Chris Gayle's century wasn't enough to prevent South Africa from winning the opening the game of the World Twenty20. They chase down 206, the highest successful run-chase in international Twenty20 games © Getty Images

Finally I have come around to my first T20 analysis. I had to do some serious T20 ratings analysis work related to another project and as part of that work, I looked at T20 matches from a totally different angle. One aspect of this analysis was to determine a reasonable target score for the first innings (the target score for the second innings is no problem, even when the learned professors, M/s Duckworth and Lewis come in with their umbrellas!). The team’s achievement in terms of exceeding or falling short of the dynamically computed target score is determined to compute one segment of the individual ratings. It also allows me to allocate the credits between bowlers and batsmen.

Let me add that my database, current upto the West Indies - England game, is limited to T20 International matches and as of now I have no intention of building a Database of other club-based T20 matches.

First some facts about T20 matches. Let me say that I have completely ignored team strengths, pitch conditions et al since there is not enough data and in this short version of the game, there is lot more evening out between the two teams.

1. A total of 84 matches have been played and completed. Out of these, 4 have been tied. 2 matches outside these 84 have been washed out.

2. 34 (out of 80) matches have been won by the team batting first. This represents 42.5% of the completed matches. One of these wins has been through D/L method.

3. 46 (out of 80) matches have been won by the team chasing. This represents 57.5% of the completed matches. One of these wins has been through D/L method.

4. Out of these 46 matches, the top 4 run chases have been against scores of 165 and above. These four succesful run chases are detailed below. In other words, any team scoring 165 and above has a 90+ % chance of winning the game. This seems to be true irrespective of the relative team strengths. It is also possible that the weaker team might bat first more often than not.

020 2007 Win 205/ 6 (20.0) Lost to Saf 208/ 2 (17.4) at Wanderer's, Jo'burg
082 2009 Slk 171/ 4 (20.0) Lost to Ind 174/ 7 (19.2) at Premadasa, Colombo
016 2007 Win 169/ 7 (20.0) Lost to Eng 173/ 5 (19.3) at Oval, London
047 2007 Aus 166/ 5 (20.0) Lost to Ind 167/ 3 (18.1) at Brabourne, Mumbai

5. It is a reasonable assumption to make that the team batting first should set themselves a Target score of 165 runs to have a 90+ % chance of winning. Anything more would obviously further increase the chance of winning. However we are not looking at a Target score with 100% chance, which, at the current moment is 206.

6. If we drop the number from 165 to 160, the number of losses is more than doubled since 5 more matches are won by batting teams chasing 164, 164, 164, 162 and 162 successfully. The win % drops to 80% so there is a need to retain the Target score at 165.

It is possible that in the next 5 matches, 170+ scores would have been chased. However that does not make the idea of working on a Target score invalid and as things stand, 165 seems to be a very good number for a captain to write on the team sheet.

The reason this score is very relevant is because of what happened in the two T20 matches between New Zealand and India. Each time India had an explosive start, looked good to score 200, tried to score 200 and finished with 162 and 149. Both scores were chased down with ease, although New Zealand were too cautious in the middle overs in the scond T20 and almost threw the match away. They should have won more comfortably with the explosive start set by the openers.

The importance of not aiming for too much cannot be over-emphasized especially in T20 matches. In T20 it is paramount for the captains to understand the nuances of the game. It is possible that Dhoni is aware of this. However his batsmen, Gambhir, Sehwag, Yuvraj, Sharma et al tried to attack without a clear understanding of the par score.

In ODIs, nowadays even scores of 300+ are chased quite comfortably. However even there a reasonable target score should be aimed at. The 100% winning score is 435. However the par Target score might very well be 285. But it must be remembered that data is available for 2822 matches for us to make a facts-based determination of a par Target score for a venue.

Just to sum up the first batting wins. Out of the 34 wins, 8 teams have won by putting up a total of 200 and above, 11 by posting wins of between 180 and 200, 10 by posting between 150 and 180 and 4 have been bowling wins with sub-150 totals. One has been an amazing defence by Ireland of a total of 43 for 7 in a D/L match.

It is impossible to infuse the other Test/ODI parameters such as Ground/Pitch conditions, Team strengths, Average scores et al because of the low number of matches, the absence of any meaningful statistics and the very nature of the game.

