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January 30, 2009

A consistency index for batsmen

Posted by Ric Finlay at in Trivia - batting
Among batsmen with at least 5000 Test runs, Jack Hobbs has the best consistency index © Getty Images
One thing we admire in our cricketers is consistency. Full marks to the gritty player who scores 50 on a minefield, even though he gets out for 50 when well set on a featherbed. But do we admire so much his team-mate who gets a duck in the first instance, but makes amends by crashing an impressive 100 in the second? They have the same average – but do they provide the same value?

Consistency can measured by calculating the standard deviation, which, in simple terms, seeks to measure the average deviation that each score is from the overall mean. The lower the standard deviation, the lower the variation in the scores.
We can obviously apply this to cricket scores, but a couple of issues need to be resolved: what to do with “not out” scores, and how can we use it to compare the consistency of players with different averages?

To resolve the first, I elected to add any uncompleted innings to the next innings, so that effectively, I was calculating the standard deviation of the runs made between dismissals. If the last innings was a “red ink”, it was ignored.

To allow comparison of consistency between different players, I simply divided the calculated standard deviation by the batting average (ignoring the last innings if it was “not out”).

I performed this exercise three times for Test cricketers; for those who scored at least 1000 runs, for those who scored at least 5000 runs, and for those who scored at least 10000 runs.

The first table lists the most consistent Test batsmen who have scored at least 1000 runs. Australia’s Bruce Laird, who scored with such consistency without scoring a century in his brief late-70s career, heads the list, and is followed by the admirable Sutcliffe, whose consistency is astounding given the extent of his career. Alastair Cook and MS Dhoni are notable current players in this list.

Table 1: Consistency Index: Most Consistent (Minimum 1000 runs)
Batsman Team CI SD Average Matches Innings Not Out Runs
Bruce Laird Australia 0.75 26.48 35.29 21 40 2 1341
Herbert Sutcliffe England 0.78 47.22 60.73 54 84 9 4555
Douglas Jardine England 0.79 37.08 46.70 22 33 6 1296
Ashley Giles England 0.80 16.81 20.90 54 81 13 1421
Alastair Cook England 0.81 34.24 42.09 36 66 2 2694
Maurice Tate England 0.82 20.96 25.49 39 52 5 1198
Rusi Surti India 0.83 23.72 28.70 26 48 4 1263
Jock Cameron South Africa 0.83 25.05 30.22 26 45 4 1239
George Gunn England 0.83 33.39 40.00 15 29 1 1120
Chandika Hathurusingha Sri Lanka 0.84 24.74 29.63 26 44 1 1274
Ian Redpath Australia 0.84 36.62 43.46 66 120 11 4737
Sid Barnes Australia 0.85 53.39 63.06 13 19 2 1072
Mark Richardson New Zealand 0.86 38.33 44.77 38 65 3 2776
Taufeeq Umar Pakistan 0.87 34.22 39.30 25 46 2 1729
Imran Farhat Pakistan 0.88 29.02 33.10 27 51 1 1655
Charles Kelleway Australia 0.88 32.83 37.42 26 42 4 1422
Dwayne Bravo West Indies 0.88 28.74 32.73 31 57 1 1833
Peter Richardson England 0.88 33.08 37.47 34 56 1 2061
Chetan Chauhan India 0.89 28.07 31.58 40 68 2 2084
Colin Bland South Africa 0.89 43.67 49.09 21 39 5 1669
Trevor Goddard South Africa 0.89 30.67 34.47 41 78 5 2516
Deryck Murray West Indies 0.89 20.40 22.91 62 96 9 1993
Mahendra Singh Dhoni India 0.89 32.20 36.14 35 56 6 1807
David Sheppard England 0.89 33.70 37.81 22 33 2 1172
Alan Davidson Australia 0.89 21.97 24.59 44 61 7 1328

At the other end, we also have some current players in the least consistent category, notably Sinclair, Taibu, and until recently, Atapattu, who mixed a dreadful sequence of low scores early in his career with some heavy scoring later on:

Table 2: Consistency Index: Least Consistent (Minimum 1000 runs)
Batsman Team CI SD Average Matches Innings Not out Runs
Matthew Sinclair New Zealand 1.62 52.70 32.55 32 54 5 1595
Vinoo Mankad India 1.51 47.57 31.48 44 72 5 2109
Jacques Rudolph South Africa 1.49 53.81 36.21 35 63 7 2028
Guy Whittal Zimbabwe 1.48 43.65 29.43 46 82 7 2207
Tatenda Taibu Zimbabwe 1.45 42.94 29.60 24 46 3 1273
Wasim Akram Pakistan 1.44 32.57 22.63 104 147 19 2898
Mohammad Ashraful Bangladesh 1.43 34.10 23.88 48 93 4 2125
Javagal Srinath India 1.43 20.31 14.21 67 92 21 1009
Wasim Jaffer India 1.42 48.30 34.11 31 58 1 1944
Vic Pollard New Zealand 1.41 34.35 24.35 32 59 7 1266
Dilip Sardesai India 1.40 55.10 39.24 30 55 4 2001
Sidath Wettimuny Sri Lanka 1.39 40.31 29.07 23 43 1 1221
Marvan Atapattu Sri Lanka 1.39 54.40 39.02 90 156 15 5502
Matthew Elliot Australia 1.38 46.20 33.49 21 36 1 1172
Madan Lal India 1.38 31.27 22.65 39 62 16 1042
Ridley Jacobs West Indies 1.37 38.70 28.32 65 112 21 2577
Tim Robinson England 1.36 49.34 36.39 29 49 5 1601
Bill Ponsford Australia 1.35 65.00 48.23 29 48 4 2122
John Bracewell New Zealand 1.35 27.56 20.43 41 60 11 1001
Jimmy Adams West Indies 1.35 55.72 41.26 54 90 17 3012

Now for the serious Test batsmen:

Table 3: Consistency Index: Most Consistent (Minimum 5000 runs)
Batsman Team CI SD Average Matches Innings Not Out Runs
Jack Hobbs England 0.92 52.33 56.95 61 102 7 5410
Don Bradman Australia 0.94 93.49 99.94 52 80 10 6996
Arjuna Ranatunga Sri Lanka 0.94 33.48 35.50 93 155 12 5105
John Wright New Zealand 0.97 36.58 37.83 82 148 7 5334
Mark Waugh Australia 0.97 40.58 41.82 128 209 17 8029
Graham Thorpe England 0.98 43.25 44.23 100 179 28 6744
Rohan Kanhai West Indies 0.98 46.58 47.53 79 137 6 6227
Clive Lloyd West Indies 0.99 46.44 46.68 110 175 14 7515
Denis Compton England 1.00 49.9 50.06 78 131 15 5807
Sourav Ganguly India 1.00 42.22 42.18 113 188 17 7212
Bill Lawry Australia 1.03 48.43 47.15 67 123 12 5234
Ken Barrington England 1.03 59.9 58.28 82 131 15 6806
Matthew Hayden Australia 1.04 52.77 50.74 103 184 14 8625
Ricky Ponting Australia 1.05 59.47 56.88 128 215 26 10750
Michael Slater Australia 1.05 45.09 42.84 74 131 7 5312
Doug Walters Australia 1.06 50.86 48.10 74 125 14 5357
Marcus Trescothick England 1.06 46.34 43.80 76 143 10 5825
Sunil Gavaskar India 1.06 54.42 51.12 125 214 16 10122
David Gower England 1.07 47.29 44.25 117 204 18 8231
Vivian Richards West Indies 1.07 53.69 50.24 121 182 12 8540
Michael Atherton England 1.07 40.41 37.70 115 212 7 7728
Len Hutton England 1.07 60.86 56.67 79 138 15 6971

The higher Consistency Indices show that it is much harder to maintain consistency over a longer career. It is interesting to observe that the two most consistent batsmen are two “old-timers”, Hobbs and Bradman – class will out! And who would have thought that the most consistent Australian after Bradman in this category was Mark Waugh!

