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Anantha Narayanan

How the bowlers started and finished

An analysis of how well or poorly the leading Test bowlers started and finished their illustrious careers

How the bowlers started & finished?

This is the second part of the analysis on the first ten and last ten Tests in a player's career. I looked at the batsmen in the first part and this article concentrates on the bowlers.

I am going to standardise the criteria. First, the start of a player's career is defined as the first ten Tests and the finish of his career as the last ten Tests. Ninety-two bowlers qualify with my cut-off for wickets which is 150. Sydney Barnes has crossed this landmark in the short span of 27 Tests, which is the lowest any player has played in this list. So, his middle period is only seven Tests. Because of the rather high cut-off, bowlers like Subhash Gupte, Hedley Verity, Bill O'Reilly, Fazal Mahmood, Colin Croft, Saeed Ajmal et al. do not qualify. But this cannot be helped. Lowering the cut-off to 100 wickets will mean that a few bowlers who have played either side of 20 Tests will get it and that does not seem correct.

I did not want to draw the line at the "active status" of players. That would exclude many players and is an artificial restriction, especially, since some of them may play very few Tests in future. I am also going to use Wickets-per-Test (WpT) as the measure of comparison. The Bowling-average is only an add-on information data element. The most important task of a bowler is to capture wickets and whether he captures 5 for 50 or 5 for 100, there is very little difference. 'Five-fors' are very important. It is also common knowledge that 5 for 80 scores over 4 for 50, almost always.

I have incorporated different types of analysis in this article. I have tables which list the best and worst starts among players' careers. I have the best and worst finishes among players' careers. Then I have combined the start and finish to create four different combinations. Great starts and great finishes, great starts and poor finishes, poor starts and great finishes and finally poor starts and poor finishes. These are represented in a BCG Chart, which is my favourite graph. Many insights can be drawn from these tables.

First let us look at the great starts. I have to have cut-offs for each table to keep the tables to reasonable sizes.

1. Best career starts: over 120%
CareerFirst-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-Ratio
MW Tate 3915526.163.97 6520.086.50163.5%
RJ Shastri 8015140.961.89 2730.412.70143.0%
IT Botham 10238328.403.75 5317.345.30141.1%
AME Roberts 4720225.614.30 6021.376.00139.6%
HH Streak 6521628.123.32 4621.504.60138.4%
S Venkataraghavan 5715636.122.74 3725.193.70135.2%
S Ramadhin 4315828.983.67 4929.064.90133.4%
TM Alderman 4117027.154.15 5422.635.40130.2%
WW Hall 4819226.394.00 5220.505.20130.0%
WPUJC Vaas 11135529.583.20 4120.714.10128.2%
WA Johnston 4016023.914.00 5117.205.10127.5%
JR Thomson 5120028.013.92 4923.654.90125.0%
Waqar Younis 8737323.564.29 5318.555.30123.6%
IR Bishop 4316124.293.74 4621.544.60122.9%

Maurice Tate had the best ever start for a bowler: 67 wickets at 20.0 in 10 Tests. Ravi Shastri's final figures were so poor that even the 2.7 WpT he captured during the start of his career pushed him into the second place. In a way, Srinivas Venkataraghavan was in a similar position. Ian Botham and Andy Roberts had great starts at over 5 WpT. Many famous bowlers have had wonderful starts, including Waqar Younis. It is clear that these starts would be neutralised by below-average figures for the rest of their career, especially for bowlers such as Tate and Botham.

2. Worst career starts: below 67%
CareerFirst-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-Ratio
A Flintoff 7922632.792.86 766.430.70 24.5%
AK Davidson 4418620.534.23 1337.541.30 30.8%
R Benaud 6324827.033.94 1735.711.70 43.2%
GS Sobers 9323534.042.53 1235.001.20 47.5%
SK Warne 14570825.424.88 2535.722.50 51.2%
JB Statham 7025224.853.60 2130.762.10 58.3%
JH Kallis 16228832.431.78 1130.001.10 61.9%
Mushtaq Ahmed 5218532.973.56 2337.782.30 64.6%
MD Marshall 8137620.954.64 3032.503.00 64.6%
HMRKB Herath 4419428.844.41 2934.242.90 65.8%
M Muralitharan 13380022.736.02 4027.324.00 66.5%

The figures are true. Andrew Flintoff, in whatever capacity he was playing, captured seven wickets in his first ten Tests, nine lower than Bob Massie and Narendra Hirwani captured in their first Test. Alan Davidson had a similar nightmare start, with a princely haul of 13 wickets in ten Tests. And his playing comrade, Richie Benaud, pitched in with 17. Garry Sobers and Jacques Kallis had awful starts as bowlers, capturing 12 and 11 wickets in their ten Tests. I remember that both had poor starts as batsmen also. And Shane Warne, and Muralitharan. But Muttiah Muralitharan had an excellent start, by anybody's standards, with 40 wickets. It is only his stupendous career figure which has pushed him down.

3. Best career finishes: over 110%
CareerLast-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-Ratio
HMRKB Herath 4419428.844.41 6123.676.10138.4%
AV Bedser 5123624.904.63 5919.755.90127.5%
SF Barnes 2718916.437.00 8810.688.80125.7%
KR Miller 5517022.983.09 3828.113.80122.9%
FS Trueman 6730721.584.58 5520.645.50120.0%
CV Grimmett 3721624.225.84 6918.996.90118.2%
MS Panesar 4816433.783.42 3933.953.90114.1%
AK Davidson 4418620.534.23 4722.384.70111.2%
Iqbal Qasim 5017128.113.42 3824.663.80111.1%

These are the great finishers. They retired at the top, so to say. Rangana Herath is still active and his presence at the top is a testament to his phenomenal form over the past year. He led the wicket-takers table for 2012-13. Alec Bedser finished very strongly. Sydney Barnes finished with 88 wickets, most of it against South Africa in two series. If anyone glances through this illustrious set of bowlers, it is a representation of truly great bowlers across the generation: Barnes, Fred Trueman, Clarrie Grimmett and Davidson. Davidson made up for his miserable start with this good finish. Monty Panesar is still active and could go better or worse.

4. Worst career finishes: below 60.5%
CareerLast-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-Ratio
Imran Khan 8836222.814.11 1328.151.30 31.6%
IR Bishop 4316124.293.74 1448.711.40 37.4%
IT Botham 10238328.403.75 1655.621.60 42.6%
Mushtaq Ahmed 5218532.973.56 1672.621.60 45.0%
RJ Shastri 8015140.961.89 1047.601.00 53.0%
Abdul Qadir 6723632.813.52 2046.952.00 56.8%
J Srinath 6723630.473.52 2040.952.00 56.8%
Waqar Younis 8737323.564.29 2535.202.50 58.3%
GD McKenzie 6024629.794.10 2442.622.40 58.5%
FJ Titmus 5315332.232.89 1745.001.70 58.9%
A Kumble 13261929.654.69 2851.072.80 59.7%
Kapil Dev 13143429.653.31 2027.552.00 60.4%
MW Tate 3915526.163.97 2429.332.40 60.4%

They finished poorly and probably after their sell-by-date. Imran Khan's presence is understandable since he played most of his later Tests as a batsman. But the fall of Ian Bishop and Botham was dramatic: they captured only 14 and 16 wickets in their last 10 Tests. Shastri fell off as a bowler. Javagal Srinath as a shadow of his peak period. But look at Abdul Qadir. Like his mentor, Imran, he also finished with a whimper: 20 wickets in ten Tests to finish his career. Waqar, who had a great start, fares poorly here. Anil Kumble and Kapil Dev round off this list. The presence of so many Indian bowlers in this list should make one think: do these bowlers stretch their career about a series or two past their retirement? Kapil, often highlighted in India for stretching his career, still finished with 20 wickets, a reasonable performance for an allrounder. Combined with his good batting finish, quite good: maybe he is the wronged player in this regard.

Now for the combination analysis. I have considered the two percentage values, start and finish and got them grouped into four combination groups. Not all bowlers are covered though. For each combination I have set different criteria and grouped the players. This is to ensure that the graph is not too crowded. The absence of players from these four groups basically means that they are in the circle in the centre. You can have a look at all players by perusing the downloadable file.

To represent these selected players I have used my favourite BCG chart. BCG stands for Boston Consulting Group for whom Bruce Henderson invented this method of depicting growth-share matrix for companies. It has since found many uses and I have used this graph extensively. When there are two independent measures, the quadrant-based representation of BCG chart is an excellent visual method of classifying players. In this case the two independent measures are the first-10-Test precentages and the last-10-Test percentages. These two measures form four groups and lend themselves to an excellent BCG representation.

We have the first-10-Tests WpT percentages in the X-axis and the last-10-Tests WpT % in the Y-axis. The graph is split into four quadrants. The top-right quadrant represents great starts and great finishes. The top-left quadrant represents poor starts and great finishes. The bottom-left quadrant represents poor starts and poor finishes. The bottom-right quadrant represents great starts and poor finishes. Let us now look at the graph.

Since I am going to show the tables for all these classifications I am not going to dwell too long on the graph now since the tables with detailed data for these players are presented later.

Now let us move on to the tables containing these group combinations.

5. Great start and great finish
CareerFirst-10Last-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-RatioWicketsAverageWpTWpT-Ratio
FS Trueman 6730721.584.58 5122.595.10111.3% 5520.645.50120.0%
AV Bedser 5123624.904.63 4829.294.80103.7% 5919.755.90127.5%
J Garner 5825920.984.47 5222.775.20116.4% 4718.324.70105.3%
CJ McDermott 7129128.634.10 4332.234.30104.9% 4525.934.50109.8%
CS Martin 7123333.813.28 3332.363.30100.6% 3428.793.40103.6%
Saqlain Mushtaq 4920829.834.24 4335.234.30101.3% 4333.584.30101.3%

This table gives the full details of the combination analysis. The criteria here are that both percentage values should be over 100%. Trueman had the best start and best finish, considered together: 51 and 55 wickets respectively. This necessarily means that his middle period was below par. He captured only 201 wickets in these 47 Tests, an average of 4.27 WpT, compared to a career value of 4.58. It is clear that it is not easy to start and finish well, as evidenced by the fact that only 6 bowlers meet these criteria. The only modern bowler is Chris Martin, who has almost certainly played his last Test for New Zealand.

6. Poor start and poor finish
CareerFirst-10Last-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-RatioWicketsAverageWpTWpT-Ratio
Mushtaq Ahmed 5218532.973.56 2337.782.30 64.6% 1672.621.60 45.0%
J Srinath 6723630.473.52 2538.802.50 71.0% 2040.952.00 56.8%
JH Kallis 16228832.431.78 1130.001.10 61.9% 1232.001.20 67.5%
BS Bedi 6726628.713.97 2935.282.90 73.0% 2548.082.50 63.0%
M Muralitharan 13380022.736.02 4027.324.00 66.5% 4435.824.40 73.2%

This is the other end of the table. Bowlers whose starts and finishes were below par. The criterion is that both percentages should be below 75%. Again very few bowlers have got into this combination. Bishan Bedi and Srinath represent India. Surprising that Bedi should figure in this, having played some of his initial Tests in India. The other great bowler to figure here is Muralitharan. This also means that Muralitharan captured 716 wickets during the interim 113 Tests at a WpT value of 6.33. But let us face it. Muralitharan sits here, despite capturing 4 WpT during both start and finish, only because of his way-out career WpT value of 6.02. The other interesting presence is Kallis. Readers might remember that Kallis also had a poor start. So he started his career poorly. However it is possible that he was pulling his weight as an allrounder. His recent form, as a bowler, has been poor. This might change in the future.

7. Great start and poor finish
CareerFirst-10Last-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-RatioWicketsAverageWpTWpT-Ratio
MW Tate 3915526.163.97 6520.086.50163.5% 2429.332.40 60.4%
IT Botham 10238328.403.75 5317.345.30141.1% 1655.621.60 42.6%
RJ Shastri 8015140.961.89 2730.412.70143.0% 1047.601.00 53.0%
IR Bishop 4316124.293.74 4621.544.60122.9% 1448.711.40 37.4%
S Venkataraghavan 5715636.122.74 3725.193.70135.2% 1758.711.70 62.1%
Waqar Younis 8737323.564.29 5318.555.30123.6% 2535.202.50 58.3%
WW Hall 4819226.394.00 5220.505.20130.0% 2637.922.60 65.0%
WA Johnston 4016023.914.00 5117.205.10127.5% 2832.822.80 70.0%
A Kumble 13261929.654.69 5324.665.30113.0% 2851.072.80 59.7%
EAS Prasanna 4918930.383.86 4334.914.30111.5% 2635.352.60 67.4%

These bowlers had wonderful starts but finished very poorly. The criteria are that they should have started at over 110% and finished at below 70%. We have already seen these bowlers in the best start category- Botham. Bishop and Shastri had excellent starts, relative to their respective careers, but failed quite badly at the end. Bishop finished the worst. No doubt caused by the debilitating injury. Many others did not know when to quit, a malaise present with many batsmen too. Tate had a difference of over 100% between start and finish, the only bowler in this group.

8. Poor start and great finish
CareerFirst-10Last-10
BowlersTestsWicketsAverageWpTWicketsAverageWpTWpT-RatioWicketsAverageWpTWpT-Ratio
AK Davidson 4418620.534.23 1337.541.30 30.8% 4722.384.70111.2%
HMRKB Herath 4419428.844.41 2934.242.90 65.8% 6123.676.10138.4%
GS Sobers 9323534.042.53 1235.001.20 47.5% 2729.332.70106.9%
SK Warne 14570825.424.88 2535.722.50 51.2% 4929.004.90100.4%
DW Steyn 6533222.665.11 3832.583.80 74.4% 5320.025.30103.8%

These bowlers had nightmare starts and fairy-tale finishes. Davidson started very poorly but finished quite well. Herath's "finish" is on-going and would change. Warne also finished very well. Dale Steyn is still playing and his figures will change. So there are only three players in this table unlike the batsmen table which was reasonably well populated.

Some readers might query that quite a few top players have not found a mention in this analysis. The point is that this article is about exceptions, on either side and in combination. Quite a few players are somewhere in the middle. As Craig Dengate put it nicely in his comment on the Batsmen start and finishes, the non-mention of a bowler in these tables would be a testament to the very steady career these bowlers had. Just to clarify this further, I have given below the values for seven top bowlers across the ages that have not been referred to. This will clarify why these have not found a mention.

 
	 
	Bowler Career-----> First 10-----> Last 10 ---->
GD McGrath 124 563 4.54 33 3.30 72.7% 38 3.80 83.7% RJ Hadlee 86 431 5.01 37 3.70 73.8% 43 4.30 85.8% Wasim Akram 104 414 3.98 34 3.40 85.4% 27 2.70 67.8% CEL Ambrose 98 405 4.13 43 4.30 104.0% 36 3.60 87.1% DK Lillee 70 355 5.07 51 5.10 100.6% 34 3.40 67.0% AA Donald 72 330 4.58 46 4.60 100.4% 33 3.30 72.0% JM Anderson 81 305 3.77 29 2.90 77.0% 35 3.50 93.0%

Wasim Akram and Dennis Lillee just about missed the poor finish list. However they were still reasonably okay since they captured 27 and 34 wickets. The others have had fairly good starts and finishes. In terms of sheer consistency, the best bowler in this elite lot is Curtly Ambrose.

To download/view the list of 92 bowlers and the complete tables ordered in different forms, in Text file format, please CLICK HERE.

A couple of readers had asked me for my comments on the recent off-field happenings. I had incorporated my comments in this article. Unfortunately, these did not meet the current editorial policy standards of ESPNcricinfo. If you want to see the comments you have to mail me directly at ananth.itfigures@gmail.com. I appreciate and understand ESPNcricinfo's reservations.

Full post
Test careers that started and finished strong

An analysis of how well or poorly the leading Test batsmen started and finished their illustrious careers

How they started and how they finished: the batsmen

The idea for this article came to me when Hussey announced his retirement from International cricket towards the end of 2012. I had an instinctive feeling that Michael Hussey had a great start to his career as well as a great end. I thought it was worthwhile looking at the start and end of the careers of all players. And I was almost certain that another player, right at the top of many batting lists, would announce his retirement from Test cricket if he had an ordinary home series against Australia. Well, Sachin Tendulkar had an ordinary series but he did not announce his retirement.

However, I did not want one player's inability to take a call on his fabulous but fading career have an influence on the timing of an important article. Hence, I have done this article knowing fully well that Tendulkar is still on for at least the next series. Let me also say this. Tendulkar's last ten Tests have been played at home and he has scored 367 runs at an average of 24.46. In three away-Tests in the forthcoming Test series against South Africa, facing Dale Steyn, Morne Morkel and Vernon Philander, would he suddenly score 400-500 runs? Even the staunchest of Tendulkar's supporters would realise the futility of such expectations. It is likely that he scores only 200 to 250 runs in these three Tests. So this article might only undergo minor changes.

I am going to standardise the criteria. First, the start of a player's career is defined as the first ten Tests and the finish of his career as the last ten Tests. The cut-off for this analysis is batsmen with 4,000-or-more Test runs and thus, 115 batsmen qualify. Everton Weekes crossed 4,000 comfortably and played 48 Tests, which is the lowest any player has played in this list. So, even he has a middle period of 28 Tests. Because of the rather high cut-off, batsmen like Hanif Mohammad, Dean Jones, Arthur Morris, Tony Greig, Clem Hill et al. do not qualify. But this also means that non-batsmen such as Shane Warne, Chaminda Vaas, Wasim Akram and a host of wicket-keeper-batsmen are also excluded. And, I am very close to the 50-Test cut-off which I was aiming at.

I did not want to filter out players who are still playing Test cricket. That would exclude many players and is an artificial restriction, especially since some of them may play very few Tests in future. I am also going to use the Batting average as the measure of comparison. It is the most used and acceptable of performance measures. Runs-per-Test value implies quantity rather than performance and Runs-per-Innings metric has its own shortcomings especially as we have batsmen who have batted from no.1 to no.8.

I had initially planned to complete both batsmen and bowlers in the same article. Then, as normally happens, I ended with 8 tables and one graph for the batsmen. I did not want to test the ability of cricinfo's production team to handle 16 tables and two graphs in one article. So the article on the bowlers is the next one.

I have incorporated different types of analysis in this article. I have tables which list the best and worst starts to the player's career. I have the best and worst finishes to a player's career. Then I have combined the start and finish to create 4 different combinations. Great starts and great finishes, great starts and poor finishes, poor starts and great finishes and finally poor starts and poor finishes. These are represented in a BCG(Boston Consultancy Group) Chart, which is my favourite graph. Many insights can be drawn from these tables.

First let us look at the great starts. In order to keep the tables to reasonable sizes I have to have cut-offs for each table.

1. Best career starts: over 125%
BatsmanTestsRunsAverageStart-InnsNOsRunsAverageRatio
RN Harvey 79 6149 48.4215 41045 95.00196.2%
TT Samaraweera 81 5462 48.7710 3 581 83.00170.2%
MA Taylor 104 7525 43.5018 11088 64.00147.1%
KD Walters 74 5357 48.2616 3 903 69.46143.9%
AJ Strauss 100 7037 40.9120 21055 58.61143.3%
N Kapil Dev 131 5248 31.0514 2 510 42.50136.9%
Javed Miandad 124 8832 52.5717 4 917 70.54134.2%
MEK Hussey 79 6235 51.5318 4 957 68.36132.7%
H Sutcliffe 54 4555 60.7314 11037 79.77131.3%
IT Botham 102 5200 33.5512 1 479 43.55129.8%
EdeC Weekes 48 4455 58.6215 01125 75.00127.9%
DL Haynes 116 7487 42.3018 1 918 54.00127.7%

Neil Harvey had the best start that any top cricketer has ever had. He had six hundreds in his first ten Tests and averaged 95.00. That is nearly 200% of his career figure. Thilan Samaraweera had a similar start, achieving over 170% of his career average. Mark Taylor, Doug Walters, Andrew Strauss and Michael Hussey should not surprise anyone. My hunch about Hussey was correct. But look at the starts Kapil Dev and Ian Botham had. They had averages like regular batsmen. Herbert Sutcliffe also had a near-80 average. It is surprising that only Sutcliffe, Javed Miandad and Hussey finished with a 50+ career average while the others dropped off.

2. Worst career starts: below 60%
BatsmanTestsRunsAverageStart-InnsNOsRunsAverageRatio
JH Kallis 16213128 56.1015 0 340 22.67 40.4%
SR Waugh 16810927 51.0616 3 271 20.85 40.8%
MS Atapattu 90 5502 39.0219 0 321 16.89 43.3%
MD Crowe 77 5444 45.3716 0 331 20.69 45.6%
HM Amla 70 5785 52.1219 0 455 23.95 45.9%
HH Gibbs 90 6167 41.9519 0 380 20.00 47.7%
DB Vengsarkar 116 6868 42.1318 1 350 20.59 48.9%
ML Hayden 103 8626 50.7416 0 413 25.81 50.9%
GS Sobers 93 8032 57.7817 3 419 29.93 51.8%
DC Boon 107 7422 43.6618 0 431 23.94 54.8%
DL Vettori 112 4516 30.1117 4 230 17.69 58.8%
JL Langer 105 7696 45.2715 0 402 26.80 59.2%

This is the other end of the table. Players, who had miserable starts to their careers. I knew about Steve Waugh's very poor start to his Test career, averaging 20.8. However, I could have never imagined that Jacques Kallis, who is currently averaging 56.1, started his career with an average of 22.67, which is around 40%, the same as Waugh's. Marvan Atapattu's starting sequence of 0 0 0 1 0 0 meant that he was going to be a contender for the worst start. It is a miracle that he has been upstaged by Kallis and Waugh. A knock of 149 runs in the 10th Test took care of that. But his average of 16.89 is the lowest by any batsman in this group at the end of the 10th test. It is surprising to see very poor starts by Martin Crowe and Hashim Amla, who currently averages over 52. But here comes the ball-to-Mike Gatting. Look at the awful start of Garry Sobers. A Kris Srikkanth-like 29.93. The amazing feature of this table is that four of these batsmen recovered very well, to post career averages exceeding 50.