Out of the 86 T20 matches, a whopping 34 have been played in South Africa, mainly because of the 2007 WC, in addition to one washed out match. 11 matches have been played in Ireland, in addition to one washed out match. 10 matches have been played in New Zealand. 8 matches have been played in Canada, all in one centre.

Wanderer's has staged the maximum of T20 matches, 16 in all. Just to give the readers an idea of the analyst's nightmare of determining a target score at Wanderer's, I have given below the 16 first innings scores. These seem to move like a yo-yo although there seems to be a recent trend for lower scores.

133, 201, 126, 129, 205, 164, 260, 164, 190, 189, 164, 147, 157, 129, 131 and 118.

Note: I stayed up to watch the interesting T20 match between Australia and South Africa. Australia scored 166 (just passing the par Target score mentioned) and lost a very close match. Strike 1 against me, I suppose.

Important footnote:
This refers to the points raised by Aneesh and Kieran. They have correctly questioned my 90+% figure.
First let me say that the 90+% is based on all instances of chasing team winning, which is 46. Out of these 46, only 4 chases have been of scores of 165 and above. Thus the figure of 90% came in.
However stricly speaking, both Aneesh and Kieran are correct. My sample should be the teams which crossed 165 and not the successful chases. Let me work out that figure below.
26 teams crossed 165 (barring the last Saf-Aus match, which has been excluded for sake of consistency). Out of these, 4 teams lost and the other 22 won. So the winning % is 84 and not 90.
Hence I am going to change my Target score to 170, which would lead to 24 wins and 2 losses (win % of 92).
My thanks to Aneesh and Kieran.

T20 Batsman Strike Rates (Min 200 runs) - (Gokul)

No Batsman        Ctry Mat Runs Balls  S/R  BatAvg

 1 Symonds A       Aus  13  337  198  170.2  56.17
 2 Yuvraj Singh    Ind   9  262  159  164.7  32.75
 3 Gayle C.H       Win   7  261  162  161.1  37.29
 4 Oram J.D.P      Nzl  13  293  187  156.6  36.62
 5 Jayasuriya S.T  Slk  11  341  221  154.3  34.10
 6 Imran Nazir     Pak  10  201  134  150.0  25.12
 7 Sehwag V        Ind  11  223  154  144.8  20.27
 8 Pietersen K.P   Eng  15  375  260  144.2  26.79
 9 Hayden M.L      Aus   9  308  214  143.9  51.33
10 Jayawardene M   Slk  11  210  147  142.8  23.33
11 Duminy J.P      Saf   9  256  181  141.4  32.00
12 Gilchrist A.C   Aus  13  272  192  141.6  22.67
13 Morkel J.A      Saf  15  270  193  139.9  24.55
14 Collingwood P.D Eng  15  344  246  139.8  24.57
15 Masakadza H     Zim   7  258  190  135.7  36.86
16 Aftab Ahmed     Bng   9  215  161  133.5  26.88
17 Ponting R.T     Aus  14  375  283  132.5  34.09
18 Gibbs H.H       Saf  13  225  171  131.5  18.75
19 Shah O.A        Eng  11  241  186  129.5  26.78
20 Taylor R.L      Nzl  17  323  253  127.6  21.53
21 Misbah-ul-Haq   Pak  14  398  312  127.5  56.86
22 Smith G.C       Saf  12  364  286  127.2  36.40
23 Gambhir G       Ind  11  328  259  126.6  29.82
24 Kemp J.M        Saf   8  203  160  126.8  50.75
25 McCullum B.B    Nzl  21  582  464  125.4  34.24
26 Shoaib Malik    Pak  16  383  307  124.7  31.92
27 Younis Khan     Pak  15  260  223  116.5  18.57
28 Styris S.B      Nzl  15  272  240  113.3  19.43
29 Dhoni M.S       Ind  12  215  207  103.8  23.89
30 Salman Butt     Pak  12  266  288   92.3  26.60

	Ian Salisbury: 20 wickets in 15 Tests, at a royal average of 76.95 runs per wicket. Need one say more? © Martin Williamson

I started this thread so I have to finish it. Some readers have suggested that I should look at the worst bowlers in Test cricket the same way I have looked at the worst specialist batsmen. This is a fair request and as Jeff wants, this gives us an opportunity to select what could be termed as the worst team in Test history.

