This article is dedicated to Muralitharan, arguably the greatest but certainly one of the greatest of all Test bowlers. I will not be doing any comparisons with other bowlers, that will be done in a later article. I will probably select all the other top bowlers to do a comparison. In this article, as a mark of appreciation and admiration for this wonderful bowler and person, I will do comparisons only within his own career. I would appreciate if readers remember this view and no negative comments are made on one of the greatest ever. Let us leave that task to Mr Bedi and umpires whose sole claim to fame will be to act as nothing more than mere historical footnotes in his legendary career. I hope the reader will pardon this moment of strong feeling on my part. But it comes in disgust at the horrendous treatment to a great bowler, who took it in the most gentlemanly way and came through a stronger man. My own personal feelings apart, I hope to highlight Murali's achievements through numbers.

Muralitharan's career is analysed from many points of view. Some of these tables might be available elsewhere but a few are quite new and are being done for the first time. The Wikipedia entry on Muralitharan incidentally is full of very useful and nice-to-know facts. The summary file containing all these tables is available at the end for viewing/downloading. I have stayed away from tables on country performances since that is often shown on television screens and I have to keep this article to reasonable size. Anyhow Murali is the only bowler to have captured 50+ wickets against all Test-playing countries and three of these are 100+ wickets. Also this article covers only Murali's Test performances.

1. Career summary

Tests played:     133
Wickets captured: 800 
Wickets/Test:     6.02
Runs conceded:    18180
Overs bowled:     7340.0
Bowling average:  22.73
Strike rate:      55.0
Runs/over:        2.48
10 wkts in match: 22 (4 in consecutive tests, that too twice, and against all 9 
countries).
5 wkts in Inns:   67
Maidens bowled:   1792
Maidens %:        24.4
Best bowling:     40.0-19-51-9 (the first 9 wickets !!!). There is another 
9-wkt haul.
Fielder combination: 77 (Murali/Jayawardene - highest for non wicket-keeper).

This has been given just to provide a starting point. And what a starting point !!! What does one say.

- Let us not forget the 508 ODI wickets, again the leading ODI bowler of all time. He and Tendulkar lead both forms of cricket in terms of wickets and runs respectively.
- 800 wkts for Sri Lanka is followed by Vaas with 355 and Jayasuriya/Malinga with 98.
- 92 wickets ahead of the next bowler, Warne, and 181 wickets ahead of the third placed bowler, Kumble.
- A wickets/Test figure comparable to the best pre-war bowlers who bowled on uncovered wickets.
- A spinner with a bowling average that is normally expected of a fast bowler.
- A spinner with a fast bowler's strike rate.
- A tally of 10 wickets per match which is more than double that of the next placed bowler.
- A 5 wickets per innings count nearly double of the next.
- A quarter of overs bowled have been score-less.

Muralitharan is the nearest a bowler has come to Bradman, the batsman. It is safe to conclude that Bradman's batting average and Murali's tally of Test wickets are the two landmarks which are never likely to be broken. In terms of the overall impact Muralitharan has had on Sri Lankan cricket, I place him no less than Bradman as a cricketer.

2. Dismissals analysis

Batsmen early dismissals: 145 - 18.1% of Career wkts

Batsmen 50+ average :      60 -  7.5% of Career wkts
Batsmen 40+ average :     152 - 19.0% of Career wkts
Batsmen 30+ average :     157 - 19.6% of Career wkts
Batsmen 20+ average :     184 - 23.0% of Career wkts
Batsmen 20- average :     247 - 30.9% of Career wkts

Top order batsmen :       280 - 35.0% of Career wkts
Middle order batsmen :    260 - 32.5% of Career wkts
Late order batsmen :      260 - 32.5% of Career wkts

Unassisted dismissals :   352 - 44.0% of Career wkts
Assisted dismissals :     448 - 56.0% of Career wkts.

This is an analysis of the individual dismissals.

The first entry refers to the number of dismissals of batsmen well before they are set. This is a variable analysis in that I have selected only dismissals of batsmen at scores 25 or more runs below their batting average. Tendulkar at scores of below 31, Ponting at scores below 30, Lara at scores below 27, Langer at scores below 21, McCullum at scores below 10 and so on.

Next is an analysis of all dismissals from the point of view of dismissed batsman's batting average. Over a quarter of Muralitharan's dismissals have been of genuine batsmen with 40+ averages. Just over 30% of his dismissals have been of less talented batsmen, understandable in view of the inability of these batsmen to read Murali.

The third grouping refers to the batting position rather than batting average. This is especially relevant against the minnows many of whose top order batsmen would have batting averages of around 20-30.

The last grouping is a split by type of dismissal. Bowled, Lbw and Return catch fall into the first entry and the other dismissals, the next entry. For 44% of the dismissals, Murali did not depend on others, barring the umpires for Lbws. It was appropriate that the last and 800th wicket was a Muralitharan-Jayawardene combination.

3. Innspells analysis

Career :       133 800 6.02 18180 44040 22.73        2.48

Home :          73 493 6.75  9646 25062 19.57 116.1% 2.31 107.3%
Away :          60 307 5.12  8534 18978 27.80  81.8% 2.70 107.3%

First inns :   133 458 3.44 10968 26527 23.95  94.9% 2.48  99.8%
Second inns :  129 342 2.65  7212 17513 21.09 107.8% 2.47 100.2%

Top teams :    108 624 5.78 15523 36606 24.88  91.4% 2.54  97.3%
Minnows :       25 176 7.04  2657  7434 15.10 150.5% 2.14 115.5%

Career 1 half:  67 356 5.31  8804 21955 24.73  91.9% 2.41 102.9%
Career 2 half:  66 444 6.73  9376 22085 21.12 107.6% 2.55  97.2%

Team wins :     54 438 8.11  7088 18726 16.18 140.4% 2.27 109.1%
Team draws :    30 112 3.73  3500  9099 31.25  72.7% 2.31 107.3%
Team losses :   49 250 5.10  7592 16215 30.37  74.8% 2.81  88.2%

Innspells:     227  Productive innspells: 218  (96.0%)

This analysis has as the base, the complete innspell.

As with most bowlers, Murali's home performance is about 40% better than his away performance. However let us not forget that Murali's away performances fall short only by the high standards he himself has set. He has captured 5.1 wickets per Test, away, and has averaged 27.12, both higher than any other contemporary bowler.

Murali's second innings performances are about 16% better than his first innings. However his bowling accuracy has been almost the same in both innings.

Now we come to an important split. Against the minnows, Zimbabwe and Bangladesh, Murali has averaged 7+ wickets per Test (higher than the highest ever), averaged 15 (150% of his career average) and captured nearly 25% of his total tally of wickets. His performances against the minnows is over 60% better than the performance against the top teams.

Murali had two halves of his career as different as chalk and cheese. In almost every measure the second half was around 15-25% better than his first half. The only measure where he has performed better in the first half is in his accuracy.

Murali's contributions in Sri Lanka's wins are out of the world, nearly twice as good as the ones in drawn and losing matches. His wickets per winning Test was an amazing 8+ at an average of 16.

A single fact is sufficient to put Muralitharan's contribution in Sri Lankan wins in perspective. In the 38 Tests Sri Lanka played before Muralitharan's debut, they won 2 Tests. Subsequently in 133 Tests Muralitharan played in, Sri Lanka won 54 Tests. There has never been a more widely varying statistic. 5.3% before compared to 40.6% afterwards. Of course Ranatunga, Vaas, Aravinda De Silva, Jayawardene, Sangakkara et al have played their part. However the leading person in this revival is Muralitharan.

I have used my definition of consistent bowling to do a simple calculation. Any innspell in which Murali bowled more than 10 overs is considered as a considered innspell. Out of these I have considered any spell in which he has gone at least one wicket as relevant ones. His effectivity index was an astounding 96%. In only 9 spells, out of 227, has he gone wicketless.

