Anantha Narayanan
A look at the most interesting duels between a batsman and a bowler in Test cricket
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
Let us now move on to the tables.
Test | Year | Batsman | Runs | Balls | Bowler | Ext B-B Runs | Ext B-B Balls |
---|---|---|---|---|---|---|---|
266 | 1938 | L Hutton | 364 | 847 | Fleetwood-Smith | 127 | 220 |
266 | 1938 | L Hutton | 364 | 847 | WJ O'Reilly | 76 | 215 |
840 | 1979 | DW Randall | 150 | 498 | JD Higgs | 69 | 203 |
193 | 1930 | A Sandham | 325 | 640 | OC Scott | 104 | 199 |
266 | 1938 | L Hutton | 364 | 847 | MG Waite | 64 | 182 |
618 | 1967 | G Boycott | 246 | 555 | EAS Prasanna | 87 | 179 |
280 | 1946 | SG Barnes | 234 | 667 | DVP Wright | 61 | 177 |
280 | 1946 | SG Barnes | 234 | 667 | AV Bedser | 55 | 177 |
1526 | 2000 | G Kirsten | 180 | 461 | M Muralitharan | 56 | 177 |
256 | 1936 | WR Hammond | 231 | 579 | FA Ward | 75 | 172 |
160 | 1925 | J Ryder | 201 | 461 | R Kilner | 54 | 169 |
256 | 1936 | WR Hammond | 231 | 579 | WJ O'Reilly | 49 | 168 |
1374 | 1997 | ST Jayasuriya | 340 | 578 | RK Chauhan | 105 | 166 |
732 | 1974 | DL Amiss | 262 | 563 | AG Barrett | 58 | 166 |
1090 | 1988 | DC Boon | 184 | 431 | EE Hemmings | 63 | 166 |
1374 | 1997 | RS Mahanama | 225 | 561 | RK Chauhan | 69 | 161 |
899 | 1981 | JG Wright | 110 | 434 | DR Doshi | 26 | 161 |
1116 | 1989 | Javed Miandad | 271 | 465 | SL Boock | 102 | 160 |
601 | 1966 | RM Cowper | 307 | 589 | FJ Titmus | 50 | 160 |
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.
Test | Year | Batsman | Runs | Balls | Bowler | Ext B-B Runs | Ext B-B Balls |
---|---|---|---|---|---|---|---|
179 | 1929 | WR Hammond | 296 | 977 | CV Grimmett | 94 | 265 |
198 | 1930 | H Sutcliffe | 215 | 565 | CV Grimmett | 79 | 228 |
899 | 1981 | JG Wright | 143 | 628 | DR Doshi | 33 | 223 |
266 | 1938 | L Hutton | 364 | 847 | Fleetwood-Smith | 127 | 220 |
193 | 1930 | A Sandham | 375 | 702 | OC Scott | 129 | 219 |
159 | 1925 | H Sutcliffe | 303 | 871 | JM Gregory | 86 | 219 |
266 | 1938 | L Hutton | 364 | 847 | WJ O'Reilly | 76 | 215 |
738 | 1974 | G Boycott | 211 | 725 | LR Gibbs | 65 | 215 |
179 | 1929 | WR Hammond | 296 | 977 | RK Oxenham | 51 | 210 |
159 | 1925 | H Sutcliffe | 303 | 871 | AA Mailey | 95 | 207 |
1530 | 2001 | ME Trescothick | 179 | 517 | M Muralitharan | 67 | 206 |
160 | 1925 | J Ryder | 289 | 580 | R Kilner | 72 | 205 |
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.
Test | Year | Batsman | Runs | Ext Bat-Balls | Bowler | Ext B-B Runs | Ext B-B Balls |
---|---|---|---|---|---|---|---|
439 | 1957 | PBH May | 285 | 811 | S Ramadhin | 94 | 308 |
564 | 1964 | KF Barrington | 256 | 757 | TR Veivers | 67 | 246 |
450 | 1958 | GS Sobers | 365 | 587 | Fazal Mahmood | 116 | 241 |
326 | 1950 | L Hutton | 202 | 654 | AL Valentine | 73 | 233 |
439 | 1957 | PBH May | 285 | 811 | DS Atkinson | 72 | 226 |
564 | 1964 | RB Simpson | 311 | 749 | TW Cartwright | 58 | 225 |
226 | 1933 | WR Hammond | 336 | 595 | FT Badcock | 80 | 225 |
371 | 1953 | FMM Worrell | 237 | 523 | MH Mankad | 96 | 208 |
631 | 1968 | GT Dowling | 239 | 567 | RG Nadkarni | 58 | 201 |
446 | 1958 | Hanif Mohammad | 337 | 1034 | DS Atkinson | 33 | 201 |
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.