3. Best career finishes: over 125%
BatsmanTestsRunsAverageFinish-InnsNOsRunsAverageRatio
S Chanderpaul 14810830 51.8215 41006 91.45176.5%
SR Waugh 16810927 51.0614 4 863 86.30169.0%
G Kirsten 101 7289 45.2718 31003 66.87147.7%
MS Dhoni 77 4209 39.7115 3 700 58.33146.9%
MJ Clarke 92 7275 52.3418 21227 76.69146.5%
CH Gayle 97 6836 42.4617 3 859 61.36144.5%
CL Hooper 102 5762 36.4715 0 742 49.47135.6%
KC Sangakkara 11710486 56.9919 41125 75.00131.6%
DL Haynes 116 7487 42.3017 4 719 55.31130.8%
N Kapil Dev 131 5248 31.05 9 2 283 40.43130.2%
RC Fredericks 59 4334 42.4920 2 974 54.11127.3%

These are the great finishers. They retired at the top, so to say. Shivnarine Chanderpaul, MS Dhoni, Michael Clarke, Kumar Sangakkara and Chris Gayle are still active and this value represents what they did in their last ten Tests. The amazing thing is the performance of Steve Waugh. Starting at 40%, he finished at 169%. Gary Kirsten, Carl Hooper, Desmond Haynes and Roy Fredericks all finished right at the top. Kapil Dev who appeared in the first Table has also finished well, though as a batsman. When I do the bowling article he is likely to find himself at the other end of the spectrum. It is safe to say that this finish helped Steve Waugh have a very good average.

4. Worst career finishes: below 60%
BatsmanTestsRunsAverageFinish-InnsNOsRunsAverageRatio
IA Healy 119 4356 27.4017 0 138 8.12 29.6%
PD Collingwood 68 4260 40.5713 0 202 15.54 38.3%
Mudassar Nazar 76 4114 38.0916 0 249 15.56 40.9%
AI Kallicharran 66 4399 44.4314 1 253 19.46 43.8%
SR Tendulkar 19815837 53.8716 1 367 24.47 45.4%
GA Gooch 118 8900 42.5819 0 397 20.89 49.1%
TT Samaraweera 81 5462 48.7718 0 440 24.44 50.1%
KJ Hughes 70 4415 37.4219 0 372 19.58 52.3%
DR Martyn 67 4406 46.3818 2 392 24.50 52.8%
MC Cowdrey 114 7624 44.0717 0 396 23.29 52.9%
ST Jayasuriya 110 6973 40.0718 0 393 21.83 54.5%
DB Vengsarkar 116 6868 42.1316 0 370 23.12 54.9%
MP Vaughan 82 5719 41.4417 0 388 22.82 55.1%
Inzamam-ul-Haq 120 8830 49.6118 2 439 27.44 55.3%
ML Hayden 103 8626 50.7418 1 486 28.59 56.3%
L Hutton 79 6971 56.6716 0 511 31.94 56.4%
GR Viswanath 91 6080 41.9315 1 334 23.86 56.9%
V Sehwag 104 8586 49.3417 0 498 29.29 59.4%
H Sutcliffe 54 4555 60.7314 1 471 36.23 59.7%

These batsmen finished very poorly. Ian Healy can be given a miss. Paul Collingwood, Alvin Kallicharran and Mudassar Nazar had nightmare finishes to their careers. But not at the same level as the next entry - Tendulkar. As already mentioned, Tendulkar, in his last 10 Tests, all at home, averaged 24.46. The writing on the wall is big and bright but is unfortunately not seen by many. "He should take the call" is the refrain used by all people, including even the latest entrants to the IPL gravy train. Would any other batsman have survived this level of performance? One really good innings, the fluent and very valuable-81 at Chennai, out of the 16 during the recent past. Graham Gooch also has finished below 50% too. Then a set of quality players have all finished below 60%. The fact that there are 19 players in this sub-60 list indicates that many batsmen stay beyond their sell-by date. And the presence of greats like Tendulkar, Len Hutton, Sutcliffe, Gundappa Viswanath, and Inzamam-ul-Haq in this lot is a matter to ponder over.

Now for the combination analysis. I have considered the two percentage values, start and finish and got them grouped into 4 combination groups. Not all batsmen are covered though. For each combination I have set different criteria and grouped the players. This is to ensure that the graph is not too crowded. The absence of players from these four groups basically means that they are in the circle in the centre. You can have a look at all players by perusing the downloadable file.

To represent these selected players I have used my favourite BCG chart. BCG stands for Boston Consulting Group for whom Bruce Henderson invented this method of depicting growth-share matrix for companies. It has since found many uses and I have used this graph extensively. When there are two independent measures, the quadrant-based representation of BCG chart is an excellent visual method of classifying players. In this case the two independent measures are the first-10-test % and the last-10-test %. These two measures form four groups and lend themselves to an excellent BCG representation.

We have the first-10-tests average percentage in the X-axis and the last-10-tests average % in the Y-axis. The graph is split into four quadrants. The top-right quadrant represents great starts and great finishes. The top-left quadrant represents poor starts and great finishes. The bottom-left quadrant represents poor starts and poor finishes. The bottom-right quadrant represents great starts and poor finishes. Let us now look at the graph.

Since I am going to show the tables for all these classifications I am not going to delve too long on the graph now. Let me highlight a few top players who are presented in the graph. Barring Kapil Dev, the top-right quadrant features many top players including Sunil Gavaskar, Chanderpaul and David Gower. Sutcliffe, Everton Weekes and Miandad are in the bottom-right quadrant. A number of top batsmen including Gooch, Michael Vaughan, Inzamam and Matthew Hayden are in the bottom-left quadrant. The top-left quadrant features Waugh, Sangakkara, Ian Chappell and of course, Kallis.

Now let us move on to the tables containing these group combinations. More players are featured in these tables than the graph.

5. Great start and great finish
BatsmanTestsRunsAverageSTART-InnsNOsRunsAverage% of Career avgeFINISH-InnsNOsRunsAverage% of Career avge
S Chanderpaul 14810830 51.8214 4 618 61.80119.3%15 41006 91.45176.5%
MA Taylor 104 7525 43.5018 11088 64.00147.1%19 2 905 53.24122.4%
N Kapil Dev 131 5248 31.0514 2 510 42.50136.9% 9 2 283 40.43130.2%
DL Haynes 116 7487 42.3018 1 918 54.00127.7%17 4 719 55.31130.8%
JH Edrich 77 5138 43.5415 2 657 50.54116.1%17 2 801 53.40122.6%
MEK Hussey 79 6235 51.5318 4 957 68.36132.7%18 3 786 52.40101.7%
SM Gavaskar 12510122 51.1220 4 978 61.12119.6%13 0 755 58.08113.6%
DI Gower 117 8231 44.2516 1 763 50.87114.9%19 4 776 51.73116.9%
AB de Villiers 85 6364 50.5117 1 841 52.56104.1%17 2 907 60.47119.7%
CH Lloyd 110 7515 46.6818 3 795 53.00113.5%14 2 611 50.92109.1%
M Azharuddin 99 6215 45.0416 2 711 50.79112.8%18 2 739 46.19102.6%
AN Cook 90 7307 49.0418 2 815 50.94103.9%19 1 947 52.61107.3%

This table gives the full details of the combination analysis. The criteria here are that both percentage values should be over 100. Chanderpaul is still active. However a start of 119.3% and a finish (on-going) of 176.5% is magnificent. The player that Chanderpaul is, he is unlikely to suffer a drastic loss of form. Mark Taylor had an equally spectacular start and finish to his career. Kapil Dev is the only non-batsman in this list. Hussey had a wonderful start and a very good finish. Gavaskar, the true professional, knew when to quit, complementing his excellent start. AB de Villiers and Alastair Cook are currently active players who could go off this list if their current form drops. Let us not forget that Chanderpaul, Hussey, Gavaskar and de Villiers have achieved this with career averages of 50+. Chanderpaul averages 48.96 during the middle 128 Tests.

6. Poor start and poor finish
BatsmanTestsRunsAverageSTART-InnsNOsRunsAverage% of Career avgeFINISH-InnsNOsRunsAverage% of Career avge
VVS Laxman 134 8781 45.9716 2 405 28.93 62.9%19 2 569 33.47 72.8%
RB Kanhai 79 6227 47.5319 2 505 29.71 62.5%16 2 479 34.21 72.0%
MW Gatting 79 4409 35.5618 1 390 22.94 64.5%19 0 425 22.37 62.9%
Mohammad Yousuf 90 7530 52.2918 1 588 34.59 66.1%20 0 636 31.80 60.8%
DC Boon 107 7422 43.6618 0 431 23.94 54.8%15 0 463 30.87 70.7%
KJ Hughes 70 4415 37.4219 0 513 27.00 72.2%19 0 372 19.58 52.3%
MP Vaughan 82 5719 41.4416 0 439 27.44 66.2%17 0 388 22.82 55.1%
Inzamam-ul-Haq 120 8830 49.6117 2 466 31.07 62.6%18 2 439 27.44 55.3%
GA Gooch 118 8900 42.5817 2 414 27.60 64.8%19 0 397 20.89 49.1%
HH Gibbs 90 6167 41.9519 0 380 20.00 47.7%17 1 439 27.44 65.4%
ML Hayden 103 8626 50.7416 0 413 25.81 50.9%18 1 486 28.59 56.3%
DB Vengsarkar 116 6868 42.1318 1 350 20.59 48.9%16 0 370 23.12 54.9%
IA Healy 119 4356 27.4014 0 231 16.50 60.2%17 0 138 8.12 29.6%

This is the other end of the table. Batsmen whose starts and finishes were below par. The criterion is that both numbers should be below 75%. There are a number of batsmen in this list. Laxman's drop in form and indifferent start are fresh in our memory. Spare a thought for top class batsmen like Gooch, Hayden and Dilip Vengsarkar who had poor starts and finishes. This double low figures also indicate that the career of these batsmen between the 11th and 11th-last Test has been very good: much better than their career averages. Let me take the striking examples of Hayden and Gooch. Hayden averaged 56.40 during the 83 matches in between and Gooch, 46.22 during the intermediate 98 Tests.

7. Great start and poor finish
BatsmanTestsRunsAverageSTART-InnsNOsRunsAverage% of Career avgeFINISH-InnsNOsRunsAverage% of Career avge
TT Samaraweera 81 5462 48.7710 3 581 83.00170.2%18 0 440 24.44 50.1%
H Sutcliffe 54 4555 60.7314 11037 79.77131.3%14 1 471 36.23 59.7%
IT Botham 102 5200 33.5512 1 479 43.55129.8%15 2 271 20.85 62.1%
Javed Miandad 124 8832 52.5717 4 917 70.54134.2%17 1 569 35.56 67.6%
AI Kallicharran 66 4399 44.4317 2 725 48.33108.8%14 1 253 19.46 43.8%
EdeC Weekes 48 4455 58.6215 01125 75.00127.9%18 1 650 38.24 65.2%
MA Atherton 115 7728 37.7019 0 840 44.21117.3%19 0 448 23.58 62.5%
V Sehwag 104 8586 49.3413 0 693 53.31108.0%17 0 498 29.29 59.4%

These batsmen had a wonderful start but finished very poorly. The criteria are that they should have started at over 105% and finished at below 75%. Not many qualify. Samaraweera had the biggest difference between the start and finish, a huge 120%. Sutcliffe, Miandad and Weekes had substantial drops. Virender Sehwag's recent travails are reflected in this table. He averages at only 60% of his career. His return back to the Test team is uncertain. More so since he is not the one to decide when he should quit. He is under the selectorial hammer. Kallicharran probably had the worst end to his career.

8. Poor start and great finish
BatsmanTestsRunsAverageSTART-InnsNOsRunsAverage% of Career avgeFINISH-InnsNOsRunsAverage% of Career avge
SR Waugh 16810927 51.0616 3 271 20.85 40.8%14 4 863 86.30169.0%
G Kirsten 101 7289 45.2718 0 568 31.56 69.7%18 31003 66.87147.7%
HM Amla 70 5785 52.1219 0 455 23.95 45.9%17 11010 63.12121.1%
RC Fredericks 59 4334 42.4919 0 525 27.63 65.0%20 2 974 54.11127.3%
KC Sangakkara 11710486 56.9917 1 638 39.88 70.0%19 41125 75.00131.6%
JG Wright 82 5334 37.8318 0 438 24.33 64.3%20 1 854 44.95118.8%
IM Chappell 75 5345 42.4216 1 409 27.27 64.3%19 3 799 49.94117.7%

These batsmen had a nightmare start and a fairy-tale finish. Steve Waugh: what can one say! He has one of the worst starts any player would have had, averaging just over 20 and finishes with an average of 86.3. This is the perfect example of quitting at the top. Generally Indians talk of Gavaskar's timing of his departure. But he averaged only 58 in the last 10 Tests. Look at Steve Waugh. Amla and Sangakkara are active players and their figures are bound to change. Look at the way Gary Kirsten and Ian Chappell ended their careers. At least Chappell is here because of his low career average. But Kirsten averaged almost 67 at the end.

Some readers might query that quite a few top players have not found a mention in this analysis. The point is that this article is about exceptions, on either side and in combination. Quite a few players are somewhere in the middle. Just to clarify this further I have given below the values for 7 top players across the ages who have not been referred to. This will clarify why these have not found a mention.

Hobbs        61  5410  56.95  785  46.18  81.1%  754  41.89  73.6%
Bradman      52  6996  99.94 1446  96.40  96.5% 1223 111.18 111.2%
Barrington   82  6806  58.67  727  51.93  88.5%  722  65.64 111.9%
Richards    121  8540  50.24  471  31.40  62.5%  550  39.29  78.2%
Lara        131 11953  52.89  812  47.76  90.3%  749  41.61  78.7%
Ponting     168 13378  51.85  670  41.88  80.8%  722  45.12  87.0%
Dravid      164 13288  52.31  773  48.31  92.3%  835  46.39  88.7%
Jayawardene 138 10806  49.57  750  46.88  94.6%  720  40.00  80.7%

Don Bradman just about missed the Great-Great combination. Richards just about missed the Poor-Poor combination. The others are right in the middle.

To download/view the list of 115 batsmen and the complete tables ordered in different forms, in Text file format, please CLICK HERE and to download/view the list of 115 batsmen and the complete tables ordered in different forms, in Excel format, please CLICK HERE.

Full post
The tightest draws in Test cricket

A comprehensive analysis of all tied Tests and drawn Tests across the eras, and a list of the most fascinating contests that were tied or drawn

This is the follow-up to the article on Test results. The initial article covered results and this one will cover the fascinating area of ties and draws. It is my personal opinion that there is as much excitement in saving a tough match as there is in winning a close match. The techniques required are different yet comparable. If you ask a captain which is tougher: scoring 150 in 40 overs to win a Test or survive the final day to draw the Test? Many captains would vote for the later task.

Unfortunately, the obsession with winning, the American dicta that there has to be a winner and winning is everything, and similar attitudes have made the cricket followers look down on Test cricket. Someone asked me "How can any one play for five days and not have a result?", I would ask him "You are ready to spend two hours watching a football match and eulogize a 3-3 result, why not this?". Availability of time is relative. Five days might be too long for some people, two hours too long for some others, 30 minutes too long for someone else. One should not put down tradition just because one does not have time to appreciate it. Or because one does not have the patience. Or because there is a crowd of 5,000 in a Test match and 50,000 in an IPL match. Or because there has to be a winner in every contest. And so on.

It is necessary to respect tradition while paving the way for the new elements. If we do not respect tradition and the old school, and allow the new to completely bull-doze the old, we will be left with high-budget, colourful, glitzy and vacuous shows. As someone succinctly put it, these are "time-pass" matches, to be put on par with the three-hour action thriller films which come out, three a week. If we allow Test cricket to fade away, the result would be similar to the disappearance of classic films like "Citizen Kane", "Casablanca", "Rashomon", "Seven Samurai", "Bicycle Thief", "Do Bigha Zamin", "Mother India", "Do Aankhen Barah Haath", "Nirmalyam", "Desadanam", "Pava Mannippu", "Punnagai", "Kappalottiya Thamizhan", "Thanneer Thanneer!", "Sagara Sangamam", "Tabarana Kathe", "Shyamchi Aai", "Nagara Haavu", "Sudi Guntalu", "Apur Sansar", "Charulata", "Aparajito" et al. We will be left with three-hour extravaganzas, mind-numbing, watch-and-forget, form-over-content types, both on field and on screen, with an unseemly alliance between both.

Has Tennis gone the cricket way? No. They have not replaced the five-set matches with single-set winner-takes-all contests, as dictated by the Television demands; or introduced 31-point tie-breaker sets so that the match could finish in 60 minutes. They are ready to have matches going 5-6 hours and beyond. And these are watched by 15,000 in the stadia and billions around the world. They might have changed the racket material and got in tie-breakers, but have remained true to the basic game. Let me also state that there are five-set classics such as Nadal-Federer, Borg-McEnroe, Graf-Sanchez and Federer-Roddick at Wimbledon, Djokovic-Murray, Djokovic-Nadal and Djokovic-Wawrinka at Melbourne, Santoro-Clament at Paris did not warrant a loser. A draw would have been an appropriate result. For that matter let us not forget Isner-Mahut at Wimbledon.

Draws are part of the Test match scenario. Of course, quite a few of the draws are dull and dreary, as can be seen in later classifications. But there are many draws which are hard-fought and no quarter given either way. I would any day view a gripping draw which finished in the last over than a 3-day drubbing of a hapless team by a strong one.

The comments for Part-1 were very revealing. Most readers only saw the anecdotal part of the article, pushing in their own memories, but almost no one commented on the analytical aspects of the article. My suggestion is "do both". Otherwise, these articles lose their value. Is it because of the new restrictions imposed that many readers have stopped sending in their comments? Anyhow, because of the lack of response to the tables and new ideas, I will present these with minimal comments. You readers have made this small corner of Cricinfo wonderful and you have to continue to do so, irrespective of the fact that I have had to move house, so to speak.

First, let me talk about the ties. It is a totally fascinating facet of the game. I love the way Milind has coined the phrases "perfect" and "imperfect" ties. Once we understand the terms, we wonder why we did not think of it. This interpretation was also needed by us for our contribution project.

Let us define these words. A perfect tie is one in which all available resources have been exhausted during the match, not just the last innings. In other words, all 40 wickets have been captured. The overs resource does not matter since the match ends when the last wicket is captured. No more deliveries can be bowled. The Brisbane tie during the 1960/61 season is an example of a perfect tie. More on this match in the later anecdotal section. Okay, the "ultra-perfect" tie, coined by me during the past minute, is one which finishes off the last available ball.

Now any reader can figure the other one by himself. The imperfect tie is one in which fewer than 40 wickets have been captured. The second tie, the Chennai match played during 1986, was an imperfect one. Australia lost only 12 wickets because they declared in both their innings. Some resources have not been used. Now, where it matters is in the team and batting/bowling allocations. For the Brisbane tie, both teams would get equal points and the batsmen and bowlers of both teams would get equal points. For the Chennai match, the Indian bowlers would get fewer points than the Indian batsmen. This match is also covered later.

There were a few matches which came close to another tie. The Mumbai Test between India and West Indies, a couple of years back, was the closest. If Ashwin had gone for a single off the penultimate ball and got out and the last ball result was repeated, it would have been the "ultra-perfect tie". The Adelaide Test between Australia and West Indies, which finished as a one-run win for West Indies, was equally close. Many of the one-wicket wins could have finished as ties.

This article is as much form as content. This is not the usual table-centric article. I have to present the analysis-data in different forms. As I normally do, let me say that most of the data presented here will be available through Cricinfo's stats and some further work. Only thing is you might need quite a few queries and results will not be available in this clear, concise format.

How does one analyse drawn matches. I have tried to separate the draws into the following five categories.

1. Could have ended in a result with one more ball.
2. Very close matches. Could have gone either way and/or great saves.
3. Close matches. Some slack in the matches.
4. Fair draws with some level of competition.
         (You would have to let the spectators in free)
5. Dull-dreary-dead drawn matches (DDD). 7/8 days to produce results.
         (Spectators would have to be paid to come in)

The description of these classifications is self-explanatory. The first group of draws occurs when a team has lost nine wickets in the fourth innings, the fourth innings target is six (or fewer) runs away or the team has lost nine wickets in the third innings and is still in arrears. Twenty six draws fall into this group. The second classification is a combination of miscellaneous factors: wickets, leads, RpW/BpW, resources available, et al. Too detailed to describe here. 80 Tests in this category. The third classification occurs when lot more resources are available and it is difficult to predict anything. The BpW/RpW combination also plays a part.

The fourth is the most populated one. All single-innings matches, most two-innings matches and a few three-innings matches fall under this umbrella. The last is the classification any cricket follower dreads. An example. India: 537/8. Sri Lanka: 952/7. India declared because this was a 5-day Test. Else they could have gone on. Sri Lanka could have gone past the 1000-run mark. Finally, how was the pitch? India was quite capable of scoring 500 more in the second innings. This is the perfect example of a level 5 draw. Another example: Aus-656/8. Eng-611ao. Aus-4/0. 59 Tests are in this classification. For obvious reasons, no four-innings matches will feature in this classification. We can't call a match dull and dreary if the fourth innings is in progress.

Easier said than done. How do I handle this split? It cannot be through inspection. By now I would have had to visit an asylum. So I used a judicious combination of the following five factors to separate the drawn matches. I cannot explain everything. Suffice to say that I used these factors to identify low-scoring vs high-scoring matches, dead vs live matches, unlikely wins vs probable wins et al. The key is to remember that all high scoring matches are not dull matches. I had to distinguish among a 500-500-200-190/8 match, a 500-500-300-90/1, a 500-500-200/1-150/1 match, and a 500-500-390 match.