4. Best & Worst periods

Best year :             90 (2006)

Worst year :            14 (1996)

Best 10-match streak :  89 (1802-1839)

Worst 10-match streak:  29 (1265-1319)

These figures are self-explanatory. 2006 was the golden year for Murali and a decade back, during 1996, he had the worst year, no doubt caused by the Australian accusations. Two ways of looking at what happened in 1996 and afterwards. He might have captured well over 800 wickets. Or, more likely, he steeled within because of the blatantly unfair accusations and performed much better.

5. Share of team wickets

Overall:       800  Team - 2065  Share - 38.7%

Home :         493  Career % - 61.6  Team - 1240  Share - 39.8%
Away :         307  Career % - 38.4  Team -  825  Share - 37.2%

First inns :   458  Career % - 57.2  Team - 1239  Share - 37.0%
Second inns :  342  Career % - 42.8  Team -  826  Share - 41.4%

Top teams :    624  Career % - 78.0  Team - 1598  Share - 39.0%
Minnows :      176  Career % - 22.0  Team -  467  Share - 37.7%

Career 1 half: 356  Career % - 44.5  Team -  967  Share - 36.8%
Career 2 half: 444  Career % - 55.5  Team - 1098  Share - 40.4%

Team Wins :    438  Team - 1070  Share - 40.9%
Team draws :   112  Team -  354  Share - 31.6%
Team losses :  250  Team -  641  Share - 39.0%

Muralitharan's overall share of team wickets is 38.7. This figure is exceeded slightly at home and below away. In the second innings his share moves up considerably to 41.5%. Against the minnows the others have also reaped the rewards. His career jump during the second half of his career is reflected in the share of team wickets also. Finally he has captured over 41% of the team wickets in won matches for Sri Lanka. A peculiar feature has emerged here. Muralitharan's share in drawn matches is way below his share in won or lost matches.

To view/down-load the complete table, please click/right-click here.

6. Into the crystal ball

Finally a note on whether Murali's tally of wickets would ever be surpassed. It was only Murali's innate goodness and hospitable nature which prompted him to say that Harbhajan is the only bowler capable of overhauling him. The truth is that there is probably less than 1% chance that Murali's record would be broken. I think Warne is right in saying that his record will stand forever. The relevant numbers, based on career performances and extrapolations on continuing their performances forever, are given below.

Harbhajan (12y/84t/355w) would take another 15 years and 105 Tests to go past Murali. He would be 45 by that time and would probably be enjoying a settled family life, not bowling doosras and teesras. 600 seems to be Harbhajan's limit.

Steyn (6y/41t/211w) would take another 16 years and 114 Tests to overtake Murali. Steyn, despite (or because of) his awesome strike rate, would have hung up his boots well before that time. For Steyn, 500 seems to be the pinnacle.

A new bowler making his debut next month would have to play 160 Tests over 20 years, in view of the ODIs, T20s and IPL-type jamborees, and maintain 5 wickets per Test. That is the 1% I have talked about earlier.

Other bowlers like Kallis and Vettori would probably require another 20 years and 200 Tests to reach 800. By that time, a son Vettori might very well be playing for New Zealand.

If there are any other analyses which could be done on Muralitharan's career, I invite readers to mail their suggestions. Let me also mention here that I have done this program as a general purpose one and could easily do that for all bowlers. That is what I would do in my follow-up analysis comparing the key measures of the top bowlers.

My only regret is that I wish Murali had chosen to play more Tests and cut down on ODIs and IPL. However the lure of IPL was probably too much of an attraction.

7. Muralitharan as a batsman

Muralitharan as a batsman was a very effective, entertaining and unorthodox no.11. His overall batting figures (1261 at 11.68) might not be very impressive. However he has played many a good potentially match-winning and match-saving innings, both in Tests and ODIS, as chronicled below. This is not necessarily a complete list.

Tests

- 26 against New Zealand in 1998.
- 22 against Pakistan in 2000.
- 43 against Australia in 2004.
- 36 against West Indies in 2005.
- 33 against England in 2006.

ODIs (both innings during 2009)

- 33 in 16 vs Bangladesh, who scored 152 and Sri Lanka were 114 for 8. 
           Murali took them to 153 for 8. 
- 32 in 15 vs Pakistan.

A final salute to the wonderful bowler and human being that Muralitharan is. There will never be a bowler like him. And the people of Sinigama, where he has helped build 1000 houses for the tsunami victims, will say that there has never been a human being like him.

In my first column for It Figures, I took a look at innings-to-innings consistency among batsmen, and reached the conclusion that, on balance, it appears to be a good thing. This time around, I've performed an analysis looking at bowlers. My methods are identical, with particular reliance on the coefficient of variation (CoV) as an estimator of consistency; please see my previous post for full details.

At the outset, it should be noted that bowling stats present a small problem. Whereas our primary concern about batsmen is how many runs they score, we tend to be interested in two things with bowlers: how many wickets they take and how many runs they concede (and, of course, the standard measure by which we judge them – the bowling average – is a quotient of the two). The problem is that it is only straightforward to observe the innings-to-innings variability of one or other of these measures at a time. For the purposes of this analysis, then, I have just relied on wickets taken.

In a way, this is helpful: although it's not a stat on which we tend to focus much attention, wickets-per-innings (WPI) is the direct equivalent of runs-per-innings (or, give or take a little adjustment for not-outs, the batting average). It is also a good, sensible measure to use to think about bowling consistency: I hope most readers would agree that a bowler who takes 5/95, 5/176, and 5/23 in consecutive innings conforms more closely to our intuitive sense of bowling consistency than one who takes 1/30, 6/180, and 2/60, even though the latter took his wickets at an identical cost in each innings.

There are some fairly good reasons why WPI is a seldom-seen stat, however. The biggest problem is that it might be heavily influenced by factors over which the bowler has no control. You might be the finest bowler in your team but, unless your captain believes that, he won't ask you to bowl much and you won't take many wickets. Moreover, if the teammates with whom you share the ball are good bowlers, they are liable to take plenty of wickets, themselves, thereby depleting the finite number of scalps left for you to claim. (Pelham Barton has made the excellent point that batting in a team of good batsmen increases your opportunity to score runs, whereas bowling in a team of good bowlers reduces your opportunity to take wickets.) For these reasons, it might be argued that WPI tells us as much about the other players in a team as it reveals about the one in whom we're interested. This is fair enough: I have to acknowledge that a bowler might have a more or less consistent record for reasons for which he cannot, himself, take all the credit or blame, but that's a way to explain differences, rather than a rationale for assuming they don't exist.

Test consistency

There's a familiar name at the top of the most consistent bowlers list (Table 1). Unless something remarkable happens in his final game, Muttiah Muralitharan will retire not only as Test cricket's most prolific wicket-taker, but also as its most consistent. He has taken between 2 and 5 wickets in over two-thirds of the Test innings in which he has bowled, and his remaining analyses are fairly evenly divided between more and less successful returns. It is predictable that these characteristics would be reflected in an exceptionally low CoV.

Joel Garner may be an example of the type of bowler whose WPI is constrained by formidable competition for the scarce resource of opposition wickets. Seeing as he took at least 4 wickets in an innings 25 times, it's hard to imagine that he wouldn't have managed more than 7 fiver-fers if wickets hadn't invariably been tumbling at the other end, too.

In the upper reaches of a list that is dominated by some very high-class bowlers, Darren Gough's name may look a tiny bit out of place, but his low CoV is testament to his dependability at a time when his country's attack sorely needed it.

