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Anantha Narayanan

First 125 years: two gladiators, 22 yards, five days

A look at the most interesting duels between a batsman and a bowler in Test cricket

In my last article, I had done a single-Test analysis of the head-to-head battles between bowler and batsman. This article covered about 550 matches from Test #1546 onwards where the complete ball-by-ball data is available.

The current article is a logical follow-up to that article and I will look at matches upto Test #1545. This covers 125 years of Test cricket. As such, I feel it is probably more important than the previous article. Some of the great confrontations ever took place during this long period.

Since no ball-by-ball data is available for these matches, this is really a pseudo-analysis of the head-to-head confrontations. However, the idea for this analysis originated from the previous one.

This analysis has been done using the single source available: the scorecard.

As astute readers would have guessed by now, the analysis is a tricky and involved one. Out of these 1545 Tests, we have data available for balls played by batsman for about 900 matches.

These represent interim levels of data. For the other 650 matches or so, we do not have the balls-played-by-batsman information. So I had to adopt different techniques to arrive at reasonable results.

For the 900 matches for which the balls-played-by-batsman information is available, I did a single extrapolation. Since I knew the balls played by each batsman, I needed to only allocate these balls between the bowlers who bowled in the innings based on the balls bowled by each of them. So this is a single extrapolation.

I had to be careful when I wanted to find out the runs scored off each bowler. This had to be a separate computation based on the runs conceded by the bowlers. This would ensure that the more accurate bowlers might bowl more balls at the batsmen but concede fewer runs.

I had to adopt a two-step algorithm for the 650 or so matches for which I had bare minimum information: only the runs scored. First I had to do an estimate of the balls played by each batsman by allocating the total innings balls based on a ratio of batsman runs and team runs.

Afterwards the allocation of balls and runs to the individual bowlers followed the method adopted earlier. These calculations are summarised below with couple of examples.

Two famous triple-centuries are used: Len Hutton's 364 in Test #266 for which the balls-played information is available (847) and Hanif Mohammad's 337 in Test #446 for which balls played information is not available, even though it is a later match.

I have avoided making any further assumptions such as batsman's batting position, bowler type, when the batsman started his innings and ended (anyhow this data is not available for these matches) et al.

"Keep it simple" has been my watchword.

Formula to determine the balls played by Batsman where not available
Batsman balls = Team balls * Batsman runs / (Sum of Batsman runs)
Hanif scored 337 out of 657 (Extras 33) in 319.0 overs.
    Balls faced by Hanif = (319x6) * 337 / (657-33) = 1034.

Common to both: Bowler allocation
Formula to determine the Batsman-Bowler balls Bat-Bow balls = Batsman balls * Bowler balls / (Sum of Bowler balls) Denis Atkinson to Hanif = 1034 * (62*6+0) / (319*6+0) = 201 (Atkinson's bowling analysis 62.0-35-61-1) Bill O'Reilly to Hutton = 847 * (85*6+0) / (335*6+2) = 215 (O'Reilly's bowling analysis 85.0-26-178-3)
Formula to determine the Batsman-Bowler runs Bat-Bow runs = Batsman runs * Bowler runs / (Sum of Bowler runs) Atkinson to Hanif = 337 * 61 / (657-33) = 33 (33 extras) O'Reilly to Hutton = 364 * 178 / (903-50) = 76 (50 extras)

Let us now move on to the tables.

Analysis for Innings: Single extrapolation (Batsman balldata available)
TestYearBatsmanRunsBallsBowlerExt B-B RunsExt B-B Balls
2661938L Hutton364847Fleetwood-Smith127220
2661938L Hutton364847WJ O'Reilly76215
8401979DW Randall150498JD Higgs69203
1931930A Sandham325640OC Scott104199
2661938L Hutton364847MG Waite64182
6181967G Boycott246555EAS Prasanna87179
2801946SG Barnes234667DVP Wright61177
2801946SG Barnes234667AV Bedser55177
15262000G Kirsten180461M Muralitharan56177
2561936WR Hammond231579FA Ward75172
1601925J Ryder201461R Kilner54169
2561936WR Hammond231579WJ O'Reilly49168
13741997ST Jayasuriya340578RK Chauhan105166
7321974DL Amiss262563AG Barrett58166
10901988DC Boon184431EE Hemmings63166
13741997RS Mahanama225561RK Chauhan69161
8991981JG Wright110434DR Doshi26161
11161989Javed Miandad271465SL Boock102160
6011966RM Cowper307589FJ Titmus50160

The featured table lists all situations where the bowler bowled more than 160 balls at a specific batsman. The downloadable table lists all instances with 120 balls as cut-off.

Hutton's 364 was a monumental innings. Wally Hammond was determined to grind Don Bradman and his team into the dust and batted for nearly three days. Hutton faced 847 balls - no extrapolation needed for this, and scored 364 runs. Bill O'Reilly and Chuck Fleetwood-Smith had contrasting spells. They had spells of 85-26-178-3 and 87-11-298-1 respectively. This wide disparity in runs conceded is reflected in the numbers. Hutton faced 215 balls against Fleetwood-Smith as against 203 against O'Reilly. However he scored many more runs off Fleetwood-Smith. This shows the advantage of separate extraction processes for balls and runs. This is the only instance of a batsman facing over 200 balls off two bowlers in an innings.

Derek Randall's presence in third position is a way-out situation since he scored only 150 runs. Coming in after a rare first-ball dismissal of Geoff Boycott, Randall batted for nearly ten hours and faced a whopping 498 balls. This, coupled with the fact that Jim Higgs bowled nearly 40% of the team overs, contributed to this unlikely combination, reaching to 199 balls.

An interesting presence in this table is that of Sanath Jayasuriya and Roshan Mahanama. In that mind-numbing "Test of patience" in 1997, Sri Lanka's mammoth 952 required 271 overs to be bowled. Rajesh Chauhan bowled most, with 78 overs, and Anil Kumble and Nilesh Kulkarni followed with 72 and 70 respectively. Chauhan features here twice, and the other two hapless bowlers feature in the longer list. Jayasuriya faced 166 balls off Chauhan and Mahanama, 161. These two faced 154, 149 balls off Kumble and 149 and 145 balls off Kulkarni. Ah! My hands get tired typing out these numbers. Paralysis of the mind could very well set in.

Analysis for Test: Single extrapolation (Batsman balldata available)
TestYearBatsmanRunsBallsBowlerExt B-B RunsExt B-B Balls
1791929WR Hammond296977CV Grimmett94265
1981930H Sutcliffe215565CV Grimmett79228
8991981JG Wright143628DR Doshi33223
2661938L Hutton364847Fleetwood-Smith127220
1931930A Sandham375702OC Scott129219
1591925H Sutcliffe303871JM Gregory86219
2661938L Hutton364847WJ O'Reilly76215
7381974G Boycott211725LR Gibbs65215
1791929WR Hammond296977RK Oxenham51210
1591925H Sutcliffe303871AA Mailey95207
15302001ME Trescothick179517M Muralitharan67206
1601925J Ryder289580R Kilner72205

The featured table covers Test confrontations of 200 balls and above.

Hammond scored 119 and 177 and played a total of 977 balls. A monumental effort indeed. Clarrie Grimmett bowled over 100 overs and Hammond played 265 balls of these. This was during Bradman's debut series.

Andy Sandham scored 375 runs in the nine-day Test in which there was no play on the last two days (yes, you read it right). It is amazing that the score stood at England: 849, West Indies: 286, and England batted again. Then they did not send the first-innings triple-centurion until the score was 176 for 5. Otherwise, Sandham might very well have upstaged Graham Gooch. Sandham faced 219 balls from Tommy Scott but more importantly scored 129 runs, the highest in all these matches.

Marcus Trescothick vs Muttiah Muralitharan just missed getting into the group of Tests with ball-by-ball data. It is noteworthy that Trescothick faced Muralitharan away for over 200 balls without giving his wicket once to Murali.

Analysis for Innings: Double extrapolation (No batsman ball data available)
TestYearBatsmanRunsExt Bat-BallsBowlerExt B-B RunsExt B-B Balls
4391957PBH May285811S Ramadhin94308
5641964KF Barrington256757TR Veivers67246
4501958GS Sobers365587Fazal Mahmood116241
3261950L Hutton202654AL Valentine73233
4391957PBH May285811DS Atkinson72226
5641964RB Simpson311749TW Cartwright58225
2261933WR Hammond336595FT Badcock80225
3711953FMM Worrell237523MH Mankad96208
6311968GT Dowling239567RG Nadkarni58201
4461958Hanif Mohammad3371034DS Atkinson33201

This table also features confrontations clocking at 200 balls and above.

First, let us not forget that this is a double extrapolation method. Peter May's 891 itself is a derived figure. This was a match in which May and Colin Cowdrey engineered one of the greatest comebacks in history. After two innings the scores stood at England: 186. West Indies: 474. Then England were tottering at 113 for 3. The amateur duo of May and Cowdrey came in and added 411 runs. Sonny Ramadhin bowled 98 overs in the innings which is a record even today. May faced 308 balls off Ramadhin, and that was some feat. It is the highest faced by a batsman off a bowler. Even allowing for a 10% variation, this is around 270 balls. Let us not forget that May, the captain, declared when he was 285, thus depriving himself of a triple-century. In the bargain West Indies scored 72 for 7 and narrowly escaped a defeat. Shades of New Zealand against India during 1965.

Ken Barrington's marathon effort of 256 runs translated to 757 balls and 246 balls off Tom Veivers. Not many runs were scored, though. Garry Sobers, in his record-breaking innings of 365, which transposed to only 587 balls, faced 241 balls off Fazal Mahmood. Hanif faced maximum balls from Denis Atkinson during his 16 hour epic of 337. This was extrapolated to 1034 balls, the only time in history of Test cricket that a batsman faced over 1000 or more balls in an innings, extrapolated or otherwise. There is a fair chance that this would be correct since Hanif was an eminently defensive batsman.

Analysis for Test: Double extrapolation (No batsman balldata)
TestYearBatsmanRunsExt bat-BallsBowlerExt B-B RunsExt B-B Balls
4391957PBH May315891S Ramadhin99340
3241950C Washbrook150679AL Valentine48264
3241950C Washbrook150679S Ramadhin57262
5211962Hanif Mohammad215733GAR Lock81258
3711953FMM Worrell260608MH Mankad104250
5641964KF Barrington256757TR Veivers67246
3771953GO Rabone175732HJ Tayfield47242
3261950L Hutton204663AL Valentine76241
4501958GS Sobers365587Fazal Mahmood116241
5641964RB Simpson315761TW Cartwright58227
2261933WR Hammond336595FT Badcock80225
6651969MG Burgess178628Intikhab Alam75224
4391957PBH May315891DS Atkinson73223
3371951EAB Rowan296836R Tattersall46223
3391951AJ Watkins177657MH Mankad36221
4461958Hanif Mohammad3541079OG Smith57221
3391951AJ Watkins177657SG Shinde83220
3371951EAB Rowan296836MJ Hilton93210
2891947B Mitchell309728R Howorth67203

The cut-off for this is also 200 balls.

May's figures were derived separately for each innings and added. Since he played a reasonable number of balls in the first innings, the total comes to 891 and May faced a mind-boggling tally of 340 balls off Ramadhin. This is by far the maximum number of balls faced by a batsman off a single bowler. Look at how far off this is from the Cyril Washbrook v Alf Valentine and Washbrook v Ramadhin numbers.

I am happy to see the presence of Allan Watkins' defensive classic during England's tour of India, with a virtual "B" side. Hutton, May, Cowdrey, Fred Trueman, Denis Compton, Trevor Bailey and Alec Bedser were missing. Watkins handled Vinoo Mankad very effectively. This is nostalgia for me since the first cricket book I ever read was the one on this tour.

Comparison of extrapolated values with actual values for selected combinations
Single innings
Test Year Batsman          Bowler          Ext Actual Diff (Act to Est)
1810 2006 DPMD Jayawardene N Boje          201  221  - 9.1%
1563 2001 JH Kallis        RW Price        188  189  -0.05%
2034 2012 Azhar Ali        MS Panesar      164  163  +0.07%
1641 2003 SP Fleming       M Muralitharan  160  185  -13.6%
1696 2004 BC Lara          GJ Batty        150  161  - 6.9%
Single Test
Test Year Batsman          Bowler          Ext Actual Diff
1641 2003 SP Fleming       M Muralitharan  249  265  - 6.1%
1572 2001 BC Lara          M Muralitharan  213  240  -11.3%
1952 2010 HM Amla          Harbhajan Singh 188  177  + 6.2%
1743 2005 Younis Khan      A Kumble        185  208  -11.1%
1562 2001 A Flower         CW Henderson    176  202  -12.9%

In this table I have compared the actual head-to-head values as determined in my previous analysis with values extrapolated using the single extrapolation method. The differences are of the order of 15% on either side. In general, the actual values tend to be higher than the extrapolated values.

Finally, a question might arise as to what degree of confidence I have on the extrapolated results. I would say around 80% for the single extrapolation and 70% for the double extrapolation method. In other words I would expect values to be around 10% either side for single extrapolation and 15% on either side for the double extrapolation. Just a gut feeling. That is all. I agree that this is an estimate. However, when we have figures like May scoring 285 runs out of a total of 547 in 258 overs, we are not going to be far off if we say, with 70% degree of confidence, that May would have faced 811 balls (1548*285/547).

Readers are requested to come up with suggestions on how the ball-by-ball data available for the recent 550 matches can be used. I have one idea, provided by Ashwin Krishnamurthy, which is to look at how players played during the period close to reaching landmarks, such as hundreds.

I have created a document file containing all the qualifying performances. There are about 380 Innings-level selections and 270 Test-level combinations, shown in four tables. To download/view this document, please CLICK HERE.

I will not comment on the South African tour happenings since ESPNcricinfo does not like outsiders using strong comments on these matters in their space, and my choice of words cannot be mild.

However, I cannot but pass a comment or two on the Indian bowling woes attributed to the new rules. The sardonic smile you see on the horizon is mine on hearing that the new rules are not helping MS Dhoni. How do the same rules that help the India team plunder 120 runs in the last ten overs become unfair when it comes to the India bowlers? Without the new rules, India might well have finished at 270, in Mohali. And how do the new rules bring down R Ashwin's skills, someone who has opened the bowling in all formats of the game regularly, and who is not a guileful Erapalli Prasanna, by a long mile. And Ravindra Jadeja's flat fastish slow left arm is not going to be affected a lot by a fresher ball. The plain truth is that, barring Mitchell Johnson (and Mohammad Shami at Ranchi), the bowling across the board has been awful. And that is the difference in the series scoreline.

Full post
Two gladiators, 22 yards, five days

A look at the most interesting duels between a batsman and a bowler in Test cricket

This is a special analysis using ball-by-ball data which was compiled recently by Milind and me. For readers who might have come in recently, let me reiterate Milind's outstanding contributions in extracting the ball-by-ball data for all Tests matches, from Test #1546. In turn, I have extracted the key elements, formed my own binary database and done a number of analyses. However, without Milind's stellar efforts, this entire exercise would have been a non-starter, like an Mbangwa innings.

Until now I have analysed the head-to-head confrontations across these 550 Tests and specific team contests, such as the Ashes series. In this analysis I have looked at the huge database, from the perspective of a single Test. Some fascinating facts emerge and offer us hitherto-unavailable insights. The unit of data in this analysis for me is a bowler-batsman combination in a single innings or Test. The analysis centres around the balls bowled, runs scored, scoring rate and percentage of balls bowled in the innings. The wickets captured is not relevant for this analysis since we have gone to the lowest level and there can only be one wicket capture per innings and two wicket captures per Test. Whether the bowler dismissed the concerned batsman or not is (almost) completely irrelevant. I am also not sure whether the boundaries information is relevant. It is obvious that MS Dhoni would have hit Nathan Lyon for quite a few and Faf du Plessis hit virtually nothing off Lyon. Actual number of boundaries probably does not mean much.

I considered doing a similar analysis for the Tests #1-#1545 through extrapolation and post tables in this article itself, but I realised that it was a lot more complex than I envisaged and would warrant a separate article. For some innings such as Len Hutton's 364 at the Kennington Oval in 1938, I have the actual balls faced by Hutton and this analysis would then have required a single extrapolation amongst the Australian bowlers, based on actual balls bowled by each of them. On the other hand, for Hanif Mohammad's 337 in Bridgetown in 1958, I do not have the balls-played information and I would have to do two levels of extrapolation. First one, to determine how many balls Hanif would have faced among the Pakistan batsmen and then, to determine how many balls Hanif would have faced off each West Indies bowler. Hence there is need for two clearly delineated threads for that article. So that analysis would be done in a separate article.

Let us now see the tables.

Single innings HtH: Ordered by balls bowled
TestYearBowlerBatsmanBallsRunsSc Rate
18102006N BojeDPMD Jayawardene221125 56.6
15632001RW PriceJH Kallis189 68 36.0
19092009M MuralitharanYounis Khan187111 59.4
16412003M MuralitharanSP Fleming185 95 51.4
20612012NM LyonF du Plessis172 20 11.6
20062011Saeed AjmalTMK Mawoyo166 73 44.0
19792010Abdur RehmanAB de Villiers164 74 45.1
20342012MS PanesarAzhar Ali163 66 40.5
16962004GJ BattyBC Lara161130 80.7
17432005A KumbleYounis Khan161 88 54.7

This table of maximum balls bowled by a bowler to a batsman is headed by a very unlikely bowler. Nicky Boje bowled 221 balls to Mahela Jayawardene during the batsman's magnificent innings of 374 against South Africa in Colombo in 2006. This is not surprising since the two Sri Lanka maestros scored 661 of their team's 756 runs. In second place is another unlikely bowler, Ray Price, who bowled 189 balls to Jacques Kallis, interestingly, in Kallis' innings of 189 against Zimbabwe at Bulawayo in 2001. In third place is Muttiah Muralitharan's effort against Pakistan at Karachi, when he bowled 187 balls to Younis Khan, who scored a triple-hundred at Karachi in 2009. Muralitharan's tally of 187 balls against Stephen Fleming at Colombo follows next. Then comes the recent bowling stint by Lyon against du Plessis during the latter's defensive match-saving classic of 110 at Adelaide Oval. Look at the scoring rate of this marvellous innings. It is of interest to see that all ten head-to-head confrontations featured here are by spinners. It is understandable. Nowadays even medium pace bowlers rarely bowl more than 40-50 overs in an innings.

Single innings HtH: Ordered by runs scored
TestYearBowlerBatsmanBallsRunsSc Rate
19772010S RandivCH Gayle154143 92.9
16962004GJ BattyBC Lara161130 80.7
18102006N BojeDPMD Jayawardene221125 56.6
19092009M MuralitharanYounis Khan187111 59.4
16002002DL VettoriInzamam-ul-Haq114109 95.6
19662010S RandivSR Tendulkar153105 68.6
20742013NM LyonMS Dhoni 85104122.4
18702008PL HarrisV Sehwag108100 92.6

This table is ordered by runs scored. Chris Gayle, during his epic innings of 333 against Sri Lanka in Galle, scored an amazing 143 runs off Suraj Randiv. Note the wonderful strike rate. And this haul was out of the 183 runs conceded by Randiv. Next comes Brian Lara, who, during his watershed innings of 400 in St John's, Antigua, took 130 runs off Gareth Batty. It is interesting to note that Batty conceded only 185 runs in this innings. We have already talked of Boje v Jayawardene. Jayawardene took 125 runs off Boje. Again we see only spinners occupying all the bowlers featured here. Marvel at Lyon v Dhoni, about which I will speak more in the next table.

Single innings HtH: Ordered by scoring rate (Min 100 balls or 100 runs)
TestYearBowlerBatsmanBallsRunsSc Rate
20742013NM LyonMS Dhoni 85104122.4
16002002DL VettoriInzamam-ul-Haq114109 95.6
19772010S RandivCH Gayle154143 92.9
18702008PL HarrisV Sehwag108100 92.6
19332009Harbhajan SinghDPMD Jayawardene102 89 87.3
20462012Abdur RehmanKC Sangakkara104 84 80.8
16962004GJ BattyBC Lara161130 80.7
20952013P UtseyaYounis Khan108 84 77.8
20032011S SreesanthAN Cook103 80 77.7
16342002SCG MacGillMP Vaughan102 79 77.5
16612003RW PriceML Hayden116 89 76.7
20272012I SharmaMJ Clarke121 92 76.0
....
15632001CW HendersonDD Ebrahim115 18 15.7
20062011RW PriceYounis Khan112 17 15.2
20612012NM LyonF du Plessis172 20 11.6
15852002M MuralitharanSV Carlisle121 11 9.1

This table is ordered on scoring rate. I have selected confrontations which contained either 100 balls or 100 runs. The recent blitzkrieg of Dhoni in Chepauk is still fresh in everyone's memory. If ever a captain made a statement and placed a marker, this was the occasion. Facing 380, India were 196 for 4 and one would have expected a war of attrition. Instead Dhoni scored a 265-ball innings of 224. Lyon bore the brunt of this effort, conceding 104 off 85 balls: the only effort in these 550 Tests of a better-than-run-a-ball effort with the said criteria.

Inzamam-ul-Haq, in his masterpiece of 329 at Lahore in 2002, took Daniel Vettori for a nearly run-a-ball 114 runs. Gayle also plundered Randiv for 143 runs in 154 balls. Suddenly we see two medium pace bowlers here. S Sreesanth against Alastair Cook, during the latter's 294 at Edgbaston in 2011 and Ishant Sharma, against Michael Clarke, during his triple-century in Sydney in 2012, during those two disastrous tours: both went above an average 75 runs per wicket.

Since this is a table on strike rates I have presented the other end also: the low scoring rates. Muralitharan tied Stuart Carlisle down completely, allowing only 11 runs in 121 balls at Galle in 2002. Similarly Lyon's effort against du Plessis also was similar. Although one must admit that du Plessis was the winner. Price was very good against Younis Khan, although it must be conceded that Younis played a match-winning innings.

Single innings HtH: Ordered by % of bowler balls for inns (Min 100 balls)
TestYearBowlerBatsmanBallsInnsBowlerBalls%
20092011TM DilshanTaufeeq Umar13419269.8%
17352005Enamul Haque jnrT Taibu14422264.9%
16392003VC DrakesRT Ponting12419862.6%
19712010Wahab RiazIJL Trott10216462.2%
19522010A MishraHM Amla14824061.7%
17862006Mohammad RafiqueWU Tharanga11819261.5%
20272012I SharmaMJ Clarke12119861.1%
15722001M MuralitharanBC Lara13522260.8%
19132009PL HarrisPJ Hughes11318660.8%
20372012CS MartinAN Petersen10216860.7%
17482005UDU ChandanaL Vincent10216860.7%
16402003Enamul HaqueHH Dippenaar11919860.1%

These tables are ordered by the percentage of balls to a specific batsman as compared to the balls in the innings. For some inexplicable reason, this table is headed by a non-regular bowler. Tillakaratne Dilshan bowled 32 overs and he bowled 22 of these to Taufeeq Umar at Abu Dhabi in 2011. Then comes Enamul Haque, who bowled nearly 65% of the innings balls to Tatenda Taibu in Dhaka in 2005. Another unlikely bowler, Vasbert Drakes, bowled 62% of his spell to Ricky Ponting in Port-of-Spain in 2003. Probably the most significant of these entries is Muralitharan's 61% of his spell to Lara during Lara's double hundred at the SSC in Colombo in 2001. More about this later as we move the analysis from single innings to single Test.

Single Test HtH: Ordered by balls bowled
TestYearBowlerBatsmanBallsRunsSc Rate
16412003M MuralitharanSP Fleming265118 44.5
15722001M MuralitharanBC Lara240164 68.3
20612012NM LyonF du Plessis227 34 15.0
18102006N BojeDPMD Jayawardene221125 56.6
17432005A KumbleYounis Khan208123 59.1
17352005Enamul Haque jnrT Taibu202101 50.0
20582012R AshwinAN Cook195 80 41.0
15632001RW PriceJH Kallis189 68 36.0
19092009M MuralitharanYounis Khan187111 59.4
19522010A MishraHM Amla187 65 34.8

This table is one after my heart. It is headed by two of the greatest confrontations between bowler and batsman in modern Test cricket. Both involved Muralitharan, bowling at home, against two wonderful, if contrasting, left-handers. The first was during 2003 when New Zealand toured Sri Lanka. Fleming was absolutely outstanding in the first Test played at the P Sara Oval, Colombo. He scored 343 runs in 710 balls and faced Muralitharan for 265 out of these. He was not dismissed in the match. He played Murali with circumspection, scoring only 118 runs.

One of the greatest contests ever was enacted during the completely one-sided tour of Sri Lanka by West Indies during 2001. The teams played three Tests, which were won by margins of ten wickets, 131 runs and ten wickets. The West Indians, barring Lara, had no answer for Muralitharan and Chaminda Vaas. Lara made scores of 178, 40, 74, 45, 221 and 130. The last Test features in this table. Muralitharan v Lara at the SSC, Colombo. Murali bowled 240 balls but could not dismiss Lara even once. Lara scored 164 runs at more than four runs per over. This was a contest the gods would have stopped to watch.