Let me also say this. I have used a combination of the five measures, listed below, to do this classification. There is no guarantee that everything would be fine. A match or two may be out of place. For that matter what is a DDD draw might be a wonderful match for someone else because a world record was broken/attempted etc. So take these classifications with a pinch of salt. A list of all 720 drawn matches, with the classifications, can be downloaded using the link provided later in the article. I would advise readers not to split hair to the nth degree, but to examine and wonder at the wonderful world of Test draws.

- Match RpW.
- Match BpW.
- Batting resources still available, at close of play.
- How far ahead or behind the third batting team is, at close of play.
- How far away is the winning target for the fourth batting team, at close of play.

1. Overall summary of results - by Period
PeriodTestsDraws% Draws1-ball away%Very Close%Competitive%Fair Draws%Dull-Dreary-Dead%
All Tests 208572034.5% 26 3.6% 8011.1%27137.6%284 39.4% 59 8.2%
2000-2013 60515125.0% 10 6.6% 13 8.6% 5435.8% 61 40.4% 13 8.6%
1980-1999 61324740.3% 6 2.4% 2510.1% 7530.4%112 45.3% 2911.7%
1949-1979 56023241.4% 9 3.9% 3314.2%10344.4% 76 32.8% 11 4.7%
1877-1948 307 9029.3% 1 1.1% 910.0% 3943.3% 35 38.9% 6 6.7%

We have already seen in Part-1 that the 1949-79 period had the highest percentage of drawn matches, closely followed by the 1980-1999 period. In these tables I have looked at the five classifications of draws within these four periods. We get a lot of additional insights. The current period has had the maximum percentage of the first and most exciting of draws. 10 draws during the identified period would mean one every year. If we take the first two classifications together, surprisingly, it is the 1949-79 period which stands out, with 18.1%, followed by the current period, with 15.2%. It seems to be a wronged period. This is further confirmed by the low % values for 1949-79 period of the fifth classification. When we look at the numbers it is clear that the 1980-99 period is the one with fewer exciting draws and more dull draws. Maybe because there was one stand-out team and other lower level teams.

Overall summary of draws - by Team
LocationTestsDraws% Draws1-ball away%Very Close%Competitive%Fair Draws%Dull-Dreary-Dead%
Australia 75420226.8% 8 4.0% 2713.4% 7939.1% 77 38.1% 11 5.4%
Bangladesh 77 810.4% 0 0.0% 0 0.0% 562.5% 2 25.0% 112.5%
England 93333435.8% 12 3.6% 3410.2%13038.9%133 39.8% 25 7.5%
India 47220443.2% 7 3.4% 20 9.8% 7335.8% 78 38.2% 2612.7%
New Zealand 38215440.3% 3 1.9% 2314.9% 4730.5% 70 45.5% 11 7.1%
Pakistan 37315441.3% 2 1.3% 13 8.4% 6240.3% 58 37.7% 1912.3%
South Africa 37711430.2% 3 2.6% 1614.0% 4943.0% 40 35.1% 6 5.3%
Sri Lanka 222 7634.2% 1 1.3% 810.5% 2634.2% 32 42.1% 911.8%
West Indies 49016834.3% 14 8.3% 16 9.5% 6438.1% 65 38.7% 9 5.4%
Zimbabwe 89 2629.2% 2 7.7% 311.5% 726.9% 13 50.0% 1 3.8%
ICC World XI 1 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Full post
Analysing Test matches across eras - part I

A comprehensive analysis of all Tests played, looking at first-innings advantage, result likelihood during different eras, margin of victories, and the best Tests ever played

Milind and I are working on a mega-project on player contributions in Tests. Analysing Test results in depth was an essential part of that exercise where we unearthed some fascinating facts. This made me think that I could do an article analysing Test results. Initially I was apprehensive that it may not have enough material to fill my normal long article. Then things developed as I delved deeper and now I am left, as it often happens, with a two-part article. These two articles are partly anecdotal. The first one will deal with those matches that finished with a definite result. The second one will deal with draws, ties, follow-ons and the like.

This article is as much form as content. This is not the usual table-centric article. I have to present the analysis data in different forms. As I normally do, let me say that most of the data presented here will be available through Cricinfo's stats and some further work. Only thing is you might need quite a few queries and results will not be available in this clear, concise format.

First, let me talk about two special matches that ended with a definite result. Both these have been considered as wins for this exercise.

The first one was Match #1483. There was a lot of rain during the first four days at Centurion and South Africa had scored 248 for 8 in the 72 overs possible. South Africa could have batted on, and the result would have been a dull draw. However Nasser Hussain and Hansie Cronje agreed to forfeit their respective first and second innings and make a match of it. England had 90 overs to score 250 for a win. They did this in 75 overs and won the match by 2 wickets. Many players, commentators and writers have argued for and against this "arrangement". The added spice was the presence of Cronje as one of the protagonists and the subsequent match-fixing allegations. However, the presence of the impeccable English captain, Nasser Hussain, in the twosome should dispel any doubts on this match. I have only one wish. Instead of forfeiting the two innings, the two captains could have played an over each before declaration, making it a complete match. It would have avoided many programming headaches for me. More significantly, no one could have questioned the captains. Anyhow as far as I am concerned this is a match which ended in a 2-wicket win/loss.

The second is a serious "non-win" which became a win. Move the clock forward by six years, to Match #1814. England played poorly and were dismissed for 173 by Pakistan. Pakistan amassed a lead of over 300 runs and England took the field on the third day, in great distress. They reached 298 for 4, still 33 runs in arrears. Darrel Hair accused Pakistan of ball-tampering and awarded 5 penalty runs to England. Pakistan did not take the field and the match was awarded to England as a forfeited match. This was revised to a draw in 2008 and was reversed back to forfeit after another year. A sorry episode all through. Even now, I do not have any clarity in determining how to treat this match. A win no doubt, but not by an innings, not by runs, and not by wickets. For that reason I do not want to create a set of columns called "forfeited". So it remains an undefined win. It does not come under any of the three categories. It is an "un-earned" win. The two concerned teams have been allotted the result, though.

First, let me say that no team should ever forfeit a match, whatever be the provocation. But Pakistan had reason to feel aggrieved, not that it justifies Inzamam-ul-Haq's action. Let us not forget that the first forfeit almost happened 25 years earlier when Sunil Gavaskar, given out lbw, and more likely because of unnecessary and provocative on-field comments from the Australians, almost walked off the field at MCG during 1981. But for the timely action of the manager, Wg CmdrSalim Durrani, in pushing Dilip Vengsarkar onto the field and ensuring that Chetan Chauhan did not cross the line, unpleasant history would have been made then and there. We were 5 seconds away from the first forfeiture of a Test match.

A. Overall summary of results - by period
PeriodTestsFI-AvgeRunsResults%FB-Wins%SB-Wins%Draws%
All Tests 2085324.6136565.5 69033.1 67532.4 72034.5
1877 - 1948 307307.8 21770.7 12540.7 9230.0 9029.3
1949 - 1979 560320.8 32858.6 18432.9 14425.7 23241.4
1980 - 1999 613316.7 36659.7 17328.2 19331.5 24740.3
2000 - 2013 605344.6 45475.0 20834.4 24640.7 15125.0

The first table sets the tone. We start sedately with a straightforward table of results across ages and then increase our pace.

In 135 years of Test cricket, 2085 matches have been played. There have been 1365 results, which is just over 65% of the matches. That is just under 2 out of 3. For the purpose of this article the two tied matches, have been categorized as draws. Teams batting first have won 690 matches, 33.1%, and the teams batting second, 675, around 32.4%. Over the long period, teams batting first have an infinitesimal edge of less than 1%. Take a look at the average of first-innings score of teams batting first, which stands at 324.6.

I have then analysed the results in four broad periods. My usual period work is done by creating 8 periods. Here, I felt that we could consider the two modern periods, one middle period and the first one, covering just over 70 years.

During the first period, upto 1948, the result percentage was higher than 70%, partly helped by timeless Tests. The average first-innings score was lower at 307.8, but the number of matches won by teams batting first was quite high, at over 40%. teams batting second won only 30% of the matches, a clear difference of 25%. Pitches deteriorated faster during this period, owing to them being uncovered.

The period between 1949 and 1979 is perceived to be the dull period when no risks were taken and draws were the first option for some teams. This is shown by the increase of average first-innings score to 320 and the huge drop of over 10% in result matches, to around 59%. Look at the draw percentage, which is over 41%. Teams batting first won more matches comfortably.

Now we arrive at the 1980s and 90s. Despite the presence of very formidable bowling attacks, this period does not even boast a 60% result rate. Probably it was difficult to shrug off the safety-first attitude. The average first-innings score dropped. For the first time more teams won batting second: 31.5% against 28.2%. Fairly high number of draws. So, contrary to the usual perception, the 1980-1999 was not that great a Test period. It is clear that the West Indian dominance was offset by mediocrity elsewhere.

Finally we reach the current era: a truly great Test playing period, despite the proliferation of ODIs and T20 matches. A 75% results in matches is truly phenomenal. That means a 4-Test series is likely to end in a 3-0 or a 2-1 result. Look at the 7% increase in the average first-innings score; it is now around 340-350. And a very significant increase in the wins by teams batting second, despite this increase. No longer can the toss-winning captain play the percentage-game of batting first. You are more likely to lose than not.

B. A look at first-innings scores

First Inns scores>=300   Tests:1070 Wins: 435 Draws: 488 Losses: 147 Perf: 63.5%
First Inns scores>=324   Tests: 958 Wins: 412 Draws: 435 Losses: 111 Perf: 65.7%
First Inns scores>=350   Tests: 832 Wins: 364 Draws: 385 Losses:  83 Perf: 66.9%
First Inns scores>=400   Tests: 607 Wins: 285 Draws: 283 Losses:  39 Perf: 70.3%

This is a special look at first-innings scores. As can be seen, the all-time average first-innings score is 324. I did a special analysis of all matches in which this mean level was reached or exceeded. There were 958 Tests and the teams batting first won 412 of these matches. The overall performance percentage was 65.7, which denotes a fair achievement level. Then I increased the cut-off values and found out that at around 394 runs, the 70% figure is reached. This represents a very good achievement. Rounding off this to 400, we get an excellent performance value of 70.3%. My take is that any target between 350 and 400 can be taken, with the stronger teams opting for the latter figure. The current acceptable level is certainly 350+. We have decided to set the target for all first innings as 400 in our contribution work. Just to get a clear overall picture, I have done this exercise for 300 and 350 runs also. The performance percentage is 63.5% and 66.9%, respectively. As the cut-off runs are reduced, the wins decrease but the number of draws increases significantly. One other interesting fact emerged as I pushed the bar further up. The magic figure of 50% wins is reached at a cut-off score of 594. Out of the 75 instances when this total was reached, 38 ended in wins and 37 in draws.

C. A summary of innings wins

Innings wins:363   Total=34938     Avge=96.2
  Wins by inns &  1-9    runs   23   6.3
  Wins by inns & 10-49   runs  101  27.8
  Wins by inns & 50-99   runs  102  28.1
  Wins by inns & 100-199 runs   96  26.4
  Wins by inns & 200+    runs   41  11.3

This is a summary of the 363 innings wins. The average shown is an interesting number. It is the average margin of the innings victories. In other words, the sum of win-runs divided by the number of wins. Also, the additional runs scored, forms the slack. The average win has been by an innings and 96 runs, which is a big win. This is explained by the analysis below. Only 6.3% of the wins have been by an innings and upto-10 runs. These are still not close contests. It was only a matter of avoiding innings defeats. It can clearly be seen that more than 66% of the innings wins have been by wide margins. This is reflected in the overall average also. Let us not forget that the winning team also had the 10 wickets in hand, in addition to the run margins.

D. A summary of wins by runs

Runs wins: 464     Total= 73968  Avge=159.4
  Wins by  1-9    runs     9    1.9
  Wins by 10-49   runs    57   12.3
  Wins by 50-99   runs    81   17.5
  Wins by 100-199 runs   175   37.7
  Wins by 200+    runs   142   30.6

This is a summary of the 464 wins by runs. The average is calculated similar to the innings victories. There is a lot of slack in these wins also. The average win has been by 159 runs, which is a reasonably big win. This is explained by the analysis below. Only 1.9% of the wins have been by upto10 runs. However, the big difference here is that all these matches were extremely close and could easily have gone the other way. In a way, even the next category, upto-50 runs, is similar to this. These are narrow wins. Beyond this, the wins become more comfortable. Look at the high %, 30.6, of the last category, 200+ runs, all these being huge wins. It can clearly be seen that more than 68% of the innings wins have been by wide margins. This is reflected in the overall average also.

E. A summary of wins by wickets

Wicket  wins: 537  Total= 3856    Avge=  7.2
  Wins by  1 wkt(s)   12   2.2
  Wins by  2 wkt(s)   17   3.2
  Wins by  3 wkt(s)   22   4.1
  Wins by  4 wkt(s)   32   6.0
  Wins by  5 wkt(s)   48   8.9
  Wins by  6 wkt(s)   47   8.8
  Wins by  7 wkt(s)   74  13.8
  Wins by  8 wkt(s)   97  18.1
  Wins by  9 wkt(s)   80  14.9
  Wins by 10 wkt(s)  108  20.1

First, let me say that these are the only wins in which there is no slack. Always, the required number of runs, i.e. the aggregate runs of the losing team plus the run(s) needed to overtake this aggregate, are scored, since the learned duo of Duckworth-Lewis have not made their appearance into the Test arena. This analysis of wins by wickets is an eye-opener. Most of the wins, 92% to be specific, are by 4 or more wickets, which are quite comfortable wins. These teams had a lot of resources to spare. Only wins by 3/2/1 wickets can be termed as narrow and that total is below 10%. The average win margin of 7.2 wickets reflects this. Also, note the increasing trend of the numbers.

F. Team performance summary
TeamTestsWinsDrawsLossesResult %Close winsClose losses
Australia 754353204199 60.3 410
Bangladesh 77 3 8 66 9.1 0 1
England 933331334268 53.4 5 4
India 472119205149 46.9 1 0
New Zealand 382 72154156 39.0 2 0
Pakistan 373115154104 51.5 2 1
South Africa377137114126 51.5 3 2
Sri Lanka 222 66 76 80 46.8 1 1
West Indies 490160169162 49.9 3 2
Zimbabwe 89 9 26 54 24.7 0 0
ICC World XI 1 0 0 1 0.0 0 0

No surprises here. Australia leads the table with a result percentage exceeding 60, the only team to do so. This is based on 1.0 for a win and 0.5 for a draw basis. But what do we have here? Australia has played 14 close matches (listed elsewhere: sub-10 runs and 1-wkt wins). They have lost 10 of those. That means they are the team, despite the abundance of talent and determination, to lose more than 2 of 3 such matches. A true paradox. And it is also a surprise that they get into these situations far more often than others.

England follows next with 53.4%. They seem to hold their nerves, as shown by their wonderful saves during the past 4 years. Maybe there is something there for the Australians to learn. Pakistan and South Africa, with their special bowling attacks capable of winning everywhere, are next with 51.5%. They do not get into these close situations often. These are the only four teams to have a performance percentage of greater than 50. West Indies fall short of the 50% mark, by a whisker. Look at the high percentage of drawn matches for India, a throw-back to the safety-first methods between 1950 and 1995. India and Sri Lanka are almost at the same level.

G. Team performance - Home/Away/Neutral
HOMEAWAYNEUTRAL
TeamTestsWinsDrawsLossesResult %TestsWinsDrawsLossesResult %Tests WinsDrawsLossesResult %
Australia 389219 76 9566.135612712710353.5 9 7 1 183.3
Bangladesh 39 1 5 33 9.0 38 2 3 33 9.2 0 0 0 0 0.0
England 47319117310958.745514015915648.2 5 0 2 320.0
India 242 82110 5156.6229 37 94 9836.7 1 0 1 050.0
New Zealand 186 44 81 6145.4194 28 71 9532.7 2 0 2 050.0
Pakistan 144 55 68 2161.8206 51 77 7843.4 23 9 9 558.7
South Africa203 87 52 6455.7169 50 59 6047.0 5 0 3 230.0
Sri Lanka 113 47 40 2659.3105 19 34 5234.3 4 0 2 225.0
West Indies 223 80 91 5256.3264 80 7810745.1 3 0 0 3 0.0
Zimbabwe 47 7 16 2431.9 42 2 10 3016.7 0 0 0 0 0.0
ICC World XI 0 0 0 0 0.0 1 0 0 1 0.0 0 0 0 0 0.0

Australia has a rather even record everywhere, confirming that they are not just lions at home. They have a result percentage of 66% at home, 53.5% away and 83% in neutral locations: all figures the best in each classification. This makes their recent 0-4 loss an aberration. Pakistan is the only other team with a home result percentage of greater than 61. All other major teams are grouped between 55% and 60%. England is quite good, playing away, with a result percentage of just below 50. South Africa, West Indies and Pakistan follow next. Sri Lanka, India and New Zealand have only average performances away from home. Only Pakistan have played reasonable number of matches in neutral locations and have only a fair result percentage and outside UAE, they have not done well.

H. Location results summary
LocationTestsResultsDrawsResult %
Australia 389314 7680.7%
Bangladesh 47 37 1078.7%
England 47830417463.6%
India 24213311054.9%
New Zealand 186105 8156.5%
Pakistan 144 76 6852.8%
South Africa 203151 5274.4%
Sri Lanka 114 74 4064.9%
West Indies 223132 9159.2%
Zimbabwe 47 31 1666.0%
U.A.E. 12 8 466.7%

This is an analysis by match ground. UAE, a non-Test playing country, has hosted 12 matches. The key measure here is the percentage of matches which ended in a result. Australia leads this table with just over 80% results. That means that a 5-Test series in Australia is likely to end with a single draw. In addition to the type of cricket played by Australia, the pitches with true bounce which provide equal help to batsmen and bowlers alike, would be the main reason. If and when the World Test Championship (WTC) is played, it should be conducted in Australia, Indian money notwithstanding. South Africa follows suit, reasonably close behind with nearly 75% results. Fine, let us have some of the WTC matches there too. Sri Lanka and England are fairly high, at around 65%. West Indies falls just short of 60%. Surprisingly New Zealand manages to produce a result only 56% of the time. India and Pakistan do not even reach 55%, no doubt weighed down by the awful 50s/60s.

Here is a potpourri of interesting result-matches gathered using special criteria. In all these summary score lines, the winning team is shown in upper-case letters.

1. Big Innings wins
    0266 1938 By I&579 runs ENG-903/7 aus-201ao fo aus-123ao
    1590 2002 By I&360 runs AUS-652/7 saf-159ao fo saf-133ao
    0463 1959 By I&336 runs WIN-614/5 ind-124ao fo ind-154ao
    0279 1946 By I&332 runs AUS-645ao eng-141ao fo eng-172ao
    1600 2002 By I&324 runs PAK-643ao nzl- 73ao fo nzl-246ao
    1289 1995 By I&322 runs WIN-660/5 nzl-216ao fo nzl-122ao
    1630 2002 By I&310 runs bng-139ao WIN-536ao    bng- 87ao
    2033 2012 By I&301 runs NZL-495/7 zim- 51ao fo zim-143ao

The Oval disaster for Australia leads the chart. Imagine facing 903 without Don Bradman, who twisted his ankle while bowling. Zimbabwe arrived after a long delay to get slaughtered by New Zealand during 2012.

2. Big Run wins
    0176 1928 By   675 runs ENG-521ao aus-122ao    ENG-342/8 aus- 66ao
    0237 1934 By   562 runs AUS-701ao eng-321ao    AUS-327ao eng-145ao
    0114 1911 By   530 runs AUS-328ao saf-205ao    AUS-578ao saf-171ao
    1726 2004 By   491 runs AUS-381ao pak-179ao    AUS-361/5 pak- 72ao
    1905 2009 By   465 runs SLK-384ao bng-208ao    SLK-447/6 bng-158ao
    0779 1976 By   425 runs WIN-211ao eng- 71ao    WIN-411/5 eng-126ao
    0300 1948 By   409 runs AUS-350ao eng-215ao    AUS-460/7 eng-186ao
    0870 1980 By   408 runs WIN-328ao aus-203ao    WIN-448ao aus-165ao

The first match featured here was Bradman's debut Test. Maybe this Brisbane massacre, followed by him being dropped in the next Test at SCG, must have been partly responsible for Bradman's later run-hunger/thirst.

3. Close Wins - by 1 wkt
    0074 1902 By     1 wkt  aus-324ao ENG-183ao    aus-121ao ENG-263/9
    0088 1906 By     1 wkt  eng-184ao SAF- 91ao    eng-190ao SAF-287/9
    0097 1908 By     1 wkt  aus-266ao ENG-382ao    aus-397ao ENG-282/9
    0149 1923 By     1 wkt  saf-113ao ENG-183ao    saf-242ao ENG-173/9
    0345 1952 By     1 wkt  win-272ao AUS-216ao    win-203ao AUS-260/9
    0873 1980 By     1 wkt  win-140ao NZL-249ao    win-212ao NZL-104/9
    1268 1994 By     1 wkt  aus-337ao PAK-256ao    aus-232ao PAK-315/9
    1453 1999 By     1 wkt  aus-490ao WIN-329ao    aus-146ao WIN-311/9
    1497 2000 By     1 wkt  pak-269ao WIN-273ao    pak-219ao WIN-216/9
    1658 2003 By     1 wkt  bng-281ao PAK-175ao    bng-154ao PAK-262/9
    1812 2006 By     1 wkt  saf-361ao SLK-321ao    saf-311ao SLK-352/9
    1972 2010 By     1 wkt  aus-428ao IND-405ao    aus-192ao IND-216/9

I wanted this section to have no more than 10 Tests in each category but had to accept this classification featuring 12 Tests. The criterion is fixed. The amazing fact is that Australia featured in 6 of these Tests and lost 5. England featured in 3 and won all. One of Australian losses was the Laxman-heist at Mohali during 2010.