Table 1: Test bowlers sorted according to consistency (coefficient of variation) in wickets-per-innings

	Name	M	I	W	Ave	W/I	SD	CoV
1.	M Muralitharan	131	226	787	22.66	3.48	1.87	0.537
2.	CTB Turner	17	30	101	16.53	3.37	1.89	0.561
3.	DW Steyn	41	75	211	23.13	2.81	1.66	0.591
4.	WJ O'Reilly	27	48	144	22.60	3.00	1.78	0.593
5.	R Peel	20	35	101	16.98	2.89	1.75	0.607
6.	J Garner	58	111	259	20.98	2.33	1.44	0.615
7.	CV Grimmett	37	67	216	24.22	3.22	2.01	0.622
8.	D Gough	58	95	229	28.40	2.41	1.53	0.633
9.	SF Barnes	27	50	189	16.43	3.78	2.41	0.638
10.	AA Donald	72	129	330	22.25	2.56	1.65	0.644
	...
12.	DK Lillee	70	132	355	23.92	2.69	1.79	0.665
	...
15.	MD Marshall	81	151	376	20.95	2.49	1.71	0.687
16.	B Lee	75	148	308	30.71	2.08	1.44	0.690
	...
19.	A Kumble	132	236	619	29.65	2.62	1.84	0.700
20.	SK Warne	144	271	702	25.53	2.59	1.82	0.701
21.	RJ Hadlee	86	150	431	22.30	2.87	2.02	0.702
	...
26.	FS Trueman	67	127	307	21.58	2.42	1.78	0.737
	...
30.	GD McGrath	123	241	560	21.69	2.32	1.73	0.746
31.	SM Pollock	108	202	421	23.12	2.08	1.56	0.747
	...
33.	Wasim Akram	104	181	414	23.62	2.29	1.73	0.754
	...
38.	CEL Ambrose	98	179	405	20.99	2.26	1.72	0.758
	...
40.	Waqar Younis	87	154	373	23.56	2.42	1.84	0.761
41.	Imran Khan	88	142	362	22.81	2.55	1.94	0.763
42.	CA Walsh	132	242	519	24.45	2.14	1.64	0.765
	...
79.	IT Botham	102	168	383	28.40	2.28	1.92	0.844
	...
86.	GA Lohmann	18	36	112	10.76	3.11	2.66	0.856
	...
102.	JC Laker	46	86	193	21.25	2.24	2.00	0.891
	...
122.	Kapil Dev	131	227	434	29.65	1.91	1.81	0.946
123.	DL Underwood	86	151	297	25.84	1.97	1.86	0.946
	...
125.	GS Sobers	93	159	235	34.04	1.48	1.40	0.950
	...
140.	JG Bracewell	41	67	102	35.81	1.52	1.61	1.061
141.	JH Kallis	139	230	265	31.57	1.15	1.23	1.067
142.	AW Greig	58	93	141	32.21	1.52	1.62	1.071
143.	N Boje	43	72	100	42.65	1.39	1.52	1.097
144.	RJ Shastri	80	125	151	40.96	1.21	1.34	1.110
145.	MA Noble	42	71	121	25.00	1.70	1.93	1.133
146.	R Illingworth	61	100	122	31.20	1.22	1.43	1.168
147.	TE Bailey	61	95	132	29.21	1.39	1.68	1.210
148.	W Rhodes	58	90	127	26.97	1.41	1.81	1.285
149.	CL Hooper	102	145	114	49.43	0.79	1.15	1.457
qual. 100 Test wickets; complete list available here

I picked Derek Underwood out in the list because, of bowlers with any sort of reputation, he has one of the highest CoVs, indicating a less consistent innings-to-innings record. This comes about because there is a bit of a feast-or-famine profile to his Test wicket-taking. He took no more than one wicket in over half of the innings in which he bowled, but he also bagged 17 five-fers. Like the batsman who swings between cheap dismissals and big hundreds (remember Vinoo Mankad?), Deadly's record suggests that he could be inspirational or ineffectual in equal measure. His famous unplayability in particular conditions (above all, on drying wickets) might partly explain this finding.

In the main, the bowlers at the bottom of the list are allrounders and/or not especially penetrative spinners of the kind used to "tie up one end". This probably isn't a great surprise, since bowlers of these types are likely to take relatively few wickets in most of their innings (remember that, in these analyses, a bowler who takes 0, 0, 2, 1, & 0 wickets in consecutive innings is judged to be less consistent than one who takes 4, 4, 6, 5, & 4, even though the absolute variability within those hauls is identical). In addition, when these bowlers turn in a significant performance (as they all at least occasionally do), it stands out in much greater contrast from their typical level of achievement, and their SDs – and, consequently, CoVs – are increased. If a bowler with a WPI of 1 records a 5-wicket haul, that's 500% of his typical performance; for a bowler with a WPI of 2.5, the same feat would only be 200% of his norm.

The upshot is that there are a lot of good bowlers at the top of the list, and progressively fewer as consistency declines. As a result, it is no surprise to find a relatively pronounced correlation between CoV and bowling average (r ²=0.322; p<0.001). This relationship is illustrated in Figure 1; you can see that a substantial majority of bowlers who average under 30 have a CoV of less than 1.

Figure 2 shows the typical relationship between CoV and win-rate, with bowlers with the most consistent wicket-taking records apparently benefitting from a very slightly increased probability of victory, although the association is not an especially dramatic one (r ²=0.043; p<0.001).

There's an interesting twist in this story, though. You may recall that, when I looked at the same relationship for Test batsmen, I found that CoV was less strongly related to winning percentage than it was to not-losing percentage. This finding was explained by the fact that consistency is also associated with drawing rate (i.e. consistent batsmen are a bit more likely to win and a bit more likely to draw, with the net result that they're a fair bit less likely to lose). This phenomenon is not repeated amongst bowlers; in fact, something rather different is going on. The first thing I noticed was that, unlike their willow-wielding counterparts, more consistent bowlers are no less likely to lose matches (r ²<0.001; p=0.866). That, I thought, must mean there's something going on with drawn games that cancels out the benefit of consistency for winning. And that is exactly what proved to be the case: in a complete reversal of the situation for batsmen, the most consistent bowlers are less likely to draw Test matches (r ²=0.050; p<0.001). The only sensible way of explaining this, as far as I can see, is that consistent batsmen help their sides to draw matches they might otherwise have lost, whereas consistent bowlers help their sides to win matches they might otherwise have drawn.

ODI consistency

When I produced stats for the most consistent ODI wicket-takers, there were two unexpected names at the top of the list (Table 2).

I have to confess that I hadn't previously realised quite how good Chris Pringle's ODI bowling statistics are generally (for example, he amassed over 100 wickets at an average better than, say, Botham's or Marshall's or Imran's). What the current analysis emphasises is the way in which he achieved that record – namely, by chipping in dependably just about every time he played. His captains could invariably rely on him to contribute a dismissal or two (he went wicketless in just 10 of the 64 ODIs in which he bowled), though they couldn't really hope for many more (he only managed a four-fer or better on just three occasions). Similarly – in a career that has been anything but stable due to his terrible luck with injuries – Pringle's compatriot Kyle Mills has managed to piece together an admirably consistent wicket-taking record in ODIs. He has taken between 1 and 3 wickets in over three-quarters of his games. It is often said of New Zealand's ODI side of the last couple of decades that they have punched above their weight – that their players manage to play to something like their full ability in a reliable fashion, even if the fundamental level of that ability is perceived to be less than that seen in more glamorous teams. This analysis appears to provide a little support for that notion, if Pringle's and Mills's records are anything to go by (and Shane Bond isn't far behind).