Lyon against du Plessis was an equally stirring contest. Where it lacked excitement like the first two, it did not lack in intensity. Two lesser lights were at work. Lyon, yet to be established. du Plessis, on debut for South Africa. du Plessis had one of the best debut Tests ever for a batsman by battling for 535 balls and 188 runs (less relevant) and saved South Africa. Out of this, Lyon bowled 227 balls but could not breach du Plessis' defence even once. The scoring rate was a lowly 15.0 but really did not matter.

Single Test HtH: Ordered by runs scored
TestYearBowlerBatsmanBallsRunsSc Rate
15722001M MuralitharanBC Lara240164 68.3
19772010S RandivCH Gayle154143 92.9
16962004GJ BattyBC Lara161130 80.7
18102006N BojeDPMD Jayawardene221125 56.6
17432005A KumbleYounis Khan208123 59.1
19732010NM HauritzSR Tendulkar168121 72.0
16412003M MuralitharanSP Fleming265118 44.5
19092009M MuralitharanYounis Khan187111 59.4
16002002DL VettoriInzamam-ul-Haq114109 95.6
19662010S RandivSR Tendulkar153105 68.6
18522007Danish KaneriaSC Ganguly177105 59.3
20742013NM LyonMS Dhoni 85104122.4
18502007Sohail TanvirW Jaffer119101 84.9
16732003SCG MacGillR Dravid174101 58.0
17352005Enamul Haque jnrT Taibu202101 50.0
18702008PL HarrisV Sehwag108100 92.6

Lara leads the Runs scored table, with 164 runs. Then comes Gayle's 143 off Randiv, already discussed. Lara's 130 runs off Batty follow afterwards. The next two entries are those of Jayawardene and Younis Khan. Sachin Tendulkar makes a rare appearance in these tables with a rich haul of 121 runs off Hauritz in Bangalore during 2010. Younis Khan makes a second appearance in the top-ten with his compilation of 111 runs off Muralitharan during his epic 313 in Karachi. Incidentally, this match produced 1400 runs for 13 wickets in the first innings.

Single Test HtH: Ordered by scoring rate (Min 100 balls or 100 runs)
TestYearBowlerBatsmanBallsRunsSc Rate
20742013NM LyonMS Dhoni 85104122.4
16002002DL VettoriInzamam-ul-Haq114109 95.6
19772010S RandivCH Gayle154143 92.9
18702008PL HarrisV Sehwag108100 92.6
18502007Sohail TanvirW Jaffer119101 84.9
16962004GJ BattyBC Lara161130 80.7
19732010NM HauritzSR Tendulkar168121 72.0
....
20142011HMRKB HerathMisbah-ul-Haq172 36 20.9
16722003M MuralitharanGP Thorpe159 33 20.8
19742010DL VettoriVVS Laxman166 28 16.9
20612012NM LyonF du Plessis227 34 15.0

Dhoni's onslaught against Lyon leads this table also since this confrontation passes the 100-balls or 100-runs test. Inzamam-ul-Haq's clinical dismembering of the usually accurate Vettori follows next. He scored at 95.6. Gayle's 82.9 against Randiv is next. Then comes the brutal innings of Virender Sehwag in Chennai. During his better-than-run-a-ball innings of 319, he scored exactly 100 runs off 108 balls against Paul Harris. One could say that Harris did well, considering that Sehwag scored 211 runs off the other bowlers in 196 balls. There is a surprise entry of the normally sedate Wasim Jaffer against Sohail Tanvir at Eden Gardens in 2007. This table is quite close to the single innings table.

At the other end, unsurprisingly, du Plessis against Lyon props up the table, with a scoring rate of 15. VVS Laxman, facing a disastrous 15 for 5 against New Zealand at Motera, Ahmedabad in 2010, understandably was quite slow against Vettori. Graham Thorpe's two innings were also match-saving efforts.

Single Test HtH: Ordered by % of bowler balls in Test (Min 100 balls)
TestYearBowlerBatsmanBallsTestBowlerBalls%
17862006Mohammad RafiqueWU Tharanga15824664.2
19812010XJ DohertyAN Cook17229358.7
19942011HMRKB HerathIJL Trott15226457.6
18102006N BojeDPMD Jayawardene22139056.7
15722001M MuralitharanBC Lara24043854.8
19732010NM HauritzSR Tendulkar16831154.0
19772010S RandivCH Gayle15429053.1
17432005A KumbleYounis Khan20840251.7
16962004GJ BattyBC Lara16131251.6
17992006Mohammad RafiqueJN Gillespie15029151.5
19522010A MishraHM Amla18736651.1
16412003HDPK DharmasenaSP Fleming16933650.3
16782003A KumbleRT Ponting17334450.3

Tharanga faced 64.2% of the balls bowled by Mohammad Rafique at Shaheed Chandu Stadium, Bogra in 2006. Cook, while scoring 67 and 235 at the Gabba, Brisbane in 2010, faced 58.7% of the balls bowled by Doherty. In his historic double effort, Lara faced 54.8% of the balls bowled by Muralitharan. A very significant entry is to be found later. Jason Gillespie against Mohammad Rafique. Not Gillespie the bowler, but Gillespie the batsman. Gillespie, confirming his position as the best late-order batsman ever, during his farewell innings of 200*, faced 150 of the 291 balls bowled by Rafique in Chittagong in 2006.

At some suitable time in future, depending on when I would be doing the series wrap-up of Pakistan-South Africa, I will do an analysis, similar in intent, but totally different in methodology, of the first 1545 Tests for which ball-by-ball data is not available.

After sending this article for publication, the news of the little maestro's retirement broke. I salute one of the greatest cricketers who ever took the field from the bottom of the heart. Tendulkar was a true gentleman, on and off the field, and was a role model extraordinaire. I will come out with a two-part analytical tribute to the extraordinary cricketer on whose shoulders the word "great" sits very lightly, starting November 24.

One of the best cricket news recently has been Afghanistan's qualification to the 2015 World Cup. They are a much-loved team and possibly the best-supported among the Associates. I love both the Ireland and Afghanistan teams and would be quite happy to see both these charismatic teams make it to the second round. Add to this mix, Netherlands (why cannot they persuade Ryan ten Doeschate to play for them since there will be no T20 bash scheduled at that time) and Scotland (UAE is a team with 11 expatriates - not my cup of tea), the tournament will be colourful.

I have created a document file containing all the qualifying performances. There are 242 Innings-level selections and 61 Test-level combinations. To download/view this document, please CLICK HERE.

Full post
Tripping up at the home stretch

A look at ODIs lost from the brink of victory

This is a follow-up article to the previous one in which I had introduced a new concept of measuring the status of ODI matches using the resources available for the team. In the first article, I had looked at the wins by second batting teams, from perilous situations. In this article I will look at losses by teams batting second, from seemingly impregnable positions.

First, let me present the revised table of wicket resources. As suggested by Anshu Jain, I split the innings into first and second and determined the wicket resources. Since there seems to be a significant variation between the resources utilised at the fall of most wickets, exceptions being 3rd and 4th wickets, I will use the appropriate innings related wicket resource values in all further work.

Resource percentages
WicketAllInns******FirstInns******SecondInns******
ResUtilizedResAvlblResUtilizedResAvlblResUtilizedResAvlbl
1 16.72%83.28% 14.67%85.33% 18.81%81.19%
2 30.86%69.14% 29.57%70.43% 32.26%67.74%
3 45.34%54.66% 44.82%55.18% 45.95%54.05%
4 57.96%42.04% 58.69%41.31% 57.04%42.96%
5 68.83%31.17% 70.42%29.58% 66.66%33.34%
6 77.39%22.61% 79.25%20.75% 74.78%25.22%
7 84.37%15.63% 85.89%14.11% 82.28%17.72%
8 90.15% 9.85% 91.18% 8.82% 88.88%11.12%
9 95.33% 4.67% 95.72% 4.28% 94.92% 5.08%
10100.00% 0.00%100.00% 0.00%100.00% 0.00%

This part of the second-innings analysis is quite tricky and far more complex than the more straight-forward chasing wins analysis. Earlier I was looking for the worst situations. As such it was easy to look at the fall of the wicket and determine the TRF-W (Target Resources Factor-Wickets). Compare this with TRF-B (Target Resources Factor-Balls) and select the higher one which would indicate the more critical of the two resource situations. When the team wins from such difficult situations it was easy to gauge the quality of win correctly.

This is a different ball game. Wickets are fine and the wicket resources are determined similarly. Except for a minor but very important tweak. Let us say that the first wicket fell at 120, chasing 250. The wicket resources will be calculated at 120 for 0, not 120 for 1. This means we have to consider the situation before the ball was bowled, not after. The reason is obvious. 120 for 0 is better situation than 120 for 1 and since the team has plummeted into a loss, we have to take as the base the better situation, unlike in the last analysis wherein we looked at the worse situation. This is relatively easy to understand.

Here comes the tougher part. There is no way for me to ignore the balls resource available. If I tell you that a team is at 150 for 1, chasing 250, the sentence does not convey anything. One cannot venture a comment on the team situation without knowing the balls available information. While chasing 250, 150 for 1 in 25 overs is a 95% winning situation, 150 for 1 in 35 overs is a 65% winning situation, 150 for 1 in 40 overs is a 35% winning situation and 150 for 1 in 45 overs is a 5% winning situation. So the balls available data is a must.

So much so, I am forced to exclude the 650 or so chasing wins for which balls-at-wicket-fall data is not available. I tried doing this based on assumptions on scoring rates but the results were skewed because of the dynamics between the two types of resources. When I used the scoring rate at the fall of wicket, many matches were included and I am not sure which match situation is good or worse. I do not want to say that the team lost a certain win from 150 for 1 for someone to say that I am a fool since they had only 7 overs to score 100 runs. So let us leave it at that.

Now comes the other tricky part. The scoring rate at the wicket-fall stage cannot be really taken as the scoring rate for the later part of the innings. If a team is 150 for 1 in 35 over, chasing 250, I cannot really take the actual scoring rate of 4.2 and conclude that the required rate of 6.3 is 50% harder. With nine wickets in hand, this is really a cakewalk. On the other hand, if the score at the same stage had been 150 for 4, the win is not that straight-forward. So the number of wickets in hand plays a part in getting a handle on this scoring rate which can be achieved. I have adopted the following rates. Not necessarily arbitrary since some logic has gone into it. I did not want to over-complicate at this stage of analysis to do an actual scoring rate achieved. Over thousands of matches the scoring rates for the rest of the innings, at the fall of early wickets, is likely to be in a narrow band of 4.5 to 5.0 and that does not help. I have left that for a later improvement, if feasible. I have ranged this between 7.0, which I feel is the highest achievable scoring rate over a number of overs, and 5.0. In addition, these expected rates are incremented by 10% if fewer than ten overs remain. Changing 7.0 to 7.7 will not cause much of a change. Anything above is infeasible.

Wkts-in-hand   Exp-S/R
10 7.0 9 6.7 8 6.4 7 6.15 6 5.9 5 5.7 4 5.5 3 5.3 2 5.15 1 5.0

Let me now summarise the calculations.

1. Determine the wickets-resource left by looking at the number of wickets lost, just before the ball is bowled. Divide the target factor (Runs left/Target runs) by this value to arrive at the TRF-W.
2. Determine the Expected SR by looking at the above table, again just before the ball is bowled.
3. Determine the Actual SR required by dividing the number of runs by number of balls left.
4. Determine the TRF-B as the ratio between the above two scoring rates (Actual/Expected). This will have a low value (easy task) when fewer wickets have fallen and the scoring rate required is not high. It will have a high value when more wickets have fallen and the scoring rate has climbed up.
5. Determine the TRF-S (Target Resources Factor-Situation) as equivalent to 0.66667*TRF-W + 0.33333*TRF-B. Wickets are far more important to retain and this fact is recognized in this equation. These are not golden numbers. These are just weights and are driven by common-sense. I tried 0.5 and 0.5 and was not happy with quite a few of the situations. A choice of 0.75 and 0.25 lowered the impact of the Balls resource too much.
6. Select situations in which the TRF-S value is lower than 0.50. This is a very happy situation to be in. And let us not forget that the team proceeded to lose from this invincible position.

I will explain this with a few clear examples.

Let us say that a team is chasing 249. The target is 250. The score before the fall of the second wicket is 150 for 1. The Wkt-resource in front is 81.19%. The target in front is 40.0% (100/250). So the TRF-W value is 0.493 (40.00/81.19).

Now let me take two scenarios. The score of 150 for 1 has been reached in 25 overs. The Expected -RpO is 6.7 (from the table). The required RpO is 4.0 (100/25). The TRF-B value is 0.597 (4.0/6.7). The final TRF-S value is 0.66667*0.493 + 0.33333 *0.597. This works to 0.527. An excellent situation to be in. This match would just miss selection for this analysis, if the team lost.

Now let me say that the score of 150 for 1 was reached in 35 overs. The Expected-RpO remains at 6.7. The required RpO is 6.6667 (100/15). The TRF-B value is 0.995 (6.6667/6.7). The final TRF-S value is 0.66667*0.493 + 0.33333*0.995. This works to 0.660. Still a good situation to be in.

Finally let us say that the openers have dawdled and the score of 150 for 1 was reached in 41 overs. The situation changes drastically. The Exp-RpO changes to 7.37 (6.7 * 1.1). The required RpO is 11.111 (100/9). The TRF-B value is 1.507 (11.111/6.37). The final TRF-S value is 0.66667*0.493 + 0.33333*1.507. This works to 0.830. A reasonable situation only because of the 9 wickets in hand.

Change the situation to 150 for 4 in 40 overs. The TRF-W is 0.931(40.00/42.96). The TRF-B comes to 1.695(10.00/5.9). The weighted TRF-S is 1.186. The balance has clearly shifted to the fielding side. Note how delicately the whole situation is balanced and the interplay of the various factors.

Let me take a breath now.

Out of the 2100 or so matches considered, and the 1056 defending wins/ties therein, 21 matches qualify under these conditions. This time I have not gone on the TRF-S value to feature matches. I have featured the matches which had more than one such situation in the match. In other words, the losing team let go more than one opportunity. Makes these losses special, so to speak. I could get seven such matches. I have selected three more matches from the list of 21; matches that caught my eye. It can be seen that most of the matches have been lost by small margins. It seems logical. A team at 107 for no loss, chasing 209, is unlikely to lose by 50 runs.

Let me now present the table of 21 selected matches. The table is self-explanatory. The downloadable table is complete and presents all the multiple situations in the matches.

ODI matches lost from certain win situations
Match IdScoreWkt-Res %T1-ScoreT2-ScoreTarget-%TRF-WEquationReq-RpOExp-RpOTRF-BTRF-S
Featured
3080188/8 11.1%190/10189/10 1.6%0.141 3 in 460.395.660.0690.117
2600192/3 54.0%210/ 8209/ 6 9.0%0.167 19 in 284.076.770.6020.312
3120164/8 11.1%171/10165/10 4.7%0.418 8 in 172.825.660.4980.445
1450249/8 11.1%252/ 9249/10 1.6%0.142 4 in 73.435.660.6050.297
2642199/4 43.0%233/ 9219/1015.0%0.348 35 in 573.686.490.5680.421
2269196/9 5.1%198/10196/10 1.5%0.297 3 in 111.645.500.2980.297
2734271/4 43.0%282/ 8281/ 6 4.2%0.099 12 in 164.506.490.6930.297
2243281/6 25.2%284/ 6283/10 1.4%0.056 4 in 64.006.050.6610.257
1344272/4 43.0%307/ 6301/1011.7%0.272 36 in 395.546.490.8530.466
1514196/8 11.1%196/10196/10 0.5%0.046 1 in 61.005.660.1770.089
Included
1283221/5 33.3%241/ 9235/10 8.7%0.260 21 in 255.046.270.8040.441
1294125/0100.0%228/ 7227/ 945.4%0.454104 in 1703.677.000.5240.478
1405198/4 43.0%232/ 8222/1015.0%0.350 35 in 464.576.490.7030.468
1722196/3 54.0%242/ 8240/1019.3%0.358 47 in 594.786.770.7070.474
1941216/6 25.2%229/ 7224/10 6.1%0.241 14 in 174.946.050.8170.433
2520235/5 33.3%257/ 8252/ 9 8.9%0.267 23 in 265.316.270.8470.460
2535203/5 33.3%221/ 9221/10 8.6%0.257 19 in 383.006.270.4780.331
2682301/3 54.0%340/ 6340/ 711.7%0.217 40 in 386.326.770.9340.456
2826212/3 54.0%270/ 7244/ 714.2%0.262 35 in 346.186.770.9130.479
3135222/6 25.2%243/10225/10 9.0%0.358 22 in 522.546.050.4200.378
3215155/3 54.0%200/10174/1022.9%0.423 46 in 733.786.150.6150.487

Let us now see the featured matches now. The sequence is rather arbitrary. In general I have shown the matches where the teams lost despite many chances first.

1. ODI # 3080. South Africa vs. India.
Played on 15 January 2011 at New Wanderers Stadium, Johannesburg.
India won by 1 run. Mom: Munaf Patel
India: 190 all out in 47.2 overs
   Yuvraj Singh        53 ( 68)
South Africa: 189 all out in 43.0 overs
   GC Smith            77 ( 98)
   MM Patel            8.0  0  29  4
This is arguably amongst the most astonishing matches ever played. The more I see what happened in the match, the more I feel like I have been caught in the eye of a typhoon, going round and round. India, batting first, at the Wanderers, reached a very ordinary total of 190. South African, despite losing the first wicket early, were coasting. Starting at 152/4 (the fifth wicket falling at 25.2), South Africa were looking almost certain winners at 160/5, 163/6, 177/7, 188/8 and 189/9. On each of these situations their TRF-S was well below 0.50. Surprisingly the best situations were at 188/8 (0.117) and 189/9 (0.155). But they lost the match by 1 run. How? It is a question they might still be trying to find an answer for. A combination of panic, good bowling by Munaf Patel and good fielding contributed to the disaster.
2. ODI # 2600. Ireland vs. Netherlands.
Played on 11 July 2007 at Civil Service Cricket Club, Stormont, Belfast.
Ireland won by 1 run. Mom: Kevin O'Brien 
Ireland: 210 for 8 wkt(s) in 50.0 overs
   EJG Morgan          51 (112)
   D Langford-Smith    31*( 13)
Netherlands: 209 for 6 wkt(s) in 50.0 overs
   Mudassar Bukhari    71 (114)
This was an equally amazing match played between two talented Associate teams. Ireland scored a moderate 210 for 8. Netherlands looked certain to win when they were 138/1, 159/2, 192/3 (0.312) and 192/4. They lost a wicket at each of these situations and were finally at 198 for 5 (0.419), needing 13 to win in 14 balls. They managed to fall couple of runs short. The scores of the later four batsmen, 15 in 24, 10 in 15, 2 in 5 and 5 in 7, tell the complete story.
3. ODI # 3120. England vs. South Africa.
Played on 6 March 2011 at MA Chidambaram Stadium, Chepauk, Chennai.
England won by 6 runs. Mom: Bopara R.S.
England: 171 all out in 45.4 overs
   IJL Trott           52 ( 94)
   RS Bopara           60 ( 98)
South Africa: 165 all out in 47.4 overs
   HM Amla             42 ( 51)
   SCJ Broad           6.4  0  15  4
This match is fresh in everyone's memory. World Cup 2011, and the unfancied England played the eternal bridesmaids, South Africa. This time the South Africans had it all figured out. England could not make head or tail of Imran Tahir and Robin Peterson and were dismissed for 171. At 124/3, 160/7 and 164/8(0.445), South Africa looked very clear favourites to win. Although the numbers may not reveal this, they needed 48 in 108 balls with seven wickets at the first-mentioned situation. That was their best chance. But they let go of all these chances and were finally dismissed for 165, six runs short. Stuart Broad was unplayable at the end. But the real culprit was Peterson who scored 3 in 16 balls.
4. ODI # 1450. India vs. Zimbabwe.
Played on 19 May 1999 at Grace Road, Leicester.
Zimbabwe won by 3 runs. Mom: Grant Flower
Zimbabwe: 252 for 9 wkt(s) in 50.0 overs
   A Flower            68*( 85)
India: 249 all out in 45.0 overs
   S Ramesh            55 ( 77)
   HH Streak           9.0  0  36  3
   HK Olonga           4.0  0  22  3
This match was during the 1999 World Cup. Zimbabwe posted a very competitive total of 252. This was not like the earlier referred matches in which the losing team had established their ascendancy early in the innings. India struggled at the start and was behind the game at 103 for 5. Then they recovered and reached recovered and were very comfortably placed at 246 for 7, requiring only 7 runs in 10 balls with three wickets left. Then Henry Olonga struck. Even then, at 249 for 8 (0.297) and 249 for 9, they were well placed to win. But then fell 3 runs short. This was an amazing result considering the difference in strength between the two teams.
5. ODI # 2642. Pakistan vs. South Africa.
Played on 29 October 2007 at Gaddafi Stadium, Lahore.
South Africa won by 14 runs. Mom: Makhya Ntini
South Africa: 233 for 9 wkt(s) in 50.0 overs
   HH Gibbs            54 ( 61)
   JH Kallis           86 (130)
Pakistan: 219 all out in 46.3 overs
   Younis Khan         58 ( 65)
   Mohammad Yousuf     53 ( 88)
   M Ntini             9.0  0  61  4
   JA Morkel           8.3  0  44  4
South Africa set Pakistan a fair target of 234. They were well ahead of the game at 199 for 4 (0.421), requiring 35 in 57. Then the score became 209 for 5 and then 219 for 7. Even then 15 in 24 looked easy. At this point Albie Morkel captured three wickets in four balls and sent Pakistan crashing to a 14-run defeat. That too, at home.
6. ODI # 2269. Africa XI vs. Asia XI.
Played on 17 August 2005 at SuperSport Park, Centurion.
Africa XI won by 2 runs. Mom: Ashwell Prince
Africa XI: 198 all out in 44.3 overs
   AG Prince           78*(113)
Asia XI: 196 all out in 48.1 overs
   Abdul Razzaq        38 ( 77)
   SM Pollock         10.0  1  32  3
   JH Kallis          10.0  2  42  3
This time it is an Africa XI. Another low score of 198 against the motley collection of players known as Asia XI. Chasing 199, Asia XI lost wickets regularly and were down in the dumps at 59 for 4 and 96 for 7. Then they recovered and were at 193 for 8, requiring 6 in 16. Soon they lost the ninth wicket and were 196 for 9 (0.297), needing only 3 runs. But fell 2 runs short.
7. ODI # 2734. West Indies vs. Australia.
Played on 4 July 2008 at Warner Park, Basseterre, St Kitts.
Australia won by 1 run. Mom: Andrew Symonds
Australia: 282 for 8 wkt(s) in 50.0 overs
   A Symonds           87 ( 78)
   DJ Hussey           50 ( 51)
West Indies: 281 for 6 wkt(s) in 50.0 overs
   CH Gayle            92 ( 92)
   RR Sarwan           63 ( 79)
   S Chanderpaul       53 ( 71)
   B Lee              10.0  0  64  3
For a change this was a close result in a big-scoring match. Australia scored a very competitive total of 282 for 8. At 138 for 1 and 188 for 2 West Indies were quite comfortably ahead. Even when the score was 247 for 3, the situation was very good. However the best situation was at 271 for 4, West Indies requiring only 12 in 16 balls. They were very well placed at a TRF-S value of 0.297. But West Indies floundered inexplicably and scored only 10 runs in the next 12 balls. They ended just a run short.
8. ODI # 2243. West Indies vs. South Africa.
Played on 11 May 2005 at Kensington Oval, Bridgetown, Barbados.
South Africa won by 1 run. Mom: Charl Langeveldt 
South Africa: 284 for 6 wkt(s) in 50.0 overs
   HH Dippenaar       123 (129)
   JH Kallis           87 (109)
West Indies: 283 all out in 49.5 overs
   CH Gayle           132 (152)
   A Nel              10.0  0  42  3
   CK Langeveldt       9.5  0  62  5
This was a most extraordinary match, won by a single bowler, like Albie Morkel did against Pakistan. How often have South Africa figured in these matches on the other side of the fence? South Africa put up a most impressive total of 283. Aided by a top-class century from Chris Gayle, but still losing wickets steadily, West Indies were 281 for 6 (0.257) requiring just 4 runs for a win. Then they were 283 for 6, requiring only two runs. Charl Langeveldt produced, arguably, the best last over in ODI history and claimed a hat-trick, letting the South Africans win by 1 run. A hat-trick was badly needed and he produced it.
9. ODI # 1344. Sri Lanka vs. India.
Played on 7 July 1998 at R. Premadasa Stadium, Colombo.
India won by 6 runs. Mom: Sachin Tendulkar
India: 307 for 6 wkt(s) in 50.0 overs
   SC Ganguly         109 (136)
   SR Tendulkar       128 (131)
   A Jadeja            25 ( 15)
Sri Lanka: 301 all out in 49.3 overs
   PA de Silva        105 ( 94)
   AB Agarkar         10.0  0  53  4
This is the only featured match that produced two scores of over 300 runs. Helped by two centuries at the top, India scored 307 and looked comfortable winners. But Sri Lanka never gave up. Their best position was 272 for 4 (0.466). They needed only 36 in 39 balls. Reasonably comfortable position. However they started losing wickets regularly and fell 6 runs short. The last 5 batsmen scored 12 runs in 25 balls, a woeful effort indeed.