4. Close Wins - by fewer than 10 runs
    1505 2000 By     7 runs SAF-253ao slk-308ao    SAF-231ao slk-169ao
    2021 2011 By     7 runs NZL-150ao aus-136ao    NZL-226ao aus-233ao
    0009 1882 By     7 runs AUS- 63ao eng-101ao    AUS-122ao eng- 77ao
    0019 1885 By     6 runs AUS-181ao eng-133ao    AUS-165ao eng-207ao
    1243 1994 By     5 runs SAF-169ao aus-292ao    SAF-239ao aus-111ao
    0943 1982 By     3 runs ENG-284ao aus-287ao    ENG-294ao aus-288ao
    0073 1902 By     3 runs AUS-299ao eng-262ao    AUS- 86ao eng-120ao
    1758 2005 By     2 runs ENG-407ao aus-308ao    ENG-182ao aus-279ao
    1210 1993 By     1 run  WIN-252ao aus-213ao    WIN-146ao aus-184ao

These are the other close matches. Single-digit-run wins should be considered the closest of wins. Australia have featured in 8 of these 9 matches and have only a 3-5 record. They seem to lose their nerve or is there another reason?

5. Lost after scoring 500 runs in first inns
    0042 1894 By    10 runs aus-586ao ENG-325ao fo ENG-437ao aus-166ao
    1673 2003 By     4 wkts aus-556ao IND-523ao    aus-196ao IND-233/6
    1819 2006 By     6 wkts eng-551/6 AUS-513ao    eng-129ao AUS-168/4
    0635 1968 By     7 wkts win-526/7 ENG-404ao    win- 92/2 ENG-215/3
    0365 1953 By     6 wkts aus-520ao SAF-435ao    aus-209ao SAF-297/4
    0180 1929 By     5 wkts eng-519ao AUS-491ao    eng-257ao AUS-287/5

Scoring 500 and losing the match. Very painful. Australia again. They have featured in 5 matches and have only a 2-3 record. One was after making England follow-on and the other was the famous Indian win at Adelaide during 2003. The English win over West Indies was because of the declaration by Garry Sobers, often widely perceived as silly.

6. Lost losing fewer than 15 wkts
    1483 2000 By 2 wkts saf-248/8                      ENG-251/8  8 wkts lost
    0635 1968 By 7 wkts win-526/7 ENG-404ao  win- 92/2 ENG-215/3  9 wkts lost
    1814 2006 Forfeited ENG-173ao pak-504ao  ENG-298/4           10 wkts lost
    0313 1949 By 3 wkts saf-379ao ENG-395ao  saf-187/3 ENG-174/7 13 wkts lost
    1556 2001 By 6 wkts aus-447ao ENG-309ao  aus-176/4 ENG-315/4 14 wkts lost

The first is the match we have discussed earlier. Had to be present here for completion of presentation. The West Indies - England match has also been referred to briefly earlier. West Indies made two declarations, at 7 and 2 wickets, and lost the match. Quixotic, to say the least. The third match also has been discussed extensively earlier. I cannot get a handle on the fourth match. The South African bowling was very ordinary: no bowler even reaching a career aggregate of 60 wickets. Yet they declared leaving England, with Len Hutton, Cyril Washbrook, and Denis Compton, to get a sub-180 target. A strange decision by Dudley Nourse, indeed. But in his favour, it must be said that there was only 96 minutes of play possible. The amazing fact is that South Africa bowled 24 8-ball overs (32 6-ball overs) and captured 7 wickets. So let me equivocate - it is not so strange a decision as I had mentioned earlier. The fourth is the famous dead-rubber loss by Australia, orchestrated by Mark Butcher.

7. Won after scoring 100 runs in first inns
    0025 1887 By    13 runs ENG- 45ao aus-119ao    ENG-184ao aus- 97ao
    0009 1882 By     7 runs AUS- 63ao eng-101ao    AUS-122ao eng- 77ao
    0043 1895 By    94 runs ENG- 75ao aus-123ao    ENG-475ao aus-333ao
    0094 1907 By    53 runs ENG- 76ao saf-110ao    ENG-162ao saf- 75ao
    0059 1899 By   210 runs ENG- 92ao saf-177ao    ENG-330ao saf- 35ao
    2034 2012 By    71 runs PAK- 99ao eng-141ao    PAK-365ao eng-252ao

All but one of these matches were before 1908. Uncovered and deteriorating pitches meant that any runs on board were very valuable. The last match is of current vintage. England's loss was because of their first-innings failure to build a substantial lead after dismissing Pakistan for 99. Then Saeed Ajmal took over. The red herring which made everyone think that they were candidates for a 4-0 drubbing later in the year in India.

8. Won in least overs
    0047 1896 By   288 runs ENG-185ao saf- 93ao    ENG-226ao saf- 30ao (41.2 ov)
    0032 1889 By I&202 runs ENG-292ao saf- 47ao fo saf- 43ao           (50.3 ov)
    0082 1904 By   218 runs AUS-247ao eng- 61ao    AUS-133ao eng-101ao (54.1 ov)
    0216 1932 By I& 72 runs saf- 36ao AUS-153ao    saf- 45ao           (54.3 ov)
    0030 1888 By I& 21 runs ENG-172ao aus- 81ao fo aus- 70ao           (55.5 ov)
    1617 2002 By I&198 runs pak- 59ao AUS-310ao    pak- 53ao           (56.4 ov)
    0353 1952 By I&207 runs ENG-347/9 ind- 58ao fo ind- 82ao           (58.1 ov)

One match finished in fewer than 250 balls. That is a strike rate of a wicket every 12 balls. The umpires must have had sore shoulders. The most recent instance was Pakistan's Sharjah collapse in less than 60 overs for two sub-60 totals.

9. Won losing fewer than 3 wickets
    0154 1924 By I& 18 runs saf-273ao ENG-531/2    saf-240ao   2 wkts lost
    0456 1958 By I& 71 runs nzl- 67ao ENG-267/2    nzl-129ao   2 wkts lost
    0741 1974 By I& 78 runs ind-165ao ENG-459/2    ind-216ao   2 wkts lost
    1640 2003 By I& 60 runs bng-173ao SAF-470/2    bng-237ao   2 wkts lost
    2049 2012 By I& 12 runs eng-385ao SAF-637/2    eng-240ao   2 wkts lost

These are all matches with winning teams declaring 2 wickets down. For the first innings, there are a few matches won losing 3 wickets. The last match is fascinating. The same bowlers who orchestrated 4-0 and 2-1(away) wins against a strong Indian batting line-up managed to capture 2 wickets in 189 overs, in the interim period.

10. Won scoring fewer than 200 runs in match
    0009 1882 By     7 runs AUS- 63ao eng-101ao    AUS-122ao eng- 77ao
    0028 1888 By    61 runs AUS-116ao eng- 53ao    AUS- 60ao eng- 62ao
    0030 1888 By I& 21 runs ENG-172ao aus- 81ao fo aus- 70ao
    0034 1890 By     2 wkts aus- 92ao ENG-100ao    aus-102ao ENG- 95/8
    0128 1912 By    10 wkts saf- 95ao ENG-176ao    saf- 93ao ENG- 14/0
    0216 1932 By I& 72 runs saf- 36ao AUS-153ao    saf- 45ao
    0238 1935 By     4 wkts win-102ao ENG- 81/7    win- 51/6 ENG- 75/6
    0275 1946 By I&103 runs nzl- 42ao AUS-199/8    nzl- 54ao

This is a fascinating collection, mostly filled with pre-WW1 matches. Imagine, the winning team did not even need 200 runs in the two innings combined, to win, thrice with an innings to spare. I am fascinated by the 1888 match when Australia followed on, merely 91 runs behind. Australia's convenient declaration at 199/8 during 1946 got them in.

11. Won trailing by more than 250 runs
    1814 2006 Forfeited   ENG-173ao pak-504ao    ENG-298/4           Deficit 331
    1194 1992 By  16 runs AUS-256ao slk-547/8    AUS-471ao slk-164ao Deficit 291
    1535 2001 By 171 runs aus-445ao IND-171ao fo IND-657/7 aus-212ao Deficit 274
    0042 1894 By  10 runs aus-586ao ENG-325ao fo ENG-437ao aus-166ao Deficit 261
    0320 1950 By   5 wkts saf-311ao AUS- 75ao    saf- 99ao AUS-336/5 Deficit 236
    0905 1981 By  18 runs aus-401/9 ENG-174ao fo ENG-356ao aus-111ao Deficit 227
    1945 2010 By  36 runs AUS-127ao pak-333ao    AUS-381ao pak-139ao Deficit 206

In these matches the winning team trailed by more than 250 runs in the first innings. Three of these matches were won after following on. The fourth is the famous Botham-Willis match. The sixth is the equally famous Laxman-Harbhajan match. The last of these matches happened three years back at SCG. Possibly Michael Hussey's best ever Test innings gave Australian bowlers 175 runs to defend against Pakistan which they did in style. Nathan Hauritz's moment of glory.

12. 1/2 wkt wins with 50+ runs partnership for 8th/9th wicket   9w  10w   
   0096 1907 By  2 wkts eng-273ao AUS-300ao  eng-300ao AUS-275/8   56
   1012 1985 By  2 wkts pak-274ao NZL-220ao  pak-223ao NZL-278/8   50
   1097 1988 By  2 wkts pak-309ao WIN-306ao  pak-262ao WIN-268/8   61
   1268 1994 By  1 wkts aus-337ao PAK-256ao  aus-232ao PAK-315/9   22   57
   1453 1999 By  1 wkts aus-490ao WIN-329ao  aus-146ao WIN-311/9   54    9
   1658 2003 By  1 wkts bng-281ao PAK-175ao  bng-154ao PAK-262/9   52    9
   1972 2010 By  1 wkts aus-428ao IND-405ao  aus-192ao IND-216/9   81   11

These are fascinating matches in which the chasing teams achieved narrow wins by 1 or 2 wickets. However, these wins were unlikely ones in that there was a 50-plus run partnership for either the 9th or the last wicket. Each is a classic. Possibly the most exciting win was Pakistan's win over Australia, which is the only instance of an unbroken last wicket partnership of over 50 runs. The other classics are all here: the Brian Lara masterpiece at Bridgetown, Laxman special at Mohali and the Inzamam-inspired win against Bangladesh.

Which was the greatest of wins? The 1-run or 1-wkt wins are very close and might have provided great drama but the cause might not have been hopeless. But for sheer drama, courage and coming from behind, I have to narrow this search to the three wins after following on. Of these three, the one most talked about is the Calcutta win engineered by Laxman-Harbhajan-Dravid. But this match does not strike the right chords for me. India, at 232 for 4, were still 42 runs in arrears, but not a desperate situation. And Sourav Ganguly's decision to bat on the fifth day gave me the impression that he was not looking for a win. The win happened happenstance, that too by a wide margin. Now let us examine the other two matches. In the 1894 match, England had taken the lead with 6 wickets in hand. At SCG on the fifth day, any total above 150 was defendable, with an excellent bowling attack of Tom Richardson, Johnny Briggs, Bobby Peel and Bill Lockwood. However there is no arguing that this was a very close match.

The most exciting Test ever. The choice is individual: one could pick between the "The Ashes" Test, the first tie, the West Indian win by a single run against Australia, or those heart-stopping wins at Bridgetown, Karachi, Multan and Mohali. No one would go wrong. Result in doubt until the last ball, great individual performances and both teams "winning": what more can be asked for?

What about the 1981 Headingley classic? When Graham Dilley walked in, England were 135 for 7, still 92 in arrears. When Dilley was out, England were only 25 ahead. When Chris Old got out, England were only 92 ahead. Finally when Bob Willis was dismissed, the target for Australia was only 129. It needed one of the greatest fast bowling performances ever to give England the unlikeliest of wins. All things considered, I have no hesitation in nominating this Botham-Willis effort as the greatest of all wins. It is possible that non-match factors such as series status, opponent's fearsome reputation, own team's poor showing etc. might tilt the scale in favour of the 2001 win. But the 1981 match cannot be touched if we look at only the match.

As I have already explained this part itself has gone quite long. In the second part, I will examine the fascinating area of Test cricket, in the form of draws (in different hues), follow-ons, tied matches et al. I trust that at the end of this pair of articles you would have known whatever there is needed to know about Test results.

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The ODI batting giants: part 2

An analysis of 15 of the best ODI batsmen across certain special performance measures

This is part two of the article on ODI Batting giants. The first part covered the standard measures. In this article I will be looking at certain special performance measures. Despite the requests by several readers, I have retained the same fifteen batsmen, in order to be consistent. However I am open to select a subset of these two articles, say 8-9 tables, and do the analysis for all ODI batsmen. This will depend on the readers' comments.

Though I could not satisfy all requests, a couple of tables were added to the few planned based on the the comments received. Since I already had seven tables planned I could not take in all requests. Also, where there were two suggestions on a single measure, say the Index, I have opted for the simpler one.

1. Impact Innings / High Scoring Index / MOM
InningsImpactInns% ImpactInnsInns-TopScored% TopScoresInns-Second TSTS PointsTS IndexMOMsMOM Frequency
Richards 167 5130.5% 5432.3% 25116.80.70 31 5.39
J Miandad 218 5022.9% 5525.2% 39122.20.56 1911.47
Crowe 141 3222.7% 4531.9% 17 85.50.61 18 7.83
M Waugh 236 4117.4% 5021.2% 40112.30.48 2210.73
Tendulkar 45210122.3%12928.5% 68282.30.62 60 7.53
Jayasuriya 433 6314.5% 8419.4% 55189.10.44 46 9.41
Lara 289 5820.1% 7024.2% 51157.40.54 30 9.63
Inzamam 350 7020.0% 6017.1% 79157.90.45 2315.22
Flower 208 4019.2% 5124.5% 37109.80.53 1020.80
Bevan 196 4321.9% 4623.5% 30 90.00.46 1216.33
Ponting 365 4913.4% 6417.5% 73152.70.42 3211.41
Kallis 307 5818.9% 7825.4% 47160.10.52 32 9.59
Gilchrist 279 5118.3% 5419.4% 35114.90.41 28 9.96
Pietersen 121 2621.5% 3226.4% 12 57.80.48 1012.10
Dhoni 196 4422.4% 3115.8% 35 74.30.38 1810.89

I am sure readers could justifiably comment that a 110 had no impact on the match while a 21 at No.7 had greater impact. I concede that. A context-driven innings ratings work, on the anvil, would bring out all such nuances. However here we are looking at players' careers at a macro level. Hence I have developed logical, easy-to-understand definitions to determine impact innings by the batsmen. The rules are given below. The idea is that it is easier for the top-order batsmen to score more runs, score a higher percentage of team runs but will score at lower rates, more often than not. The late-order batsmen are unlikely to accumulate runs and score higher percentage of team runs but are likely to score at a much faster rate. It is certain that some tweaks of the following numbers could be suggested. However these are based on common sense and are applied across all batsmen. My advice to readers is not to split hairs on these numbers and concentrate on the broad picture.

Definition of Impact innings

BatPos 1-3:
Runs scored 100 or more OR
Runs scored 50 or more and % of Team Runs 33% or more OR
Runs scored 50 or more and Relative Scoring Rate 125 or more.
BatPos 4-6:
Runs scored 75 or more OR
Runs scored 40 or more and % of Team Runs 25% or more OR
Runs scored 40 or more and Relative Scoring Rate 137.5 or more.
BatPos 7-11:
Runs scored 50 or more OR
Runs scored 25 or more and % of Team Runs 20% or more OR
Runs scored 25 or more and Relative Scoring Rate 150 or more.
Relative scoring rate = Individual SR / Team SR.

Richards leads the table with an impressive tally of 30.5% in the impact innings measure. That is just under one-in-three. He is way ahead of the next best, in this case, Miandad with 22.9% and Martin Crowe, with 22.7%. All three played their cricket before the 1990s. Dhoni and Tendulkar follow next. Jayasuriya's uncertain career moves are reflected in his 14.1% value. And I am sure most of these would have been in the second third of his career.

For the Innings Top score analysis I have adopted an intriguing method. For this I only consider the innings in which the batsman either top-scored or was the second-best score. Let us define these as PR, HS1 and HS2, where PR is the player runs and the other two represent the top two scores. It is easier to represent this in a formulaic fashion. If PR equal to HS1, then add PR/HS2 (will be above 1.00) to the TS points value, otherwise, add PR/HS1 (will be below 1.00). Finally divide this by the total number of innings played to arrive at the TS-Index. Higher TS-Index values indicate higher players performances at around the top of team scores.

First the % of innings the batsman top-scored. Richards (how often do we see him at the top in these performance based measures) with 32.3% of his innings being top scores. Martin Crowe follows close with 31.9% and then there is some daylight and Tendulkar at 28.5%. As expected, Dhoni, batting at the late order positions, has top scored only 15.8%. Richards is also in the top position of the TS-Index table, with a value 0.70. Tendulkar is next with 0.62 and Martin Crowe follows with 0.61. The way this index value is structured, it is not easy to even finish with 0.50.

Now comes the often subjective but important measure of MOM awards received. For sheer number of awards, Tendulkar, having played over 450 innings, leads with 60 awards. However the performance measure for this is the MOM-frequency which is Innings per MOM award. Who leads? Who leads? None other than Richards, with a very low figure of 5.39 inns per MOM. The next best is Tendulkar, requiring 7.5 innings per MOM and then, Martin Crowe, with a MOM every 7.83 innings. Incidentally Amla's TS-Index is 0.77 and he wins a MOM every 6.5 innings.

These are all performance-based analyses and it is amazing that Richards leads in each and every one of these.

2. World Cup SF-F Champions Trophy Finals / Significant / Early matches
WC - F&SF, CT - FSignificant matchesEarly matches
BatsmanInnsRunsBallsRpIS/RInnsRunsBallsRpIS/RInnsRunsBallsRpIS/R
Richards 6 303 40050.50 75.8 0 0 0 0.00 0.0 15 710 80447.33 88.3
J Miandad 4 185 27146.25 68.3 3 68 12822.67 53.1 23 830 116936.09 71.0
Crowe 1 91 8391.00109.6 1 43 6243.00 69.4 19 746 90939.26 82.1
M Waugh 4 49 7312.25 67.1 6 383 44363.83 86.5 14 653 78546.64 83.2
Tendulkar 7 331 42847.29 77.3 22 800 98036.36 81.6 29 1588 171454.76 92.6
Jayasuriya 7 165 19723.57 83.8 23 874 94138.00 92.9 27 662 79624.52 83.2
Lara 4 72 10018.00 72.0 16 592 69237.00 85.5 30 1026 123934.20 82.8
Inzamam 3 117 10639.00110.4 13 191 34814.69 54.9 20 472 64023.60 73.8
Flower 0 0 0 0.00 0.0 10 354 50935.40 69.5 23 726 99331.57 73.1
Bevan 4 170 26142.50 65.1 10 300 44330.00 67.7 8 150 25718.75 58.4
Ponting 10 308 36530.80 84.4 26 1341 164451.58 81.6 24 687 94628.62 72.6
Kallis 3 95 15231.67 62.5 23 1000 130243.48 76.8 23 706 93230.70 75.8
Gilchrist 7 305 26143.57116.9 22 674 69230.64 97.4 15 488 56132.53 87.0
Pietersen 0 0 0 0.00 0.0 7 383 47254.71 81.1 9 310 34334.44 90.4
Dhoni 2 116 12158.00 95.9 4 10 21 2.50 47.6 9 233 30125.89 77.4

This is a very important table to measure how the batsmen contributed in important tournaments. I have been quite tough in fixing the qualification criteria. I have only considered the 10 Word Cups and 6 Champions Trophy tournaments. There may be other 6/7-team tournaments. But only true World level tournaments make the cut.

I have looked at the performances in three categories. The first consists of the really important tournament-winning matches: World Cup Finals, Semi-Finals and Champions Trophy Finals. The second category consists of the significant later stage matches: Super-Six matches, Quarter-Finals and Champions Trophy Semi-Finals. The third category consists of all other matches in these tournaments.

In the first category, Tendulkar, Ponting, Gilchrist and Richards have exceeded 300 runs. This is reflected in their teams' successes. The average does not mean much. Hence only RpI is shown. More important than that is the total number of runs scored. Look at Gilchrist's strike rate in these matches, exceeding 115. Tendulkar has scored 331 runs, at a much lower strike rate.

Ponting leads in the significant matches category, with over 1300 runs. Kallis comes in next with exactly 1000 runs, outlining his importance to South Africa in these key matches. There is nothing for Richards since these matches were non-existent during the first 3/4 World Cups. Tendulkar is the run-away leader in the third category, with nearly 1600 runs, at an excellent strike rate. Lara follows next with just over 1000 runs and Miandad has also done well considering that he played only in World Cups.

It should be noted that all these three classifications are mutually exclusive. Tendulkar has scored a staggering 2700+ runs in these important world level tournaments. He missed the first four editions of the World Cup.