Table 2: ODI bowlers sorted according to consistency (coefficient of variation) in wickets-per-innings

	Name	M	I	W	Ave	WPI	SD	CoV
1.	C Pringle	64	64	103	23.87	1.61	1.15	0.717
2.	KD Mills	108	109	162	26.46	1.49	1.11	0.744
3.	AA Donald	164	162	272	21.79	1.68	1.26	0.748
4.	B Lee	183	179	317	23.18	1.77	1.33	0.750
5.	CJ McDermott	138	138	203	24.72	1.47	1.13	0.769
6.	SK Warne	193	190	291	25.82	1.53	1.18	0.769
7.	MG Johnson	81	80	128	25.72	1.60	1.23	0.769
8.	Saqlain Mushtaq	169	165	288	21.79	1.75	1.36	0.779
9.	DW Fleming	88	88	134	25.39	1.52	1.19	0.779
10.	DK Lillee	63	63	103	20.83	1.63	1.28	0.781
	...
12.	SE Bond	78	80	147	20.88	1.84	1.45	0.791
	...
15.	SCJ Broad	65	65	109	25.76	1.68	1.34	0.797
	...
19.	IT Botham	116	115	145	28.54	1.26	1.01	0.804
20.	D Gough	158	155	234	26.30	1.51	1.21	0.805
21.	M Muralitharan	326	322	504	23.07	1.57	1.26	0.805
22.	GD McGrath	245	245	377	22.06	1.54	1.25	0.812
	...
26.	J Garner	98	98	146	18.85	1.49	1.23	0.826
27.	Shoaib Akhtar	142	141	221	23.64	1.57	1.31	0.833
	...
32.	A Kumble	269	263	334	30.84	1.27	1.09	0.855
33.	A Flintoff	138	116	168	23.62	1.45	1.24	0.857
	...
36.	Kapil Dev	225	221	253	27.45	1.14	1.00	0.870
	...
44.	Wasim Akram	356	351	502	23.53	1.43	1.27	0.885
	...
47.	Waqar Younis	262	258	416	23.84	1.61	1.43	0.890
	...
49.	RJ Hadlee	115	112	158	21.56	1.41	1.26	0.891
50.	SM Pollock	294	291	387	24.31	1.33	1.19	0.893
	...
52.	Harbhajan Singh	209	201	238	32.97	1.18	1.06	0.896
	...
56.	Imran Khan	175	153	182	26.62	1.19	1.11	0.936
57.	CEL Ambrose	176	175	225	24.13	1.29	1.21	0.940
58.	WPUJC Vaas	321	319	399	27.46	1.25	1.18	0.945
	...
60.	MD Marshall	136	134	157	26.96	1.17	1.11	0.947
	...
85.	JH Kallis	298	261	250	32.12	0.96	1.04	1.090
	...
93.	ST Jayasuriya	440	364	319	36.65	0.88	1.10	1.257
94.	IVA Richards	187	131	118	35.83	0.90	1.16	1.286
95.	SB Styris	165	144	125	34.95	0.87	1.12	1.290
96.	WJ Cronje	188	153	114	34.79	0.75	0.97	1.307
97.	Azhar Mahmood	142	139	123	39.13	0.88	1.17	1.322
98.	PA de Silva	308	156	106	39.41	0.68	0.90	1.323
99.	GW Flower	219	154	104	40.26	0.68	0.95	1.411
100.	PD Collingwood	182	139	103	38.86	0.74	1.05	1.414
101.	SR Tendulkar	442	267	154	44.27	0.58	0.95	1.641
102.	SC Ganguly	308	170	100	38.35	0.59	1.00	1.706
qual. 100 ODI wickets; complete list available here

Again, the lower reaches of the table are dominated by bits-and-pieces players, who might provide occasional match-altering spells (even Ganguly and Tendulkar each have two ODI five-fers under their belts), but are more commonly asked to use up overs (17 of the bottom 20 contribute fewer than one wicket per ODI).

Gough – along with three Australian heroes in the assorted shapes of Dennis Lillee, Shane Warne, and Brett Lee – makes the top 20s of both lists, but there's one player who ranks among the 10 most consistent for both Tests and ODIs, and that's Allan Donald. His skipper could reliably expect over 2½ wickets per test innings and 1⅔ scalps per ODI from him. Maybe that doesn't sound like much, but it's equivalent to saying that – match-in, match-out – Donald could be depended upon to contribute his share of opposition wickets, and probably somewhat more, whenever he took the ball (and regardless of whether that ball was red or white).

There's a very pronounced correlation between CoV and ODI bowling average (r ²=0.557; p<0.001), with increasing inconsistency obviously reflected in increasing averages (Figure 3). This association is a bit stronger than we saw in Test bowling figures. One possible explanation is that, because the amount of bowling available to any one bowler is constrained in ODIs (usually to 10 overs), WPI becomes a purer measure of a bowler's contribution, and consistency in this measure becomes a more direct index of out-and-out quality with the ball. One way or another, though, it's very clear that better ODI bowlers tend to be more consistent ODI bowlers.

The relationship between bowling consistency and ODI win-rate (Figure 4) is not quite as obvious, though it certainly appears that bowlers with lower CoVs tend to be more likely to win their games (r ²=0.034; p=0.007).

Conclusions

To at least as marked a degree as we saw with batsmen, consistent bowlers appear to be worth having on your team. And it can't be a surprise to learn that the bowlers who take wickets most dependably tend to be those with the lowest averages.

However, we have to be careful with our conclusions, this time. It may be that good bowlers with low averages are asked to bowl more, so they end up taking wickets more consistently. Perhaps less good bowlers would take wickets with equal consistency – though not as high frequency – given the opportunity. In this way, the fact that allrounders and certain types of spin bowlers have the least consistent WPI records may reflect the ways in which they are used as much as it reveals anything fundamental about the bowlers themselves (this takes us back to general concerns about the meaningfulness of WPI as a stat). For instance, we can assume that, if he batted like Chris Martin, Jacques Kallis would have been asked to take a greater share of South Africa's bowling, over the years. Had that been the case, he would surely have taken more wickets, and he would probably also have taken wickets more consistently. His record would not have been so dominated by 0- and 1-wicket innings (69% of his Tests and 72% of his ODIs fall into this category), and his significant wicket-taking bursts would have been much less occasional. As a result, we would expect him to climb the consistency table – perhaps markedly so. But, just because we think we can explain Kallis's relatively inconsistent record, that doesn't mean that his record is, in some way, actually more consistent than we're giving him credit for.

The relationship between consistency and winning is similar for bowlers as we saw for batsmen (although the finding that consistent bowlers draw fewer Test matches is an interesting one). Again, I tend to conclude that, in both forms of the game, teams benefit from dependable – though not necessarily dazzling – contributors at least as much as they do from hit-or-miss performers. However, the overall range of variation is somewhat narrower amongst bowlers: it appears that, while there really is such a thing as a ton-or-bust batsman, bowlers who are capable of significant hauls but commonly contribute little are altogether rarer beasts.

All stats calculated Jul 04, 2010 (i.e. all Tests up to West Indies v South Africa at Bridgetown, Jun 26-29, 2010 [Test # 1962] and all ODIs up to England v Australia at Lord's, Jul 3, 2010 [ODI # 3011]).

---

Technical appendix

(Some notes on my methods, for anyone who's almost as dull as me. Everyone else can stop reading now.)

Technical note #1. All regressions are limited to bowlers with at least 50 wickets. I'd have preferred to use fuller datasets, but they're just too noisy (probably due to the phenomenon of the truly occasional bowler).

Technical note #2. As last time, I performed a multivariate regression on these data. For both forms of the game, I regressed CoV against average, winning percentage, and an interaction term. In each instance, the only significant covariate was average (p<0.001). This suggests that the reason more consistent bowlers win more Test matches and ODIs is that they average less: there is no independent effect of consistency on winning.

Technical note #3.I said in my introduction that there is no straightforward way of measuring variability in wickets taken and runs conceded simultaneously. I can think of quite complicated ways, though. One approach would be to use a Poisson regression model, with wickets as events considered against an exposure variable of runs conceded. Such an analysis is a little beyond the scope of this kind of column, and I have some reservations about the strict applicability of the paradigm. Nevertheless, if anyone's remotely interested, I might try to find a moment to do explore this sort of approach.