This match is very similar to ODI 2932, in which the mammoth Indian total of 414 was almost chased down by Sri Lanka, who fell 3 runs short. The only reason it does not get into this list is because at 401 for 6, chasing 414, the balls situation, 14 in 10, was not that favourable to Sri Lanka. And it proved difficult. They could not make those runs.

10. ODI # 1514. Pakistan vs. Sri Lanka.
Played on 15 October 1999 at Sharjah C.A. Stadium.
Match tied. Mom: Abdul Razzaq.
Pakistan: 196 all out in 49.4 overs
   Mohammad Yousuf     48 ( 90)
Sri Lanka: 196 all out in 49.1 overs
   RS Kaluwitharana    75 (108)
   RP Arnold           61 ( 93)
   Wasim Akram        10.0  1  38  3
   Abdul Razzaq        9.1  2  31  5
This is the only tied match featured here. Pakistan were dismissed for 196. Chasing the relatively modest target of 197, Sri Lanka looked certain winners at various positions such as 157/1, 173/3, 174/3, 177/4, 186/5, 186/6, 194/7 and finally 196/8. The TRF-R values were way under 0.500 in all these situations. Interestingly the best situation was at 196 for 8 (0.089) since the scores were level and 1 run was needed. However, they lost both wickets and the match was tied. The batsmen at positions 4-11 scored 25 runs in 71 balls. These included Aravinda de Silva, Sanath Jayasuriya, Mahela Jayawardene and Chamara Silva, all recognised batsmen.

I have created a document file with details of all matches in which the TRF-S values were below 0.50. This includes multiple occurrences within the same match. To download/view the document, please CLICK HERE.

Full post
Great ODI recoveries

A look at the top successful ODI chases achieved from positions of no hope

ODI wins achieved from the brink of disaster

The year 2012: Still fresh in the memory of many a football follower. Arsenal, yes, we are talking about the "team", played Reading FC. Arsene Wenger showed his disdain for this lesser cup by selecting a team with many second XI players. Reading were all over Arsenal and were 4-0 up in 37 minutes. An Arsenal win was as unlikely as an Indian win over Brazil in football. Theo Walcott reduced the deficit by half time. Then the recovery started. Arsenal made it 4-2, but only a minute of play remained. Two goals were scored in the last minute to restore parity at 4-4. In the extra time, the floodgates opened. Arsenal scored three goals and Reading once, for the match to finish 7-5. Wenger could smile once again.

Move back 55 years to 1957. Charlton FC is 1-5 down with 26 minutes remaining. Half the stadium has left the ground. Then Johnny Summers scored four goals in 17 minutes and John Ryan followed up with two more goals to more than compensate the additional Huddersfield goal. The match ended in a 7-6 win for Charlton, the greatest comeback in recorded football history and the narrowest win in English football history. In a frenetic second half, ten goals were scored.

A sunny Sunday during July 1999. Paul Lawrie started the last round of the British Open, ten strokes behind the leader, Jean Van de Velde. How does one explain this to the non-golf persona? Let me say it is the equivalent of a four-goal deficit at half time or a 300-run deficit at the end of the first innings. Lawrie had a terrific round of 67, Van de Velde had a monstrous meltdown and the regulation 18 holes ended in a tie between Lawrie, Van de Velde and Justin Leonard. It was poetic justice that Lawrie won the claret jug, winning the play-off. He completed the biggest comeback in major championship and PGA Tour history by coming back from ten strokes behind in the final round.

Finally let us use the time machine to roll a few years forward. Sunny Melbourne, January 2002. Australian Open Final between Jennifer Capriati, seeded No. 1 and Martina Hingis, seeded at No. 3. This had been a tournament of upsets, the top four men's seeds not lasting beyond second round. Twenty-four hours later the unfancied 16th seed, Thomas Johansson would win the men's singles. Hingis won the first set comfortably and broke Capriati twice to lead 4-0. Capriati fought back and took the final to a tie-breaker. Hingis led 6-2 and now had four championship points. Capriati saved them all, and went on to win the second set. She was broken by Hingis but then won five straight games to win an extraordinary match. This is the only time a Grand Slam title had been won after saving four match points.

This preamble would have given readers an idea about the theme of this article. I will be looking at ODI matches in which teams were so far behind that some of the betting companies stopped taking bets and half the stadia emptied. Then they slowly clawed their way back and won the match. I look at the top ten recoveries in depth in this article and provide a potted summary of a few other recoveries.

Although this is seemingly an anecdotal article, I will not do my usual selection of matches based on my memory, knowledge aided by visual inspection of the scorecards and some analysis. This is going to be 100% objective and analytical and based on new measures developed for this type of analysis. So readers can rest be assured that no match will be left out.

For reasons briefly explained in this paragraph, I will only look at the second innings and chasing wins. The first innings is difficult to define in view of the absence of a clear target. The target in front of the first batting team is a notional one which varies from period to period and place to place. A 250, which was an excellent score during 1980 at Headingley, would seem wholly insufficient during 2010 in Faisalabad. Not just the arbitrary nature of the target, but it would be difficult to get a correct handle on the situation in the first innings.

Let us say a team is 50 for 4, batting first. Way below the requirement to reach 250, the notional target. Let us say this team reaches 150 and then dismisses the opponents for 120 winning the match. This clearly indicates an awful pitch. So the 50 for 4 is far better than it looks. Taking the other side, let us say a team is 100 for 1. No doubt an excellent situation; they reach 300 and the other team chases down this score in 40 overs for the loss of two only wickets. The 100 for 1, which was seemingly a very good position, was rather inadequate. Hence the first innings is excluded in all matches. At a later date I might find a way to solve all these complex situations.

So I will consider only successful chases. Even there, we have a huge population of 1691 innings. As I have already mentioned, I am going 100% analytical and objective. How do I do this?

At any point in the game, in the second innings, there is a clear target in front of the chasing team. The innings has 11 clear markers in the form of innings beginning and loss of each successive wicket. It is clear that the situation is at a defining point at the fall of a wicket and keeps on improving until the next wicket falls. There are two types of resources available. Wickets and balls. The wicket-related data is available for all the 3400+ matches. However, balls available for the team is available only for the recent 1600 matches. However, I am able to bring that factor into the equation because the limiting resource is the one which is lower.

The wickets resource is the more important one since my calculations prove that at no time in the later part of the innings does the balls remaining become the limiting resource. I am going to compare the target in front of the team and the wicket resource available using two metrics - Target Resources Factor-Wickets (TRF-W) and Target Resources Factor-Balls (TRF-B) - to get a handle of the situation. I compare this with the ratio between the target in front and balls available just to complete the analysis. Just to give an example of the importance of TRF-W. For the TRF-B value to be above 3.00, a scenario like the following needs to be there. The batting team needs to score 36 runs in 12 balls and achieve that win. To locate such instances we need ball-by-ball data, which is some time away.

Wicket resource! Easier said than done. Each wicket carries a different value. The first wicket carries a high value and the last wicket, a fairly low value. To associate correct values for each wicket, I have determined the resource utilised percentage value at the fall of each wicket in every match played, compiled and averaged the same and got a set of values across 3410 matches. The final values seem very sound since there are over 6800 innings to work with. The values are given below. These values are somewhat similar to the D/L table values. However, I suggest that readers should not compare these with the D/L values. The learned academic duo has their methods and I have mine. They are fixing target scores. I am analysing target scores. This table is going to be a very useful one for many future analyses.

Wkt  Res-Utl%  Res-Avl%

1. 17.53% 82.47% 2. 30.87% 69.13% 3. 45.36% 54.64% 4. 57.97% 42.03% 5. 68.84% 31.16% 6. 77.39% 22.61% 7. 84.37% 15.63% 8. 90.16% 9.84% 9. 95.33% 4.67% 10. 100.00% 0.00%
The target in front is determined through a linear function, as also the balls available resource. Since there have been over a hundred rule changes in the 40-plus years of ODI existence, there is no point trying to incorporate these rule changes into either target or balls working. The linear mappings are simple and effective. These three values are determined at the fall of each wicket and a ratio arrived at by dividing the task in front by the resource available. This ratio is 1.00 at the beginning of the innings and becomes 0.00 at the fall of the last wicket. None of the matches that we have considered will reach this stage since we are only looking at chasing wins. A ratio above 1.00 indicates a tough task and a ratio below 1.00 is an easier task. Let me explain this through a few examples.

Target Score-at-FoW Target-% BallsRes% TRF-B  WktRes-%  TRF-W

200 20/2( 60) 90.0 80.0 1.12 69.13 1.30* 200 50/0( 60) 75.0 80.0 0.94* 100.00 0.75 200 100/5(150) 50.0 50.0 1.00 31.16 1.60* 300 40/1( 90) 86.7 70.0 1.23* 82.47 1.05 300 200/6(210) 33.3 30.0 1.11 22.61 1.47* 300 210/8(240) 30.0 20.0 1.50 9.84 3.04*
It is clear that situation 2 is favourable to the batting team and others not so good. The last one is quite a desperate one. If a team won from this situation, it would be quite creditable. In the second and fourth situations, the restricting factor is the balls resource. However it is very likely that the balls resource is likely to be a factor only in low wicket situations. It is almost certain that when more wickets are lost, the wickets lost would prove to be a much more critical factor than balls remaining. The factor values appended with * are the limiting values.

Out of the 3408 matches, there were 1663 wins by wickets and these teams went through well over 10000 wicket-fall situations. Out of these only ten situations were so desperate that the TRF was over 3.0. These are the matches featured here. There were 18 other matches which had situations between 2.5 and 3.0 and their potted scores are also provided. Please note that there might be more than one very tough situations (even TRF values exceeding 3.0) for one match. But the worst one in each match has been selected.

It should be noted that D/L matches are also covered here. In fact, there are two D/L matches in this lot of 29. Of course, there might have been multiple target changes within an innings, but that is not documented anywhere.

Finally let me emphasise that this is a pure scorecard-based analysis. No information beyond the scorecard is needed. Other contextual factors such as relative team strengths, batting and bowling strengths, quality of batsmen at the crease, importance of the match etc are not relevant to this analysis.

Javed Miandad, Lance Klusener, Brendan Taylor, Shivnarine Chanderpaul, Ed Rainsford and Ryan McLaren have won ODI matches with sixes off the last ball. It is possible that the TRF-B in these matches at the beginning of the last ball was as high as 6. But the purpose of this analysis is much more than identifying such instances.

First let us look at a table containing the details of ten matches.

List of matches in which the teams recovered from TRF situations of 2.5 and above
MatchIdFoW ScrBallsDLTgtMaxFB ScrSB ScrBlsFTRF-BTgtFWktFTRF-W
Featured
3065107/8152 240300239/8243/90.4931.1230.5540.0985.632
26203/9 0 267360266/7267/90.0000.0000.2400.0475.133
2499231/9262 285300284/4286/90.1271.4960.1890.0474.057
1028 74/7 0 173258172/9173/90.0000.0000.5720.1563.661
1976135/8226 205300204/8208/80.2471.3840.3410.0983.470
2922187/9269 222300221/9222/90.1031.5260.1580.0473.376
3323140/8193 209300208 ao209/90.3570.9260.3300.0983.355
2182147/8202 218300217 ao218/80.3270.9970.3260.0983.310
241 92/7 0 178300177/8180/90.0000.0000.4830.1563.091
2794 6/5 48 153300152 ao153/80.8401.1440.9610.3123.083
Included
2617114/7143 213300212 ao213/70.5230.8880.4650.1562.974
2632 64/6113 194300193 ao195/80.6231.0750.6700.2262.966
1799 82/6129 246300245/8248/80.5701.1700.6670.2262.951
2455178/9230DL206252223/8205/90.0871.5570.1360.0472.911
2797 44/6118 125300124 ao127/80.6071.0680.6480.2262.869
1537 71/6130 196294195 ao196/80.5581.1430.6380.2262.823
2403134/8228 185300184 ao185/80.2401.1490.2760.0982.802
83 61/6 0 164300163 ao164/80.0000.0000.6280.2262.780
679158/8 0 216300215 ao217/90.0000.0000.2690.0982.729
676152/9 0 174330173/8175/90.0000.0000.1260.0472.707
2375 89/7175DL154264157/9153/70.3371.2520.4220.1562.700
3358133/7222 230300229/9230/80.2601.6220.4220.1562.698
88 80/6 0 204300203/7207/90.0000.0000.6080.2262.691
3161 92/6134 226300225/8228/70.5531.0720.5930.2262.625
31 39/6 0 94360 93 ao 94/60.0000.0000.5850.2262.590
3127169/8238 226300225 ao227/80.2071.2200.2520.0982.563
2634 49/5 65 231300230 ao233/60.7831.0060.7880.3122.528
2265 95/6156 221300220/8221/60.4801.1880.5700.2262.524

There are ten matches which had TRF values exceeding 3.0 and these are featured here. A brief perusal of the scorecards will clearly reveal how tough the task for the chasing team was. Most of these situations have occurred at 7/8/9 wickets down and only one has been at the fall of the fifth wicket. The TRF-B values are also calculated and shown in this table. The table is self-explanatory. The potted scores for the other 18 matches are available in the downloadable document which is in text format and can be viewed by Notepad or similar editor.

The potted scores of the top ten matches, along with brief commentaries, are detailed below.

1. ODI # 3065. Australia vs Sri Lanka.
Played on 3 November 2010 at Melbourne Cricket Ground.
Sri Lanka won by 1 wicket. Mom: Matthews A.D.
Australia: 239 for 8 wkt(s) in 50.0 overs
   MEK Hussey          71*( 91)
   NLTC Perera         8.0  0  46  5
Sri Lanka: 243 for 9 wkt(s) in 44.2 overs
   AD Matthews          77*( 84)
   SL Malinga          56 ( 48)
   XJ Doherty         10.0  1  46  4
The match at the top of the list is of recent vintage and still fresh in everyone's memory. At MCG, Australia posted a very competitive total of 239 and reduced Sri Lanka to 107 for 8. Only 9.84% of resources are available and 55.4% of target runs are yet to be scored. This leads to a TRF of 5.632, the highest in ODI history, for winning teams. Angelo Mathews and Lasith Malinga got together and set up arguably the most exciting stand in all ODI cricket and added 132 runs. Then, with four runs to go, Malinga is run out. Muttiah Muralitharan came and swatted the second ball for four, taking Sri Lanka to the most unlikely win amongst 3400-plus ODI matches.
2. ODI # 26. Pakistan vs West Indies.
Played on 11 June 1975 at Edgbaston, Birmingham.
West Indies won by 1 wicket. Mom: Sarfraz Nawaz.
Pakistan: 266 for 7 wkt(s) in 60.0 overs
   Majid Khan          60 ( 90)
   Mushtaq Mohammad    55 ( 82)
   Wasim Raja          58 ( 87)
West Indies: 267 for 9 wkt(s) in 59.4 overs
   CH Lloyd            53 ( 76)
   DL Murray           61*( 95)
   Sarfraz Nawaz      12.0  1  44  4
The first World Cup in 1975. An important league match. Pakistan post an imposing total of 266. West Indies are devastated by Sarfraz Nawaz and slump to 89 for 5, 166 for 8 and finally, 203 for 9. The key factors are 24.8% of target runs to be scored and 4.67% of resources available, a very high TRF of 5.133. Also, nine wickets down, so no second chance like the first match. Deryck Murray and Andy Roberts put together, arguably, the best last-wicket partnership ever, of 64 runs, and West Indies script an unlikely win. They went on to win that World Cup, the next, and only their disdain of India prevented them from completing a hat-trick of World Cup wins.

This was one of the matches in which even the early situations such as 151 for 7 and 166 for 8 produced TRF values exceeding 2.75. But the worst situation was at the fall of the ninth wicket.

3. ODI # 2499. Kenya vs Ireland.
Played on 2 February 2007 at Ruaraka Sports Club Ground, Nairobi.
Kenya won by 1 wicket (with 6 balls remaining). Mom: Odoyo T.M.
Ireland: 284 for 4 wkt(s) in 50.0 overs
   WTS Porterfield    104*(131)
   KJ O'Brien         142 (123)
Kenya: 286 for 9 wkt(s) in 49.0 overs
   N Odhiambo          66 ( 82)
   TM Odoyo            61*( 36)
   AC Botha            9.0  0  42  4
   WK McCallan        10.0  2  36  4
Minnows they might be but Kenya and Ireland produced a cracker of match. Ireland, helped by two hundreds by William Porterfield and Kevin O'Brien, set Kenya a huge task of 285. Kenya lost wickets steadily and were at 231 for 9. The key numbers were 18.9% and 4.67%. The TRF was 4.057. Then Thomas Odoyo played a magnificent innings of 61 in 36 balls, supported by Hiren Varaiya, who faced ten balls. Kenya won by a wicket with an over to spare. The TRF based on balls was 1.496.
4. ODI # 1028. Australia vs West Indies.
Played on 1 January 1996 at Sydney Cricket Ground.
Australia won by 1 wicket. Mom: Reiffel P.R.
West Indies: 172 for 9 wkt(s) in 43.0 overs
   CL Hooper           93*( 96)
Australia: 173 for 9 wkt(s) in 43.0 overs
   MG Bevan            78*( 88)
   CEL Ambrose         9.0  3  20  3
New Year's day at the SCG. West Indies, tied down by Paul Reiffel and Shane Warne, managed to reach 172 for 9 in the allotted 43 overs. Curtly Ambrose ripped through the Australian top order and they were soon struggling at 74 for 7. The TRF worked out to 3.661, with the constituent values being 57.2% and 15.63%. Michael Bevan then played one of the best finishing innings ever. He added 83 with Reiffel and nursed Warne and Glenn McGrath to take Australia to a win with nothing but a wicket to spare. Australia were 169 for 9 with a ball to go and Bevan smashed a four through long-on. Truly, a memorable finish.
5. ODI # 1976. Australia vs England.
Played on 2 March 2003 at St George's Park, Port Elizabeth.
Australia won by 2 wickets. Mom: Bichel A.J.
England: 204 for 8 wkt(s) in 50.0 overs
   AJ Stewart          46 ( 92)
   AJ Bichel          10.0  0  20  7
Australia: 208 for 8 wkt(s) in 49.4 overs
   MG Bevan            74*(126)
   AR Caddick          9.0  2  35  4
World Cup 2003 played at South Africa. Andy Bichel, producing one of two greatest spells of fast bowling in a World Cup (who can forget Gary Gilmour's 6 for 14 in 1975), limited England to 204 for 8. The Australian batsmen failed to Andy Caddick and Ashley Giles and were floundering at 135 for 8. That man, Bevan, steady at one end, was joined by the bowler of the World Cup: Andy Bichel. The TRF was 3.470 (34.1% and 9.84%). Bevan and Bichel finished off the job on hand themselves, reaching 208 for 8, winning by two wickets. McGrath's debatable batting skills were not needed.
6. ODI # 2922. Bangladesh vs Zimbabwe.
Played on 5 November 2009 at Zohur Ahmed Chowdhury Stadium, Chittagong.
Bangladesh won by 1 wicket. Mom: Naeem Islam.
Zimbabwe: 221 for 9 wkt(s) in 50.0 overs
   BRM Taylor         118*(125)
Bangladesh: 222 for 9 wkt(s) in 49.0 overs
   Naeem Islam         73*( 90)
Again, two unfancied teams. Brendan Taylor, with an excellent hundred, helped Zimbabwe reach a modest 221 for 9. Bangladesh, with some atrocious running between the wickets, were looking down the barrel at 187 for 9. The TRF was 3.376 (15.8% & 4.67%). Naeem Islam was already batting well at 40. He farmed the strike beautifully, allowing Nazmul Hossain to face only four balls and took Bangladesh to a one-wicket win, with an over to spare.
7. ODI # 3323. South Africa vs New Zealand.
Played on 19 January 2013 at Boland Park, Paarl.
New Zealand won by 1 wicket. Mom: Franklin J.E.C.
South Africa: 208 all out in 46.2 overs
   F du Plessis        57 ( 72)
New Zealand: 209 for 9 wkt(s) in 45.4 overs
   JEC Franklin        47*( 61)
   R McLaren           8.4  0  46  4
We finally come to 2013. South Africa are dismissed for 208 through a wonderful bowling performance by Mitchell McClenaghan. But New Zealand could not face Lonwabo Tsotsobe and Ryan McLaren. They were at 140 for 8, which produced the highest TRF of 3.355 (33.0% and 9.84%). The situation at 105 for 7 was only slightly better. James Franklin and Kyle Mills added 47 and paved the way. Still, the ninth wicket fell at 187. Franklin scored all the 22 runs for the last wicket and garnered an excellent one-wicket win.
8. ODI # 2182. England vs West Indies.
Played on 25 September 2004 at The Brit Oval, London.
West Indies won by 2 wickets. Mom: Bradshaw I.D.R.
England: 217 all out in 49.4 overs
   ME Trescothick     104 (124)
West Indies: 218 for 8 wkt(s) in 48.5 overs
   S Chanderpaul       47 ( 66)
   A Flintoff         10.0  0  38  3
England reached an average total of 217, aided by a hundred from Marcus Trescothick. The English bowlers struck regularly and reached 147 for 8. This produced a TRF of 3.310 (32.6% & 9.84%). The unlikely pair of Courtney Browne and Ian Bradshaw got together and scripted an unlikely win for West Indies, adding 71 priceless runs.
9. ODI # 241. Pakistan vs West Indies.
Played on 28 January 1984 at Adelaide Oval.
West Indies won by 1 wicket. Mom: Marshall M.D.
Pakistan: 177 for 8 wkt(s) in 50.0 overs
   Wasim Raja          46 ( 40)
West Indies: 180 for 9 wkt(s) in 49.1 overs
   MD Marshall         56*( 84)
   Wasim Raja         10.0  1  33  3
   Abdul Qadir        10.0  1  34  3
Pakistan and West Indies produced another thriller. Pakistan reached a below-par total of 177. West Indies were up the creek without a paddle at 72 for 7. The TRF was 3.091 (48.3% and 15.63%). Malcolm Marshall donned the unlikely role of a batting saviour and added the remaining 88 runs in partnerships with Eldine Baptiste, Michael Holding and Wayne Daniel.
10. ODI # 2794. Bangladesh vs Sri Lanka.
Played on 16 January 2009 at Shere Bangla National Stadium, Mirpur.
Sri Lanka won by 2 wickets. Mom: Sangakkara K.C.
Bangladesh: 152 all out in 49.4 overs
   Raqibul Hasan       43*(107)
Sri Lanka: 153 for 8 wkt(s) in 48.1 overs
   KC Sangakkara       59 (133)
   M Muralitharan      33*( 16)
   Nazmul Hossain     10.0  3  30  3
The last in this lot of featured matches, producing TRF values above 3.0, was played recently in Bangladesh. Bangladesh reached a poor total of 152. It looked like a cakewalk for Sri Lanka. They had reckoned without Nazmul Hossain and Shakib Al Hasan. The first five batsmen scored 2, 0, 0, 1 and 1. The score was 6 for 5 leading to a TRF of 3.091 (96.1% and 31.16%). Then Kumar Sangakkara steadied the innings with Jehan Mubarak. Both of them got out and the score became 114 for 8. The TRF was quite high even now but not as bad as 6 for 5. Then Murali took over. With an unconventional innings of 33 in 16 balls, he saw Sri Lanka through. This is the only instance of a TRF value exceeding 3.0, with the loss of only five wickets.

I have created a document file with details of all matches in which the TRF values exceeded 2.5. This includes multiple occurrences within the same match. This document also includes the potted scores of the 18 matches which contained TRF values between 2.5 and 3.00. To download/view the document, please CLICK HERE.

While I was working on this article I realised that this analysis has a lot of implications for evaluation of live matches. I hope no broadcaster picks up the idea from here without giving me credit! Let me give a few examples from recent matches.

1. Ireland: 269. England: 48 for 4. The TRF-W was 1.95 (82.22/42.03). England won from this position. But they would not have made it to a list of top 50 matches.
2. Australia: 315. England: 103 for 5. The TRF-W was 2.14 (66.77/31.16). But they did not win.
3. Australia: 315. England: 169 for 8. The TRF-W was 4.72 (46.52/9.84). But they did not win.