3. Career Summary (Revised Index) incorporating Batting position analysis
BatsmanInnsNOsRunsBallsAvgeS/RRpIIndexBatPosAvgeBest BPBBP InnsBBP RunsBBP RpI
Richards 16724 6721 745147.000.9020.1928.163.964 81 337341.64
J Miandad 21841 73811101441.700.6700.1704.754.074160 567835.49
Crowe 14119 4704 647638.560.7260.1734.853.214 53 189935.83
M Waugh 23620 85001105339.350.7690.1614.872.271141 572940.63
Tendulkar 45241184262136744.830.8620.1806.951.8313401531045.03
Jayasuriya 43318134301472332.360.9120.1434.211.5313831274033.26
Lara 28932104061308640.490.7950.1715.523.303106 444741.95
Inzamam 35053117391581239.530.7420.1524.464.174147 517535.20
Flower 20816 6785 909735.340.7460.1564.123.554 82 286834.98
Bevan 19667 6914 932053.600.7420.1505.975.326 87 300634.55
Ponting 36539137031704642.030.8040.1575.303.1033301266138.37
Kallis 30753114991575645.270.7300.1655.443.423196 776039.59
Gilchrist 27911 9619 992235.890.9690.1465.091.391259 920035.52
Pietersen 12116 4369 503641.610.8680.1575.673.764 67 235235.10
Dhoni 19656 7259 822851.850.8820.1506.875.456 82 251230.63

This is a revision of the ODI Batting Index. I have adopted Deepak's suggestion and got a revised Index value. His suggestion that the Index could be "Average x Strike Rate x Share of team runs" has a lot going for it. The top order batsmen who could lose on average because of decreased number of not-outs are likely to score a higher % of team runs. The compensation may not be complete but at least there would be a partial compensation. The "share of team runs" is also a dimension-less value. Richards scored 19.2% of his team runs, Tendulkar, 18% and Jayasuriya, 14.3%. The average seems to be around 16%. It should be understood that this analysis is valid only across the entire career since only then does the % of team runs have meaning.

What do we have here? This clearly shows how far ahead Viv Richards is. His revised Index value is 8.16 and is nearly 15% ahead of Tendulkar, the second-best. Dhoni is next, a very high average of 51 contributing to this position. Quite a number of batsmen are in the sub-5 level indicating how tough it is to get a high value in this revised index. Just out of interest, Amla (57.81/0.922/0.21) hits the ceiling with a stupendous Index value of 11.2. de Villiers has an imposing 7.8 and Kohli, an equally good 7.4.

The average batting position is self-explanatory. The only additional information needed is that both openers are assigned 1 as the batting position. Thus the batsmen who spent the better part of their careers opening the batting, such as Gilchrist, Jayasuriya and Tendulkar have Avge Batpos values below 2.0. The lower the value, the more often the batsman has opened. The best batting position numbers are based on runs scored. There could be other positions in which the batsmen could have averaged more. There is no surprise. Tendulkar, Jayasuriya, Mark Waugh and Gilchrist have excelled in the opening positions. Dhoni and Bevan in position number 6. And the others in the middle-order positions (3/4/5).

4. Middle-order runs (3 and 4)
Batsman3/4 Inns3/4 NOs3/4 Runs3/4 Balls3/4 Avge3/4 S/R3/4 RpI3/4 Index
Richards 13221 5791 648452.17 89.343.939.2
J Miandad 17835 6409 957244.82 67.036.024.1
Crowe 11115 3671 499538.24 73.533.124.3
M Waugh 54 4 1786 240035.72 74.433.124.6
Tendulkar 71 9 2151 285634.69 75.330.322.8
Jayasuriya 12 1 252 32622.91 77.321.016.2
Lara 19018 6963 852040.48 81.736.630.0
Inzamam 20828 7208 979240.04 73.634.725.5
Flower 108 7 3775 483237.38 78.135.027.3
Bevan 5616 2359 338958.98 69.642.129.3
Ponting 34734133071655342.51 80.438.330.8
Kallis 27047104141417646.70 73.538.628.3
Gilchrist 1 0 29 4429.00 65.929.019.1
Pietersen 96 8 3131 373635.58 83.832.627.3
Dhoni 34 9 1903 187676.12101.456.056.8

This is again based on a request from a few readers. They asked me to do a table for runs made in positions 3 and 4 also. This would round up the batting analysis since I have already covered opening, 5 and 6 positions. It is obvious that 3 and 4 are the key positions usually occupied by the best batsmen: Richards, Tendulkar, Ponting, Lara et al. I decided to combine the 3 & 4 into a single analysis.

Look at Richards. An average of 52 when he bats in these pivotal positions, at a strike rate of 89 leads to an Index value of 39. He is far ahead, to the tune of 30%, of the next best significant players, Ponting and Lara, clocking in at just above 30. Ponting, however, has scored millions of runs at these key positions. Dhoni's numbers are high, but too few innings have been played.

5. Team share of runs/balls
BatsmanRunsTeamRuns% RunsBallsTeamBalls% BallsRatio
Richards 6721 3491619.2% 7451 4633816.1%124.4%
J Miandad 7381 4338417.0%11014 5917718.6% 89.6%
Crowe 4704 2713717.3% 6476 3804517.0%102.2%
M Waugh 8500 5285716.1%11053 6575516.8% 94.8%
Tendulkar 1842610247218.0%2136712197217.5%103.2%
Jayasuriya 13430 9410914.3%1472311556512.7%114.0%
Lara 10406 6067717.1%13086 7744316.9%101.8%
Inzamam 11739 7720115.2%15812 9709716.3% 92.2%
Flower 6785 4345515.6% 9097 5805015.7% 99.6%
Bevan 6914 4606115.0% 9320 5545916.8% 87.4%
Ponting 13703 8736115.7%17046 9954317.1% 90.0%
Kallis 11499 6989916.5%15756 8342218.9% 84.6%
Gilchrist 9619 6573314.6% 9922 7426413.4%111.2%
Pietersen 4369 2781815.7% 5036 3281915.3%102.8%
Dhoni 7259 4830815.0% 8228 5377615.3% 97.9%

This is a straight-forward % of player numbers out of total team numbers. More important than the numbers are the ratios between the two numbers. This gives a clear idea of the % of out-performance for each player. Richards out-performed his team mates by 24%. Jayasuriya, by 14% and Gilchrist, by 11%. Kallis and Bevan are at the other end of the table. It should be noted that for want of complete data on when the batsman was dismissed, this analysis is based on the total team score. Hence please apply some caveats when using this.

6. First & Second Innings
First InningsSecond Innings
BatsmanInnsRunsBallsRpIS/RInnsRunsBallsRpIS/RRpI % First-to-Second
Richards 80 3711 389346.39 95.3 87 3010 355934.60 84.6134.1
J Miandad 127 4340 646134.17 67.2 91 3041 455233.42 66.8102.3
Crowe 75 2422 334532.29 72.4 66 2282 313034.58 72.9 93.4
M Waugh 130 5181 657339.85 78.8106 3319 448131.31 74.1127.3
Tendulkar 220 97061150744.12 84.3232 8720 986137.59 88.4117.4
Jayasuriya 223 7688 856834.48 89.7210 5742 615627.34 93.3126.1
Lara 132 4981 613237.73 81.2157 5425 695334.55 78.0109.2
Inzamam 199 6943 923134.89 75.2151 4796 658231.76 72.9109.8
Flower 110 3825 502734.77 76.1 98 2960 407130.20 72.7115.1
Bevan 115 4032 504735.06 79.9 81 2882 427235.58 67.5 98.5
Ponting 212 86291040740.70 82.9153 5074 664033.16 76.4122.7
Kallis 152 5981 809439.35 73.9155 5518 766235.60 72.0110.5
Gilchrist 149 4830 517232.42 93.4130 4789 475136.84100.8 88.0
Pietersen 60 2370 274039.50 86.5 61 1999 229532.77 87.1120.5
Dhoni 101 4104 438440.63 93.6 95 3155 384433.21 82.1122.4

This analysis looks at the performances of batsmen while batting first or second. Nothing is gained by looking across batsmen. It is necessary to look within batsman. Richards, Mark Waugh, Jayasuriya, Ponting et al have performed better setting up the target than while chasing. Gilchrist, Martin Crowe, Bevan, Miandad et al have done better while chasing. I leave it to the readers to draw their own conclusions. Richards has the biggest positive difference and Gilchrist, the highest negative difference.

7. Home / Neutral / Away analysis
Home matchesNeutral locationsAway matches
BatsmanInnsRunsBallsRpIS/RInnsRunsBallsRpIS/RInnsRunsBallsRpIS/R
Richards 26 805 89230.96 90.2 59 1995 234133.81 85.2 82 3921 425347.82 92.2
J Miandad 60 1976 260532.93 75.9 82 2832 427734.54 66.2 76 2573 413133.86 62.3
Crowe 56 1884 261733.64 72.0 32 1179 162636.84 72.5 53 1641 223130.96 73.6
M Waugh 113 3827 510033.87 75.0 43 1614 205937.53 78.4 80 3059 389838.24 78.5
Tendulkar 160 6976 789543.60 88.4146 6385 727843.73 87.7146 5065 619534.69 81.8
Jayasuriya 124 3880 435731.29 89.1162 5463 594433.72 91.9147 4087 442227.80 92.4
Lara 85 3225 409037.94 78.9111 3969 483035.76 82.2 93 3212 416734.54 77.1
Inzamam 64 2674 330641.78 80.9159 5133 695532.28 73.8127 3932 555130.96 70.8
Flower 57 1887 245733.11 76.8 76 2544 349133.47 72.9 75 2354 314831.39 74.8
Bevan 80 2849 395835.61 72.0 45 1577 212635.04 74.2 71 2488 323135.04 77.0
Ponting 150 5406 681436.04 79.3 86 3208 405137.30 79.2129 5089 618639.45 82.3
Kallis 131 5102 679438.95 75.1 75 2689 383635.85 70.1101 3708 512636.71 72.3
Gilchrist 110 3960 401036.00 98.8 62 2017 213432.53 94.5107 3642 377934.04 96.4
Pietersen 41 1130 131927.56 85.7 17 816 99648.00 81.9 63 2423 272038.46 89.1
Dhoni 75 3010 330240.13 91.2 38 1232 136132.42 90.5 83 3017 356536.35 84.6

This is a location-based analysis. The matches are split into Home, Away and Neutral locations since many matches are played in neutral locations and many World Cups have two outside teams playing. It is interesting to note that most batsmen play more outside their home location. Tendulkar was the best performer at home, closely followed by Inzamam and Dhoni. Pietersen, albeit in very few innings, was masterful in neutral locations, followed by Tendulkar, in nearly 150 innings. Richards was the king in outside locations. Ponting was also quite good. Look at the magnificent strike rates of Gilchrist everywhere, Jayasuriya on neutral and away grounds and Richards in outside locations.

8. Won / Lost matches
Won matchesLost matches
BatsmanInnsRunsBallsRpIS/RInnsRunsBallsRpIS/RRpI % Won-to-Lost
Richards 114 5129 563044.99 91.1 51 1501 183929.43 81.6152.9
J Miandad 107 3931 539836.74 72.8104 3389 536932.59 63.1112.7
Crowe 60 2694 341544.90 78.9 78 1938 298724.85 64.9180.7
M Waugh 146 6054 768341.47 78.8 85 2335 321927.47 72.5150.9
Tendulkar 231111571235848.30 90.3200 6585 824332.92 79.9146.7
Jayasuriya 228 8873 918938.92 96.6192 4044 496921.06 81.4184.8
Lara 134 6554 756548.91 86.6144 3557 502024.70 70.9198.0
Inzamam 191 7434 942738.92 78.9146 4118 605428.21 68.0138.0
Flower 57 2402 311642.14 77.1144 4252 582129.53 73.0142.7
Bevan 122 4504 595336.92 75.7 70 2276 316432.51 71.9113.5
Ponting 254107251300742.22 82.5 96 2658 360227.69 73.8152.5
Kallis 194 80121058241.30 75.7100 3162 463831.62 68.2130.6
Gilchrist 196 7657 770939.07 99.3 72 1767 195524.54 90.4159.2
Pietersen 51 1878 214636.82 87.5 64 2281 268335.64 85.0103.3
Dhoni 107 4578 469842.79 97.4 82 2333 315428.45 74.0150.4

Wins are achieved by teams. However this analysis completes the huge exercise. It is certain that the winning RpI values for all these batsmen would be much higher than the RpI in losing matches. The difference ranges from very little for Pietersen (3% difference) to very high for Lara (98% difference).

I have created 16 tables for these selected 15 batsmen. Many readers have suggested that other batsmen should have been considered. Ganguly has had quite a few votes. Hence I will select 8-9 tables out of these, based on readers' responses. I will then do the analysis across all batsmen, subject to a minimum number of innings or runs, and come out with an ordered set of tables. This will ensure that there is fair representation across all players and it would be a performance-centric article.

Any doubts in deciding on the best ODI batsman have been clearly dispelled. The leading position of Viv Richards in many of these tables indicates that he is, unarguably, the best ODI batsmen of all time. This is supported by the fact that there is considerable gap between Richards and the next batsman in many measures. All this was done when the rest of the world scored at around 70 and the target for most teams was 250. He also did not have any powerplays assisting him. Not just the "Master Blaster" but the "Master".

Any number of IPL matches, with coloured clothing, Bollywood stars, million-dollar players, imported cheerleaders and umpteen numbers of sixes cannot match those last 15 minutes at Eden Park, Auckland. Those dot balls were far more important than many a six hit. Who cares if Prior does not have an IPL contract? He can hold his head high. Panesar faces 5 balls, probably more important than many a wicket he has captured. Test Cricket lives, and how! And from next week onwards, the sublime to the big-brash-bash.

And my fervent prayers go to Jesse Ryder to get well soon. A great character with undeniable talent, with a special fascination for the Indian attack: all three of his hundreds were scored off the Indian bowlers.

Full post
The ODI batting giants: part 1

A statistical look at 15 of the best ODI batsmen across various eras, analysing how they measured up in several different parameters

At the outset let me apologise to all the readers for my inability to read and respond to the comments sent for my previous article. Even though the reasons were beyond my control, it is my corner of "the Cordon" and it was my responsibility to keep this small area working, accessible and free of trash. My thanks to Cricinfo technical team for addressing this sticky problem and I will have access to the comments for my articles, which will henceforth be published, interjected with my responses.

The year 2012 witnessed retirement of the two giants of ODI format. Two pillars of the game, neither of whom could ever be denied a place among the top four of the ODI game. They scored tons of runs and scored these in a magnificent manner, scored these when their team needed them and pulverised top-quality attacks. Sachin Tendulkar and Ricky Ponting played like kings and retired in style. Towards the end of the year another player retired from Test cricket, in the opinion of many, when he was still at the top. Unfortunately this also meant an exclusion from a farewell ODI series. However, this cannot deny the stellar contributions Michael Hussey made towards his team's successes. The retirement of these three giants has prompted me to do a very exhaustive analysis of the ODI batting giants. This is a two-part article due to the number of areas covered. At the end of this article I have outlined the second article so that reader requests can be incorporated wherever possible.

How many batsmen do I include in this analysis and how do I decide on the specific batsmen? A very difficult task indeed. I have used a combination of numbers, the team achievements, their contributions to the ODI format in general and their team in particular. I have tried to ensure as wide a representation across countries and as broad-based representation across the years as possible. Over the past 40 odd years, 10 World Cups and 6 Champions Trophy tournaments have been held. Australia has won 6, West Indies 3, India 2.5, Sri Lanka 1.5 and Pakistan, South Africa and New Zealand, one each. The selection of players reflects, to some extent, this level of success of their teams.

Taking all above into consideration, I have selected following 15 batsmen, listed in chronological order. There may be minor disagreements among readers but there is no denying that these 15 represent the very cream of ODI batting. They have contributed over 130,000 runs, just short of 10% of the total runs scored in ODI matches. Most of these batsmen select themselves.

Richards      1975 1991
Miandad       1975 1996
M Crowe       1982 1995
M Waugh       1988 2002
Tendulkar     1989 2012
Jayasuriya    1989 2011
Lara          1990 2007
Inzamam       1991 2007
A Flower      1992 2003
Bevan         1994 2004
Ponting       1995 2012
Kallis        1996 2012 Active
Gilchrist     1996 2008
Pietersen     2004 2013 Active
Dhoni         2004 2013 Active

I included Hussey in the beginning but towards the end felt that Mark Waugh could not be ignored. Since both are among my favourite batsmen, it was a wrench to exclude either of them. Martin Crowe played in tough times and just about edged out Fleming. Jayasuriya transformed the game itself. Miandad and Inzamam selected themselves. So did Richards and Lara. The Tendulkar lily need not be gilded. Dhoni's finishing exploits are legendary giving him the edge ahead of Ganguly. Pietersen and Andy Flower are, by far, their respective country's best batsmen.

My sincere apologies to Lloyd, Gayle, Haynes, Dean Jones, Hussey, Saeed Anwar, Mohammad Yousuf, de Silva, Sangakkara, Jayawardene, Ganguly, Azharuddin, Sehwag, Graeme Smith, Gibbs, Fleming et al, and their supporters. Any of them would have graced this list with distinction. Shakib Al Hasan will certainly qualify into an allrounder's list but has not done enough in batting.

In view of the number of tables and the huge amount of information, I have decided to do this mammoth analysis in two parts. The first part is based on available data and I would venture to say that most of this data could be extracted using statsguru. However, here it is available in a single place in easily understandable tables for the crème de la crème of ODI batsmen. The second part will be slightly different where I have done a lot of extraction and grouping for those tables. Many of the ideas in the second part are unique and will not be available anywhere. Readers would also have the opportunity to suggest any new tables which could be developed. I would be glad to create these if I can.

Here is one important factor about the presentation of these tables. I have decided not to order the tables on any data field. It will invite unnecessary discussions. These are all great players and this exercise is not to determine who the best is. Hence all tables will be presented in strictly chronological order. The highlighting would be done in the commentary after the tables.

1. Career Summary
BatsmanInngsNOsRunsBallsAvgeS/RRpIIndex
Richards 16724 6721 758147.00 88.740.235.7
Miandad 21841 73811097941.70 67.233.922.8
M Crowe 14119 4704 646438.56 72.833.424.3
M Waugh 23620 85001106339.35 76.836.027.7
Tendulkar 45241184262137144.83 86.240.835.1
Jayasuriya 43318134301473632.36 91.131.028.3
Lara 28932104061305640.49 79.736.028.7
Inzamam 35053117391582739.53 74.233.524.9
Flower 20816 6785 914435.34 74.232.624.2
Bevan 19667 6914 929953.60 74.435.326.2
Ponting 36539137031706742.03 80.337.530.1
Kallis 30753114991575645.27 73.037.527.3
Gilchrist 27911 9619 992335.89 96.934.533.4
Pietersen 12116 4369 503541.61 86.836.131.3
Dhoni 19656 7259 822851.85 88.237.032.7

These are numbers which any cricket aficionado would reel off if woken up at 3am. The key columns here are RpI and the Index. The Batting average in ODIs is far more skewed than in Test matches because of the limited number of overs, non-completion of innings and high percentage of not-outs. The number of not-outs varies between 67 for the middle-order stalwart like Bevan to 18 for an attacking opener like Jayasuriya. Hence RpI (Runs per Innings) is a very important measure and reflects the relative positioning of batsmen far more accurately. Hence almost all these tables will have both Average and RpI.

Now for the Index. This has been a favourite combination measure of mine over the past 15 years. Realizing the importance of Average/RpI and the Strike Rate, I had multiplied the two measures, thus giving them equal importance. It allows players to compensate shortcomings in one measure with higher level performances in the other. Earlier I used this Index based on Batting average but now I always use RpI in all Index calculations.

The batting averages which stand out are Richards' 47.00, Bevan's 53.60 and Dhoni's 51.85. Jayasuriya's 90+ strike rate and the near-90 strike rate of Richards at 88.7 and Dhoni at 88.2 stand out. The 35+ Index values of Richards and Tendulkar sets them apart. Readers can note how Jayasuriya's low RpI value is partly compensated by the high strike rate. Similarly Kallis' average strike rate is offset by a good RpI value. The Index represents a clear value to the team: non-contextual of course.

2. Opening runs
BatsmanInnsNOsRunsBallsAvgeS/RRpIIndexOPP RunsOPP Avge
Richards 0 0 0 0 0.00 0.0 0.0 0.0 0 0.0
J Miandad 4 0 85 8621.25 98.821.221.0 10225.5
Crowe 22 1 814 117338.76 69.437.025.7 100845.8
M Waugh 14111 5729 747344.07 76.740.631.1 595942.3
Tendulkar 34023153101739748.30 88.045.039.61415441.6
Jayasuriya 38315127401378834.62 92.433.330.71287133.6
Lara 52 5 2166 287146.09 75.441.731.4 159730.7
Inzamam 12 0 516 72243.00 71.543.030.7 49341.1
Flower 44 2 1352 192832.19 70.130.721.5 167638.1
Bevan 1 1 40 62 0.00 64.540.025.8 1717.0
Ponting 6 1 272 35054.40 77.745.335.2 29549.2
Kallis 7 0 135 20619.29 65.519.312.6 24334.7
Gilchrist 259 7 9200 938636.51 98.035.534.81109242.8
Pietersen 8 1 412 46958.86 87.851.545.2 56370.4
Dhoni 2 0 98 11349.00 86.749.042.5 2110.5

The opening position in ODIs has undergone sea-changes across the years. Steady opening partnerships with both batsmen striking at around 60, with the objective of scoring a match-winning 250, were the order of the day around the 1980s. Mark Greatbatch was the first of the attacking openers who set the 1992 World Cup alight. This was followed by the Sri Lankan blitz with both openers, Jayasuriya and Kaluwitharana, blazing away, in the next edition. They won a World Cup with these attacking methods although the final two matches were won by conventional batsmen. Over the next 15 years the opening batting has changed in accordance with rule changes and power play implementations. Today it would be difficult to find a Greenidge-Haynes combination opening, both striking at below 65. This is a specialist position and various top batsmen have occupied it, with telling effect. Hence a special view of this anchor position is necessary.