At the other end of the scale for this category, we find Waugh’s twin brother prominently placed:

Table 4: Consistency Index: Least consistent (Min 5000 runs)
Player For CI SD Ave M I NO Runs
Marvan Atapattu SL 1.39 54.40 39.02 90 156 15 5502
Zaheer Abbas Pak 1.32 59.29 44.80 78 124 11 5062
Kumar Sangakkara SL 1.31 71.23 54.38 78 129 9 6525
Virender Sehwag Ind 1.27 64.81 51.06 66 114 4 5617
Steve Waugh Aus 1.26 64.16 51.06 168 260 46 10927
Shivnarine Chanderpaul WI 1.25 62.37 49.72 114 196 31 8203
Brian Lara WI 1.24 65.33 52.89 131 232 6 11953
Herschelle Gibbs SA 1.24 51.85 41.95 90 154 7 6167
Ian Botham Eng 1.24 41.69 33.55 102 161 6 5200
Sanath Jayasuriya SL 1.23 49.15 40.07 110 188 14 6973
VVS Laxman Ind 1.22 54.24 44.46 102 169 24 6446
Aravinda de Silva SL 1.21 52.21 42.98 93 159 11 6361
Mark Taylor Aus 1.19 51.55 43.50 104 186 13 7525
Wally Hammond Eng 1.19 69.46 58.46 85 140 16 7249
Jacques Kallis SA 1.19 64.91 54.58 128 216 33 9988
Mahela Jayawardene SL 1.18 61.73 52.36 100 164 12 7959
Carl Hooper WI 1.18 43.09 36.47 102 173 15 5762
Sachin Tendulkar Ind 1.1 64.28 54.28 156 256 27 12429
Rahul Dravid Ind 1.17 61.07 52.28 131 227 26 10509
Stephen Fleming NZ 1.17 47.05 40.07 111 189 10 7172

The case of Chanderpaul is interesting. Ten years ago, he was heading towards being one of the most consistent batsmen ever, with a CI of 0.82. Over the last decade, while he has been one the Windies few shining lights, there has also been much greater variation in his scoring.

This group also contains a few batsmen who play more aggressively than most: Sehwag, Jayasuriya and Botham are notable here. One would expect, naturally, their consistency to suffer as a result of their aggression.

Finally, a table just for the mega-stars, those who have scored 10000 Test runs, plus Kallis, who will surely join them the next time he goes to bat:

Table 5: Consistency Index: Top eight run-scorers
Player For CI SD Ave M I NO Runs
Ricky Ponting Aus 1.05 59.47 56.88 128 215 26 10750
Sunil Gavaskar Ind 1.06 54.42 51.12 125 214 16 10122
Allan Border Aus 1.08 54.45 50.37 156 265 44 11174
Rahul Dravid Ind 1.17 61.07 52.28 131 227 26 10509
Sachin Tendulkar Ind 1.18 64.28 54.28 156 256 27 12429
Jacques Kallis SA 1.19 64.91 54.58 128 216 33 9988
Brian Lara WI 1.24 65.33 52.89 131 232 6 11953
Steve Waugh Aus 1.26 64.16 51.06 168 260 46 10927

I for one was surprised to find the Aussie captain heading this list, and Tendulkar so far down the table. And perhaps Gavaskar was a better player than he is perhaps given credit for.

I hope the browsers of this site find this a worthwhile exercise. I would value their comments.

Comments (58)

January 23, 2009

A ranking system for Test openers

Posted by Ananth Narayanan at in Trivia - batting
Herbert Sutcliffe: the best of the lot © Getty Images
Mathew Hayden's retirement has drawn the curtains on the career of one of the greatest openers of all time. He, along with Sehwag and Greame Smith, re-defined the art of Test opening. Where do these wonderful opening batsmen stand vis-a-vis other greats like Hobbs, Gavaskar and Sutcliffe? I feel that this is the right time to do such a study.

The study of opening batsmen is a complicated task. Over the years the role of opening batsmen has changed. From defensive, stay-at-wicket-at-all-costs batsmen they have become match-winners who have been primarily responsible for the attacking attitudes which captains employ now. The study has to recognise this evolution and be fair to all types of opening batsmen.

The first task is to fix a minimum limit criteria. I have fixed this as 3000 runs, scored in the opening position (not complete career). This lets in most great openers. The only top-drawer opener left out is Hanif Mohammad (2638 runs). Unfortunately nothing can be done. I apologise to my Pakistani friends for this. I have also given at the end Hanif Mohammad's values. The other great opener left out, Victor Trumper, has scored only 1650 runs in the opening position. I wanted to avoid any longevity-based weighting and the only way is to keep a high entrance bar. The number of qualifying batsmen has also to be kept at a reasonable number, 35 in this case.

In order to cater to the different playing times, tactics, grounds et al, I have used the following 7 criteria. Each is explained in full later. 

1. Home Batting Average.
2. Away batting Average.
3. Average Runs scored - weighted by the quality of bowling attack.
4. Scoring Rate.
5. Average opening partnerships participated in.
6. Quality of the top 3 pace bowlers faced.
7. Quality of batting support - Other opener and next 3 batsmen.

The principle I have followed is that the three direct measures, Home average, Away average and Average weighted runs, will carry a total weight of 50%. The other four secondary measures will have equal weight.

1. Home Batting Average (15 points).

This is the most basic of all measures. It is a straight forward computation of the home batting average. Since the minimum number of home runs scored by a batsman in the group of 35 is 1246 (by Michael Vaughan), any average figure will be valid.

The highest home average is that of Herbert Sutcliffe who has an outanding 64.60 average while playing as an opener in England. Mike Atherton of England is at the bottom with an average of 39.14.

2. Away batting Average (20 points).

This is the other basic measure. It is a straight forward computation of the away batting average. It carries a higher weighting than the home batting average for obvious reasons. Since the minimum number of away runs scored by a batsman in the group of 35 is 916 (by John Edrich), any average figure will be reasonably valid.

Away from home, the other great opener Hobbs averages 59.17. Mudassar Nazar travels very poorly with an average of 25.75.

3. Average Runs scored - weighted by the quality of bowling attack (15 points).

The first two were basic measures. However there is need to value the runs scored against better bowling attacks higher. Greame Smith should get much more credit for his knock of 154 against England as compared to his innings of 232 against Bangladesh even though both were match-winning innings and the second is 50% higher. This is done by weighting the runs scored by the bowling strength of the opposing team and averaging the same.

Hobbs' run tally comes down to 90% while Andrew Strauss' tally moves up to 109%.

4. Scoring Rate (12.5 points).

This is a new measure. The openers have changed the way the Tests are played now. First Hayden and then Greame Smith, Sehwag and Gayle et al have scored consistently at well above 3 runs per over and this has resulted in many more decisive games. This factor has to be recognized and has been.

We have accurate balls played information for the past 15 years and this can be used. For the early Tests I have assigned to the opening batsmen the team's strike rate for the innings. This might vary slightly from actual balls played information, which is, unfortunately, available nowhere. However this will even out over a career. It is also true that the olden day openers, barring a very few attacking players, played quite slowly and most of them would in reality be benefited by this methodology. For openers such as Jayasuriya, Greenidge, Haynes et al, wherever available, actual balls faced information is utilised.

The highest scoring rate for an opener has been achieved by Sehwag who has scored at an incredible 4.75 runs per over.

5. Average opening partnerships participated in (12.5 points).

This is a very good measure since it provides an indication of the effectiveness of the opener. Herbert Sutcliffe has averaged opening stands around 73 runs. The lowest figure is for Alec Stewart, around 36 runs.

6. Quality of the top 3 pace bowlers faced (12.5 points).

When the openers walk in at 0 for 0, they have a daunting task. If they reach lunch at xyz for 0, they would have done their job. Everything afterwards is a bonus. During these two hours or so, the opening batsmen are likely to face the three best pace bowlers of the other team. If these three happen to be Marshall, Holding and Garner as a few opening pairs faced during the 80s, as against the openers who faced Madan Lal, Amarnath and Solkar, they have to be given due credit.

The best three pace bowlers' averages are summed and averaged over the number of times the batsman opened.

Alec Stewart has faced the toughest pace bowlers with a low average of 27.75. A number of recent English opening batsmen have somewhat low figures since they have faced strong Australian attacks in frequent Ashes series. At the other end Hobbs, surprisingly, has had the easiest of opening stints at 37.09. Understandable since the non-English bowling between 1908 and 1930 was quite ordinary.

7. Quality of batting support - Other opener and next 3 batsmen (12.5 points).

Imagine Greenidge walking in with Haynes, with Richards, Kallicharan and Lloyd to follow. Or Langer walking in with Hayden with Ponting, Clarke and Hussey to follow. Contrast this with Gavaskar walking with the happy-go-lucky Srikkanth and P Sharma, Viswanath and BP Patil to follow. These are the extremes. This measure takes into account the supporting batsmen. The other opener gets highest weighting, followed by the no.3, no.4 and no.5 batsmen with progressive lower weightings. These proportionate averages are added and averaged. Higher credit is given for lower support averages.

