 23 415.6 24.23
131 1962 WIN-Ind Sobers G.St.A  (Win) 5-5 1084.7 216.9 424 23 412.3 22.41
135 1963 ENG-Win Sobers G.St.A  (Win) 5-5 1073.5 214.7 322 20 379.4 23.14
126 1960 AUS-Win Sobers G.St.A  (Win) 5-5 1071.8 214.4 430 15 525.4 18.21
...
 76 1947 ENG-Saf Edrich W.J     (Eng) 5-4  994.5 248.6 552 16 501.8 16.42
248 1983 ENG-Nzl Hadlee R.J     (Nzl) 4-4  993.4 248.4 301 21 367.5 20.86
157 1967 AUS-Ind Surti R.F      (Ind) 4-4  885.1 221.3 367 15 377.5 16.92
157 1967 AUS-Ind Cowper R.M     (Aus) 4-4  866.6 216.7 485 13 479.2 12.92
106 1955 IND-Nzl Mankad M.H     (Ind) 5-4  858.1 214.5 526 12 506.5 11.72
443 2001 WIN-Saf Pollock S.M    (Saf) 4-4  849.8 212.4 285 19 313.7 17.87
507 2004 ENG-Win Flintoff A     (Eng) 4-4  802.2 200.6 387 14 384.6 13.92
...
240 1982 ENG-Pak Imran Khan     (Pak) 3-3  912.7 304.2 212 21 250.3 22.08
582 2009 SAF-Aus Johnson M.G    (Aus) 3-3  829.2 276.4 255 16 295.0 17.80
153 1966 IND-Win Sobers G.St.A  (Win) 3-3  797.5 265.8 342 14 370.6 14.23
208 1978 NZL-Eng Botham I.T     (Eng) 3-3  734.8 244.9 212 17 239.8 16.50
 40 1921 SAF-Aus Gregory J.M    (Aus) 3-3  718.9 239.6 205 15 229.0 16.33
181 1973 PAK-Eng Mushtaq Mohd   (Pak) 3-3  713.2 237.7 327 12 341.6 12.39
156 1967 ENG-Pak Asif Iqbal     (Pak) 3-3  705.5 235.2 267 11 313.8 13.06
181 1973 PAK-Eng Intikhab Alam  (Pak) 3-3  704.0 234.7 202 15 200.5 16.78

Botham leads the 6-Test series. In the 5-test series, Sobers' once-in-a-100-years performance of 722 runs and 20 wickets leads the way. Giffen, with 475 runs and 34 wickets, is just behind. Look at the number of times Sobers has appeared in the 5-test table.

Bill Edrich, with 552 runs and 16 wickets is a surprise leader in the 4-test group. However look at the performance of Imran Khan in the series against England. 212 runs and 21 wickets. Johnson is a surprise presence here, however, 255 runs and 16 wickets indicating a real allrounder. It is also interesting to note that 4 out of the 8 players in the 3-Test category are Pakistani players.

Now for the second table, a completely performance-based one. This is ordered on the average Run index per match. In other words, consider as approximately equivalent to the number of runs scored per match. To understand the significance a Run index average of 200 indicates 1000 runs in a series, a figure not yet reached.

Ser Year Hme-Awy Player          For  #-P RunIdx  Avge   R  W  Wt-R  Wt-W 

240 1982 ENG-Pak Imran Khan     (Pak) 3-3  912.7 304.2 212 21 250.3 22.08
152 1966 ENG-Win Sobers G.St.A  (Win) 5-5 1474.0 294.8 722 20 840.2 21.13
 18 1894 AUS-Eng Giffen G       (Aus) 5-5 1454.6 290.9 475 34 541.3 30.44
582 2009 SAF-Aus Johnson M.G    (Aus) 3-3  829.2 276.4 255 16 295.0 17.80
153 1966 IND-Win Sobers G.St.A  (Win) 3-3  797.5 265.8 342 14 370.6 14.23
185 1974 WIN-Eng Greig A.W      (Eng) 5-5 1319.2 263.8 430 24 476.5 28.09
 33 1910 SAF-Eng Faulkner G.A   (Saf) 5-5 1317.7 263.5 545 29 552.5 25.51
113 1957 SAF-Aus Benaud R       (Aus) 5-5 1268.2 253.6 329 30 408.9 28.64
 76 1947 ENG-Saf Edrich W.J     (Eng) 5-4  994.5 248.6 552 16 501.8 16.42
248 1983 ENG-Nzl Hadlee R.J     (Nzl) 4-4  993.4 248.4 301 21 367.5 20.86
208 1978 NZL-Eng Botham I.T     (Eng) 3-3  734.8 244.9 212 17 239.8 16.50
 40 1921 SAF-Aus Gregory J.M    (Aus) 3-3  718.9 239.6 205 15 229.0 16.33
181 1973 PAK-Eng Mushtaq Mohd   (Pak) 3-3  713.2 237.7 327 12 341.6 12.39
526 2005 ENG-Aus Flintoff A     (Eng) 5-5 1178.1 235.6 402 24 421.1 25.23
103 1955 WIN-Aus Miller K.R     (Aus) 5-5 1175.8 235.2 439 20 469.6 23.54
156 1967 ENG-Pak Asif Iqbal     (Pak) 3-3  705.5 235.2 267 11 313.8 13.06
181 1973 PAK-Eng Intikhab Alam  (Pak) 3-3  704.0 234.7 202 15 200.5 16.78
161 1968 AUS-Win Sobers G.St.A  (Win) 5-5 1169.7 233.9 497 18 551.9 20.59
232 1981 ENG-Aus Botham I.T     (Eng) 6-6 1397.0 232.8 399 34 457.2 31.33
537 2006 IND-Eng Flintoff A     (Eng) 3-3  693.6 231.2 264 11 302.3 13.04

Imran Khan, with a Run index value of 304, stop for a moment to digest this figure, 300+ runs per Test, leads this performance-oriented table. Sobers' stupendous series during 1966 follows closely with a near-300 figure. Giffen has also got a Run index value exceeding 290. How about Johnson going through a 3-test series averaging 276 runs per test.

Just to complete the Series bowling analysis, I have given below the table of allrounders who have met the tough criteria set. This is a clear indication of the quality of allrounders. Very few would be surprised at the results. Sobers leads with 6 such performances, indicating that he is the supreme allrounder. Botham, five times, Miller and Flintoff, possibly unexpectedly, four times each, confirm their claim to greatness. Surprises, Kapil Dev just once and the presence of Johnson and Harbhajan Singh.

Sobers:     6
Botham:     5
Miller:     4
Flintoff:   4   
         on 2, plenty (J.M.Gregory, Imran Khan, Hadlee, Greig, Kallis).

On this strong evidence, there is very little doubt that Sobers is the supreme allrounder. Botham has also performed the all-round feats in series quite often. Miller, not surprisingly, and Flintoff, quite surprisingly, have reached the lofted heights four times each.

To download the complete list of players who have crossed 500 runs in a Test series, please right-click here and save the file.

Now for the allrounders hall of fame (or more correctly, shame). While I sympathise with these players, I like this part of the exercise since it throws a challenge to me to identify such performances. The only criteria I have set is that the concerned player should have captured 100 Test wickets and scored 2000 Test runs. This is to ensure that the list contains only regular allrounders.

Ser Year Hme-Awy Player          For  #-P RunIdx  Avge   R  W  

302 1990 WIN-Eng Hooper C.L     (Win) 4-3   67.1  16.8  71  0
 96 1953 ENG-Aus Benaud R       (Aus) 5-3   89.9  18.0  15  2
 99 1954 ENG-Pak Bailey T.E     (Eng) 4-3  106.0  26.5  81  1
296 1989 ENG-Aus Botham I.T     (Eng) 6-3  163.3  27.2  62  3
322 1992 SAF-Ind Shastri R.J    (Ind) 4-3  124.0  31.0  59  2
107 1956 NZL-Win Sobers G.St.A  (Win) 4-4  138.9  34.7  81  2

Sobers and Botham are arguably the top two allrounders ever. However they had nightmare series. The above players scored less than 30 runs per Test and captured fewer than one wicket per Test. Their average Run index was less than 35, in eminently forgettable series for all. However, let us not forget that Sobers and Botham are the top two allrounders in the performance table.

The minimum number of wicket-keeper dismissals has been set at a slightly higher level than the wickets (12/14/16/18). The wicket-keeping allrounder table is ordered on the Run index, which is determined by assigning a value of 20 runs per dismissal. This has been done with some basis. 26 is the highest number of dismissals in this group and 600 runs. Hence the number 20 has been chosen. In case you think that this is arbitrarily done, it is true. However do not forget that it is the same for all wicket-keepers and we are not comparing outside the wicket-keeper domain.

Ser Year Hme-Awy Player          For  #-P RunIdx  Avge   R  D  Wt-R  

463 2002 SAF-Aus Gilchrist A.C  (Aus) 3-3  829.7 276.6 473 14 549.7
418 1999 ZIM-Slk Flower A       (Zim) 3-3  679.5 226.5 388 13 419.5
154 1966 SAF-Aus Lindsay D.T    (Saf) 5-5 1083.9 216.8 606 24 603.9
377 1997 NZL-Eng Stewart A.J    (Eng) 3-3  605.9 202.0 257 16 285.9
350 1994 SAF-Nzl Richardson D.J (Saf) 3-3  571.8 190.6 247 16 251.8
399 1998 ENG-Saf Stewart A.J    (Eng) 5-5  943.7 188.7 465 23 483.7
591 2009 NZL-Pak Kamran Akmal   (Pak) 3-3  561.3 187.1 257 13 301.3
447 2001 ENG-Aus Gilchrist A.C  (Aus) 5-5  924.1 184.8 340 26 404.1
416 1999 AUS-Pak Gilchrist A.C  (Aus) 3-3  537.4 179.1 264 13 277.4
499 2004 SLK-Aus Gilchrist A.C  (Aus) 3-3  527.7 175.9 201 14 247.7
126 1960 AUS-Win Alexander F.C.M(Win) 5-5  877.4 175.5 484 16 557.4
443 2001 WIN-Saf Jacobs R.D     (Win) 4-4  698.4 174.6 299 17 358.4
178 1972 AUS-Pak Marsh R.W      (Aus) 3-3  517.3 172.4 210 16 197.3
515 2004 AUS-Pak Gilchrist A.C  (Aus) 3-3  505.6 168.5 230 14 225.6
475 2002 AUS-Eng Gilchrist A.C  (Aus) 5-5  830.3 166.1 333 25 330.3
565 2008 NZL-Eng McCullum B.B   (Nzl) 3-3  495.1 165.0 212 14 215.1
593 2009 SAF-Eng Boucher M.V    (Saf) 4-4  655.1 163.8 341 16 335.1
439 2001 SLK-Eng Sangakkara K.C (Slk) 3-3  484.9 161.6 215 13 224.9
592 2009 AUS-Win Haddin B.J     (Aus) 3-3  479.1 159.7 225 14 199.1
259 1984 AUS-Win Dujon P.J.L    (Win) 5-5  781.9 156.4 341 19 401.9
615 2011 ENG-Ind Prior M.J      (Eng) 4-4  610.9 152.7 271 17 270.9
404 1998 SAF-Win Jacobs R.D     (Win) 5-5  763.0 152.6 317 19 383.0
190 1974 AUS-Eng Knott A.P.E    (Eng) 6-6  908.0 151.3 364 23 448.0
289 1988 ENG-Win Dujon P.J.L    (Win) 5-5  749.2 149.8 305 20 349.2
587 2009 ENG-Aus Haddin B.J     (Aus) 5-4  598.9 149.7 278 15 298.9
481 2003 WIN-Aus Gilchrist A.C  (Aus) 4-4  583.2 145.8 282 15 283.2

Look at Gilchrist's 2002 series against South Africa. In 3 Tests, Gilchrist scored 473 runs (this is a performance Bradman would have been proud of) being weighted into 549 runs, away against top quality bowling. He dismissed 14 batsmen, this working out to 280 runs. The total is 829 equivalent runs, averaging 276 runs per Test. One would be at a loss of words to describe this performance.

Andy Flower was equally impressive against Sri Lanka. Playing for a weaker team, he scored just a few runs fewer and almost the same number of dismissals. An average Run index of 226 is ample proof of Andy Flower's contribution in a decent series for Zimbabwe.

Dennis Lindsay's performance in the South African series against Australia has been discussed quite a lot during the Series Batting analysis discussions. 606 runs and 24 dismissals must rank amongst the most impressive all-round performances ever, bowling or wicket-keeping type.

No Indian wicket-keeper has met the criteria set indicating the lack of wicket-keeper-batsmen amongst the Indian players.

Now for the wicket-keepers who have cleared the bar a number of times.

Gilchrist:    7
Stewart:      2
Dujon:        2
Jacobs:       2
Haddin:       2
              1 (10 keepers have reached this once each).

The above table tells a story, loud and clear. Gilchrist has achieved the selected landmarks in seven series. Four other keepers, twice. For those who compare Dhoni and Gilchrist, I would like to point out that Dhoni has not reached the set target even once. At least Prior, Akmal, McCullum, Boucher, Haddin, Sangakkara amongst modern keepers have got at least one successful jump over the bar.

I would conclude saying that, as wicket-keeper allrounders go, Gilchrist is as far ahead of the rest of the field as Bradman was, of the next batsmen.

The Readers' list

This is not a merit list since I have not come out with my list. This is just a list of all-rounders who missed the cut. Please check the downloaded file before sending an entry. Also please send the complete series figures for me to consider inclusion.

1. Warne's 249 runs and 40 wickets during 2005 vs England, away (Boll/Raghav).
2. Davidson's 212 runs and 33 wickets during 1960 vs West Indies (Waspsting).
3. Marshall's 244 runs and 33 wickets during 1983 vs India, away (Ravi).
4. Botham's 187 runs and 19 wkts in 3 tests during 1979 vs Aus away (Gerry).
5. Kapil's 278 runs and 32 wkts vs Pak during 1979 (Ganesh).
6. Noble's 417 runs and 16 wkts vs Eng during 1903 (Boll).
7. Healy's 356 runs and 15 dismissals vs Win in 1996-97 (Boll).
8. Marsh's 297 runs and 17 dismissals vs Win in 1972-73, away (Boll).
9. Procter's 209 runs and 28 wickets, in 4 Tests, vs Aus during 1970 (Blakeley).

(Revised on 22/05/11)

This article is a logical conclusion to the previous three articles. In these articles I looked at two teams which dominated the periods 1976-1995 and 1989-2008. I also looked at the batsmen who faced up these two outstanding sets of bowlers effectively. There was a discussion amongst the readers on the batsmen who faced up to strong bowling attacks, across years, effectively. It was also agreed that a composite single number indicating the weighted average bowling quality faced by a batsman across the career hides many truths.

Then Arjun Hemnani came out with a suggestion that I classify all bowling attacks into four groups and develop batting tables based on these groups. It seemed to be an excellent idea and I have created this article based on this idea. This is a quasi-rating work based on the most important of parameters, viz., the Bowling quality. I may do a similar exercise based on the Pitch conditions. Again some really tough work but at the end worthwhile.

I have summarized all relevant facts related to this analysis. First let me emphasize that this is not a Test innings Ratings analysis. There are many other relevant factors which would have to be considered in such an analysis. I have not done so in this analysis which is centred on Bowler quality. I would appreciate if the readers do not keep on repeating again and again that other relevant factors such as Pitch type, Innings status at entry, Result, Series status, Bowler recent form, Innings target et al, have not been included. That would be counter-productive.

1. As I have done in the Team strength calculations, I have considered only Tests played after 1900. It is impossible to fit in the Tests before 1900 because of uncovered pitches and many sub-20 averages. However we lose only 64 Tests.

2. The Bowling quality index (BQI) is based on Career-to-date values. This is the most dependable and accurate of the bowling measures. There is no situation where the Career-to-date figure is not the appropriate one. A bowler like Lee with a great start and tapering off towards the end or Muralitharan who had a poor start and wonderful finish will be taken care of equally well.

3. The BQI is based on the actual bowlers who bowled in the particular innings. This is very important. There is a Sri Lankan innings in which Wasim Akram and Waqar Younis bowled 14 overs each. That is all. This would have been a terrifying situation for the batsmen. Contrast this with an innings in which Akram and Younis bowled 50% of the overs.

4. The BQI is determined using the modified reciprocal method suggested by Arjun Hemnani which irons out the imbalance created by weak fifth bowlers. The career strike rate and career rpo are computed separately to arrive at the final BQI.

5. The BQI is determined for each innings. However in order to reduce wild variations, I will apply the BQI of the first innings to the second innings also in case the number of balls bowled in the second innings is less than 60. This is commonsense. This is explained through an example. Readers should know that this would not have much of an impact since no batsman is likely to score even 25 within the 10 overs.

Test # 1962: Win 231, Saf 346 (Win BQI 41.68), Win 161, Saf 49/3 in 8.4 overs (Win BQI 50.67).
In the above Test, the Saf second innings will be evaluated at 41.68 since fewer than 10 overs were bowled.

6. The BQI is reduced by 5% for Home games and increased by 5% for away games. Reader should remember that the lower the BQI, the more potent the attack is. There have been suggestions on increasing this quantum and on making this dependent on the specific country. I feel 5% either way is ample and the later requires some tricky work since I am not sure how to make it work. So that is for a later day. In general this concept is fine and works well in most cases.

It is possible that the visiting team has the right bowlers and can exploit the "away" bowling conditions. However there is no denying that, in most cases, the home bowlers would have the advantage of familiarity with and knowledge of local conditions.

The following italicised points are to be ignored in the current version.

7. The BQI is based on the Bowling average. However in order to recognize the importance of Strike rates in Test cricket is a special adjustment based on Strike rate. These concepts are explained in the examples.

8. The BQI is further modified by the Period related factor. The concerned table is given below. If the period average is lower than the all-time average of 31.76, it is a bowler-friendly age and the bowler/team averages are adjusted upwards. On the other hand, if the period average is higher than the all-time average of 31.76, it is a batsmen-friendly age and the bowler/team averages are adjusted downwards. I have adjusted the factor at a bowler level than spin/pace level since the later would have required a completely different way of working, at a player level. Even checking of results would have become very cumbersome and difficult. I also do not think that there is that much of a change.

Bowling average adjustment:  AMF - Average multiplying factor
Period       BowAvg     AMF
1877-1899     22.20    1.431
1900-1914     25.69    1.236
WW1-WW2       32.56    0.976
40s-50s       29.96    1.060
1960s         32.11    0.989
1970s         31.94    0.995
1980s         32.07    0.990
1990s         31.51    1.008
2000-2004     33.56    0.946
2005-2011     34.94    0.909
All Tests     31.76    1.000

Finally the bowling attacks are classified into 5 groups, as described below. The fifth group was necessary to separate the REALLY weak bowling attacks.

With the idea of short innings being tagged with the first innings, there have been 6837 qualifying innings until the West Indies - Pakistan Test which finished recently. The first cut-off has been fixed at 30 to have around 20% of the total innings into the top group. There may be a subjective element in this part of the exercise but that cannot be avoided. The basis on which we have decided that 30 will be the first cut-off point is not subjective. In fact Arjun's assertion that 20% means in a loose manner that at any time there are 2 really good bowling attacks makes eminent sense. The other cut-offs follow logically. The group cut-off details are given below.

Group  B Q I        # of Inns   % (out of 6837)

  5    19.03-29.99:   1353     19.8% Very good bowling attack. (Prev: 19.2%)
  4    30.00-34.99:   1703     24.9% Good bowling attack.      (Prev: 23.9%)
  3    35.00-39.99:   1753     25.6% Average bowling attack.   (Prev: 21.3%)
  2    40.00-44.99:   1095     16.0% Passable bowling attack.  (Prev: 23.4%) 
  1    45.00+:         933     13.6% Very poor bowling attack. (Prev: 12.2%) 

Note: In group 5 only three innings were below 20.00.
Test 327: Australia (18.94).
    Lindwall (19.19), Johnston (18.24) and Miller (22.00) bowled 19 overs. 
Test 347: England   (19.31). 
    Lindwall (21.08), Johnston (19.25) and Miller (21.49) bowled 39 overs.
Test 104: England   (19.66). 
    Barnes (20.14) and Blythe (19.20) bowled 47 of the 54 overs.

A note on the revised groupings. The S/R adjustments and the Period adjustments have been removed. The less-than-50-ctd-wickets situation has been ironed out. Established bowlers are assigned a better strike rate/rpos in line with their career averages. Only bowlers who did not even get 50 wickets in their careers are treated a bit roughly. All this has has resulted in some softening of the Bowling group allocations. The first two groups together have 2% of additional innings associated with them. However 4% more innings have come into the third group. This means that a total of over 70% of the innings now find place in the acceptable groups and below 30% in the two weaker groups. This contrasts with the 64-36% in the previous version. This has resulted in a better distribution of batsman performances.

In fact Arjun questioned the necessity to have the last group. He felt that the last two could be combined into one. However I strongly feel it is essential for the reason cited below. Let us look at the following two bowling attacks.

Test 1833, Bangladesh, Mortaza/Rafique/Shakib/Rasel/Sharif, BQI value is 41.45.
Test 226, Nzl (Hammond's 336), 4 "bowlers" had a ctd total of 26 wkts and a career total of 36 wkts, BQI value is 53.21.

There is no way I am going to put these into the same group. One is a good Test level attack and the other is barely at the level of a First Class side. So the last group is necessary.

The average BQI for this huge sample is 36.56 (37.13) and the median is at 35.93 (37.13). This indicates a fairly balanced distribution of values. The Standard Deviation is 7.30 (7.67). I have explained the whole concept of determining the BQI with the following examples.

First is MatchId 1267 between Sri Lanka and Pakistan, played at Kandy during 1994. In the first innings Wasim Akram (ctd 22.9) bowled 14.2 overs and Waqar Younis (ctd 19.3) bowled 14 overs and dismissed Sri Lanka for 71. The weighted BQI starts life at 20.81. This is multiplied by 1.05 (this being away Test for Pakistan). The final BQI value is 21.85 which puts this attack as a very potent one. Any runs scored in this particular innings, say A de Silva's 7 will get into the highest classification.

The second is MatchId 1844 between Pakistan and South Africa, played during 2007. These were Steyn's early years. As everyone knows he had a fairly average start to his career. Steyn bowled 12 overs, Ntini 8 overs, Kallis 7 overs, Harris 20 overs and Nel 16 overs. The base BQI is 30.77. The separation of strike rate and rpo in the reciprocal BQI calculation has benefited this attack because of Steyn's strike rate. This is multiplied by 1.05 (this being away Test for South Africa). The final BQI value is 32.31 which puts this attack as a fair one. Any runs scored in this particular innings, say Mohammed Yousuf's 25 will get into the second classification.

I have got into details here so as to give the readers a clear idea of the calculations.

There is so much data available that even the organization of the article is getting into trouble. I can only present in the article a certain amount of data. The serious reader should download the complete files and read the same. I have given below what I would be presenting within the article.

1. Top 20 batsmen for group 5, the top one. Ordered by batting average.
2. Top 20 batsmen for group 4, the second best one. Ordered by batting average.
3. Top 10 batsmen for groups 3-2-1. Ordered by batting average.
4. Top 10 batsmen for groups 5-1, the top one. Ordered by runs scored.
5. For selected batsman, their group-wise distribution of runs scored.

For all the above, complete files are available for downloading/viewing.

Let us look at the tables. First the Group tables based on Batting average. The batsman should have scored a minimum of 500 runs to be included. Otherwise we will have funny numbers.

Batsman              Cty Inns N Runs Grp  Avge

Hunte C.C            Win   6  1  586  5 117.20
Bradman D.G          Aus  15  0 1159  5  77.27 
Sobers G.St.A        Win  22  2 1328  5  66.40 
Hutton L             Eng  21  5  949  5  59.31 
Wessels K.C          Saf  14  1  763  5  58.69 
Graveney T.W         Eng  18  2  922  5  57.62 
Hobbs J.B            Eng  16  1  837  5  55.80 
Lawry W.M            Aus  14  3  613  5  55.73
Shoaib Mohammad      Pak  11  1  539  5  53.90 
Richards I.V.A       Win  44  0 2338  5  53.14 
Sangakkara K.C       Slk  23  2 1045  5  49.76 
Ponting R.T          Aus  39  2 1794  5  48.49 
Edrich J.H           Eng  21  1  968  5  48.40 
Martyn D.R           Aus  24  2 1061  5  48.23 
Lloyd C.H            Win  39  2 1748  5  47.24 
O'Neill N.C          Aus  15  3  560  5  46.67 
Cook A.N             Eng  24  2 1017  5  46.23 
Gomes H.A            Win  21  3  830  5  46.11 
Sehwag V             Ind  33  2 1428  5  46.06 
Amarnath M           Ind  18  0  829  5  46.06 

Hunte, by virtue of his huge unbeaten double century, has moved to the top with 117.20, but only 586 runs. Bradman's is the more significant performance since he has a 77+ average with over 1100 runs. Sobers, again buoyed by the 365*, has 1300+ runs at 66. Wessels is a surprise entrant as also Graveney. There is a complete churning of players with the result that Lara and Tendulkar have moved out of the top-20. The recent bowling attacks have lost their edge because of the removal of both s/r and period adjustments. Only Sangakkara, Ponting and Sehwag remain.

Bradman D.G          Aus  15  2 1275  4  98.08
Walcott C.L          Win  15  1 1067  4  76.21
Chappell G.S         Aus  49 10 2723  4  69.82
Sutcliffe H          Eng   9  0  617  4  68.56 
McCabe S.J           Aus  16  1  986  4  65.73 
Richards I.V.A       Win  54  9 2917  4  64.82 
Wasim Raja           Pak  23  7 1019  4  63.69 
Younis Khan          Pak  40  3 2352  4  63.57 
Mohsin Khan          Pak  13  1  761  4  63.42 
Hobbs J.B            Eng  15  2  758  4  58.31 
Tendulkar S.R        Ind  85 10 4345  4  57.93 
Crowe M.D            Nzl  34  5 1671  4  57.62 
Smith G.C            Saf  53  4 2754  4  56.20 
Walters K.D          Aus  46  6 2243  4  56.08 
Border A.R           Aus  86 15 3935  4  55.42 
Taylor R.L           Nzl  13  1  659  4  54.92 
Richardson M.H       Nzl  18  0  977  4  54.28 
Javed Miandad        Pak  44  4 2164  4  54.10 
Kallicharran A.I     Win  26  4 1176  4  53.45 
Gilchrist A.C        Aus  38  6 1701  4  53.16 

Here we see 20 batsmen exceeding average of 50. Bradman has a near-career average of 98+ with a decent amount of runs. Walcott and Chappell come in next with 70+ and 70- averages. Sutcliffe and, nice to say McCabe, are next. Probably the most significant is Richards who has scored over 2900 runs at nearly 65. Quite a few modern batsmen have plenty of runs at 55+ averages. Mark Richardson is a surprise at the top, way above his career average of 44.77. He has done well against Pakistan and India.

Bradman D.G          Aus  17  3 1479  3 105.64
Sutcliffe H          Eng  22  5 1498  3  88.12 
Zaheer Abbas         Pak  19  2 1495  3  87.94 
EdeC Weekes          Win  15  1 1071  3  76.50 
Amiss D.L            Eng  25  2 1744  3  75.83 
Flower A             Zim  33  7 1940  3  74.62 
Lara B.C             Win  52  2 3674  3  73.48 
Compton D.C.S        Eng  14  3  808  3  73.45 
Barrington K.F       Eng  34  4 2131  3  71.03 
Walcott C.L          Win  14  1  912  3  70.15 

Kallis J.H           Saf  30  8 2333  2 106.05
Mohammad Yousuf      Pak  16  1 1506  2 100.40
Headley G.A          Win  12  3  890  2  98.89
Pietersen K.P        Eng  11  2  851  2  94.56
Worrell F.M.M        Win  14  2 1133  2  94.42
Woodfull W.M         Aus   6  0  545  2  90.83
Prince A.G           Saf  10  4  515  2  85.83
Shastri R.J          Ind  15  4  932  2  84.73
Kirsten G            Saf  16  3 1067  2  82.08
Vengsarkar D.B       Ind  23  6 1389  2  81.71

Adams J.C            Win   8  4  658  1 164.50
Bell I.R             Eng   6  1  531  1 106.20
Mohammad Yousuf      Pak  11  4  703  1 100.43
Dravid R             Ind  14  4  987  1  98.70
Sehwag V             Ind   9  2  672  1  96.00
Waugh S.R            Aus  20  6 1268  1  90.57
Bradman D.G          Aus  17  2 1342  1  89.47
de Villiers A.B      Saf  12  4  713  1  89.12
Kallis J.H           Saf  21  7 1228  1  87.71
Prince A.G           Saf  12  5  614  1  87.71

Quite a few 100+ averages at the lower bowling quality levels. Kallis has a 100+ average against group 4, as so does Yousuf. Do not forget that group 3 is still a fair bowling attack.