The table contents are standard for most of these analyses. Richards never opened, Miandad once in three years and Martin Crowe, very rarely. Many of the others like Mark Waugh, Tendulkar, Jayasuriya and Gilchrist, spent most of their careers opening the batting. Mark Waugh, less than the other three. Gilchrist was the true opening-zone batsman, striking at 98. Jayasuriya was nearly as good, at 92 and Tendulkar did his scoring at 88. Mark Waugh was more sedate, probably content with watching Gilchrist's striking at the other end. Still a respectable 77. Tendulkar's RpI of 45 is mind-blowing. This also means that he has the highest Index value of nearly 40. It can be seen that all the four had Index values exceeding 30. Lara's opening stints were more effective than the rest of his batting efforts. Andy Flower, on the other hand, was less successful opening the batting.

I have also determined the average opening partnerships when the concerned batsman opened: mostly with some other batsman, other than Mark Waugh and Gilchrist who opened the innings regularly together. Gilchrist leads this quartet for an average opening partnership of 45.8 and is closely followed by Mark Waugh, with 45.3: a testament to the fact that they opened together often. Tendulkar, often with Ganguly, and the rest of the time with different batsmen, averages 41.6. Jayasuriya's average is only 33.6, a reflection of the fact that he and his partner were in attacking mood almost throughout their partnerships.

3. Late order runs (6 onwards)
BatsmanInnsNOsRunsBallsAvgeS/RRpIIndexTeamRunsBatRuns %
Richards 6 2 80 10020.00 80.013.310.7 69111.6
Miandad 9 1 175 26721.88 65.519.412.7 40043.8
M Crowe 3 1 138 17669.00 78.446.036.1 50727.2
M Waugh 4 2 51 6025.50 85.012.810.8 15333.3
Tendulkar 5 1 168 13542.00124.433.641.8 20781.2
Jayasuriya 31 2 405 55013.97 73.613.1 9.6 172023.5
Lara 8 3 263 27452.60 96.032.931.6 51551.1
Inzamam 25 3 542 75424.64 71.921.715.6 176230.8
Flower 8 3 197 29739.40 66.324.616.3 68928.6
Bevan 10645 3350 428654.92 78.231.624.7 824340.6
Ponting 6 3 75 9025.00 83.312.510.4 42417.7
Kallis 7 0 120 22017.14 54.517.1 9.4 49424.3
Gilchrist 19 4 390 49326.00 79.120.516.2 121432.1
Pietersen 5 1 128 12532.00102.425.626.2 49825.7
Dhoni 11334 3375 403242.72 83.729.925.0 947935.6

Just as opening the batting is important, finishing an innings, whether setting a target or chasing is important. Unfortunately in this analysis the required data, which is the information on when a batsman was dismissed, is available only over the past 20 years, for two-thirds of the matches. So I have to take a view based on when the batsman entered to start his innings. So this may not be a complete analysis. But we can draw a few insights. For this analysis I have compiled the runs scored where a batsman came in at no.5/6 or afterwards. At no.6, only two of these batsmen, viz., Bevan and Dhoni have played enough innings and that is the reason why I have considered that the role of a finisher can be at No.5 or No.6. Those at 1 and 2 are openers, 3/4/5 are consolidators and 5/6 onwards are finishers. I know this is not perfect but it cannot be helped.

Examining the table reveals that only two batsmen have played enough innings at No.6 onwards. Bevan has played 106 very effective innings at an RpI of 31.6 and Index of 24.7. Dhoni has also excelled in this position with 113 innings at 29.9 and Index of 25.0. It should be noted that the RpI will necessarily be lower since these two batsmen have remained not out 45 and 34 times respectively. These values are very important for the team since these are scored at the end of the innings in crunch situations, whether the team was batting first or second.

Here I have looked for a different type of additional analysis. I compiled the sum of the runs added by the team after the entry of the concerned batsman and looked at what % was scored by the concerned batsman. I think I struck pay dirt since Bevan's 40.6% of all the runs scored by the team after his entry is a testament to the great impact on the Australian batting. Inclusive of Bevan's own failures this figure of 40+% is the essence of finishing a match. Dhoni is slightly below, at 35.6% possibly because he often had top-order batsmen batting with him.

4. Late-order runs (5 onwards)
BatsmanInnsNOsRunsBallsAvgeS/RRpIIndexTeamRunsBatRuns %
Richards 35 3 930 109729.06 84.826.622.5 282832.9
Miandad 36 6 887 132129.57 67.124.616.5 306229.0
M Crowe 8 3 219 29643.80 74.027.420.3 125717.4
M Waugh 41 5 985 119027.36 82.824.019.9 281335.0
Tendulkar 41 9 965 111830.16 86.323.520.3 309731.2
Jayasuriya 38 2 438 62212.17 70.411.5 8.1 218420.1
Lara 47 9 1277 166533.61 76.727.220.8 407431.3
Inzamam 13025 4015 531338.24 75.630.923.31282031.3
Flower 56 7 1658 238433.84 69.529.620.6 478734.6
Bevan 13950 4515 584850.73 77.232.525.11111740.6
Ponting 12 4 124 16415.50 75.610.3 7.8 113510.9
Kallis 30 6 950 137439.58 69.131.721.9 356326.7
Gilchrist 19 4 390 49326.00 79.120.516.2 121432.1
Pietersen 17 7 826 83082.60 99.548.648.4 181645.5
Dhoni 16047 5258 623946.53 84.332.927.71383138.0

This is a slight variation to the previous table. I have looked at batting efforts from No.5 onwards. A lot more batting efforts now find a place. Bevan improves slightly while Dhoni has a significant move upwards. Inzamam is the other batsman who has played many important innings at No.5 onwards. His Index value is a reasonable 23.3. Note how badly Jayasuriya and Ponting performed on the few occasions when they were moved out of their comfort zones of opening and No.3 respectively.

Bevan remains at 40.6% in the % team runs measure. Dhoni's figure improves to 38.0%. The new serious entrant to this table, Inzamam scored 34.6% of his team runs.

5. Against Best Team (based on runs scored)
BatsmanTeamInnsNOsRunsBallsAvgeS/RRpIIndex
Richards Aus 50 7 2187 258250.86 84.743.737.0
Miandad Win 64 7 1930 300533.86 64.230.219.4
M Crowe Aus 34 3 1096 158135.35 69.332.222.3
M Waugh Win 45 2 1708 222739.72 76.738.029.1
Tendulkar Slk 80 9 3113 355843.85 87.538.934.0
Jayasuriya Ind 85 5 2899 298936.24 97.034.133.1
Lara Aus 50 3 1858 242939.53 76.537.228.4
Inzamam Ind 64 9 2403 306043.69 78.537.529.5
Flower Ind 35 3 1297 172440.53 75.237.127.9
Bevan Saf 31 5 1163 149044.73 78.137.529.3
Ponting Ind 59 5 2164 265840.07 81.436.729.9
Kallis Win 40 7 1666 214450.48 77.741.632.4
Gilchrist Ind 45 1 1622 163436.86 99.336.035.8
Pietersen Ind 28 3 1138 132345.52 86.040.635.0
Dhoni Slk 4511 2041 225260.03 90.645.441.1

Who were the favourite opponents of these wonderful batsmen? I have gone on runs scored rather than an average since scoring 2000 at 40 is more significant than scoring 500 at 50. The table is self-explanatory. The numbers which stand out are Dhoni's outstanding Index value of 41 against Sri Lanka, Richards' 37 against Australia and Gilchrist's 35+ against India. Tendulkar's 3000+ runs against Sri Lanka is the only instance of a batsman scoring over 3000 runs against a single country. I must confess that this is an educated guess and I will be glad to be disproved.

6. Best Year (based on runs scored)
BatsmanYearInnsNOsRunsBallsAvgeS/RRpIIndex
Richards 1985 25 5 1231 133261.55 92.449.245.5
J Miandad 1987 22 6 1084 154267.75 70.349.334.6
Crowe 1990 20 1 810 117742.63 68.840.527.9
M Waugh 1999 36 3 1468 194244.48 75.640.830.8
Tendulkar 1998 33 4 1894 185465.31102.257.458.6
Jayasuriya 2001 33 1 1202 144437.56 83.236.430.3
Lara 1993 30 3 1349 185749.96 72.645.032.7
Inzamam 1999 28 4 1106 157146.08 70.439.527.8
Flower 2001 33 3 1060 130135.33 81.532.126.2
Bevan 1998 22 8 959 117468.50 81.743.635.6
Ponting 2007 24 6 1424 155379.11 91.759.354.4
Kallis 2000 38 9 1300 195244.83 66.634.222.8
Gilchrist 1999 37 0 1241 139333.54 89.133.529.9
Pietersen 2007 25 4 889 113042.33 78.735.628.0
Dhoni 2009 24 7 1198 140070.47 85.649.942.7

Measuring performance over a year is a good analysis since the year is a sufficiently long time to give due respect to high level of performances. It is possible that during the 1980s a player might have only played 20 matches while a player might have played 30 matches during the 2000s. However since this table uses runs scored as a basis the lean years do not figure in the same.

Tendulkar's 1998 must rank among the greatest achievement by a player across formats. Even though he played only 33 matches, he aggregated 1894 runs at better than run-a-ball. The Index value of 58 is certainly Bradmanesque. Ponting's 2007 performance, the year during which Australia won the World Cup, is second to Tendulkar's and the Index value of 54 defies description. Richards, during 1985, suffers only in comparison with these two giants. It is nice to note that, arguably the best three ODI batsmen of all time, feature in the top positions in this table.

7. Best/Worst streaks: of 15 matches
BatsmanBest StreakWorst Streak
StODIYearRunsBallsRpIS/RIndexStODIYearRunsBallsRpIS/RIndex
Richards 19840253 994 108166.27 92.060.919880485 291 37419.40 77.815.1
J Miandad 19870417 906 125360.40 72.343.719770041 250 41616.67 60.110.0
Crowe 19920734 725 88248.33 82.239.719850305 337 50722.47 66.514.9
M Waugh 20001620 846 101556.40 83.347.019890549 271 34618.07 78.314.2
Tendulkar 19981323 1105 110473.67100.173.719930795 209 30913.93 67.6 9.4
Jayasuriya 19971207 922 74561.47123.876.119900623 112 163 7.47 68.7 5.1
Lara 19940947 934 98262.27 95.159.219981364 258 35717.20 72.312.4
Inzamam 20001580 744 103549.60 71.935.719961095 251 39416.73 63.710.7
Flower 20021814 719 85447.93 84.240.419950982 248 38016.53 65.310.8
Bevan 19981300 740 92949.33 79.739.320021802 309 43420.60 71.214.7
Ponting 20072473 925 100861.67 91.856.620082687 342 45222.80 75.717.3
Kallis 20032029 893 109759.53 81.448.520052244 315 55521.00 56.811.9
Gilchrist 20032052 860 74657.33115.366.120062434 306 34220.40 89.518.3
Pietersen 20042193 786 79052.40 99.552.120092827 268 35217.87 76.113.6
Dhoni 20092815 773 85851.53 90.146.420103030 311 50120.73 62.112.9

This is an analysis based on 15 consecutive matches. 15 represents about 4-6 months of cricket and is a very clear indication of short-term form. And I have not even bothered with not-outs and average for this short period since three not-outs out of 15 will distort the figures considerably. So it is only RpI and Index based on RpI.

Tendulkar during 1998 features again. A golden run, rather platinum run, starting on 20 April, 1998 and ending on 28 October, 1998 produced an unforgettable sequence of 38, 143, 134, 33, 18, 100*, 65, 53, 17, 128*, 77, 127*, 29, 2 and 141: 1105 runs in 15 innings at a strike rate of almost exactly 100. The first two centuries were those famous Sharjah blitzes against Australia. Richards' golden run is equally noteworthy considering the run-scarcity during the 1980s. He scored 67, 189*(!!!), 3, 84*, 47, 98, 49, 103*, 30, 74, 51, 46, 68, 9 and 76. A total of 994 runs off 1081 balls, striking at 92. The 189, considered by many as the greatest ODI innings ever played, is the jewel in this crown. Ponting's sequence only suffers by comparison. His 2007 sequence was 82*, 10, 5, 51*, 111, 104, 75, 7, 113, 23, 91, 35, 86, 66* and 66. The aggregate was 925 runs at a strike rate exceeding 90. The later part of this golden run was during the 2007 World Cup.

Jayasuriya's worst streak during 1990, a run of 4, 1. 23, 5, 0, 4, 1, 26, 0, 0, 5, 3, 32, 5, 3 is something to behold. A mere 112 runs in 15 innings. Let me also add that he compiled 271 runs in 30 innings during this disastrous period. The next lowest is Tendulkar during the barren period of 1993. Note the consistency of Ponting. Even during his worst streak period, he aggregated 342 runs. Martin Crowe, against better bowlers, was nearly as consistent, aggregating 337 runs. Dhoni is in a surprise third position with 315 runs.

It is interesting to note that three other batsmen have exceeded 1000 runs in 15 innings. Hayden, with 1101 runs off 1108 balls during 2007, Amla, with 1083 runs off 1070 balls during 2009-10 and Kohli, with 1003 runs off 1054 balls during 2012. There are three instances of competent batsmen scoring below 112 runs in a 15-innings streak. Samuels had a nightmare run of 90 runs in 15 innings during 2006, Pollock compiled only 105 runs during 2002 and Boucher scored 109 runs during 1999. It may seem obvious but it is clear that when a batsman is in great form he scores much faster than when he is in miserable form.

A shot-in-the-dark measure, not based on any scientific reasoning, is the difference between the best 15-innings RpI and worst 15-innings RpI figures. Tendulkar leads in this measure with a difference of around 60, followed by Jayasuriya, with a near-55 figure. Richards has a value of around 46. Readers can make what they can of these numbers.

In Part-2 I will be covering the following areas of analyses. If any reader comes out with a good suggestion it can be incorporated. I request that the readers do not ask for changes in players. I have completed a part of this analysis with one set of players and cannot abruptly follow-up with another set. The next part covers mostly performance oriented measures.

8. World Cup SF-F Champions Trophy Finals / Significant / Early matches
9. Batting Position / Boundary analysis
10. First & Second Innings analysis
11. Home / Neutral / Away analysis
12. Won / Lost matches analysis
13. Impact Inns / High Scoring Index / MOM analysis
14. Team share of runs/balls

Since I see many new readers I have to make my usual pitch regarding this specific blogspace, a small corner of "The Cordon". Please bear with me for this, just once.

I am always welcome to criticism and negative comments. In fact I value these a lot since new ideas flow and I can correct any blinkered views I have. But there is a clear line of propriety drawn for this particular blogspace. I had established that with "It Figures" and I had the best collection of informed readers who I respected and whose respect was my reward. When you come into this blogspace you are expected to follow these ground rules since you are here by invitation. If anyone makes a rude or insulting comment it only reflects his own shortcomings, not mine.

You will not insult me, any fellow reader or any player. That is the single commandment here. I have no problems with the following observations:

- Your analysis is based on a wrong premise.
- Your computations are wrong.
- Your analysis is statistically weak.
- You have over-complicated a simple issue.
- You have over-simplified a complex issue.
- You are not being fair to *.
- You have tried to solve a non-existing problem.
- Reader * is wrong/has not understood.
- Player * should retire.

I have problems with the following statements (and the like) and your comment will be junked instantly.

- You are stupid. Even if you have a Ph.D. in Statistics, you have no right to say that. I could, but never will, counter with a retort in far more colourful language.
- You favour players from *. Because, to me all countries are same.
- You favour *. Because I do not, and always leave my personal preferences aside.
- Reader * is stupid. Because he is not.
- Player * is selfish/greedy. Not in this forum.
- You are biased. I may publish this if I feel I can provide additional insight by answering this comment.

Finally let me say this unequivocally. I write for the average and interested cricket enthusiast who may or may not possess any serious statistical/mathematical qualifications. I do not write for the statistical/mathematical experts. Although I possess graduate-level statistical knowledge, I limit myself to Mean, Median, Mode, Standard Deviation, Quartiles, Normal Distribution and the like. I know that I will lose 75% of my readers the minute I bring in p-Value or z-Score.

I have only one avowed objective. I want my article to be understood by 95% of the visiting readers. I am not writing to get my articles published in the conferences of RSC or ISI or ASA. I am certain they would not be. Common sense is the cornerstone of my articles and I am proud of that. If I do not meet your expectations, my apologies and if you feel very strongly about it, au revoir.

Let me close with a short story. I had an excellent reader during the early years of "It Figures". Sometime back he stopped following the blog for various reasons. But he was never rude or insulting to me. I thanked him and said that the doors of this blogspace would always remain open since I valued his insights. I see that he has made a comment for the first article - to the point and that too, a point well-made. I never have any problems with readers like him.

Full post
The vexed question of 'not outs' in Test cricket

The statistical measurement of a player's batting average is one that has survived unaltered for 130 years of Test cricket - but it suffers from a fundamental flaw in the way 'not outs' are handled

Due to technical issues, Ananth has not been able to view and respond to the comments. We are working on the issue and hope to have it resolved as soon as possible.
This article addresses the often-debated question of 'not outs' in Test cricket. 'Batting average' is an archaic statistical measure with a glaring weakness. While other statistical measures have seen many changes over 130 years of Test cricket, this measure with a fundamental flaw has survived unaltered. Let's begin by understanding the flaw and then look at the methods to address it.

So what exactly is the problem? Well, it lies in the manner of handling not outs. Lara played an epic, scoring 400 runs over 13 hours but this innings, as far as determining the batting average is concerned, does not exist. On the other hand, his three first-ball ducks against Australia, England and New Zealand are considered as three innings. While it is true that he was dismissed in the later three innings, it is also a fact that he played long enough to have played four complete innings. Basically 'batting average' should not exclude such innings.

As Milind puts it quite effectively, the batting average computation violates a basic mathematical dictum. Runs are added to the numerator and nothing to the denominator. Absolutely perfect description of the anomaly that exists.
Let us compare the figures of two modern great batsmen.

Batsman     Team    T   I  No SNo No %  Runs  Avge  RpI
Kallis J.H   Saf  162 274  40   5 14.6 13128 56.10 47.91
Lara B.C     Win  131 232   6   2  2.6 11953 52.89 51.52

Kallis has played 31 more Tests to score additional 1150 runs but averages just over three runs more. That is because Kallis has 40 not outs compared with Lara's four. It might be due to the way Lara played, his batting positions or more declarations for Kallis who is a part of a stronger team and so on. Let us see how we can address the anomaly which is somewhat unfair to the top-order batsmen.

It should be noted that this problem is more pronounced in ODI matches because of the limited number of overs available and absence of declarations. It is also a fact that two batsmen remain not out in most ODI innings. However ODI batting is measured by the batting average and strike-rate, thus lowering the singular importance of batting averages.

I have selected 34 batsmen, who have scored over 2000 Test runs and averaged over 50, for this analysis. Virender Sehwag is just hanging on by the skin of his teeth and a failure in Chennai may very well plunge him below 50. And a reasonable Test at Centurion would push de Villiers past the 50 mark. However the data for all batsmen who have crossed 2000 runs is available for downloading and the link is provided later. The data is current up to match 2073, the Cape Town Test which finished just now.

BatsmanTeamTestsInnsNoNo %RunsAvge
 
Bradman D.GAus52801012.5699699.94
Pollock R.GSaf234149.8225660.97
Headley G.AWin2240410.0219060.83
Sutcliffe HEng5484910.7455560.73
BarringtonEng821311511.5680658.67
EdeC WeekesWin488156.2445558.62
Hammond W.REng851401611.4724958.46
SobersWin931602113.1803257.78
Hobbs J.BEng6110276.9541056.95
Walcott C.LWin447479.5379856.69
Hutton LEng791381510.9697156.67
Kallis J.HSaf1622744014.61312856.10
SangakkaraSlk115196168.21004555.81
TendulkarInd1943203210.01564554.32
ChappellAus871511912.6711053.86
Nourse A.DSaf3462711.3296053.82
Lara B.CWin13123262.61195352.89
MiandadPak1241892111.1883252.57
Clarke M.JAus891481510.1698952.55
Dravid RInd1642863211.21328852.31
Mohd YousufPak90156127.7753052.29
Amla H.MSaf68118108.5561051.94
Ponting R.TAus1682872910.11337851.85
ChanderpaulWin1462494216.91069651.67
Flower AZim631121917.0479451.55
HusseyAus791371611.7623551.53
GavaskarInd125214167.51012251.12
Waugh S.RAus1682604617.71092751.06
Younis KhanPak80140117.9658051.01
Hayden M.LAus103184147.6862650.74
Border A.RAus1562654416.61117450.56
RichardsWin121182126.6854050.24
ComptonEng781311511.5580750.06
Sehwag VInd10217763.4855950.05

Most cricket followers are au fait with the above table. The one data element not shown normally is the "Not out %". This shows the % of not outs out of the total innings played. Among this elite collection of 34 batsmen, who account for 13% of runs scored in Test cricket, the highest % of not outs has been achieved by Steve Waugh, the middle-order giant from Australia. He has been unbeaten one in six innings. Andy Flower, Shivnarine Chanderpaul and Allan Border have similar numbers. In Flower's case, it has been more a question of a top drawer batsman in a weak team remaining unbeaten as his compatriots were dismissed.

The lowest figure has been achieved by Lara with 2.6%: that means once in 40 innings. Sehwag, with his attacking instincts is the only other batsman who clocks in fewer than 5%.

Out of interest, let me share with the readers some facts related to not outs across the 135 years of Test cricket. Of the 72865 innings played, there have been 9502 not outs, accounting for about 13%. Out of these 9502, 4253 not outs - nearly half - have been at scores below 10 runs.


A simple alternative is to use the Runs per Innings (RpI) instead of the batting average. Unfortunately it is a drastic step taking the other extreme. It affects the middle-order batsmen considerably. Many of their low-score not outs would be considered as completed innings and players like Kallis would be penalised. The graph below illustrates the two extreme situations - batting averages and RpI.

Full post
Where is No. 2 and No. 20?