... © Getty Images

Wides and no-balls are the bane of the bowlers in Twenty20 matches. Not to forget the additional (unrecorded) runs scored off possible free hits. This article analyses the wides and no-balls bowled by bowlers in Twenty20 internationals. I have specifically considered only Twenty20 internationals and excluded IPL matches, which I do not consider as true internationals. The basic criteria is that the bowlers should have bowled a minimum of 120 balls, which works to no less than 5 Twenty20 International matches. 1. Bowlers who have conceded the most number of wides and no-balls

No Bowler             Ctry Mat  Overs Wides NBs Total
                                                 W+Nb

 1 Malinga S.L         Slk  28   94.0   35   2    37
 2 Umar Gul            Pak  26   93.2   25  11    36
 3 Johnson M.G         Aus  21   77.1   32   4    36
 4 Sohail Tanvir       Pak  15   51.0   26  10    36
 5 Steyn D.W           Saf  21   78.0   29   2    31
 6 Tait S.W            Aus  15   55.4   30   1    31
 7 Anderson J.M        Eng  18   66.2   29   0    29
 8 Lee B               Aus  16   58.1   13  14    27
 9 Roach K.A.J         Win  10   35.0   20   5    25
10 Broad S.C.J         Eng  26   89.5   17   5    22

Lasith Malinga of Sri Lanka has bowled the maximum number of wides and no-balls. with 37. Umar Gul, Johnson and Sohail Tanvir come in next with 36 wides and no-balls. In fifth place in this list is Steyn with 31.

It is not a surprise that all the bowlers in the table are the quicker bowlers. They are all attacking wicket-taking bowlers. The spinner who has conceded the most wides and no-balls is Shoaib Malik with 21.

Now a look at the best performing bowlers in this classification.

2. Bowlers who have conceded the least number of wides and no-balls

No Bowler             Ctry Mat  Overs Wides NBs Total
                                                 W+Nb
 1 Mudassar Bukhari    Hol   7   25.4    0   0     0
 2 Haq R.M             Sco   7   25.0    0   0     0
 3 Seelaar P.M         Hol   9   35.0    1   0     1
 4 Borren P.W          Hol   9   35.0    1   0     1
 5 Dhaniram S          Can  11   33.4    1   0     1
 6 Patel J.S           Nzl  11   33.1    0   1     1
 7 Vaas WPUJC          Slk   6   22.0    0   1     1
 8 McCallan W.K        Ire   8   21.5    1   0     1
 9 Collingwood P.D     Eng  30   32.0    2   0     2

Quite a few bowlers from the unfancied teams have conceded one noball or wide. Vaas and Jeetan Patel have also bowled a single wide.

Now for some qualitative assessments. First a table based on the number of wides and no-balls conceded per match.

3. Bowlers who have conceded most numbers of wides & no-balls per match

No Bowler             Ctry Mat  Overs  Total WNb/M
                                        W+Nb

 1 Roach K.A.J         Win  10   35.0    25   2.50
 2 Sohail Tanvir       Pak  15   51.0    36   2.40
 3 Rampaul R           Win   8   30.0    17   2.12
 4 Tait S.W            Aus  15   55.4    31   2.07
 5 Shoaib Akhtar       Pak   7   23.0    14   2.00
 6 Johnson M.G         Aus  21   77.1    36   1.71
 7 Lee B               Aus  16   58.1    27   1.69
 8 Langeveldt C.K      Saf   9   35.0    15   1.67
 9 Sreesanth S         Ind   9   34.0    15   1.67
10 Anderson J.M        Eng  18   66.2    29   1.61

Kemar roach, who bowls quite wildly often averages 2.5 wides and no-balls per match. That is something. If you add the runs scored off the free hits, if any, he is quite a liability.

Sohail Tanvir also clocks in at 2.4 wides and no-balls per match. However he is a great match-winner, at least in IPL matches. Rampaul follows next.

Ray Price is the leading (maybe the wrong term) spinner. He has conceded 1.43 wides and no-balls per match.

4. Bowlers who have conceded least numbers of wides & no-balls per match

No Bowler             Ctry Mat  Overs  Total WNb/M
                                        W+Nb

 1 Mudassar Bukhari    Hol   7   25.4     0   0.00
 2 Haq R.M             Sco   7   25.0     0   0.00
 3 Collingwood P.D     Eng  30   32.0     2   0.07
 4 Patel J.S           Nzl  11   33.1     1   0.09
 5 Dhaniram S          Can  11   33.4     1   0.09
 6 Dilshan T.M         Slk  31   20.0     3   0.10
 7 Yuvraj Singh        Ind  21   20.0     2   0.10
 8 Styris S.B          Nzl  28   46.3     3   0.11
 9 Seelaar P.M         Hol   9   35.0     1   0.11

Patel, Yuvraj Singh and Styris have quite low wides and noballs per match.

Now for the frequency of no-balls and wides.

5. Bowlers who have been most frequent with no-balls and wides

No Bowler             Ctry Mat  Overs  Total Balls/WNb
                                        W+Nb

 1 Roach K.A.J         Win  10   35.0    25     8.4
 2 Sohail Tanvir       Pak  15   51.0    36     8.5
 3 Shoaib Akhtar       Pak   7   23.0    14     9.9
 4 Rampaul R           Win   8   30.0    17    10.6
 5 Tait S.W            Aus  15   55.4    31    10.8
 6 Edwards F.H         Win  12   36.3    18    12.2
 7 Shoaib Malik        Pak  30   43.0    21    12.3
 8 Johnson M.G         Aus  21   77.1    36    12.9
 9 Lee B               Aus  16   58.1    27    12.9
10 Bresnan T.T         Eng  12   37.0    17    13.1

The usual fast bowling culprits lead this list. One wide or no-ball every 10 balls or so.

Ray Price leads the spinners with a wide or no-ball every 16.8 balls, quite frequent for a spinner.

6. Bowlers who have been least frequent with no-balls and wides

No Bowler             Ctry Mat  Overs  Total Balls/WNb
                                        W+Nb

 1 Seelaar P.M         Hol   9   35.0     1   210.0
 2 Borren P.W          Hol   9   35.0     1   210.0
 3 Dhaniram S          Can  11   33.4     1   202.0
 4 Patel J.S           Nzl  11   33.1     1   199.0
 5 Vaas WPUJC          Slk   6   22.0     1   132.0
 6 McCallan W.K        Ire   8   21.5     1   131.0
 7 Mascarenhas A.D     Eng  14   42.0     2   126.0
 8 Abdul Razzaq        Pak  17   39.3     2   118.5
 9 O'Brien K.J         Ire  16   35.3     2   106.5
10 Collingwood P.D     Eng  30   32.0     2    96.0

Three of the bowlers from the lesser teams have bowled a no-ball or wide once in 200 balls or so. That shows a level of accuracy not necessarily present in the more fancied bowlers.

Conclusion:

This started as a simple article. However the results are extremely fascinating. So much so the conclusions are quite speculative and I invite the enlightened readers to come in with their comments.

The tables 1,3,5 are the "negative" tables in this analysis in that these show the bowlers who have bowled more wides/no-balls, more wides/no-balls per match and more frequent wide/no-balls. However these tables are dominated by the genuinely good fast bowlers from top teams who have won more matches for their teams than the other bowlers.

The tables 2,4,6 are the "positive" tables in this analysis in that these show the bowlers who have bowled less wides/no-balls, less wides/no-balls per match and less frequent wide/no-balls. However these tables are dominated by the bowlers from lesser teams and some ordinary spinners. These are not necessarily match-winners. The top spinners, Muralitharan, Mendis, Harbhajan, Vettori, Botha, Swann et al are conspicous by their absence.

What does one conclude.

- That the top fast bowlers go for broke at the cost of control.
- That the top spinners do similarly but exercise more control.
- That the lesser bowlers, especially from the weaker teams, handicapped by their own lack of skills and team strength, show greater discipline and exercise lower levels of variety.
- That the wides/no-balls, especially the wides, because of the unknown free-hit component of the no-balls, are not that negative a trait that a bowler can have.

Note: For some perceptive comments on the conclusion, I must thank Sriram (Ananthanarayanan) who has brought in welcome independent editing skills.

The bottom line is that the really attacking bowlers, especially the fast bowlers, necessarily go for pace and variation and this might lead to more wides and no-balls. Maybe such a measure should be looked into in conjunction with strike rates of bowlers. My gut feel is that it is not possible to derive any conclusion from looking only at wides and no-balls.

To view/down-load the complete table, please click/right-click here.