Batsman              Cty Inns N Runs Grp  Avge

Stewart A.J          Eng  97  8 3311  5  37.20
Lara B.C             Win  76  1 3270  5  43.60
Atherton M.A         Eng  98  1 2581  5  26.61
Gooch G.A            Eng  73  1 2573  5  35.74
Tendulkar S.R        Ind  63  2 2396  5  39.28
Richards I.V.A       Win  44  0 2338  5  53.14
Dravid R             Ind  65  3 2288  5  36.90
Border A.R           Aus  70 10 2191  5  36.52
Chanderpaul S        Win  67  9 2135  5  36.81
Hussain N            Eng  66  6 2048  5  34.13

Tendulkar S.R        Ind  85 10 4345  4  57.93
Border A.R           Aus  86 15 3935  4  55.42
Dravid R             Ind  75 10 3410  4  52.46
Kallis J.H           Saf  85 10 3302  4  44.03
Waugh S.R            Aus  76 10 3291  4  49.86
Lara B.C             Win  70  1 3286  4  47.62
Richards I.V.A       Win  54  9 2917  4  64.82
Atherton M.A         Eng  66  2 2875  4  44.92
Inzamam-ul-Haq       Pak  59  5 2791  4  51.69
Smith G.C            Saf  53  4 2754  4  56.20

Ponting R.T          Aus  97 13 5146  3  61.26
Kallis J.H           Saf  79  9 3941  3  56.30
Lara B.C             Win  52  2 3674  3  73.48
Jayawardene D.P.M.D  Slk  55  1 3579  3  66.28
Tendulkar S.R        Ind  69  7 3505  3  56.53
Hayden M.L           Aus  67  5 3474  3  56.03
Dravid R             Ind  64  6 3307  3  57.02
Gower D.I            Eng  61  4 3063  3  53.74
Border A.R           Aus  62 11 2993  3  58.69
Gavaskar S.M         Ind  60  5 2940  3  53.45

Tendulkar S.R        Ind  49  7 2982  2  71.00
Kallis J.H           Saf  30  8 2333  2 106.05
Javed Miandad        Pak  39  4 2242  2  64.06
Ponting R.T          Aus  46  9 2181  2  58.95
Dravid R             Ind  41  6 2071  2  59.17
Edrich J.H           Eng  43  5 1894  2  49.84
Hammond W.R          Eng  35  5 1890  2  63.00
Barrington K.F       Eng  32  6 1860  2  71.54
Sangakkara K.C       Slk  31  2 1820  2  62.76
Jayawardene D.P.M.D  Slk  37  5 1813  2  56.66

Hammond W.R          Eng  66  8 4133  1  71.26
Hutton L             Eng  68  7 3599  1  59.00
Compton D.C.S        Eng  47  5 2456  1  58.48
Harvey R.N           Aus  35  2 2180  1  66.06
Sutcliffe H          Eng  35  4 1897  1  61.19
Gavaskar S.M         Ind  30  2 1882  1  67.21
Cowdrey M.C          Eng  39  4 1761  1  50.31
Graveney T.W         Eng  32  4 1704  1  60.86
Javed Miandad        Pak  30  6 1660  1  69.17
Barrington K.F       Eng  29  3 1624  1  62.46

The above tables are ordered on runs scored against the bowling groups. Stewart and Tendulkar lead the top two groups with 3311 and 4345 runs. Lara also has over 3000 runs against each of the top groups. Almost the same with Tendulkar indicating that, on balance, they faced better quality of bowling. The modern batsmen, led by Tendulkar top the middle group table. Tendulkar and quite a few current batsmen top the weaker group 2. Finally look at Hammond. Nearly 60% of his runs have come against the weakest of attacks, albeit, at no great an average. It must be accepted that when batsmen play 100+ tests, they are likely to figure in both groups 5 and 1 prominently. Hammond, Hutton and Compton are the surprises since they had career runs of 7000 and just above or below.

Now for the group-wise runs and % of career runs for selected 20 odd batsmen. The complete file is available for downloading.

Batsman              Cty Inns N  Runs    %  Grp  Avge

Hobbs J.B            Eng  16  1   837  15.5  5  55.80
Hobbs J.B            Eng  15  2   758  14.0  4  58.31
Hobbs J.B            Eng  29  2  1642  30.4  3  60.81
Hobbs J.B            Eng  20  1   854  15.8  2  44.95
Hobbs J.B            Eng  22  1  1319  24.4  1  62.81

Sutcliffe H          Eng   6  0   110   2.4  5  18.33
Sutcliffe H          Eng   9  0   617  13.5  4  68.56
Sutcliffe H          Eng  22  5  1498  32.9  3  88.12
Sutcliffe H          Eng  12  0   433   9.5  2  36.08
Sutcliffe H          Eng  35  4  1897  41.6  1  61.19

Hammond W.R          Eng   4  0   124   1.7  5  31.00
Hammond W.R          Eng  11  1   397   5.5  4  39.70
Hammond W.R          Eng  24  2   705   9.7  3  32.05
Hammond W.R          Eng  35  5  1890  26.1  2  63.00
Hammond W.R          Eng  66  8  4133  57.0  1  71.26

Bradman D.G          Aus  15  0  1159  16.6  5  77.27
Bradman D.G          Aus  15  2  1275  18.2  4  98.08
Bradman D.G          Aus  17  3  1479  21.1  3 105.64
Bradman D.G          Aus  16  3  1741  24.9  2 133.92
Bradman D.G          Aus  17  2  1342  19.2  1  89.47

Hutton L             Eng  21  5   949  13.6  5  59.31
Hutton L             Eng  21  0   884  12.7  4  42.10
Hutton L             Eng  12  1   530   7.6  3  48.18
Hutton L             Eng  16  2  1009  14.5  2  72.07
Hutton L             Eng  68  7  3599  51.6  1  59.00

Sobers G.St.A        Win  22  2  1328  16.5  5  66.40
Sobers G.St.A        Win  47  4  2169  27.0  4  50.44
Sobers G.St.A        Win  43  6  2060  25.6  3  55.68
Sobers G.St.A        Win  26  4  1626  20.2  2  73.91
Sobers G.St.A        Win  22  5   849  10.6  1  49.94

Lloyd C.H            Win  39  2  1748  23.3  5  47.24
Lloyd C.H            Win  40  3  1688  22.5  4  45.62
Lloyd C.H            Win  54  5  2068  27.5  3  42.20
Lloyd C.H            Win  35  4  1712  22.8  2  55.23
Lloyd C.H            Win   7  0   299   4.0  1  42.71

Chappell G.S         Aus  42  2  1490  21.0  5  37.25
Chappell G.S         Aus  49 10  2723  38.3  4  69.82
Chappell G.S         Aus  30  3  1465  20.6  3  54.26
Chappell G.S         Aus  20  2   918  12.9  2  51.00
Chappell G.S         Aus  10  2   514   7.2  1  64.25

Gavaskar S.M         Ind  47  2  1604  15.8  5  35.64
Gavaskar S.M         Ind  42  1  2122  21.0  4  51.76
Gavaskar S.M         Ind  60  5  2940  29.0  3  53.45
Gavaskar S.M         Ind  35  6  1574  15.6  2  54.28
Gavaskar S.M         Ind  30  2  1882  18.6  1  67.21

Richards I.V.A       Win  44  0  2338  27.4  5  53.14
Richards I.V.A       Win  54  9  2917  34.2  4  64.82
Richards I.V.A       Win  48  1  1795  21.0  3  38.19
Richards I.V.A       Win  32  2  1439  16.9  2  47.97
Richards I.V.A       Win   4  0    51   0.6  1  12.75

Gooch G.A            Eng  73  1  2573  28.9  5  35.74
Gooch G.A            Eng  53  2  2409  27.1  4  47.24
Gooch G.A            Eng  52  1  2010  22.6  3  39.41
Gooch G.A            Eng  26  2  1269  14.3  2  52.88
Gooch G.A            Eng  11  0   639   7.2  1  58.09

Javed Miandad        Pak  39  0  1434  16.2  5  36.77
Javed Miandad        Pak  44  4  2164  24.5  4  54.10
Javed Miandad        Pak  37  7  1332  15.1  3  44.40
Javed Miandad        Pak  39  4  2242  25.4  2  64.06
Javed Miandad        Pak  30  6  1660  18.8  1  69.17

Border A.R           Aus  70 10  2191  19.6  5  36.52
Border A.R           Aus  86 15  3935  35.2  4  55.42
Border A.R           Aus  62 11  2993  26.8  3  58.69
Border A.R           Aus  30  6  1038   9.3  2  43.25
Border A.R           Aus  17  2  1017   9.1  1  67.80

Waugh S.R            Aus  43  5  1643  15.0  5  43.24
Waugh S.R            Aus  76 10  3291  30.1  4  49.86
Waugh S.R            Aus  82 17  2920  26.7  3  44.92
Waugh S.R            Aus  39  8  1805  16.5  2  58.23
Waugh S.R            Aus  20  6  1268  11.6  1  90.57

Atherton M.A         Eng  98  1  2581  33.4  5  26.61
Atherton M.A         Eng  66  2  2875  37.2  4  44.92
Atherton M.A         Eng  34  2  1534  19.8  3  47.94
Atherton M.A         Eng   9  1   371   4.8  2  46.38
Atherton M.A         Eng   5  1   367   4.7  1  91.75

Tendulkar S.R        Ind  63  2  2396  16.3  5  39.28
Tendulkar S.R        Ind  85 10  4345  29.6  4  57.93
Tendulkar S.R        Ind  69  7  3505  23.9  3  56.53
Tendulkar S.R        Ind  49  7  2982  20.3  2  71.00
Tendulkar S.R        Ind  24  6  1464  10.0  1  81.33

Stewart A.J          Eng  97  8  3311  39.1  5  37.20
Stewart A.J          Eng  69  6  2240  26.5  4  35.56
Stewart A.J          Eng  35  3  1628  19.2  3  50.88
Stewart A.J          Eng  25  3   845  10.0  2  38.41
Stewart A.J          Eng   9  1   441   5.2  1  55.12

Lara B.C             Win  76  1  3270  27.4  5  43.60
Lara B.C             Win  70  1  3286  27.5  4  47.62
Lara B.C             Win  52  2  3674  30.7  3  73.48
Lara B.C             Win  22  2   979   8.2  2  48.95
Lara B.C             Win  12  0   744   6.2  1  62.00

Inzamam-ul-Haq       Pak  40  1  1347  15.3  5  34.54
Inzamam-ul-Haq       Pak  59  5  2791  31.6  4  51.69
Inzamam-ul-Haq       Pak  52  7  2409  27.3  3  53.53
Inzamam-ul-Haq       Pak  30  5  1474  16.7  2  58.96
Inzamam-ul-Haq       Pak  19  4   809   9.2  1  53.93

Fleming S.P          Nzl  50  2  1459  20.3  5  30.40
Fleming S.P          Nzl  47  5  2093  29.2  4  49.83
Fleming S.P          Nzl  55  2  1906  26.6  3  35.96
Fleming S.P          Nzl  25  1  1147  16.0  2  47.79
Fleming S.P          Nzl  12  0   567   7.9  1  47.25

Ponting R.T          Aus  39  2  1794  14.5  5  48.49
Ponting R.T          Aus  65  3  2751  22.3  4  44.37
Ponting R.T          Aus  97 13  5146  41.6  3  61.26
Ponting R.T          Aus  46  9  2181  17.6  2  58.95
Ponting R.T          Aus  12  1   487   3.9  1  44.27

Kallis J.H           Saf  31  4  1143   9.6  5  42.33
Kallis J.H           Saf  85 10  3302  27.6  4  44.03
Kallis J.H           Saf  79  9  3941  33.0  3  56.30
Kallis J.H           Saf  30  8  2333  19.5  2 106.05
Kallis J.H           Saf  21  7  1228  10.3  1  87.71

Dravid R             Ind  65  3  2288  19.0  5  36.90
Dravid R             Ind  75 10  3410  28.3  4  52.46
Dravid R             Ind  64  6  3307  27.4  3  57.02
Dravid R             Ind  41  6  2071  17.2  2  59.17
Dravid R             Ind  14  4   987   8.2  1  98.70

Laxman V.V.S         Ind  52  4  1876  23.7  5  39.08
Laxman V.V.S         Ind  61  7  2480  31.4  4  45.93
Laxman V.V.S         Ind  46 12  1709  21.6  3  50.26
Laxman V.V.S         Ind  29  8  1591  20.1  2  75.76
Laxman V.V.S         Ind  10  0   247   3.1  1  24.70

Jayawardene D.P.M.D  Slk  29  1  1124  11.8  5  40.14
Jayawardene D.P.M.D  Slk  44  4  1639  17.2  4  40.97
Jayawardene D.P.M.D  Slk  55  1  3579  37.6  3  66.28
Jayawardene D.P.M.D  Slk  37  5  1813  19.0  2  56.66
Jayawardene D.P.M.D  Slk  25  2  1375  14.4  1  59.78

Sehwag V             Ind  33  2  1428  18.6  5  46.06
Sehwag V             Ind  46  0  2239  29.1  4  48.67
Sehwag V             Ind  33  0  1760  22.9  3  53.33
Sehwag V             Ind  29  2  1595  20.7  2  59.07
Sehwag V             Ind   9  2   672   8.7  1  96.00

Sangakkara K.C       Slk  23  2  1045  12.7  5  49.76
Sangakkara K.C       Slk  36  4  1655  20.1  4  51.72
Sangakkara K.C       Slk  43  0  2178  26.4  3  50.65
Sangakkara K.C       Slk  31  2  1820  22.1  2  62.76
Sangakkara K.C       Slk  23  4  1546  18.8  1  81.37

Hobbs, Sutcliffe and Hammond have made very few runs against top group, mainly indicating that there were very few top group bowling attacks during these 50 years. Lloyd, Chappell, Laxman and Fleming all have around 20-25% against the top bowling group. However the real numbers are for Stewart with 39%, Atherton with 33.4%, Richards with 27.4%, Gooch with 28.9% and Lara with 27.4%.

Looking at the other end of the tables, Hammond has scored 57% of career runs against the weakest of attacks. Hutton stands at 51% and Sutcliffe at 41%. Ponting, Laxman, Lloyd and Stewart have only 3-5% against these weak attacks. But the amazing number is for Richards, who in his cricketing life has almost faced no group 5 bowling attack (0.6%). That says something about the sign of the period 1970s-90s.

Group table - by Batting average: please click/right-click here.
Group table - by Runs scored: please click/right-click here.
Batsman table - by Group (for all 2000+ batsmen): please click/right-click here.
Batsman table - all Group 5 performances (for all 5000+ batsmen): please click/right-click here.
BQI table - ordered by BQI (for all 6827 innings): please click/right-click here.

Er-Sr calculations: please click/right-click here.
Weighted bowling quality table - ordered by WtBowQty value (gt 4000 runs): please click/right-click here.

I would like to inform the readers that we are away on holiday between June 2 and 25 and I will be taking the month of June off. I will be back in July. I am confident that most of the comments on this article, and I expect plenty, to be in before June 1.

The last two articles on the two wonderful golden periods of West Indian and Australian domination were received very well and elicited over 300 comments. This blog almost became a forum for discussion amongst the interested readers. It is obvious that the bowlers were the key players during these periods of domination, more for the West Indies teams than the Australian ones. A number of readers also commented and initiated discussions on the batsmen who did well against these bowlers. So I have decided to complete this informative series of articles by doing an analysis on the teams and batsmen who performed well against the West Indian and Australian bowlers.

The cut-off Tests are more or less similar. For the West Indians, I have tweaked the cut-offs to start with Test # 764 (1975) in which Holding made his debut. This ensures that at least two of the selected bowlers are there. Similarly I have since modified the the cut-off at the end to Test # 1371 (1997), the one just before the 3-0 whitewash in Pakistan. In other words I have excluded those last few Tests in which only Walsh played.

The Australian cut-off starts with Test # 1121 (1989), the first Ashes Test. The last match is Test # 1879, during 2008, against West Indies. I have excluded those last Tests in which Johnson was the leading bowler.

I have weighted the runs scored by the batsmen with two relevant measures. The first is the Test venue, home/away as far as the batting team is concerned.

However more important, I have weighted the runs scored by the weighted bowling quality. This is an important adjustment and the relevant points are explained below.

- This is based on career-to-date figures.
- I have also used reciprocal method suggested by Arjun Hemnani, so as to reduce the impact of the weaker fifth bowler.
- The adjustment factor is based all-tests bowling average during the respective cut-off years.
- This works to 29.96 for the West Indian bowlers and 30.74 for the Australian bowlers.

The weighting with bowler quality is essential since the West Indian and Australian attacks have had 4, 3, 2, 1 and even 0 bowler out of the top bowlers. The last instances occurred during the World Series Tests.

Given below are examples of how these calculations have been done. I have presented these examples since these are quite compilcated and readers might be interested in knowing the workings.

Against West Indies

Test Year Batsman       Loc H/A-Idx BowQty BQ-Idx  Runs  Adj-Runs

0862 1979 G.S.Chappell  Aus   0.95   25.47  1.18    74     82.9
0835 1978 S.M.Gavaskar  Ind   0.95   39.67  0.76   205    148.0

1142 1990 G.A.Gooch     Win   1.05   34.56  0.87    84     76.7
1171 1991 G.A.Gooch     Eng   0.95   24.78  1.21   154    177.0

BQ-Idx = 29.96/BowQty.

Against Australia

Test Year Batsman       Loc H/A-Idx BowQty BQ-Idx  Runs  Adj-Runs

1405 1998 S.R.Tendulkar Ind   0.95   33.32  0.92   155    136.1
1479 1999 S.R.Tendulkar Aus   1.05   27.67  1.11   116    135.2

1208 1993 B.C.Lara      Aus   1.05   37.79  0.82   277    238.5
1453 1999 B.C.Lara      Win   0.95   24.06  1.28   153    186.0

BQ-Idx = 30.74/BowQty.

Finally I have also done an analysis on the teams which did very well against the two concerned teams. The methodology is similar to the one used for individual batsmen. The runs scored are weighted by home/away factor and bowling quality.

To get a reasonable number of batsmen into the table I have set 800 runs as the cut-off value for batsmen against West Indies and 1000 runs for batsmen against Australia. Readers can ask for the figures of other batsmen.

First the batsmen who have done well against the 1975-2000 West Indies' bowlers.

Cty Batsman        Career  M I No   Runs-Avge   Runs -  Avge   % to
                     Avge         (Unadjusted)   (Adjusted)   CarAvg

Aus Chappell G.S    53.86 12 23 5 (1058-58.78) 1020.4 - 56.69 109.1%
Eng Gooch G.A       42.58 26 51 2 (2197-44.84) 2465.5 - 50.32 105.3%
Eng Smith R.A       43.67 19 35 5 (1333-44.43) 1469.1 - 48.97 101.7%
Ind Gavaskar S.M    51.12 21 36 3 (1867-56.58) 1594.3 - 48.31 110.7%
Aus Waugh M.E       41.82 19 32 2 (1317-43.90) 1407.8 - 46.93 105.0%
Aus Waugh S.R       51.06 20 33 4 (1208-41.66) 1303.5 - 44.95  81.6%
Eng Stewart A.J     39.56 13 24 2 ( 829-37.68)  935.6 - 42.53  95.3%
Aus Border A.R      50.56 31 59 7 (2052-39.46) 2205.4 - 42.41  78.0%
Aus Boon D.C        43.66 22 40 4 (1437-39.92) 1518.1 - 42.17  91.4%
Ind Vengsarkar D.B  42.13 24 40 4 (1596-44.33) 1470.4 - 40.84 105.2%
Eng Atherton M.A    37.70 16 30 0 (1077-35.90) 1194.1 - 39.80  95.2%
Eng Gower D.I       44.25 19 38 3 (1149-32.83) 1324.4 - 37.84  74.2%
Eng Lamb A.J        36.09 22 42 3 (1342-34.41) 1452.5 - 37.24  95.3%
Ind Amarnath M      42.50 17 30 2 (1076-38.43) 1028.2 - 36.72  90.4%
Aus Wood G.M        31.83 17 33 1 (1077-33.66) 1075.5 - 33.61 105.7%
Aus Taylor M.A      43.50 20 37 2 ( 984-28.11) 1065.8 - 30.45  64.6%
Ind Shastri R.J     35.79 18 33 5 ( 847-30.25)  847.5 - 30.27  84.5%
Pak Javed Miandad   52.57 16 28 0 ( 834-29.79)  832.8 - 29.74  56.7%
Ind Kapil Dev N     31.05 23 39 4 (1079-30.83) 1011.4 - 28.90  99.3%
Aus Healy I.A       27.40 24 40 5 ( 907-25.91)  997.2 - 28.49  94.6%
Ind Gaekwad A.D     30.08 19 32 1 ( 812-26.19)  709.4 - 22.88  87.1%

Greg Chappell leads the table comfortably from Gooch. His raw average is 58.78 and is slightly reduced with adjustments to 56.69. Interestingly, during this period, Greg Chappell never travelled to West Indies. Gooch has been truly outstanding against West Indies. He averages 44.43 but scored many of these runs against very tough and fearsome West Indian attacks (a la 154 (out of 252) at Headingley). These adjustments have boosted his average to 50.32. These two being the only two to exceed 50. R A Smith is in third place. Gavaskar's high average of 56 is reduced considerably because a number of these innings were against below-par West Indian attacks. His average is 48.31. Mark Waugh averages 46.93 and is slightly ahead of Steve.

The adjusted averages of the first four batsmen are higher than their career batting averages. Vengsarkar and Wood are the only other batsmen to have a better batting average against the powerful West Indian bowlers than their career batting averages.

Now for the Team analysis.

Australia      658  50 20605 33.89
India          420  36 12189 31.74
England        657  39 18782 30.39
New Zealand    178  15  4863 29.83
South Africa    14   0   410 29.29
Sri Lanka       39   4   935 26.71
Pakistan       273  17  6653 25.99

Australia have done the best against West Indies with an overall average, for the top 7 batsmen, of 33.89. India follows with 31.74. England is the only other team with an average exceeding 30.

Let us now see how the top batsmen fared against Australia between 1985 and 2008.

Cty Batsman        Career  M I No   Runs-Avge   Runs -  Avge   % to
                     Avge         (Unadjusted)   (Adjusted)   CarAvg

Ind Tendulkar S.R   56.95 25 47 5 (2352-56.00) 2379.2 - 56.65  98.3%
Ind Sehwag V        53.43 11 22 1 (1132-53.90) 1171.5 - 55.79 100.9%
Win Lara B.C        52.89 31 58 2 (2856-51.00) 3074.6 - 54.90  96.4%
Ind Laxman V.V.S    47.32 20 37 1 (1823-50.64) 1933.8 - 53.72 107.0%
Win Chanderpaul S   48.99 15 29 4 (1210-48.40) 1271.5 - 50.86  98.8%
Eng Thorpe G.P      44.66 16 31 4 (1235-45.74) 1275.1 - 47.22 102.4%
Ind Dravid R        52.45 23 43 5 (1740-45.79) 1779.2 - 46.82  87.3%
Win Richardson R.B  44.40 14 24 2 (1084-49.27)  977.6 - 44.44 111.0%
Saf Kallis J.H      57.44 18 35 4 (1188-38.32) 1334.1 - 43.04  66.7%
Eng Hussain N       37.19 23 45 4 (1581-38.56) 1749.3 - 42.67 103.7%
Eng Trescothick M.E 43.76 15 30 0 (1013-33.77) 1175.9 - 39.20  77.2%
Eng Butcher M.A     34.58 20 40 1 (1287-33.00) 1506.2 - 38.62  95.4%
Eng Gooch G.A       42.58 20 39 0 (1527-39.15) 1480.9 - 37.97  91.9%
Saf Kirsten G       45.27 18 34 1 (1134-34.36) 1228.6 - 37.23  75.9%
Eng Smith R.A       43.67 15 30 3 (1074-39.78) 1004.4 - 37.20  91.1%
Eng Stewart A.J     39.56 33 65 6 (1810-30.68) 2008.3 - 34.04  77.6%
Ind Ganguly S.C     42.18 20 36 2 (1079-31.74) 1099.5 - 32.34  75.2%
Eng Atherton M.A    37.70 33 66 2 (1900-29.69) 1975.2 - 30.86  78.8%

As expected, Indian batsmen dominate the table of performances against Australia. Tendulkar is on top with a base average of 56.00 and improves this slightly through the adjustments. Sehwag clocks in next with an average of over 55. Then comes Lara, who has scored the maximum runs of 2856 against Australians at 54.72. Laxman is in fourth position, again with an adjusted average over 53. Chanderpaul rounds off this table with an average exceeding 50. These five batsmen are the only ones to go past 50. The interesting thing is that the top four batsmen also average over 50 in the unadjusted measure. Richie Richardson averages 52 but loses out heavily on the adjustments.

Laxman has outperformed against Australia considerably. Note also how Izaz Ahmad has outperformed against Australia by 25%.

And the Team analysis, the average of the top 7 batsmen.

India          350  23 11791 36.06
Sri Lanka      221  14  7026 33.94
England        725  41 23134 33.82
West Indies    486  35 14986 33.23
South Africa   318  18  9677 32.26
Pakistan       280  10  8493 31.46
New Zealand    294  15  8748 31.35
Bangladesh      56   1  1569 28.53
Zimbabwe        42   0  1018 24.24

It would have been a surprise if India had not been on top in the team table since, during the 2000s, India have been the most successful team against Australia. They average a huge 36.06 per top-order wicket and are ahead of the next team, Sri Lanka, by nearly 10%. England, buoyed by their twin Ashes triumphs during this period, is next. West Indies also averages over 33. Note the number of teams which have averaged over 30.

To view/down-load the file containing the list of Test matches against West Indies which have been included in this analysis, and the details of players who have scored over 500 runs against West Indies, please click/right-click here.

To view/down-load the file containing the list of Test matches against Australians have been included in this analysis, and the details of players who have scored over 500 runs against West Indies, please click/right-click here.

This is a special request by Yogesh I have done an analysis of his hard classification. Really looking only at the peak years. The cut-offs are given below.

Australia:  1463(1975) to 1879(1990) (100 tests). 76 wins/13 draws - 82.5%
West Indies: 764(1999) to 1158(2008) (122 tests) 

No major change against West Indies. Wasim Raja is second and Gooch has slipped a bit.

England has gained a lot against Australia. They are the best side and Pietersen is the best batsman. Michael Vaughan is also right on top there.

To view/down-load the file containing the special tables, and the details of players who have scored over 750 runs against West Indies, please click/right-click here.

To view/down-load the file containing the special tables, and the details of players who have scored over 750 runs against Australia, please click/right-click here.

The response to the previous off-the-beaten-track article on West Indian pace bowlers was so good and the comments were so interesting that I decided to continue on a similar theme rather than move into the ODI domain. This time I have taken the Australian teams for analysis. I have read the readers' comments and have realized that I must include both batsmen and bowlers in the analysis. So this article is quite a different one to the previous one which was almost totally graphic. This one has only a single graph and many other tables.

What are the cut-off Tests? After a lot of deliberation, inspection and perusal of the readers' comments, I have decided that the golden period will start with Test no 1121, the first Ashes 1989 Test and end with Test no 1957, the second Test between New Zealand and Australia which was played during March 2010. There could be a variation of a few Tests at either end but most of the readers would agree that this really represented the golden period of Australian supremacy. Before the 1989 cut-off, Australia lost to West Indies and Pakistan. Since the 2010 cut-off, Australia have drawn the Pakistan series and lost against India and England and one can clearly see the fall.

I have selected the following 24 players who were the top Australian performers during these 22 years. Most of these players select themselves. There are 15 batsmen and 9 bowlers in this elite collection. Readers might want to add one or two to this list but I am sure none of these players will be taken out. I considered and discarded Alderman (only 70+ wickets after the cut-off), Border (since added), Reiffel (since added), Kasprowicz (quite average), Symonds (not enough batting impact), Watson (impact probably in future), Clark & Siddle (less than 100 wkts) et al.

Batsmen:

Border, Boon, Steve Waugh, Healy, Taylor, Mark Waugh, Martyn, 
Langer, Slater, Hayden, Ponting, Katich, Gilchrist, Clarke, Hussey. 

Bowlers:

McDermott, Hughes, Reiffel, Warne, McGrath, Gillespie, MacGill, B Lee, Johnson.

First, a graphic time-line of the careers of the 14 batsmen and 7 bowlers.

The timeline started with the continuation of the careers of Boon, Steve Waugh, Healy and Taylor. After a couple of years, Mark Waugh made his debut. Then came Martyn and Slater. Hayden and Ponting came in within the next couple of years. All the while the first four stalwarts continue to play. Boon retired, followed by Taylor and Healy who handed over his gloves to Gilchrist. No new batsmen came in for some time. Then Katich, Clarke and Mike Hussey took their deserved places.