It is clear that a strong bowler in a weak team has the benefit that he can take a greater share of wickets than a strong bowler in a strong team (Hadlee/Muralitharan against McGrath/Warne). Contrast this with batting where good support is always a boost to the batsmen.

As can be expected, Justin Langer has the best supporting batting with a figure of around 50. Don't forget that Langer had Mathew Hayden as the other opener. The one who had the least support is Chris Gayle with 33.63, despite the presence of Lara at no.4.

Table of top opening batsmen of all time 

No Cty Batsman                 HmAvg  AwAvg AdjRpt ScRate OpPshp PaceBow BatSup

                       100.00  15.00  20.00  15.00  12.50  12.50  12.50  12.50

 1.Eng Sutcliffe H      72.00  12.92  15.20  11.40   5.43  11.51   7.03   8.51
 2.Ind Sehwag V         71.72  10.41  14.05  11.12   9.89   8.25   8.85   9.15
 3.Aus Simpson R.B      70.71  10.51  15.60  11.36   5.56  10.71   8.05   8.93
 4.Saf Smith G.C        69.46   9.13  15.31  10.13   7.69  10.03   7.60   9.57
 5.Eng Hobbs J.B        68.70  10.46  15.78  10.08   5.98  10.05   6.45   9.91
 6.Ind Gavaskar S.M     67.80   9.57  14.11  10.33   5.84   6.95   9.49  11.50
 7.Eng Hutton L         67.69  11.60  14.54  10.56   5.01   8.52   7.34  10.11
 8.Eng Amiss D.L        66.77  11.18  13.94  11.40   5.29   6.73   7.22  11.02
 9.Aus Hayden M.L       66.26  11.58  11.38  10.33   7.51   8.91   8.53   8.01
10.Eng Boycott G        65.55   9.68  12.77  10.14   5.01   8.40   9.09  10.46
11.Eng Vaughan M.P      65.52  11.33  10.71   9.39   6.77   9.59   7.72  10.02
12.Win Greenidge C.G    65.15   9.84  11.34   9.18   6.78   9.30   9.31   9.40
13.Pak Saeed Anwar      64.61   9.27  12.72   9.44   6.97   5.80   9.14  11.28
14.Aus Langer J.L       64.42  10.15  11.98   9.97   7.24   9.27   8.50   7.32
15.Saf Gibbs H.H        64.40   9.22  12.92   9.66   6.54   8.61   8.82   8.63
16.Eng Trescothick M.E  64.22  10.21   9.63   9.40   6.81   9.52   8.48  10.18
17.Eng Stewart A.J      64.15  10.17  11.03   9.21   6.08   5.64  11.12  10.92
18.Win Haynes D.L       63.21  11.33   8.94   8.50   6.65   8.74   9.36   9.69
19.Aus Lawry W.M        63.21  11.27  10.56   9.67   5.38   9.15   7.92   9.24
20.Eng Gooch G.A        63.10   9.56  10.12   9.16   6.03   6.82  10.39  11.03
21.Win Fredericks R.C   63.06   9.22  10.68   9.18   6.24   9.69   8.58   9.47
22.Eng Edrich J.H       62.16   9.14  11.10   9.40   5.25   8.37   9.05   9.84
23.Slk Jayasuriya S.T   62.15   8.85  10.07   8.00   8.14   8.41   8.92   9.76
24.Eng Strauss A.J      61.92   8.15  11.97   9.19   6.11   7.97   9.03   9.52
25.Aus Slater M.J       61.77  10.53   9.41   8.43   6.66   8.55   9.02   9.18
26.Win Hunte C.C        61.64  10.70  10.32   9.42   5.78   8.12   7.18  10.12
27.Win Gayle C.H        61.60   7.66  11.28   8.36   7.17   7.00   8.54  11.59
28.Aus Taylor M.A       61.25   8.68  11.63   8.65   5.37   7.42   9.82   9.69
29.Slk Atapattu M.S     60.46   8.28  12.05   8.12   5.59   8.48   8.45   9.49
30.Aus Morris A.R       60.25   7.75  14.74   8.91   5.79   6.10   7.97   8.98
31.Saf Kirsten G        59.80   7.90  11.81   8.65   5.20   6.39   9.33  10.52
32.Eng Atherton M.A     59.27   8.28   9.63   8.35   4.86   6.40  10.98  10.76
33.Aus McDonald C.C     57.65   9.53   8.89   8.40   5.01   7.34   8.02  10.46
34.Nzl Wright J.G       57.11   8.40   9.00   7.48   5.08   6.03   8.98  12.14
35.Pak Mudassar Nazar   56.04  10.43   6.87   7.20   6.25   5.81   9.02  10.47

Herbert Sutcliffe's position at the top is a well-earned one. He leads in two of the key measures 

	- Home average, 
	- Average opening partnership and
	- Has a very good Away batting average of 57.00
He is only one of two batsmen, the other being Miandad, who has never fallen below 50 in their (reasonably long) career. He clocks in comfortably in the other measures. He however had good support (Hobbs/Hammond) at the other end. The bowling Sutcliffe faced was nothing great.

Sehwag's second position should not surprise any unbiased observer. His credentials are listed below. 

	- 50+ averages both home and away, 
	- Almost all his top scores have been against top class bowling,
	- He has an excellent strike rate of 4.75 rpo, 
	- Has faced very good quality pace bowling almost always and 
	- He has scored only around 200 runs in 5 Tests against Bangladesh/Zimbabwe.
In fact he would have been at the top if the Strike Rate measure was, say, 15.00 instead of 12.50. That would have been a worthy position for Sehwag. He has won many matches for India through his uncompromising attacking style.

Bobby Simpson is the surprise package. The main reason is that his overall batting average is only 46.82. However his opening average is 55.52, that too, 52.55 at home and 58.48 away. His opening partnerships, mostly with Lawry, averaged 68 and he faced good quality pace bowling almost always.

Then comes Graeme Smith, who is somewhat similar to Sehwag and Hayden. He has an away average of 57.43. He loses out slightly in view of the runs scored against weaker teams, and also the quality of pace attacks faced.

Then come three great openers of yesteryears. Hobbs, Gavaskar and Hutton. Each of them could have been at the top with no questions asked. All have very good averages. Gavaskar loses in the average opening partnership but gains on the pace bowling quality and a very average middle order.

Hayden has lost out a little because of the indifferent end to his career (His average dropped by 2.5 runs during the last 10 Tests). Otherwise he would have challenged for a place in the top 5.

Readers would note that the top 10 opening batsmen comprise of 3 attacking match-winning openers of today and 7 openers of the previous eras. It is clear that for any opener of today to break into the top-10 they have to be extraordinarily good, as these three have been. One does not necessarily have to score at around 4 rpo, in which case, they have to average well above 50, both home and away and do that consistently against the top sides, not just the minnows. Being part of a good opening pair and consistently putting up above average partnerships would help.

As I had indicated earlier, I have given below Hanif Mohammad's summary figures. What is very relevent is his away batting average, which, standing at 44.05, is 20% better than his Home average. Also the total lack of support batting. 

Pak Hanif Mohammad   56.62   7.37  11.75   8.01   4.38   5.44   7.17  12.50

Finally a note to the readers. One factor I keep in my mind always is that each of the measures used in all my articles should be understood by all the readers, without exception. One of the reasons I try to stay away from complex statistical measures and methodologies.

Click here to view supporting information.

Comments (59)

January 19, 2009

Another take at the best Test captains

Posted by David Barry at in Captaincy
The tendency of Mark Taylor's team to lose dead rubbers cost his captaincy numbers © Getty Images
To evaluate how good a captain's results are, you need to know how good they would have been with an average captain. We all know that Ricky Ponting has a stupendously high number of wins as captain, but for much of his captaincy he's had one of the all-time great teams under him. So we should expect that he'd have a lot more wins than losses. The problem is now to quantify what we would expect. Though Ananth has tried to account for differences in team strength in his latest post, I don't think it works well enough.

I've taken each Test and calculated the overall batting average and the overall bowling average for each team. The latter was done by weighting each bowler's average according to the number of balls bowled in each innings. If there were two innings, I took the average of the two innings. That's a bit lazy of me, but it shouldn't make too much difference. (All averages are adjusted using the methods explained in this post.)