Sreesanth is one short of playing 50 ODIs, but he still hasn't figured out a way to concede fewer runs © Associated Press

To start with, I must admit that I’ve always enjoyed watching Sreesanth bowl. He has a smooth, rhythmical action, has a classical side-on delivery motion, and, when he gets it right, the outswinger is wicked and a thing of sheer beauty. None of these things matter, though, when the format is limited-overs cricket, because then the rule is that Sreesanth will get clobbered no matter what he tries.

When Sreesanth returned to the ODI team with much fanfare at the beginning of the year, I had my doubts. Sure, he’d taken five in an innings against Sri Lanka in a matchwinning performance in the Kanpur Test, but this was a different format. Consistency has never been his forte, and on these benign subcontinent pitches, I feared he would be ruthlessly exposed.

And so it happened. Sri Lanka milked him for 47 off seven overs, while even Bangladesh too 54 and 53 off eight overs in the triangular tournament in Dhaka. More punishment from Sri Lanka in the final – none for 72 in 9.3. If anything, it got worse in the three-match home series against South Africa, with 74 and 83 runs – the fifth-highest for an Indian in ODIs – going off his nine overs in two of those matches.

Which brings us to a pertinent question: should Sreesanth be considered at all for one-day cricket? Let’s look a little more closely at his ODI stats: he has bowled in 48 matches so far, and 15 times – very nearly one third of all innings – he has gone at seven runs an over or more. Another eight times he has conceded more than a run a ball. That means 23 out of 48 times – almost 50% - he has leaked in excess of a run a ball. In contrast only 11 times has he gone at less than five an over.

Admittedly, his strike rate is reasonably impressive – a wicket every 34 balls – but his profligacy completely undoes his wicket-taking ability. Compare him with Irfan Pathan, who has the same strike rate but has an economy rate of 5.25, which is way better than Sreesanth’s 6.03. And we’re not even starting on the relative batting capabilities of the two.

And did you know that Sreesanth belongs to a highly exclusive club of which he is the only member? Of those who’ve bowled at 1500 balls in ODIs, he is the only one with an economy rate of more than six. Which means Sreesanth in the team is excellent news for the opposition, but if I were MS Dhoni, I would much rather have him in my Test line-up than in the ODIs.

Worst economy rate among ODI bowlers (Qual: 1500 balls)

Bowler	ODIs	Wickets	Average	Strike rate	Econ rate
Sreesanth	49	68	34.20	34.0	6.03
M Nkala	50	22	71.36	71.9	5.95
Elton Chigumbura	103	73	36.94	37.7	5.87
Ishant Sharma	41	56	32.48	33.5	5.81
Henry Olonga	50	58	34.08	35.5	5.76
Sean Ervine	42	41	38.07	40.2	5.67
N Odhiambo	45	46	35.95	38.0	5.67
Shahadat Hossain	46	42	43.42	45.9	5.67
Tapash Baisya	56	59	41.55	44.2	5.64
Naved-ul-Hasan	74	110	29.28	31.5	5.57

Muttiah Muralitharan: the leader in Tests and ODIs © AFP

Finally the analysis many of you have asked and been waiting for patiently. This has been on the drawing board for the past six months and I have had quite a few exchanges with many readers to fine-tune the analysis. A lot of care has been taken care to equalise performances by the players across years and across formats. This follows the best batsman analysis.

First, the "Twelve Commandments" followed in doing the analysis.

1. Equal weight for Tests and ODIs. T20-Intls not included since many top players have not played any T20-I matches and anyhow very few matches have been played. Let the number of T20-I matches cross 1000 before we consider it worthy of inclusion in this type of analysis.
2. Recognise longevity measures, such as wickets captured, but make sure that the total weight does not exceed 20%.
3. Especially for ODIs, recognise and incorporate the important fact that during the early 20 years very few ODI matches were played.
4. Unlike Batting where there is no necessity to distinguish between Right and Left handers, there is a clear need to distinguish in the Bowling analysis between Pace bowlers and Spinners because of the significant difference in the three main bowling measures, viz., primarily the Bowling average and secondarily, the Strike rate and Bowling accuracy. Since this is much more pronounced in Test matches than ODI matches, the handling is different.
5. Recognise how the bowler has performed in comparison to his peers, in the Strike rate and Bowling accuracy measures, for both Tests and ODIs. Mura;litharan and Garner are outstanding in these comparisons.
6. Recognise the fact that wickets of top order batsmen should carry additional weight as compared to wickets of late order batsmen. Pathan and Anderson are the best in this regard.
7. Use only career level figures. Match performances, while very relevant, would make it difficult to be equitable to Tests and ODIs. The peer comparisons cover this to some extent.
8. Give weight for share of team wickets. This is quite relevant in Test cricket, but is probably more relevant in ODIs. A bowler is allowed to bowl only 20% of his team overs (barring rain-hit and abandoned matches). Overall a bowler might have shared around 18% of his team's bowling. As such a bowler who captures, say 22/23% of the team wickets has performed admirably and so on. Let me say that even the spinners have done quite well in this measure. Brett Lee leads in this measure.
9. My idea initially was not to distinguish between home and away performances in Tests. However the following table of the the top-5 bowlers changed my mind. Let me assure readers that enough away wickets have been captured by all these bowlers.

              Overall   Home    Away    Ratio

Muralitharan   22.71   20.09   27.02    0.74
Warne          25.42   25.55   25.27    1.01
Kumble         29.65   24.90   37.36    0.67
McGrath        21.64   21.97   21.23    1.03
Walsh          24.44   23.15   25.66    0.90

It is clear that bowlers like Warne, even though he is a spinner, and McGrath performed better away than home. Muralitharan was less effective away, but still had a good away average. However Kumble was very average away. This fact has to be recognised and this has prompted to give some additional weight for away average. This is a change of heart and follows the batting ideas.
10. Since this analysis is limited to bowlers who played between 1970 and 2010, work out the algorithms based on these years. In other words, keep out of the equation Lohmann's outrageous figures. An average of 20.00 is the pinnacle, not halfway down the pole. This has helped to rationalise the analysis quite well.
11. Since this is a pure bowler based analysis, exclude the non-bowling factors such as Captaincy, Results, World Cup wins etc. McGrath, Garner and Warne might have won more matches and World Cups than Muralitharan, Ambrose and Hadlee but that should not be used to decide who is ahead in this bowling analysis.
12. I also decided that I would sum the points at rounded-integer level and would tie bowlers who have similar points. I would not use decimal points to separate any groups.

As usual there has to be a minimum criteria. I have decided on 200 combined international wickets AND minimum of 50 wickets in each format. This has allowed me to include Bond, Roberts, Jayasuriya and keep out Bedi, Chandrasekhar and Gibbs. Keeping a single qualification, a la Batting, 100 wickets in each format unfortunately gave me only 49 bowlers, which is quite a low sample.

The table below is quite illuminating and the ratios have been used in making the adjustments between Pace and Spin. For instance the base average for Test Pacers is 27.5 and for Test Spinners is 31.3. To that extent the Spinner would benefit. The base RpO for Test Pacers is 2.85 and for Spinners is 2.58. To that extent the Pace bowler would benefit. And so on... I have taken these numbers only for bowlers who have captured 100 wickets to ensure that the bar is set higher.

Tests played from 1970 - 2010 (only for bowlers who have taken 100 wkts)
                                       Ratios to All
       All   Pace   Spin              Pace       Spin
Avge: 28.6   27.5   31.3 - 13.8%      0.96       1.09
S/R:  62.4   57.8   72.8 - 25.9%      0.93       1.17
RpO:  2.75   2.85   2.58 - 10.4%      1.04       0.94

All ODIs (only for bowlers who have taken 100 wkts)

       All   Pace   Spin              Pace       Spin
Avge: 28.9   27.8   31.9 - 14.8%      0.96       1.10
S/R:  39.6   38.3   43.3 - 13.0%      0.97       1.09
RpO:  4.37   4.35   4.42 -  1.6%      0.99       1.01

The following are the points allotted for different measures.