McDermott started the timeline period and bowled on his own, with support from Alderman for some time. Then Warne made his, fairly ordinary, debut. Within a year McGrath made his debut, again nothing great. No one could have foreseen such wonderful careers, for both. Gillespie came after a few years. Afterwards MacGill started his interrupted, but great-in-numbers, career. Lee started with a bang, only to fade away in the second half of his career. Warne and McGrath retired on the same day, along with Langer. Johnson made his bow 4 years back and, despite some off-colour series, has performed very creditably.

Next the results summary of these 236 Tests.

Period      T   W   D   L    %

1989-2010 236 142  51  43  71.0%

1989-1994  59  27  22  10  64.4%
1995-1999  58  32  11  15  64.7%
2000-2004  59  44   7   8  80.5%
2005-2010  60  39  11  10  74.2%

Overall the Australian teams have achieved 71.0% success during these 22 years. Across three generations of players, this is outstanding and represents, arguably, the longest domination of the world scene. This has been split further into four approximately equal periods. I have not gone on players or series but rather calendar years split to get four similar sub-groups.

The 1990s have been more or less uniform with an average success % of around 64%. Half the matches have been won and a fair number drawn. There was a propensity to draw more matches during the early 1990s than later on. Defeats are fewer as are wins. Border captained during most of the first period and passed the captaincy to Mark Taylor during mid-1994. Taylor captained most of the Tests during the second period and handed over the captain's cap to Steve Waugh. Taylor was, by nature, a more aggressive captain than Border and has also acquired world-beaters as players.

Now we come to the real golden period of all. During the next 5 years, Steve Waugh captained Australia and amassed an incredible 80% success rate, despite the blip in India during 2001. Nearly three-quarter of the matches were won. Draws, as a playing option, were not offered to the opposing teams. Similar to the pattern already established, Steve Waugh passed the baton to Ponting during early 2004. There was a noticeable drop in success rate during the last period. However the 74% figure still represents strong domination of world cricket. Now that the responsibility has been passed on to Michael Clarke, the world will watch with interest how the next 5/6 years will shape up for Australia.

Now the details, viz., the batting averages and scoring rates for Australia and the opposition teams during these period.

          |--------Australia----------| |-------Other Teams---------|
Period    Wkts   Runs  Avge  Balls  RpO Wkts   Runs  Avge  Balls  RpO

1989-2010 3927 134071 34.14 243382 3.31 4187 119118 28.45 240984 2.97

1989-1994  972  32138 33.06  65699 2.94  989  29117 29.44  64656 2.70
1995-1999 1009  30332 30.06  60124 3.03  992  26464 26.68  55122 2.88
2000-2004  933  34853 37.36  55419 3.77 1104  29923 27.10  58786 3.05
2005-2010 1013  36748 36.28  62140 3.55 1102  33614 30.50  62420 3.23

Across these 22 years, Australian batsmen have scored at an average of 34.14 and at an overall rate of 3.31. The opposition have scored at an average of 28.45 and a scoring rate of 2.97. This represents a differential of 20% and 15% and explains the overall success of the Australian teams.

Now the period numbers. The first period has lower numbers for both but shows a differential of 12% and 9%, just enough for the edge which has been achieved. The second period has still lower numbers all around and show differentials of 12% and only 5%. These indicate only marginal superiority.

Now comes the wonderful period when Australian batting averages moved upwards and the other team averages moved downwards. The third period showed a differential of 37% and 23%. That has translated into the phenomenal 80% success rate.

During the last period, there has been 19% and 10% differential. Looks like there is a strong correlation between these differential values and overall success rates.

Now for the special analysis on player groups. First the Bowlers groups analysis which is probably more interesting. I have identified the Bowler groups which played in all these 236 Tests and ordered these on the number of matches played. Then each of these groups has been analyzed for all relevant measures. I have excluded the one-bowler groups since these do not convey much (only one selected bowler played). I have also not shown bowler groups which played in only one Test (e-g, Warne/MacGill or McGrath/MacGill/Lee et al). The players are given in order of their debut.

The presentation itself is quite complex. It was impossible to show the bowler groups and the numbers in one line. The display would have gone past the screen. Also if the player group line and the numbers line are shown together the numbers are not clear. Hence I have separated the player line and numbers line. The group number is the common link. Readers should not forget that these are unique player groups.

 1. Warne; McGrath; Gillespie; 
 2. Warne; McGrath; Gillespie; Lee; 
 3. Warne; McGrath; Lee; 
 4. Lee; Johnson; 
 5. Warne; McGrath; Reiffel; 
 6. McDermott; Hughes; 
 7. Warne; McGrath; 
 8. McDermott; Warne; Hughes; 
 9. McDermott; Warne; McGrath; Reiffel; 
10. McGrath; MacGill; 
11. McDermott; Warne; McGrath; 
12. Warne; McGrath; MacGill; Lee; 
13. McDermott; Warne; 
14. McGrath; Gillespie; MacGill; Lee; 
15. Gillespie; MacGill; Lee; 
16. Warne; Lee; 
17. MacGill; Lee; Johnson; 
18. Warne; McGrath; Gillespie; MacGill; 
19. Warne; McGrath; Gillespie; Reiffel; 

                   |--- Bowler Group--| |--- Other team --|Comparisons
No.  T  W D L    % Wkts Runs  Avge  RpO Wkts Runs  Avge RpO  Avge  RpO

 1. 23 15 3 5  71.7 304 7344 24.16 2.68 412 10701 25.97 2.90 1.08 1.08
 2. 16 10 4 2  75.0 265 7402 27.93 3.15 284  8086 28.47 3.30 1.02 1.05
 3. 16 14 2 0  93.8 224 5413 24.17 2.81 311  7470 24.02 2.91 0.99 1.04
 4. 13  5 3 5  50.0 111 3359 30.26 3.19 221  8141 36.84 3.31 1.22 1.04
 5. 10  5 3 2  65.0 126 2775 22.02 2.50 164  4133 25.20 2.71 1.14 1.08
 6. 10  4 4 2  60.0 100 2370 23.70 2.96 165  4986 30.22 3.07 1.28 1.04
 7. 10  6 2 2  70.0  86 1959 22.78 2.50 173  4174 24.13 2.87 1.06 1.15
 8.  9  4 2 3  55.6 105 3062 29.16 2.87 149  4632 31.09 2.90 1.07 1.01
 9.  7  4 2 1  71.4 103 2867 27.83 2.57 123  3374 27.43 2.57 0.99 1.00
10.  7  3 3 1  64.3  71 1706 24.03 2.73 120  3473 28.94 2.84 1.20 1.04
11.  6  4 1 1  75.0 104 2282 21.94 2.70 120  3185 26.54 2.78 1.21 1.03
12.  6  6 0 0 100.0 106 2797 26.39 2.88 115  3169 27.56 2.97 1.04 1.03
13.  6  2 3 1  58.3  50 1512 30.24 2.79  99  3331 33.65 3.02 1.11 1.08
14.  6  5 0 1  83.3 106 2584 24.38 2.79 117  3029 25.89 2.97 1.06 1.06
15.  5  3 1 1  70.0  60 2247 37.45 3.27  88  3621 41.15 3.40 1.10 1.04
16.  4  3 0 1  75.0  44 1070 24.32 3.24  77  2133 27.70 3.33 1.14 1.03
17.  4  3 1 0  87.5  52 1661 31.94 3.19  75  2288 30.51 3.09 0.96 0.97
18.  4  2 0 2  50.0  62 1677 27.05 2.97  69  1921 27.84 3.15 1.03 1.06
19.  4  3 0 1  75.0  72 1443 20.04 2.67  74  1643 22.20 2.81 1.11 1.05

It would not surprise many that Warne, McGrath and Gillespie have played together in the maximum number of Tests as a unique group. Their 27 Tests have yielded an excellent success rate of 72%. They have been 10% and 8% better than the the entire team values. I have shown the % difference to the entire team than the other bowlers since in cases where the group has three bowlers, the rest of the team would have captured very few wickets.

However the best group with significant number of Tests is Warne, McGrath and Lee. When they played as a group, they played 16, won 14 and drew 2. However the fourth bowler also seems to have pulled his weight since the differentials are quite low.

McDermott and Warne, when they played together, have not been very successful.

Note the success rate of Warne, McGrath, MacGill and Lee. They played 6 and won all and captured 105 of the 112 wickets.

As a super-group, Warne and McGrath, played together, along with other bowlers, in no fewer than 104 Tests, won 71, drew 17 and lost 16 for an overall success rate of 76.4. Undoubtedly the most potent bowling combination in history of Test cricket.

I have since added Hughes and Reiffel. Because of this the cut-off has been increased to 4 Tests. A few new groups involving Reiffel and Hughes have been created. Readers can peruse these themselves.

The batsmen groups are less interesting since upto 7 batsmen are involved and it is not easy to visualize the groups immediately. Let us see the tables. In the bowler groups there were 1-bowler groups. Here the minimum number of batsmen in a group is 4. There are a lot more groups than for the bowlers. Hence only batsmen groups which have played in 4 test or more are selected. It should be also noted that only Batting average comparisons are done since Balls faced information is not available for about 30 of the early matches.

 1. Ponting; Katich; Clarke; Hussey; 
 2. Boon; S Waugh; Healy; Taylor; Border; 
 3. Boon; S Waugh; Healy; Taylor; M Waugh; Slater; 
 4. S Waugh; M Waugh; Martyn; Langer; Hayden; Ponting; Gilchrist; 
 5. Boon; S Waugh; Healy; Taylor; M Waugh; Slater; Border; 
 6. Boon; Healy; Taylor; M Waugh; Border; 
 7. S Waugh; Healy; Taylor; M Waugh; Ponting; 
 8. Martyn; Langer; Hayden; Ponting; Gilchrist; Katich; Clarke; 
 9. Hayden; Ponting; Katich; Clarke; Hussey; 
10. S Waugh; M Waugh; Langer; Slater; Hayden; Ponting; Gilchrist; 
11. Hayden; Ponting; Gilchrist; Clarke; Hussey; 
12. S Waugh; M Waugh; Langer; Slater; Ponting; Gilchrist; 
13. S Waugh; Martyn; Langer; Hayden; Ponting; Gilchrist; 
14. S Waugh; Healy; M Waugh; Langer; Slater; Ponting; 
15. S Waugh; Martyn; Langer; Hayden; Ponting; Gilchrist; Katich; 
16. S Waugh; Langer; Hayden; Ponting; Gilchrist; 
17. Martyn; Langer; Hayden; Ponting; Gilchrist; Clarke; 
18. S Waugh; Healy; Taylor; M Waugh; Hayden; 
19. S Waugh; Healy; Taylor; M Waugh; Langer; Slater; 
20. S Waugh; Healy; Taylor; M Waugh; Langer; Slater; Ponting; 

                    |Batsmen Group| |---Entire team ---|  Comp
No.  T  W D L    %  Ins  Runs  Avge Ins  Runs  Avge  RpO  Avge

 1. 17 10 4 3  70.6 119  5415 45.50 283 10811 38.20 3.51  1.19
 2. 15  8 6 1  73.3 123  5092 41.40 244  8900 36.48 3.03  1.13
 3. 14  7 3 4  60.7 149  5620 37.72 258  7289 28.25 3.08  1.34
 4. 13  9 3 1  80.8 135  6446 47.75 190  7571 39.85 3.87  1.20
 5. 12  8 3 1  79.2 125  6208 49.66 164  7199 43.90 3.10  1.13
 6. 12  6 5 1  70.8 105  3706 35.30 220  6597 29.99 2.87  1.18
 7. 10  6 3 1  75.0  82  3271 39.89 171  5514 32.25 3.03  1.24
 8.  9  3 3 3  50.0 106  3682 34.74 161  4792 29.76 3.71  1.17
 9.  9  3 2 4  44.4  82  3279 39.99 169  5347 31.64 3.19  1.26
10.  7  5 0 2  71.4  77  2992 38.86 113  3688 32.64 3.39  1.19
11.  7  6 1 0  92.9  49  2600 53.06  88  4489 51.01 3.72  1.04
12.  6  6 0 0 100.0  55  2701 49.11  88  3560 40.45 3.59  1.21
13.  6  5 0 1  83.3  54  2981 55.20  82  3778 46.07 4.24  1.20
14.  6  2 2 2  50.0  54  1831 33.91  99  2570 25.96 2.74  1.31
15.  5  2 2 1  60.0  60  3014 50.23  85  3420 40.24 4.06  1.25
16.  5  5 0 0 100.0  31  1925 62.10  52  3026 58.19 3.93  1.07
17.  5  5 0 0 100.0  46  2523 54.85  70  3177 45.39 3.91  1.21
18.  4  2 0 2  50.0  35   898 25.66  74  1856 25.08 2.86  1.02
19.  4  2 1 1  62.5  42  1669 39.74  77  2191 28.45 2.96  1.40
20.  4  2 2 0  75.0  51  2304 45.18  63  2583 41.00 3.16  1.10

Border has since been added. The group which played in most Tests together is during the early years, viz., Taylor, Slater, Boon, M Waugh, S Waugh and Healy, which played together in 26 tests and had a respectable success value of 69.2%. The more recent foursome of Ponting, Katich, Clarke and Hussey has played in 17 Tests with a success rate of 70%. This number is likely to increase further. A four-some sub-set of the first group has played in 15 Tests with a higher success rate of 73.3%.

The most successful group with significant number of matches is the powerful one consisting of Hayden, Langer, Ponting, Mike Waugh, Martyn, Steve Waugh and Gilchrist which played in 13 tests and won 9 leading to a success % of 80+.

Like the bowlers, here also there is a group which achieved a 100% success rate in 6 Test matches. this group consists of Slater, Langer, Ponting, Mark Waugh, Steve Waugh and Gilchrist. Couple of other groups have achieved 100% in the 5 Tests they played together.

Finally we stand in admiration, awe and wonder at the team of great players who dominated the world scene for over 22 years. No current team can ever hope to match this record. India does not have the bowlers and their batting is going to get decimated soon. South Africa lacks the spin strength, unless otherwise Imran Tahir just blazes through, to do well everywhere. Australia themselves have to find quality replacements soon. They are also unable to finish off won matches nowadays. Sri Lanka are going through a transitory phase and the future does not look that great, for most of the teams. There is going to be periodic domination by teams for periods of 2/3 years. That is all.

The Test-player matrix could not be drawn in a graphical mode in view of the huge number of players. The graph would have become very unwieldy and impossible to view. Hence I have created a viewable text file for the readers.

To view/down-load the file containing the matrix between all 24 players and the 236 Tests, to indicate which player played in which test, please click/right-click here. You could export this into an Excel sheet or view as a text file.

To view/down-load the file containing the matrix between 9 bowlers and the 236 Tests, to indicate which player played in which test, please click/right-click here. You could export this into an Excel sheet or view as a text file.

To view/down-load the file containing the matrix between 15 batsmen and the 236 Tests, to indicate which player played in which test, please click/right-click here. You could export this into an Excel sheet or view as a text file.

This analysis is based on a request by Alex who wanted me to do an analysis of the Test performances by innings. It is a straight-forward analysis based on raw numbers. Please take this as a break up of the Career performances into lower levels with no adjustment whatsoever. The innings status at entry, match conditions, match location, quality of bowling, quality of opposition team et al are relevant factors but have not been incorporated. Once I open one door, the draught will open all the other doors and I do not want to do that. There are a number of tables shown. These tables are provided with minimal comments. The top-20/10/5 entries are shown in the main article and the complete tables are made available for viewing/downloading.

First the Team innings tables. For the Team innings, the cut-off is 3000 career runs. In addition to the batting average and runs scored tables, I have one on the comparison ratio to the career batting average. This table will indicate how close or away from their career averages have the batsmen performed in different innings and will give an insight into whether the batsman has excelled in setting up or finish the matches. Both are important but we need this insight to get a proper handle on batsmen appreciation.

1.1. Team First innings (Match inns 1/2) analysis: Table ordered by Batting average

Batsman             Inns No  Runs   Avge

Bradman D.G           50  2  4697  97.85
EdeC Weekes           48  0  3429  71.44
Sehwag V              87  1  5917  68.80
Barrington K.F        82  5  5069  65.83
Hutton L              79  4  4905  65.40
Hammond W.R           85  6  5070  64.18
Tendulkar S.R        174  9 10557  63.98
Lara B.C             130  1  8249  63.95
Hobbs J.B             60  1  3750  63.56
Jayawardene D.P.M.D  115  2  7127  63.07
Worrell F.M.M         51  5  2843  61.80
Waugh S.R            166 25  8558  60.70
Samaraweera T.T       61  7  3251  60.20
Sangakkara K.C        93  4  5345  60.06
Mohammad Yousuf       89  5  5043  60.04
Sobers G.St.A         93  7  5109  59.41
Ponting R.T          152  5  8723  59.34
Walcott C.L           44  1  2547  59.23
Sutcliffe H           53  2  3014  59.10
Dravid R             150  8  8329  58.65

This is an important classification since it removes the distinction between first/second and third/fourth innings. Bradman just about misses the 100 mark. Note Sehwag's near-70 average. Also how the two modern greats, Tendulkar and Lara are separated only in the second decimal point. Jayawardene is the other modern batsman to appear in the top-10.

1.2. Team First innings analysis: Table ordered by Runs scored

Batsman             Inns No  Runs   Avge

Tendulkar S.R        174  9 10557  63.98
Ponting R.T          152  5  8723  59.34
Waugh S.R            166 25  8558  60.70
Dravid R             150  8  8329  58.65
Lara B.C             130  1  8249  63.95
Kallis J.H           145  9  7590  55.81
Jayawardene D.P.M.D  115  2  7127  63.07
Border A.R           154 13  6803  48.25
Javed Miandad        123  8  6504  56.56
Gavaskar S.M         124  3  6159  50.90

Not surprising to see Tendulkar with 10000+ runs atop the table which is dominated by batsmen of recent vintage.

1.3. Team First innings analysis: Table ordered by Ratio to Career average

Batsman             Inns No  Runs   Avge   Ratio

Sehwag V              87  1  5917  68.80  128.8%
McDonald C.C          47  0  2380  50.64  128.8%
Zaheer Abbas          77  6  3977  56.01  125.0%
Worrell F.M.M         51  5  2843  61.80  124.9%
Atapattu M.S          88  5  4044  48.72  124.9%
Hassett A.L           43  1  2435  57.98  124.5%
Bell I.R              62  6  3043  54.34  123.1%
EdeC Weekes           48  0  3429  71.44  121.9%
Lara B.C             130  1  8249  63.95  120.9%
Waugh S.R            166 25  8558  60.70  118.9%
Adams J.C             53  9  2152  48.91  118.6%
...
Amla H.M              51  1  2351  47.02  100.1%
Boon D.C             107  4  4491  43.60   99.9%
...
Redpath I.R           66  1  2503  38.51   88.6%
Mitchell B            42  0  1817  43.26   88.5%
Butcher B.F           44  2  1428  34.00   78.9%

It may not be a surprise to see that Sehwag tops the table in first innings performances, scoring at nearly 30% above his career average. Lara clocks in at over 20%. Butcher has had a very average first innings. Amla and Boon are either side of 100%.

2.1. Team Second innings (Match inns 3/4) analysis: Table ordered by Batting average

Batsman             Inns No  Runs   Avge

Bradman D.G           30  8  2299 104.50
Kallis J.H           101 29  4357  60.51
Sobers G.St.A         67 14  2923  55.15
Border A.R           111 31  4371  54.64
Sangakkara K.C        63  8  2899  52.71
Hayden M.L            81 14  3473  51.84
Laxman V.V.S          78 18  3104  51.73
Gavaskar S.M          90 13  3963  51.47
Boycott G             85 20  3319  51.06
Redpath I.R           54 10  2234  50.77
Compton D.C.S         53 12  2020  49.27
Richards I.V.A        61 10  2495  48.92
Haynes D.L            86 24  3030  48.87
Younis Khan           53  8  2195  48.78
Hammond W.R           55 10  2179  48.42
Cook A.N              50  6  2108  47.91
Thorpe G.P            79 23  2659  47.48
Greenidge C.G         77 15  2923  47.15
Inzamam-ul-Haq        82 14  3194  46.97
Crowe M.D             56 11  2098  46.62

Bradman is back on top with a 100+ average. Kallis is the only other batsman with a 60+ average. Sangakkara, Hayden and Laxman are the other modern batsmen in the top-10.

2.2. Team Second innings analysis: Table ordered by Runs scored

Batsman             Inns No  Runs   Avge

Border A.R           111 31  4371  54.64
Kallis J.H           101 29  4357  60.51
Tendulkar S.R        116 23  4135  44.46
Gavaskar S.M          90 13  3963  51.47
Gooch G.A             97  6  3898  42.84
Dravid R             109 21  3734  42.43
Lara B.C             102  5  3704  38.19
Ponting R.T          107 23  3636  43.29
Hayden M.L            81 14  3473  51.84
Stewart A.J          103 15  3462  39.34

The second innings averages of Tendulkar, Lara and Ponting are significantly lower than the rest of the top modern batsmen.

2.3. Team Second innings analysis: Table ordered by Ratio to Career average

Batsman             Inns No  Runs   Avge   Ratio

Butcher B.F           34  4  1676  55.87  129.6%
Manjrekar V.L         37  8  1341  46.24  118.2%
Redpath I.R           54 10  2234  50.77  116.8%
Mitchell B            38  9  1654  57.03  116.7%
Haynes D.L            86 24  3030  48.87  115.5%
Amarnath M            45  7  1865  49.08  115.5%
May P.B.H             40  6  1795  52.79  112.9%
Saleem Malik          57 16  1960  47.80  109.4%
Laxman V.V.S          78 18  3104  51.73  109.3%
Flower A              49 14  1972  56.34  109.3%
...
Boon D.C              83 16  2931  43.75  100.2%
Amla H.M              39  6  1546  46.85   99.8%
...
Zaheer Abbas          47  5  1085  25.83   57.7%
Sehwag V              63  5  1777  30.64   57.3%
Hassett A.L           26  2   638  26.58   57.1%

We all know about Laxman's second innings exploits. We would expect him to perform above his career average. But who would have thought that Butcher would have a 30% higher performance level in the second innings or that Haynes would have a 15% higher level batting in the second innings. As expected Sehwag almost props up the table, having performed at 57% of his career levels. Zaheer Abbas performed at similar low levels. As mentioned already, Boon and Amla are almost at their career levels in both innings.

For the Match innings 1-2-3, the cut-off is 1000 runs and for the Match innings 4, the cut-off is 500 runs. I have also replaced the average comparison table with one on % of Team score.

3.1. Match First innings analysis: Table ordered by Batting average

Batsman             Inns No  Runs   Avge

Bradman D.G           22  1  2387 113.67
Ponsford W.H          15  1  1148  82.00
Hassett A.L           22  1  1655  78.81
EdeC Weekes           27  0  2068  76.59
Samaraweera T.T       32  3  2126  73.31
Lara B.C              58  1  4000  70.18
Barrington K.F        42  3  2735  70.13
Tendulkar S.R         83  6  5397  70.09
Javed Miandad         60  6  3730  69.07
Leyland M             19  0  1256  66.11
Hutton L              35  1  2232  65.65
Kanhai R.B            44  0  2869  65.20
Walters K.D           37  2  2271  64.89
Walcott C.L           24  0  1541  64.21
Sehwag V              38  1  2330  62.97
Hammond W.R           46  3  2691  62.58
Jones D.M             31  1  1871  62.37
Ponting R.T           84  4  4986  62.33
Waugh S.R             94 16  4855  62.24
Worrell F.M.M         24  3  1302  62.00

Bradman's 110+ average is expected. What is significant is that the two modern greats, Lara and Tendulkar, average over 70. Possibly more relevant is the unfancied Samaraweera's 70+ average.

3.2. Match First innings analysis: Table ordered by Runs scored

Batsman             Inns No  Runs   Avge

Tendulkar S.R         83  6  5397  70.09
Ponting R.T           84  4  4986  62.33
Waugh S.R             94 16  4855  62.24
Border A.R            87  9  4056  52.00
Lara B.C              58  1  4000  70.18
Dravid R              69  3  3921  59.41
Kallis J.H            70  4  3805  57.65
Javed Miandad         60  6  3730  69.07
Gooch G.A             69  0  3184  46.14
Langer J.L            55  2  3181  60.02

Almost totally filled by modern batsmen, indicating the high number of tests played by them.

3.3. Match First innings analysis: Table ordered by % of Team runs

Batsman             Inns No  Runs TeamRuns %Share

Bradman D.G           22  1  2387    9438  25.3%
Lara B.C              58  1  4000   18111  22.1%
EdeC Weekes           27  0  2068    9997  20.7%
Hassett A.L           22  1  1655    8407  19.7%
Ponsford W.H          15  1  1148    6117  18.8%

Bradman's 25+% is in line with his overall career % share while Lara has had a higher share than his career average figure of 20%.

4.1. Match Second innings analysis: Table ordered by Batting average

Batsman             Inns No  Runs   Avge

Bradman D.G           28  1  2310  85.56
Sehwag V              49  0  3587  73.20
Jayawardene D.P.M.D   60  1  4124  69.90
Mohammad Yousuf       47  4  2983  69.37
Sangakkara K.C        46  3  2940  68.37
Hobbs J.B             37  0  2503  67.65
Hammond W.R           39  3  2379  66.08
Chappell G.S          38  2  2378  66.06
Hutton L              44  3  2673  65.20
Bell I.R              26  4  1428  64.91
EdeC Weekes           21  0  1361  64.81
Prince A.G            31  5  1642  63.15
Hussey M.E.K          22  1  1322  62.95
Worrell F.M.M         27  2  1541  61.64
Barrington K.F        40  2  2334  61.42
Sobers G.St.A         37  1  2211  61.42
Gavaskar S.M          63  3  3613  60.22
Gilchrist A.C         47  5  2501  59.55
Lara B.C              72  0  4249  59.01
Waugh S.R             72  9  3703  58.78

Bradman drops well below 100. Note how Bradman is followed with 70+- averages by four modern stalwarts, Sehwag, Jayawardene, Yousuf and Sangakkara.

4.2. Match Second innings analysis: Table ordered by Runs scored

Batsman             Inns No  Runs   Avge

Tendulkar S.R         91  3  5160  58.64
Dravid R              81  5  4408  58.00
Lara B.C              72  0  4249  59.01
Jayawardene D.P.M.D   60  1  4124  69.90
Kallis J.H            75  5  3785  54.07
Ponting R.T           68  1  3737  55.78
Waugh S.R             72  9  3703  58.78
Gavaskar S.M          63  3  3613  60.22
Sehwag V              49  0  3587  73.20
Richards I.V.A        73  1  3514  48.81

Richards just about gets in the run aggregate table.

4.3. Match Second innings analysis: Table ordered by % of Team runs

Batsman             Inns No  Runs TeamRuns %Share

Bradman D.G           28  1  2310   10513  22.0%
Hutton L              44  3  2673   12850  20.8%
Hobbs J.B             37  0  2503   12585  19.9%
Turner G.M            29  1  1588    8345  19.0%
Hammond W.R           39  3  2379   12831  18.5%

5.1. Match Third innings analysis: Table ordered by Batting average

Batsman             Inns No  Runs   Avge

Bradman D.G           15  3  1565 130.42
Kallis J.H            59 15  3128  71.09
May P.B.H             21  3  1225  68.06
Compton D.C.S         31  7  1565  65.21
Border A.R            76 21  3511  63.84
Martyn D.R            25  6  1203  63.32
Walcott C.L           21  4  1067  62.76
Butcher B.F           24  2  1352  61.45
Flower A              38 10  1704  60.86
Saleem Malik          36 11  1512  60.48
Armstrong W.W         27  4  1391  60.48
Amla H.M              22  4  1044  58.00
Sobers G.St.A         48  8  2316  57.90
Laxman V.V.S          47  9  2197  57.82
Sangakkara K.C        42  4  2187  57.55
Amiss D.L             20  2  1002  55.67
Nourse A.D            23  3  1105  55.25
Thorpe G.P            45 11  1870  55.00
Amarnath M            33  5  1525  54.46
Gambhir G             19  0  1033  54.37

Bradman, aided by 3 not out innings, averages a huge 130+, nearly double that of the next batsman in the table. These are the difficult innings and note how Kallis weighs in with an outstanding 70+ average. Martyn. Andy Flower, Amla and Laxman all have 57+ averages.

5.2. Match Third innings analysis: Table ordered by Runs scored

Batsman             Inns No  Runs   Avge

Border A.R            76 21  3511  63.84
Kallis J.H            59 15  3128  71.09
Gooch G.A             68  2  2777  42.08
Tendulkar S.R         66  8  2764  47.66
Gavaskar S.M          57  4  2565  48.40
Dravid R              59  4  2334  42.44
Inzamam-ul-Haq        51  6  2327  51.71
Stewart A.J           64  9  2326  42.29
Sobers G.St.A         48  8  2316  57.90
Gower D.I             62  9  2287  43.15

Border and Kallis lead, indicating their propensity to score in these difficult innings.