So this is only a theoretical exercise at the end of the match if the chasing team did not win. But it indicates the difficulty of the task ahead of the teams and has a lot of relevance during a match. It also puts in perspective what the teams featured here achieved.

Full post
Ashes 2013: battles within the war

Head-to-head stats for England v Australia 2013 using ball-by-ball data

This is the first attempt at a new type of analysis. I have done an analysis of the head-to-head confrontations during a specific series: the 2013 Ashes, to start with. Since this is a venture into uncharted seas, we will improve as we go along. I will make this a regular practice before important series, the ones coming to my mind now are the Ashes series in Australia later this year and the South Africa - India series around the same time.

There are no preambles to this analysis. There are no cut-offs and every single ball bowled is covered. The uploaded Excel sheet covers every single combination. In the main article I have selected four bowlers and six batsmen from each team and developed the tables. Otherwise the article will become too long.

The players selected are given below. The reasons are obvious. The best bowlers and the top-order batsmen, barring a minor variation make the cut.

Australia
Bowlers: Ryan Harris, Peter Siddle, Mitchell Starc
and Nathan Lyon. Batsmen: Chris Rogers, David Warner, Shane Watson,
Michael Clarke, Steven Smith and Brad Haddin
(for want of a suitable batsman).
England Bowlers: Graeme Swann, James Anderson, Stuart Broad
and Tim Bresnan. Batsman: Alastair Cook, Joe Root, Jonathan Trott,
Kevin Pietersen, Ian Bell and Jonny Bairstow.

Kindly note that there are no exclusions. If you are going to lose sleep if you did not know how Bairstow faced up to Ashton Agar or Simon Kerrigan bowled to Watson, please refer to the Excel chart.

Let us move on to the tables now.

1. The best Australian bowler has to be Harris, with no one else coming close. Even leaving aside 24 wickets at sub-20 average in four Tests, look at how Harris has performed against the English top order. He has done very well against Cook (three wkts at 24), dominated Root (four wkts at 9.5) and Trott (four wkts at 12) and performed very competently against Pietersen, Bell and Bairstow (five wickets at below-30). Sixteen of his 24 wickets are those of top-order batsmen. For once we can say with certainty, based on these macro-level figures that Harris was the bowler of the series.

2. Siddle has been less dominating. Root and Trott have played quite well, with averages exceeding 40. Cook and Pietersen have, to an extent, been taken care of by Siddle. However look at Bell. He has totally and overwhelmingly dominated Siddle. No wicket conceded in 239 balls. It is also relevant that only nine of Siddle's 17 wickets are those of top-order batsmen.
Full post
Ryan ten Doeschate on the top!

A detailed look at the top allrounders in ODI cricket based on their batting and bowling skills

I started looking at the work I had done over the years and found out that I had never really done an article on ODI allrounders. Test allrounders, plenty, but almost nothing on ODI allrounders. So I decided to complete this gap in my bio-data.

There is no doubt that ODI allrounders analysis is a specialised area requiring a deeper level of analysis than the Test exercise. Wickets are paramount in Tests and a 6 for 75 is invariably considered to be better than 5 for 50. However in ODIs with the bowlers bowling for a limited number of overs, an analysis of 2 for 20 is almost always more effective than 3 for 40 or 4 for 60. Also a 50-ball 30 is more likely to win a match than 75 in 90 balls. These are true in most situations. I agree that defending a low total or chasing a middling score would promote the importance of wickets and runs. Hence it is essential to give due weight to all four facets of batting and bowling.

As normally happens, the first step is to draw up a minimum cut-off point. With lofty ideas I started with 100 wickets and 2500 runs to find that not many qualified. I progressively lowered the bar and finally decided on 50 wickets and 1500 runs. These numbers represent an average playing career of 40-50 matches and would allow the players from the 1980s and associate countries to be considered. There were 65 qualifying players, which is a fair number.

How does one measure the all-round ability of an ODI allrounder? I decided on the following measures.

1. A composite career-level ratings of the four measures: Batting RpI, Scoring rate, Bowling Strike rate and RpO.
3. The trusted AllRounder (A-R) ratio of Batting RpI / Bowling average.
2. A run-equalised delivery per match measure.
4. Run-equalised values for career. This is strictly a longevity measure and is meant to recognise the allrounders who played a huge number of matches.

I will also show a final table classifying allrounders into bowler-centric, balanced and batsman-centric groups.

Let us now move on to the tables.

Allrounder Rating Index
NameCtryODIsRpISc/RSt/RRpORpI-IdxSc/R-IdxSt/R-IdxRpO-IdxA/R-Index
RN ten DoeschateNed 3348.15 87.728.725.0424.0820.1026.1114.8885.17
A Flintoff Eng14127.81 88.833.274.4013.9020.3622.5417.0673.86
SR Watson Aus16034.25 88.536.344.7817.1220.2820.6415.6873.72
IVA Richards Win18740.24 90.247.834.4920.1220.6715.6816.6973.16
V Sehwag Ind25133.76104.345.755.2616.8823.9116.3914.2571.43
DS Lehmann Aus11730.47 81.334.484.8415.2318.6421.7515.5071.13
KJ O'Brien Ire 7228.89 83.334.134.9114.4419.1021.9715.2870.80
Shahid Afridi Pak35921.99114.643.864.6110.9926.2717.1016.2670.63
JH Kallis Saf32137.45 73.039.394.8318.7316.7219.0415.5470.03
GS Chappell Aus 7432.37 75.743.164.0516.1817.3517.3818.5369.44
CH Gayle Win25335.11 84.244.774.7417.5619.3116.7515.8269.44
L Klusener Saf17126.10 89.938.194.7013.0520.6119.6415.9469.24
SR Tendulkar Ind46340.76 86.252.335.1020.3819.7614.3314.7069.17
A Symonds Aus19831.60 92.444.625.0115.8021.1816.8114.9768.76
ME Waugh Aus24436.01 76.943.374.7818.0017.6217.2915.6968.61
Shakib Al Hasan Bng12929.74 78.240.854.3114.8717.9218.3617.3968.54
N Kapil Dev Ind22519.10 95.144.273.72 9.5521.7916.9420.1768.45
ST Jayasuriya Slk44431.01 91.246.034.7915.5120.9016.2915.6668.37
RJ Hadlee Nzl11517.86 75.539.123.31 8.9317.3019.1722.6968.09
SM Pollock Saf30317.16 86.739.973.68 8.5819.8718.7620.3967.60

The first is the allrounder ratings table. I decided that the batting and bowling functions would get 50% weight each. I could not separate the importance of the two bowling measures. Hence those two get 25% each. However I realised that the Batting scoring rate should be valued marginally higher than the Batting RpI. Most followers would agree with this. The quantum of differential: a simple 10%, leading to an actual differential of just below 20%. So this was 27.5% and 22.5% for the two measures. Arbitrary: Of course, yes. I have no problems with this allocation. If any reader wants a different weight, the Excel sheet contains all measures and the readers can work out their own alternate tables.

It is very difficult to get a high A-R Index. The concerned player would have to be within the top-80% level in each of the four measures. That is what Ryan ten Doeschate has achieved. His numbers are, to say the least, Bradmanesque! In 33 matches, he has scored 1541 runs at an average of 67.00 and captured 55 wickets at an average of 24.13. Individually, these are figures which would put him at the top of the batting tables and the top-15 of the bowling tables. To the sceptics, let me say that he has played eight matches against Test-playing countries and 25 against very tough teams such as Ireland, Kenya and Afghanistan et al. He plays for an average team and does not get as much support as the other big-team players. If he has not played more matches, then that is the problem playing for an associate country. He does not seem to have played in the recent Netherlands-matches. Probably was trying to earn a living. But let us give credit to the best allrounder the world has ever seen: Ryan ten Doeschate of Netherlands.

ten Doeschate is a clear ten points ahead of Andrew Flintoff who has 73.32 points. He has been excellent: 3394 runs at 27.81 and 169 wickets at 24.83 indicate that he has every right to be called the best allrounder ever, only the freakish short-career numbers of ten Doeschate are better. I get the feeling that Flintoff's ODI skills are rather underrated and overshadowed by his Test exploits. Next in the list is Shane Watson. May not be everybody's favourite with his Test woes now but one of the greatest ODI allrounders ever. 4795 runs at 34.25 and 156 wickets at 28.98 illustrate that he is only marginally behind Flintoff. And both these wonderful allrounders have strike rates around 88+.

These are followed by two explosive batsmen but no mean bowlers. Viv Richards must be the most underrated ODI bowler ever. Coming as the fifth bowler, he plundered 118 wickets, albeit at a reasonably high average of 35.83, to go with his 1980s compilation of 6721 runs at 47.83 (and a strike rate of 90.2). A surprise at No.5 is Virender Sehwag. A very much underrated bowler like Richards, he still managed to capture 96 wickets (albeit at 40.14) to go with his 8273 runs at a strike rate exceeding 100. Shahid Afridi is in the eighth place confirming his status as one of the top allrounders ever. And nice to see Kevin O'Brien in the top ten.

Ratio of Batting RpI and Bowling average
NameCtryODIsRpIBow-AvgeA-R Ratio
RN ten DoeschateNed 3348.1524.131.9957
SR Watson Aus16034.2528.981.1818
JH Kallis Saf32137.4531.701.1815
A Flintoff Eng14127.8124.381.1405
IVA Richards Win18740.2435.831.1231
GS Chappell Aus 7432.3729.121.1114
DS Lehmann Aus11730.4727.811.0957
ME Waugh Aus24436.0134.561.0418
KJ O'Brien Ire 7228.8927.931.0343
Shakib Al Hasan Bng12929.7429.371.0125
CH Gayle Win25335.1135.380.9925
SC Ganguly Ind31137.8738.510.9834
MJ Clarke Aus22735.6237.540.9490
Imran Khan Pak17524.5626.620.9226
SR Tendulkar Ind46340.7644.510.9157
WJ Cronje Saf18831.8034.790.9141
AR Border Aus27325.8828.370.9122
L Klusener Saf17126.1029.950.8714
NJ Astle Nzl22332.6738.460.8494

This is a simpler measure. I divide the Batting RpI by Bowling average to get an Index value. This is my favourite measure and tells a lot about a player's all-round abilities. The ratio is superior to the difference. A player with values of 30 and 25, will have a difference of 5 and a ratio of 1.20. A player with values of 40 and 35 will have the same difference of 5 but a lower ratio of 1.14. It is obvious that the first player is a better allrounder since the lowering of 10 in bowling average is more valuable than the dropping of 10 in batting.

Since this is a performance oriented measure there are some juxtaposition of players at the top from the previous table. Ten Doeschate is at the top with an index value of nearly 2.0, more Bradmanesque than the previous table, since the next value is Watson's 1.18. Jacques Kallis, Flintoff and Richards complete the top-five positions with index values just over 1.12. Watson and Kallis are separated only at the fourth decimal.

Average Run-equalised delivery per match
NameCtryODIsRunsWicketsEqualised valuePer Match
RN ten DoeschateNed 33 1541 55 3301100.0
Shakib Al Hasan Bng129 3688161 8840 68.5
JH Kallis Saf3211149827020138 62.7
GS Chappell Aus 74 2331 72 4635 62.6
A Flintoff Eng141 3394169 8802 62.4
SR Watson Aus160 4795156 9787 61.2
RJ Hadlee Nzl115 1751158 6807 59.2
IK Pathan Ind120 1544173 7080 59.0
IT Botham Eng116 2113145 6753 58.2
L Klusener Saf171 3576192 9720 56.8
IVA Richards Win187 672111810497 56.1
HH Streak Zim189 294323910591 56.0
Wasim Akram Pak356 371750219781 55.6
DJ Bravo Win146 2495173 8031 55.0
Imran Khan Pak175 3709182 9533 54.5
CH Gayle Win253 874315713767 54.4
ST Jayasuriya Slk4441343032323766 53.5
SM Pollock Saf303 351939316095 53.1
CL Cairns Nzl215 495020111382 52.9
M Prabhakar Ind130 1858157 6882 52.9

This is a measure of the actual performance delivered per match. For this, I valued a bowler wicket at 32 runs. Arbitrary? No way. In the 3403 matches played until 3 August 2013, 42832 wickets were captured by bowlers at a total cost of 1372875 runs. This works to 32.05 RpW. I rounded this to 32. So no one can say this is arbitrary. Of course it has changed over the years. However let me give the readers the following summary.

 
	1971-1984 281 3469 99425 28.66 
	1985-2013 3122 39363 1273450 32.35 
	

So this confirms that for 29 years and for 92% of matches, the average wicket value has been slightly above 32. Just to firm up this number, let me say that, for the period 1985-1989, the average was 32.09.

Ten Doeschate has delivered an equivalent of 100 runs per match. I feel this is one of the most significant figures in the ODI game. A player from an Associate country walked in and delivered the equivalent of a hundred in every match he played. I checked his match performances. He has failed to deliver in either batting or bowling in just two matches out of 33. That means he has delivered in 94% of the matches. I am glad to see the equally talented Shakib Al Hasan in the second position, delivering the equivalent of 68 runs per match. Imagine what these two would have achieved with better support. Then comes the giant, Kallis, with 62.7 runs. Greg Chappell is placed next just behind and then come Flintoff and Watson. Imagine these players guaranteed 60+ runs each time they took the field.

Career Run-equalised delivery
NameCtryODIsRunsWicketsEqualised value
ST Jayasuriya Slk4441343032323766
SR Tendulkar Ind4631842615423354
JH Kallis Saf3211149827020138
Wasim Akram Pak356 371750219781
Shahid Afridi Pak359 730335818759
SM Pollock Saf303 351939316095
WPUJC Vaas Slk324 202540014825
SC Ganguly Ind3111136310014563
SR Waugh Aus325 756919513809
CH Gayle Win253 874315713767
Abdul Razzaq Pak265 508026913688
PA de Silva Slk308 928410612676
CL Hooper Win227 576119311937
N Kapil Dev Ind225 378325311879
Yuvraj Singh Ind282 821111211795
CL Cairns Nzl215 495020111382
V Sehwag Ind251 8273 9611345
ME Waugh Aus244 8500 8511220
DL Vettori Nzl275 211028411198
CZ Harris Nzl250 437920310875

Now the final table. This is the same table as previous one but ordered on the total match deliveries, in terms of run-equivalence. Sanath Jayasuriya stands on top with 23766 "runs". When we talk of Jayasuriya the destroyer we forget the fact that he also captured 323 wickets. A very canny bowler who averaged 0.75 wickets per match. Sachin Tendulkar, again the 18000+ runs over-shadowing the fact that he also captured over 150 wickets, is close behind. He has 23354 "runs". Then comes Kallis, with 20138 "runs". Now we get two Pakistani giants, Wasim Akram, with 19781 "runs" and Shahid Afridi, with 18759 "runs". This is a tribute to the longevity of these outstanding allrounders.

Bowling-centric, Balanced and Batting-centric
NameCtryODIsRpI-IdxSc/R-IdxBatting IndexSt/R-IdxRpO-IdxBowling IndexRatio
WPUJC Vaas Slk324 4.6016.6221.219.0217.9036.90.57
RJ Hadlee Nzl115 8.9317.3026.219.1722.6941.90.63
M Prabhakar Ind130 9.4813.8523.318.5217.5436.10.65
Wasim Akram Pak356 6.6420.2426.920.7119.2540.00.67
Mudassar Nazar Pak12211.5312.0023.517.1517.6834.80.68
...
CL Hooper Win22713.9817.5631.515.1217.2032.30.98
SB Styris Nzl18813.9218.2032.116.7915.8132.60.99
Shoaib Malik Pak21614.2217.9432.215.6216.5032.11.00
GW Flower Zim22115.3515.4930.814.2916.1630.41.01
WJ Cronje Saf18815.9017.5333.415.9616.8832.81.02
...
A Symonds Aus19815.8021.1837.016.8114.9731.81.16
TM Dilshan Slk26715.7919.7435.512.9215.9728.91.23
IVA Richards Win18720.1220.6740.815.6816.6932.41.26
V Sehwag Ind25116.8823.9140.816.3914.2530.61.33
SR Tendulkar Ind46320.3819.7640.114.3314.7029.01.38

This is a quirky report. I have divided the batting rating total points by the bowling rating total points. This ratio reveals the nature of the player's all-round abilities: ranging from bowlers who could bat through genuine allrounders to the batsmen who could bowl. The first five belong to the bowling allrounders classification. One surprise there! Chaminda Vaas, Richard Hadlee, Manoj Prabhakar and Wasim Akram were top bowlers first and their batting skills were only add-ons. However Mudassar Nazar is a surprise. My conclusion is that, for a batsman, his batting numbers are quite average.

The middle five, either side of a ratio 0f 1.00, are here only because of the way the numbers fell. Shoaib Malik is the only allrounder whose batting total matches the bowling total exactly. The others are all good allrounders.

The third group is quite clear. All five were far superior batsmen than bowlers. Jayasuriya does not appear here because his bowling numbers are quite impressive.

Finally, who do I salute? I will doff my imaginary hat at ten Doeschate, Flintoff, Watson, Jayasuriya and Afridi, in that order. I will end with an additional salute to ten Doeschate.

I have created an Excel sheet with complete details for these 65 players. To download/view the document, please CLICK HERE.

One final comment on ten Doeschate. He can only play the cards dealt to him. Since he made his debut and got a permanent place, Netherlands have played 50-odd matches. As I have mentioned before, he missed playing the last few matches for his country. So 33 matches in six years is the limit for a player like him. Anyhow if any reader does not want to consider Tendo, he only has to take off the top entry in the relevant tables.

To round off the article I have given below what I feel, based on a number of relevant objective measures, the five greatest all-round performances ever in ODI matches.

1. Shahid Afridi's 76 and 7 for 12 against West Indies during 2013. That an all-round performance contains the second best bowling spell ever speaks volume of this superb effort. And not to forget that the 76, made out of a middling total of 224 for 9, and a recovery from 47 for 5, was itself a truly match-winning effort.
2. Scott Styris' 63 and 6 for 25 against West Indies during 2002. This was a low scoring and close match. New Zealand scored 212, mainly due to Styris lovely innings late in the order. Then he captured 6 for 25 to restrict West Indies to 202 for 9. I would say this performance is only bettered by Afridi's recent effort.
3. Richards' 119 and 5 for 41 against New Zealand during 1987. Until Paul Collingwood's effort this remained a unique effort. Richards' 119 comprised of more than 50% of his team total. The next highest score was 48. Four of his five wickets were of top order batsmen.
4. Paul Collingwood's 112 and 6 for 31 against Bangladesh during 2005. Granted that this was against Bangladesh but let us not forget that no one has scored a century and captured 6 wickets in a match.
5. Tendulkar's 141 and 4 for 38 against Australia during 1998. This was a big innings and the four late order wickets arrested Australia push towards a win. This was also the quarter-final of the Wills International Cup.

My next article will again be the first of a kind. I will apply the ball-by-ball data to a single event, in this case the Ashes series, and come out with the highlights of head-to-head confrontations.

Full post
Head-to-head stats for Lara, Tendulkar, Muralitharan, Warne and eight others

An analysis of how the top batsmen and bowlers fared against their major opponents in Tests based on the available ball-by-ball data

This is the article, the third of a series, using ball-by-ball data, which the readers have repeatedly asked for during the past three years. For an introduction to that work please refer to the first article on contemporary bowlers. I had followed this with another article on contemporary batsmen.

First, let me present a paradox while determining a bowler-batsman confrontation metrics. This relates to the grey area in handling no-balls. The no-ball related runs are charged to the bowlers but not to the batsmen. The ball itself is added to the batsman but not to the bowler. This leads to the following anomaly.

Let us take an over by Mitchell Starc to Alastair Cook, which is the first over of the match.

Ball 1: Dot ball.
Ball 2: 2 runs scored by Cook. 2 runs for team and against Starc.
Ball 3: Wide. 1 run to team and 1 run against Starc.
Ball 3: 2 leg byes. 2 runs to team.
Ball 4: No ball. 1 run scored. 2 runs to team, 2 runs against Starc and 1 run to Cook.
Ball 4: 4 byes. 4 runs to team.
Ball 5: Dot ball.
Ball 6: No ball. 1 run to team, 1 run against Starc.
Ball 6: Dot ball.

At the end of the over the team score is 12 for 0 (9 extras). Starc's analysis reads 1.0-0-6-0 (6 balls and 6 runs (3 to Cook and 3 wide/no-balls)). Cook's score reads 7 balls and 3 runs (2 & 1). No problem about the runs. But the head-to-head confrontation between Starc and Cook has a problem. Do we take six balls or seven balls? I have taken the no ball as a ball for the combination. That is common-sense.

The present article covers the batsmen and bowlers, some who rank amongst the best whoever wielded a bat or held a ball, who have fewer than 75% of ball-by-ball data available. I have changed the format of this article as compared to the previous two. In those I had covered bowlers and batsmen separately and featured four bowlers and batsmen and created a number of tables for each of those. I had also created a downloadable Excel sheet which contained the complete data for the selected batsmen and bowlers.

In this analysis, I have gone about it differently. Since 100% data is not available for these players nothing is gained by doing an elaborate analysis. There would always be that feeling of incomplete data around these tables. Hence I have selected six batsmen and 6 bowlers each from the collection of players who have between 40% and 75% ball-by-ball data available and presented a single table for each player. The comments are thus specific to these players.

I have also uploaded an Excel sheet containing all instances of bowler-batsman combinations with 100 balls or more, extracted from the entire ball-by-ball data. There are 2844 such instances. In addition I have included 110 instances where three or more wickets were captured and fewer than 100 balls bowled. Thus, the data would almost be complete if one downloads all three Excel sheets. A hundred-balls represents a good cut-off. It is of very little relevance to know that Shane Warne bowled ten balls to Dinesh Karthik and 16 runs were scored or that VVS Laxman bowled ten balls to AB de Villiers and 3 runs were scored.

The players selected are given below. The percentage value on the left shows the extent of ball-by-ball data available. Sachin Tendulkar's ball-by-ball percentage is slightly higher since he is still active and each new Test adds to this component. If, as expected, he retires at the end of the South African tour, he is likely to finish at around 60%.

Batsmen: 
    45.1%  Brian Lara
    58.2%  Sachin Tendulkar
    71.3%  Rahul Dravid
    71.9%  Jacques Kallis
    67.4%  Mohammad Yousuf
    72.5%  Shivnarine Chanderpaul
Bowlers:
    54.1%  Muttiah Muralitharan
    40.2%  Shane Warne
    43.0%  Glenn McGrath
    50.2%  Shaun Pollock
    66.7%  Shoaib Akhtar
    53.7%  Anil Kumble

Justification of these players' selections would be akin to gilding the lily. Most of them select themselves. I selected Mohammad Yousuf instead of Inzamam-ul-Haq since there is a lot more data available for him. Shoaib Akhtar is a late selection. Daniel Vettori was an alternative. Similarly, Stephen Fleming for Shivnarine Chanderpaul was another possibility.

I would like to emphasise that the ball-by-ball data availability for these players is around 50%. This has to be remembered when deriving insights. It is also a fact that the 50% mark pertains to the latter half of the concerned player's career. My suggestion is not to extrapolate. Just take the figures at their face value.

Selected 6 Batsmen

1. Summary table for BRIAN LARA
BowlerTypeBowling AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
M Muralitharan rob22.73 9 709 373 3 52.6124.33236.3
Chaminda Vaas LFM29.58 9 372 233 1 62.6233.00372.0
Andre Nel RFM31.8611 341 185 8 54.3 23.12 42.6
Makhaya Ntini RF 28.8311 312 225 1 72.1225.00312.0
Steve Harmison RFM31.8213 303 146 4 48.2 36.50 75.8
Danish Kaneria rlb34.80 8 298 260 3 87.2 86.67 99.3
Andrew Flintoff RF 32.7910 263 109 4 41.4 27.25 65.8
Jacques Kallis RFM32.43 8 251 148 0 59.0148.00251.0
Brett Lee RF 30.8214 243 172 2 70.8 86.00121.5
Stuart MacGill rlb29.03 7 236 174 2 73.7 87.00118.0
Glenn McGrath RFM21.6412 233 90 2 38.6 45.00116.5
Jason Gillespie RF 26.14 8 214 82 0 38.3 82.00214.0
Shaun Pollock RFM23.12 6 192 63 1 32.8 63.00192.0
Shahid Nazir RFM35.33 4 181 88 0 48.6 88.00181.0
Andy Bichel RFM32.24 8 171 112 4 65.5 28.00 42.8
Shane Warne rlb25.42 7 168 105 3 62.5 35.00 56.0
Abdul Razzaq RFM36.93 6 168 110 0 65.5110.00168.0
Thilan Samaraweera rob45.93 7 161 80 1 49.7 80.00161.0
Gareth Batty rob66.64 1 161 130 0 80.7130.00161.0
Matthew Hoggard RFM30.5010 159 137 1 86.2137.00159.0

1. Muttiah Muralitharan bowled millions of balls to Brian Lara, 709 to be precise (for whatever part of the ball-by-data available career of two). But it is safe to say that Lara mastered Muralitharan: and how? Strike rate over 50, average of 124 and a wicket every 40 overs. Not forgetting that most of these balls were bowled in Sri Lanka.
2. On the flip side, a fairly ordinary bowler like Andre Nel had the complete measure of Lara. Eight wickets at a strike rate of 42. Andy Bichel was also quite successful: four wickets, striking every 43 balls. This is difficult to explain considering that he handled much better fast bowlers better.
3. Lara took Danish Kaneria to the cleaners. A scoring rate of more than 87 over nearly 300 balls. He had a scoring rate of over 70 against six bowlers out of these 20.
4. Glenn McGrath, Shaun Pollock and Jason Gillespie kept Lara in check, but with very little success. In fact, Kallis and Gillespie bowled a lot at Lara but did not dismiss him even once. Lara attacked Warne but also lost his wicket often.