Tests:  Wickets captured- 100 
        Adjusted wkts   -  50 (adjusted for matches played during career)
        Bowling average - 100
        Away bow average-  50
        Peer comparison -  50 (bowling strike rate comparison)
        Peer comparison -  50 (bowling accuracy comparison)
        % of Team wkts -   50
        % of Top wkts -    50

ODIs:   Wickets captured- 100 
        Adjusted wkts   -  50 (adjusted for matches played during career)
        Bowling average - 100   
        Peer comparison -  50 (bowling strike rate comparison)
        Peer comparison -  50 (bowling accuracy comparison)
        % of Team wkts -   50
        % of Top wkts -    50
        Wicket quality -   50 

The "Adjusted wkts" measure requires an explanation, especially for ODIs. This is best explained with an example. Take the case of Dennis Lillee. He had a career span of 12 years. That is fine and represents a long career. However the problem is that he played only 63 ODIs during this period. Compare this with Brett Lee who, in a shorter 10-year career, has played 186 matches, over 3 times more. An adjustment is needed and this is explained below.

The average number of ODIs per year played by Australia during 39 years is 18.7. The average number of ODIs played by Australia during Lillee's career is 7.75. The wickets captured by Lillee are multiplied by a factor 2.41(18.7/7.75) and points allotted for this measure. For Brett Lee, his career span number for Australia is 27.9 and the multiplying factor is 0.67 (18.7/27.9). Thus this redresses the wide imbalance which exists in the number of matches, especially ODIs, played over the years.

Note that the country figures rather than individual player figures are used since the player might not play due to injuries or non-selection or in Lillee's case, Packer matches. Note also that the base country is used as the base for doing this calculation for the player. Since the number of matches played by various countries varies by a factor of 2.5 to 1, comparisons with a single across-countries base would go haywire.

This is also done for Tests although the variations are far less for Tests.

For both Tests and ODIs, the overall Bowling average, adjusted for the decade values, carries 10 points. Only for Tests, the Away Bowling average, again adjusted for decade values, carries a weight of 5 points.

Independent peer comparisons are done on both Bowling strike rate and Bowling accuracy. The comparisons are only with similar bowlers.

For ODIs, the wicket quality is used by summing the "batting average" of the batsmen dismissed and dividing by the number of wickets. Also to determine the % of top wickets only batsmen whose average exceeds 30.0 (top batsman by all measures) is considered. Harmison is amongst the best in this measure.

Now let me unveil the tables. These tables are current upto Test # 1950 (second Bng-Ind test) and ODI # 2948 (fifth Aus-Pak ODI).

The best bowlers across formats - across years

  Rating                     Spin Test   ODI   Test    ODI
  Points                     Flag Wkts  Wkts    Pts    Pts
   1000                                         500    500

 1  752 Muralitharan M     Slk *   792   505  380.6  371.7
 2  697 McGrath G.D        Aus     563   380  348.6  348.8
 3  656 Wasim Akram        Pak     414   502  301.2  354.4
 4  655 Warne S.K          Aus *   708   293  346.5  308.8
 5  637 Donald A.A         Saf     330   272  309.7  327.4
 6  635 Pollock S.M        Saf     421   393  302.2  332.5
 7  631 Waqar Younis       Pak     373   416  295.3  335.2
 8  624 Garner J           Win     259   146  308.2  316.0
 9  623 Hadlee R.J         Nzl     431   158  328.1  294.9
10  621 Ambrose C.E.L      Win     405   225  328.6  292.3
11  600 Lillee D.K         Aus     355   103  305.8  293.8
12  587 Marshall M.D       Win     376   157  327.0  259.8
13  580 Holding M.A        Win     249   142  287.5  292.4
14  573 Imran Khan         Pak     362   182  307.4  265.5
15  570 Kumble A           Ind *   619   337  286.9  283.3
16  568 Bond S.E           Nzl      87   126  265.0  303.3
17  565 Lee B              Aus     310   324  232.5  332.9
18  564 Walsh C.A          Win     519   227  311.7  252.5
19  561 Saqlain Mushtaq    Pak *   208   288  236.1  324.8
20  556 Roberts A.M.E      Win     202    87  262.6  293.4
21  553 Ntini M            Saf     390   265  243.4  310.0
22  549 Vaas WPUJC         Slk     355   400  241.2  308.0
23  545 Shoaib Akhtar      Pak     178   223  249.9  295.0
24  538 Kapil Dev N        Ind     434   253  258.7  279.5
25  529 Gough D            Eng     229   235  246.6  282.2

Muralitharan heads both Test and ODI tables and is ahead by a comfortable margin. Only the churlish and the narrow-minded would deny this great bowler his place at the top. It is easy to say that he played in a weaker team so he had more opportunities to pick up more wickets. What about the batting and fielding. A strong team would have provided these cushions to their bowlers.

McGrath is second in Tests and third in ODIs and again fully deserves his high position. Has there ever been a better fast bowler? He is ahead of his long time compatriot Warne and Wasim Akram quite comfortably.

Wasim Akram is the other way around. Had a great ODI career (he is second) but had a slightly below-par Test career, of course compared to the Test giants. Overall a phenomenal fast bowler, worthy of his third position.

Warne is third in Tests. His achievements are legendary and do not need further words. He is a hair-breadth behind Wasim Akram. Would we ever see a twosome like McGrath and Warne bowling together?

The outstanding South African fast bowler, Donald is in fifth position. Consistency across the formats is his forte.

The top-10 is completed by Pollock, Waqar Younis, Garner, Hadlee and Ambrose. I am quite happy that there three great pairs in this group. It should be noted that the somewhat low number of wickets of Hadlee and Garner has not prevented them from coming to the top. Lillee misses the cut mainly because of the average ODI placements, not his fault, though. Marshall could also not find his place in the top-10 because of the ODI points.

The top-10 has 2 Australians, 2 Pakistanis, 2 South Africans, 2 West Indians, one Srilankan and one New Zealander. A fair distribution, one would say, with 6 countries represented. For the record, Kumble, Gough, Streak and Mashrafe Mortaza are the other country's best bowlers.

There also two spinners in the top-10 and four in the top-20. This is in line with the overall proportion since only 19 spinners qualified, representing 25% of the total. For the record, Chris Gayle props up the rankings.

Overall this is a fast bowler-dominated period. Only 25% of the bowlers are spinners. Also if one takes great spinners during this period, it would be difficult to look beyond Murali, Warne, Kumble, Abdul Qadir, Saqlain and Harbhajan (probably not there yet). However if I have to select the best pece bowlers, a limit of 15 would leave me unhappy.

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

Because of the length of the article I am not dwelling on the individual tables in depth. Suffice to say that Muralitharan, McGrath, Warne, Ambrose, Hadlee, Marshall, Walsh, Donald, Garner and Imran Khan could not be bettered as a Test top-10 of the past forty years. This list is dominated by West Indies, the most effective bowling team over the past 40 years.

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

And the ODI-10 of Muralitharan, Wasim Akram, McGrath, Waqar Younis, Pollock, Lee, Donald, Saqlain Mushtaq, Garner and Ntini represented the cream amongst ODI bowlers. I am happy that Saqlain, with an incredible ODI average of 21.7 and strike rate of 30.5 finds a place in the top-10. This group is dominated by Pakistan, rightly so.

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

A request to readers. You have every right to comment negatively. Every right to fault this analysis. Every right to be upset. Every right to disagree. What you do not have is the right to be abusive, personal or otherwise, to me or to the other readers or to the great players themselves or to other countries.

After a reasonable break I will do a "Who is the best player - across years and formats" article.

(This piece has been written in collaboration with Anshu Jain: Updated on Sunday, Jan 16/17)

Based on Alex Tierno's excellent suggestion I had worked on Batting Power Factor - a simple measure to determine the most destructive ODI innings through simple, easy-to-create methodologies. The article was well-received because of the simplicity of the idea. My thanks to Alex.