A study to rank and analyse Test batsmen and bowlers across various performance parameters

The idea for this article transpired when I was asked about the likelihood of any player catching up with Tendulkar. Although the prevailing opinion was in the negative, I was not as convinced as others. It is essential to put the contrasting measures in perspective and carry out an objective evaluation of the relative positions of players. Hence this article with the intriguing title.

Let me make it clear upfront to the readers that many of these conclusions would be obvious but there are some additional deductions which would throw fresh insights. This method of reducing all numbers to a % of the top value will make these measures dimension-less thereby providing easier comparisons.

I have separated Performance based measures from the Longevity based numbers. Conceding that extraordinary skill levels, stamina, fitness and sustained performance levels are a prerequisite to achieve the numbers, there is no doubt that these are the result of players playing in a lot of Tests over several years.

For the performance based tables, I have set 3000 runs as the cut-off point for batting. This would exclude great batsmen like Pollock and Headley but will also exclude the bowler-batsmen like Kumble, Akram, Harbhajan et al. We must have a cut-off to keep the population size manageable. Similarly the bowler cut-off is 100 wickets. Bond gets excluded, that is all. In addition, for reasons I have explained many times, I have excluded bowlers who made their debut before 1900. Bowling averages and strike rates were at a completely different level during the pre-1900 period due to uncovered wickets, batsmen finding their feet and Test match techniques at a nascent stage.

The tables are presented in a standardised format. I have shown the top-5 players, 20th placed player and the last three players in Performance tables. In addition, the highest placed currently active player is highlighted, if not present already. For the Longevity analysis, the top 10-12 players are shown depending on the way the numbers pan out. In addition, the highest placed active player is included, if not in the list already. For active players who have achieved at least 40% of the top value, an extrapolation is done, based on their own data, to indicate how many years and Tests it would take for the concerned player to overtake the top player. This is nothing but a ball-park estimate, I may add.

I have selected 5 batting measures and 5 bowling measures for Performance analysis. For the longevity analysis I have taken the staple of runs, wickets, hundreds and 5-wicket-captures. First let us inspect the Batting Performance measures.

Performance: Batting Average

SNo Batsman Inns Runs Avge % to Top Status  
               
1 Bradman D.G 80 6996 99.94 100.0%    
2 Sutcliffe H 84 4555 60.73 60.8%    
3 Barrington 131 6806 58.67 58.7%    
4 EdeC Weekes 81 4455 58.62 58.7%    
5 Hammond W.R 140 7249 58.46 58.5%    
               
10 Kallis J.H 274 13128 56.10 56.1% Active Highest
               
20 Amla H.M 120 5693 51.75 51.8% Active  
               
162 Marsh R.W 150 3633 26.52 26.5%    
163 Vaas WPUJC 163 3087 24.31 24.3%    
164 Warne S.K 199 3154 17.33 17.3%    

Unfortunately the lily, already gilded a million times over, has to be gilded again. The next best player at 60% and the twentieth placed player at around 50% reveals the real domination of Bradman. Suffice to say that no one, I repeat no one, is ever going to accomplish even 75% of what Bradman has achieved. Just for information, let me state that Hussey, with a phenomenal start to his career, was averaging 55 when he reached 3000 Test runs. The highest average at the 3000 mark was that of Sutcliffe, with 64.83. Then a host of West Indians - Sobers, Weekes, Lara - reached 60. There might be one or two others who have done that.

Performance: Batting Strike rate

SNo Batsman Runs Balls StRt % to Top Status
             
1 Sehwag V 8559 10389 82.4 100.0% Active
2 Gilchrist 5570 6796 82.0 99.5%  
3 Kapil Dev N 5248 7591 69.1 83.9%  
4 Dilshan T.M 5255 8052 65.3 79.2% Active
5 Jayasuriya 6973 10686 65.3 79.2%  
             
20 Vettori D.L 4516 7768 58.1 70.6% Active
             
162 Congdon B.E 3448 9656 35.7 43.3%  
163 Wright J.G 5334 14995 35.6 43.2%  
164 Flower G.W 3457 10011 34.5 41.9%  

This is the domain of modern day batsmen. Sehwag may be going through a bad patch now and can hardly put bat to ball, but no can disregard his outstanding attacking ability, with which he scored his 8500 runs at a strike rate of just over 82. The only batsman to challenge him is the already-retired Gilchrist who is close behind. It is possible that Sehwag may drop below 82. Note the wide gap which exists after Gilchrist. However this table is reasonably close as indicated by the strike rate of 20th placed Vettori who strikes at 70.

Performance: Runs per Test

SNo Batsman Tests Runs RpT % to Top Status  
               
1 Bradman D.G 52 6996 134.5 100.0%    
2 EdeC Weekes 48 4455 92.8 69.0%    
3 Lara B.C 131 11953 91.2 67.8%    
4 Hobbs J.B 61 5410 88.7 65.9%    
5 Hutton L 79 6971 88.2 65.6%    
6 Sangakkara 115 10045 87.3 64.9% Active Highest
               
20 Kallis J.H 162 13128 81.0 60.2% Active  
               
162 Pollock S.M 108 3781 35.0 26.0%    
163 Vaas WPUJC 111 3087 27.8 20.7%    
164 Warne S.K 145 3154 21.8 16.2%    

Bradman is way ahead, probably not as much as the Batting average, in this measure. Weekes and Lara come in at above 67%. Kallis is the 20th placed batsman who clocks at 60%. Sangakkara is the highest placed of the modern batsmen, at 65%.

Performance: Innings per hundred

SNo Batsman Inns 100s Inns/100 % to Top Status  
               
1 Bradman D.G 80 29 2.76 100.0%    
2 Headley G.A 40 10 4.00 69.0%    
3 Walcott C.L 74 15 4.93 55.9%    
4 Sutcliffe H 84 16 5.25 52.5%    
5 EdeC Weekes 81 15 5.40 51.1%    
               
8 Kallis J.H 274 44 6.23 44.3% Active Highest
               
20 Cook A.N 154 23 6.70 41.2% Active  
               
110 Jayasuriya 188 14 13.43 20.5%    
111 Gatting M.W 138 10 13.80 20.0%    
112 Stewart A.J 235 15 15.67 17.6%    

This is the frequency of scoring hundreds. The cut-off is 10 hundreds. Like WpT, the second best batsman in this regard, Headley is at 69%. Then there is a big drop. Cook is the 20th placed batsman at a very low 41%. Kallis is the highest placed modern batsmen at 44%. Until now it is certain that in these four measures, Bradman's numbers are as unassailable as a mountain which scales at Mt.Everset + Aconcagua together.

Performance: Single digit dismissal %

SNo Batsman Inns SglDgtOuts % % to Top Status  
               
1 Hobbs J.B 102 13 12.7 100.0%    
2 Sutcliffe H 84 12 14.3 89.2%    
3 Hammond W.R 140 24 17.1 74.3%    
4 Hutton L 138 24 17.4 73.3%    
5 Bradman D.G 80 14 17.5 72.8%    
               
15 Smith G.C 191 38 19.9 64.1% Active Lowest
               
20 Sangakkara 196 40 20.4 62.5% Active  
               
162 Flower G.W 123 48 39.0 32.7%    
163 Vaas WPUJC 163 67 41.1 31.0%    
164 Warne S.K 199 92 46.2 27.6%    

This table exposes life beyond Bradman. It is a tabulation of the % of single-digit dismissals, which are true failures in every sense. Hobbs has had a failure once every 8 innings and is at 100%. His partner, Sutcliffe, follows closely at 89%. For a change Bradman is only fifth at 72%. Sangakkara occupies the 20th position, clocking in at 62.5%. Graeme Smith, surprisingly for an opener, is the best modern batsman, at 64%, just ahead of Sangakkara. He has failed once every 5 innings. Note the presence of many an opener in the top-20.

In summary, at the risk of repeating myself, let me say, with 100% conviction and analytical proof, that none of Bradman's Performance marks will ever be overhauled.

Performance: Bowling Average

SNo Bowler Wkts Runs Avge % to Top Status  
               
1 Barnes S.F 189 3106 16.43 100.0%    
2 Blythe C 100 1863 18.63 88.2%    
3 Wardle J.H 102 2080 20.39 80.6%    
4 Davidson 186 3819 20.53 80.0%    
5 Marshall 376 7876 20.95 78.5%    
               
15 Steyn D.W 327 7418 22.69 72.4% Active Lowest
               
20 Pollock S.M 421 9733 23.12 71.1%    
               
152 Shastri R.J 151 6185 40.96 40.1%    
153 Boje N 100 4265 42.65 38.5%    
154 Hooper C.L 114 5635 49.43 33.2%    

While Barnes is at the top, quite a few bowlers are within 80% of the top. Shaun Pollock is 20th placed bowler, at a reasonable 71%. The best modern bowler is Steyn who clocks in at 72%. Even though Steyn's average is unlikely to drop below 20 there is no doubt that he has been magnificent. Let me add that Vernon Philander has 87 wickets at 16.82 currently. Two more successful Tests, 13 more wickets conceding 200 runs, would put him at the cut-off point of 100 wickets at 16.63, below Barnes!!!. We would need to pinch ourselves to believe this modern miracle. Can anyone bet against it?

Performance: Bowling Strike rate

SNo Bowler Wkts Balls StRt % to Top Status
             
1 Steyn D.W 327 13456 41.1 100.0% Active
2 Barnes S.F 189 7873 41.7 98.8%  
3 Waqar Younis 373 16223 43.5 94.6%  
4 Blythe C 100 4546 45.5 90.5%  
5 ShoaibAkhtar 178 8143 45.7 90.0%  
             
20 Lee B 310 16531 53.3 77.2%  
             
152 Shastri R.J 151 15751 104.3 39.4%  
153 Emburey J.E 147 15391 104.7 39.3%  
154 Hooper C.L 114 13788 120.9 34.0%  

Well the miracle has happened. We have a modern bowler at the top of a table, comprising of bowlers across 110 years. Dale Steyn, with a truly majestic strike rate of just over 41, is standing at the top with 100%. Barnes breaks the sequence of modern greatness since Waqar Younis is at no.3 with 94.6%. Then Blythe comes in between Waqar and the much-maligned Shoaib Akhtar who is at 90%. The 20th best player is Lee standing at 77%, a fairly close bunch of bowlers. We can safely say that this is one measure where the modern bowlers, led by Steyn, truly reign. And let us not forget Philander, currently striking at 36 balls per wicket.

Performance: Bowling accuracy

SNo Bowler Overs Runs RpO % to Top Status  
               
1 Goddard T.L 1956 3226 1.65 100.0%    
2 Nadkarni 1527 2559 1.68 98.4%    
3 Verity H 1862 3510 1.88 87.5%    
4 Wardle J.H 1099 2080 1.89 87.2%    
5 Illingworth 1989 3807 1.91 86.2%    
               
20 Benaud R 3184 6704 2.11 78.3%    
               
81 Vettori D.L 4779 12392 2.59 63.6% Active Lowest
               
190 Mohd Sami 1249 4483 3.59 46.0%    
191 Fernando 1030 3784 3.67 44.9%    
192 Edwards F.H 1600 6249 3.90 42.2% Active  

It is unbelievable that Nadkarni has been pushed into the second place, by the wonderful South African medium-pacer, Goddard. Then comes Verity. All the five bowlers are within 15% of the top. Benaud is placed at the 20th position at 78%. That the modern game affords no such luxuries is indicated by the poor placement, in the 81st position, of Vettori, the best modern bowler, at 63%. No one is going to breach the 50th place, leave alone the top place. The cut-off for this exercise is 1000 overs.

Performance: Wickets per Test

SNo Bowler Tests Wkts WpT % to Top Status  
               
1 Barnes S.F 27 189 7.0 100.0%    
2 Muralitharan 133 800 6.0 85.9%    
3 Grimmett 37 216 5.8 83.4%    
4 O'Reilly 27 144 5.3 76.2%    
5 Saeed Ajmal 25 133 5.3 76.0% Active Highest
               
20 McGrath G.D 124 563 4.5 64.9%    
               
152 Shastri R.J 80 151 1.9 27.0%    
153 Kallis J.H 162 288 1.8 25.4% Active  
154 Hooper C.L 102 114 1.1 16.0%    

Barnes stands alone at 7 WpT and 100%. Muralitharan's greatness is divulged by his comfortable second position, at 86%. It is not a surprise that Saeed Ajmal is in the top-5, at 76%. McGrath is the 20th placed bowler, at 65%.

Performance: Spells per 5-wicket-captures

SNo Bowler Spells 5wInns Spells/5WI % to Top Status  
               
1 Barnes S.F 50 24 2.08 100.0%    
2 Grimmett 67 21 3.19 65.3%    
3 Muralitharan 230 67 3.43 60.7%    
4 FazalMahmood 53 13 4.08 51.1%    
5 Hadlee R.J 150 36 4.17 50.0%    
               
10 Herath HMRKB 76 14 5.43 38.4% Active Lowest
               
20 Swann G.P 90 14 6.43 32.4% Active  
               
62 Lee B 150 10 15.00 13.9%    
63 Zaheer Khan 158 10 15.80 13.2% Active  
64 Vaas WPUJC 194 12 16.17 12.9%    

Barnes had a 5-wkt capture every two spells, amazing but true. Grimmett went past 3 and Muralitharan, around 3.4. See how rapidly this value increases, with Hadlee at 50% of Barnes. The 20th bowler is conveniently Swann who is at a very low 32.4%. However he is upstaged by Herath, the best active bowler, who is at 38.4%.

Summarizing, I am unable to say with certainty that Barnes' average will not be overhauled by Philander, if not in his entire career, at least while crossing the threshold of 100 wickets. Same conclusion applies to the Strike rate and, to a lesser extent, the WpT measures. But one thing can be said, with as much certainty as Bradman's achievements, the Goddard/Nadkarni axis is never going to be breached.

Longevity: Runs scored

SNo Batsman Status Tests Runs % to Top How long to catch up
             
1 Tendulkar Active 194 15645 100.0%  
2 Ponting R.T   168 13378 85.5%  
3 Dravid R   164 13288 84.9%  
4 Kallis J.H Active 162 13128 83.9% 31 tests & 4 years
5 Lara B.C   131 11953 76.4%  
6 Border A.R   156 11174 71.4%  
7 Waugh S.R   168 10927 69.8%  
8 Jayawardene Active 138 10806 69.1% 62 tests & 8 years
9 Chanderpaul Active 146 10696 68.4% 68 tests & 9 years
10 Gavaskar   125 10122 64.7%  
11 Sangakkara Active 115 10045 64.2% 64 tests & 7 years
             
39 Cook A.N Active 87 7117 45.5% 104 tests & 8 years

Longevity: Hundreds scored

SNo Batsman Status Tests Hundreds % to Top How long to catch up
             
1 Tendulkar Active 194 51 100.0%  
2 Kallis J.H Active 162 44 86.3% 26 tests & 3 years
3 Ponting R.T   168 41 80.4%  
4 Dravid R   164 36 70.6%  
5 Lara B.C   131 34 66.7%  
6 Gavaskar   125 34 66.7%  
7 Waugh S.R   168 32 62.7%  
8 Jayawardene Active 138 31 60.8% 89 tests & 11 years
9 Hayden M.L   103 30 58.8%  
10 Sangakkara Active 115 30 58.8% 80 tests & 9 years
11 Bradman D.G   52 29 56.9%  
             
23 Cook A.N Active 87 23 45.1% 106 tests & 9 years

Are Tendulkar's marks that unbreachable? I do not think so. Kallis, to a lesser extent, and Cook, to a greater extent, have a fighting chance of overhauling Tendulkar's aggregate of runs and hundreds. It is unlikely, though. With the proliferation of IPL, BPL, BBL, SLL, EPL, APL (Albanian Pro League), ZPL(Zambian Pro League) and the likes, it may very well be impossible for Cook to play as many Tests and maintain the same level of consistency through the next 10 years, as he has done over the past 8. And the slight possibility, considering Tendulkar's current form, of Tendulkar raising the bar. It is unlikely, but not out of the realms of possibility, that Tendulkar stands second.

Longevity: Wickets captured

SNo Batsman Status Tests Wickets % to Top How long to catch up
             
1 Muralitharan   133 800 100.0%  
2 Warne S.K   145 708 88.5%  
3 Kumble A   132 619 77.4%  
4 McGrath G.D   124 563 70.4%  
5 Walsh C.A   132 519 64.9%  
6 Kapil Dev N   131 434 54.2%  
7 Hadlee R.J   86 431 53.9%  
8 Pollock S.M   108 421 52.6%  
9 Wasim Akram   104 414 51.8%  
10 Harbhajan Active 99 408 51.0% 95 tests & 14 years
11 Ambrose   98 405 50.6%  
             
21 Steyn D.W Active 64 327 40.9% 93 tests & 14 years

Longevity: 5-wicket-captures

SNo Batsman Status Tests 5Ws % to Top
           
1 Muralitharan   133 67 100.0%
2 Warne S.K   145 37 55.2%
3 Hadlee R.J   86 36 53.7%
4 Kumble A   132 35 52.2%
5 McGrath G.D   124 29 43.3%
6 Botham I.T   102 27 40.3%
7 Wasim Akram   104 25 37.3%
8 Harbhajan Active 99 25 37.3%
9 Barnes S.F   27 24 35.8%
10 Lillee D.K   70 23 34.3%
11 Imran Khan   88 23 34.3%
12 Kapil Dev N   131 23 34.3%
           
18 Steyn D.W Active 64 21 31.3%

Is Muralitharan ever going to be the no.2? Certainly never. The possibility of someone crossing 800 wickets and 67 x 5-wicket-hauls is as unlikely as any batsman scoring 5000+ runs at an average 100+. This is proved by the numbers. Harbhajan, unlikely to play 5 more Tests, is at 50% of Muralitharan's mark. Steyn, with more years ahead of him, could reach 500 wickets, no more. And no active bowler is even at 40% of Muralitharan's number of 5-wicket hauls: hence any projection becomes meaningless.

To download/view the comprehensive Excel sheet containing the values for the 5 Batting Performance tables, please CLICK HERE.

To download/view the comprehensive Excel sheet containing the values for the 5 Bowling Performance tables, please CLICK HERE.

To download/view the comprehensive Excel sheet containing the values for the 4 Longevity tables, please CLICK HERE.

Wicket-keeper dismissals

How long to catch up
1 Boucher M.V           147   555 100.0%
2 Gilchrist              96   416  75.0%
3 Healy I.A             119   395  71.2%
4 Marsh R.W              96   355  64.0%
5 Stewart A.J           133   277  49.9%
6 Dujon P.J.L            81   272  49.0%
7 Knott A.P.E            95   269  48.5%
8 Dhoni M.S    Active    73   234  42.2%       100 tests
9 Wasim Bari             81   228  41.1%
10 Evans T.G              91   219  39.5%

It seems very unlikely that Boucher's landmark will be breached. I cannot really see Dhoni playing 100 more Tests. With his interest in CSK et al, I would expect him to play 20 more Tests. So the chances are probably around 1%.

Non-WK dismissals

How long to catch up
1 Dravid R              164   209 100.0%
2 Ponting R.T           168   195  93.3%
3 Kallis J.H   Active   162   195  93.3%        11 Tests
4 Jayawardene  Active   138   193  92.3%        11 Tests
5 Waugh M.E             128   181  86.6%
6 Fleming S.P           111   171  81.8%
7 Lara B.C              131   164  78.4%
8 Taylor M.A            104   157  75.1%
9 Smith G.C    Active   109   157  75.1%        36 Tests
10 Border A.R            156   156  74.6%

I can clearly see both Kallis and Jayawardene overtaking Dravid's mark. It is almost certain that either or both would do that. Smith is less likely though.

Full post
Country-wise look at dismissals in Tests

A stats analysis to determine the distribution of Test wickets by team and host country

This data-centric analysis is a follow-up to my previous article on Test Dismissals across the ages. It was clear from the beginning that a follow-up analysis by country would complete the analysis. The comments are minimal due to number of tables, and I expect the readers to come out with their own views.

Even within the country division, multiple analyses are possible. The first is "by country" from the batting point of view which analyses how batsmen from each country lost their wickets. The second one is "by country" but from the bowling/fielding point of view analysing how the wickets were captured. The final one is "by country" based on location of these Tests. Each one will offer some insights.

In view of the number of tables (18, to start with), I have restricted the third analysis, "by location" only to the three bowler-centric dismissals which are likely to be influenced by the type of pitches: Lbw, Bowled and Caught by wicketkeeper. The other three dismissals, viz., Ct by other fielders, Run outs and Stumped, relate less to the type of pitches and more to fielding. Yet we are left with 15 tables, each shown by dismissal type.