Then you take (home bat - away bat - home bowl + away bowl) and you have a measure of the relative strength of the home side to the away side. I calculated this for all Tests, noted the result of each Test, and then saw how the fraction of wins, losses and draws changed as the strength of the home team varies. The results are shown in Figure 1.

The fractions of wins does basically what we'd expect – it starts out flat and very low for teams that are outclassed, before rising steadily before plateauing. There are always going to be some draws (because of rain), so the fraction of wins won't hit zero or one. Even the weakest of home teams can achieve a draw rate of about 30% (well, maybe not Bangladesh), whereas very weak teams away can only draw about 20% of Tests.

The trend in draws is a bit different. It seems to go gently upwards until the teams are evenly matched, and then more sharply downwards as the home team becomes stronger.





The graph for wins and draws (Click here for a bigger image) © David Barry
I approximated these curves with piecewise linear functions. For the draws, it's flat for x less than -27, then upwards so that it hits the y-axis at y = 0.424, then downwards until x = 17, and then flat, at a value of 0.185.

For the wins, it's flat at 0.031 below x = -13.7, then upwards until x = 17.2, and then flat at a value of 0.785.

So now, for each Test, I calculate the difference in strength. Then I plug that number into the fitted graphs to get a fraction of a win, draw, and loss. For example, suppose that the teams are evenly matched. Then the home side gets 0.366 wins, 0.424 draws, 0.21 losses. The wins and losses for the away side are flipped: 0.21 wins and 0.366 losses.

You do this for each Test that a captain plays, and add up the expected wins, draws, and losses. Now we can compare to the actual record.

There's a question here about how to deal with draws. I decided to ignore them, for a couple of reasons. The first is that teams which score runs faster should have less draws, but I didn't take strike rate into account when doing the regressions above (I don't have strike rate data for all Test batsmen). Also, all Tests in Australia (as well as some elsewhere) were played to a finish between 1882/3 and World War II – no draws in a major cricketing country for over sixty years!

So while I'm happy that draws became almost extinct under Steve Waugh's captaincy as his batsmen increased average scoring rates, he's not going to benefit from this in this analysis.

Instead I calculated the fraction of wins out of matches that ended in a result, that is: wins / (wins + losses). Do this for the actual value, divide by the expected value, and you get a ratio saying how much better or worse the captain's record is compared to what would be expected.

Whether or not it is reasonable to ascribe all the difference to the captain is certainly debatable, but let's look at the results anyway. The table below shows the number of matches captained, the expected results, the actual results, the expected and actual values of wins/(wins + losses), and the ratio of the latter two. Qualification of 20 Tests.

                     ----expected----  --actual--  exp   act
captain          mat w     d     l     w   d   l    w/(w+l)    ratio
Abdul Hafeez     23  5.1   7.1   10.8  6   11  6   0.32  0.50  1.56
GP Howarth       30  7.6   11.0  11.4  11  12  7   0.40  0.61  1.52
Inzamam-ul-Haq   31  6.8   11.3  12.9  11  9   11  0.35  0.50  1.44
J Darling        21  6.0   7.8   7.2   7   10  4   0.46  0.64  1.39
JM Brearley      31  11.5  12.0  7.5   18  9   4   0.60  0.82  1.35
GA Gooch         34  8.0   12.5  13.5  10  12  12  0.37  0.45  1.22
RB Richardson    24  8.4   8.2   7.4   11  7   6   0.53  0.65  1.22
MP Vaughan       51  19.0  18.2  13.7  26  14  11  0.58  0.70  1.21
CA Walsh         22  5.7   7.6   8.7   6   9   7   0.40  0.46  1.16
DG Bradman       24  11.7  7.7   4.6   15  6   3   0.72  0.83  1.16
SP Fleming       80  23.3  27.2  29.5  28  25  27  0.44  0.51  1.15
DPMD Jayawardene 26  10.2  8.8   7.0   15  4   7   0.60  0.68  1.14
Nawab of Pataudi 40  7.3   14.6  18.1  9   12  19  0.29  0.32  1.12
IVA Richards     50  22.0  18.1  9.9   27  15  8   0.69  0.77  1.12
N Hussain        45  14.1  15.5  15.5  17  13  15  0.48  0.53  1.12
RB Simpson       39  11.1  14.2  13.7  12  15  12  0.45  0.50  1.11
SM Gavaskar      47  13.9  17.9  15.2  9   30  8   0.48  0.53  1.11
IM Chappell      30  13.0  11.0  6.0   15  10  5   0.69  0.75  1.09
CH Lloyd         74  32.4  26.9  14.8  36  26  12  0.69  0.75  1.09
L Hutton         23  9.9   8.3   4.8   11  8   4   0.67  0.73  1.09
Wasim Akram      25  9.5   7.9   7.6   12  5   8   0.56  0.60  1.08
SM Pollock       26  11.9  8.7   5.4   14  7   5   0.69  0.74  1.07
Imran Khan       48  18.0  18.0  12.0  14  26  8   0.60  0.64  1.06
R Benaud         28  12.5  10.5  5.0   12  12  4   0.71  0.75  1.05
AL Hassett       24  11.7  8.1   4.1   14  6   4   0.74  0.78  1.05
MC Cowdrey       27  10.8  10.0  6.1   8   15  4   0.64  0.67  1.04
RT Ponting       52  28.1  16.4  7.4   35  9   8   0.79  0.81  1.03
SC Ganguly       49  19.7  16.1  13.1  21  15  13  0.60  0.62  1.03
MJK Smith        25  9.6   9.3   6.1   5   17  3   0.61  0.63  1.03
R Illingworth    31  13.7  11.1  6.2   12  14  5   0.69  0.71  1.02
WM Lawry         25  8.5   8.9   7.6   9   8   8   0.53  0.53  1.00
ST Jayasuriya    38  15.1  12.9  10.0  18  8   12  0.60  0.60  1.00
Javed Miandad    34  16.1  11.1  6.8   14  14  6   0.70  0.70  0.99
GC Smith         66  28.6  22.3  15.1  33  15  18  0.65  0.65  0.99
PBH May          41  17.8  14.7  8.5   20  11  10  0.68  0.67  0.98
WJ Cronje        53  25.3  18.1  9.6   27  15  11  0.73  0.71  0.98
GS Chappell      48  19.3  17.8  10.9  21  14  13  0.64  0.62  0.97
RS Dravid        25  9.2   9.4   6.4   8   11  6   0.59  0.57  0.97
AR Border        93  36.4  34.5  22.1  32  39  22  0.62  0.59  0.95
SR Waugh         57  33.3  18.3  5.4   41  7   9   0.86  0.82  0.95
JDC Goddard      22  7.7   8.3   6.0   8   7   7   0.56  0.53  0.95
MA Atherton      54  14.1  19.4  20.4  13  20  21  0.41  0.38  0.94
MA Taylor        50  23.7  17.5  8.8   26  11  13  0.73  0.67  0.91
ER Dexter        30  11.8  11.3  6.9   9   14  7   0.63  0.56  0.89
A Ranatunga      56  16.5  18.6  20.9  12  25  19  0.44  0.39  0.88
ADR Campbell     21  2.4   6.2   12.4  2   7   12  0.16  0.14  0.88
WM Woodfull      25  13.1  7.8   4.1   14  4   7   0.76  0.67  0.87
Kapil Dev        34  9.1   12.1  12.8  4   23  7   0.42  0.36  0.87
WR Hammond       20  8.7   6.9   4.4   4   13  3   0.66  0.57  0.86
HH Streak        21  4.7   6.0   10.3  4   6   11  0.31  0.27  0.85
SR Tendulkar     25  5.9   8.7   10.4  4   12  9   0.36  0.31  0.85
MW Gatting       23  4.9   8.8   9.3   2   16  5   0.35  0.29  0.83
BC Lara          47  10.5  16.1  20.4  10  11  26  0.34  0.28  0.82
M Azharuddin     47  18.6  17.2  11.2  14  19  14  0.62  0.50  0.80
GS Sobers        39  14.4  14.9  9.7   9   20  10  0.60  0.47  0.79
CL Hooper        22  5.1   7.8   9.2   4   7   11  0.36  0.27  0.75
BS Bedi          22  7.0   7.8   7.3   6   5   11  0.49  0.35  0.72
DI Gower         32  6.6   12.0  13.5  5   9   18  0.33  0.22  0.66
JR Reid          34  5.2   11.1  17.8  3   13  18  0.23  0.14  0.63
AC MacLaren      22  6.4   7.9   7.7   4   7   11  0.46  0.27  0.59
KJ Hughes        28  7.4   10.3  10.3  4   11  13  0.42  0.24  0.56
A Flower         20  3.4   6.3   10.2  1   9   10  0.25  0.09  0.36

The results are (of course) far from perfect. Nevertheless, there is plenty to be gleaned from the table. Gavaskar is placed relatively highly, because his teams turned more losses into draws than wins into draws. Thirty draws in 47 Tests is not exciting or something I would encourage captains to aim for, but it helped India's win/loss during that period.