5.3. Match Third innings analysis: Table ordered by % of Team runs

Batsman             Inns No  Runs TeamRuns %Share

Bradman D.G           15  3  1565    5170  30.3%
May P.B.H             21  3  1225    5537  22.1%
Kallis J.H            59 15  3128   15731  19.9%
Nourse A.D            23  3  1105    5570  19.8%
Sangakkara K.C        42  4  2187   11142  19.6%

Bradman has scored a phenomenal 30+%. We should not forget that many of the third innings would have been declared. Note Kallis's near 20% share.

6.1. Match Fourth innings analysis: Table ordered by Batting average

Batsman             Inns No  Runs   Avge

Mitchell B            12  5   629  89.86
Stollmeyer J.B        10  4   518  86.33
Bradman D.G           15  5   734  73.40
Hussey M.E.K          12  4   505  63.12
Hunte C.C             13  4   549  61.00
Boycott G             34 13  1234  58.76
Gavaskar S.M          33  9  1398  58.25
Hobbs J.B             23  6   979  57.59
Younis Khan           20  6   806  57.57
Javed Miandad         22  7   816  54.40
Ponting R.T           39 14  1358  54.32
Sutcliffe H           15  3   644  53.67
Stackpole K.R         19  5   749  53.50
Greenidge C.G         38 12  1383  53.19
Smith G.C             31  6  1322  52.88
Hayden M.L            39 13  1288  49.54
Chappell G.S          25 11   688  49.14
Jayawardene D.P.M.D   27  9   879  48.83
Dexter E.R            16  5   535  48.64
Taylor R.L            11  0   532  48.36

Finally we have an average table in which Bradman has been relegated to third place. He averages a mere mortal level 73+. Mitchell of South Africa and Stollmeyer of West Indies lead the table with 80+ averages. Note Mike Hussey's high average.

6.2. Match Fourth innings analysis: Table ordered by Runs scored

Batsman             Inns No  Runs   Avge

Lara B.C              46  5  1440  35.12
Dravid R              50 17  1400  42.42
Gavaskar S.M          33  9  1398  58.25
Greenidge C.G         38 12  1383  53.19
Atherton M.A          39  6  1375  41.67
Tendulkar S.R         50 15  1371  39.17
Chanderpaul S         41 10  1364  44.00
Ponting R.T           39 14  1358  54.32
Smith G.C             31  6  1322  52.88
Hayden M.L            39 13  1288  49.54

Lara leads the modern list of batsmen. It must be remembered that West Indies, being considerably weak, probably played more fourth innings than the other teams. There were very few times when West Indies had the luxury of innings wins or 9-10 wicket wins.

6.3. Match Fourth innings analysis: Table ordered by % of Team runs

Batsman             Inns No  Runs TeamRuns %Share

Stollmeyer J.B        10  4   518    1419  36.5%
Mitchell B            12  5   629    2312  27.2%
Greenidge C.G         38 12  1383    5369  25.8%
Bradman D.G           15  5   734    2901  25.3%
Hunte C.C             13  4   549    2215  24.8%

Stollymeyer scored 36% of the runs. However the cut-off here is 500 runs.

As I have already explained, I have deliberately kept my comments to a minimal level since the article already has 18 tables. Readers can send in their own comments.

To view/down-load the complete Innings performance tables, please click on links given below. Each of these files has three tables.

Team First innings table: please click/right-click here.
Team Second innings table: please click/right-click here.

Match First innings table: please click/right-click here.
Match Second innings table: please click/right-click here.
Match Third innings table: please click/right-click here.
Match Fourth innings table: please click/right-click here.

Time for a Christmas Quiz on the It Figures blog. All questions apply to Test cricket only. The first three correct entries sent to rfinlay7@bigpond.com will receive a free Tastats cricket compute database.

Following are the ten questions:

1. Which player has taken part in the most partnerships in Test cricket?

2. Who has the highest innings top score in a losing team?

3. Who shares the record for the lowest innings top score in a winning team?

4. Who is the only player to be dismissed for a duck having come in immediately at the conclusion of a partnership of at least 400 runs?

5. What is the highest team score at which three wickets have consecutively fallen for the addition of no runs?

6. What partnership record does Desmond Haynes uniquely hold?

7. Which player fielded in the most consecutive innings without taking a catch?

8. Which player scored most runs in a Test in which his birthday fell?

9. Which player took most wickets after his 40th birthday?

10 What is the highest partnership to end in a run out?

Recently Unnikrishnan had suggested a way of measuring individual Test innings in a different manner. His suggestion was that the innings should be evaluated against the average score of the other batsmen who batted in that particular innings. He also wanted the individual innings values summed across all innings for each batsmen and averaged across their career, similar to the way the Batting Averages are calculated. For instance, to compute Don Bradman's career Innings Index value, the Innings Index values for all his 80 innings would be added and divided by 80. These are excellent suggestions in view of the following plus factors.

- This is an out-and-out peer comparison, that too within the same team.
- The comparison is within the same innings: Hence the conditions would be almost identical.
- The bowling quality faced would be almost identical, barring innings-level variations.
- This effectively takes take care of the oft-repeated complaints by readers regarding batsmen playing in weak or strong teams.

In some ways this is similar to the simpler % of Team score measure. However the one major difference is that in the % TS measure the number of batsmen who batted is not taken into account. "For no loss" and "for 7 wkts" will produce the same % TS, as explained in the examples. However the Innings Index takes care of this very well and is a true peer comparison. Team score, as given below, is sans extras.

Team-Score Batsman-Score  % TS   Inns Index

100 for 0      50          50        1.0
100 for 5      50          50        6.0
200 for 3     100          50        4.0
200 for 9     100          50       10.0
300 for 2     150          50        3.0
300 for 10    150          50       10.0

100 for 10     60          60       15.0
100 for 1      25          25       0.33
200 for 7     120          60       12.0
200 for 1      40          20        0.5
300 for 10    200          66.7     20.0

The formula for determining the Inns Index is quite simple and outlined below.

                    Runs scored by batsman
Innings Index  = -------------------------------
                 Average score of other batsmen
				
where
                                 Total runs made by other batsmen
Average score of other batsmen = --------------------------------
                                  No of other batsman who batted

I had to do limiting of the Innings Index values for innings in which fewer than 5 wickets fell as otherwise the following silly situation emerges. Aamir Sohail's 46 out of 61/2 will get 15.33 ??? Such cases have been limited to a reasonable number below 5 since these do not really reflect batsman contributions in demanding situations.

I have shown two tables. The first is a table of the top innings based on the Innings Index value. The second is a table of batsmen ordered by the average Innings Index value over the career.

Now for the first table. Readers will note a clear correlation between this and the % Team Score. However this is a far more robust and well-thought out measure which stands any test. Let me repeat, for the sake of readers itching to put in their tuppenny-worth on the innings they think should be placed high. This is not a list of the best innings. It is a table of innings whose Innings Index values, as described in this article are high. That is all. Do not draw unnecessary inferences from either of the tables.

Now for the first table. I have listed here the top-25 innings ordered by the Inns Index.

Table of Innings ordered by Innings Index 
(Batsman score > 199 or Inns Index > 5.0)

MtId Year Batsman            Bat Team (Ext) Batsman Oth  Inns
                             Pos Score      Score   Avge Index
			      
1156 1990 Gurusinha A.P       3  82/10 ( 8)   52*   2.2  23.64
0001 1877 Bannerman C         1 245/10 ( 8)  165*   7.2  22.92
1439 1999 Slater M.J          1 184/10 ( 4)  123    5.7  21.58
1481 2000 Laxman V.V.S        1 261/10 (21)  167    8.1  20.59
0732 1974 Amiss D.L           1 432/ 9 (41)  262*  12.9  20.31
0779 1976 Greenidge C.G       1 211/10 (11)  134    6.6  20.30
0542 1963 Reid J.R            4 159/10 ( 9)  100    5.0  20.00
1171 1991 Gooch G.A           1 252/10 (21)  154*   7.7  20.00
1306 1995 Moin Khan           7 212/10 (34)  117*   6.1  19.18
0401 1955 Sutcliffe B         3 125/10 (12)   74    3.9  18.97
0303 1948 Hutton L            1  52/10 ( 6)   30    1.6  18.75
1283 1995 Inzamam-ul-Haq      5 165/10 (19)   95    5.1  18.63
0164 1926 Macartney C.G       3 194/ 5 (17)  133*   7.3  18.14
0652 1969 Nurse S.M           3 417/10 (14)  258   14.5  17.79
1913 2009 Duminy J.P          6 138/10 (23)   73*   4.2  17.38
1884 2008 Sehwag V            1 329/10 (12)  201*  11.6  17.33
0665 1969 Burgess M.G         6 200/10 (12)  119*   6.9  17.25
1716 2004 Jayasuriya S.T      1 438/10 (37)  253   14.8  17.09
0130 1913 Taylor H.W          1 182/10 ( 9)  109    6.4  17.03
0079 1904 Tyldesley J.T       3 103/10 ( 8)   62    3.7  16.91
0846 1979 Yallop G.N          4 198/10 ( 5)  121    7.2  16.81
1206 1992 Kapil Dev N         7 215/10 ( 8)  129    7.8  16.54
0330 1951 Hutton L            1 272/10 (21)  156*   9.5  16.42
1820 2006 Sangakkara K.C      3 170/10 ( 9)  100*   6.1  16.39
0059 1899 Sinclair J.H        4 177/10 ( 6)  106    6.5  16.31
1747 2005 Sarwan R.R          3 194/10 (21)  107*   6.6  16.21
1444 1999 Saeed Anwar         1 316/10 (12)  188*  11.6  16.21
1749 2005 Lara B.C            4 296/10 (10)  176   11.0  16.00
0841 1979 Gomes H.A           3 151/10 ( 3)   91    5.7  15.96
0587 1965 Saeed Ahmed         3 307/ 8 (38)  172   10.8  15.96

A real surprise at the top. Asanka Gurusinha, a competent performer for Sri Lanka (with an average of 38.9), with his innings of 52 out of 84 all out (8 extras). This leads to an Inns Index value of 23.64. Then come three classics spread across 123 years. Charles Bannerman's 165 has a value of 22.9, Slater's 123 has a value of 21.5 and Laxman's career-defining 167 leads to an Inns Index value of 20.5. Then comes one of the greatest match-saving innings of all time by Amiss of 262, with an Inns Index value of 20.3.

There is a case for keeping a minimum team score as 100 to ensure that the index may have more validity. However I feel that in cases like Gurusinha's or Hutton's innings, the important factor is that the team was all out, in other words, 11 batsmen batted. Hence I have decided to retain these values.

Note the presence of some modern classics such as Sehwag's 201, Inzamam's 95, Jayasuriya's 253 and Sangakkara's 100. These are wonderful innings and fully deserve to be in this special list.

To view/down-load the complete Innings Index table of innings of 200 runs or more or an Inns Index value greater than 5.0, please click/right-click here.

Now for the batsmen table. To do this table I have added the Inns Index values for all the innings played by the batsman and divided the sum by the number of innings played. This leads to an average Inns Index value. An innings is what it says. When a batsman takes strike and whether he finishes at 400* or 0*, it is an innings. I am sure readers would come out with their own suggestions on excluding certain types of not outs, such as single digit ones. Let me wait for such suggestions and I am prepared to do the tweak and show the alternate table. As of now it is one straight forward calculation. As usual the batsmen who have scored over 2000 runs are shown. There is only one batsman of significance in the below-2000 group, Eddie Paynter who had scored 1540 runs at 59.23.

Batsman              Cty Inns   Runs   Bat   Avge  Inns Index  
                               Total   Avge  IIdx   <1.0 >5.0 

Bradman D.G          Aus   80   6996  99.94  3.348   22   19
Headley G.A          Win   40   2190  60.83  3.226   17   11
Lara B.C             Win  232  11953  52.89  2.701   99   42
Taylor H.W           Saf   76   2936  40.78  2.560   38   10
Nourse A.D           Saf   62   2960  53.82  2.551   28    9
Hutton L             Eng  138   6971  56.67  2.504   55   16
Hobbs J.B            Eng  102   5410  56.95  2.463   43   14
Turner G.M           Nzl   73   2991  44.64  2.438   36    9
Flower A             Zim  112   4794  51.55  2.387   58   17
EdeC Weekes          Win   81   4455  58.62  2.360   34   12
Hazare V.S           Ind   52   2192  47.65  2.283   24    5
Sutcliffe B          Nzl   76   2727  40.10  2.255   29    8
Hanif Mohammad       Pak   97   3915  43.99  2.254   49   16
Pollock R.G          Saf   41   2256  60.97  2.246   22    5
Taylor R.L           Nzl   51   2077  41.54  2.240   30    7
Habibul Bashar       Bng   99   3026  30.88  2.216   47   11
Sangakkara K.C       Slk  156   8244  57.25  2.190   74   21
Gavaskar S.M         Ind  214  10122  51.12  2.185  106   27
Mitchell B           Saf   80   3471  48.89  2.178   31    9
Walcott C.L          Win   74   3798  56.69  2.160   42   11
Hammond W.R          Eng  140   7249  58.46  2.158   73   15
Gooch G.A            Eng  215   8900  42.58  2.156  103   25
Sutcliffe H          Eng   84   4555  60.73  2.147   34    9
Saeed Anwar          Pak   91   4052  45.53  2.135   37   10
Mohammad Yousuf      Pak  156   7530  52.29  2.130   63   17
Sehwag V             Ind  146   7613  54.38  2.117   63   17
Chanderpaul S        Win  219   9063  48.99  2.116  106   24
Cowper R.M           Aus   46   2061  46.84  2.104   23    3
Saeed Ahmed          Pak   78   2991  40.42  2.093   34    6
May P.B.H            Eng  106   4537  46.77  2.080   41   11
Tendulkar S.R        Ind  286  14513  56.91  2.075  131   29

Bradman leads the table with an average Inns Index value of 3.348. What does this mean. Across his career he has scored 3.3 times the average of his compatriots, taken innings by innings. And in Bradman's case, because of the strength of Australia, the proportion of late order batting performances which are compared with Bradman would be fewer. That says something. Imagine, each time he performed at the level of his fellow players, he has to make up by notching up an innings with an Inns Index value of nearly 6 !!! He has performed below his compatriots only just over 25%, while the other batsmen have done between 40 and 50%. Similarly he has batted at a level above 5 times the average of his fellow batsmen just below 25%, while the rest of the batsmen do this between 10 and 15%. These are unbelievable numbers to read, digest and marvel.

The "Black Bradman" is second with the only other 3+ value. The fact that he is quite close to Bradman speaks volumes. Lara is third with a score of 2.701. There is no doubt that he would have benefited from playing in a weaker teams. However it is still necessary to outscore them consistently. A surprise next. Herb Taylor of South Africa is next with 2.560 and the classical batsman, Nourse next with 2.551.

Look at the next six batsmen. Hutton, Hobbs, Glenn Turner, Andy Flower, Everton Weekes and Vijay Hazare. This is an eclectic mix of batsmen playing for stronger and weaker batting line-ups. So playing for a stronger batting line-up does not necessarily prevent a player from getting a reasonable high average value. Hutton, Hobbs and Weekes played in strong batting line-ups. I get the feeling that this might be true where there were 3 top batsmen in the side, not 5 was the case with the Australian team of the 2000s and recent Indian teams. Andy Flower virtually carried his team for most of his career as did Glenn turner. Hazare played in a reasonably strong batting line-up. Not a surprise that Gavaskar and Hanif Mohammad are the leading batsmen of their respective countries.

I would conclude that the top batsmen in this analysis would have an average Inns Index value of over 2.00.

To view/down-load the complete Player table of all batsmen who have scored 2000 runs and above, please click/right-click here.

Many thanks to Unnikrishnan for the suggestion. This will become part of my ratings work replacing the % of Team Score measure.

The quality of a batsman is usually measured against the bowling and conditions in which he performed. Very few matches in the 2000s have provided the opportunity to witness high quality knocks. The bowling standard has drastically fallen away in the second half of the decade and the pitches have been lifeless. In contrast, the 1990s still had fantastic fast bowlers in each team and run scoring was not the easiest. Zimbabwe’s problems and Bangladesh’s entry have meant there are ample opportunities for most batsmen to boost their averages.

The average has always been an excellent measure of consistency and quality, but has a flip side because it does not quite consider the difference between a half century made on a minefield (read Sunil Gavaskar’s 96) and a century made on a featherbed (most matches at the SSC). A batting average of 50 which was earlier considered elite has now become commonplace this decade due to poor bowling attacks and placid tracks. The 2000s remains the decade with the highest batting average after the 1940s, which was a decade with very few matches. In this piece, I try to come up with a method to measure the true average of batsmen by considering the bowling strength of the opposition and the conditions encountered in the match.

The parameters used for the analysis are quite basic.
1. The bowling average for each opponent (in matches involving the player) is taken into consideration for home and away games.
2. The match average for all the matches is used to measure the difficulty level encountered. In matches involving Zimbabwe and Bangladesh, I do not consider the batting average of the minnows as the figure can skew the numbers badly. In these cases, the measure is purely the batting average of the other team.

The base value to measure the quality of an innings is calculated as the geometric mean (square root of the product) of the batting average (30.61) and bowling average (32.31) since Jan 1 1940. The quality index value obtained is 31.44. For each batsman, the similar values are calculated and measured with respect to the base value to obtain the accurate or effective average. For example if the batting and bowling average are 30 and 32 respectively , then the geometric mean is 30.98 and the quality factor is obtained by dividing the base value by the mean which yields 1.0147.

The table below lists the top run-getters in the 2000s (minimum qualification of 6000 runs). The table provides the details of runs aggregated home and away against each opponent (neutral venues also considered for Pakistan). Read the values as runs (innings played).

Ricky Ponting has had a wonderful decade as can be seen from his position at the top of the tree. After his horror run in India in 2000-01, he was unstoppable for the next six years, but has shown signs of decline over the last two years. Jacques Kallis and Rahul Dravid have been the rocks of the middle order for their respective teams. Dravid though has been slightly on the wane over the last three years which has seen his average drop from almost 59 to around 54. Mahela Jayawardene and Kumar Sangakkara have contributed immensely to Sri Lanka’s rise as a competitive Test team, especially at home. Sachin Tendulkar’s recent resurgence has stunned everybody and the early years of the 2000s when his injuries led to some poor performances have now been forgotten completely.

VVS Laxman and Virender Sehwag have eased much of the burden on Tendulkar in this decade with some exceptional performances. Shivanrine Chanderpaul and Brian Lara were the best batsmen for the West Indies in an otherwise forgettable decade. Lara retired on a high scoring 21 centuries in the 2000s. Mohammad Yousuf had a brilliant first half of the decade including a record breaking 2006 when he went past Viv Richards’ aggregate runs in a calendar year.

** The tables are in two parts for sake of clarity
***Ricky Ponting and Matthew Hayden played one Test against ICC W XI scoring 54 and 188 runs in two innings respectively. The calculations for these are done separately and included.

Top run-getters in the 2000s (minimum qualification 6000 runs)

Batsman	Aus(h)	Aus(a/n)	Eng(h)	Eng(a/n)	Ind(h)	Ind(a/n)	NZ(h)	NZ(a/n)	Pak(h)	Pak(a/n)
Ricky Ponting	-	-	993(16)	1082(25)	1115(16)	530(18)	496(11)	362(8)	781(12)	440(8)
Jacques Kallis*	700(17)	708(17)	1118(19)	292(13)	327(8)	760(15)	826(13)	354(6)	408(5)	521(8)
Rahul Dravid*	737(24)	972(24)	574(14)	915(15)	-	-	313(4)	766(14)	524(11)	550(9)
Mahela Jayawardene	185(6)	274(4)	1070(14)	502(12)	863(14)	628(10)	434(7)	194(7)	430(15)	630(15)
Sachin Tendulkar	1173(22)	925(17)	546(13)	629(12)	-	-	71(4)	444(9)	394(8)	268(7)
Matthew Hayden	-	-	909(17)	552(18)	861(13)	1027(22)	461(11)	197(7)	128(6)	246(4)
Kumar Sangakkara	112(6)	391(6)	671(14)	336(12)	892(14)	365(10)	317(7)	334(7)	619(10)	695(9)
Graeme Smith*	260(11)	493(14)	696(17)	1083(17)	227(6)	431(12)	220(8)	290(6)	347(9)	358(8)
Virender Sehwag*	763(20)	833(14)	290(12)	237(6)	-	-	177(4)	180(9)	544(6)	732(8)
VVS Laxman	1082(22)	1034(17)	180(9)	404(11)	-	-	279(4)	322(9)	375(10)	262(9)
Shivnarine Chanderpaul	699(12)	260(12)	400(12)	1061(20)	863(15)	260(5)	103(3)	276(8)	464(9)	306(9)
Mohammad Yousuf	-	367(12)	684(9)	815(15)	741(10)	366(11)	29(1)	718(14)	-	-
Brian Lara*	533(4)	707(18)	500(7)	503(17)	413(15)	-	149(3)	90(5)	331(4)	448(5)
Chris Gayle	186(6)	449(10)	474(13)	721(21)	481(16)	160(5)	280(3)	540(8)	115(5)	324(9)

Top run-getters in the 2000s (minimum qualification 6000 runs)

Batsman	SA(h)	SA(a/n)	SL(h)	SL(a/n)	WI(h)	WI(a/n)	Bang(h)	Bang(a/n)	Zim(h)	Zim(a/n)
Ricky Ponting	915(17)	867(17)	207(5)	198(6)	707(19)	846(11)	69(2)	191(3)	259(3)	-
Jacques Kallis	-	-	257(7)	318(10	929(11)	942(22)	254(4)	63(3)	112(2)	388(3)
Rahul Dravid	453(12)	504(16)	542(7)	662(21)	148(5)	1260(22)	-	560(10)	504(6)	475(7)
Mahela Jayawardene	1158(12)	314(10)	-	-	335(8)	294(7)	556(7)	304(7)	167(4)	137(2)
Sachin Tendulkar	414(11)	392(10)	386(9)	485(11)	306(5)	331(8)	-	820(9)	616(6)	199(4)
Matthew Hayden	862(18)	540(11)	381(7)	283(6)	681(14)	379(8)	61(2)	107(3)	501(3)	-
Kumar Sangakkara	790(12)	392(10)	-	-	452(8)	238(7)	592(7)	284(7)	255(4)	281(2)
Graeme Smith	-	-	88(3)	179(4)	717(12)	876(13)	408(4)	335(5)	162(2)	-
Virender Sehwag	924(11)	238(9)	547(7)	692(11)	286(5)	357(7)	-	176(6)	74(1)	102(3)
VVS Laxman	333(9)	330(9)	370(9)	494(11)	271(4)	731(15)	-	117(4)	31(2)	249(6)
Shivnarine Chanderpaul	820(15)	533(11)	130(4)	154(4)	-	-	108(2)	39(3)	73(3)	186(6)
Mohamamad Yousuf	96(3)	255(8)	285(12)	338(11)	665(5)	549(9)	227(4)	276(2)	-	222(3)
Brian Lara	793(15)	531(8)	299(3)	688(6)	-	-	173(2)	-	-	222(4)
Chris Gayle	814(20)	545(10)	164(7)	54(6)	-	-	221(3)	126(3)	46(3)	307(7)

The fact that Ponting played in a top class team meant that victories were assured more often than not and also meant he faced weaker attacks for much of the 2000s. He struggled in the subcontinent, but was very successful at home and in South Africa. The Pakistani attacks were far less potent away in the 2000s after the retirement of Wasim Akram and Waqar Younis. All this pointed to Ponting facing comparatively weaker attacks in fairly easy conditions which is quite clearly a blot on an otherwise superb decade. Kallis has faced fairly consistent attacks throughout. His run glut against the minnows does pull his average down. Rahul Dravid’s best performances usually came when the chips were down and he has been very prolific in almost all away conditions. A considerable proportion of his runs though, have been made against the weakened West Indies and the minnows. Jayawardene and Sangakkara have scored tons of tuns against Bangladesh home and away boosting their averages. They have hardly played and succeeded in Australia and South Africa though Sangakkara’s 192 at Hobart was one of the best innings of the decade. Sri Lanka’s awesome home record and ordinary away record is very evident from the less impressive showing of these two batsmen in away matches. Matthew Hayden resurrected his career on the 2000-01 tour of India and proceeded to amass 30 centuries at a rate only next to Bradman. He, like Ponting, played in a top team and faced ordinary attacks throughout. His away performance was definitely under par when compared to his home batting.

Tendulkar’s prolific recent run has seen him score at a Bradmanesque average and he recently registered his sixth double century. His records in the 2000s against Australia has been excellent but the lack of quality in the attack in recent years does pull down his performance a little. He has also aggregated plenty against the minnows home and away in the past decade. Sehwag and Laxman also average more than 50 in the 2000s. Sehwag has two triple hundreds and four double tons. The Chennai and Lahore efforts though came on very flat tracks and the innings against Sri Lanka in Mumbai was against a highly weakened attack. Laxman usually has reserved his best against the top teams and hardly ever makes massive scores against the lesser opponents which have ensured that his contributions are always valued highly.

Brian Lara played in a team accustomed to losing in the 2000s. Right from the remarkable 2001 tour of Sri Lanka where he scored 688 runs in 3 Tests only to lose 3-0, he has made runs home and away against all opponents. His average against Australia is 47 in matches involving McGrath. His otherwise ordinary showing against England is boosted by the unbeaten 400 in Antigua. His consistency was exceptional in the last 3-4 years as he scored hundreds against Pakistan and South Africa home and away. Chanderpaul’s case is similar as he has been part of a very weak outfit for much of this decade and has done brilliantly in losing causes.

Quality measure (bowling average of opposition and runs/wicket in match)- base value: 31.44

Batsman	Aus(h)	Aus(a/n)	Eng(h)	Eng(a/n)	Ind(h)	Ind(a/n)	NZ(h)	NZ(a/n)	Pak(h)	Pak(a/n)
Ricky Ponting	-	-	0.7602	0.8975	0.7362	0.9803	0.7495	0.6821	0.8298	1.2303
Jacques Kallis	1.0493	0.9353	0.9367	0.9295	0.9824	0.8805	0.9599	0.7748	0.9757	0.8589
Rahul Dravid*	0.9357	0.8458	0.9295	0.8048	-	-	0.5993	0.9980	0.7167	0.6545
Mahela Jayawardene	1.0799	1.0310	0.9034	0.9935	0.7756	0.8823	0.7634	1.1236	1.0553	0.8867
Sachin Tendulkar	0.9183	0.8893	0.8808	0.8072	-	-	0.7478	0.8450	0.8148	0.6840
Matthew Hayden	-	-	0.7555	0.9176	0.7055	0.9833	0.7476	0.7841	0.7949	1.1382
Kumar Sangakkara	1.0799	1.0465	0.9034	0.99135	0.7756	0.8823	0.7645	1.1236	1.0657	0.7290
Graeme Smith*	1.0679	0.9171	0.9308	0.8195	1.1856	0.8141	0.9921	0.7748	0.9756	0.8589
Virender Sehwag*	0.9356	0.8076	0.9390	0.7216	-	-	0.5994	0.9980	0.7741	0.6545
VVS Laxman	0.9584	0.8530	0.8513	0.7994	-	-	0.5994	0.9980	0.7899	0.6545
Shivnarine Chanderpaul	0.9517	1.1543	0.9722	1.0476	0.9237	1.0987	0.9347	1.0011	1.0465	1.0459
Mohammad Yousuf	-	1.1473	0.8558	0.9556	0.6944	0.7859	0.7107	0.9887	-	-
Brian Lara*	1.0891	1.2303	1.0850	1.2345	0.9250		1.0804	1.1582	1.0622	0.9080
Chris Gayle	0.8670	0.9263	0.8804	1.0749	0.9250	1.1637	1.0804	1.0527	1.1037	0.9351

Quality measure (bowling average of opposition and runs/wicket in match)- base value: 31.44

Batsman	SA(h)	SA(a/n)	SL(h)	SL(a/n)	WI(h)	WI(a/n)	Bang(h)	Bang(a/n)	Zim(h)	Zim(a/n)
Ricky Ponting	0.8006	0.9059	0.5873	0.9594	0.8462	0.7027	0.3539	0.5627	0.4184	-
Jacques Kallis	-	-	0.9848	1.1188	0.6881	0.8749	0.4910	0.5941	0.3962	0.3210
Rahul Dravid	1.0164	1.1325	0.6701	0.9353	0.8365	0.9240	-	0.6127	0.4725	0.8009
Mahela Jayawardene	0.8508	1.4016	-	-	0.8985	0.9608	0.4264	0.7099	0.5016	0.3336
Sachin Tendulkar	0.9096	1.1583	0.7320	0.7995	0.9168	0.9678	-	0.6139	0.4663	1.1030
Matthew Hayden	0.8052	0.8969	0.7573	0.9623	0.8646	0.6560	0.3533	0.5627	0.4184	-
Kumar Sangakkara	0.8508	1.4016	-	-	0.8985	0.9608	0.4273	0.7099	0.5016	0.3336
Graeme Smith	-	-	1.0559	1.0277	0.6880	0.6903	0.4772	0.6267	0.3970
Virender Sehwag	0.8245	1.1322	0.6957	0.8791	0.8366	0.8608	-	0.6407	0.9945	0.6754
VVS Laxman	0.9350	1.0955	0.7290	0.8358	0.8366	0.9271	-	0.6930	0.3630	0.8692
Shivnarine Chanderpaul	0.9740	1.0715	0.9560	1.6700	-	-	0.4079	0.7548	1.3315	0.8383
Mohammad Yousuf	0.8219	1.2829	1.0985	1.0370	0.7561	1.0519	0.5406	0.5872	-	0.8901
Brian Lara	1.0368	0.8171	0.8839	1.0385	-	-	0.4079	-	-	1.1129
Chris Gayle	1.0411	0.9132	0.9259	1.0385	-	-	0.4079	0.7548	1.3315	0.8383

** The quality value for Ponting and Hayden in the ICC World XI match is 1.2964.

The table below lists the effective averages of the top batsmen in the 2000s. Brian Lara is on top in terms of quality of innings played and Ricky Ponting and Matthew Hayden are at the bottom. This is not a method that questions the quality of a player, but merely an alternative to measure the average effectively.