2. Summary table for SACHIN TENDULKAR
BowlerTypeBowling AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Mitchell Johnson LF 30.9318 502 250 3 49.8 83.33167.3
Paul Harris lsp37.87 7 441 154 3 34.9 51.33147.0
Brett Lee RF 30.8219 432 242 5 56.0 48.40 86.4
M Muralitharan rob22.7314 366 196 6 53.6 32.67 61.0
James Anderson RFM29.6723 350 208 9 59.4 23.11 38.9
Ashley Giles lsp40.60 5 348 125 1 35.9125.00348.0
Andrew Flintoff RF 32.7917 342 133 2 38.9 66.50171.0
Daniel Vettori lsp34.4212 314 95 3 30.3 31.67104.7
Dale Steyn RF 22.6611 310 149 3 48.1 49.67103.3
Monty Panesar lsp33.7813 304 149 4 49.0 37.25 76.0
Matthew Hoggard RFM30.5013 292 182 3 62.3 60.67 97.3
Mohammad Sami RF 52.74 9 287 127 1 44.3127.00287.0
Mohammad Rafique lsp40.76 5 283 140 1 49.5140.00283.0
Graeme Swann rob28.1414 279 150 4 53.8 37.50 69.8
Danish Kaneria rlb34.80 8 269 151 1 56.1151.00269.0
Mervyn Dillon RFM33.6310 267 163 2 61.0 81.50133.5
Ben Hilfenhaus RFM28.5110 250 161 0 64.4161.00250.0
Nathan Hauritz rob34.98 5 236 179 1 75.8179.00236.0
Shakib Al Hasan lsp32.75 5 234 119 1 50.9119.00234.0
Cameron Cuffy RF 33.67 8 233 107 2 45.9 53.50116.5

1. James Anderson had the complete measure of Tendulkar. He got his wickets nine times at a strike rate of 39 balls.
2. In view of the contest at year-end, it is significant to note that Tendulkar has handled Dale Steyn quite comfortably.
3. Tendulkar has been circumspect against most bowlers. There is only one bowler, Nathan Hauritz, against whom Tendulkar had a scoring rate exceeding 70.
4. Possibly because this pertained to Tendulkar's second half of his career, there seems to be a cautious handling of the bowlers. Most spinners have kept Tendulkar quiet.

3. Summary table for RAHUL DRAVID
BowlerTypeBowling AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
M Muralitharan rob22.7316 688 326 5 47.4 65.20137.6
Daniel Vettori lsp34.4212 609 275 2 45.2137.50304.5
Danish Kaneria rlb34.8013 583 305 5 52.3 61.00116.6
Matthew Hoggard RFM30.5016 531 218 5 41.1 43.60106.2
Andrew Flintoff RF 32.7917 470 154 3 32.8 51.33156.7
Mohammad Sami RF 52.7414 454 205 2 45.2102.50227.0
James Anderson RFM29.6718 432 197 5 45.6 39.40 86.4
Brett Lee RF 30.8216 389 153 5 39.3 30.60 77.8
Stuart MacGill rlb29.03 8 357 225 0 63.0225.00357.0
Makhaya Ntini RF 28.8313 345 149 3 43.2 49.67115.0
Monty Panesar lsp33.7811 343 145 2 42.3 72.50171.5
Pedro Collins LFM34.6211 341 178 0 52.2178.00341.0
Stuart Broad RFM31.1910 340 136 2 40.0 68.00170.0
Devendra Bishoo rlb39.55 9 339 165 2 48.7 82.50169.5
Mitchell Johnson LF 30.9313 324 113 4 34.9 28.25 81.0
Graeme Swann rob28.14 9 318 163 3 51.3 54.33106.0
Ashley Giles lsp40.60 7 313 112 2 35.8 56.00156.5
Jason Gillespie RF 26.1412 300 84 4 28.0 21.00 75.0
Paul Harris lsp37.87 8 300 107 1 35.7107.00300.0
Chris Martin RFM33.8110 297 89 3 30.0 29.67 99.0

1. Rahul Dravid has been quite careful against almost all bowlers. There is only one scoring rate in excess of 60: against Stuart MacGill.
2. No bowler has quite mastered Dravid. The lowest strike rate in this collection is 75, that of Gillespie.
3. Dravid faced Vettori very comfortably: 609 balls and only 2 wickets.

4. Summary table for JACQUES KALLIS
BowlerTypeBowling AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Harbhajan Singh rob32.3818 676 382 6 56.5 63.67112.7
Danish Kaneria rlb34.8013 621 258 4 41.5 64.50155.2
Shane Warne rlb25.4222 550 280 5 50.9 56.00110.0
Brett Lee RF 30.8221 528 199 3 37.7 66.33176.0
Anil Kumble rlb29.6514 494 191 1 38.7191.00494.0
Daniel Vettori lsp34.4210 475 208 0 43.8208.00475.0
Abdur Rehman lsp28.41 8 434 222 0 51.2222.00434.0
James Anderson RFM29.6722 419 177 7 42.2 25.29 59.9
Zaheer Khan LFM32.3614 382 157 2 41.1 78.50191.0
Glenn McGrath RFM21.6416 378 133 3 35.2 44.33126.0
Andrew Flintoff RF 32.7915 372 139 4 37.4 34.75 93.0
Steve Harmison RFM31.8213 346 146 4 42.2 36.50 86.5
S Sreesanth RFM37.6112 328 150 4 45.7 37.50 82.0
Chris Martin RFM33.8115 319 158 4 49.5 39.50 79.8
Umar Gul RFM34.0710 303 165 1 54.5165.00303.0
Peter Siddle RFM28.5815 294 170 2 57.8 85.00147.0
Graeme Swann rob28.14 8 288 147 1 51.0147.00288.0
Ray Price lsp36.06 3 277 143 0 51.6143.00277.0
Mitchell Johnson LF 30.9312 269 88 5 32.7 17.60 53.8
Dwayne Bravo RM 39.70 9 267 132 2 49.4 66.00133.5

1. Anderson has been very successful against Jacques Kallis: 7 wickets at a strike rate of 60. Mitchell Johnson has also been quite successful.
2. Barring a few pace bowlers, Kallis has been quite successful against most bowlers.
3. Kallis vs Anil Kumble is simply amazing. 500 balls and a single dismissal. Similarly Graeme Swann has not been successful against Kallis. A single wicket in the 288 balls bowled.
4. Kallis has handled all bowlers quite well but at relatively low scoring rates: all, barring Steve Harmison, below 60.

5. Summary table for MOHAMMAD YOUSUF
BowlerTypeBowling AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Anil Kumble rlb29.6517 504 287 5 56.9 57.40100.8
Matthew Hoggard RFM30.5011 376 196 1 52.1196.00376.0
Steve Harmison RFM31.82 7 355 235 2 66.2117.50177.5
Daniel Vettori lsp34.42 8 315 110 2 34.9 55.00157.5
Irfan Pathan LM 32.2616 295 141 5 47.8 28.20 59.0
Monty Panesar lsp33.78 7 291 145 3 49.8 48.33 97.0
Harbhajan Singh rob32.3811 263 155 3 58.9 51.67 87.7
Rangana Herath lsp29.52 9 244 112 6 45.9 18.67 40.7
L Balaji RM 37.19 9 233 134 2 57.5 67.00116.5
Dave Mohammed lws51.38 3 228 132 1 57.9132.00228.0
Corey Collymore RFM32.30 5 191 89 1 46.6 89.00191.0
Zaheer Khan LFM32.36 8 174 100 1 57.5100.00174.0
Andrew Flintoff RF 32.79 5 171 64 3 37.4 21.33 57.0
Jerome Taylor RF 35.65 5 169 121 0 71.6121.00169.0
Ray Price lsp36.06 2 158 80 2 50.6 40.00 79.0
Chris Gayle rob42.01 6 154 64 2 41.6 32.00 77.0
Dwayne Bravo RM 39.70 5 148 95 0 64.2 95.00148.0
Iain O'Brien RFM33.27 5 145 73 2 50.3 36.50 72.5
Daren Powell RFM47.99 4 144 82 0 56.9 82.00144.0
Enamul Haque lsp57.11 3 140 89 0 63.6 89.00140.0

1. Mohammad Yousuf against Matthew Hoggard is something. A single wicket in 376 balls.
2. Rangana Herath had the measure of Yousuf. He dismissed him six times in 244 balls. Similarly, Irfan Pathan.
3. Kumble bowled the maximum balls and had only reasonable success. Many bowlers had fair strike rates against Yousuf.
4. Yousuf attacked Harmison and Jerome Taylor.

6. Summary table for S CHANDERPAUL
BowlerTypeBowling AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Harbhajan Singh rob32.3818 790 260 2 32.9130.00395.0
Anil Kumble rlb29.6513 500 232 6 46.4 38.67 83.3
Steve Harmison RFM31.8218 464 239 1 51.5239.00464.0
Andre Nel RFM31.8612 428 185 3 43.2 61.67142.7
Makhaya Ntini RF 28.8316 413 197 5 47.7 39.40 82.6
Danish Kaneria rlb34.8011 403 207 6 51.4 34.50 67.2
Monty Panesar lsp33.78 8 392 179 2 45.7 89.50196.0
Javagal Srinath RFM30.4711 382 139 3 36.4 46.33127.3
Paul Harris lsp37.87 9 359 179 1 49.9179.00359.0
Zaheer Khan LFM32.36 9 355 136 2 38.3 68.00177.5
James Anderson RFM29.6714 339 151 2 44.5 75.50169.5
Jacques Kallis RFM32.4317 334 113 2 33.8 56.50167.0
Graeme Swann rob28.1410 330 122 5 37.0 24.40 66.0
Brett Lee RF 30.8216 329 126 3 38.3 42.00109.7
Ashley Giles lsp40.60 9 310 138 3 44.5 46.00103.3
Stuart MacGill rlb29.03 9 283 210 3 74.2 70.00 94.3
Daniel Vettori lsp34.42 8 277 116 3 41.9 38.67 92.3
Matthew Hoggard RFM30.5014 269 146 4 54.3 36.50 67.2
Stuart Broad RFM31.1910 268 89 5 33.2 17.80 53.6
Ashish Nehra LM 42.41 6 261 108 0 41.4108.00261.0

1. This has already been discussed when looking at Harbhajan Singh. Chanderpaul was dismissed only twice in 790 balls.
2. Still more dominant is Chanderpaul against Harmison. A single dismissal in 464 balls. On a normal day this represents nearly a day's bowling.
3. But look at Chanderpaul's scoring rates. Plenty of instances below 40. He attacked only one bowler: Stuart MacGill.

Selected 6 Bowlers

7. Summary table for M MURALITHARAN
BatsmanTypeBatting AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Brian Lara LHB52.89 9 709 373 3 52.6124.33236.3
Rahul Dravid rhb52.3116 688 326 5 47.4 65.20137.6
Ramnaresh Sarwan rhb40.0113 597 222 7 37.2 31.71 85.3
Mohammad Ashraful rhb24.0117 563 276 7 49.0 39.43 80.4
VVS Laxman rhb45.9715 496 240 2 48.4120.00248.0
Stephen Fleming LHB40.07 5 453 171 0 37.7171.00453.0
Alastair Cook LHB48.45 8 450 152 2 33.8 76.00225.0
Paul Collingwood rhb40.5715 393 136 7 34.6 19.43 56.1
Graham Thorpe LHB44.66 8 387 110 5 28.4 22.00 77.4
Sachin Tendulkar rhb53.8714 366 196 6 53.6 32.67 61.0
Mark Butcher LHB34.58 7 357 106 2 29.7 53.00178.5
Sourav Ganguly LHB42.1813 323 141 8 43.7 17.62 40.4
Michael Vaughan rhb41.4412 320 97 6 30.3 16.17 53.3
Jacob Oram LHB36.3311 296 107 5 36.1 21.40 59.2
Damien Martyn rhb46.38 6 291 122 3 41.9 40.67 97.0
Shoaib Malik rhb33.46 4 288 62 0 21.5 62.00288.0
Gautam Gambhir LHB44.1910 271 137 4 50.6 34.25 67.8
Ashwell Prince LHB41.65 6 267 88 3 33.0 29.33 89.0
Marcus Trescothick LHB43.7611 266 110 8 41.4 13.75 33.2
Daniel Vettori LHB30.1110 263 127 3 48.3 42.33 87.7

1. We have already talked of the dominance Lara had over Muralitharan. VVS Laxman and Cook were equally effective. Dravid suffers only in comparison.
2. The top batsmen seem to have played Muralitharan quite well. Only the English trio of Paul Collingwood, Michael Vaughan and Marcus Trescothick seem to have a fair time, at best, against Muralitharan.
3. However the best against Muralitharan is undoubtedly Fleming. Over 453 balls and no dismissal. Shoaib Malik has been equally good.
4. Tendulkar has attacked Muralitharan but also been dismissed frequently. Lara and Tendulkar have been quite aggressive against Muralitharan.

8. Summary table for SHANE WARNE
BatsmanTypeBatting AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Jacques Kallis rhb56.1022 550 280 5 50.9 56.00110.0
Kevin Pietersen rhb48.3118 521 308 5 59.1 61.60104.2
Ashwell Prince LHB41.6518 466 16411 35.2 14.91 42.4
Mark Boucher rhb30.3022 417 219 9 52.5 24.33 46.3
Andrew Flintoff rhb31.7819 407 225 7 55.3 32.14 58.1
Ian Bell rhb46.5813 396 177 5 44.7 35.40 79.2
Neil McKenzie rhb37.3911 366 153 4 41.8 38.25 91.5
Herschelle Gibbs rhb41.9514 347 166 6 47.8 27.67 57.8
Nathan Astle rhb37.0215 333 141 2 42.3 70.50166.5
Paul Collingwood rhb40.5710 317 165 2 52.1 82.50158.5
Alec Stewart rhb39.5612 294 160 5 54.4 32.00 58.8
Stephen Fleming LHB40.07 8 294 125 2 42.5 62.50147.0
Mark Butcher LHB34.5812 287 151 4 52.6 37.75 71.8
Michael Vaughan rhb41.4410 285 131 3 46.0 43.67 95.0
Nasser Hussain rhb37.1910 278 109 3 39.2 36.33 92.7
Jacques Rudolph LHB35.4310 260 114 4 43.8 28.50 65.0
Shaun Pollock rhb32.3213 252 172 2 68.3 86.00126.0
Andrew Strauss LHB40.9112 241 141 8 58.5 17.62 30.1
Gary Kirsten LHB45.27 5 238 128 1 53.8128.00238.0
Thilan Samaraweera rhb48.77 7 226 78 0 34.5 78.00226.0

1. What do we see with Ashwell Prince? In the earlier article we have already seen Prince's three dismissals by Swann in five balls. Now we see that Warne has dismissed Prince 11 times at a strike rate of 40 balls.
2. Mark Boucher was dismissed nine times at a strike rate of 46, Andrew Flintoff seven times at 58, Alec Stewart five times at 59 and finally Andrew Strauss eight times at 30. Warne seems to have had the measure of all.
3. Kevin Pietersen has attacked Warne and has a high strike rate. Look at the way Shaun Pollock has handled Warne very effectively.
4. Look at how effectively Thilan Samaraweera has handled Warne.

9. Summary table for GLENN MCGRATH
BatsmanTypeBatting AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Herschelle Gibbs rhb41.9517 492 191 3 38.8 63.67164.0
Marcus Trescothick LHB43.7624 438 184 6 42.0 30.67 73.0
Jacques Kallis rhb56.1016 378 133 3 35.2 44.33126.0
Mark Butcher LHB34.5815 365 174 5 47.7 34.80 73.0
Michael Vaughan rhb41.4414 348 193 6 55.5 32.17 58.0
Andrew Strauss LHB40.9115 336 168 3 50.0 56.00112.0
Nathan Astle rhb37.0210 297 189 3 63.6 63.00 99.0
Ian Bell rhb46.5813 293 108 5 36.9 21.60 58.6
Kevin Pietersen rhb48.3113 270 135 5 50.0 27.00 54.0
Brian Lara LHB52.8912 233 90 2 38.6 45.00116.5
Ramnaresh Sarwan rhb40.01 9 232 82 2 35.3 41.00116.0
Graeme Smith LHB48.6312 224 81 5 36.2 16.20 44.8
Stephen Fleming LHB40.0713 222 63 7 28.4 9.00 31.7
Mike Atherton rhb37.7010 210 86 6 41.0 14.33 35.0
Paul Collingwood rhb40.5711 199 54 2 27.1 27.00 99.5
Gary Kirsten LHB45.2710 196 75 4 38.3 18.75 49.0
Mark Richardson LHB44.77 9 193 58 1 30.1 58.00193.0
Nasser Hussain rhb37.1912 192 41 4 21.4 10.25 48.0
Chris Gayle LHB42.46 8 177 63 4 35.6 15.75 44.2
Neil McKenzie rhb37.3910 176 76 2 43.2 38.00 88.0

1. With whatever data available, it is clear that McGrath has dominated quite a few batsmen. Fleming has the lowest strike rate: seven wickets at 32. Mike Atherton, six at 35. Pietersen and Ian Bell have similar figures.
2. Only Herschelle Gibbs has really dominated McGrath. To a lesser extent, Kallis and Strauss.
3. The metronome that McGrath was, it is amazing to see Nathan Astle taking him quite comfortably at a very good strike rate. Nasser Hussain found it difficult to get McGrath away.

10. Summary table for SHAUN POLLOCK
BatsmanTypeBatting AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Marcus Trescothick LHB43.7618 381 126 4 33.1 31.50 95.2
Michael Vaughan rhb41.4418 367 91 5 24.8 18.20 73.4
Matthew Hayden LHB50.7411 356 152 2 42.7 76.00178.0
Justin Langer LHB45.2711 352 137 3 38.9 45.67117.3
Andrew Strauss LHB40.91 9 336 121 2 36.0 60.50168.0
Michael Hussey LHB51.53 8 312 122 1 39.1122.00312.0
Ricky Ponting rhb51.8714 291 151 3 51.9 50.33 97.0
Rahul Dravid rhb52.3111 277 69 5 24.9 13.80 55.4
Taufeeq Umar LHB38.72 8 277 72 1 26.0 72.00277.0
Ramnaresh Sarwan rhb40.01 9 241 108 4 44.8 27.00 60.2
Mark Butcher LHB34.5810 233 66 1 28.3 66.00233.0
Chris Gayle LHB42.46 6 224 117 1 52.2117.00224.0
Damien Martyn rhb46.38 8 223 72 2 32.3 36.00111.5
Virender Sehwag rhb49.34 8 206 120 3 58.3 40.00 68.7
Mahela Jayawardene rhb49.57 8 195 58 2 29.7 29.00 97.5
Brian Lara LHB52.89 6 192 63 1 32.8 63.00192.0
Sachin Tendulkar rhb53.8710 186 85 3 45.7 28.33 62.0
Graham Thorpe LHB44.6610 185 69 2 37.3 34.50 92.5
Marvan Atapattu rhb39.02 8 183 55 3 30.1 18.33 61.0
Andrew Flintoff rhb31.7810 177 88 4 49.7 22.00 44.2

1. Shaun Pollock has had the measure of Flintoff and to a lesser extent, Dravid.
2. Mike Hussey has handled Pollock very well. 312 balls and a single dismissal tells the story. A few Australian top order batsmen and Lara have also been quite effective.
3. Chris Gayle has attacked Pollock's bowling with lot of success.

11. Summary table for ANIL KUMBLE
BatsmanTypeBatting AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Younis Khan rhb50.7413 661 332 5 50.2 66.40132.2
Ricky Ponting rhb51.8713 579 295 4 50.9 73.75144.8
Mohammad Yousuf rhb52.2917 504 287 5 56.9 57.40100.8
S Chanderpaul LHB51.8213 500 232 6 46.4 38.67 83.3
Jacques Kallis rhb56.1014 494 191 1 38.7191.00494.0
Michael Clarke rhb51.5914 469 276 6 58.8 46.00 78.2
Michael Vaughan rhb41.4411 459 272 2 59.3136.00229.5
Simon Katich LHB45.0315 439 265 6 60.4 44.17 73.2
Matthew Hayden LHB50.7415 399 256 5 64.2 51.20 79.8
Ramnaresh Sarwan rhb40.0112 394 151 3 38.3 50.33131.3
Kamran Akmal rhb30.7915 379 201 5 53.0 40.20 75.8
Mahela Jayawardene rhb49.57 8 370 161 3 43.5 53.67123.3
Inzamam-ul-Haq rhb49.6110 352 234 5 66.5 46.80 70.4
Paul Collingwood rhb40.5710 324 146 3 45.1 48.67108.0
Misbah-ul-Haq rhb43.20 6 320 125 0 39.1125.00320.0
Damien Martyn rhb46.3812 317 178 5 56.2 35.60 63.4
Kevin Pietersen rhb48.3111 310 176 2 56.8 88.00155.0
Nasser Hussain rhb37.19 9 288 147 4 51.0 36.75 72.0
Michael Hussey LHB51.53 7 276 170 1 61.6170.00276.0
Mohammad Sami rhb11.6013 272 67 5 24.6 13.40 54.4

1. Many of the batsmen who faced Kumble have played him quite well. We have already seen Kallis' 494 balls per wicket.
2. For all the accurate bowling Kumble was famous for, quite a few batsmen have very good scoring rates, led by Inzamam.
3. Look at how comfortably Hussey and Misbah-ul-Haq have handled Kumble.
4. Damien Martyn is the one Kumble had some measure of.

12. Summary table for SHOAIB AKHTAR
BatsmanTypeBatting AvgeInnsBallsRunsWicketsBatsman Scoring RateHtH AverageBowler Strike Rate
Rahul Dravid rhb52.3112 283 91 2 32.2 45.50141.5
Virender Sehwag rhb49.34 8 212 177 3 83.5 59.00 70.7
Justin Langer LHB45.27 8 174 127 0 73.0127.00174.0
Marcus Trescothick LHB43.76 7 165 73 2 44.2 36.50 82.5
Sourav Ganguly LHB42.18 9 164 100 2 61.0 50.00 82.0
VVS Laxman rhb45.9710 154 80 1 51.9 80.00154.0
Sachin Tendulkar rhb53.87 8 140 79 2 56.4 39.50 70.0
Sanath Jayasuriya LHB40.07 4 137 103 1 75.2103.00137.0
Ian Bell rhb46.58 6 129 84 2 65.1 42.00 64.5
Matthew Hayden LHB50.74 7 115 55 3 47.8 18.33 38.3
Ricky Ponting rhb51.87 8 111 65 2 58.6 32.50 55.5
Wasim Jaffer rhb34.11 6 109 47 2 43.1 23.50 54.5
Habibul Bashar rhb30.88 5 102 95 1 93.1 95.00102.0

1. Shoaib Akhtar has been quite effectively handled by the Indian batsmen, led by Dravid and Laxman. Tendulkar and Virender Sehwag have had mixed time against Akhtar.
2. Matthew Hayden is the batsmen against whom Akhtar has had some success.

One final reminder that we are looking at ball-by-ball data of around 50% for the players concerned. However, it should be noted that in certain cases, because one part of the concerned bowler-batsman pair could as well have complete data, the data presented is complete for this combination. Examples are Steyn vs Tendulkar and Warne vs Pietersen.

These are just samples of the type of insights which can be drawn. I have created an Excel sheet with 2954 instances of ball-by-ball data where the number of balls exceeds 100 or number of dismissals exceed 3. To download/view the document, a veritable treasure-trove of information, please CLICK HERE.

These three articles complete the first phase of analysis using the ball-by-ball data which has been extracted by Milind. After a break of an article or two I will look at some special analysis using this priceless data. Any suggestions from readers will be welcome. To start with, I may start with a single-Test based analysis.

Full post
Every ball that Clarke, Pietersen, Cook and Amla faced

A look at batsmen-versus-bowlers duels in Tests - how top batsmen performed against their favourite and not-so-favourite bowlers

This is the second article of a series, using ball-by-ball data, which the readers have repeatedly asked for during the past three years. For an introduction to the work done, please refer to the first article on contemporary bowlers.

I have given below the revised plan for the analyses which would be done. Readers can contribute their bit in suggesting whether anything else can be done.