Abdul Hafeez Kardar, Pakistan's first captain, comes out on top by virtue of turning about half of the losses he "should" have had into draws.

Mark Taylor comes out worse than his immediate predecessor and successors, which is at odds with most observers' opinions of his captaincy. Taylor's sides were notorious for losing dead rubbers; if these are excluded then his ratio moves up to around 1.

The one major problem with this analysis occurs with captains with very long reigns. In these cases, the good (or bad) field placings and so forth feed into his bowlers' averages for much (or all) of their careers. This has the effect of making the captain's expected results closer to what they actually were. I don't know how big this effect is. But captains like Border, Fleming, and Lloyd should probably have their ratios moved further away from 1.

Comments (30)

January 9, 2009

Test Captains - an in-depth look

Posted by Ananth Narayanan at in Captaincy
Imran Khan: superb allrounder and an inspirational captain © Getty Images
This article has been in the pipeline for long. An analysis of Test Captains is not an easy task and will lead to many arguments and comments. However that cannot deter us from making an honest attempt. As long as the comments are positive in nature, it does not matter.

What are the requirements of a good Test captain? The measurable factors are on-field performance as a player, leading from the front, achieving good match and series results, both home and away. The non-measurable factors are man management, identification of talent, getting players to do their best and support of team members with selection entities. I will only concentrate on the measurable factors and stay away from the non-measurable ones. I am confident that this will be fair even to great captains whose on-field performance might be below par.

I have decided on a few yardsticks for this analysis. Readers should be happy with these since these reflect earlier reader comments.

The first is that there will be no longevity based allocation of points. I will set a fairly high bar for selection. Once this bar is crossed, all the selected captains will have an equal chance of achieving a high position in the table.

The second is that the team strength measures will be adjusted for the period during which the concerned Test was played. This will ensure a fair playing field.

The third is that the captains' individual performances will be weighted for the quality of opposition. The all-Test batting average of 29.92 and bowling average of 31.51 are used as reference. In other words, a 100 against a strong Australian team will be weighted at a much higher level than a 100 against a weak Bangladesh team. Similarly for bowling.

After a number of trial runs I have decided on 30 Tests as the minimum requirement for inclusion. This has been worked on various factors, not the least is the need to keep the number of qualifying cricketers, in this case 35, to a reasonable number. Also 30 Tests represents between 3 and 5 years reign, a fairly long one. Unfortunately this keeps out very successful captains such as Don Bradman, Richie Benaud, Wasim Akram, Jayawardene, Shaun Pollock (he was a very good Test captain) to name a few. To do proper justice to these great players, I have presented an additional table of captains who have led their teams in 20-29 tests at the end.

Now for the details, to be followed by the tables. I waited for the end of the wonderful Test match at Sydney to prepare these tables since the result there might have had a bearing on the final positions.

The measures for analysing Test Captains is broadly classified into the following four (measurable) factors.

1. Base unadjusted match results.
2. Match results adjusted for team quality and venue.
3. Series results.
4. Individual performances - Batting, Bowling and Fielding.

1. Base unadjusted match results.

These are the raw unadjusted results. A win is a win, whether it is against Australia at Sydney or against Bangladesh at Mirpur. Similarly a draw is not a loss and as such some credit has to be given. The measure of success is derived by the following formula and converted to points. 

                  No of wins   +   (No of draws / 2)
Success Factor =  ----------------------------------
                            No of matches
A captain who wins all the matches (not that any one has done it) gets full credit.

2. Match results adjusted for team quality and venue.

The best way of explaining this measure, which carries the most weight is to show a table of imaginary match results. Let me take three teams. Australia, with a TSI of 75, England, with a TSI of 60 and Bangladesh, with a TSI of 45. All possible results and the winning captain credits are tabulated below. 

                                               Home win           Away win
Stronger team winning
    Australia (75) defeats England (60)           60                 72
    Australia (75) defeats Bangladesh (45)        36 (lowest)        45
    England (60) defeats Bangladesh (45)          41                 50
Weaker team winning
    Bangladesh (45) defeats Australia (75)        83                100 (highest) 
    Bangladesh (45) defeats England (60)          66                 80
    England (60) defeats Australia (75)           75                 90
The summary is that the minimum points are allocated when the strongest team defeats the weakest team at home and the maximum points are allocated when the weakest team defeats the strongest team away. The limiting values have a factor of nearly 3 between themselves. Everything else is in between.

Captains in drawn matches get 50% of the adjusted TSI values.

The points for all tests captained by one player are summed and divided by the number of Tests captained. This ensures that longevity in captaincy does not play a part.

3. Series results.

A few comments on the Series calculations. Until now a total of 590 series have been played. Single Test series, 50 of these at last count, are not considered to be series. A minimum of two Tests have to be played. There have been three multi-team series (The 1912 Triangular tournament at England between Eng-Aus-Saf, the First Asian Test Championship of 1998-99 and Second Asian Test Championship of 2001-02). For these three tournaments, the home teams are respectively England, Pakistan and Bangladesh. The winner of these three tournaments, viz., England, Pakistan and Sri Lanka get the winner's credits. For the only series played in neutral locations, the 2002 matches between Pakistan and West Indies/Australia, all three teams are considered to be "Away".

The winning captain gets the average of the losing team's TSI as credit for winning the series. A bonus of 20% is given for winning an away series. If multiple captains have captained within a series they get proportionate credit. All these are subject to the above mentioned adjustments for relative strengths of the two teams. Aus/Ind/Saf will get least credit for winning at Bangladesh while Bangladesh will get maximum credit for winning at Aus/Saf/Ind, if ever that miracle happens.

The points for all series/part series captained by one player are summed and divided by the number of Tests captained. This ensures that longevity in captaincy does not play a part. Number of Tests rather than number of series is used to ensure uniform weighting. Also all series wins are treated the same. Of course, if a captain wins the series 5-0 he would have got substantial match win credit points as against one who wins 1-0.

It is possible that there is some overlap amongst the three Results based parameters. However each has a different objective and the overlap exists unformly across all captains. The across-the-board division by the "Tests captained" figure smoothes all variations.

4. Individual performances - Batting, Bowling and Fielding.

Finally on-field performance. I think it is essential to recognize the batting, bowling and fielding performances of the captain. Cricket is not any longer, and should never have been, a non-playing-captain game. We recognize the performances by converting runs/wickets/catches to points, adjust these for the quality of other team's batting and bowling, sum these and then divide by the number of tests captained. Wicket-keeper-captains' dismissals are given additional weighting.

Let me summarize these. I have kept in mind a figure of 70-75% for different Results related points allocation and 25-30% for Performance related points allocation. I also expected to achieve these allocations at the total level. At individual levels the allocations will vary considerably. A low-performing captain such as Brearley gets over 90% on Results related allocations, an average-performing captain such as Steve Waugh gets over 80% on Results related allocations while a Performing captain such as Imran Khan or Sobers gets over 40% in Performance related points allocations. The summary is given below. 

              For 62 Captains     For 290 captains
               (20+ tests)           (All)
Results:          14.35%             14.76%  
Matches:          45.55%             46.04%
Series:           13.86%             12.04% 
Performance:      26.22%             27.16%
The summarized weighted percentages have come almost very close to what I set out at the beginning.

These summary figures meet the target I had set before beginning the analysis and we can now proceed to complete the table preparation work. 