Effective averages of top batsmen in 2000s

Batsman	Actual runs	Actual average	Effective runs	Effective average	Quality deviation
Brian Lara	6380	54.06	6572.1	55.69	1.0301
Shivnarine Chanderpaul	6735	53.03	6805.0	53.58	1.0103
Rahul Dravid	8904	53.63	8733.0	52.6	0.9807
Mohammad Yousuf	6633	56.21	5950.5	51.29	0.9124
Jacques Kallis	9277	59.08	8022.3	51.09	0.8647
Kumar Sangakkara	8016	56.85	6800.9	48.23	0.9112
Mahela Jayawardene	8475	55.39	7324.3	47.87	0.8642
Sachin Tendulkar	8399	57.13	6933.4	47.16	0.8295
Ricky Ponting	10158	57.38	8207.3	46.36	0.8079
VVS Laxman	6864	52.00	5920.4	44.85	0.8625
Virender Sehwag	7152	53.37	5838.1	43.56	0.8161
Matthew Hayden	8364	52.93	6803.6	43.06	0.7537
Graeme Smith	7170	50.49	5818.2	40.97	0.8114
Chris Gayle	6007	40.31	5758.6	38.64	0.9585

A similar approach yields an average of 85.23 for Bradman (three weak teams played considered minnows) and 51.45 for Gavaskar. The approach can be further modified to calculate period wise averages to understand the batting quality better. Gavaskar for example averages almost 83 with 10 centuries against the West Indies prior to 1980 when the bowling attack was not at its best, but only 41 after 1980 with just three hundreds in dull draws, in between falling seven times to Malcolm Marshall before crossing 20.

A more detailed approach analysing period wise performance and in matches involving particular bowlers will be taken up later.

In a recent post, the Test performance of all teams across the ages was analysed. Australia have proved to be the most consistent team with an outstanding win-loss record throughout. In this piece however, I decided to take a more detailed look at the batting, bowling and fielding records of all teams over the years which will help better to analyse the performance of teams. This analysis does not take various periods into consideration but instead the records across all years which is a fair indicator of team strength and performance. The period wise analysis provides a more detailed performance evaluation and will be taken up in a later post.

The first table lists the number of batsmen in each team possessing an average greater than 40. I have considered a minimum qualification of 3000 runs. England have played the most Tests and also have the most batsmen averaging over 40 followed closely by Australia. West Indies have fallen been ordinary over the last decade, but had dominated world cricket earlier for almost three decades. The fact that they have 19 batsmen averaging over 40 clearly indicates the quality of batting they possessed in those years. India’s batting has been at its best since the mid 1990s with five batsmen in the period averaging greater than 40. South Africa also have an impressive number of batsmen averaging over 40 since their return to international cricket. Andy Flower has an excellent Test record and is the only batsman from Zimbabwe to make the list.

Number of batsmen averaging over 40 (min qualification 3000 runs)

Team	No of batsmen	Best batsman (terms of average)	Highest average
England	26	Herbert Sutcliffe	60.73
Australia	25	Don Bradman	99.94
West Indies	19	Everton Weekes	58.61
India	12	Sachin Tendulkar	56.02
South Africa	9	Jacques Kallis	54.94
Pakistan	8	Javed Miandad	52.57
Sri Lanka	7	Kumar Sangakkara	56.85
New Zealand	2	Martin Crowe	45.36
Zimbabwe	1	Andy Flower	51.54

Dominant teams over the years have produced outstanding bowling attacks. West Indies in their heyday comfortably won in all conditions due to the presence of top class fast bowlers and the combination of Glenn McGrath and Shane Warne enabled Australia to rule world cricket in the late 1990s and 2000s. Australia, over the years have produced the finest bowlers consistently and their presence at the top of the table vindicates this. Alan Davidson had a fantastic average of 20.53 and among fast bowlers; McGrath and Dennis Lillee come closest. Among England bowlers, Sydney Barnes averaged a scarcely believable 16.43 picking up 189 wickets in just 27 Tests. But among bowlers who made their debut after 1990, only Darren Gough and Andy Caddick make the list.

West Indies through the 1970s to 1990s had a superb array of fast bowlers, each of them averaging below 30. Malcolm Marshall was the finest of them all, with a haul of 376 wickets at under 21. Pakistan’s fast bowling reserves have never been affected over the years and they have continued to churn out quality pace bowlers. Imran Khan was one of the world’s best bowlers in the early 1980s while Wasim Akram and Waqar Younis spearheaded the attack through the 1990s. India have had just four bowlers in the list, with Kapil Dev being the only fast bowler. Traditionally batting friendly tracks have undoubtedly been the reason behind the high averages of Indian bowlers. Allan Donald and Richard Hadlee have been the best bowlers for their respective teams. Muttiah Muralitharan holds virtually every record in the bowling department and it is no surprise he figures in the list as Sri Lanka’s best ever.

Number of bowlers averaging less than 30 (min qualification 150 wickets)

Team	No of bowlers	Best bowler (terms of average)	Best average
Australia	17	Alan Davidson	20.53
England	14	Sydney Barnes	16.43
West Indies	10	Malcolm Marshall	20.94
Pakistan	6	Imran Khan	22.81
South Africa	5	Allan Donald	22.25
India	4	Bishan Singh Bedi	28.71
New Zealand	2	Richard Hadlee	22.29
Sri Lanka	2	Muttiah Muralitharan	22.67
Zimbabwe	1	Heath Streak	28.14

The table below looks at the number of batsmen in each team who have more than ten Test centuries. England have 28 batsmen who have over 10 hundreds, but the highest number of centuries is just 22, scored by Geoff Boycott. Australia are next with 24, but have three batsmen over 30 centuries, with Ricky Ponting leading the way with 39. West Indies are next with Brian Lara on top with 34 centuries including 9 scores over 200. India and Pakistan have 12 players with over 10 centuries and Sachin Tendulkar and Inzamam-ul-Haq top the hundreds tally.

Number of batsmen with over 10 centuries in Tests

Team	No of batsmen	Batsman with most 100s	No of 100s
England	28	Geoff Boycott, Wally Hammond, Colin Cowdrey	22
Australia	24	Ricky Ponting	39
West Indies	16	Brian Lara	34
India	12	Sachin Tendulkar	48
Pakistan	12	Inzamam-ul-Haq	25
South Africa	8	Jacques Kallis	35
Sri Lanka	8	Mahela Jayawardene	28
New Zealand	3	Martin Crowe	17
Zimbabwe	1	Andy Flower	12

Shane Warne, with 37 five wicket hauls leads the list of 15 Australian bowlers with over ten five fors. Australia are followed by England, Pakistan and India. West Indies have three bowlers on top with 22 five fors which is further indication of how powerful their bowling attack was. Richard Hadlee is by far the finest New Zealand bowler with 36 five wicket hauls while Muttiah Muralitharan with 67 five fors is light years ahead of the next best by a Sri Lankan which is Chaminda Vaas with 12.

Number of bowlers with over 10 five fors in Tests

Team	No of bowlers	Bowler with most five fors	Most five fors
Australia	15	Shane Warne	37
England	10	Ian Botham	27
Pakistan	9	Wasim Akram	25
India	8	Anil Kumble	35
West Indies	7	Curtly Ambrose, Malcolm Marshall, Courtney Walsh	22
South Africa	5	Allan Donald	20
New Zealand	4	Richard Hadlee	36
Sri Lanka	2	Muttiah Muralitharan	67

The next two tables are related to wicket-keeping and fielding dismissals. England have the most keepers with 100 plus dismissals and the list is led by Alan Knott. Australia have had three of the finest keepers over the last three decades and Adam Gilchrist tops the list with 416 dismissals. Bert Oldfield of Australia, with 52 stumpings still holds the record for the most stumpings. Mark Boucher surpassed Gilchrist and is the world record holder with over 500 dismissals.

Number of wicket keepers with more than 100 dismissals

Team	No of wicket keepers	Keeper with most dismissals	No of dismissals
England	7	Alan Knott	269
Australia	6	Adam Gilchrist	416
West Indies	5	Jeff Dujon	270
Pakistan	5	Wasim Bari	228
India	4	Syed Kirmani	198
New Zealand	3	Adam Parore	201
South Africa	3	Mark Boucher	502
Sri Lanka	2	Kumar Sangakkara	144
Zimbabwe	1	Andy Flower	151

Australia have had a tradition of producing high class fielders, especially in the slip cordon. Bob Simpson, Greg Chappell, Mark Taylor and Mark Waugh have over a 100 catches with Mark Waugh leading the list. Ian Botham and Colin Cowdrey lead the list for England with 120 catches. Rahul Dravid overtook Mark Waugh’s tally and is closing in on 200 catches. Stephen Fleming and Mahela Jayawardene top the table for their respective teams.

Number of fielders with over 100 catches

Team	No of fielders	Fielder with most catches	Most catches
Australia	10	Mark Waugh	181
England	5	Ian Botham, Colin Cowdrey	120
India	5	Rahul Dravid	195
West Indies	4	Brian Lara	164
South Africa	2	Jacques Kallis	155
New Zealand	1	Stephen Fleming	171
Sri Lanka	1	Mahela Jaywardene	161

* The highest number of catches by a Pakistani is 94 by Javed Miandad

Another factor that determines a team’s dominance is the innings per hundred. Australia lead the way in this regard too with a century every 17 innings and have a fairly excellent away record too with a century every 18.45 innings. Sri Lanka, surprisingly are second with a century every 18 innings but this is mainly due to their extraordinary home record. They have a century every 14.5 innings in home Tests and an even more incredible hundred every nine innings against Bangladesh and Zimbabwe.

West Indies, between 1960 and 1990, had an outstanding record of a century every 17 innings, but have fallen away since then. India’s away performance has consistently improved over the years and they have scored a century every 16.2 innings since 2000 which is far better than their overall away record which stands at 20.7 innings per century. Bangladesh’s predicament is Tests can be clearly seen from the fact that the batsman score a hundred only every 66 innings, which is far too high to be able to compete.

Innings/hundred for teams

Team	Innings	100s	Inns per 100	HS	Batsman
Australia	12605	734	17.17	380	Matthew Hayden
Sri Lanka	3359	184	18.25	374	Mahela Jayawardene
West Indies	8200	432	18.98	400*	Brian Lara
India	7565	396	19.10	319	Virender Sehwag
Pakistan	6045	312	19.37	337	Hanif Mohammad
England	15652	766	20.43	364	Len Hutton
South Africa	6319	289	21.86	277	Graeme Smith
New Zealand	6569	218	30.13	299	Martin Crowe
Zimbabwe	1601	42	38.11	266	Dave Houghton
Bangladesh	1449	22	65.86	158*	Mohammed Ashraful

This is a simple analysis of the results of teams across ages. I have split the 133 year period into the following 8 ages.

PreWW1: 1877-1914
PreWW2: 1921-1939
1950s:  1946-1959
1960s:  1960-1969
1970s:  1970-1979
1980s:  1980-1989
1990s:  1990-1999
2000s:  2000-2010

A simple formula is used. Readers might find this a little simplistic but I am working with limited parameters to do justice to such a macroscopic analysis. My idea is to bring to light the teams which performed well during each period and then see how each team performed over the years since they made their debut in international cricket. Many of these insights might be obvious to some of the readers but this article is a single place compendium of team performances across the years. And the normal complaints of comparing players/teams across the ages do not arise in this analysis.

A win carries 2 points. A draw/tie will carry 1 point. The total points will be compiled during the concerned period. This is evaluated against the maximum points available for the team and a Performance % arrived at. There is also a need to recognize away performances. This is especially needed to break deadlocks. Take two teams which have played 10 matches each. Both win 5 matches and draw the remaining 5 matches. Both teams will have a 75% performance index. If team A won 3 away and 2 at home and the other team 2 away and 3 at home, Team A should be considered to have done slightly better. Hence I have provided 25% additional weight for away performances, that too, only for wins and draws. The actual weight given is less consequential than the fact that the away performances are recognized.

This is a simple analysis based on results. The relative team strengths or the series position or the win margins are not considered. That is a totally different type of analysis of Team Ratings.

Reg the Graphs. The first graph is the one covering all 1971 tests. This is across 133 years. This graph can be used to lead on to the other graphs. The Period graphs have been drawn in the order of teams' performances. I have also included the summary table for the period in the right as part of the graph for easier viewing and identification. At the end of the 8 period graphs, the graphs for the teams are drawn.

Australia leads the all-time table comfortably with a Performance value of 66.0%. England come next with 59.3%. It may be a surprise that Pakistan edges out West Indies for the third position. This has been a result of the recent fall from grace of the West Indian team. Again it is a surprise that Sri Lanka edges out India for the fifth place although it must be admitted that India has had a 50 year head start to put in some awful years earlier. This has also been made possible by Sri Lanka's strong showing during the 99 tests played during the 2000s. New Zealand is the only leading team to have an overall sub-50% index value.

The dominant team during 2000s has been the Australians with a Performance Index (PIdx) value of 84.6%. Even their recent wobble has only got them down a bit. They are still the team to beat. South Africa are next with 66.6% and then India with 63.9%. It is debatable whether India can maintain this ascendant graph over the next few years with the huge void which is going to be created. England, with its periodic high-level performances are in next and Sri Lanka, buoyed by their strong home record, complete the top-5. Pakistan comes in next despite their continuing problems and their inability to play at home. The next 4 teams each have significant daylight between themselves and the team ahead of them. One reason why the 2000s has seen a wider dispersion of the numbers are the increased number of decisive results (only 23.8% draws) and presence of two weak teams.

The dominant team during 1990s has again been the Australians with a PIdx value of 69.7%. They have not had the extent of domination they had during the last decade. South Africa are next clocking in at a very close 68.2%. Pakistan, with the lethal bowling attack and great batsmen, are next placed with a PIDx value of 65.0%. The West Indies, not be confused with today's hapless and dispirited team, were fourth placed at 56.8%. India completed the top-5 barely crossing 50%. Sri Lanka, England and New Zealand were closely bunched around the 45% mark and even Zimbabwe clocked in at a respectable 34%.

The interesting point in this period was the close bunching of the teams. The difference between the first and ninth team was a low 35% as compared to the 2000s where this difference is a whopping 74%. The other surprising feature is the low number of matches played by teams other than the Ashes rivals. There have also been a greater number of draws (35.7%).

It would not be a surprise to read the 1980s charts. The dominant team, by a mile, was the great West Indian team, with their quintet of outstanding pace bowlers and feared batting attack. They clock in at 81.2%. Next comes the Imran Khan controlled Pakistan with 61.9%. Now comes the Hadlee-inspired New Zealand with 58.0%. Australia is the only other team to have a 50+%. India's lack of match-winning players kept them in the lower half. England comes in next and finally the new entrants, Sri Lanka. This period witnessed 46.1% draws.

The 1970s was an interesting period. Packer and World Series happened. England, probably less affected by WSC than Australia and West Indies were the leading, if not dominant, team with PIdx value of 63.3%. They are followed by four teams with 50+ %, led by West Indies. India, no doubt bolstered by Gavaskar and the spinners, did not do too badly. New Zealand had only a 33.5% index value. A tweak had to be done for this decade. South Africa played 4 tests and won all these. The 100% index value is an anomaly and should be removed from the analysis. This has been done. No major impact, though.

The 1960s was very much a defensive era as evidenced by the single digit column of wins for four of the six teams. The three leading teams, West Indies, Australia and England were separated only at the decimal point level, that too only because West Indies had slightly better away results. The close bunching of teams during these two periods, 1960s and 1970s, is a reflection of the parity which existed between the teams. It is also caused by fewer decisive results 42.6% and 47.8%).

The post-war period of 40s/50s was probably much better than the later dreary period. Bradman was there to start with. His legacy was continued by strong players. Australia had an outstanding PIdx value of 78.3%. England also had a very good team and were second with 61.7%, very closely followed by the W-driven West Indies. Surprisingly, Pakistan the new entrants were the next team having a better than 50% record. This is probably the best entrance decade for any of the later entrants. One must also allow for the fact that the pitches were conducive to the great strength of Pakistan, their seam bowling. The draw % was around 35%.

The in-between Wars period was a two team period with Australia comfortably ahead of England. That England, despite Bradman, were only 7% behind Australia indicates the effective manner in which their strategies, starting with body-line, worked. The newcomers, India, New Zealand and West Indies propped up the table. There was a spurt in the draw % compared to the previous era, 37.1%.

There were only three teams before WW1. England were the comfortable leaders during this period, no doubt aided by their bowling attack, led by Barnes and Lohmann. Not to forget Hobbs and Sutcliffe. Only 17.9% of the matches were draws, no doubt contributed by the types of pitches.

Now for the team performance graphs, presented in a different format. I have used line graphs instead of the bar graphs since it is easier to follow the changes. Also the graphs are shown in a chronological sequence. There is no graph for Bangladesh which has had one decade nor for Zimbabwe which has had two decades. It is not possible to derive anything sensible without three decades.

Australia has maintained very steady performance levels throughout the 133 years. they are the only team never to have fallen below 50% in any of the periods. What is important is that Australia have topped in 4 out of the 8 periods, the PreWw2, 1940s-50s, 1990s and 2000s period.

Barring the 1980s and 1990s, England have always maintained a 60+ % level. That is a consistency which is comparable to that of Australia. They have led the table in two of the eight periods, the 1970s and the Pre-WW1 periods.

West Indies led the table during two periods, the 1960s and 1980s but have since fallen off drastically, especially during the past decade. Their 80+% can be compared only to the Australians of the 2000s. Compared to the awful 2000s even the average 1990s looks good.

India have had a poor start, understandable, and had a poor 1980s and barely acceptable 1990s. They recovered in the current decade although the huge chasm is in front of them. The day without the three gladiators at 3/4/5 is looming ahead. The bowling is another major concern. Where are the bowlers to take 20 wickets on good pitches?

Barring a slight dip in the current decade, South Africa have improved their figures every decade. Possibly the only team to do so. There is a caveat so far as South Africa are concerned. This has already been referred to in the period graph. They played 4 Tests during the 70s and won all. Since I did not want their graph to have an abrupt dip or spurt, I have allotted a notional % for this period. 1980s, of course, is excluded.

Pakistan started very well, dropped off, picked up very well again but again fell of during the current decade. Overall they have been quite good. Very understandable in view of the circumstances. We must feel for the talented Pakistanis. As they seem to come out of one problem, another one crops up. Maybe it is time for Imran Khan to come forward and run Pakistan cricket the way he ran his team.

New Zealand have been like the proverbial yo-yo. Down, up, down, up and so on.They had a golden 1980s when the kings were scattered around the tropical islands near Florida..

Sri Lanka have had only three decades and have been steadily improving a la South Africa. However the impressive thing is that their excellent performance of 61+% has been over the last 100 tests, more than a half of their tally.

To view the "Results Summary - By Periods" tables, please click here.

To view the "Results Summary - By Teams" tables, please click here.

An important announcement to the readers. I have created an open mailid to which the comments and suggestions, not meant for publication, can be submitted. The mail id is ananth.itfigures@gmail.com. Since the readers would have to use a mail route I give the readers my assurance that the mail id is safe and will never be used by me for anything other than communicating with the reader specifically. This will not be part of any group mail nor will mails be cc'd.

While the IPL’s idea of bringing in the world’s best players to play for various franchises deserves praise, World Series Cricket (WSC) envisioned by Kerry Packer in 1977 was a watershed moment in the game’s history. It was the first time that the world’s best players were roped in to play for three teams: WSC Australia, WSC West Indies and WSC World XI. Sadly, the huge upheaval that WSC caused has meant that the top quality cricket played in the two seasons is often forgotten.

The contests involved Test matches, known as ‘SuperTests’ and limited overs games. The WSC is renowned for many innovations, many of which are still in use in the modern game. The idea of day-night cricket, the use of the white ball and coloured clothing went a long way in popularising the game. The Test matches in particular, showcased some of the most compelling cricket pitting the world’s best batsmen against supreme fast bowlers. The first season in 1977-78 played in Australia saw WSC Australia play two three match series against the other two teams. The second season in 1978-79 featured a triangular Test series among the three teams in Australia and the latter half of the season saw a five match series between WSC Australia and the WSC West Indies in the Caribbean.

The performance of the three teams across the two seasons is summarised below. The World XI played fewer matches, but had a glittering array of stars including top batsmen Viv Richards, Barry Richards and Gordon Greenidge, a bowling attack featuring West Indian pacemen and the all rounder Imran Khan. Viv Richards and other West Indians also played for the WSC West Indies later in the season. The World XI was by far the best team then and this is clearly seen in their exceptional record of five wins in six matches.

Performance of three teams involved in World Series Cricket (SuperTests)

Team	Played	Won	Lost	Drawn
WSC Australia	15	4	7	4
WSC West Indies	11	3	4	4
WSC World XI	6	5	1	0

The table below shows the performance of top batsmen across the seasons of WSC. Viv Richards came into the World Series with great confidence, after having scored 1710 runs in 1976, which remained a Test record till 2006. He certainly lived up to his reputation scoring four centuries at an average of 64.05. The fact that this was achieved against the finest fast bowlers lends further weight to the fact that he was the best batsman in the world at that point. Barry Richards played just four Tests in his career, but his batting in WSC showed just what cricket had missed.

Greg Chappell vindicated his status as one of the best players of fast bowing and his tally of over 1400 runs at an average of 56.60 with five centuries put him in a league of his own. The bowling that he faced included the likes of Andy Roberts, Michael Holding, Joel Garner and Imran Khan. Many batsmen wilted in the face of hostile pace bowling and they averaged well below their overall Test averages. David Hookes, on the other hand, despite being fairly new to international cricket, performed superbly in World Series Cricket, but rather surprisingly turned out to be a failure in international cricket after the two years.

Performance of top batsmen in World Series Cricket

Batsman	Team	Matches	Innings	Runs	100	50	Average
Barry Richards	World XI	5	8	554	2	2	79.14
Vivian Richards	West Indies and World XI	14	25	1281	4	4	55.69
Greg Chappell	Australia	14	26	1415	5	4	56.60
David Hookes	Australia	12	22	769	1	7	38.45
Clive Lloyd	West Indies and World XI	13	21	683	1	3	37.94
Gordon Greenidge	West Indies and World XI	13	23	754	1	4	35.90
Ian Chappell	Australia	14	27	893	1	5	35.72

WSC was the most difficult test for batsmen due to incredible line up of pace bowlers present then. Many batsmen failed to perform at the end of the series and only a few were able to counter the aggressive bowling consistently. While the performance of Roberts, Holding, Lillee and Imran was more or less expected considering their reputation, the showing of the South African all-rounder Mike Procter and Garth le Roux was highly impressive. Dennis Lillee picked up the most wickets for Australia and was ably supported by Max Walker and later Jeff Thomson.

Performance of top bowlers in World Series Cricket

Bowler	Team	Matches	Wickets	Average	5	10
Garth Le Roux	World XI	3	17	15.88	2	0
Mike Procter	World XI	4	14	16.07	0	0
Imran Khan	World XI	5	25	20.84	0	0
Michael Holding	West Indies	9	35	23.31	1	0
Andy Roberts	West Indies and World XI	13	50	24.14	1	0
Joel Garner	West Indies and World XI	7	35	24.77	1	0
Max Walker	Australia	7	28	25.42	2	0
Dennis Lillee	Australia	14	67	26.86	4	0
Jeff Thomson	Australia	5	16	29.75	1	0

The table below compares the averages of batsmen prior to World Series Cricket and after it ended. Viv Richards entered the tournament in the best form of his career and was the top batsman across the two seasons. His average did fall a little later on in his career after the WSC. Greg Chappell, who reaffirmed his status as Australia's best batsman with superb performances during the WSC years was remarkably consistent in his performances even after WSC.

Gordon Greenidge played most of his Test cricket after the end of World Series cricket and his average in this period did not deviate much from his overall record. His performance in the WSC though dropped well below his career record. Zaheer Abbas had a much better period post the WSC, but he averaged only 34 prior to WSC. His performance across the two seasons also was not very good as he averaged below 30. Ian Chappell played majority of his career before the World Series, but his average during WSC fell well below his career mark. Clive Lloyd's average during WSC was poorer than his performances prior to and post the WSC years. Barry Richards’ career ended prematurely when South Africa were banned from International cricket, but his class was very much evident with his superb showing during WSC.

Performance of batsmen before and after World Series Cricket

Batsman	Matches before WSC	Average before WSC	Matches during WSC	Average during WSC	Matches after WSC	Average after WSC
Viv Richards	26	56.69	14	55.69	93	48.32
Greg Chappell	51	53.20	14	56.60	36	54.78
Gordon Greenidge	17	47.18	13	35.90	89	43.82
Zaheer Abbas	26	34.41	4	30.57	49	45.02
Clive Lloyd	63	43.35	13	37.94	45	52.16
Ian Chappell	72	42.86	14	35.72	3	31.60
Barry Richards	4	72.57	5	79.14	-	-

Further proof that the mainstream Australian and West Indian teams badly missed their best players who were participating in the World Series can be seen by comparing their performance before, during and after the WSC period. The Australian team’s performance went down drastically in the WSC years when they were trounced 5-1 by England and squeezed a 3-2 win over India. Only after majority of the players got back into the main side did the team start performing consistently again. West Indies on the other hand were getting to be a top side in 1976 after their impressive win over England, but during the WSC, their performance was ordinary. After the WSC though, they were the best side in the world by a distance as their win-loss ratio indicates.

Performance of Australia and West Indies in the non WSC years and WSC years

Team	Matches before WSC years (four years)	Win-Loss ratio before WSC years	Matches played during WSC years	Win-Loss ratio during WSC years	Matches after WSC years (four years)	Win-Loss ratio after WSC years
Australia	33	2.28	18	0.54	45	0.81
West Indies	32	1.20	11	1.50	25	4.00

World Series Cricket, apart from benefiting the game in general with all the innovations and improved salaries for players, featured some of the toughest contests ever seen. Despite the Tests never being accorded official status, the performance of the players during WSC is one of the surest ways to measure quality.

Ah! I fooled you, didn't I. You must have thought that I have sent an article meant for Fortune or Forbes magazine by mistake to Cricinfo. First let us put that matter to rest. The richest team must be the Indian team which collectively must be earning more than the rest of the teams together. Not that I care two cents about what the players earn. By "richest team" I mean, cricketing riches, in other words, the sum total of matches, runs and wickets which the team members take on to the field. It is also a lighter piece, coming in the wake of some serious and heavy analysis which have been done by me recently.

When a match is being telecast, the broadcasters talk about the experience behind a team in terms of matches played. However the real measures in this aspect are the number of runs scored and wickets captured by the concerned players.

I had done a sub-set of this article for another blog. I used the career figures. As I finished the article I realized that the career-to-date figures are the more appropriate figures to be used. So I applied the career-to-date figures, expanded the scope to matches also and have come out with a more comprehensive article here.

Since it usually happens that these analyses develop further based on user comments, I have done a simple accumulation of career-to-date figures of all 11 players. It certainly will give us some insight into the richness of teams in terms of the aggregates. I could look at the following options in later articles. I would also like the readers to come in with their own takes on these numbers and how these could be interpreted.

- Adding only the runs of the first 7 batsmen
- Add only for career-to-date runs greater than a certain value
- Add the wickets for the best 5 bowlers
- Do a comparison of the two team aggregates and analyse the most matched or ill-matched pairings.