It follows logically that I should create a similar Power Factor for bowling. I had asked for suggestions. The simplest and most effective suggestion, closest to what I myself was thinking, came from Anshu Jain. My thanks to Anshu.

The requirements are set out below.

1. The methodology should be easy to understand and easy to work out. I have been influenced by Sattvir who mentioned that he wanted to calculate the IPF for each innings as he watches TV. There should be no need to go to the net to get the batsman average or bowler strike rate or whetever. Everything should be available from the Scorecard. A calculator might be needed.

2. The first factor to be recognized is the number of wickets captured. This is the most signicant of a bowler's contributions in a match. It should be recognized that in a 10 over spell, capturing more number of wickets is progressively more difficult. Unlike batting where a batsman can play 150 balls and score 200 runs, here the bowler achieves all in a spell limited to 20% of team overs.

3. The batting position of wickets captured is also important. Not necessarily the batting average.

4. Bowling accuracy is important but only in relation to the team numbers. By itself the bowling accuracy figure means very little as explained below.

India: 150/50 overs (Lee 10-2-25-2,Johnson 10-1-40-2,Watson 10-1-35-1) 
India: 250/50 overs (Lee 10-0-45-2,Johnson 10-1-40-2,Watson 10-0-55-1) 

Johnson has identical analysis in both matches. However his bowling in the first match is below-par and in the second batch is above-par. Lee has been above-par in both matches and Watson is below-par in both matches.

So the Bowling Accuracy index will be determined based on the bowler's numbers as well as the team's numbers.

I considered briefly and discarded the "% of team wickets" measure since good 4 and 3 wicket performances, where the "% of team wickets" figure was 100, moved up drastically in an unjustifiable manner. This is quite unlike the "% of team score" measure which moves in a 10%-20% band.

Methodology used:

The base is the wicket points. The following are the points allotted. There is a progressive increase for each wicket.

1   2   3   4   5   6   7   8
7  15  25  37  50  64  80  100

To determine the wicket quality, batting position is determined rather than batting average. Anyhow the best batsmen normally bat within no.4. Also if Ponting bats at no.10 his wicket is nowhere as important as at no.4. If a team is reduced to nothing for 3 or 4, it is normally quite difficult to recover. The bowler who captures top order wickets is rewarded and the bowler who captures low order wickets is penalized. This is based on the following formula.

Wickets 1 -  4: 2.0 points
Wickets 5 -  6: 1.5 points
Wickets 7 -  8: 0.75 points
Wickets 9 - 11: 0.25 points

The total for all wickets is added and divided by the number of wickets to arrive at the Wicket Quality Index value. The highest value for WQI is 2.0 (the bowler all whose wickets are 1-4) and the lowest value for WQI is 0.25 (the bowler all whose wickets are 9-11).

The Bowling Accuracy Index is determined by dividing the "Other bowlers' RpO" by the Bowler RpO. The highest ratio value for relevant spells is 10.16 (Walsh's 5 for 1 against SLK). In fact in 3882 such spells only 10 values are above 4 and represent completely bizarre situations, as perfectly illustrated by the Walsh spell. Hence these ratios are first capped at 4.0 and then the square root taken to arrive at the BAI. The index maximum is thus 2.0. This halving is to enure that for a bowler to get a par factor of 1.0, he has to perform at a level twice that of the team. Also to ensure parity with the WQI values. The highest value for BAI is 2.0 and the lowest value for BAI is 0.23.

Now the BPF is determined by multiplying the WP (Wicket Points) by WQI and BAI.

Let us look at the table and the top-20 performances. Only bowlers who captured 3 or more wickets are considered.

No Bowler         MtNo For  Vs  Analysis  WktPts  WQI  BAI   BPF

 1 Gilmour G.J    0031 Aus Eng 12.0-6-14-6  64.0 1.71 1.67 182.39
 2 Bichel A.J     1976 Aus Eng 10.0-0-20-7  80.0 1.43 1.52 173.32
 3 McGrath G.D    1970 Aus Nam  7.0-4-15-7  80.0 1.43 1.41 161.62
 4 Johnston D.T   2843 Ire Can 10.0-4-14-5  50.0 1.80 1.79 161.36
 5 Mendis B.A.W   2735 Slk Ind  8.0-1-13-6  64.0 1.42 1.77 160.30
 6 Muralitharan M 1826 Slk Nzl 10.0-3- 9-5  50.0 1.55 2.00 155.00
 7 Imran Khan     0325 Pak Ind 10.0-2-14-6  64.0 1.54 1.56 153.71
 8 Bond S.E       1986 Nzl Aus 10.0-2-23-6  64.0 1.58 1.42 143.70
 9 Vaas WPUJC     1776 Slk Zim  8.0-3-19-8 100.0 1.41 1.02 143.65
10 Joshi S.B      1504 Ind Saf 10.0-6- 6-5  50.0 1.40 2.00 140.00
11 Edwards F.H    2069 Win Zim  7.0-1-22-6  64.0 1.71 1.28 139.55
12 Simmons P.V    0777 Win Pak 10.0-8- 3-4  37.0 1.88 2.00 138.75
13 Umar Gul       2043 Pak Bng  9.0-2-17-5  50.0 1.65 1.67 137.63
14 Aaqib Javed    0685 Pak Ind 10.0-1-37-7  80.0 1.57 1.07 134.73
15 Vaas WPUJC     1950 Slk Bng  9.1-2-25-6  64.0 1.62 1.28 133.59
16 Wasim Akram    0311 Pak Aus  8.0-1-21-5  50.0 1.90 1.41 133.56
17 Styris S.B     1843 Nzl Win  7.0-0-25-6  64.0 1.50 1.38 132.54
18 Strang B.C     1242 Zim Bng 10.0-2-20-6  64.0 1.62 1.26 131.55
19 Streak H.H     2034 Zim Eng  9.0-3-21-4  37.0 1.88 1.89 131.45
20 Waqar Younis   1724 Pak Eng 10.0-0-36-7  80.0 1.68 0.97 130.43

Gilmour's innspell in the World Cup semi-final, rated by many as the best ever bowling performance of all time, comes in top place. 4 top wickets plus 2 of the next 3, complemented by oustanding bowling accuracy figure, contribute to this top position.

The seven wicket spells of Bichel and McGrath are in the next two positions. Bichel captured wickets 2-8. McGrath's spell included 6 of the top-5. Also note the bowling accuracy of both these spells.

D T Johnston took 5 of the top-6 wickets. Every one knows what Mendis did against India in the Asia Cup Final. He took 3 of the top-6 wickets.

Muralitharan's 5-wkt haul, all in the top-6, coupled with a bowling accuracy which is better than his team's figures by more than 4 times has propelled his performance to the top-5. Imran Khan's 6-14 demolition of India is next, followed by Bond's 6-23 against Australia.

Vaas's best ever ODI bowling effort of 8 for 19 is next. He would have captured all 10 wickets but for the introduction of Muralitharan. Joshi's 5 wickets were in the top-8 and he had an RpO figure of 0.6, way below his team's. This takes him to tenth place.

Note the high placement of Simmons' 4 for 3 against Pakistan. Aaqib Javed's 7 for 30 against India is in 14th position since the bowling accuracy just about matched the rest of the bowlers. Waqar Younis' 7 for 36 finds its way into the top-20.

To view/download the complete 3-wkt bowler list, limited to BPF of 50.0 points and above, please click/right-click here and save the file.

I have created an alternative version of the table based on the suggestion of Unnikrishnan in that I have used the Batting quality total points as it is, without dividing by the number of wickets. This has then been multiplued by the BAI value. The points for the 4 batting groups are 10(1-4), 7(5-6), 3(7-8) and 1(9-11) to get a reasonable final number. To view/download the revised 3-wkt bowler list, limited to BPF of 30.0 points (not comparable to the main table) and above, please click/right-click here and save the file.

I am happy that Gilmour stays on top. A few 7-wkt hauls have been pushed down and great 4-5 wkt spells have moved up because the differential values of the base points has been taken out of the equation.