Top Test Captains - Minimum 30 tests as captain

SNo Player           Cty (Runs  Wkts C/S)   Matches Ser  Win%  Win  Mat  Ser Perf CapIdx
                          (Adjusted)        M  W  D  W         Pts  Pts  Pts  Pts

  1 Imran Khan       Pak (2438 198.6  17)  48 14 26  5  56.2% 11.2 36.9 11.1 43.6 102.88
  2 Ponting R.T      Aus (4698   1.1  53)  53 36  9 13  76.4% 15.3 49.8 17.8 18.9 101.71
  3 Waugh S.R        Aus (3854   3.1  34)  57 41  7 13  78.1% 15.6 49.1 15.4 14.6  94.69
  4 Sobers G.St.A    Win (3516 120.1  48)  39  9 20  3  48.7%  9.7 32.4  7.2 43.9  93.26
  5 Illingworth R    Eng (1262  53.1  24)  31 12 14  6  61.3% 12.3 41.5 13.8 22.6  90.25
  6 Chappell I.M     Aus (2463   6.0  46)  30 15 10  5  66.7% 13.3 43.5 13.8 19.6  90.14
  7 Richards I.V.A   Win (3093  18.3  49)  50 27 15  7  69.0% 13.8 44.2 12.9 16.3  87.18
  8 Lloyd C.H        Win (5114   0.0  71)  74 36 26 13  66.2% 13.2 45.1 13.3 14.8  86.34
  9 Taylor M.A       Aus (3292   1.1  84)  50 26 11 11  63.0% 12.6 41.3 15.5 15.0  84.50
 10 Cronje W.J       Saf (2912  39.4  27)  53 27 15  9  65.1% 13.0 40.8 11.6 17.4  82.93
 11 Smith G.C        Saf (5717   8.1  88)  67 33 15 14  60.4% 12.1 36.5 14.5 19.4  82.48
 12 Chappell G.S     Aus (3934  24.2  59)  48 21 14  6  58.3% 11.7 37.8 11.0 21.7  82.09
 13 Vaughan M.P      Eng (3132   1.1  27)  51 26 14  8  64.7% 12.9 43.0 12.5 13.0  81.49
 14 Brearley J.M     Eng (1060   0.0  41)  31 18  9  5  72.6% 14.5 46.5 12.2  8.2  81.37
 15 Jayasuriya S.T   Slk (2194  43.4  23)  38 18  8  8  57.9% 11.6 34.5 13.9 21.3  81.20
 16 Kapil Dev N      Ind (1351 118.7  26)  34  4 23  2  45.6%  9.1 28.5  6.7 36.6  80.91
 17 Simpson R.B      Aus (3677  41.7  62)  39 12 15  3  50.0% 10.0 34.1  6.6 29.0  79.65
 18 Dexter E.R       Eng (2393  35.7  18)  30  9 14  3  53.3% 10.7 34.8  7.5 26.1  79.04
 19 Inzamam-ul-Haq   Pak (2388   0.0  14)  31 11  9  5  50.0% 10.0 36.2 15.5 15.9  77.46
 20 May P.B.H        Eng (2971   0.0  28)  41 20 11  7  62.2% 12.4 38.9 10.2 15.2  76.72
 21 Javed Miandad    Pak (2433   0.0  32)  34 14 14  7  61.8% 12.4 36.9 12.2 15.3  76.65
 22 Ganguly S.C      Ind (2609   5.4  37)  49 21 15  9  58.2% 11.6 37.2 14.6 12.3  75.75
 23 Border A.R       Aus (6759  27.0  89)  93 32 39  9  55.4% 11.1 36.1  8.2 17.8  73.24
 24 Gooch G.A        Eng (3566   9.0  29)  34 10 12  3  47.1%  9.4 32.1  6.9 24.0  72.37
 25 Howarth G.P      Nzl (1449   1.1  21)  30 11 12  6  56.7% 11.3 36.3 13.4 10.6  71.70
 26 Hussain N        Eng (2362   0.0  27)  45 17 13  6  52.2% 10.4 38.0 11.0 11.1  70.52
 27 Fleming S.P      Nzl (5101   0.0 132)  79 28 24 13  50.6% 10.1 31.5 13.5 14.6  69.77
 28 Gavaskar S.M     Ind (3438   0.0  45)  47  9 30  4  51.1% 10.2 34.0  7.0 15.6  66.85
 29 Azharuddin M     Ind (3064   0.0  50)  47 14 19  5  50.0% 10.0 29.6  7.4 14.1  61.09
 30 Ranatunga A      Slk (3242   5.0  26)  56 12 25  6  43.8%  8.8 26.1  9.4 12.8  57.07
 31 Atherton M.A     Eng (3600   1.1  33)  54 13 20  3  42.6%  8.5 28.7  5.4 14.1  56.73
 32 Reid J.R         Nzl (2022  55.5  23)  34  3 13  0  27.9%  5.6 19.9  3.0 25.6  54.19
 33 Lara B.C         Win (4388   0.0  72)  47 10 11  4  33.0%  6.6 21.3  5.9 20.2  53.98
 34 Mansur Ali Khan  Ind (2446   1.0  26)  40  9 12  2  37.5%  7.5 23.8  5.1 13.1  49.47
 35 Gower D.I        Eng (2295   0.0  26)  32  5  9  2  29.7%  5.9 19.9  5.1 15.2  46.08

Imran Khan is deservedly on top, both for his success as a captain and as a performer. He always led from the front. His average of 50 runs & 4 wickets per test as captain are testimony to this. His top position is due to his high level of consistent performances, And that is how it should be.

Ponting has been a very good and successful captain. People might say that this was easy with world class performers such as Warne, McGrath and Gilchrist playing under him. He still had to produce the results. Incidentally he was comfortably in the top position when I started this a couple of months back. The twin losses to India and South Africa have pushed him down. Ponting has averaged nearly 95 runs per test as captain.

Steve Waugh was as charismatic as Imran Khan. He inherited a good side from Taylor and handed over nearly as good side to Ponting. The changeover of the old guard under him was smooth and effective. His performance, however, has been average. Only 65 runs per test as captain.

Gary Sobers' results as a captain have been only average. He is the one of two captains to get a below-50% success rate in the top-20. However his performances on the field as captain have been the best by anyone. 90 runs and 3 wickets per test have pushed him into the fourth place. Overall a very deserved position.

Illingworth was again a successful captain with above average performance. His Ashes wins are legendary.

It can be seen that Mike Brearley, considered by many to be possibly the best captain ever is very well placed at the 14th place. Note his results scores and his performance score. He was a great captain but a mediocre performer. He scored a very low 35 runs per test.

If there was a bravery factor introduced, Greame Smith would be at the top. His performance at Sydney was heart-warming. However his achievements came much earlier, at Perth and Melbourne. There is no doubt that, by the time he finishes his captaincy career, he would be right at the top. A performing leader, Smith averaged 85 runs per test.

Lara is placed way down the table, justifiably so. One of the greatest batsmen who ever played the game, Lara was, at best, an average captain. These statements would also apply to the other great, Tendulkar.

Kapil Dev is the best Indian captain. Readers might say that Ganguly achieved more as a captain. However Ganguly's average performance (52 runs per test as captain) pushed him down a few places. Readers must also remember that this is an all-time best captain list and Kapil's 16th and Ganguly's 22nd places are reasonable rewards for their contributions to Indian cricket.

A few interesting captaincy related points:

1. 290 players have captained their teams in the 1905 Test matches, 41 of them having done so only once.
2. Alan Border has captained in most tests, 93, followed by Stephen Fleming with 79 tests.
3. Steve Waugh has won most tests, 41, followed by Clive Lloyd and Ricky Ponting (after the great Sydney win), with 36 wins.
4. The best result has been achieved by Steve Waugh with 78.1%, followed by Ponting with 76.4%.
5. With the great Australian series win, Greame Smith has won 14 series, alone at the summit he shared with four others. Lloyd, Steve Waugh, Ponting and Fleming have 13 series wins.
6. Imran Khan has taken most wickets, 187 in 48 tests, followed by Richie Benaud with 138 in only 28 tests as captain. Incidentally Benaud has performed in an outstanding manner as a captain. In 35 other tests he has taken only 110 wickets. 7. Border leads the run tally for captains with 6623 runs in 93 tests, followed by Greame Smith with 5633 in 67 tests as captain. 