I am aware that these are quantitative measures and not performance oriented. However there is no substitute for experience as the Indian batsmen showed at Dambulla against a New Zealand attack, which can at best be termed good and effective. It must be understood that the aggregates normally keep on increasing for a team but take a dip when senior player(s) retire.

The other thing I have done is not to show the top-10 accumulations. That would be quite silly on my part since the same team is likely to occupy the top-10 positions in terms of aggregates. Instead I have taken the top 8 teams + ICC XI and found the best for each of these teams and then ordered the tables accordingly. The other key feature is that I have taken the first innings figures. In other words, the test-beginning values. The second innings values would be higher, but this is a very minor matter.

Let us look at the tables. I have also provided the relevant details for the players who played in the particular innings for the top 3 teams. The support files provide the complete data.

Top teams based on number of Tests played

2008 1887 India           861 vs Aus
          Gambhir G            18
          Sehwag V             61
          Dravid R            126
          Tendulkar S.R       151
          Laxman V.V.S         97
          Ganguly S.C         110
          Dhoni M.S            30
          Harbhajan Singh      70
          Zaheer Khan          57
          Kumble A            131
          Sharma I             10
2005 1768 ICC XI          818 vs Aus
          Smith G.C            40
          Sehwag V             37
          Dravid R             92
          Lara B.C            118
          Kallis J.H           94
          Inzamam-ul-Haq      102
          Flintoff A           53
          Boucher M.V          85
          Vettori D.L          65
          Harmison S.J         36
          Muralitharan M       96
2006 1819 Australia       811 vs Eng
          Langer J.L          102
          Hayden M.L           86
          Ponting R.T         107
          Martyn D.R           67
          Hussey M.E.K         13
          Clarke M.J           24
          Gilchrist A.C        87
          Warne S.K           142
          Lee B                56
          Clark S.R             6
          McGrath G.D         121

2008 1860 South Africa    707 vs Win
1991 1170 West Indies     701 vs Aus
2007 1845 Sri Lanka       614 vs Aus
2001 1532 England         542 vs Slk
1999 1443 Pakistan        504 vs Ind
2006 1822 New Zealand     415 vs Slk

All 11 players are shown.

The 2008 Indian team against Australia carried on to the field the collective tally of 861 matches. Kumble and Ganguly, with their 100+ Tests were the main contributors for this huge totals. Both were coming to the end of their careers.

Not so surprisingly the ICC XI comes in next with 818 collective Test appearances. Let me mention at this point that the ICC-Aus Test is official as determined by ICC. At no time would I ignore the match, as a few readers have suggested earlier. Flintoff's wickets were against a quality Australian batting line-up and Hayden's runs were scored against a quality ICC bowling attack.

Australia's 2006 team comes in next, just behind the ICC aggregate.

To download the complete all-time list, please right-click here and save the file.

Top teams based on number of career-to-date runs scored

2005 1768 ICC XI        49141 vs Aus
          Smith G.C            3441
          Sehwag V             3181
          Dravid R             7871
          Lara B.C            10818
          Kallis J.H           7337
          Inzamam-ul-Haq       7620
          Flintoff A           2641
          Boucher M.V          3007
          Vettori D.L          1855
          Harmison S.J          347
          Muralitharan M       1023
2010 1964 India         47232 vs Slk
          Gambhir G            2798
          Sehwag V             6691
          Dravid R            11395
          Tendulkar S.R       13447
          Laxman V.V.S         7136
          Yuvraj Singh         1582
          Dhoni M.S            2428
          Harbhajan Singh      1585
2006 1819 Australia     40682 vs Eng
          Langer J.L           7575
          Hayden M.L           7385
          Ponting R.T          9044
          Martyn D.R           4390
          Hussey M.E.K         1225
          Clarke M.J           1179
          Gilchrist A.C        5124
          Warne S.K            2975
          Lee B                1076
          McGrath G.D           639

2010 1962 South Africa  35736 vs Win
1991 1170 West Indies   35090 vs Aus
2010 1964 Sri Lanka     27925 vs Ind
2001 1532 England       27585 vs Slk
2007 1830 Pakistan      25303 vs Saf
2004 1721 New Zealand   20312 vs Aus

Only career-to-date runs exceeding 250 are shown.

The ICC XI tops in batting aggregate. No surprise considering that they had Lara, Kallis, Inzamam and Kallis. If Tendulkar had come in for one of the later three batsmen, the tally would have been still higher. The high run values of Vettori, Flintoff and Boucher have helped the ICC XI>

India's team for the first Test against Sri Lanka clocks in next. The problem has been the low run values for the last three batsmen, Ishant, Ojha and Mithun contributing 180 runs. Even this total drops off drastically in the next two Tests.

Some distance behind in third place is the Australian team of 2006, clocking in at 40682 runs. After this match slowly the top Australian batsmen started going off.

To download the complete all-time list, please right-click here and save the file.

Top teams based on number of career-to-date wickets captured

2006 1780 Australia      1574 vs Saf
          Warne S.K           657
          Lee B               188
          MacGill S.C.G       178
          McGrath G.D         539
2007 1851 Sri Lanka      1290 vs Eng
          Jayasuriya S.T       97
          Vaas WPUJC          320
          Fernando C.R.D       80
          Malinga L.S          85
          Muralitharan M      704
2005 1768 ICC XI         1246 vs Aus
          Kallis J.H          183
          Flintoff A          143
          Vettori D.L         207
          Harmison S.J        138
          Muralitharan M      563

2008 1887 India          1209 vs Aus
2008 1860 South Africa   1177 vs Win
2000 1497 Pakistan        985 vs Win
2000 1506 West Indies     972 vs Eng
1982 0920 England         847 vs Ind
1989 1116 New Zealand     684 vs Pak

Only career-to-date wicket values of above 10 are shown.

Another Australian team of 2006 has the next wicket aggregate, 1574 wickets. This team's attack was led by Warne and McGrath and well supported by MacGill and Lee.

With Muralitharan contributing over half, Vaas nearly a quarter, the Sri Lankan attack of 2007 is in second place with 1290 wickets, way, way behind the Australian attack, which looks like it will not be surpassed for a very long times.

The ICC XI attack, not necessarily the best one at that time, is in third position. I have forgotten the match. However since Kumble had 464 wickets at that stage, a replacement of Vettori by Kumble would have moved them way up.

To download the complete all-time list, please right-click here and save the file.

It can clearly be seen that the experience in terms of matches, runs and wickets, are the cornerstone for success. The top teams shown above have all been very successful, ignoring the hotch-potch ICC XI. I will later do a correlation between the experience factor and the results, especially when there is a significant dip in the numbers, as happened with Australia last year.

Sriram, my in-house Editor has correctly mentioned that I have left the article short and it does not have any analytical conclusions. He is perfectly right. There are two reasons. One is that I wanted to get the reader comments/suggestions and come with a meaningful concluding article. The other is that I have to say something important here.

A regular reader has stated that he will not be visiting this site and stated three reasons. The first is a coloured-glass narrow-minded view on my being India-centric which needs no further look in. However there are two other reasons mentioned which need a response and that too, to the readers, since it concerns them also.

He has said that he will not participate in discussions in this blog because

1. I am not a mathematician/statistician and "only" an IT person. and
2. I have not played cricket.

Both perfectly true. Impeccable statements of 100% veracity. So let me say something on these.

I am proud that I am an Engineer/IT Person/Analyst. Foremost, I love the game, in all its areas, the play, the players, the prose, the analysis and the debates. Without this omnipresent love for the game, it does not matter who one is, one cannot do anything which will carry a very high degree of conviction leading to acceptance. I may not understand Chi-squared methodology or Gini adjustment or the philosophy behind stochastic processes. But I know when a 153 is better than a 400 or when a 2-wicket haul is superior to a 5-wicket haul or under what match conditions would a 50 made at no.7 be far superior to a 150 at no.1 and so on.

When I look at Cricinfo's wonderful analytical brain-bank, what do I see, an MBA, an Engineer, an MS from Kansas and so on. There might certainly be a statistician/mathematician or two there also. However they would be there, not just for their academic qualifications, but for their love of cricket and the ability to weave excellent articles around the dull and dreary numbers.

Let me take the recent theoretical study undertaken by two academicians which is currently doing the rounds. I will not make a single comment on the merits or demerits of this analysis. I may do that at a later date or someone from Cricinfo might do that. I downloaded the article and spent an hour trying to understand the same. I am sorry, I failed. Cricketing statements are interspersed with obscure (for the common man) statistical statements. The numbers do not make sense immediately since these are derived based on complex statistical processes. In other words, this article, possibly great in its own sphere, is not meant for the common man, but for other academics. The reader is expected to accept the findings even if he/she does not understand the basis.

To download the above referenced article, please right-click here and save the file.

I do not work that way. Every one of my articles has to be read and understood by all the readers, none excepted. If they do not understand something, it is my duty to explain. If they point out an error, it is my duty to correct the same. If they suggest something better, it is my duty to incorporate the same or explain why I have not done so. That is the way I have worked for the past two years and will continue to do so. If my articles do not sound technical and complicated enough for the segments of the academic readers, not all, let me add, so be it. I am proud of what I do and more proud of my own rapport with the readers, despite the many arguments I have had with them. And if ever I deviate from these self-imposed principles, send an immediate electronic brickbat.

Also if a reader suggest something unusual, as Soundararajan from Stanford who has suggested the factor, h-index. I have studied the same and am amazed at the simplicity and effectiveness of the same. I am in touch with Soundar to work out how it can be done effectively. At the same time, another reader, Murali, suggested a Gaussian distribution analysis on the top bowler tables. Since I do not understand the methodology completely I have requested him to do the work himself and offered to publish the results. The bottom line is that this is not a scientific journal but a blog, open to all.

Now for the second shortcoming I have. That I have not played any cricket. Eminently true. My highest score is 18 not-out, coming in at no.11, in a school match, played with tennis balls. Although I must add that this score was out of 50 for 9, and we won the match. Coming in at 28 for 9, I closed my eyes, swished and swished, and was incredibly lucky. So I have played no cricket.

Does it make me ineligible to write on or analyse the game. Even though I cannot last 6 balls against Sehwag bowling blind-folded and left-handed, that does not prevent me from understanding the value of his sub-100 innings at Chennai or Dambulla. If this is correct, most of the writers and analysts would have to stop doing what they are doing. Pauline Kael or Roger Ebert or James Agee did not act in films to write on films. Nirmal Shekhar, arguably the best Indian tennis correspondent, probably has not played tennis and so on.

Looking at the other side, a number of past players make good commentators, far fewer players can write and only very few are good analysts. I have worked with quite a few past cricketers and barring two leg-spinners, one very successful and the other, not-so-successful, the others could not understand even the rudiments of cricket analysis.

I apologise if I have gone on. However it needed to be said.

Winning a Test against Sri Lanka in Sri Lanka is one of the toughest tasks going around, but beating them in a home venue after losing the toss is perhaps the toughest task in international cricket. In April next year, the island will celebrate a decade of never having lost a home Test in which they’ve won the toss. An awesome stat for them, and a scary one for all opponents.

The table below lists the records of all teams after winning tosses in home games, and none is as imposing as the Sri Lankans. In 19 matches before the ongoing one in Colombo, they’d won 15 and drawn four. Their preferred method has been, as you’d expect, bat first and knock the stuffing out of the opposition – they’ve done that 11 times. And on six of the seven occasions when they’ve fielded, the opponents have been Bangladesh – so the move was probably to ensure an early finish to the match. None of the other sides have a record which is as dominant, though Pakistan haven’t lost any of ten Tests either. (To see how these teams perform when they lose the toss, click here.)

The last team to achieve the near-impossible feat of losing the toss and winning the match against Sri Lanka in Sri Lanka was England, in that acrimonious series in 2001, when they edged past the home team by four wickets at the SSC. On the basis of what has been witnessed in the first two sessions of the current match at the SSC, it can safely be said that MS Dhoni’s team won’t repeat that feat over the next four days.

Win-loss ratios of teams in Tests at home after winning toss since April 2001

Team	Matches	Win/loss	Draw	W/L ratio	Bat ave	Bowl ave
Sri Lanka	19	15/ 0	4	-	50.37	22.79
Pakistan	10	5/ 0	5	-	48.56	37.21
Australia	24	20/ 3	1	6.67	47.44	28.52
England	30	19/ 3	8	6.33	42.33	29.41
India	20	9/ 2	9	4.50	43.38	33.21
South Africa	24	14/ 7	3	2.00	37.20	29.87
New Zealand	21	9/ 5	7	1.80	31.69	30.12
West Indies	24	5/ 11	8	0.45	32.85	35.59
Zimbabwe	13	3/ 7	3	0.42	28.99	36.64
Bangladesh	20	1/ 18	1	0.05	23.87	46.30

Malcolm Marshall: 32 wickets in five Tests a an average of 17.18 © Getty Images

An intriguing title to an article radically different from my normal analytical efforts. I can assure the readers that they would not be disappointed.

During early 1990s we had developed a series of complex and unique Test and ODI simulation systems. We had simulated for Sportstar a ODI World Cup. We had also conducted an inter-school tournament between the top schools letting the children captain various teams. Also we had done some innovative pre-match simulation of the matches during the 1999 World Cup.

During 2002, I undertook a very different and unusual exercise with Times of London, in conjunction with Wisden On-line. This was to simulate a series of 5 Tests between an all-time England XI and all-time World XI. For various logical reasons we restricted ourselves to the post-war players. These matches were to be played at Lord's, Bridgetown, Cape Town, SCG and Calcutta. The two teams were selected by Christopher Martin-Jenkins with inputs from us. The actual simulation was done in Bangalore over a few days. The results were published in London times, with comments by Steven Lynch, between 26 July 2002 and 3 August 2002.

Since most readers might not have seen these articles, I felt I ought to do an article on this unique exercise. In the first part I talked about the simulation methodology and the teams which were selected. In the second part I will cover the actual "Test" match scores and the original match reports as sent by us to London Times. I am sure the readers would find these worthwhile to peruse.

In the first part, I had laid the foundation of this unique Test series. In this follow-up article I have given the scorecards and match reports.

First Test: played at Lord's, London (ROW won by six wickets)

England Post-war XI: First  innings - 
  292 (Hutton 129*, May 89, Marshall 5/46)
R O W   Post-war XI: First  innings - 
  440 (V Richards 85, Lara 75, Tendulkar 59, Gichrist 95*, Statham 4/86, Underwood 4/84)
England Post-war XI: Second innings - 
  302 (Hutton 136, Cowdrey 63, Warne 5/84, Muralitharan 4/74)
R O W   Post-war XI: Second innings - 
  156/4 (Gavaskar 57*)

To view the scanned scorecard properly, please right-click here and download the file.

Viewing on the browser may not be clear since most browsers reduce the picture sizes. This applies to all jpg files. It is suggested that readers download the files and peruse at leisure.

To view the scanned match report properly, please right-click here and download the file.

Alternately, to view the match report in browser-friendly html format, please click here.

Second Test: played at Bridgetown, Barbados (England won by 43 runs)

England Post-war XI: First  innings
  308 (May 92*, Botham 73, Marshall 4/67, Lillee 4/79)
R O W   Post-war XI: First  innings
  339 (V Richards 103, Lara 50, Trueman 3/70, Statham 4/60)  
England Post-war XI: Second innings
  299 (Botham 101*, Dexter 46, Marshall 6/81)
R O W   Post-war XI: Second innings
  223 (B Richards 62, Sobers 53*, Trueman 3/46, Statham 4/57).

To view the scanned scorecard properly, please right-click here and download the file. Viewing on the browser may not be clear since most browsers reduce the picture sizes.

To view the scanned match report properly, please right-click here and download the file.

Alternately, to view the match report in browser-friendly html format, please click here.

Third Test: played at Cape town, South Africa (ROW won by 55 runs)

R O W   Post-war XI: First  innings
  485 (Gavaskar 145, Lara 75, Sobers 89*, Gilchrist 66)
England Post-war XI: First  innings
  150 (Hutton 48, Marshall 4/30, Warne 5/35) 
R O W   Post-war XI: Second innings
  150 for 3 decl (Gavaskar 57*)
England Post-war XI: Second innings\
  430 (Hutton 113, Gooch 104, May 64, Muralitharan 5/118).

To view the scanned scorecard properly, please right-click here and download the file. Viewing on the browser may not be clear since most browsers reduce the picture sizes.

To view the scanned match report properly, please right-click here and download the file.

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Fourth Test: played at SCG, Sydney (England won by 5 wickets)

R O W   Post-war XI: First  innings
  242 (B Richards 72, V Richards 74, Underwood 3/34, Laker 3/26)
England Post-war XI: First  innings
  429 (Hutton 182, Dexter 82, May 69, Murali 5.91, Warne 4/91)
R O W   Post-war XI: Second innings
  261 (B Richards 53, Lara 84, Botham 4/74)
England Post-war XI: Second innings
  76 for 5 (Marshall 5/33).

To view the scanned scorecard properly, please right-click here and download the file. Viewing on the browser may not be clear since most browsers reduce the picture sizes. Pl note that this scanning has been done off the original newspaper.

To view the scanned match report properly, please right-click here and download the file.

Alternately, to view the match report in browser-friendly html format, please click here.

Fifth Test: played at Calcutta, India (ROW won by an innings and 52 runs)

England Post-war XI: First  innings
   282 (Dexter 132, Marshall 3/56, Lillee 3/66, Sobers 3/64)
R O W   Post-war XI: First  innings
   616 for 4 decl (Tendulkar 200*, Lara 106, Sobers 102*)
England Post-war XI: Second innings
   282 (Hutton 56, May 102, Marshall 3/71, Muralitharan 3/40).

To view the scanned scorecard properly, please right-click here and download the file. Viewing on the browser may not be clear since most browsers reduce the picture sizes.

To view the scanned match report properly, please right-click here and download the file.

Alternately, to view the match report in browser-friendly html format, please click here.

In addition to the five Test series, a one-off "Test" was played between the team selected by a lucky reader (P.J.Mickleburgh) and an eleven selected by Christopher Martin-Jenkins.

To view the scanned scorecard properly, please right-click here and download the file. Viewing on the browser may not be clear since most browsers reduce the picture sizes.

A statistical summary:

Runs scored:      Hutton scored 744 runs.
Batting average:  Hutton's average was a Bradman-like 93.0.
Wickets captured: Marshall captured 32 wickets.
Bowling average:  Marshall's bowling average was a miserly 17.18.
Hundreds:         Hutton scored 4 hundreds.
Four-wkt hauls:   Marshall had 5 four-wkt hauls.
Highest score:    Tendulkar's unbeaten 200 in the last Test.
Best bowling:     Marshall's 6 for 81 although his devastating
                  spell of 5 for 33 when England needed only 76 to win 
                  probably the bowling performance of the series.

Summing up this has been a Hutton-Marshall dominated series.

To view all five scorecards/simulation reports, please click/right-click here and view/download the file. Viewing on the browser may be fine since this is only a MS Word file.

Download this document and read the simulation reports at leisure. You will get a clear insight into the rationale behind the game development and the way it is played. Do not miss the last bit of the fourth Test where England chases 76 to win and almost comes a cropper due to wrong strategy adopted by the simulation captain.

Many readers have expressed their surprise at the non-inclusion of Barrington. If the readers peruse the simulation reports carefully, they will notice this sentiment expressed in more than one place. I myself was quite surprised at the preference of Cowdrey, no more than competent, to Barrington, among the best of defensive batsmen.

The final image. To view the scanned Player selection report of CM-J properly, please right-click here and download the file. Viewing on the browser may not be clear since most browsers reduce the picture sizes.

Truly this was a series for the Gods. If these teams were made into all-time XIs, Bradman, Barnes SF and Hammond might have replaced B Richards, Statham and Cowdrey. My hunch is that that team, immeasurably strengthened with the arrival of the great man himself, would probably win 4-1. Possibly not. Who knows, Barnes was well-nigh unplayable on many pitches and Hammond has a 14-run lead over Cowdrey.

Even in this series the presence of Barrington might (or might not) have tilted the scales. Readers must remember that if Barrington was playing, the role-playing captains might have attempted alternate strategies.

A few people have asked whether some simulation exercise can be done now. Unfortunately the programs were kept in cold storage in 2002. The database was also a manually created one since I was not able to link the simulation with my established and dynamic database in 2002, mainly because of time constraints. That exercise is a massive one, as also the one of fine tuning the simulation to fit in with today's 75+% result and 3.5+ rpo Test environment. I promise I will do it one day. At least let me see whether I can wake the Simulation suite of programs from their Rip van Winkle-like slumber.

Again let me re-assure the readers that this is not an attempt to plug any of our company products since I have nothing to sell, no products, no services, nothing !!! I have been driven by nostalgia and the need to share unique experiences with enlightened readers.

An intriguing title to an article radically different from my normal analytical efforts. I can assure the readers that they would not be disappointed.

During early 1990s we had developed a series of complex and unique Test and ODI simulation systems. We had simulated for Sportstar an ODI World Cup. We had also conducted an inter-school tournament between the top schools, letting the children captain various teams. Also we had done some innovative pre-match simulation of the matches during the 1999 World Cup.

During 2002, I undertook a very different and unusual exercise with Times of London, in conjunction with Wisden Online. This was to simulate a series of 5 Tests between an all-time England XI and all-time World XI. For various logical reasons we restricted ourselves to the post-war players. These matches were to be played at Lord's, SCG, Bridgetown, Cape Town and Calcutta. The two teams were selected by Christopher Martin-Jenkins with inputs from us. The actual simulation was done in Bangalore over a few days.

The results were published in London Times, with comments by Steven Lynch, between 26 July 2002 and 3 August 2002. The published scorecards will be scanned and shown in the next article.

Since most readers might not have seen these articles, I felt I ought to do an article on this unique exercise. In the first part I will talk about the simulation methodology and the teams which were selected. In the second part I will cover the actual "Test" match scores and the original match reports as sent by us to London Times. I am sure the readers would find these worthwhile to peruse.

SIMULATION METHODOLOGY:

1. Player Data:

The actual career data of the player concerned is used. The following figures are part of the Player data. Readers should remember that I have lot more data available now than during 2002.

- No of Tests
- Career years span
- Type of batsman (Opening/EMO/LMO/Tail) 
- Runs scored
- Batting average
- Highest score
- No of 100s & overall pattern of 100s
- Catches/Stumpings
- Type of bowler (Fast/FM/M/SLA/OB/LBG/LAC)
- No of balls bowled
- Runs conceded
- Wickets taken
- Bowling average
- Bowling RPO
- Bowling strike rate.

Certain other data is derived from the player career figures and perusal of scorecards. The derived data explained below.

- Innings Size index: The ability of the player to play long innings. Bradman and Zaheer (and now Lara/Sehwag) converted most of their 100s into big scores. Not Lamb, Mark Waugh or M.Amarnath.
- Expected balls per innings: The average number of balls expected to be faced by the player. Highest is Bradman with 175 balls.
- Expected runs per ball: Ranges from .75 for Jessop/Gilchrist to .2 for strokeless wonders. Product of above two generally works out to the Career average.
- Strokeplay index: How far can the batsman be moved into attacking situations. Ranges from 6 for Bradman/Jessop to 1 for C'Shekhar/Malcolm.
- Defensive index: How far can the batsman be moved into match saving situations. Ranges from 5 for Gavaskar/Atherton to 1 for C'Shekhar/Malcolm.
- Bad wicket technique: High for Hobbs/Gavaskar and low for Srikkanth/Smith.
- Adjustment factor: Provide for Trumper et al scoring runs on uncovered wickets.
- Fielding index: Gives an indication of the quality of players' ground fielding. Highest index is 5 for Constantine/Bland/Randall and Rhodes.
- Bowling type: Type of bowler – Attacking, Normal or Defensive.
- Variation index: Ability to vary the deliveries. Hadlee/Grimmett/Warne high.
- Effectivity index: Ability to use atmospheric conditions for Fast/Medium bowlers and ability to flight for spinners. Prasanna/Murali high and Emburey low.
- Fielding: Team's Run-saving based on Fielding Index. Catching ability on average catches per match (Hammond/Solkar/Mark Waugh fairly high).

2. Ground Data :

Around the world, all test playing grounds including Sharjah have been included. Each ground has 6 index values.

- The support to Fast Bowlers (On a scale of 1 to 5)
- The support to Medium Pace Bowlers (On a scale of 1 to 5)
- The support to Spin Bowlers (On a scale of 1 to 5)
- A Run-Index for the ground (On a scale of 5 to 25). These have been built based on an article which appeared in Sportstar during the early 90s and have been updated since.
- Rain Index : Ranges from 5 for Manchester (almost every match will be affected by rain) to Sydney (almost always sunny).
- Close of play Index : Ranges from 4 for UK Grounds (Good chance of 2 Hours after Close of Play) to 1 for Calcutta (virtually no chance of extension of play). This factor has an impact on the number of overs bowled during the day.

3. Current Form :

This is randomised by the Computer for each player. The form index ranges from 4 (In Great form) to 1 (In poor form). Each block of 50 balls safely negotiated by the player will improve his form. The captain has to take into account the form and shepherd his players through poor form phases.

4. Rain

Rain is an integral part of the game, especially if a match is played at Manchester, Galle or Port of Spain. The concept of rain is built into the game depending on the ground rain index. Complex calculations determine the occurrence and duration of rain. It is also possible that matches take place without any occurrence of rain.

5. Simulation :

The match is, in reality, between two external captains who have at their disposal the players as resources. They are responsible for all actions including team selection, batting orders, strategies and fine tuning of plays.

The simulation is a complex process. Each ball is a mini-match and the complete match consists of x such mini-matches. For each ball, a total of no less than 30 randomising decisions are taken to decide on the outcome of ball. Some of the factors depend on the quality of the players involved, some on the match situation and some on the decisions taken by the two non-playing captains. These are briefly described below.

- The characteristics of the batsman who is batting. 13 factors are used.
- His form at the start of innings.
- How long has he been batting. Form improves as he settles down but he will get tired.
- The characteristics of the bowler who bowls the ball. 11 factors are used.
- What is the bowler type (See note below).
- His form at the start of the innings.
- How long is his current spell, breaks taken care of. Fast bowlers lose some effectiveness after 10, Medium after 15 and Spinners after 20 overs. - What is the condition of the ball, how old is the same.
- What is the time of day. Early mornings will favour seamers.
- Ground characteristics, both in terms of support to bowler type and run getting index.
- What is the average of the fielding index of the team. This will have an impact on the runs taken by the batsman.
- What is the average of the catching index of the team. This will have a slight impact on the wicket falling scenario.
- What is the bowling strategy. The fielding captain will be allowed to select one of 8 bowling strategies (ranging from completely wicket-taking (8 fielders near the bat) all-out defence (all at the boundary)) for both the bowlers. He/she has to take into account the match situation, ball situation, bowler bowling the current over and the specific skills of the batsman. The strategies can vary between the two bowlers. These can be changed at any time.
- What is the batting strategy. The batting captain will be allowed to select one of 5 batting strategies (ranging from all-out attack to all-out defence) for both the batsmen. He/she has to take into account the match situation, ball situation, bowler bowling the current over and the specific skills of the batsman. Nothing will be gained by asking Atherton to attack or Jessop to defend. The strategies can vary between the two batsmen. These can be changed at any time.
- What is the innings status. A number of factors are used in this.
- Is there a Run control option in force. This is mainly to let a senior batsman control the strike when batting with a tail-ender. Runs will be declined during early part of the over and odd number of runs will be attempted during later part.

Note: Only Sobers has bowled at the top level with equal effectiveness as a seam bowler and a spinner. So only for Sobers will the captain be asked at the beginning of each over as to what type of bowling he wants Sobers to do.

The Captain, whose role is a combination of on-field captain and off-field coach, has to use his resources very effectively. He should make his bowling changes with care, give his bowlers required rest, plan his strategies sharply, decide on how to optimise the resources at his disposal, especially outstanding resources such as Bradman et al.

6. Teams selected:

The two teams which were selected are given below. Since each team had two outstanding fast bowlers, two great spinners and a top all-rounder, it was decided that the same team would play in all 5 locations.

All-time Post-war England XI

    Hutton
    Gooch
    Dexter
    May
    Cowdrey
    Botham
    Knott (wk)
    Laker
    Underwood
    Trueman
    Statham
    12th man: Randall

All-time Post-war World XI

    Gavaskar
    Richards B A
    Richards I V A
    Lara
    Tendulkar
    Sobers
    Gilchrist (wk)
    Warne
    Marshall
    Muralitharan
    Lillee
    12th man: Rhodes

It is gratifying to see that the World XI is a time-less one in that if I were to select one today, I may not make a single change. Ponting for Barry Richards perhaps, maybe not, since opening is a specialist position. I would dearly love to have Wasim Akram, but at whose expense ???

As far as the England team is concerned, maybe the same holds good. Possibly Pietersen for Cowdrey.

In addition to the five Test series, a one-off "Test" was played between the team selected by a lucky reader (P.J.Mickleburgh) and an eleven selected by Christopher Martin-Jenkins.