For the batsmen I had a very effective measure, the Batting Position Average, which could be used to identify a specialist batsman, in addition to other measures. We do not have such a measure for bowlers and we have to improvise.

Let me list down the criteria for selection.

1. The bowler must have played in a minimum of 15 Tests.
2. The bowler should have bowled, on an average, a minimum of 150 balls per Test. This excludes casual bowlers.
3. The bowling average should be above 40.00. Fair enough condition.
4. To exclude all-rounders (Hooper/Ramchand et al), bowlers who bat well (Giles/Dharmasena et al) and batsmen who bowl frequently (Richards), the batting average should be below 20.00.
5. I have also excluded bowlers such as Mohammad Rafique, who have a bowling average between 40 and 50 and a difference in average values (bowling average minus batting average) less than 30. There is no way a quality player such as Rafique should get in this collection of incompetents.

This gets us a list of 18 bowlers.

It would be very simple to rank these based on the Bowling Average and that table would as well be enough. However I have done a simple additional analysis of the constituent measures to bring out the level of bowling. The following measures are used.

1. The Bowling Strike rate.
2. The Bowling RpO.
3. The number of wickets captured per Test.

It must be remembered that the Bowling Strike rate and RpO are the two components which form the Bowling Average and I have separated these to let the readers judge the lack of effectiveness.

The formula is given below.

Index=StrikeRate x 0.25 + RpO x 5 + (3.0 - W/T) x 10.

The final table is given below.

Cty Bowler            Mat Balls B/M Wkts  Avge  B/W   RpO  W/T Index 

Eng Salisbury I.D.K    15  2492 166  20  76.95 124.6 3.71 1.33  66.3 
Bng Manjural Islam(Sr) 17  2970 175  28  57.32 106.1 3.24 1.65  56.3 
Bng Tapash Baisya      21  3376 161  36  59.36  93.8 3.80 1.71  55.3 
Nzl Moir A.M           17  2650 156  28  50.64  94.6 3.21 1.65  53.2 
Nzl Cave H.B           19  4074 214  34  43.15 119.8 2.16 1.79  52.9 
Nzl Hayes J.A          15  2675 178  30  40.57  89.2 2.73 2.00  45.9 
Ind Agarkar A.B        26  4857 187  58  47.33  83.7 3.39 2.23  45.6 
Win Powell D.B         37  7090 192  85  47.99  83.4 3.45 2.30  45.1 
Pak Mohammad Sami      33  6984 212  81  51.37  86.2 3.57 2.45  44.9 
Slk Wickramasinghe G.P 40  7260 182  85  41.87  85.4 2.94 2.12  44.8 
Nzl Wiseman P.J        25  5660 226  61  47.59  92.8 3.08 2.44  44.2 
Saf McCarthy C.N       15  3499 233  36  41.94  97.2 2.59 2.40  43.2 
Win McLean N.A.M       19  3299 174  44  42.57  75.0 3.41 2.32  42.6 
Slk Ramanayake C.P.H   18  3654 203  44  42.73  83.0 3.09 2.44  41.8 
Pak Asif Masood        16  3038 190  38  41.26  79.9 3.10 2.38  41.7 
Eng Pocock P.I         25  6650 266  67  44.42  99.3 2.69 2.68  41.4 
Ind Nehra A            17  3447 203  44  42.41  78.3 3.25 2.59  39.9 
Eng Jones I.J          15  3546 236  44  40.20  80.6 2.99 2.93  35.8

Ian Salisbury stays supremely on top with such a huge lead that, whatever be the criteria used, he is unlikely to give up his top position. I am surprised that England could not find a better bowler than Salisbury nor could they have decided that the part-time spin of the much-maligned Hick (incidentally he captured 23 wickets at a much better average of 56.78) was enough. It is also relevant that Tufnell was England's leading spinner during the 1990s and the reason why they kept selecting Salisbury over eight years escapes me.

Then we have a couple of average Bangladeshi bowlers and a trio of average New Zealand bowlers.

The interesting entry then is Agarkar. How he could have played 26 Tests as an all-rounder is one of the mysteries of Indian cricket. I can understand his being selected for 191 ODI matches because he had one of the best strike rates as a bowler in ODIs (288 wickets in 191 matches). But 26 Tests, even conceding the Adelaide contribution, is inexplicable.