Top Test Captains - Addl report for those who captained between 20 and 29 tests

SNo Player           Cty (Runs  Wkts C/S)  Cm Cw Cd Sw   Win% WPts MPts SPts PPts CapIdx

  1 Benaud R         Aus ( 765 144.3  32)  28 12 12  5  64.3% 12.9 44.1 13.6 47.8 118.35
  2 Pollock S.M      Saf ( 946 108.7  22)  26 14  7  7  67.3% 13.5 41.0 20.3 41.6 116.36
  3 Wasim Akram      Pak ( 928 110.7  16)  25 12  5  4  58.0% 11.6 38.6 13.0 43.5 106.63
  4 Bradman D.G      Aus (3244   0.0  18)  24 15  6  4  75.0% 15.0 48.3 12.7 27.8 103.79
  5 Jayawardene M    Slk (2683   0.0  42)  26 15  4  6  65.4% 13.1 38.4 17.7 22.3  91.38
  6 Walsh C.A        Win ( 121  89.6   7)  22  6  9  4  47.7%  9.5 33.3 12.9 34.0  89.69
  7 Hutton L         Eng (1817   1.1  11)  23 11  8  4  65.2% 13.0 43.1 14.2 16.7  87.05
  8 Hassett A.L      Aus (1890   0.0  13)  24 14  6  3  70.8% 14.2 44.1  8.8 16.3  83.32
  9 Dravid R         Ind (1722   0.0  32)  25  8 11  5  54.0% 10.8 37.4 14.2 15.1  77.45
 10 Richardson R.B   Win (1260   0.0  20)  24 11  7  3  60.4% 12.1 43.1  9.9 11.3  76.34
 11 Bedi B.S         Ind ( 296  99.5   6)  22  6  5  1  38.6%  7.7 24.8  3.4 39.2  75.06
 12 Woodfull W.M     Aus (1495   0.0   2)  25 14  4  4  64.0% 12.8 39.0 11.0 12.0  74.84
 13 Lawry W.M        Aus (1921   0.0  17)  25  9  8  2  52.0% 10.4 37.2  8.0 16.0  71.61
 14 Goddard J.D.C    Win ( 658  28.6  14)  22  8  7  3  52.3% 10.5 33.5 10.4 17.0  71.42
 15 Cowdrey M.C      Eng (1663   0.0  22)  27  8 15  2  57.4% 11.5 35.3  9.7 13.1  69.60
 16 Hammond W.R      Eng (1792   3.0  28)  20  4 13  3  52.5% 10.5 28.4  9.7 20.5  69.11
 17 Darling J        Aus ( 863   0.0  15)  21  7 10  4  57.1% 11.4 36.1 11.7  8.9  68.08
 18 Smith M.J.K      Eng (1097   0.0  33)  25  5 17  2  54.0% 10.8 34.4  9.6 10.1  64.98
 19 Kardar A.H       Pak ( 873  19.8  15)  23  6 11  1  50.0% 10.0 32.5  5.0 15.1  62.57
 20 Hooper C.L       Win (1576  22.5  21)  22  4  7  2  34.1%  6.8 22.8  5.7 23.5  58.84
 21 Tendulkar S.R    Ind (1951   4.4  16)  25  4 12  2  40.0%  8.0 25.6  7.6 17.7  58.83
 22 Streak H.H       Zim (1101  54.3   8)  21  4  6  2  33.3%  6.7 15.2  4.8 31.6  58.20
 23 Gatting M.W      Eng (1555   1.8  13)  23  2 16  1  43.5%  8.7 28.6  5.0 14.7  57.05
 24 Hughes K.J       Aus (1668   0.0  18)  28  4 11  1  33.9%  6.8 23.0  3.0 12.6  45.34
 25 Flower A         Zim (1350   0.0 117)  20  1  9  0  27.5%  5.5 17.4  3.0 19.4  45.26
 26 MacLaren A.C     Eng (1311   0.0  23)  22  4  7  0  34.1%  6.8 23.6  0.0 13.0  43.41
 27 Campbell A.D.R   Zim ( 958   0.0  30)  21  2  7  1  26.2%  5.2 18.1  6.9 10.6  40.73

Richie Benaud was an outstanding leader and a great performer, averaging nearly 5 wickets and 30 runs per test as captain. The unassuming Shaun Pollock also achieved considerable success as a Test captain. These should not be forgotten because of the 2003 WC fiasco. Coupled with a high success rate he also averaged 38 runs and 4 wickets per test. Wasim Akram had slightly better figures as a performer and slightly worse figures under the results category. Don Bradman's success as a captain and performer is reflected in the fourth position. Note Jayawardene's performance. He is the only one, other than the Don, to average over 100 runs per test as captain.

If the cut-off had been lower at 25 tests, Benaud, Pollock and Wasim Akram would have taken the first three positions. I would not have too many problems with that list.

Douglas Jardine does not make the cut-off for this list also. He captained England 15 times and won 9 times, 4 of these, through the probably unethical body-line methods, against the strong Australian team. 

Top Test Captains - Addl report excluding Performance data - 20 tests and above

SNo Player           Cty  Cm Cw Cd Sw   Win% WPts MPts SPts  CapIdx

  1 Ponting R.T      Aus  53 36  9 13  76.4% 15.3 49.8 17.8   82.82
  2 Waugh S.R        Aus  57 41  7 13  78.1% 15.6 49.1 15.4   80.13
  3 Bradman D.G      Aus  24 15  6  4  75.0% 15.0 48.3 12.7   76.01
  4 Pollock S.M      Saf  26 14  7  7  67.3% 13.5 41.0 20.3   74.77
  5 Brearley J.M     Eng  31 18  9  5  72.6% 14.5 46.5 12.2   73.21
  6 Lloyd C.H        Win  74 36 26 13  66.2% 13.2 45.1 13.3   71.55
  7 Richards I.V.A   Win  50 27 15  7  69.0% 13.8 44.2 12.9   70.90
  8 Chappell I.M     Aus  30 15 10  5  66.7% 13.3 43.5 13.8   70.59
  9 Benaud R         Aus  28 12 12  5  64.3% 12.9 44.1 13.6   70.53
 10 Hutton L         Eng  23 11  8  4  65.2% 13.0 43.1 14.2   70.37
 11 Taylor M.A       Aus  50 26 11 11  63.0% 12.6 41.3 15.5   69.46
 12 Jayawardene M    Slk  26 15  4  6  65.4% 13.1 38.4 17.7   69.13
 13 Vaughan M.P      Eng  51 26 14  8  64.7% 12.9 43.0 12.5   68.50
 14 Illingworth R    Eng  31 12 14  6  61.3% 12.3 41.5 13.8   67.64
 15 Hassett A.L      Aus  24 14  6  3  70.8% 14.2 44.1  8.8   67.03
 16 Cronje W.J       Saf  53 27 15  9  65.1% 13.0 40.8 11.6   65.49
 17 Richardson R.B   Win  24 11  7  3  60.4% 12.1 43.1  9.9   65.01
 18 Ganguly S.C      Ind  49 21 15  9  58.2% 11.6 37.2 14.6   63.45
 19 Wasim Akram      Pak  25 12  5  4  58.0% 11.6 38.6 13.0   63.16
 20 Smith G.C        Saf  67 33 15 14  60.4% 12.1 36.5 14.5   63.13
This table is provided only for information. Readers can draw their own conclusion. Only comment is on how high the position of Mike Brearley is in this list, fifth.

January 2, 2009

McCullum's blitzkreig and other demolition jobs

Posted by Ananth Narayanan at in Trivia - batting
Brendon McCullum launched such an assault on Bangladesh that their bowlers didn't know what hit them © Getty Images
This is my second lightweight post in preparation for the serious analysis on Test Captains.

While I was perusing a table I found that there was an innings scoring rate of 15.83. I went back to the scorecard and saw what could be termed as the most devastating win in ODI history. I started thinking about such matches. Until now we have only looked at wins by huge number of runs or by 10 wickets as comprehensive wins. Now there is a different angle in terms of scoring rates.

This also enables us to look across both types of matches, whether teams win batting first or second. In both these matches the RpO differential is a clear indicator of the extent of domination. We should remember that a 10-wkt win need not be that dominating a victory. Imagine a team bats first and scores 200 in 40 overs. The chasing team bats very carefully and wins, say, in 45 overs by 10 wickets. This is certainly not a very comprehensive a win.

There are no qualifying conditions for this analysis. It is a very simple one of finding the RpO differential and ranking by this measure. I have separated the two tables so that we can have a clearer understanding of the win margins.

Let us look at the tables. 