The second part will follow within a few days. This will contain all six scorecards and reports.

Finally let me assure the readers that this is not an attempt to plug any of our company products, as insinuated by couple of readers earlier, possibly when their favourite player was positioned below the top. I have nothing to sell, no products, no services, nothing !!!

Analysis of Test results - by team has been done quite often. This article covers the other aspect, viz., by host country. I have taken a single theme of Test match results by country for the last four decades. The period has been selected because of the immediate relevance and to study the impact of the ODI games. The only measures are number of matches played, results and the result %.

For this particular analysis it does not matter whether the results were home wins or away wins. It is also quite possible that an innings win might be a dull mach when compared to a close draw. However I have a limited perspective here of looking only at results. In another later article I will look at excluding "dull" results and including "exciting" draws.

   |<-1970-2010->|<---1970s-->|<---1980s-->|<---1990s-->|<---2000s-->|
   |   M   R   % |  M   R   % |  M   R   % |  M   R   % |  M   R   % | 
ALL|1277 831 65.1|197 113 57.4|267 144 53.9|347 223 64.3|460 346 75.2|
                                                                       
AUS| 216 165 76.4| 43  35 81.4| 55  35 63.6| 56  42 75.0| 60  51 85.0|
BAN|  32  28 87.5|            |            |  1   1  100| 29  25 86.2|
ENG| 231 151 65.4| 47  26 55.3| 57  35 61.4| 57  37 64.9| 70  53 75.7|
IND| 153  86 56.2| 34  18 52.9| 42  17 40.5| 30  22 73.3| 47  29 61.7|
NZL| 131  76 58.0| 21  11 52.4| 28  12 42.9| 40  24 60.0| 42  29 69.0|
PAK| 122  65 53.3| 14   4 28.6| 43  19 44.2| 34  21 61.8| 31  21 67.7|
SAF|  96  75 78.1|  4   4  100|            | 36  24 66.7| 54  46 85.2|
SRI|  96  65 67.7|            | 12   7 58.3| 30  15 50.0| 54  43 79.6|
WIN| 156  92 59.0| 34  15 44.1| 30  19 63.3| 41  27 65.9| 51  31 60.8|
ZIM|  44  28 63.6|            |            | 22  10 45.5| 22  18 81.8|

Country analysis

Barring the disastrous 1980s, Australian matches have produced results over 80% of the time. This figure is going up year by year. No doubt due to the sporting nature of the pitches there.

Not worth talking about Bangladesh since most of the results there are Bangladeshi losses. No offence meant.

England had a very dull 1970s decade but recovered well and are now comfortably having results in three out of four matches.

India seems to have the worst record amongst all countries. Even in the last decade, when the rest of the world, especially outside the subcontinent, produced result-oriented pitches, India had only a 60% result value. This is quite low for the modern game of Test cricket desperately trying to maintain spectator interest.

New Zealand was very poor during the first two decades but seems to be improving steadily. However it must be mentioned that quite a few results there are the result of diabolic poor quality pitches, especially during thge early-2000s.

There was a time when Pakistan had a result % of 28. Now they have progressed to 2 out of 3. Still ranks with India as not conducive to results.

South Africa must be the most improved country in this regard and are mirroring Australia in producing pitches with opportunities for both Batsmen and Bowlers. Incidentally there were two great exciting draws there recently.

Srilankan pitches were flat as recently as last decade with a result % of only 50. Now there is a sudden improvement and they have a lot more results, mostly for the home team (and Muralitharan).

West Indies are nearly as bad as India. Only around 60% of the matches produce results. The West Indies situation, with progressively weakening teams, is understandable.

Zimbabwe is somewhat like Bangladesh. They lose home matches quite regularly. However they have at least managed to draw quite a few home tests as shown by the low results %.

Decade analysis

Over the past 40 years, the result % has been 65, no doubt aided by the recent spurt in result matches. The last decade has been excellent with over 3 out of 4 matches decisive.

The 1970s were average with only 57% being result matches. Australia were the only exception to the safety-first method employed by home countries. Pakistan was exceptionally poor.

The 1980s was the nadir with even Australia falling into this mire. No country exceeded 64% and only around half the matches produced results. Pakistan improved but India and New Zealand fell back.

There was a marked move up in the 1990s. The result % moved up to 64. Australia had 75% result matches but the real improvement was in India with 73% result matches, possibly through Kumble.

The last decade was an excellent one overall with 75% result matches. The only two countries pulling down the result figure are India, with 61.7% and West Indies, with 60.8%. As already stated, West Indies situation is understandable. However, the Indian scene, with a team aspiring and succeeding to go to the top and possessing an outstanding team is inexplicable. I hope the Indian pitches change quickly and we see a 75+% during the coming decade.

What I would like to see in the 2010s decade is for the overall figure to go upto 80%. I would prefer that this is achieved through India and West Indies consistently reaching 75% results.

I have stayed away from a graphic representation of these numbers since the figures any readers would be interested in are readily available and the readers can draw their own conclusions. Nothing is gained by doing a graph for the sake of showing something visual.

From this month onwards I will be doing at least two light-weight posts such as this and the preceding one. Over the past few weeks many readers have asked for special types of analysis and most of these would fall into this category.

This is a continuation of my previous article which was based on a request by Seshasayee. I had posted the eleven-players-together article and Sumanth Sankaran did an excellent job of doing the 2-10 groupings using some nifty Jave code. I had already done the 2-3 player group work and the results match. Hence I am pleased to present his findings. Let me confess that I have only done the formatting and editing work related to the article using Sumant's findings and have also updated the recent matches. My thanks to Sumanth for this. I have reproduced below Sesha's specific request.

Ananth in future when you have some time you can consider analysing number of Test matches a group of players in a team have played together...Min 2 to Max 11.

Updated till Test# 1944 (South Africa - England : Dec 26 2009)

Number of players together : 2

IND: 122 R Dravid, SR Tendulkar (# 1)
     122 A Kumble, SR Tendulkar (# 1)
     113 R Dravid, SC Ganguly
SAF: 118 JH Kallis, MV Boucher  (# 3)
      96 M Ntini, MV Boucher     
      93 JH Kallis, SM Pollock
AUS: 108 ME Waugh, SR Waugh
     104 GD McGrath, SK Warne
     103 IA Healy, MA Taylor
ENG:  99 AJ Stewart, MA Atherton
      87 DI Gower, IT Botham
      79 AJ Stewart, N Hussain
WI :  99 CG Greenidge, IVA Richards
      95 CA Walsh, CEL Ambrose
      94 DL Haynes, IVA Richards
NZ :  78 NJ Astle, SP Fleming
      76 DL Vettori, SP Fleming
      67 AC Parore, SP Fleming
SL :  95 M Muralitharan, WPUJC Vaas
      95 DPMD Jayawardene, M Muralitharan
      90 M Muralitharan, ST Jayasuriya
PAK:  78 Imran Khan, Javed Miandad
      75 Javed Miandad, Mudassar Nazar
      68 Inzamam-ul-Haq, Mohammad Yousuf
ZIM:  61 A Flower, GW Flower
BAN:  42 Habibul Bashar, Khaled Mashud

Tendulkar, in company with two other great Indian stalwarts, Dravid and Kumble, occupies the top two positions with 122 Tests each. Kallis and Boucher are next. There is no doubt that two of these combinations will continue to prosper in future. Note that Australia have three independent combinations occupying the top-3 places.

Number of players together : 3

IND: 103 R Dravid, SC Ganguly, SR Tendulkar (# 1)
      97 A Kumble, R Dravid, SR Tendulkar   (# 2)
      96 R Dravid, SR Tendulkar, VVS Laxman (# 3)
SAF:  88 JH Kallis, M Ntini, MV Boucher      
      80 JH Kallis, MV Boucher, SM Pollock
      74 HH Gibbs, JH Kallis, MV Boucher
AUS:  92 ME Waugh, SK Warne, SR Waugh
      85 IA Healy, MA Taylor, SR Waugh
      83 IA Healy, MA Taylor, ME Waugh
ENG:  60 AJ Stewart, GP Thorpe, MA Atherton
      56 AJ Stewart, MA Atherton, N Hussain
      53 AJ Stewart, D Gough, MA Atherton
WI :  82 CG Greenidge, DL Haynes, IVA Richards
      75 DL Haynes, IVA Richards, PJL Dujon
      74 DL Haynes, IVA Richards, MD Marshall
NZ :  59 DL Vettori, NJ Astle, SP Fleming
      49 AC Parore, NJ Astle, SP Fleming
      49 IDS Smith, JG Wright, MD Crowe
SL :  76 DPMD Jayawardene, KC Sangakkara, M Muralitharan
      76 DPMD Jayawardene, M Muralitharan, WPUJC Vaas
      71 MS Atapattu, ST Jayasuriya, WPUJC Vaas
PAK:  50 Abdul Qadir, Javed Miandad, Mudassar Nazar
      46 Imran Khan, Javed Miandad, Mudassar Nazar
      45 Asif Iqbal, Majid Khan, Wasim Bari
ZIM:  56 A Flower, ADR Campbell, GW Flower
BAN:  33 Habibul Bashar, Javed Omar, Khaled Mashud

Almost the same as 2-player combinations with the Indian "Famous Five" forming various combinations and occupy the top three places. What a trio for West Indies at the top.

Number of players together : 4

IND:  86 A Kumble, R Dravid, SC Ganguly, SR Tendulkar    (# 1)
      80 R Dravid, SC Ganguly, SR Tendulkar, VVS Laxman  (# 2)
      73 A Kumble, R Dravid, SR Tendulkar, VVS Laxman    (# 3)
SAF:  65 GC Smith, JH Kallis, M Ntini, MV Boucher        
      59 HH Gibbs, JH Kallis, MV Boucher, SM Pollock
      58 G Kirsten, JH Kallis, MV Boucher, SM Pollock
AUS:  68 GD McGrath, ME Waugh, SK Warne, SR Waugh
      67 AC Gilchrist, JL Langer, ML Hayden, RT Ponting
      66 IA Healy, MA Taylor, ME Waugh, SR Waugh
ENG:  44 DI Gower, IT Botham, RGD Willis, RW Taylor
      41 AJ Strauss, AN Cook, KP Pietersen, PD Collingwood
      39 AJ Stewart, GP Thorpe, MA Atherton, N Hussain
WI :  67 CG Greenidge, DL Haynes, IVA Richards, PJL Dujon
      64 DL Haynes, IVA Richards, MD Marshall, PJL Dujon
      64 CG Greenidge, DL Haynes, IVA Richards, MD Marshall
NZ :  39 AC Parore, CL Cairns, NJ Astle, SP Fleming
      39 IDS Smith, JG Wright, MD Crowe, Sir RJ Hadlee
      37 CD McMillan, DL Vettori, NJ Astle, SP Fleming
SL :  62 DPMD Jayawardene, MS Atapattu, ST Jayasuriya, WPUJC Vaas
      61 M Muralitharan, MS Atapattu, ST Jayasuriya, WPUJC Vaas
      61 DPMD Jayawardene, KC Sangakkara, M Muralitharan, WPUJC Vaas
PAK:  38 Asif Iqbal, Majid Khan, Mushtaq Mohammad, Wasim Bari
      35 Abdul Qadir, Javed Miandad, Mudassar Nazar, Saleem Malik
      35 Asif Iqbal, Majid Khan, Wasim Bari, Zaheer Abbas
ZIM:  43 A Flower, ADR Campbell, GJ Whittall, GW Flower
BAN:  26 Habibul Bashar, Javed Omar, Khaled Mashud, Mohammad Ashraful

This time the Indian "Pancha Pandavas" have formed groups of four players and taken the first three places.

Number of players together : 5

IND:  65 Kumble, Dravid, Ganguly, Tendulkar, Laxman  (# 1)
WI :  58 Greenidge, Haynes, Richards, Marshall, Dujon (# 2)
AUS:  55 Healy, Taylor, ME Waugh, Warne, SR Waugh (# 3)
SL :  54 Jayawardene, Muralitharan, Atapattu, Jayasuriya, Vaas
SAF:  43 de Villiers, Smith, Kallis, Ntini, Boucher  
ENG:  34 Strauss, Cook, Pietersen, Panesar, Collingwood
ZIM:  34 A Flower, Campbell, GJ Whittall, GW Flower, Streak
NZ :  32 Parore, Cairns, Vettori, Astle, Fleming
PAK:  29 Asif Iqbal, Majid Khan, Mushtaq Mohd, Wasim Bari, Zaheer Abbas
BAN:  19 Habibul Bashar, Javed Omar, Khaled Mashud, Ashraful, Rafique

Ah! the same 5 together for one last hurrah, or should we say, 65 hurrahs. What a group of players. The five great West Indian players, another wonderful group, come next and the 1990s Australians clock in at no.3.

Number of players together : 6
 40 AUS Langer, Hayden, Ponting, Gilchrist, McGrath, Warne
 39 SL  Atapattu, Jayasuriya, Jayawardene, Sangakkara, Muralitharan, Vaas
 38 AUS Langer, Hayden, Ponting, Martyn, Gilchrist, Warne
 36 IND Sehwag, Dravid, Ganguly, Tendulkar, Laxman, Kumble

Number of players together : 7
 30 AUS Langer, Hayden, Ponting, Gilchrist, Martyn, 
        McGrath, Warne
 30 WIN Greenidge, Haynes, Richards, Richardson, Dujon,
        Marshall, Walsh
 28 AUS Slater, Taylor, Boon, ME Waugh, SR Waugh, 
        Healy, Warne
 27 SAF Smith, Amla, Kallis, de Villiers, Steyn, 
        Ntini, Boucher   

Number of players together : 8
 23 AUS Langer, Hayden, Ponting, Martyn, Gilchrist,
        McGrath, Gillespie, Warne
 21 WIN Haynes, Richards, Richardson, Logie, Walsh,
        Ambrose, Marshall, Dujon and 3 other West Indian groups
 22 SAF Smith, Amla, Kallis, de Villiers, AG Prince,
        Steyn, Ntini, Boucher 

Number of players together : 9
 18 WIN Haynes, Richards, Logie, Richardson, Hooper,
        Walsh, Ambrose, Marshall, Dujon
 17 WIN Two West Indian teams of 1980s
 16 AUS Hayden, Ponting, SR Waugh, Martyn, Gilchrist,
        McGrath, Waugh, Warne, B.Lee
 15 SAF Smith, Amla, Kallis, de Villiers, Prince,
        Steyn, Ntini, Boucher, Harris  

Number of players together : 10
 14 WIN Greenidge, Haynes, Richards, Richardson, Logie,
        Hooper, Marshall, Dujon, Walsh, Ambrose
 13 AUS Langer, ME Waugh, Hayden, Ponting, Martyn,
        Gilchrist, McGrath, Warne, SR Waugh B Lee
 13 WIN One West Indian team of the 1980s
 11 SAF Smith, McKenzie, Amla, Kallis, de Villiers,
        Harris, Steyn, Morkel, Ntini, Boucher

For the player groups 6-10, I have given only the top three placings. No specific comments since these classifications are only a few players away from the eleven player groups discussed in depth last time.

One final word of thanks to Sesha for a thought-provoking request and Sumanth for doing an excellent job.

To view/download the updated tables (.xls file) Sumanth has created (top-10 for each country instead of top-3), please click here. You might have to download/save and view.

To view/download the updated tables (.txt file) Sumanth has created (top-10 for each country instead of top-3), please click here. You might have to download/save and view.

This is a continuation of the theme of my previous article. I have tried to do justice to an excellent request put in by Seshasayee. Unlike the one I did in collaboration with Alex Tierno where we had a number of exchanges before I did the analysis, here Sesha has bowled a "googly spinning square" and let me handle it. I thank him for one heck of a suggestion.

I have reproduced below Sesha's specific request.

Ananth in future when you have some time you can consider analysing number of Test matches a group of players in a team have played together...Min 2 to Max 11 :-)

That is a single statement which has multiple analysis of different shades built in. I have done the first one out of these. Let me say that this was one of the toughest bits of analytical work I have ever done. The details would be of interest to some of the readers and I have created a separate document which can be viewed by clicking on the link provided at the end.

The first analysis I have done is to find out the maximum number of Tests played by the same eleven players. A real tough analysis but well worth the effort since it provides us many insights to the teams, their selection methodology and players' fitness.

Readers must remember that the emphasis is on Tests, not series. Also the playing order is not relevant. Let me warn the readers that they would be surprised with the numbers shown.

West Indies leads the list with 11 Tests in which the same 11 players played. This was at their heyday. These 11 Tests were played, not necessarily in close proximity, over a three-year period between 1988 and 1991. The eleven players were

Greenidge, Haynes, Richards, Richardson, Hooper, Logie, Dujon, Marshall, Ambrose, Walsh, Patterson.

The Tests are shown below.

1098 1988 Win-Eng Draw
1099 1988 Win-Eng Win
1108 1988 Win-Aus Win
1110 1988 Win-Aus Win
1112 1988 Win-Aus Win 
1114 1989 Win-Aus Draw
1166 1991 Win-Aus Draw
1167 1991 Win-Aus Win
1168 1991 Win-Aus Draw
1169 1991 Win-Aus Win
1170 1991 Win-Aus Loss

This was one strong team, one of the strongest of all time. The interesting thing is that Lara made his debut in match #1158 smack in the middle of this run and was then not played for a few Tests. For quite a few Tests in the middle Ian Bishop and Benjamin played. The surprising fact is that this strong West Indian team fared in a below-average manner during these 11 Tests, only winning 6, drawing 4 and losing 1.

Australia is next in the list with 9 Tests in which the same 11 players played. This was at their heyday. These 9 Tests were played over a 15-month period. The eleven players were

Hayden, Langer, Ponting, M Waugh, S Waugh, Martyn, Gilchrist, Lee, Warne, Gillespie, McGrath.

The tests are shown below.

1558 2001 Aus-Eng Win
1565 2001 Aus-Nzl Draw
1571 2001 Aus-Nzl Draw
1573 2001 Aus-Nzl Draw
1576 2001 Aus-Saf Win
1590 2002 Aus-Saf Win
1593 2002 Aus-Saf Win
1595 2002 Aus-Saf Loss
1615 2002 Aus-Pak Win

This was again a strong team, among the strongest of all time. In between, for two Tests, MacGill and Bichel played. The irony was that even this Australian team also fared in a below-average manner during these 9 Tests, only winning 5, drawing 3 and losing 1.

There are three teams which come in next, having 11 players in 6 Test matches each. I have only given the summary information to keep the article length to a reasonable one. It will be of interest to readers that two of these occurences have been during the past year, indicating the settled nature of the South African and English teams.

Smith, McKenzie, Amla, Kallis, Prince, de Villiers, Boucher, M Morkel, Harris, Steyn, Ntini.

South Africa: 2008 (3 wins, 2 draws, 1 loss)
1870 2008 Saf-Ind Draw
1871 2008 Saf-Ind Win
1873 2008 Saf-Ind Loss
1880 2008 Saf-Eng Draw
1881 2008 Saf-Eng Win
1893 2008 Saf-Bng Win

Tancred, Shalders, White, AD Nourse, Hathorn, Faulkner, Snooke, Sinclair, Schwarz, Sherwell, Vogler.

South Africa: 1906-07 (4 wins, 2 losses)
0088 1906 Saf-Eng Win
0089 1906 Saf-Eng Win
0090 1906 Saf-Eng Win
0091 1906 Saf-Eng Loss
0092 1906 Saf-Eng Win
0094 1907 Saf-Eng Loss

Strauss, Cook, Vaughan, Pietersen, Bell, Collingwood, Ambrose, Broad, Sidebottom, Abderson, Panesar.

England: 2008 (4 wins, 1 draw, 1 loss)
1867 2008 Eng-Nzl Win
1868 2008 Eng-Nzl Win
1874 2008 Eng-Nzl Draw
1876 2008 Eng-Nzl Win
1878 2008 Eng-Nzl Win
1880 2008 Eng-Saf Draw

India has had two separate teams of 11 players playing 4 Tests each. Both data sets are given below. Kapil Dev has been an integral part of both sets, although these have been 14 years apart. India has has quite a few 3-match sets of eleven players, twice under Ganguly and once under Dhoni. The main problem has been that the batsmen have had a steady presence. However the bowling combinations have been many. The permutations of spin annd pace bowler combinations have precluded playing the same side for long.

Prabhakar, Sidhu, Kambli, Tendulkar, Azharuddin, Amre, Kapil Dev, More, Kumble, Chauhan, Raju.

India: 1993
1211 1993 Ind-Eng Win
1213 1993 Ind-Eng Win
1214 1993 Ind-Eng Win
1229 1993 Ind-Slk Draw

Gavaskar, Chauhan, Vengsarkar, Viswanath, Yashpal Sharma, Kapil Dev, Kirmani, Binny, Ghavri, S Yadav, Doshi.

India: 1979
0861 1979 Ind-Pak Draw
0863 1979 Ind-Pak Draw
0865 1979 Ind-Pak Win
0866 1979 Ind-Pak Draw

Pakistan has had 6 different sets of eleven players who have played in 3 Tests together. The most recent is shown. Their opening combinations would have split up many a eleven.

Mohd Hafeez, Imran Farhat, Younis Khan, Mohd Yousuf, Inzamam-ul-haq, Shoaib Malik,
Abdul Razzaq, Kamran Akmal, Shahid Nazir, Umar Gul, Kaneria.

Pakistan: 2006
1815 2006 Pak-Win Win
1816 2006 Pak-Win Draw
1818 2006 Pak-Win Win

New Zealand has had 3 different sets of eleven players who have played in 3 Tests together. The most recent is shown.

Franklin, Wright, Jones, M Crowe, Greatbatch, Rutherford, RJ Hadlee, Bracewell, IDS Smith, Snedden, Morrison.

New Zealand: 1990
1136 1990 Nzl-Ind Win
1138 1990 Nzl-Ind Draw
1146 1990 Nzl-Eng Draw

Sri Lanka has had only one set of 11 players who have played in 3 Tests together.

Atapattu, Jayasuriya, Sangakkara, M Jayawardene, Tillekaratne, Samaraweera,
Arnold, Vaas, Fernando, Zoysa, Muralitharan.

Sri Lanka: 2001-02
1581 2001 Slk-Zim Win
1583 2002 Slk-Zim Win
1592 2002 Slk-Pak Win

Zimbabwe has had 5 sets of 11 players who have played in 2 Tests together. Bangladesh has had 3 sets of 11 players who have played in 2 Tests together.

To view an interesting note on the technical complexities in doing this analysis please, please click here. You might have to download/save and view.

At a future date I will do an analysis of lower number of players who have played together, starting with 2 players. That again is a tough analysis and requires different algorithms for each analysis.

	Younis Khan's average in the second half of his Test career is 55.7% more than his average in the first half © AFP

In the past few posts, we have compared Test batsmen (and bowlers) with their peers; with batsmen batting at specific batting positions; with one's own team members. Now we will be looking inward. Let us compare a Test batsman/bowler with himself. I will look at the two halves of the player careers and do a comparison between these two (mostly dissimilar) periods.

The usual criteria apply. This is just to ensure that the career is sufficiently long. I have taken 4000 runs and 45 Tests as the cut-off for batsmen and 150 wickets and 45 Tests as cut-off for bowlers. These two sets of twin conditions ensure that bowlers such as Barnes do not get into the picture. Most of the top keepers get in.

Only the batting average and bowling average are used for comparison. These two are the most trusted of all measures and will provide a very good platform for a clear understanding of a Test players' career.

Test Batsmen: Analysing the two career halves

SNo Cty Batsman         |<----Career---->|<--1st Half->|<-2nd Half>| % Chg
                        |Tests Runs  Avge|Mt Runs  Avge|Runs   Avge|
                        |                |             |           |
  1.Pak Younis Khan     |  63  5260 50.10|32-2033 39.10|3227  60.89| 55.7%
  2.Zim Flower A        |  63  4794 51.55|32-2013 41.94|2781  61.80| 47.4%
  3.Aus Redpath I.R     |  66  4737 43.46|33-1813 35.55|2924  50.41| 41.8%
  4.Nzl Wright J.G      |  82  5334 37.83|41-2123 31.22|3211  43.99| 40.9%
  5.Aus Chappell I.M    |  75  5345 42.42|38-2219 35.22|3126  49.62| 40.9%
...
 53.Eng Hobbs J.B       |  61  5410 56.95|31-2733 56.94|2677  56.96|  0.0%
...
 97.Aus Hayden M.L      | 103  8626 50.74|52-4714 58.92|3912  43.47|-26.2%
 98.Eng Smith R.A       |  62  4236 43.67|31-2255 51.25|1981  37.38|-27.1%
 99.Win Kallicharran A.I|  66  4399 44.43|33-2582 52.69|1817  36.34|-31.0%
100.Aus Gilchrist A.C   |  96  5570 47.61|48-3073 59.10|2497  38.42|-35.0%
101.Aus Harvey R.N      |  79  6149 48.42|40-3830 61.77|2319  35.68|-42.2%

Younis Khan has achieved the highest jump from the first half to second half, an astounding 55.7%. His average has improved from 39.10 to 60.89. Note that in his last 31 Tests he has scored at higher than 100 runs per Test.

Andy Flower has improved from 41.94 to 61.80, an increase of 47.4%, that too playing in a weak team. Ian Redpath, John Wright and Ian Chappell have also finished their careers very strongly.

For consistency one need not look beyond Jack Hobbs. He has only a second decimal difference in his second half average to the first half. Steve Waugh and Andrew Strauss are close to achieving this perfection.

Gilchrist's huge fall, from 59.10 to 38.42 is understandable considering that he had an explosive start and fell off drastically towards the end. What is surprising is the fall of Neil Harvey, who dropped his average from 60+ to 35. This is quite inexplicable. He scored 15 of his 21 hundreds in the first half of his career. Gilchrist, on the other hand, scored 9 of his 17 hundreds in the first half of his career. However he was dismissed for many single digit scores, quite a few 0s included, during the second half.

Note how Hayden, R Smith and Kallicharan have also fallen off.

To view the complete list, please click here.

Test Bowlers: Analysing the two career halves

No Cty Batsman          |<----Career---->|<-1st Half-->|<2nd Half>| % Chg
                        |Tests Wkts  Avge|Mt Wkts  Avge|Wkts  Avge|
                        |                |             |          |
 1.Eng Laker J.C        |   46  193 21.25|23-  78 29.95| 115 15.35| 48.8%
 2.Eng Bedser A.V       |   51  236 24.90|26- 100 33.87| 136 18.30| 46.0%
 3.Pak Iqbal Qasim      |   50  171 28.11|25-  65 35.78| 106 23.41| 34.6%
 4.Nzl Hadlee R.J       |   86  431 22.30|43- 192 26.17| 239 19.19| 26.7%
 5.Nzl Morrison D.K     |   48  160 34.68|24-  73 39.53|  87 30.61| 22.6%
 6.Slk Muralitharan M   |  129  783 22.22|65- 337 25.48| 446 19.76| 22.5%
...
38.Aus McKenzie G.D     |   60  246 29.79|30- 126 29.81| 120 29.77|  0.1%
...
66.Win Gibbs L.R        |   79  309 29.09|40- 176 24.56| 133 35.09|-42.9%
67.Pak Mushtaq Ahmed    |   52  185 32.97|26- 105 27.51|  80 40.14|-45.9%
68.Win Hall W.W         |   48  192 26.39|24- 119 22.15|  73 33.29|-50.3%
69.Eng Botham I.T       |  102  383 28.40|51- 231 23.46| 152 35.91|-53.1%
70.Eng Lock G.A.R       |   49  174 25.58|25- 104 20.13|  70 33.67|-67.2%

Laker moved from an average spinner to Lohmannish figures in the second half, no doubt aided by the 19 for 90 at Manchester. That is nearly 50% improvement. Similar with Alec Bedser, who had totally different career halves. What about Richard Hadllee, with sub-20 average in the second half of his career. Again Muralitharan's last 64 Tests have had sub-20 average and an average of 7, yes, you read it correctly, 7 wickets per Test.

McKenzie was like Hobbs, averaging almost the same figure in his two halves. Saqlain Mushtaq and McDermott are in the middle group.

Look at the last five, especially Ian Botham. He was a shadow of himself, increasing his average by over 50%. Lock's figures are still more astounding. An average of 20.13 moving to 33.67 and below 3 wickets per Test. Possibly he played the supporting role to Laker quite often as happened at Manchester in 1956.

To view the complete list, please click here.

This blog is going nowhere with readers following a single agenda, whatever be the subject matter of the article. I have had complaints from serious readers that the purpose of the articles is lost. Hence a firm reminder that only relevant comments will be published. Henceforth I will not and readers should not forget that the purpose of the blog is to come out with new analytical efforts. I myself have been guilty of side-tracking into irrelevant and/or non-cricketing issues. Remind me, gently or otherwise, to remove the offending comment or response.

A number of readers had raised queries requesting me to answer those. I have taken a few of these and attempted to provide an answer. Once in two months or so I will do a similar article.