I am equally amazed that Mohammad Sami was selected for 33 Tests and captured fewer than 2.5 wickets per Test at a 50+ average. I will not make any comments except that Pakistan has had very competent and effective pace bowlers during this period and it is a surprise that Sami was on for such a long time.

Just to demonstrate the point that the Bowling Average is the most effective of all cricketing measures I have given below the table in decreasing order of Bowling average. Readers will note that there are very few significant changes.

Cty Bowler            Mat  Wkts BowAvge  BatAvge

Eng Salisbury I.D.K    15   20   76.95   (16.73)
Bng Tapash Baisya      21   36   59.36   (11.29)
Bng Manjural Islam(Sr) 17   28   57.32   ( 3.68)
Pak Mohammad Sami      33   81   51.37   (12.05)
Nzl Moir A.M           17   28   50.64   (14.86)
Win Powell D.B         37   85   47.99   ( 7.83)
Nzl Wiseman P.J        25   61   47.59   (14.08)
Ind Agarkar A.B        26   58   47.33   (16.79)
Eng Pocock P.I         25   67   44.42   ( 6.24)
Nzl Cave H.B           19   34   43.15   ( 8.81)
Slk Ramanayake C.P.H   18   44   42.73   ( 9.53)
Win McLean N.A.M       19   44   42.57   (12.27)
Ind Nehra A            17   44   42.41   ( 5.50)
Saf McCarthy C.N       15   36   41.94   ( 3.11)
Slk Wickramasinghe G.P 40   85   41.87   ( 9.41)
Pak Asif Masood        16   38   41.26   (10.33)
Nzl Hayes J.A          15   30   40.57   ( 4.87)
Eng Jones I.J          15   44   40.20   ( 4.75)

Now for the serious task of selecting the worst Test team to be assembled. First let me say that the team will be assembled from the two "worst" tables. Also it will be a balanced team. The incompetency will be spread right through. A team of 11 batsmen with averages exceeding 50 might very well draw all Tests they play while a team with 11 bowlers with averages below 10 might very well dismiss any opposing team cheaply.

I am not able to select a wicket-keeper since keepers have, by definition, been excluded in the two selections. Readers can insert their own keeper. Khaled Mashud is one possibility. I will select 12 players so that the bowlers' selection can be effectively done between spinners and pace bowlers.

I will take the task seriously. Here is my team.

                          Bt/Bw
                          Avge

 1.Nzl Miller L.S.M       13.84 
 2.Eng Brearley J.M       22.89 (Captain)
 3.Aus Bonnor G.J         17.07 
 4.Eng Ikin J.T           20.90 
 5.Bng Alok Kapali        17.70 
 6.Nzl McGregor S.N       19.82 
 7.Wicket keeper
 8.Eng Salisbury I.D.K    76.95
 9.Bng Tapash Baisya      59.36
10.Pak Mohammad Sami      51.37
11.Nzl Moir A.M           50.64
12.Bng Manjural Islam(Sr) 57.32

It is with heavy heart that I have to leave out Javed Omar, Ashraful, Ebrahim, Simmons, Agarkar, Nehra et al. But we are limited to 11 (okay 12) players and I owe it to the readers to select the "best". For bowlers I have almost totally gone on numbers. Brearley could be replaced by one of the New Zealand openers without "strengthening" the team.

Readers should remember that there is no malice in this selection and everything has been done in a lighter vein. Do not come in with serious objections. You are welcome to form your own teams.

	Mohammad Ashraful averages less than 24, and more than 45% of his innings have ended before he has reached ten © AFP

A number of remarks raised in response to my last article on the worst Test batsmen suggested that these poor "batsmen" were in reality bowlers and I should also look at the specialist batsmen to determine who was the worst ever. These comments, led by "Voyager", made a lot of sense and I have completed the study. I must say this is also a fascinating one and my thanks to all who suggested this. I will admit, this specific analysis completely escaped me.

As usual I have set some criteria for selection. Let me outline these first.

1. These should be specialist batsmen. Bowlers (even those who might only have averaged 1-2 wickets per Test) and wicketkeepers have been excluded.

2. A minimum of 25 Test innings should have been played.

3. The Batting Average should be below 20.00 for those who played their entire career before 1925 and below 25.00 for those who played afterwards.