Big wins in ODI matches : Batting second

No. MtId Year FBt Score         RpO WonBy Score         RpO   RpO  Result
                                                              Diff

 1. 2660 2007 Bng  93/10 (37.5) 2.46 NZL  95/ 0 ( 6.0) 15.83 13.38 10 wkts
 2. 1776 2001 Zim  38/10 (15.4) 2.43 SLK  40/ 1 ( 4.2)  9.23  6.81  9 wkts
 3. 1940 2003 Eng 117/10 (41.0) 2.85 AUS 118/ 0 (12.2)  9.57  6.71 10 wkts
 4. 1958 2003 Can  36/10 (18.4) 1.93 SLK  37/ 1 ( 4.4)  7.93  6.00  9 wkts
 5. 1961 2003 Bng 108/10 (35.1) 3.07 SAF 109/ 0 (12.0)  9.08  6.01 10 wkts
 6. 1883 2002 Hol 136/10 (50.0) 2.72 PAK 142/ 1 (16.2)  8.69  5.97  9 wkts
 7. 1221 1997 Bng 130/ 8 (43.0) 3.02 IND 132/ 1 (15.0)  8.80  5.78  9 wkts
 8. 2172 2004 Usa  65/10 (24.0) 2.71 AUS  66/ 1 ( 7.5)  8.43  5.72  9 wkts
 9. 2521 2007 Pak 107/10 (45.4) 2.34 SAF 113/ 0 (14.0)  8.07  5.73 10 wkts
10. 1464 1999 Bng 178/ 7 (50.0) 3.56 AUS 181/ 3 (19.5)  9.13  5.57  7 wkts
11. 1758 2001 Ken  90/10 (37.1) 2.42 IND  91/ 0 (11.3)  7.91  5.49 10 wkts
12. 1963 2003 Can 202/10 (42.5) 4.72 WIN 206/ 3 (20.3) 10.05  5.33  7 wkts
13. 2575 2007 Ire  77/10 (27.4) 2.78 SLK  81/ 2 (10.0)  8.10  5.32  8 wkts
14. 2574 2007 Eng 154/10 (48.0) 3.21 SAF 157/ 1 (19.2)  8.12  4.91  9 wkts
15. 1465 1999 Sco  68/10 (31.3) 2.16 WIN  70/ 2 (10.1)  6.89  4.73  8 wkts
16. 2677 2008 Eng 158/10 (35.1) 4.49 NZL 165/ 0 (18.1)  9.08  4.59 10 wkts 
(D/L)
17. 2063 2003 Eng  88/10 (46.1) 1.91 SLK  89/ 0 (13.5)  6.43  4.53 10 wkts
18. 1891 2002 Bng 154/ 9 (50.0) 3.08 SAF 155/ 0 (20.2)  7.62  4.54 10 wkts
19. 1977 2003 Can 196/10 (47.0) 4.17 NZL 197/ 5 (23.0)  8.57  4.40  5 wkts
20. 2026 2003 Pak 185/10 (44.0) 4.20 ENG 189/ 3 (22.0)  8.59  4.39  7 wkts
The first match in this table defies description. Bangladesh is not a weak team such as Hong Kong or Bermuda are. It is not clear what prompted McCullum's assault on the hapless Bangladesh bowlers. Maybe a Bangladeshi remark on beating New Zealand before the match or a personal comment on McCullum. Anyhow here are the details. Bangladesh, batting first, scored 93 in 38 overs and would have expected to pick up a wicket or two in 20 overs during which New Zealand would have cantered towards a comprehensive win.

What happened cannot be forgotten. New Zealand scored these 95 runs in 6 overs at a rate of 15.83, the highest for an innings, by a margin of over 50%, in ODI history. McCullum scored 80 in 28 balls, the second fastest completed 50+ innings in history. The difference in RpO is 13.38. The mind goes blank.

Given below is McCullum's scoring sequence. 6x6s, 9x4s and only 7 dot balls. Makes great viewing on print and should have made greater viewing, in person. Shahid Afridi, being the only batsman with a 100+ strike rate, who I consider the most attacking batsman ever in ODI cricket would have been proud to own this innings. 

4 . 4 4b . 4 6 4 6 . . 2 . 4 4 6 4 1 2 1 6 . 6 2 4 6 . 4

Look at the next entry. In terms of RpO difference, it is almost half of the first. Sri Lanka, chasing the third lowest ever ODI total of 38, reached this target in over 4 overs. McCullum might have reached in 2 overs. The blast in this match did not come from batsmen but from Vaas who took 8 for 19.

The third match is interesting. England were dismissed for 117 and then mayhem. Gilchrist and Hayden (the vintage Hayden, not the 2008 imposter) reached this target in 12 overs (including 22 boundaries).

The West Indies innings rate of 10.05, in the 12th match against Canada, is the secong highest innings scoring rate, one of only two exceeding 10.0. This was a great performance since as many as 206 runs were scored in just over 20 overs, during which 36 boundaries were scored.

Note the number of 10-wicket wins. There are 8 such wins in the top 20. Also the number of times England have been at the receiving end of such margins, four in all, sharing the lead with Bangladesh.

It is surprising that 6 of these losses have been inflicted on the top teams, England 4 times and Pakistan 2 times. Sri Lanka and South Africa lead with 4 wins each. 

Big wins in ODI matches : Batting first

No. MtId Year WonBy Score       RpO  Vs  Score         RpO  RpO   Result
                                                            Diff  Won by

 1. 2537 2007 SAF 353/ 3 (40.0) 8.82 Hol 132/ 9 (40.0) 3.30 5.53 221 runs
 2. 2542 2007 IND 413/ 5 (50.0) 8.26 Ber 156/10 (43.1) 3.61 4.65 257 runs
 3. 2716 2008 IND 374/ 4 (50.0) 7.48 Hkg 118/10 (36.5) 3.20 4.28 256 runs
 4. 2272 2005 NZL 397/ 5 (44.0) 9.02 Zim 205/10 (43.0) 4.77 4.26 192 runs
 5. 2727 2008 NZL 402/ 2 (50.0) 8.04 Ire 112/10 (28.4) 3.91 4.13 290 runs
 6. 1652 2000 SLK 299/ 5 (50.0) 5.98 Ind  54/10 (26.3) 2.04 3.94 245 runs
 7. 0297 1985 AUS 323/ 2 (50.0) 6.46 Slk  91/10 (35.5) 2.54 3.92 232 runs
 8. 2376 2006 ZIM 338/ 7 (50.0) 6.76 Ber 144/ 7 (50.0) 2.88 3.88 194 runs
 9. 1763 2001 SAF 354/ 3 (50.0) 7.08 Ken 146/10 (45.3) 3.21 3.87 208 runs
10. 1599 2000 PAK 320/ 3 (50.0) 6.40 Bng  87/10 (34.2) 2.53 3.87 233 runs
11. 0531 1988 PAK 284/ 3 (45.0) 6.31 Bng 111/ 6 (45.0) 2.47 3.84 173 runs
12. 0457 1987 WIN 360/ 4 (50.0) 7.20 Slk 169/ 4 (50.0) 3.38 3.82 191 runs
13. 2390 2006 SLK 443/ 9 (50.0) 8.86 Hol 248/10 (48.3) 5.11 3.75 195 runs
14. 0951 1994 SLK 296/ 4 (50.0) 5.92 Zim 105/10 (48.1) 2.18 3.74 191 runs
15. 2169 2004 NZL 347/ 4 (50.0) 6.94 Usa 137/10 (42.4) 3.21 3.73 210 runs
16. 1764 2001 IND 351/ 3 (50.0) 7.02 Ken 165/ 5 (50.0) 3.30 3.72 186 runs
17. 1868 2002 AUS 332/ 5 (50.0) 6.64 Pak 108/10 (36.0) 3.00 3.64 224 runs
18. 0405 1986 WIN 248/ 5 (45.0) 5.51 Slk  55/10 (28.3) 1.93 3.58 193 runs
19. 2420 2006 SAF 418/ 5 (50.0) 8.36 Zim 247/ 4 (50.0) 4.94 3.42 171 runs
20. 2532 2007 AUS 334/ 6 (50.0) 6.68 Sco 131/10 (40.1) 3.26 3.42 203 runs
It is necessary to understand the reason why South Africa's win over Holland (by 221 runs) is placed ahead of India's win over Bermuda (by 257 runs). The first was over 40 overs while the second was over 50 overs. New Zealand's win by 290 runs over Ireland has an RpO differential of only 4.13 since Ireland scored quite freely.

India has two of the most comprehensive wins in the top 5 while New Zealand also has two. But all these 5 matches are against the minnows.

The most comprehensive "relevant" win was Sri Lanka's 245 run win over India. Jayasuriya and Vaas contributed to this demolition job.

Five of the losses have been sustained by the top teams, Sri Lanka sustaining such heavy defeats thrice, all during mid-1980s. Quite a few teams, including Sri Lanka have done this thrice in the top-20 table.

Comments (24)

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