1. The top three modern bowlers: with over 85% of ball-by-ball data available (15 bowlers: Steyn/Anderson/Harbhajan are featured). This article has already been published.
2. The top four modern batsmen: with over 75% of ball-by-ball data available. Clarke, Pietersen, Cook and Amla are featured in this article, which is the current one. Thirteen other batsmen are included in the downloadable tables.
3. The third analysis will be a combined analyses of the entire data. I will look at all the batsmen and bowlers together and bring out tables of bowler-batsman combinations exceeding 100 balls. There are 2831 such combinations. This will mean that there will be no artificial restrictions or cut-offs. This table will be available in two orders: by bowler and by batsman.
4. Special analyses, to be decided as we go on, based on reader inputs.

The current analysis will cover the batsmen for whom over 75% of data is available and over 5000 Test runs have been scored. I have selected 17 batsmen and featured four batsmen in the article. This article features four top batsmen of the current generation. The batsmen featured are Michael Clarke, Kevin Pietersen, Alastair Cook and Hashim Amla. Virtually no one will have any problems with this selection. The others considered are Kumar Sangakkara, Mahela Jayawardene, VVS Laxman and Ricky Ponting. These eight batsmen, along with eight others form the complete selection. Jacques Kallis, Rahul Dravid and Shivnarine Chanderpaul just missed the cut-off of 75%. Brian Lara, Sachin Tendulkar and Stephen Fleming are way below the cut-off, in fact, below 60% mark. However, I can assure all readers that all these great batsmen are very well represented in the third article.

I am not going to spend too much time on explaining the types of analyses which are possible. It is better that we move on to the tables. There will only be minimal comments. There is, however, a summary at the end. There are six tables for each of the featured batsmen since the balls/runs ones have been combined into one and the late order batsmen table, which was there in the bowler analysis, does not have a place here.

Michael Clarke

1. Ordered by Wickets in MICHAEL CLARKE-Bowler combination
BowlerTypeBowAvgeInnsBallsRunsWicketsStrikeRateAvgeVsBowler
James Anderson RFM29.7021 267 157 7 38.1 22.43
Dale Steyn RF 22.6619 376 253 7 53.7 36.14
Ishant Sharma RFM37.9919 435 273 7 62.1 39.00
Steve Harmison RFM31.8217 270 140 6 45.0 23.33
Anil Kumble rlb29.6514 469 276 6 78.2 46.00
Zaheer Khan LFM32.3619 460 260 5 92.0 52.00
Ravindra Jadeja lsp19.85 6 190 72 5 38.0 14.40
Rangana Herath lsp29.52 8 309 192 4 77.2 48.00
Matthew Hoggard RFM30.5012 243 158 4 60.8 39.50
Mohammad Asif RFM24.37 8 198 87 4 49.5 21.75
Total for 10 batsmen 32171868 55 58.5 33.96

James Anderson moved to top of Clarke dismissals with his Trent Bridge dismissal. Ravindra Jadeja is a surprise presence here. And at a very low average.

2. Ordered by Balls bowled in MICHAEL CLARKE-Bowler combination
BowlerTypeBowAvgeInnsBallsDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Harbhajan Singh rob32.3823 52737270.6%13525.6%20 3.8%
Anil Kumble rlb29.6514 46933571.4% 9820.9%36 7.7%
Zaheer Khan LFM32.3619 46033472.6% 9420.4%32 7.0%
Ishant Sharma RFM37.9919 43530971.0% 9221.1%37 8.5%
Dale Steyn RF 22.6619 37625367.3% 9425.0%30 8.0%
Morne Morkel RF 29.9812 37525467.7% 7921.1%4211.2%
Andrew Flintoff RFM32.7917 37528074.7% 7520.0%20 5.3%
R Ashwin rob28.53 8 35522763.9%10028.2%29 8.2%
Daniel Vettori lsp34.4211 33623870.8% 8023.8%18 5.4%
Graeme Swann rob28.7311 33225376.2% 6519.6%14 4.2%

The increase in India-Australia contests has propelled four Indian bowlers to the top of this table. And then two South African bowlers.

3. Ordered by Bowling SR (High) in CLARKE-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Andrew Flintoff RFM 66.217 375 0375.0
R Ashwin rob 59.1 8 355 1355.0
Tim Southee RFM 65.1 7 273 0273.0
Chris Martin RFM 60.210 257 1257.0
Virender Sehwag rob 93.3 8 234 0234.0
Jacques Kallis RFM 68.911 229 0229.0
Ashley Giles lsp 85.2 9 222 1222.0
Makhaya Ntini RF 53.4 9 204 0204.0
M Muralitharan rob 55.0 4 178 0178.0
Mohammad Amir RF 56.2 6 171 1171.0
Total for 10 batsmen 2498 4624.5

Andrew Flintoff and Tim Southee have not managed a single dismissal despite bowling 650 balls. It is surprising that R Ashwin has been mastered by Clarke but in Jadeja, he has found his Waterloo.

4. Ordered by Bowling SR (Low) in CLARKE-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Simon Jones RFM 47.8 7 69 3 23.0
Narsingh Deonarine rob 61.5 7 85 3 28.3
Shaminda Eranga RFM 64.0 5 104 3 34.7
Ravindra Jadeja lsp 58.5 6 190 5 38.0
James Anderson RFM 57.821 267 7 38.1
Amit Mishra rlb 81.3 3 121 3 40.3
Steve Harmison RFM 59.217 270 6 45.0
Mohammad Asif RFM 48.8 8 198 4 49.5
Dwayne Bravo RFM 75.0 8 156 3 52.0
Dale Steyn RF 41.219 376 7 53.7
Total for 10 batsmen 1836 44 41.7

Simon Jones, in the 2005 Ashes series had the complete measure of Clarke. A very surprising bowler at the top: Narsingh Deonaraine. Then there are Shaminda Eranga, and Jadeja. Is there a chink in Clarke's armour when it comes to fairly ordinary bowlers?

5. By Batting Scoring rate (High) in CLARKE-Bowler combination
BowlerTypeCareerScRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Imran Tahir rlb 55.7 5 109 119109.2 5045.9% 4238.5%1715.6%
Umesh Yadav RFM 55.7 6 153 122 79.710266.7% 3422.2%1811.8%
Morne Morkel RF 55.712 375 277 73.925467.7% 7921.1%4211.2%
R Ashwin rob 55.7 8 355 247 69.622763.9%10028.2%29 8.2%
Danish Kaneria rlb 55.7 8 221 152 68.813561.1% 7333.0%13 5.9%
Dale Steyn RF 55.719 376 253 67.325367.3% 9425.0%30 8.0%
Ashley Giles lsp 55.7 9 222 149 67.114364.4% 6027.0%19 8.6%
Chris Martin RFM 55.710 257 174 67.718572.0% 4919.1%24 9.3%
Chanaka Welegedara rob 55.7 7 123 83 67.5 9274.8% 1814.6%1310.6%
Monty Panesar lsp 55.7 4 136 89 65.4 8965.4% 3626.5%11 8.1%
Total for 10 batsmen 23271665 71.6

Clarke dismissed Imran Tahir from his presence. Look at the good scoring rates against Dale Steyn and Morne Morkel.

6. By Batting Scoring rate (Low) in CLARKE-Bowler combination
BowlerTypeCarScrRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Ravindra Jadeja lsp 55.7 6 190 72 37.915481.1% 2714.2% 9 4.7%
Paul Harris lsp 55.711 324 127 39.224274.7% 7121.9%11 3.4%
Darren Sammy RFM 55.7 7 125 49 39.2 9576.0% 2721.6% 3 2.4%
Dwayne Bravo RFM 55.7 8 156 64 41.012479.5% 2717.3% 6 3.8%
Fidel Edwards RF 55.7 6 124 52 41.9 9475.8% 2520.2% 5 4.0%
Amit Mishra rlb 55.7 3 121 52 43.0 9578.5% 2117.4% 5 4.1%
Mohammad Asif RFM 55.7 8 198 87 43.915980.3% 2814.1%11 5.6%
Doug Bracewell RFM 55.7 3 102 44 43.1 8280.4% 1413.7% 6 5.9%
Mohammad Amir RF 55.7 6 171 76 44.413679.5% 2715.8% 9 5.3%
Iain O'Brien RFM 55.7 3 109 48 44.0 8578.0% 1715.6% 7 6.4%
Total for 10 batsmen 1620 671 41.4

Clarke found Jadeja impossible to score off. And some fairly innocuous bowlers like Paul Harris and Darren Sammy contained him.

Kevin Pietersen

7. Ordered by Wickets in KEVIN PIETERSEN-Bowler combination
BowlerTypeBowAvgeInnsBallsRunsWicketsStrikeRateAvgeVsBowler
M Muralitharan rob22.73 9 235 168 6 39.2 28.00
Brett Lee RF 30.8217 324 228 6 54.0 38.00
Glenn McGrath RFM21.6413 270 135 5 54.0 27.00
Shane Warne rlb25.4218 521 308 5104.2 61.60
S Sreesanth RFM37.6113 231 142 5 46.2 28.40
Morne Morkel RF 29.9815 241 172 5 48.2 34.40
Peter Siddle RFM28.2311 208 103 5 41.6 20.60
Saeed Ajmal rob27.60 7 104 64 5 20.8 12.80
Shakib Al Hasan lsp32.75 7 172 110 4 43.0 27.50
Daniel Vettori lsp34.42 8 282 114 4 70.5 28.50
Total for 10 batsmen 25881544 50 51.8 30.88

It so happens that this is Muttiah Muralitharan's sum total of Pietersen's dismissals since Pietersen made his debut only in 2005. Then come three Australian bowlers. S Sreesanth is a surprise placement in this table. Steyn does not seem to be as successful against Pietersen as he is against Jonathan Trott.

8. Ordered by Balls bowled in KEVIN PIETERSEN-Bowler combination
BowlerTypeBowAvgeInnsBallsDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Shane Warne rlb25.4218 52136269.5%12624.2%35 6.7%
Brett Lee RF 30.8217 32421867.3% 8125.0%28 8.6%
Anil Kumble rlb29.6511 31022472.3% 6220.0%24 7.7%
Ishant Sharma RFM37.99 9 30620065.4% 7524.5%3210.5%
Daniel Vettori lsp34.42 8 28221777.0% 5419.1%11 3.9%
Glenn McGrath RFM21.6413 27020676.3% 4617.0%18 6.7%
Harbhajan Singh rob32.3810 26416462.1% 8231.1%18 6.8%
Zaheer Khan LFM32.3611 25019076.0% 4518.0%18 7.2%
Danish Kaneria rlb34.8011 24915461.8% 6726.9%2811.2%
Stuart Clark RFM23.8610 24718775.7% 5421.9% 7 2.8%

This list is led by the older bowlers.

9. Ordered by Bowling SR (High) in PIETERSEN-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Ishant Sharma RFM 68.4 9 306 1306.0
Stuart Clark RFM 54.710 247 1247.0
Daren Powell RFM 83.4 9 196 0196.0
Amit Mishra rlb 81.3 4 169 0169.0
Praveen Kumar RFM 59.7 4 164 1164.0
Anil Kumble rlb 66.011 310 2155.0
Chris Martin RFM 60.2 8 155 0155.0
Harbhajan Singh rob 68.510 264 2132.0
Makhaya Ntini RF 53.4 8 129 1129.0
Zaheer Khan LFM 59.711 250 2125.0
Total for 10 batsmen 2190 10219.0

There are six Indian bowlers in this table indicating that the Indian bowlers found it difficult to dismiss Pietersen quickly.

10. Ordered by Bowling SR (Low) in PIETERSEN-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Saeed Ajmal rob 62.1 7 104 5 20.8
M Muralitharan rob 55.0 9 235 6 39.2
Peter Siddle RFM 56.611 208 5 41.6
Shakib Al Hasan lsp 68.3 7 172 4 43.0
Fidel Edwards RF 58.212 175 4 43.8
S Sreesanth RFM 62.313 231 5 46.2
Umar Gul RFM 58.910 139 3 46.3
Morne Morkel RF 55.115 241 5 48.2
RP Singh LFM 63.3 7 152 3 50.7
Rangana Herath lsp 63.9 7 156 3 52.0
Total for 10 batsmen 1813 43 42.2

Saeed Ajmal had the measure of Pietersen, probably mainly because of the Tests in the UAE. There is really no top bowler, other than Muralitharan, in this table. Some unlikely bowlers like Sreesanth, RP Singh and Shakib Al Hassan. The top three bowlers are all off-spinners.

11. By Batting Scoring rate (High) in PIETERSEN-Bowler combination
BowlerTypeCareerScRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Dwayne Bravo RFM 62.5 4 122 103 84.4 7158.2% 3831.1%1310.7%
Dale Steyn RF 62.511 187 155 82.913572.2% 2412.8%3016.0%
Jerome Taylor RF 62.5 9 121 99 81.8 7259.5% 3528.9%1411.6%
Danish Kaneria rlb 62.511 249 201 80.715461.8% 6726.9%2811.2%
Makhaya Ntini RF 62.5 8 129 103 79.8 9069.8% 2418.6%1713.2%
Amit Mishra rlb 62.5 4 169 130 76.910562.1% 4426.0%2011.8%
Fidel Edwards RF 62.512 175 129 73.710761.1% 5330.3%16 9.1%
Chris Gayle rob 62.5 8 165 120 72.7 8652.1% 7143.0% 8 4.8%
Morne Morkel RF 62.515 241 172 71.416970.1% 5121.2%2410.0%
M Muralitharan rob 62.5 9 235 168 71.515164.3% 6326.8%21 8.9%
Total for 10 batsmen 17931380 77.0

To score at nearly 5 runs per over against Steyn must be Pietersen's crowning achievement.

12. By Batting Scoring rate (Low) in PIETERSEN-Bowler combination
BowlerTypeCarScrRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Jacob Oram RM 62.5 6 114 34 29.8 9583.3% 1714.9% 3 2.6%
Ben Hilfenhaus RFM 62.5 8 194 75 38.715780.9% 2914.9% 8 4.1%
Stuart Clark RFM 62.510 247 96 38.918775.7% 5421.9% 7 2.8%
Daniel Vettori lsp 62.5 8 282 114 40.421777.0% 5419.1%11 3.9%
Praveen Kumar RFM 62.5 4 164 76 46.312274.4% 3320.1% 9 5.5%
Chaminda Vaas LFM 62.510 159 74 46.512478.0% 2515.7%10 6.3%
Sulieman Benn lsp 62.5 7 168 79 47.011870.2% 4325.6% 7 4.2%
Peter Siddle RFM 62.511 208 103 49.516378.4% 3114.9%15 7.2%
Glenn McGrath RFM 62.513 270 135 50.020676.3% 4617.0%18 6.7%
Kyle Mills RM 62.5 6 104 54 51.9 7875.0% 2019.2% 6 5.8%
Total for 10 batsmen 1910 840 44.0

Who contained Pietersen? A very unlikely set of second-tier bowlers, led by Jacob Oram and Ben Hilfenhaus. Daniel Vettori and Sulieman Benn are the two left arm spinners in this list.

Alastair Cook

13. Ordered by Wickets in ALASTAIR COOK-Bowler combination
BowlerTypeBowAvgeInnsBallsRunsWicketsStrikeRateAvgeVsBowler
Ishant Sharma RFM37.9912 350 130 7 50.0 18.57
Morne Morkel RF 29.9818 428 175 6 71.3 29.17
Umar Gul RFM34.0714 262 120 6 43.7 20.00
Stuart Clark RFM23.86 8 132 35 5 26.4 7.00
Zaheer Khan LFM32.3615 384 200 4 96.0 50.00
Mitchell Johnson LFM30.9312 268 206 4 67.0 51.50
Peter Siddle RFM28.2315 386 146 4 96.5 36.50
R Ashwin rob28.53 7 510 221 4127.5 55.25
Trent Boult RFM29.12 9 221 62 4 55.2 15.50
Kyle Mills RM 33.02 8 148 69 3 49.3 23.00
Total for 10 batsmen 30891364 47 65.7 29.02

Ishant Sharma seems to have the opposition's captain and best batsman in his radar, always. After Ponting it is Alastair Cook now. The top bowlers are all pace bowlers, understandable since Cook is an opener.

14. Ordered by Balls bowled in ALASTAIR COOK-Bowler combination
BowlerTypeBowAvgeInnsBallsDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
R Ashwin rob28.53 7 51039677.6% 8717.1%27 5.3%
M Muralitharan rob22.73 8 45035879.6% 7817.3%14 3.1%
Ben Hilfenhaus RFM28.5115 44035079.5% 6514.8%27 6.1%
Morne Morkel RF 29.9818 42833778.7% 7617.8%19 4.4%
Peter Siddle RFM28.2315 38630779.5% 6316.3%17 4.4%
Zaheer Khan LFM32.3615 38430078.1% 5414.1%32 8.3%
Ishant Sharma RFM37.9912 35029383.7% 3810.9%21 6.0%
Jerome Taylor RF 35.6515 34925773.6% 6217.8%30 8.6%
Fidel Edwards RF 37.8717 33524272.2% 7121.2%22 6.6%
Dale Steyn RF 22.6612 32925978.7% 5215.8%19 5.8%

Ashwin is at the top because of the marathon innings Cook played in the eight Tests of 2011-12. The top two are off-spinners indicating the length of time Cook bats.

15. Ordered by Bowling SR (High) in COOK-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Ben Hilfenhaus RFM 61.415 440 1440.0
Pragyan Ojha lsp 70.9 7 317 1317.0
S Sreesanth RFM 62.310 308 0308.0
Harbhajan Singh rob 68.5 8 291 1291.0
Danish Kaneria rlb 67.8 7 265 1265.0
Tim Southee RFM 65.110 264 0264.0
Suranga Lakmal RFM108.2 7 252 1252.0
Sulieman Benn lsp 85.9 6 239 1239.0
M Muralitharan rob 55.0 8 450 2225.0
Xavier Doherty lsp131.1 3 200 0200.0
Total for 10 batsmen 3026 8378.2

Cook certainly had the measure of the Indian bowlers. And of Hilfenhaus: 440 balls and one wicket speaks volumes of Cook's mastery over Hilfenhaus.

16. Ordered by Bowling SR (Low) in COOK-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Mohammad Amir RF 56.2 6 78 3 26.0
Stuart Clark RFM 54.7 8 132 5 26.4
Vernon Philander RFM 36.8 6 104 3 34.7
Riyad Mahmudullah rob 78.5 6 106 3 35.3
Umar Gul RFM 58.914 262 6 43.7
Kyle Mills RM 66.0 8 148 3 49.3
Ishant Sharma RFM 68.412 350 7 50.0
Trent Boult RFM 59.4 9 221 4 55.2
Mohammad Asif RFM 48.8 9 166 3 55.3
Glenn McGrath RFM 52.010 176 3 58.7
Total for 10 batsmen 1743 40 43.6

Mohammad Amir and Stuart Clarke had excellent sub-30 strike rates against Cook. Mohammad Mahmudullah and Trent Boult are surprising presence in this list.

17. By Batting Scoring rate (High) in COOK-Bowler combination
BowlerTypeCareerScRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Mitchell Johnson LFM 47.412 268 206 76.916762.3% 7728.7%25 9.3%
S Sreesanth RFM 47.410 308 201 65.322272.1% 5517.9%3210.4%
Abdur Razzak lsp 47.4 4 115 73 63.5 6859.1% 4135.7% 6 5.2%
Chanaka Welegedara rob 47.4 5 134 82 61.210074.6% 2115.7%13 9.7%
Jerome Taylor RF 47.415 349 207 59.325773.6% 6217.8%30 8.6%
Shakib Al Hasan lsp 47.4 4 114 67 58.8 7263.2% 3631.6% 6 5.3%
Paul Harris lsp 47.4 8 184 107 58.212869.6% 4524.5%11 6.0%
Tillakaratne Dilshanrob 47.4 8 116 64 55.2 8270.7% 2622.4% 8 6.9%
Neil Wagner RFM 47.4 8 165 92 55.812072.7% 3420.6%11 6.7%
Dilhara Fernando RFM 47.4 5 176 98 55.712973.3% 3419.3%13 7.4%
Total for 10 batsmen 19291197 62.1

Cook had taken a liking to the inconsistent left arm fast bowling of Mitchell Johnson. And a few left arm spinners. But overall not as high figures as Pietersen has.

18. By Batting Scoring rate (Low) in COOK-Bowler combination
BowlerTypeCarScrRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Stuart Clark RFM 47.4 8 132 35 26.511284.8% 1712.9% 3 2.3%
Trent Boult RFM 47.4 9 221 62 28.119387.3% 2210.0% 7 3.2%
Chris Gayle rob 47.4 8 259 85 32.819776.1% 5922.8% 3 1.2%
M Muralitharan rob 47.4 8 450 152 33.835879.6% 7817.3%14 3.1%
Saeed Ajmal rob 47.4 5 254 88 34.621082.7% 3313.0%11 4.3%
Danish Kaneria rlb 47.4 7 265 91 34.320978.9% 4918.5% 7 2.6%
Jacques Kallis RFM 47.410 169 62 36.713680.5% 2514.8% 8 4.7%
Dwayne Bravo RFM 47.4 5 134 50 37.311082.1% 2115.7% 4 3.0%
Ishant Sharma RFM 47.412 350 130 37.129383.7% 3810.9%21 6.0%
Rangana Herath lsp 47.4 7 247 93 37.718474.5% 5622.7% 7 2.8%
Total for 10 batsmen 2481 848 34.2

Look at the way Muralitharan contained Cook. And Saeed Ajmal. This table is equally divided between spinners and pace bowlers.

Hashim Amla

19. Ordered by Wickets in HASHIM AMLA-Bowler combination
BowlerTypeBowAvgeInnsBallsRunsWicketsStrikeRateAvgeVsBowler
S Sreesanth RFM37.6115 234 155 6 39.0 25.83
Mitchell Johnson LFM30.9317 374 245 6 62.3 40.83
Harbhajan Singh rob32.3814 606 291 5121.2 58.20
Mohammad Asif RFM24.37 8 129 60 5 25.8 12.00
Peter Siddle RFM28.2317 465 173 4116.2 43.25
Steve Harmison RFM31.82 5 68 38 3 22.7 12.67
Stuart Broad RFM30.9415 437 226 3145.7 75.33
Abdur Rehman lsp28.41 6 232 117 3 77.3 39.00
Shane Shillingford rob31.23 5 102 42 3 34.0 14.00
Daniel Vettori lsp34.42 8 320 133 2160.0 66.50
Total for 10 batsmen 29671480 40 74.2 37.00

20. Ordered by Balls bowled in HASHIM AMLA-Bowler combination
BowlerTypeBowAvgeInnsBallsDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Harbhajan Singh rob32.3814 60642369.8%15926.2%24 4.0%
Peter Siddle RFM28.2317 46539484.7% 45 9.7%27 5.8%
Stuart Broad RFM30.9415 43733977.6% 7316.7%31 7.1%
James Anderson RFM29.7015 42931072.3% 8419.6%37 8.6%
Graeme Swann rob28.73 6 37526169.6% 9525.3%19 5.1%
Mitchell Johnson LFM30.9317 37426470.6% 7921.1%34 9.1%
Amit Mishra rlb43.30 3 32626280.4% 5416.6%10 3.1%
Daniel Vettori lsp34.42 8 32023473.1% 7423.1%12 3.8%
Zaheer Khan LFM32.3610 28020573.2% 5118.2%24 8.6%
Saeed Ajmal rob27.60 7 27417463.5% 8731.8%13 4.7%

Surprisingly, Harbhajan Singh is at the top: over 100 overs to Amla. Maybe the long innings played during their Indian tour was the cause. Stuart Broad, Anderson and Graeme Swann must have bowled a fair share of these balls during the triple century in 2012.

21. Ordered by Bowling SR (High) in AMLA-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Amit Mishra rlb 81.3 3 326 0326.0
Chris Martin RFM 60.211 251 0251.0
James Anderson RFM 57.815 429 2214.5
Danish Kaneria rlb 67.8 8 202 0202.0
Doug Bracewell RFM 60.3 7 195 1195.0
Graeme Swann rob 59.2 6 375 2187.5
Umar Gul RFM 58.910 184 0184.0
Ben Hilfenhaus RFM 61.4 7 164 1164.0
Daniel Vettori lsp 79.7 8 320 2160.0
Stuart Broad RFM 60.615 437 3145.7
Total for 10 batsmen 2883 11262.1

There are quality spinners in this lot, indicating the comfort with which Amla played spinners.