4. The Batting Position Average for the batsman (already presented and discussed by me in these columns) should not be below 6.5. This is to make sure that only specialist batsmen are included. Otherwise bowlers like Kumble, Warne, Vaas et al would come in. The number 6.5 ensures a tilt towards no.6 position than no.7 position.

These entry constraints let 41 batsmen walk under the bar.

Now for the analysis.

I have considered the following three measures for analysis. These are all logical and make sense.

1. The Batting Average, the truest of all measures. The highest weight is given for this measure.

2. The % of single digit scores. This is an improvement on the number of Zeroes I considered earlier and was suggested by Karthik. The lower this % is, the greater credit to the batsman. The range is from 26.7% to 70.0%.

3. The quality of bowling faced. Just in case the less-performing specialist batsmen faced top quality bowling, they have to be given credit. I have also used the weighted bowling average faced, in other words, the exact quality of bowling faced. If Parker faced a Pakistani bowling attack sans Imran, playing, but only as a batsman, this is taken care of. The lower this Average Bowling Quality figure is, the greater credit to the batsman. The range is from 26.6 to 41.5.

The formula is given below.

Index = 
                  (100.0 - Single digit inns %)   (60 - Avge Bowling Quality) 
Batting Average +  ---------------------------  +  -------------------------
                                10                             5

The formula is self-evident. The division by 10 and 5 is to ensure appropriate weights.

Let us look at the tables.

Cty Batsman          Mats Inns NO Runs  HS BPA Batting Scores<10 Bow  Index
                                                Avge    No   %   Qty

Nzl Miller L.S.M      13   25   0  346  47 3.96 13.84   12 48.0% 29.2 25.20
Aus Bonnor G.J        17   30   0  512 128 5.27 17.07   21 70.0% 26.6 26.75
Eng Read J.M          17   29   2  463  57 5.17 17.15   13 44.8% 31.0 28.47
Bng Alok Kapali       17   34   1  584  85 6.06 17.70   13 38.2% 35.8 28.71
Pak Maqsood Ahmed     16   27   1  507  99 4.67 19.50   13 48.1% 33.0 30.08
Nzl Chapple M.E       14   27   1  497  76 4.52 19.12   13 48.1% 31.0 30.11
Aus Horan T.P         15   27   2  471 124 4.00 18.84   12 44.4% 29.4 30.51
Bng Hannan Sarkar     17   33   0  662  76 2.03 20.06   14 42.4% 36.3 30.56
Eng Ikin J.T          18   31   2  606  60 4.81 20.90   12 38.7% 41.5 30.73
Nzl McGregor S.N      25   47   2  892 111 4.11 19.82   18 38.3% 31.6 31.67
Zim Ebrahim D.D       29   55   1 1230  94 2.69 22.78   27 49.1% 39.1 32.05
Zim Gripper T.R       20   38   1  809 112 2.18 21.86   17 44.7% 36.3 32.12
Bng Aminul Islam      13   26   1  530 145 4.31 21.20   10 38.5% 35.5 32.26
Nzl Morgan R.W        20   34   1  734  97 4.82 22.24   16 47.1% 36.3 32.28
Bng Aftab Ahmed       14   27   3  514  82 5.56 21.42   10 37.0% 35.8 32.56
Zim Wishart C.B       27   50   1 1098 114 5.20 22.41   24 48.0% 34.5 32.71
Bng Javed Omar        40   80   2 1720 119 2.12 22.05   33 41.2% 36.1 32.71
Eng Larkins W         13   25   1  493  64 2.72 20.54   10 40.0% 28.9 32.77
Win Morton R.S        15   27   1  573  70 3.89 22.04   13 48.1% 31.9 32.84
Win Simmons P.V       26   47   2 1002 110 2.40 22.27   16 34.0% 36.3 33.60
Nzl Morrison J.F.M    17   29   0  656 117 2.55 22.62   13 44.8% 31.6 33.81
Nzl Bell M.D          18   32   2  729 107 2.16 24.30   17 53.1% 35.6 33.86
Bng Mohammad Ashraful 48   93   4 2125 158 4.59 23.88   42 45.2% 35.1 34.35
Nzl Franklin T.J      21   37   1  828 101 2.00 23.00   10 27.0% 39.1 34.47
Aus Richardson V.Y    19   30   0  706 138 4.97 23.53   13 43.3% 33.5 34.51
Eng Athey C.W.J       23   41   1  919 123 3.22 22.98   16 39.0% 32.4 34.60
Zim Rennie G.J        23   46   1 1023  93 2.89 22.73   16 34.8% 32.9 34.68
Nzl How J.M           18   34   1  771  92 2.00 23.36   10 29.4% 38.7 34.68
Nzl Murray B.A.G      13   26   1  598  90 2.00 23.92   11 42.3% 34.4 34.81
Nzl Pocock B.A        15   29   0  665  85 2.00 22.93   10 34.5% 32.3 35.02
Eng Brearley J.M      39   66   3 1442  91 3.12 22.89   23 34.8% 31.7 35.06
Pak Asif Mujtaba      25   41   3  928  65 4.46 24.42   15 36.6% 37.7 35.23
Bng Al Sahariar       15   30   0  683  71 2.80 22.77    8 26.7% 34.3 35.25
Eng Knight N.V        17   30   0  719 113 3.70 23.97   11 36.7% 34.8 35.35
Win Griffith A.F.G    14   27   1  638 114 2.00 24.54   12 44.4% 32.2 35.64
Pak Mathias W         21   36   3  783  77 5.81 23.73   12 33.3% 32.8 35.83
Win Smith D.S         28   49   2 1165 108 2.31 24.79   16 32.7% 36.2 36.29
Saf Cheetham J.E      24   43   6  883  89 5.74 23.86   13 30.2% 32.2 36.41
Nzl Parker J.M        36   63   2 1498 121 3.67 24.56   24 38.1% 30.6 36.62
Win Williams S.C      31   52   3 1183 128 2.29 24.14   14 26.9% 33.0 36.84
Pak Kardar A.H        23   37   3  847  93 6.16 24.91   12 32.4% 32.8 37.12