1. Test teams with maximum number of 10+ / 15+ / 20+ Batting averages:

There was a query from WPHE about Test teams where all eleven players have had a career-to-date average in double figures.

I did a simple analysis and as I expected there are many teams, over 600, with this level of all cumulative batting averages exceeding 10. For instance most recent Indian, Australian and South African teams have even the no.11 batsman with a 10+ average.

However, this query intrigued me quite a bit especially as the late order batsmen have improved drastically of late. I did some more work on this very interesting query and the results are posted below.

First I raised the bar to 15.00 thinking that it would reduce the list to a manageable one. Good reduction, but not enough. 59 teams qualified. That is a lot. So I took the plunge and set the bar at 20.00, fully expecting a list with no entries. I was surprised to see 3 teams with all players having a career-to-date average exceeding 20.00. The teams are given below.

All batsmen exceeding career-to-date average of 20.00

0023 1886 Eng vs Aus  11
0528 1962 Ind vs Win  11
1177 1991 Ind vs Aus  11

Let us look at the three teams. Most of the analysis would centre around the last three players since the other 8 are normally expected to have averages exceeding 20.00.

The first is a very early English team. Tylecote, the keeper, had an average of 20.29. Briggs, although a bowler, had an average of 22.50. Lohmann made his debut in the previous Test and had a score and average of 32.00. To readers who complain that only one innings had been played, take it easy, this is only a quixotic analysis.

The third team, also India, has peculiar similarities to the first English team. Kiran More, the wicketkeeper batting at no.8, was a good batsman. Raju had a career-to-date average of 21.00 in 5 innings. Srinath, who made his debut in this Test, scored 21 in the first innings, hence having a career-to-date average of 21.00. Needless to say that both these bowlers finished with career averages way below 20.00. However the rules have been satisfied.

The second team, the Indian team of 1962, is the only team to have all genuine averages exceeding 20.00 since all the eleven batsmen also finished with averages exceeding 20.00. This team had Borde (3061 at 35.59) at no.8, Durrani (1202 at 25.04) at no.9, Nadkarni (1414 at 25.71) at no.10 and Kunderan (981 at 32.70) at no.11. All these four also had career-to-date average exceeding 20.00. To boot, all these four have career Test centuries to their credit. This is the only team in Test history to have such a collection of good averages. The fact that they lost to a strong West Indian team is incidental.

The underlined sentence made me think that there is something unique. If the last four in the batting order have a Test century to their credit, does this team have 11 centurions (career, not career-to-date). Alas, the Indian propensity for weak top order batsmen spoiled that. Vijay Mehra has a highest Test score of 62 and Rusi surti has a heart-breaking highest Test score of 99. So there are only 9 centurions in this team.

2. Test teams with maximum number of centurions:

The threads seem to go on. What, then about other teams with 9 or 10 Test centurions.

One more program written and the results are set out below. I set the bar at 9 centurions. Well the table hit the ceiling, with 267 entries. So I raised the limit to 10 centurions and the table is presented below.

List of teams with 10 centurions

1397 1998 Saf vs Aus  10  (Adam Bacher - 96)
1444 1999 Pak vs Ind  10  (Shoaib Akhtar - 47)
1485 2000 Pak vs Slk  10  (Waqar Younis - 45)
1547 2001 Pak vs Eng  10  (Waqar Younis - 45)
1717 2004 Nzl vs Bng  10  (Wiseman - 36)
1775 2005 Ind vs Slk  10  (Harbhajan - 66)
1776 2005 Ind vs Slk  10         Do
1778 2005 Ind vs Slk  10         Do
1781 2006 Ind vs Pak  10         Do

Of great interest is the one batsman who has not scored a century than the other 10. That information is given in brackets along with the highest score reached by the batsman.

It is of interest that the only case of a genuine top-order batsman spoiling the "Perfect 11" is Adam Bacher. The others are bowlers. It is also of interest that in many of these matches, bowlers such as Wasim Akram, Saqlain Mushtaq, Vettori, Kumble et al have scored their 100s, before or after the concerned match.

The most interesting set is the one containing the last 4 matches. The way Harbhajan Singh bats nowadays, it is only a matter of time before he reaches 100, in which case, all these four teams would reach the "Perfect 11".

3. Test teams with career-to-date double centurions:

Chandran had raised a query on Test teams with 6 batsmen who had scored double centuries. I had analysed this and presented two teams, one Pakistani and another Australian, which had seven double centurions. However, Keyur has correctly pointed that two of the double centuries in both matches had been scored after the concerned match. As such the India - South Africa match referred to by Chandran becomes the first match in which 6 batsmen have had double centuries to their credit. Great little idea and my thanks to Chandran, Agni and of course Keyur.

4. Test teams with all 11 players having captured wicket(s):

The idea of looking at teams which had all players with at least one test wicket to their names came to me as a logical extension to the batsman queries which I have been doing. In reality it is the batsmen who determine this list.

Teams with all 11 players capturing wicket(s)

0384 1954 Win vs Eng  11 (McWatt-1, Weekes-1)
0386 1954 Win vs Eng  11 (McWatt-1, Weekes-1, Holt-1)
0404 1955 Win vs Aus  11 (McWatt-1, Weekes-1, Holt-1)
0571 1964 Eng vs Saf  11 (Parks-1, MJK Smith-1) 
0572 1964 Eng vs Saf  11 (Parks-1, MJK Smith-1)
0573 1965 Eng vs Saf  11 (Parks-1, MJK Smith-1)
0575 1965 Eng vs Saf  11 (Parks-1, MJK Smith-1)
0871 1980 Ind vs Pak  11 (Kirmani-1, Viswanath-1, Gavaskar-1)
0961 1983 Ind vs Pak  11 (Kirmani-1, Gavaskar-1)
0962 1983 Ind vs Pak  11 (Kirmani-1, Yashpal-1, Gavaskar-1)

Normally the wicket-keeper is likely to be the culprit when it comes to taking wicket(s) so his name is listed first. Only the single wicket takers are listed.

5. Bowler/Fielder combination:

For this there is a ready-made table in Cricinfo's records section. For the record, Lillee/Marsh combination leads with 95 dismissals. My take is also that it may be very difficult for any Bowler/Fielder combination to reach 100 dismissals. Ntini/Boucher need 16 more dismissals which might require around 17/18 matches. Quite unlikely to happen. Muralitharan/Jayawardene, which is the highest Bowler/Fielder combination, accounts for 71 dismissals. 29 more (?!), possibly not since it might require 25 more Tests.

I get the feeling that the career-to-date figures are going to play a significant part in any future analysis. i will strengthen the Batting career-to-date figures and introduce one for Bowling also since I have not completed the Bowling career-to-date figures in a structured manner, resorting to ad-hoc computations when needed.

	The numbers of catches taken by a wicketkeeper per Test has doubled from what it was in the Pre-World War One days © Getty Images

In the first part we saw the way the numbers related to Matches, Innings, Results, Partnerships and Extras have changed over the 130 years of Test cricket. In this second part we will cover Batting, Bowling, Keeping and Dismissals.

Let me emphasise that some of this information can be garnered using Cricinfo's excellent Statsguru. Mine will offer a different perspective and is a summarised analysis using my database.

Batting will be analysed by right- and left-hand batsmen. Bowling will be analysed by pace and spin bowling. All dismissals would be analysed. As far as the keepers are concerned, byes have already been analysed in Part 1. Here the two wicketkeeper dismissals would be covered.

1. Batting analysis 1 (average - left & right)

Period     R-Avg  L-Avg  T-Avg

Pre-WW1    22.73  25.33  23.06
WW1-WW2    31.68  29.73  31.40
40s-50s    28.44  30.98  28.81
1960s      29.72  35.37  30.82
1970s      30.29  32.86  30.79
1980s      29.65  33.61  30.44
1990s      28.21  33.32  29.45
2000s      28.99  37.89  31.68

All Tests  28.77  34.19  29.92

All->1000R 37.34 39.46 37.90

First the period changes. After a relatively difficult first period, the other seven periods have seen very little variations in batting average. The current decade has seen the best batting average of all times. This is almost 5% above the all-test average.

However the real shock comes when we see the right and left-hand figures. Barring a single period (the period in between the World Wars - no doubt caused by Bradman & Co), left-handers have consistently averaged between 10 and 30% more than the right-handers. Across all Tests there is a 15% variance. Look at the current decade. Left-handers have averaged nearly 30% more than the right-handers. I have no explanations. The readers will certainly have a few.

This is borne out by the following facts. This may explain "how" but not "why".

1. As per my records, 440 players have batted left-handed. This, out of 2525 players. A frequency of approximately one in six.
2. In the list of top 25 batting averages, there are seven left-hand batsmen. This is a much higher frequency of one in every 3.5. It explains why left-handers have a much better average. Extending it further, 107 out of 400 top averaging batsmen are left-handed. One in four!
3. In the list of top 25 run-scorers, there are eight left-hand batsmen. This is a much higher frequency of one in every three. They not only average more but score more also, it seems. Extending it further, 101 out of 400 top-scoring batsmen are left handed. Again, one in four.

I have not done any analysis on centuries since I strongly feel a century is only a personal milestone and does nothing more for the team, other than, of course the 100th run. A 99 will serve the team as much as a 100. There is a lot of unnecessary hype over a century. At least I will ignore this measure.

It can be clearly seen that the difference between Right and Left handers is less pronounced when I do a separate analysis of only batsmen who have scored greater than 1000 runs, thus clearly excluding the real tail-enders. Many thanks to Hariharan Sriram's observation.

To view the complete table, click here.

2. Bowling analysis 1 (average - pace & spin)

Period    P-Avg  S-Avg  T-Avg

Pre-WW1   23.24  25.00  24.02
WW1-WW2   32.15  33.10  32.56
40s-50s   28.78  31.20  29.96
1960s     30.41  34.47  32.11
1970s     30.19  35.01  31.94
1980s     29.93  37.71  32.07
1990s     29.84  35.62  31.51
2000s     32.94  35.43  33.76

All Tests 30.27  33.72  31.51

All->100w 26.75  29.25  27.67

The bowling average is analysed between pace and spin. First the period analysis. Barring the first period and the 1940s-1950s (just barely) the bowling average has been in excess of 30. The all-Test average is still higher at 31.51.

Now the split between pace and spin. The average for pace is about 5% below the all-Test average and 10% below the spin average. This is as expected and does not offer any surprises.

Since this involves every wicket taken, I have done an alternate measure. This is to consider the averages only for bowlers who have taken 100 wickets and more. For obvious reasons this can be done at a total level only and not by period.

These figures are considerably (about 10%) below the all-bowler averages. Pace averages 26.25 while spinners average 29.25, both very reasonable figures.
To view the complete table, click here.

3. Bowling analysis 2 (strike-rate - pace & spin)

Period   P-S/R  S-S/R  T-S/R

Pre-WW1   55.2   57.0   56.0
WW1-WW2   75.6   76.7   76.0
40s-50s   75.6   82.7   79.1
1960s     72.2   92.7   80.8
1970s     68.0   89.7   75.9
1980s     63.0   90.8   70.6
1990s     63.2   82.0   68.6
2000s     62.3   72.9   65.8

All Tests 65.6   80.4   70.9

All->100w 58.9   73.1   64.1

The strike-rates follow a similar pattern to the bowling averages. The pace bowlers strike at a frequency which is about 20% below the spinners. This applies to the bowlers who have captured more than 100 wickets also.
To view the complete table, click here.

4. Bowling analysis 3 (runs per over - pace & spin)

Period   P-Rpo  S-Rpo  T-Rpo

Pre-WW1   2.52   2.63   2.57
WW1-WW2   2.55   2.59   2.57
4os-50s   2.28   2.26   2.27
1960s     2.53   2.23   2.38
1970s     2.66   2.34   2.53
1980s     2.85   2.49   2.72
1990s     2.83   2.61   2.76
2000s     3.17   2.92   3.08

All Tests 2.77   2.52   2.67

All->100w 2.73   2.40   2.59

The spinners come into their own in the runs per over measure. They are about 10-15% more economical. The surprise is the figures do not show much variation across the periods, the first one included. Note also the current decade. The bowlers have become more expensive. Even the spinners are going at nearly three runs per over.
To view the complete table, click here.

Now let us analyse the dismissals effected.

5. Dismissals analysis 1 (bowled - % and per match)

Period    Bowled  Wkts  % of Tot Bow/Mtch

Pre-WW1     1639  4301     38.1    12.2
WW1-WW2     1205  3998     30.1     8.6
40s-50s     1774  6089     29.1     8.5
1960s       1449  5546     26.1     7.8
1970s       1268  5866     21.6     6.4
1980s       1489  7504     19.8     5.6
1990s       1786 10203     17.5     5.1
2000s       2084 12278     17.0     5.1

All Tests  12694 55785     22.8     6.7

Major surprises here. The number of bowled wickets was as high as 38.1 during the first period and then fell only to around 30% during the next two periods. Now it stands at a low 17%, around one in six.

To what can this be attributed? Improvement in technique, change in bowling line, more lbws et al.

6. Dismissals analysis 2 (lbw - % and per match)

Period    Lbw    Wkts  % of Tot  Lbw/Mtch

Pre-WW1      286  4301      6.6     2.1
WW1-WW2      509  3998     12.7     3.6
40s-50s      821  6089     13.5     3.9
1960s        661  5546     11.9     3.6
1970s        716  5866     12.2     3.6
1980s       1201  7504     16.0     4.5
1990s       1755 10203     17.2     5.1
2000s       2178 12278     17.7     5.3

All Tests   8127 55785     14.6     4.3

Here it has happened the other way. During the first period, only one in 16 were lbws. Now it is one in six. Again, why? Changes in lbw laws, umpires being more liberal in giving lbw decisions, reverse-swing (?) et al.

7. Dismissals analysis 3 (caught - % and per match)

Period    Ct Others Wkts % of Tot Ct/Mtch

Pre-WW1     1809  4301     42.1    13.5
WW1-WW2     1639  3998     41.0    11.7
40s-50s     2332  6089     38.3    11.2
1960s       2325  5546     41.9    12.5
1970s       2630  5866     44.8    13.4
1980s       3154  7504     42.0    11.8
1990s       4323 10203     42.4    12.5
2000s       5314 12278     43.3    12.9

All Tests  23526 55785     42.2    12.4

These are the non-wicketkeeper catches and have remained fairly static across the years. No information is available on where the catches were taken. As such I will not be able to separate the slip/gully cathes. No doubt these would be on the increase during the later years.

8. Dismissals analysis 4 (stumped - % and per match)

Period    Stumped  Wkts  % of Tot  St/Mtch

Pre-WW1      152  4301      3.5     1.1
WW1-WW2      158  3998      4.0     1.1
40s-50s      207  6089      3.4     1.0
1960s        106  5546      1.9     0.6
1970s         99  5866      1.7     0.5
1980s        109  7504      1.5     0.4
1990s        148 10203      1.5     0.4
2000s        222 12278      1.8     0.5

All Tests   1201 55785      2.2     0.6

The percentage of stumpings started at quite a high value and has now come down to less than 2%. Note that it takes an average of two matches to get a stumping now. Probably there is a lot of stand and swat rather than use one's feet and move out.

9. Dismissals analysis 5 (Ct by Wk - % and per match)

Period   Ct by Wk Wkts  % of Tot CWk/Mtch

Pre-WW1      373  4301      8.7     2.8
WW1-WW2      432  3998     10.8     3.1
40s-50s      859  6089     14.1     4.1
1960s        920  5546     16.6     4.9
1970s       1053  5866     18.0     5.3
1980s       1406  7504     18.7     5.3
1990s       2032 10203     19.9     5.9
2000s       2308 12278     18.8     5.6

All Tests   9383 55785     16.8     5.0

As expected this figure has more than doubled from the first to last period. This is now a very effective manner of dismissal. More than one in six. The drop in bowled has indicated bowlers now try and get the edges. Consequently the keeper comes in more often. Without entering into the bowler-keeper argument again, let me now say most of the credit should go to the bowler, with some credit going to the keeper, especially for the difficult catches.

10. Dismissals analysis 6 (run-outs - % and per match)

Period   Runouts  Wkts   % of Tot  RO/Mtch

Pre-WW1     179   4301      4.2     1.3 
WW1-WW2     147   3998      3.7     1.1 
40s-50s     241   6089      4.0     1.2 
1960s       232   5546      4.2     1.2 
1970s       218   5866      3.7     1.1 
1980s       258   7504      3.4     1.0 
1990s       359  10203      3.5     1.0 
2000s       419  12278      3.4     1.0 

All Tests   2053 55785      3.7     1.1 

There seems to be a slight drop in the percentage of run-outs over the years. Is there a possible reason that with the advent of the third umpire, in both run-out and Stumping cases, the batsman gets the benefit of technology and marginal decisions which were given with the naked eye are now not given?

I had made an offer that all this information would be available to the readers. This is going to take some time since I am preparing a comprehensive XL sheet with all the parameters for easier access and retrieval. I will make this available at a later date by providing a suitable link.

	Thanks largely to the Australians, the run-rate and result percentage have gone up significantly in Tests since 2000 © Getty Images

This is a major attempt to generate a set of measures for Test Cricket by period. The purpose is two-fold. The first is to look at the way the figures change over the years, letting us get a handle on the evolution of the game. The second is to establish a criteria for adjusting any analysis we do which spans across the years. Many a time have I found myself in a situation needing to adjust a particular period's figures and I have re-invented the wheel every time. Now I hope to have a set of figures which can be used as a ready reckoner for such adjustments. Readers who do similar analysis are welcome to use these figures.

Readers should also realize that after I thought of this complex topic, I have put in nearly a month's work, on and off. into preparing this complicated analysis. I would appreciate avoiding of a superficial read and flippant off-the-cuff comments.

The analysis covers various aspects of Test Cricket. Since the article has become too long, it has been split into two parts. The first part covers Matches, Innings, Results, Partnerships and Extras. The second part covers Batting, Bowling, Keeping and Dismissals.

To start with let me divide the 130 years into 8 periods, taking into account the evolution of the game, years and the number of Tests played. The following are the periods.

1. 1877 - 1914  (Pre World war 1)
2. 1920 - 1939  (In between the two World Wars)
3. 1946 - 1959  (1940s & 1950s)
4. 1960 - 1969  (1960s)
5. 1970 - 1979  (1970s)
6. 1980 - 1989  (1980s)
7. 1990 - 1999  (1990s)
8. 2000 - 2008  (2000s)

These are logical and reasonably evenly spaced periods. Anything more will result in too many periods with consequent difficulty in following the tables and anything less will telescope multiple differing periods into one and we will lose out in analysis.

Even the formatting of the article required a lot of thinking. I tried having the periods horizontally. It was difficult to read. There was also the need to present the core data such as runs, wickets, balls, wickets et al to the readers. So I adopted a dual presentation approach. In the main body of the article I show the calculated measures in a grouped form and the base core data in the supporting pages. That way all the information is shown and the main report is not cluttered. I have also avoided showing the variance of each period figure to the all-Test averages to avoid showing too many numbers. That will indeed be the key figure to make adjustments.

Let us get into the analysis results.

First the base Match analysis.

1. Match analysis 1 (Balls/Runs/Wkts per match)

Period     Mats   B/M  R/M  W/M

Pre-WW1     134  1799  812 33.6 
WW1-WW2     140  2171  976 29.9 
40s-50s     209  2303  912 30.4 
1960s       186  2409 1003 31.1 
1970s       197  2259 1014 31.0 
1980s       267  1985  949 29.2 
1990s       347  2018  963 30.5 
2000s       409  1967 1046 31.1 

All Tests  1889  2093  973 30.7 

During the first period, timeless Tests and 3-day Tests alternated. Later 3-day, 4-day, 5-day, 6-day and timeless Tests were played through the years until 1979, from which year almost all the 1000+ tests have been played over 5 days. As recently as 1973, 4-days tests were played between New Zealand and Pakistan. Please remember these pertinent facts while perusing this table.

Surprisingly the Balls per match figure during the first period has been quite high despite the number of 3-day tests. This, despite 4-ball overs during most of these years requiring more change over time. During 1960s the balls per match is the highest. More than the match days, I feel this is certainly a result of lot more drawn matches during this period and to a lesser extent the 1970s.

The runs per match is the highest during the current decade and the lowest during the first period when batting was indeed difficult. The relatively high 1960s and 1970s figure must no doubt be due to the number of drawn matches.

More Wickets per match fell during the first period. Barring this period the figure has remained fairly static.

To view the complete table please click here.

2. Match analysis 2 (Runs/Wkt, Runs/Over)

Period      RpO    RpW 

Pre-WW1    2.71   24.2 
WW1-WW2    2.70   32.7 
40s-50s    2.37   29.9 
1960s      2.50   32.2 
1970s      2.69   32.7 
1980s      2.87   32.5 
1990s      2.87   31.6 
2000s      3.19   33.7 

All Tests  2.79   31.7 

The RpO figure is the most important measure we have seen until now. It has varied quite significantly over the years. Surprisingly the Rpo figure was quite high during the first two periods despite the pitches. It fell drastically during the post-112 period, certainly due to a combination of accurate bowling and defensive batting and attitudes. The figure picked up later and has crossed the key value of 3.0 for the current decade, where it is 14% higher than the all-test average. This has been the result of most teams, led by Australia, scoring quickly in a bid to go for a result.

There have been 4/5/8 ball overs at different times in Test cricket, however all RpO figures have been standardized to 6 bpo for this table.

Barring the first period the Runs per wicket figure has remained fairly stable. The figure is highest during current decades. For most of the periods the RpW figure has exceeded 30.

To view the complete table please click here.

3. Inns Analysis (Runs per completed inns, Low and high scores)

Period      R/CI  I<100   I>500 

Pre-WW1     231  12.71%   2.63% 
WW1-WW2     289   3.14%   6.68% 
40s-50s     256   6.46%   6.79% 
1960s       284   1.93%   5.80% 
1970s       276   2.62%   5.24% 
1980s       278   2.23%   5.64% 
1990s       269   1.71%   5.47% 
2000s       282   3.42%   9.87% 

All Tests   272   3.84%   6.49% 

The average completed innings size has followed the pattern. Quite low (15% below all-Test average) during the first period and then around the all-Test average mark subsequently, barring the low-scoring 40s-50s period..

During the first period, there was an extraordinarily high instances of sub-100 innings. Over 12.5% of the innings completed (53 out of 494) were below 100. The second period was a major drop in the sub-100 innings. However the figure almost doubled during the 40s-50s. Then it has settled down. The 1990s had the lowest figure. Surprisingly the current decade's is double that of the previous decade. There have been 36 such instances out of 1052 completed innings.

I was so intrigued by this sudden escalation that I decided to make a detailed study. As expected the culprits were Bangladesh with 8 sub-100 scores and Zimbabwe with 7. However the situation has been worsened by the West Indian decline. They have had 5 sub-100 scores. At the other end, Australia and South Africa have had one instance each.

Predictably there were very few 500+ innings during the first period. Then the % stabilized to the all-Test average during the next 6 periods. There has been a noticeable increase during the current decade with 147 of the 1489 innings crossing 500. Remember that these are not just completed innings but all innings.

Australia leads with 28 500+ scores while India is close with 24. At the other end Zimbabwe has only 2 scores in excess of 500 while Bangladesh has not crossed 500.

The paradoxical current decade situation of high number of 500+ scores and high number of sub-100 scores is a pointer to the wide gap between teams as well as the drive to achieve results.

To view the complete table please click here.

4. Partnerships analysis (Opening & Last 3 wkts)

Period     Open OP100+ OPSub10 Last3W

Pre-WW1    29.8   5.9%   37.2%  47.3
WW1-WW2    40.5  11.3%   28.1%  47.5
4os-50s    36.3   8.1%   27.4%  40.7
1960s      38.2   7.5%   24.9%  49.0
1970s      38.3   8.0%   27.0%  47.5
1980s      34.2   6.4%   27.5%  50.0
1990s      35.7   8.2%   30.3%  48.2
2000s      39.0   8.9%   28.7%  49.8 

All Tests  36.7   8.1%   28.7%  47.8

This is an analysis of two types of partnerships. The first wicket partnership is the most important one since it lays the foundation for the innings. The average first-wicket score has been reasonably scattered around the all-Test average of 36.7 barring the first period when it fell below 30. In between the wars the partnership average went past 40, possibly owing to the strong opening partnerships of England and Australia.

Even though I am not a fan of measuring quality through individual 100s (I always treat the 100th run as nothing more than the run(s) scored around the 99 mark), a 100 partnership is more significant since it delivers a psychological blow for the team. A fairly low number of partnerships during the first period crossed 100. Surprisingly this was followed by a doubling during the next period with over 10% of the partnerships crossing 100 (56 out of 494). There has been a recent increase during the current decade, also at a good scoring rate.

The next is a measure of opening failures. These are the sub-10 (single digit) partnerships. This includes only instances where the first wicket has fallen. During the early days, especially during the first period, well over a third of the partnerships have been failures. This figure improved over the years but has picked up now and we are back to a fairly high (either side of) 30% figure. It may have to do with the attacking attitude of the opening batsmen nowadays. I could have done a "opener dismissed at 0" analysis. However I feel that a single digit partnership is a failure and a 0 is no worse than a 5 or 9.

The next measure is the number of runs added for the last 3 wickets. This has not varied much barring the 40s-50s when it fell to around 40. For the current decade the value is around 50, indicating a more committed late order batting set-up with better techniques and application.

To view the complete table please click here.

5. Extras Analysis - per 1000 balls (Extras/Byes/LegByes/NoBalls/Wides)

Period     E/Tb B/Tb L/Tb N/Tb W/Tb

Pre-WW1    22.6 12.8  6.5  2.3  1.0 
WW1-WW2    21.2  9.3  8.6  2.8  0.5 
40s-50s    16.8  7.6  6.3  2.3  0.5 
1960s      18.9  6.6  7.3  4.4  0.5 
1970s      27.9  6.5  9.2 11.3  1.0 
1980s      32.0  6.0 11.8 12.5  1.7 
1990s      33.1  5.9 12.4 13.4  1.4 
2000s      34.0  6.9 11.9 12.2  2.9 

All Tests  27.4  7.1  9.9  8.9  1.4

All the extras calculations have been done per 1000 balls. This is just a convenient measure and is to be used only as a relative measure for comparison. All the extras components have been analyzed.

The number of Extras per Tb has increased over the years and the current decade figure is the highest, about 20% higher than the all-Tests average.

The Byes per Tb started at a high figure and now stands around the all-Test average. Have the keepers become that much better?

Leg Byes follows the reverse pattern. Starting at a low level it is now at a fairly high level.

No Balls per Tb have increased significantly. They were extremely low during the first 70 years and suddenly zoomed up during the 1970s and have remained there. Possibly the changing of the No ball rule during the 1960s must have contributed to this increase.

Wides per Tb have also increased during the current decade, almost double of the all-Test average and the previous period of value. Possibly the bowlers are striving for too much. May also be that the unmpires, no doubt influenced by the ODI experience, are calling wides more often now.

The increase in LB/Nb/Wides per Tb has more than odffset the drop in Byes per Tb and this has resulted in the overall increase in Extras per Tb.

To view the complete table please click here.

6. Results Analysis (Results/HomeWins/AwayWins)

Period     Res% HW % AW % Dr %

Pre-WW1    82.1 44.0 38.1 17.9
WW1-WW2    62.9 35.7 27.1 37.1
40s-50s    65.1 36.8 28.2 34.9
1960s      52.2 30.6 21.5 47.8
1970s      57.4 35.0 22.3 42.6
1980s      53.9 32.6 21.3 46.1
1990s      64.3 40.9 23.3 35.7
2000s      77.0 46.2 30.8 23.0

All Tests  64.9 38.6 26.3 35.1

This is a very interesting table. The overall Results % started at an incredible 82+ value during the first period, dropped to a low 50+% during the miserable 1960s and has risen again now to a near-80% value. Australia might be stuttering now. However they are the team which started the equivalent of "total cricket", hard, attacking and always striving for results. Due credit should be given to them for changing the face of Test cricket, especially after the miserable 1960s-1980s periods.

A similar pattern emerges in the Home wins measure. The first and last periods have high Home wins % values.

The best period for Away wins was the first one when the 3 month sea travel seemed to have done something good since 38% of the matches finished with Away wins. This value has since dropped and stood at its lowest during the 1960s when "Not to lose" was the motto. The value has picked up significantly during the current decade with over 30% Away wins.

The Draws % shows low values during the first and last periods. The most boring period in Test history was during 1960s when nearly half of the matches ended in draws, not all of them the exciting ones.

To view the complete table please click here.

The second part of the article will follow in a week's time covering the Batting, Bowling, Keeping and Dismissals aspects. I will also try and do some changes based on any significant comments. I invite readers' comments, both on these areas and the ones being analyzed next week. At the end of the second part, if readers so desire, I will also make available an XL sheet containing all the measures analysed, including % variances to the all-Test averages.