22. Ordered by Bowling SR (Low) in AMLA-Bowler combination
BowlerTypeBowCarStRateInnsBallsWicketsStrike rate
Steve Harmison RFM 59.2 5 68 3 22.7
Mohammad Asif RFM 48.8 8 129 5 25.8
Shane Shillingford rob 63.1 5 102 3 34.0
S Sreesanth RFM 62.315 234 6 39.0
Mitchell Johnson LFM 55.317 374 6 62.3
Abdur Rehman lsp 66.1 6 232 3 77.3
Total for 10 batsmen 2647 38 69.7

Steve Harmison had the measure of Amla. And Asif. Then comes Shane Shillingford. But the real surprise is Sreesanth: 6 wickets at below 40 balls per wicket. There are only 7 bowlers with balls per wicket values below 100, indicating how careful Amla has been. It may also be caused by the fewer number matches played by Amla.

23. By Batting Scoring rate (High) in AMLA-Bowler combination
BowlerTypeCareerScRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Nathan Lyon rob 52.6 8 134 106 79.1 7757.5% 4735.1%10 7.5%
S Sreesanth RFM 52.615 234 155 66.217273.5% 3715.8%2510.7%
Mitchell Johnson LFM 52.617 374 245 65.526470.6% 7921.1%34 9.1%
Ishant Sharma RFM 52.6 7 258 165 64.017768.6% 5822.5%23 8.9%
Tim Bresnan RFM 52.6 3 128 79 61.7 8969.5% 2922.7%10 7.8%
Shahadat Hossain RFM 52.6 5 106 64 60.4 7671.7% 2220.8% 9 8.5%
Virender Sehwag rob 52.6 5 113 68 60.2 7969.9% 2421.2%10 8.8%
Umar Gul RFM 52.610 184 110 59.813070.7% 4122.3%14 7.6%
Mark Gillespie RFM 52.6 4 103 61 59.2 7976.7% 1615.5% 9 8.7%
Saeed Ajmal rob 52.6 7 274 164 59.917463.5% 8731.8%13 4.7%
Total for 10 batsmen 19081217 63.8

Possibly the most impressive of these numbers is the one against Johnson. 374 balls at nearly 4 runs per over. This table is stuffed with pace bowlers.

24. By Batting Scoring rate (Low) in AMLA-Bowler combination
BowlerTypeCarScrRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Amit Mishra rlb 52.6 3 326 99 30.426280.4% 5416.6%10 3.1%
James Pattinson RFM 52.6 3 103 37 35.9 8683.5% 1615.5% 3 2.9%
Danish Kaneria rlb 52.6 8 202 74 36.614973.8% 4723.3% 6 3.0%
Peter Siddle RFM 52.617 465 173 37.239484.7% 45 9.7%27 5.8%
Anil Kumble rlb 52.6 7 224 83 37.117377.2% 4419.6% 7 3.1%
Mohammad Hafeez rob 52.6 7 129 52 40.3 9372.1% 3124.0% 5 3.9%
Shane Shillingford rob 52.6 5 102 42 41.2 7775.5% 2019.6% 5 4.9%
Daniel Vettori lsp 52.6 8 320 133 41.623473.1% 7423.1%12 3.8%
Chris Martin RFM 52.611 251 108 43.020180.1% 3714.7%14 5.6%
Mohammad Asif RFM 52.6 8 129 60 46.510581.4% 1410.9%10 7.8%
Total for 10 batsmen 2251 861 38.2

Amit Mishra contained Amla to around 30. And quite a few spinners in this lot, indicating that Amla played the spinners carefully.

These are is just samples of the type of insights which can be drawn. I have created an Excel sheet with 17 contemporary batsmen who have ball-by-ball data exceeding 80% and uploaded this. To download/view the document, a veritable treasure-trove of information, please CLICK HERE.

The 17 batsmen covered in this table are given below. The figures at the beginning indicate the quantum of ball-by-ball data available for this batsman.

BBB % Batsman selected 
	100.0 - Michael Clarke 
	100.0 - Kevin Pietersen 
	100.0 - Alastair Cook 
	100.0 - Hashim Amla 
	100.0 - Michael Hussey 
	100.0 - Virender Sehwag 
	100.0 - Graeme Smith 
	100.0 - Andrew Strauss 
	100.0 - AB de Villiers 
	93.9 - Kumar Sangakkara 
	90.6 - Chris Gayle 
	89.9 - Younis Khan 
	86.5 - Matthew Hayden 
	85.3 - VVS Laxman 
	80.8 - Adam Gilchrist 
	80.8 - Mahela Jayawardene 
	78.5 - Ricky Ponting 
	

I have given below a few exceptional situations from the tables of 17 batsmen. Let me also suggest that the interested readers can peruse the Excel sheet and come out with such interesting sidelights.

Balls bowled: Sangakkara -Ajmal 906 
	Shivnarine Chanderpaul-Harbhajan Singh 790 
	Kumar Sangakkara -Harbhajan Singh 742 
	

Runs scored: Mahela Jayawardene-Harbhajan Singh 431 Graeme Smith -James Anderson 411 Kumar Sangakkara -Saeed Ajmal 393

High St Rate: Kumar Sangakkara -Umar Gul 508 (1) Jacques Kallis -Anil Kumble 494 (1) Jacques Kallis -Daniel Vettori 475 (0) Shivnarine Chanderpaul-Steve Harmison 464 (1)

Low St Rate: Virender Sehwag -Graeme Swann 79 (5 @ 15.8) Ricky Ponting -Darren Gough 103 (5 @ 20.6) Kevin Pietersen -Saeed Ajmal 104 (5 @ 21.8) Virender Sehwag -James Anderson 109 (5 @ 21.9)

High Sc Rate: Adam Gilchrist -Steve Harmison 152 in 120 Chris Gayle -Andre Nel 147 in 129 Virender Sehwag -Ajantha Mendis 146 in 130

Low Sc Rate: Rahul Dravid -Glenn McGrath 26 in 170 Rahul Dravid -Michael Kasprowicz 20 in 130 Shivnarine Chanderpaul-Kyle Mills 20 in 124

Readers can, if they care, write on the types of analyses which could be done using these data. Please do not, however, ask for details of how Asad Shafiq faced up to Lonwabo Tsotsobe or Nick Compton's performance against Ashwin. Let it be of interest to all the readers.

My tuppennyworth on the happenings in the first Ashes Test.

1. Broad family does not walk. For that matter most families do not walk. This is the generation of stayers, not walkers.
2. Broad cannot be blamed. Michael Holding has a point. But there seems to be a fine line between cheating and blatantly taking advantage of rules.
3. Gilchrist, the batsman (I repeat, the batsman), walked and walked always. I remember Lara, after a very tough tour of India in 1994, walked at 91 for the faintest of touches. S Srinivas Venkataraghavan said that he was not going to give Lara out since he was not sure.
4. It is clear that the English are better at planning the DRS referrals than Australians. Their innate conservatism helps them a lot.
5. No colouring of the rules should allow a howler of this sort. It is easy to say things from the outside. But common-sense should take over.
6. Howlers are howlers and should be taken off the map. There are two options. Let the third umpire immediately call the umpire concerned and ask for a special referral. Then the established steps could follow.
7. Alternately or in addition, allow a team six referrals (reduced from the current total of 8), but for the entire match, batting, bowling and both innings combined.
8. It is also possible that the Ashton Agar stumping more than compensated for the Broad fiasco and Trott semi-fiasco. However three wrongs do not make two rights.
9. Irrespective of what happened earlier, were England ahead of Australia by 14 runs? Of course, yes.
10.The comment I appreciated most was that of McGrath. "If Australia had a review, Broad would have walked". Beautifully put. On the stumps, with unwavering accuracy and a very keen understanding of the situation. As the great guy bowled.

Give me one such Test any day and you can keep the entire IPL-6. I will throw in a few of these Tri-series also. I had written to Milind before play started on the last day "I hope there is a final twist in the Test today. Already there have been quite a few (217 ao, 117 for 9, Agar stumping, 280, 120 for 2 to 4, Ian Bell DRS, Broad incident, Clarke's faintest of touches (needed a magnifying glass to see that dab of white) leading to 2 more wickets)". Well there were probably three more twists: the 5 quick wickets, the missed run-out and catch and finally a DRS decision which was missed by Aleem Dar again. What a Test? Towards the end I was rooting for an Australian score of 310.

Shahid Afridi's magnificent performance, in probably his 27th comeback in a remarkable career, is probably the greatest all-round performance in the history of the ODI game. Paul Collingwood 's 6 for 31 and 112 were against Bangladesh. Viv Richards' 5 for 41 and 119 were against a rather weak New Zealand. But Afridi's efforts were against a very good West Indian side. Pakistan surely missed Afridi in the Champions Trophy.

Full post
Steyn, Anderson and Harbhajan versus the batsmen

A look at batsmen-versus-bowlers duels in Tests - who played the top bowlers best and which leading batsmen were susceptible - using available ball-by-ball data

This is the article, the first of a series, using ball-by-ball data, which the readers have repeatedly asked for during the past three years. I wish I could have done it in the previous avatar of my blog, where there would have been 500 comments and wonderful exchanges between readers. Now, I expect 35 comments, although, I presume many read the articles but do not comment because of the hassle associated with that process. Anyhow, nothing can be done about that.

A word of sincere thanks to ESPNcricinfo for the wonderful and sustained effort in doing the ball-by-ball commentary over the past 12 years. They have set a standard of excellence unreached in the past and possibly never in the future. All of us, the cricket lovers, owe them a lot. And all these, without paying a single paisa/penny/cent. May their tribe flourish!

The major credit for getting this analysis work completed should vest with Milind Pandit. I do not want to emphasise the technical aspects. My extensive "C" knowledge lets me mine the data extensively, make the numbers dance and create analysis of different types across and in depth. But I lack the required knowledge for extracting extensive data from the web. Milind is a master in this area. He extracted the ball-by-ball commentary, parsed the same, validated and cleared errors and sent me a 50MB file. A single sentence, but about six weeks of intense effort. I, then, incorporated that huge data segment into my database in my own format and this is the first of, hopefully, many articles to come, based on the huge and exhaustive data base.

I wanted this article to be a co-authored one, with Milind, but the reluctant contributor that he is, he declined. But I will say that this entire analysis would have been still-born but for Milind. May his tribe flourish too! This analysis is named AMB3.

We have complete ball-by-ball data for Tests 1546 to 2089, barring 1553. This fact has to be kept in mind when viewing all AMB3 analyses. We do not have complete data for many modern greats. But we will make by with what we have. After all, there is no need to be rigid in this regard. Whatever insights we draw are like gold dust.

I am going to do the following types of analyses over the next three to four months. Readers can contribute their bit in suggesting whether anything else can be done.

1. The top three modern bowlers: with over 85% of ball-by-ball data available (15 bowlers: Dale Steyn/James Anderson/Harbhajan Singh are featured).
2. The top three previous generation bowlers: with over 40% of ball-by-ball data available (12-15 bowlers: Muttiah Muralitharan/Shane Warne/Glenn McGrath will be featured).
3. The top three modern batsmen: with over 80-85% of ball-by-ball data available.
4. The top three previous generation batsmen: with over 40-45% of ball-by-ball data available.
5. Special analyses, to be decided as we go on, based on reader inputs.

The first analysis will cover the bowlers for whom over 80% of data is available and, wherever possible, over 200 Test wickets have been captured. I have selected 15 bowlers. This article features three top bowlers who are currently active. The selection of three is simple. Two bowlers select themselves. Dale Steyn and James Anderson are almost automatic selections. Only the myopic can question the inclusion of these two. The third selection is a headache. Harbhajan Singh, Graeme Swann, Steve Harmison, Mathew Hoggard, Rangana Herath and Mitchell Johnson present themselves for selection.

Johnson has as many off days as on days and his average is quite high. Herath's success is primarily in Sri Lanka: nearly 70% of his wickets have been captured there. Harmison and Hoggard have retired long back. That leaves us with Swann and Harbhajan. Swann is the traditional offspinner, probably the best after Erapalli Prasanna. He has succeeded all over the world, taken more wickets outside England. However Harbhajan, for whom we have just over 90% of data available, has captured 413 wickets overall and 360 wickets during the covered period. So he gets the nod. That leaves us with Steyn, Anderson and Harbhajan as the featured bowlers. Please note that the complete data for all 15 bowlers is available for downloading.

I am not going to spend too much time on explaining the types of analyses which are possible. It is better that we move on to the tables. Let us see the eight tables for Steyn. Even when commenting on the tables I will offer minimal comments.

D W Steyn

1. Ordered by Wickets in DW STEYN-Batsman combination
BatsmanBatAvgeInnsBallsRunsWicketsStrikeRateAvgeVsBowler
Mohammad Hafeez 35.1214 130 87 8 16.2 10.88
MJ Clarke 52.3419 376 253 7 53.7 36.14
MEK Hussey 51.5317 228 89 7 32.6 12.71
IJL Trott 50.0111 150 65 7 21.4 9.29
V Sehwag 49.3416 257 208 7 36.7 29.71
Harbhajan Singh 18.3610 59 34 7 8.4 4.86
BB McCullum 35.3915 224 129 6 37.3 21.50
Younis Khan 50.7413 293 149 5 58.6 29.80
SM Katich 45.0312 291 162 5 58.2 32.40
RT Ponting 51.8714 228 144 4 57.0 36.00
Total for 10 batsmen 22361320 63 35.5 20.95

An innings is counted when the bowler bowls at least a single ball to the batsman. Mohammad Hafeez is the only batsman whose wicket has been captured eight times, that too very economically. Both BpW (Balls-per-Wicket: Strike Rate) and Avge figures are way below the batsman career figures. There are many batsmen at seven wickets. The most noteworthy one is Jonathan Trott, who has been dismissed by Steyn, once every 22 balls. His average against Steyn is around 20% of his career figure. Out of this lot, no one has even exceeded 60 balls per wicket. The top ten batsmen in this regard have been dismissed at a very low strike rate of 35.5. No wonder that Steyn's career strike rate is 41.1.

2. Ordered by Balls bowled in DW STEYN-Batsman combination
BatsmanBatAvgeInnsBallsDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
MJ Clarke 52.3419 37625367.3% 9425.0%30 8.0%
AJ Strauss 40.9116 36028178.1% 5114.2%28 7.8%
AN Cook 49.1812 32925978.7% 5215.8%19 5.8%
IR Bell 45.5813 31024177.7% 4915.8%20 6.5%
SR Tendulkar 53.8711 31023977.1% 5016.1%21 6.8%
Younis Khan 50.7413 29322576.8% 5117.4%19 6.5%
SM Katich 45.0312 29121473.5% 5920.3%19 6.5%
V Sehwag 49.3416 25717266.9% 5119.8%3413.2%
S Chanderpaul 51.82 9 23118278.8% 4419.0% 7 3.0%
RT Ponting 51.8714 22816672.8% 4519.7%17 7.5%

Michael Clarke has faced the maximum number of balls and has scored off a third of the balls he faced. Most of the others have been quite circumspect, including Sachin Tendulkar who has faced 310 balls.

3. Ordered by Runs scored in DW STEYN-Batsman combination
BatsmanBatAvgeInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
MJ Clarke 52.3419 376 253 67.325367.3% 9425.0%30 8.0%
V Sehwag 49.3416 257 208 80.917266.9% 5119.8%3413.2%
AJ Strauss 40.9116 360 182 50.628178.1% 5114.2%28 7.8%
SM Katich 45.0312 291 162 55.721473.5% 5920.3%19 6.5%
KP Pietersen 49.0111 187 155 82.913572.2% 2412.8%3016.0%
Younis Khan 50.7413 293 149 50.922576.8% 5117.4%19 6.5%
PJ Hughes 33.0010 220 149 67.715470.0% 4319.5%2310.5%
SR Tendulkar 53.8711 310 149 48.123977.1% 5016.1%21 6.8%
AN Cook 49.1812 329 147 44.725978.7% 5215.8%19 5.8%
IR Bell 45.5813 310 144 46.524177.7% 4915.8%20 6.5%

Clarke is on top with a good scoring rate. However look at Virender Sehwag who has an excellent 80+ scoring rate. Kevin Pietersen is still better at 83.

4. Ordered by Bowling strike rate (High) in DW STEYN-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
Azhar Ali 99.6 8 228 1228.0
PJ Hughes 60.010 220 1220.0
KC Sangakkara 97.1 8 203 1203.0
AJ Strauss 80.816 360 2180.0
W Jaffer 69.7 8 161 1161.0
PD Collingwood 79.7 5 153 0153.0
TT Samaraweera 88.2 6 150 0150.0
S Chanderpaul 100.5 9 231 2115.5
AN Cook 97.112 329 3109.7
SP Fleming 82.8 8 215 2107.5
Total for 10 batsmen 2250 13173.1

These are the batsmen who sold their wickets very dearly to Steyn. And they succeeded. For the division in this analysis 0 wkt is taken as 1. Who would have expected Azhar Ali and Phillip Hughes to top the table? Probably the most praiseworthy is Andrew Strauss who has a BpW figure of 180 over 360 balls. Paul Collingwood and Thilan Samaraweera were bloody-minded. They told Steyn, "You are the best bowler in the world. But you will not dismiss us". It took 173 balls for Steyn to get rid of each of these obdurate batsmen, nearly four times his career strike rate.

5. Ordered by Bowling Strike rate (Low - Top order batsmen) in DW STEYN-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
Mohammad Ashraful 49.9 6 26 3 8.7
NJ Astle 69.2 6 33 3 11.0
N Deonarine 66.0 4 59 4 14.8
TM Dilshan 57.8 8 50 3 16.7
Mohammad Hafeez 60.314 130 8 16.2
AF Giles 37.9 5 53 3 17.7
GP Swann 25.4 8 78 4 19.5
IJL Trott 98.211 150 7 21.4
SB Styris 64.4 9 99 4 24.8
Tamim Iqbal 61.4 8 97 4 24.2
Total for 10 batsmen 775 43 18.0

Now for the low strike rates. Three wickets are necessary to be considered as minimum for this table. To get proper insights I have split this table into two. One for the proper batsmen, averages exceeding 20 and the other for late order batsmen. Mohammad Hafeez, Nathan Astle, Tillakaratne Dilshan and Trott are the leading batsmen in this table. All have lost wickets more frequent than once every 25 balls. These batsmen were dismissed at around 40% of Steyn's career strike rate.

6. Ordered by Bowling Strike rate (Low - Late order batsmen) in DW STEYN-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
IE O'Brien 16.7 3 10 3 3.3
CS Martin 5.9 6 18 4 4.5
RP Singh 14.5 3 21 3 7.0
Harbhajan Singh 23.810 59 7 8.4
DAJ Bracewell 22.8 5 36 4 9.0
NM Lyon 22.1 5 49 3 16.3
JE Taylor 23.5 6 56 3 18.7
PM Siddle 28.311 95 3 31.7
Total for 10 batsmen 344 30 11.5

Are we seeing it correctly? There is a late-order batsman who is above our dear Chris Martin. Iain O'Brien faced only ten balls and was dismissed three times. Martin was dismissed four times but he faced a whopping eight balls more. Look at how competently Peter Siddle has batted.

7. Ordered by Batting Scoring rate (High) in DW STEYN-Batsman combination
BatsmanCareerScRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
CH Gayle 59.8 9 122 115 94.3 7662.3% 3125.4%1814.8%
MG Johnson 58.611 148 133 89.9 9966.9% 2919.6%2114.2%
KP Pietersen 62.811 187 155 82.913572.2% 2412.8%3016.0%
V Sehwag 82.216 257 208 80.917266.9% 5119.8%3413.2%
DL Vettori 58.110 127 94 74.0 8869.3% 2418.9%1511.8%
MJ Prior 63.0 9 135 101 74.8 8965.9% 3123.0%1511.1%
MJ Clarke 55.819 376 253 67.325367.3% 9425.0%30 8.0%
PJ Hughes 53.810 220 149 67.715470.0% 4319.5%2310.5%
Mohammad Hafeez 53.614 130 87 66.9 9774.6% 1914.6%1410.8%
KC Sangakkara 54.0 8 203 131 64.515073.9% 3316.3%2110.3%
Total for 10 batsmen 19051426 74.9

These are the batsmen who decided that even if it was Steyn bowling, he had to go for runs. Chris Gayle, Pietersen and Sehwag are predictably the top placed batsmen, with scoring rates exceeding 80. But they have a usurper in the middle. Somehow, Mitchell Johnson has taken a liking for Steyn's bowling, scoring at 90. Look at the boundary ball percentage of Pietersen, with 16% and Gayle/Johnson, at 14%. That means Pietersen hit a boundary for each over Steyn bowled to him. Steyn's propensity to attack is shown by the very high scoring rate of these ten batsmen.

8. Ordered by Batting Scoring rate (Low) in DW STEYN-Batsman combination
BatsmanCarScrRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
D Ganga 38.9 6 106 23 21.7 9185.8% 1413.2% 1 0.9%
KS Williamson 40.3 8 151 37 24.513086.1% 1811.9% 3 2.0%
Misbah-ul-Haq 40.710 207 58 28.018388.4% 16 7.7% 9 4.3%
TT Samaraweera 46.9 6 150 50 33.312784.7% 1812.0% 6 4.0%
MHW Papps 35.3 7 101 37 36.6 8685.1% 9 8.9% 6 5.9%
S Chanderpaul 42.9 9 231 90 39.018278.8% 4419.0% 7 3.0%
MJ Guptill 43.410 190 73 38.416084.2% 18 9.5%12 6.3%
Junaid Siddique 41.4 7 114 45 39.5 9179.8% 1714.9% 6 5.3%
MEK Hussey 50.117 228 89 39.018581.1% 3314.5%12 5.3%
W Jaffer 48.1 8 161 67 41.613282.0% 2113.0% 9 5.6%
Total for 10 batsmen 1639 569 34.7

These batsmen hung on for dear life. It did not matter to them that the dot-ball percentage was 85+ or that they hit a boundary every 25 balls but survival was a must. Shivnarine Chanderpaul has played maximum number of balls in this group. Michael Hussey follows closely.

J M Anderson

9. Ordered by Wickets in JM ANDERSON-Batsman combination
BatsmanBatAvgeInnsBallsRunsWicketsStrikeRateAvgeVsBowler
SR Tendulkar 53.8723 350 208 9 38.9 23.11
JH Kallis 56.1022 419 177 7 59.9 25.29
KC Sangakkara 56.9910 241 147 6 40.2 24.50
MJ Clarke 52.3419 255 153 6 42.5 25.50
GC Smith 48.6327 701 411 6116.8 68.50
MV Boucher 30.3021 273 161 6 45.5 26.83
R Dravid 52.3118 432 197 5 86.4 39.40
V Sehwag 49.3414 109 120 5 21.8 24.00
AG Prince 41.6513 247 113 5 49.4 22.60
RT Ponting 51.8719 347 233 4 86.8 58.25
Total for 10 batsmen 33741920 59 57.2 32.54

Tendulkar leading the table is not a surprise seeing that eight Tests have been played during the past two years. Note the high quality of Anderson wickets: almost all are top-order batsmen. Anderson has taken nearly ten overs for each of these wickets.

10. Ordered by Balls bowled in JM ANDERSON-Batsman combination
BatsmanBatAvgeInnsBallsDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
GC Smith 48.6327 70150471.9%14220.3%57 8.1%
R Dravid 52.3118 43234980.8% 5011.6%33 7.6%
HM Amla 52.1215 42931072.3% 8419.6%37 8.6%
SR Watson 35.3415 42733879.2% 5512.9%34 8.0%
MEK Hussey 51.5317 42432376.2% 7517.7%26 6.1%
JH Kallis 56.1022 41933780.4% 6014.3%23 5.5%
G Gambhir 44.1916 39833183.2% 4310.8%24 6.0%
AB de Villiers 50.5116 39330377.1% 6616.8%26 6.6%
SR Tendulkar 53.8723 35026074.3% 5616.0%34 9.7%
RT Ponting 51.8719 34724570.6% 7020.2%33 9.5%

England and South Africa seem to have played quite often. The combination of Anderson-Graeme Smith is over 700 balls. This is way above the next highest. This collection is a top-ten list of batsmen over the past few years.

11. Ordered by Runs scored in JM ANDERSON-Batsman combination
BatsmanBatAvgeInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
GC Smith 48.6327 701 411 58.650471.9%14220.3%57 8.1%
HM Amla 52.1215 429 254 59.231072.3% 8419.6%37 8.6%
RT Ponting 51.8719 347 233 67.124570.6% 7020.2%33 9.5%
SR Watson 35.3415 427 217 50.833879.2% 5512.9%34 8.0%
MEK Hussey 51.5317 424 214 50.532376.2% 7517.7%26 6.1%
SR Tendulkar 53.8723 350 208 59.426074.3% 5616.0%34 9.7%
MS Dhoni 39.7119 347 201 57.925874.4% 5917.0%32 9.2%
R Dravid 52.3118 432 197 45.634980.8% 5011.6%33 7.6%
AB de Villiers 50.5116 393 193 49.130377.1% 6616.8%26 6.6%
RR Sarwan 40.0111 312 190 60.923374.7% 4815.4%3210.3%

This follows a similar sequence to the balls played table. Graeme Smith is the runaway leader, with 411 runs. Note how quickly Ricky Ponting has scored.