Lawrence Miller is an unknown name but is going to become quite well-known, one suspects. He barely gets in having played 25 innings. He played between 1953 and 1958. To boot, he batted in the middle order to start with but opened in the last six Tests. I am amazed that New Zealand cricket was at such a low ebb that they could not replace a batsmen who did not go past 50 in 13 Tests, had a single digit score in half the innings he played (and bowled a total of 2 balls). However I must mention that his top score of 47 helped New Zealand secure their first ever Test win against West Indies. Also that Miller faced good quality bowling almost always.

George Bonnor and John Read played duriing the first few years of Test cricket. Bonnor was more successful with a century and two 50s. Their averages of around 17 should be considered to be slightly higher in view of the time they played in. I have not done any average adjustment.

Now comes the interesting part. Couple of average Bangladeshi batsmen follow them. Some reader mentioned Jack Ikin. He finds a place in the top 10. It can be seen that the bowling he faced was very average quality, the post-war Indians, New Zealanders and West Indian bowlers.

Note how high Mohammad Ashraful and Javed Omar are in the table. They have also played a huge number of Tests. To be the premier batsmen of a modern team and average around 23 reflects the state of Bangladeshi cricket. What is also galling is the high % of single digit dismissals by both these batsmen, both above 40%.

As expected, Mike Brearley takes his place in this table in the lower half. That too because he crossed 10 a few times more than other batsmen and also faced very good bowling almost always.

What surprises me is the presence of Jamie How in this table. For How to be given 18 Tests in today's situation is quite surprising.

New Zealand has most entries in this table, 11. Bangladesh follows with 7. Surprisingly England has a few recent batsmen, viz., Athey, Brearley, Knight and Larkins in this list. Similarly West Indies has Morton, Simmons, D.S.Smith and Williams present. Pakistan has four players incluyding Asif Mujtaba. A.H.Kardar just about makes the list. He captained Pakistan during the difficult early days.

How, along with Pollard, Franklin, Murray are the New Zealanders in this list who have opened, quite unsuccessfully, in all the Tests they have played. The only other ever-present opener is Griffith of West Indies. Martin Bell should also have been there. However he played once in the no.7 position.

Note the absence of a single Indian in this list. For the record, the worst Indian specialist batsman is Eknath Solkar, with an average of just over 25, since his tally 18 wickets in 27 Tests is quite low. But his extraordinary fileding should give him the all-rounder status. As such the crown should go to Ashok Mankad, with an average of around 26, followed by Arun Lal.

For that matter the only Australians are the pre-1930. The nearest a modern Australian comes in is John Dyson, with an average just over 26.