LBW dismissals

Lbw: Batsmen Out %187719201946196019701980199320002007All
 191419391959196919791992199920062012Tests
 
Australia6.029.8815.7010.7011.8614.5513.6116.0213.6712.23%
Bangladesh       18.6914.0916.82%
England6.5212.4512.0212.0013.8617.8115.1516.1618.6213.57%
India 15.5610.659.019.9515.4513.1914.7416.0813.04%
New Zealand 14.8512.6613.1911.1416.0717.1020.5717.7615.77%
Pakistan  10.8210.2311.1014.5018.0016.1020.8815.06%
South Africa6.7411.7914.2511.3211.9412.5016.6515.6016.7713.62%
Sri Lanka     14.5214.2314.7716.0314.88%
West Indies 15.1013.5913.0411.1217.5619.7619.7422.8416.98%
Zimbabwe     11.3620.2719.5821.3319.71%
Lbw: Dismissals %
Australia6.1811.5411.969.4012.1315.1217.8018.0814.9513.08%
Bangladesh       16.8319.5518.09%
England5.8512.5113.4811.779.6915.0314.3016.8618.6912.68%
India 16.2816.2113.3213.6915.3119.3019.6920.8917.04%
New Zealand 5.598.689.4612.8012.9815.5714.3615.2512.94%
Pakistan  12.868.9910.9820.7422.2918.5122.6618.36%
South Africa8.6714.0412.9814.4011.2515.6214.8713.1811.5812.92%
Sri Lanka     20.1114.0020.9623.2719.75%
West Indies 10.3412.3012.4412.4215.1511.8314.9412.4313.28%
Zimbabwe     3.0314.9815.9713.7915.03%
Lbw: In Country %
Australia5.7111.7113.948.5510.0012.9014.2215.1811.9811.37%
Bangladesh      13.3319.4717.4018.38%
England6.9911.0712.7112.3513.2516.9014.7317.4917.4113.67%
India 19.0013.6411.3913.3117.0119.8616.7320.3915.98%
New Zealand 8.1110.3810.8410.2714.6414.5517.5715.4613.70%
Pakistan  11.239.5611.9221.1123.3519.5411.7018.18%
South Africa6.7314.3212.6712.0511.5617.0515.3012.4113.0412.49%
Sri Lanka     15.4013.0119.0821.3117.86%
West Indies 14.1813.7714.7011.4214.3217.8216.7119.8815.41%
Zimbabwe     7.7915.2817.2518.8716.06%
U.A.E.       26.7232.0030.18%

New Zealand batsmen of the recent period of 2000-2006, have been out Lbw over 20% of all dismissals, a figure which is way above the rest of the periods. Maybe a sign of the struggles the Kiwis have faced in recent times. Pakistani batsmen over the most recent period have been out Lbw over 20%. And look at the post-Lara West Indians. They have been out Lbw over 22%. During recent times, Australian batsmen have been out Lbw only 13.6%.

Now for the bowling dismissals. Pakistan has been the leaders in this mode of dismissal during the recent few periods. They have exceeded 20% during three of the four periods and are well above the 20% mark. The influence of Imran, Akram, Younis, Saqlain, Akhtar et al, can be seen. During the past two periods Sri Lanka has also been comfortably above the 20% mark: a certain influence of Murali. Recently India have also been well above the 20% mark. Look at South Africa. Fairly low Lbw % during the past two periods. The recent drop in Australia's % of Lbw dismissals is noteworthy.

Pakistan stands out in the in-country Lbw dismissals. During two periods between 1980 and 1999, well over 20% of the dismissals in Pakistan were of this kind. I would give the major credit to the bowlers and a minor reason could be the often-referred-to situation of home umpires. India also came close to 20% during the 1990s. Sri Lankans, during the most recent period, part of it without Murali, have comfortably gone past 21%. Note the low Lbw dismissal % in Australia and South Africa during recent times.

Bowled dismissals

Bowled: Batsmen Out %187719201946196019701980199320002007All
 191419391959196919791992199920062012Tests
 
Australia33.5629.2325.5425.9121.2320.4117.2014.1016.9623.01%
Bangladesh       14.1416.4715.09%
England36.7526.6526.7424.3019.5920.7518.7817.4117.1123.85%
India 25.1931.3925.4022.2317.9817.2217.3217.7521.12%
New Zealand 32.6727.9726.1119.7616.9215.7017.4617.8920.09%
Pakistan  29.2227.1417.5017.0213.5613.9515.1817.61%
South Africa42.5935.2628.5024.4919.4025.0018.4419.5218.1826.08%
Sri Lanka     18.5215.6915.7215.7716.29%
West Indies 22.9228.0122.7823.1018.2615.2016.9015.3819.72%
Zimbabwe     25.0015.4516.3417.3316.29%
Bowled: Dismissals %
Australia37.7828.0428.0820.9517.8416.3815.7215.4816.3221.95%
Bangladesh       16.3518.4417.31%
England35.4730.6429.6325.9722.5317.5714.3916.2418.3624.54%
India 26.7421.8025.2019.4419.0216.7713.5917.6918.77%
New Zealand 30.0731.2726.4318.2819.8213.4415.0912.1118.82%
Pakistan  29.9232.7022.2621.8321.6720.2318.9822.46%>
South Africa36.1728.0923.5523.0022.5015.6219.5716.3815.4121.62%
Sri Lanka     15.3716.2917.0216.2216.39%
West Indies 21.7229.9025.3623.1321.2515.9218.0316.8021.43%
Zimbabwe     12.1213.2914.0727.5914.39%
Bowled: In Country %
Australia34.1225.3328.3121.1618.8716.4216.1015.0316.1521.57%
Bangladesh      13.3315.0718.1316.41%
England37.5731.2927.7425.9121.7120.4417.4517.1718.0224.38%
India 15.0026.4427.5020.6320.2317.2115.7323.0721.44%
New Zealand 35.6834.9927.2618.4618.5115.4316.7612.7719.87%
Pakistan  27.9728.9620.9819.8620.0515.8425.5320.93%
South Africa39.8031.5525.2217.1221.0918.1818.0616.1813.4022.88%
Sri Lanka     15.4017.0518.5215.4516.93%
West Indies 22.0127.8026.0423.2320.1615.6916.2913.6220.00%
Zimbabwe     19.489.3814.5224.5313.45%
U.A.E.       22.1418.8019.95%

The only batsmen dismissal figure over 20%, of the bowled variety, during recent times has been England during the 1980s. I cannot get a handle on this.

Look at the string of 20+ % values by Pakistani bowlers, barring a slight drop during the last period. I think this can again be attributed to the range of incisive fast bowlers Pakistan possessed.

Same thing is true of Pakistan, the country. Glad to note that these are direct bowler-centric dismissals. The only comparable number is by the West Indian bowlers during the 1980s. It is a surprise that the bowled dismissal figure is below 14% in South Africa.

Caught by Wicket-keeper

CtWk: Batsmen Out %187719201946196019701980199320002007All
 191419391959196919791992199920062012Tests
 
Australia9.8012.6312.8714.4316.6918.9521.0318.0417.3715.73%
Bangladesh       18.4617.8318.20%
England7.1810.2915.7517.7917.4718.6619.7820.7418.8115.82%
India 10.3712.6715.3617.9720.8814.0318.7617.3517.03%
New Zealand 7.9211.7214.4919.0218.5519.3018.3017.3716.95%
Pakistan  13.2015.2418.7817.7519.2017.8518.3917.62%
South Africa7.688.7213.6217.7023.8815.6220.5617.8318.0515.14%
Sri Lanka     19.5619.5918.8418.1319.01%
West Indies 9.3812.1715.7013.9016.2417.1616.3914.5715.04%
Zimbabwe     15.9116.1115.829.3315.62%
CtWk: Dismissals %
Australia7.059.0216.2018.4421.7119.9218.4220.0521.0616.81%
Bangladesh       18.7513.4116.28%
England9.4211.0411.5515.7516.3118.9223.1517.9614.8914.85%
India 9.3011.449.7611.2916.1815.2013.7616.6213.72%
New Zealand 10.4915.3817.2918.6519.1217.9219.3420.0318.28%
Pakistan  15.7510.9018.4016.0314.4517.9419.8316.52%
South Africa7.8610.3413.8218.8018.7531.2522.4121.6116.7517.17%
Sri Lanka     20.1112.6515.0012.5014.71%
West Indies 11.0313.2617.7516.4619.3922.8319.2820.7718.31%
Zimbabwe     18.1821.3118.2517.2419.52%
CtWk: In Country %
Australia8.4711.3813.7716.7920.8021.0420.6219.8720.3316.91%
Bangladesh      6.6716.4816.6716.32%
England8.2611.1313.5417.1318.1117.8422.5019.5717.4816.00%
India 12.0011.6012.0412.7414.8411.5515.3213.7313.18%
New Zealand 7.5711.9614.4519.5821.4421.1219.7522.1318.95%
Pakistan  16.0812.0215.2815.5614.3817.5719.1515.56%
South Africa7.968.5015.5922.4121.0922.7322.4322.0918.4517.01%
Sri Lanka     20.6014.7415.3414.3215.73%
West Indies 8.2112.2816.6114.0719.0918.6817.5417.7516.46%
Zimbabwe     16.8819.6217.1014.1517.89%
U.A.E.       13.7414.4014.17%

England during the years just after turn of the millennium, India during the 1980s and South Africa, immediately after their return are the only cases where a team has lost more than a fifth of the wickets to catches behind by the keeper. Of course I am aware that it has not been possible to separate the catches taken by slip fielders. In this regard, only Sri Lankans appear to have a slightly more pronounced weakness than others.

Now for the bowlers. The period 1993-99 has been the best period for bowlers in inducing edges to the wicket-keeper. England, South Africa and West Indies had 22-plus % figures for the keeper-catches during this period. South Africa continued with 21.6% during the next period. Look at Australia's figures of 21-plus % during the last period.

If anyone is asked which country would have had the highest % of keeper-catches, there would be quite a few answers, with England or New Zealand as candidates for the first amongst equals. Well, the figures seem to confirm this except that New Zealand is way ahead of the others with nearly 19%. And they have been consistent over the past 30 years. Australia also had similar figures over the same period. Indians, with their predominantly spin attacks, have been below 14% overall.

Run Out dismissals

Run Outs: Batsmen Out %187719201946196019701980199320002007All
 191419391959196919791992199920062012Tests
 
Australia4.844.583.414.613.953.583.343.773.083.94%
Bangladesh       2.223.062.56%
England3.493.192.223.473.322.272.552.432.652.84%
India 0.744.373.463.253.843.894.403.143.71%
New Zealand 3.473.283.002.233.333.603.472.703.15%
Pakistan  6.062.713.983.913.254.203.503.89%
South Africa3.233.074.126.174.484.692.793.302.823.50%
Sri Lanka     3.414.383.794.073.92%
West Indies 4.175.565.194.173.074.343.352.103.86%
Zimbabwe     2.273.824.412.674.02%
Run Outs: Dismissals %
Australia3.643.342.734.213.292.132.773.052.733.06%
Bangladesh       6.253.915.17%
England4.183.573.533.992.824.162.503.562.733.54%
India 2.334.635.014.913.313.263.052.143.63%
New Zealand 6.294.714.573.663.424.603.413.293.93%
Pakistan  4.202.453.563.412.993.533.263.35%
South Africa4.262.012.963.402.504.693.622.652.593.03%
Sri Lanka     3.614.713.774.264.07%
West Indies 6.215.203.503.743.053.563.673.013.72%
Zimbabwe     6.064.853.995.174.49%

Run Outs for the batting team reflects, in general, a lack of communication and not so athletic batsmen. It is no wonder that India and Pakistan are ranked high on this table with % of run outs in excess of 3.7% during the recent times. These days, Sri Lankans too have caught this bug.

High Run Outs dismissals % values indicate an above-average fielding ability. New Zealand, during the 1990s and England, during the 1980s are examples. However look at Bangladesh's figures. They have averaged 5.2%. It is probably due to the liberties which the batsmen of the opposing teams took as well as a surprisingly athletic ability of the young cricketing nation. Recently Sri Lanka has been quite good. India has the lowest figures amongst all teams, during recent years.

Stumping dismissals

Stumpings: Batsmen Out %187719201946196019701980199320002007All
 191419391959196919791992199920062012Tests
 
Australia3.271.832.552.551.681.951.632.191.952.21%
Bangladesh       2.222.552.35%
England3.594.032.641.741.700.761.551.801.232.18%
India 5.192.022.311.731.091.531.721.861.78%
New Zealand 5.454.381.311.490.601.500.961.801.70%
Pakistan  4.981.251.281.471.741.951.751.89%
South Africa3.104.423.881.232.991.562.010.981.412.41%
Sri Lanka     1.331.581.801.051.48%
West Indies 4.954.261.771.501.741.191.821.282.06%
Zimbabwe      1.001.692.671.41%
Stumpings: Dismissals %
Australia3.705.863.181.791.320.661.942.160.732.31%
Bangladesh       2.402.792.58%
England2.833.052.731.561.110.921.431.101.161.87%
India 1.166.133.033.132.601.692.182.332.86%
New Zealand 4.202.731.471.650.880.711.220.901.29%
Pakistan  3.152.182.082.732.482.391.982.44%
South Africa4.423.242.541.200.000.000.391.011.031.68%
Sri Lanka     1.333.632.684.123.02%
West Indies 2.412.971.811.110.400.731.090.821.22%
Zimbabwe     3.030.841.521.721.28%

Not so surprisingly, South African batsmen lead the stumpings wickets % with 2-plus value. What about New Zealand batsmen having a stumpings % below 1.00 during the 2000-06 period? Possibly due to fewer spinners travelling to New Zealand.

Look at the drop of stumpings % of Australian bowlers during the pre and post Warne-retirement periods. 2.16% dropped to 0.73%. Indians have been quite good. However the real high numbers rest with the Sri Lankan bowlers. 3.6% during the Murali reign and 4.12%, even after his retirement. The lowest figure is 0.4% by the pace-dominant West Indian bowling line-ups of the 1980s.

Caught by others

CtOth: Batsmen Out %187719201946196019701980199320002007All
 191419391959196919791992199920062012Tests
 
Australia40.9939.7137.8438.8642.3138.7641.8943.4345.9440.96%
Bangladesh       42.1743.8042.84%
England41.2541.1638.4639.4843.1437.8039.2639.6040.1739.97%
India 41.4836.6642.7341.1238.2248.3341.6343.1441.30%
New Zealand 33.6638.1240.7344.7342.4842.0038.0440.4140.80%
Pakistan  33.7741.1345.2343.4042.8444.2939.5642.22%
South Africa35.7134.7734.3837.8635.8237.5037.7741.3541.1037.74%
Sri Lanka     39.7041.6143.5643.6342.31%
West Indies 41.1534.2840.5143.9640.9140.7240.5041.6140.49%
Zimbabwe     45.4541.8640.6045.3341.49%
CtOth: Dismissals %
Australia40.3839.5036.3443.9642.1844.8142.5240.1043.1241.48%
Bangladesh       36.0639.9437.86%
England40.9036.9437.8139.9845.5142.2742.9042.4942.6841.00%
India 43.0236.7840.3744.5140.8140.5345.7338.9741.39%
New Zealand 42.6635.4838.5043.3341.0546.1144.7746.6442.74%
Pakistan  33.0740.8741.2532.4033.9535.0232.4434.82%
South Africa37.4841.8241.6137.6045.0032.8137.9644.3851.2942.38%
Sri Lanka     36.2446.1639.7338.3040.31%
West Indies 44.4832.9837.6840.2038.1642.4140.4844.2639.44%
Zimbabwe     54.5543.4644.6829.3143.63%

No great insights can be drawn from this amorphic collection of dismissals. The catch could be a diving effort in the first slip or a skier at long-off. Let me leave the readers to draw whatever insights they want to.

The only outlier is South Africa, which is the only country to exceed 50%. This, they did during the most recent period. Possibly many slip catches have been taken due to the presence of Steyn, Philander, Kallis et al in the bowling line-up. Look at the low values for Pakistan. Their bowlers believed in hitting the stumps, pads or toes.

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Analysing Test dismissals across the ages

A detailed look at various forms of dismissals in Tests, and their frequency over the years

It has always been my desire to carry out a complete analysis of run-outs in Test matches covering every aspect of this fascinating form of dismissal. Since I have never looked at Test dismissals as a single topic, I decided to take an overall look at dismissals and subsequently go to the next level.

The initial analysis is an in-depth look at dismissals across various periods following the usual classification. The Pre-WW1, Between-wars, 1950s, 1960s and 1970s were automatic selections. On this occasion, I have tweaked the remaining years. Tendulkar, who frequently gives his wicket to debutants, was also the first victim of TV umpires who made their debut in 1992 at Durban. Hence I decided to have 1980-1992 as a period followed by three more: 1993-1999, 2000-2006 and 2007-2012. This ensures decent number of Tests in each period.

Let us begin with the base table of number of dismissals in each period. This analysis covers the period until 31 December 2012. Even though three Tests have since been played, all my table work was done before Test no 2069 was incorporated into the database.

Number of dismissals by period

Dismissal type187719201946196019701980199320002007All Tests
 -1914-1939-1959-1969-1979-1992-1999-2006-2012
 
Tests1341402091861983392743452432068
 
Bowled16391205177414491271188313871747127413629
LBW28650982166172115861365182313239095
WK Caught3734328599201058184815851946132210343
Fldr Caught18091639233223252647396834924436319925847
Stumped152158207106991271301861241289
Run Outs1791472412322183252923722262232
Others5889127961292111521781091149
 
Total449641796361578961439948840310688757763584

This table has been shown just for information. There is very little insight to be drawn from this since the number of Tests varies between periods. However the data is available if anyone wants to do some work.

Now the first of two special tables. The first shows the % of dismissals by dismissal type across periods.

Dismissals analysis: % of total dismissals

Dismissal type187719201946196019701980199320002007All Tests
 -1914-1939-1959-1969-1979-1992-1999-2006-2012
 
Bowled36.4528.8327.8925.0320.6918.9316.5116.3516.8121.43%
LBW6.3612.1812.9111.4211.7415.9416.2417.0617.4614.30%
WK Caught8.3010.3413.5015.8917.2218.5818.8618.2117.4516.27%
Fldr Caught40.2439.2236.6640.1643.0939.8941.5641.5042.2240.65%
Stumped3.383.783.251.831.611.281.551.741.642.03%
Run Outs3.983.523.794.013.553.273.473.482.983.51%
Others1,292.132.001.662.102.121.811.671.441.81%

Bowled: This type of dismissal has varied drastically across the ages. During the first period about 37% of batsmen were bowled. The figure dropped below 30% soon and remained around this figure until after the WW2. The next three periods exhibit further drops till it stabilized around 16% during the past three periods covering 20 years. The current figure is well below half the initial figure. How does one explain this? Can we infer that the batsman’'s defence was suspect? Or that the bowler was looking for the most direct form of the dismissals? Could it have been the effect of the uncovered pitches? Or the need to score quickly in 3-day matches? I will let the readers have a field day.

LBWs: This type of dismissal has moved in the other direction. Starting from a very low 6%, the LBW share doubled in the next period. Afterwards the figure remained reasonably steady but took a higher turn in 1980s. It was around that figure until a significant drop during the last period. What does it convey? Possibly that until the change of LBW laws, one could pad away with impunity. Did technique have an effect on these changes? During the past 5 years there is an increase of about 0.4%. This could be due to the partial implementation of DRS. Again let the readers come in with their comments.

WK Catches: Similar to LBWs, at 8% in the first period, followed by a slight increase between the wars and then steady increase until the peak was reached during the 1990s. Then, inexplicably, there has been a drop and now the figure is around 16%.

Fielder Catches: It is a great surprise that, irrespective of the period and whether the batsmen were out bowled or LBW, the fielder catches figure remains either side of 40%, the variation no more than 5% during most of these periods. Taking cognizance of the fact that 40% represents the highest share of all dismissal types, I am as surprised with this revelation as the drastic movement in Bowled and LBW dismissals.

Now we come to two very similar dismissals based on a batsman straying out and failing to reach home.

Stumpings: During the first three periods, the stumpings dismissal share remained at just over 3%. Then it dropped to nearly half and reached a low of 1.3% during 1980-92. It has picked up since and is around 2% these days. Can the current increase be attributed to the more attacking instincts of the batsmen? Third umpire came to the party during 1992. This meant a significant increase during the next three periods. Good spinners have always been around during all these periods.

Run Outs: Surprisingly the Run Outs % has remained steadily at around 4% right through the ages. The value dropped to 3% during 2000-2006, despite the introduction of third umpire. Perhaps the third umpire reversed more decisions in favour of the batsmen.

An analysis of dismissal percentages in Tests
© Anantha Narayanan

Dismissals analysis: Dismissals per match

Dismissal type187719201946196019701980199320002007All Tests
 -1914-1939-1959-1969-1979-1992-1999-2006-2012
 
Bowled12.28.68.57.86.45.65.15.15.26.6
LBW2.13.63.93.63.64.75.05.35.44.4
WK Caught2.83.14.14.95.35.55.85.65.45.0
Fldr Caught13.511.711.212.513.411.712.712.913.212.5
Stumped1.11.11.00.60.50.40.50.50.50.6
Run Outs1.31.11.21.21.11.01.11.10.91.1
Others0.40.60.60.50.70.60.60.50.50.6
           
Total33.029.229.930.630.328.930.230.530.630.2

Now for an alternate form of representation. This one relates to the specific numbers instead of percentage values. Though quite similar, they offer different insights.

The total number of dismissals was quite high to start with. 33 dismissals per Test. Then the value dropped and has stabilized at around 30. So these numbers are relevant indeed.

Notice how the average number of bowling dismissals has dropped over the periods and has stabilized now. On the other hand, LBW dismissals kept increasing and are slightly above the Bowled figure now. Wicket keeper catches increased steadily with a slight drop in recent years. Look at fielder catches which have remained either side of 12 catches per Test. Stumpings have dropped significantly and plateaued. The average number of run outs has more or less remained unchanged.

The combined values across all the periods are - 12.5 fielder catches, 6.6 bowled to 1.1 run outs and 0.6 stumpings per match totaling to about 30 dismissals per match including a few others but excluding those fancy dismissals like hitting the ball twice, obstructing the fielder, hit wicket, handling the ball etc.

An analysis of dismissals per match in Tests
© Anantha Narayanan

Here we are to where we started with. A complete look at run-outs. I wanted to look at how run outs have panned over the years: across periods, by countries, against countries et al. Nothing is gained by looking across 137 years and saying that Australia has lost 1.7% due to run-outs or has effected 1.9% of dismissals in run-outs. So the real need is to develop a four dimensional matrix: by dismissal type, by country/for country and by period. Then present the tables in an easy-to read and understandable form.

I plan to do that next. But why stop at run-outs? Every form of dismissal will throw some light on this fascinating aspect of the game. In fact I have a sneaking suspicion that this follow-up analysis could be very very interesting. We may be able to relate the numbers to famous names such as Harvey, Bland, Harper, Rhodes, Wasim, Waqar, McGrath, Alderman et al.

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