12. Ordered by Bowling strike rate (High) in JM ANDERSON-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
RR Sarwan 81.111 312 1312.0
HM Amla 90.915 429 2214.5
TT Samaraweera 88.2 8 204 1204.0
AB de Villiers 82.016 393 2196.5
SM Katich 85.7 9 183 1183.0
AN Petersen 72.7 5 172 1172.0
S Chanderpaul 100.514 339 2169.5
G Kirsten 95.4 7 167 0167.0
CA Pujara 101.9 5 160 0160.0
MN Samuels 71.3 4 158 0158.0
Total for 10 batsmen 2517 10251.7

Ramnaresh Sarwan has lasted 312 balls and been dismissed once. Hashim Amla has been equally effective, lasting 429 balls for two dismissals. The high numbers for Amla, AB de Villiers, Alviro Petersen and Smith (117) makes me think that Anderson was not that successful against the South African top order. Gary Kirsten, Cheteshwar Pujara and Marlon Samuels have lasted 150 balls and did not lose their wicket to Anderson. Well over 40 overs were required for Anderson to capture each of these tough-to-dislodge batsmen.

13. Ordered by Bowling Strike rate (Low - Top order batsmen) in JM ANDERSON-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
Shoaib Malik 67.0 3 33 3 11.0
AJ Redmond 56.1 6 60 4 15.0
HDRL Thirimanne 61.8 6 69 4 17.2
V Sehwag 58.014 109 5 21.8
SK Raina 49.7 4 70 3 23.3
DG Brownlie 63.5 7 102 4 25.5
JM How 43.710 140 4 35.0
SPD Smith 61.3 6 110 3 36.7
SR Tendulkar 89.623 350 9 38.9
Imran Farhat 64.5 8 152 4 38.0
Total for 10 batsmen 1195 43 27.8

The "batsmen" are included in this table. The really top batsmen in this collection are the two Indian stalwarts. Sehwag's discomfiture against the lateral movement is well known. Also, this reflects the past eight Tests. However Tendulkar's record against Anderson is surprising. His BpW is below 50, contrast this with his 100+ BpW against Steyn. 26 balls per wicket is a fairly low strike rate considering that these were all top-flight batsmen.

14. Ordered by Bowling SR (Low - Late order batsmen), ANDERSON-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
Umar Gul 18.0 5 48 3 16.0
Z Khan 18.6 7 49 3 16.3
PM Siddle 28.310 87 4 21.8
DW Steyn 25.4 7 78 3 26.0
LMP Simmons 37.1 6 83 3 27.7
Total for 10 batsmen 345 16 21.6

Nothing specific to say here.

15. Ordered by Batting Scoring rate (High) in JM ANDERSON-Batsman combination
BatsmanCareerScRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
V Sehwag 82.214 109 120110.1 6156.0% 2623.9%2220.2%
BB McCullum 60.412 132 136103.0 7859.1% 3627.3%1914.4%
LRPL Taylor 57.713 225 187 83.115568.9% 4118.2%3214.2%
HH Gibbs 50.3 8 190 159 83.713772.1% 2513.2%3116.3%
BJ Haddin 57.412 206 151 73.314469.9% 4119.9%2210.7%
HD Rutherford 65.7 8 137 97 70.8 9871.5% 2216.1%1712.4%
RT Ponting 58.719 347 233 67.124570.6% 7020.2%33 9.5%
G Kirsten 43.4 7 167 111 66.512373.7% 2615.6%1810.8%
CH Gayle 59.811 160 101 63.111974.4% 2616.2%1610.0%
JM How 50.410 140 86 61.410776.4% 1913.6%1510.7%
Total for 10 batsmen 18131381 76.2

Sehwag and McCullum exceeded 100. Sehwag hit a boundary every 5 balls against Anderson but also lost his wicket every 20 balls. One scatter-brained batting strategy indeed. McCullum at least lost his wicket only 3 times. If anything, Anderson was more expensive than Steyn.

16. Ordered by Batting Scoring rate (Low) in JM ANDERSON-Batsman combination
BatsmanCarScrRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
D Ramdin 48.3 7 182 45 24.715685.7% 2212.1% 4 2.2%
MJ North 48.1 8 195 50 25.617388.7% 16 8.2% 7 3.6%
PG Fulton 42.4 9 295 88 29.825787.1% 26 8.8%12 4.1%
AN Petersen 50.9 5 172 52 30.214785.5% 17 9.9% 8 4.7%
Imran Farhat 48.3 8 152 49 32.213186.2% 12 7.9% 9 5.9%
Azhar Ali 39.110 241 81 33.620384.2% 2811.6%11 4.6%
Misbah-ul-Haq 40.7 4 107 36 33.6 8680.4% 1816.8% 3 2.8%
HAPW Jayawardene 50.1 7 102 37 36.3 8583.3% 1312.7% 4 3.9%
BP Nash 43.3 8 121 44 36.410082.6% 1613.2% 6 5.0%
MN Samuels 48.5 4 158 60 38.012881.0% 2213.9% 8 5.1%
Total for 10 batsmen 1725 542 31.4

These are the wicket-preservers by batting slowly. No real surprises. Even this scoring rate is not too bad, nearly 2 RpO.

Harbhajan Singh

Now let us see the tables for Harbhajan Singh. First a caveat. We have ball-by-ball data for just over 90% of balls bowled by Harbhajan. Unfortunately the first 11 Tests, in which he captured 53 wickets, including the fabulous 2001 series, are not included. So this is not a complete analysis. However I have plumped for Harbhajan for reasons already discussed.

17. Ordered by Wickets in HARBHAJAN SINGH-Batsman combination
BatsmanBatAvgeInnsBallsRunsWicketsStrikeRateAvgeVsBowler
ML Hayden 50.7415 356 226 7 50.9 32.29
JH Kallis 56.1018 676 382 6112.7 63.67
DW Steyn 13.97 8 75 35 6 12.5 5.83
HM Amla 52.1214 606 291 5121.2 58.20
RT Ponting 51.8716 340 227 5 68.0 45.40
SM Katich 45.0314 432 177 5 86.4 35.40
LRPL Taylor 42.22 6 209 100 5 41.8 20.00
WW Hinds 33.01 6 195 99 5 39.0 19.80
Kamran Akmal 30.7910 227 119 5 45.4 23.80
M Morkel 13.69 8 123 54 5 24.6 10.80
Total for 10 batsmen 32391710 54 60.0 31.67

Hayden has been dismissed by Harbhajan 7 times. Add to this the 2 dismissals during the 2001 series. Similarly Ponting was dismissed 5 times. This becomes 10 dismissals since he lost his wicket every time in 2001 to Harbhajan. However it is clear that Harbhajan has bought his wickets, at a price. There is very little difference Harbhajan's career strike rate and the strike rate against this collection.

18. Ordered by Balls bowled in HARBHAJAN SINGH-Batsman combination
BatsmanBatAvgeInnsBallsDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
S Chanderpaul 51.8218 79063280.0%13817.5%20 2.5%
KC Sangakkara 56.9918 74257477.4%14419.4%27 3.6%
JH Kallis 56.1018 67641260.9%24235.8%22 3.3%
DPMD Jayawardene 49.5720 64939560.9%21733.4%38 5.9%
HM Amla 52.1214 60642369.8%15926.2%24 4.0%
Younis Khan 50.7410 54136868.0%13024.0%43 7.9%
MJ Clarke 52.3423 52737270.6%13525.6%20 3.8%
MEK Hussey 51.5314 48235673.9%10922.6%17 3.5%
SM Katich 45.0314 43233677.8% 7517.4%21 4.9%
AB de Villiers 50.5112 39426767.8%10927.7%18 4.6%

Did India and Sri Lanka play each other so many times in Tests also? Jayawardene and Sangakkara have together faced nearly 1400 balls of Harbhajan. Similarly Kallis and Amla have clocked over 1250 balls together.

19. Ordered by Runs scored in HARBHAJAN SINGH-Batsman combination
BatsmanBatAvgeInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
DPMD Jayawardene 49.5720 649 431 66.439560.9%21733.4%38 5.9%
JH Kallis 56.1018 676 382 56.541260.9%24235.8%22 3.3%
Younis Khan 50.7410 541 332 61.436868.0%13024.0%43 7.9%
HM Amla 52.1214 606 291 48.042369.8%15926.2%24 4.0%
KC Sangakkara 56.9918 742 287 38.757477.4%14419.4%27 3.6%
S Chanderpaul 51.8218 790 260 32.963280.0%13817.5%20 2.5%
MJ Clarke 52.3423 527 239 45.437270.6%13525.6%20 3.8%
RT Ponting 51.8716 340 227 66.820760.9%10831.8%25 7.4%
ML Hayden 50.7415 356 226 63.523866.9% 9125.6%28 7.9%
TM Dilshan 40.9913 308 221 71.818861.0% 9731.5%23 7.5%

Similar pattern like balls. The Sri Lankan duo and the South African duo have scored tons of runs. Jayawardene at a very good scoring rate. Look at Chanderpaul's scoring rate.

20. Ordered by Bowling SR (High), HARBHAJAN SINGH-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
S Chanderpaul 100.518 790 2395.0
AN Cook 97.1 8 291 1291.0
GW Flower 81.4 8 277 0277.0
Younis Khan 89.410 541 2270.5
MP Vaughan 76.1 6 264 0264.0
BB McCullum 55.1 8 252 1252.0
Misbah-ul-Haq 88.6 6 248 0248.0
KC Sangakkara 97.118 742 3247.3
AB de Villiers 82.012 394 2197.0
IR Bell 79.7 9 181 1181.0
Total for 10 batsmen 3980 12331.7

Harbhajan to Chanderpaul must be the slowest running movie ever made. Nothing happening ever. 790 balls, a mere 258 runs and a wicket every 395 balls. And look at Cook, a wicket every 290 balls. And Flower, and Younis, and Vaughan: all clocking over 250 balls per wicket. Harbhajan surely had a lot of patience. 55 overs per wkt: we are going past a typically long spell by a bowler in an innings.

21. Ordered by Bowling SR (Low - Top order batsmen), HARBHAJAN-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
JP Duminy 70.0 3 13 3 4.3
SCJ Broad 33.9 4 39 3 13.0
AN Petersen 72.7 5 75 4 18.8
JDP Oram 59.9 5 75 3 25.0
ADR Campbell 62.8 6 86 3 28.7
SB Styris 64.4 6 133 4 33.2
RD Jacobs 48.1 5 102 3 34.0
MJ North 69.5 3 107 3 35.7
WW Hinds 68.2 6 195 5 39.0
A Flower 95.0 6 125 3 41.7
Total for 10 batsmen 950 34 27.9

Harbhajan had to start his bowling run and Duminy would inform his colleagues in the pavilion to hold the calls. A top class batsman averaging a mere 4 balls per wicket. Later there is a reference to Swann vs Prince. What is with South African batsman against quality off-spinners? And Alviro clocking at below 20 BpW. These leaden-footed batsmen were at least dismissed at around once every five overs.

22. Ordered by Bowling Strike rate (Low - Late order batsmen) in HARBHAJAN-Batsman combination
BatsmanCareer Balls/InnsInnsBallsWicketsStrike rate
Danish Kaneria 8.8 4 14 3 4.7
MS Kasprowicz 17.9 4 17 3 5.7
GD McGrath 11.4 5 18 3 6.0
A Sanford 19.3 4 24 4 6.0
DW Steyn 25.4 8 75 6 12.5
M Muralitharan 10.910 51 4 12.8
PL Harris 28.3 9 54 4 13.5
M Dillon 20.3 9 54 4 13.5
PT Collins 14.9 8 76 5 15.2
MJ Hoggard 22.7 8 56 3 18.7
Total for 10 batsmen 439 39 11.3

It must be said that Danish Kaneria has done better than Duminy. And Steyn the batsman had no answer for Harbhajan the bowler. And let me add that Steyn dismissed Harbhajan 7 times in 59 balls. Each could call the other his bunny.

23. Ordered by Batting Scoring rate (High) in HARBHAJAN SINGH-Batsman combination
BatsmanCareerScRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
AC Gilchrist 82.0 9 139 112 80.6 7755.4% 5136.7%11 7.9%
JL Langer 54.2 5 170 128 75.310762.9% 4627.1%1710.0%
TM Dilshan 65.513 308 221 71.818861.0% 9731.5%23 7.5%
MJ Prior 63.0 6 149 104 69.8 8154.4% 6040.3% 8 5.4%
HAPW Jayawardene 50.110 236 156 66.115063.6% 7230.5%14 5.9%
RT Ponting 58.716 340 227 66.820760.9%10831.8%25 7.4%
KP Pietersen 62.810 264 176 66.716462.1% 8231.1%18 6.8%
Inzamam-ul-Haq 54.0 4 109 72 66.1 6862.4% 3330.3% 8 7.3%
DPMD Jayawardene 51.520 649 431 66.439560.9%21733.4%38 5.9%
ML Hayden 60.115 356 226 63.523866.9% 9125.6%28 7.9%
Total for 10 batsmen 27201853 68.1

As expected Harbhajan was attacked by Gilchrist and Langer. Gilchrist gave his wicket away thrice while Langer was dismissed only once. Dilshan's attacking was over much higher number of balls. Harbhajan won 4 of these battles with Dilshan. Harbhajan was relatively more economical even against the free-scoring batsmen.

24. Ordered by Batting Scoring rate (Low) in HARBHAJAN SINGH-Batsman combination
BatsmanCarScrRtInnsBallsRunsScoring RateDot Balls% of total1/2/3 run balls% of totalBoundary balls% of total
Salman Butt 47.2 6 146 21 14.413290.4% 13 8.9% 1 0.7%
BJ Haddin 57.4 6 110 28 25.5 8980.9% 2018.2% 1 0.9%
MH Richardson 37.7 4 162 44 27.213080.2% 2917.9% 3 1.9%
MJ Guptill 43.4 4 114 33 28.9 9381.6% 1916.7% 2 1.8%
GW Flower 34.5 8 277 83 30.022480.9% 4616.6% 7 2.5%
TR Gripper 32.7 2 100 29 29.0 8282.0% 1515.0% 3 3.0%
AJ Hall 46.1 3 133 41 30.811183.5% 1914.3% 3 2.3%
AG Prince 43.711 229 69 30.118781.7% 3615.7% 6 2.6%
JEC Franklin 37.4 4 126 38 30.210885.7% 1310.3% 5 4.0%
MA Butcher 42.9 7 269 82 30.521881.0% 4416.4% 7 2.6%
Total for 10 batsmen 1666 468 28.1

Nothing important here. Most of these batsmen were uncomfortable facing top quality spin and took the safer way out. They were bottled up for less than 1.8 RpO.

These are is just samples of the type of insights which can be drawn. I have created an Excel sheet with 15 contemporary bowlers who have ball-by-ball data exceeding 80% and uploaded this. To download/view the document, a veritable treasure-trove of information, please CLICK HERE.

I have given below a few exceptional situations from the tables of 15 bowlers. Let me also suggest that the interested readers can peruse the Excel sheet and come out with such interesting sidelights.

- Take the Swann-Prince combination. This is something weird. Prince played 5 balls from Swann, had 2 dot balls and lost his wickets 3 times. And this happened after he had played 94, 28 and 44 balls in the three innings. That was some magic that Swann wove, probably more than what Warne did to Cullinan.
- The maximum number of balls bowled has been by Ajmal to Sangakkara. He bowled 906 balls, nearly two days of bowling.
- Harmison's single wicket of Chanderpaul cost 239 runs while Ntini's single dismissal of Lara cost 225 runs.
- Anderson-Tendulkar, Ntini-Trescothick and Ntini-Hayden combinations have ended in 9 dismissals. Let us not forget the 10 dismissals of Ponting by Harbhajan.
- Harmison bowled 464 balls to Chanderpaul and got 1 wicket. Harbhajan-Chanderpaul was 790 (2 wkts-395), Hoggard-Yousuf was 378, Johnson-de Villiers was 383, Ntini-Lara was 312, Anderson-Sarwan was 312 and Ajmal-Sangakkara was 906 (3 wkts-302).
- Anderson was hit 57 times for a boundary by Graeme Smith. Ntini was carted to the fence 53 times by Ponting and Trescothick. Lee was also despatched 50 times by Trescothick. But the most awesome performance was when Harmison bowled to Gayle. 48 boundaries were hit but at 15.8%, nearly one every over.

The 15 bowlers covered in this table are given below. The figures at the beginning indicate the quantum of ball-by-ball data available for this bowler.

BBB %   Bowler selected
100.0 - Steyn
100.0 - Anderson
 90.2 - Harbhajan Singh
100.0 - Swann
100.0 - Harmison
 99.4 - Hoggard
 88.0 - Ntini
 95.9 - Zaheer Khan
 91.7 - Lee
100.0 - Johnson
 90.5 - Martin
 95.1 - Herath
 96.9 - Danish Kaneria
100.0 - Saeed Ajmal
100.0 - FH Edwards

The last two players have been exempted from the 200-wicket limit since there is no West Indian bowler who has crossed 200 wickets recently and Ajmal is an intriguing bowler. Kaneria has captured 261 Test wickets and I am not going to sit in moral judgement on subsequent happenings, on and off the field. On field, as a Test player, he performed very well and that is enough for me.

Readers can, if they care, write on the types of analyses which could be done using these data. Please do not, however, ask for details of how RA Austin bowled to Raqibul Haasan or about MM Patel's performance against McIntosh. Let it be of interest to all the readers. I would intersperse these articles with the other articles so that I can handle these myself. These articles take a lot off me in view of the number of tables and writing.

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All the quirky Test numbers

What's the lowest score that's never been made? How obsessed are batsmen with 100s? What's the most popular all-out total? A look at these, and many more unusual stats

This is a very different article. For some time now I have wanted to take an irreverent look at some of the numbers relating to Tests. I have done enough of serious number-crunching and analytical articles. This article is going to be fun. At the same time there are enough interesting sparks to make the readers think.

As such, I want to only add in one caveat, in the form of a message. I understand that the self-styled academics and fault-finders will not find this article interesting, not that they found anything of value in other articles. My message to them is, if you do not have fun with this type of analysis, it is your problem. Do not transfer that problem to others by making inane and worthless comments. My thanks, in advance, for this consideration.

I am going to look at Test batting, purely from the numbers point of view. In this article there might be a player or two mentioned, that will be all. I will look at the batsman scores, team scores, team fall of wickets, the related frequencies, the limits of these number of occurrences, the surprises and the patterns, with no reference to the executors of these numbers. I can assure you that you will find enough interesting gems in this potpourri of information. My apologies also for some haphazard presentation. The nature of analysis is such.

Batsman scores

Brian Lara (this is the only reference to an individual player in this article) scored an unbeaten 400. Nearly 10,000 batsmen scored the grand total of 0, some unbeaten. Between 0 and 400, 298 scores have been reached by batsmen. That means there are 103 scores yet to be reached. This was news to me also. This amounts to more than 25% of all scores of 400 and lower.

Let this be the starting point. Let us now look at these score distributions closely. To put things in perspective, let me first say that there have been 73,626 innings played during the 136 years of Test cricket. This analysis covers up to Test #2089, the second Test between England and New Zealand. That makes it an average of 35.2 innings per Test, this number makes sense. The maximum, of course, is 44 per Test and this works out to about 80%.

The lowest score not yet reached is 229. Why? I do not know. Considering that 231 was reached five times and 232, six times, there is no reason for this specific number, other than the fact that there has to be one number. The next two scores not reached are 238 and 245.

What is the highest score reached by multiple batsmen? Well, 334 has been reached by two batsmen (I have resisted the temptation to name the two batsmen), 333 by two batsmen and 329 by two batsmen. The beyond-two occurrences are at 275 (three times) and 274, also three times. These are just stray numbers: there seem to be no specific reasons.

What is the significance of 167? There has been no instance of a 167* score. Nor for that matter a score of 171*, 175* and 180*.

Now, for the most interesting of these numbers. Look at the following frequencies.

 
	Score Freq NO 
	96 93 5 
	97 75 5 
	98 72 13 
	99 86 5 
	100 149 56 
	101 104 27 
	102 106 32 
	103 108 34 
	104 95 20 
	
An innocuous set of numbers! Not at all. Look at the jump between the score of 99 and 100, well over 60%. This jump is way, way beyond the normal increase or decrease by a small number. What are the reasons? One can only surmise.

- The first reason is that the batsmen take a lot more care as they reach 100. That would explain the significant drop between the score of 96 and 97. Maybe the batsmen take that additional care when they come within a stroke of 100. I can hear someone saying 94 is also a stroke away: agreed, but this is a Test match.
- But why such a high number at 100. The only reason for this must be the number of declarations made when a batsman reaches hundred. Is this borne out by the number of not-outs? Of course, yes. Look at the increase in not-outs from five to 56. And the trend continues beyond also. Well over the 99-value of five, indicating later declarations.
- I am amazed at the importance the score of 100 plays. This obsession seems to have been there over the past 136 years.

Does this trend exist when going from 149 to150 or from 199 to 200?. Let us look at the figures.

 
	Score Freq NO 
	147 21 4 
	148 27 8 
	149 21 3 
	150 29 8 
	151 24 6 
	152 27 5 
	... 
	... 
	Score Freq NO 
	197 6 1 
	198 2 1 
	199 9 2 
	200 15 9 
	201 21 8 
	202 6 2 
	203 15 9 
	

What do we have here? Batsmen moving from 149 to150 show less of this trend than the their movement from 199 to 200. It is clear that the score of 200 is deemed to be far more valuable than the score of 150. Batsmen going from 149 to 150 has a change factor of 21 to 29. Their scores going from 199 to 200 shows clear variation trend: 9 to 15 and then to 21. This again indicates many declarations - revealed by an increase in not outs from 2 to 9.

At what score do we have the highest percentage of not-outs? We should ignore the single scores of 400*, 365* et al. There are two instances of scores on which batsmen remain unbeaten 60% of the times. At 200, there were 15 innings and nine were not outs, making this 60%. And at 203 also, there were 15 innings and nine were unbeaten. The previous discussion seems to clearly pave the way for this. As soon as the batsman reached 200, indicating a team score exceeding 400, there were declarations. Not always, of course. Incidentally there were two unbeaten innings of 199. At 100, the % of not outs is a very high 37.5%.

Now, for some statistical derivations.

The 50-percentile mark appears between 12 and 13. That means over 50% of innings have scores below or at 13. The Median value of scores is 13. The 90-percentile mark is reached between the scores of 68 and 69, meaning that below 10% of the scores are above 69. The Weighted Mean (by the frequency of such scores) of all scores is 28.3. In terms of runs scored at a specific score, the score of 30 gets the top place. There are 680 occurrences, leading to a total of 20,400 runs. I am not sure whether these figures mean anything to readers. But it is a nice thing to round up the analysis.

The graphs for this article were quite difficult to do. There were two problems. The range was mind-boggling: 0 to 400, 0 to 952 and 26 to 829. This made drawing of graph quite difficult in view of ESPNcricinfo's limit of 640 pixels for the graphs. The bigger problem was the value of numbers. Over 10,000 for a score of 0 and 1 for 400 and a similar situation for the team scores.

Hence I have adapted different methods. For the Batsmen scores I have not looked at the entire range of 0 to 400 which would have been impossible to handle from both X and Y axis point of view. So I zeroed into a range of 80 to 220. These are important scores and the exclusion of scores up to 80 meant that the frequencies were more manageable. Anyhow the high scores had very small numbers.

The graph is self-explanatory. Readers can see visual evidence of all what we have discussed so far. The drops before 100, the huge spurts after reaching 100 and the moderate spurts around the 150 and 200 marks. There is no clear pattern emerging other than a general decrease in values.

Team scores (All)

In the 2,089 Tests 7,561 innings were played. The qualification is that at least a ball should have been bowled. With this macro number in place let us see some of the interesting facts about these numbers. First I will look into the set of all innings, complete and incomplete.

The range of team scores is 0 to 952. Yes, you read it correct. Zero was a valid score. I wondered whether my program had gone wrong. But then I may go wrong but my program, never. So I went and checked. Yes, it is true. In Test# 1293, New Zealand scored 0 for 0 off a single ball bowled by Sri Lanka. Why did they play a single ball? Wisden Almanack reports that "Vaas bowled one ball of New Zealand's second innings before the umpires agreed that the light was too bad."

The highest score is 952 and everyone, especially the Indian bowlers, would have painful memory of those 3 days. It is a fair guess how many days might have been needed in this Test to produce a result: Maybe 11. The lowest three scores not reached are 18, 56 and 557.

The score distribution for all innings follows a normal distribution between zero and 600. Beyond that the numbers are very low. The most popular score is 296, with 37 occurrences. Then come 252 and 223, with 34 occurrences each. Why? I have no idea. I am as much bemused as you are, with these specific numbers. And may I ask why there should be 10 scores of 521 and 1 of 525 and 2 of 514? Sure beats me.

I will not be doing any statistical derivations for these types of team innings since there are many short innings, especially in case of wicket-wins, and these distort the numbers.

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