Test | Year | Batsman | Runs | Ext bat-Balls | Bowler | Ext B-B Runs | Ext B-B Balls |
---|---|---|---|---|---|---|---|
439 | 1957 | PBH May | 315 | 891 | S Ramadhin | 99 | 340 |
324 | 1950 | C Washbrook | 150 | 679 | AL Valentine | 48 | 264 |
324 | 1950 | C Washbrook | 150 | 679 | S Ramadhin | 57 | 262 |
521 | 1962 | Hanif Mohammad | 215 | 733 | GAR Lock | 81 | 258 |
371 | 1953 | FMM Worrell | 260 | 608 | MH Mankad | 104 | 250 |
564 | 1964 | KF Barrington | 256 | 757 | TR Veivers | 67 | 246 |
377 | 1953 | GO Rabone | 175 | 732 | HJ Tayfield | 47 | 242 |
326 | 1950 | L Hutton | 204 | 663 | AL Valentine | 76 | 241 |
450 | 1958 | GS Sobers | 365 | 587 | Fazal Mahmood | 116 | 241 |
564 | 1964 | RB Simpson | 315 | 761 | TW Cartwright | 58 | 227 |
226 | 1933 | WR Hammond | 336 | 595 | FT Badcock | 80 | 225 |
665 | 1969 | MG Burgess | 178 | 628 | Intikhab Alam | 75 | 224 |
439 | 1957 | PBH May | 315 | 891 | DS Atkinson | 73 | 223 |
337 | 1951 | EAB Rowan | 296 | 836 | R Tattersall | 46 | 223 |
339 | 1951 | AJ Watkins | 177 | 657 | MH Mankad | 36 | 221 |
446 | 1958 | Hanif Mohammad | 354 | 1079 | OG Smith | 57 | 221 |
339 | 1951 | AJ Watkins | 177 | 657 | SG Shinde | 83 | 220 |
337 | 1951 | EAB Rowan | 296 | 836 | MJ Hilton | 93 | 210 |
289 | 1947 | B Mitchell | 309 | 728 | R Howorth | 67 | 203 |
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.
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.
Test | Year | Bowler | Batsman | Balls | Runs | Sc Rate |
---|---|---|---|---|---|---|
1810 | 2006 | N Boje | DPMD Jayawardene | 221 | 125 | 56.6 |
1563 | 2001 | RW Price | JH Kallis | 189 | 68 | 36.0 |
1909 | 2009 | M Muralitharan | Younis Khan | 187 | 111 | 59.4 |
1641 | 2003 | M Muralitharan | SP Fleming | 185 | 95 | 51.4 |
2061 | 2012 | NM Lyon | F du Plessis | 172 | 20 | 11.6 |
2006 | 2011 | Saeed Ajmal | TMK Mawoyo | 166 | 73 | 44.0 |
1979 | 2010 | Abdur Rehman | AB de Villiers | 164 | 74 | 45.1 |
2034 | 2012 | MS Panesar | Azhar Ali | 163 | 66 | 40.5 |
1696 | 2004 | GJ Batty | BC Lara | 161 | 130 | 80.7 |
1743 | 2005 | A Kumble | Younis Khan | 161 | 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.
Test | Year | Bowler | Batsman | Balls | Runs | Sc Rate |
---|---|---|---|---|---|---|
1977 | 2010 | S Randiv | CH Gayle | 154 | 143 | 92.9 |
1696 | 2004 | GJ Batty | BC Lara | 161 | 130 | 80.7 |
1810 | 2006 | N Boje | DPMD Jayawardene | 221 | 125 | 56.6 |
1909 | 2009 | M Muralitharan | Younis Khan | 187 | 111 | 59.4 |
1600 | 2002 | DL Vettori | Inzamam-ul-Haq | 114 | 109 | 95.6 |
1966 | 2010 | S Randiv | SR Tendulkar | 153 | 105 | 68.6 |
2074 | 2013 | NM Lyon | MS Dhoni | 85 | 104 | 122.4 |
1870 | 2008 | PL Harris | V Sehwag | 108 | 100 | 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.
Test | Year | Bowler | Batsman | Balls | Runs | Sc Rate |
---|---|---|---|---|---|---|
2074 | 2013 | NM Lyon | MS Dhoni | 85 | 104 | 122.4 |
1600 | 2002 | DL Vettori | Inzamam-ul-Haq | 114 | 109 | 95.6 |
1977 | 2010 | S Randiv | CH Gayle | 154 | 143 | 92.9 |
1870 | 2008 | PL Harris | V Sehwag | 108 | 100 | 92.6 |
1933 | 2009 | Harbhajan Singh | DPMD Jayawardene | 102 | 89 | 87.3 |
2046 | 2012 | Abdur Rehman | KC Sangakkara | 104 | 84 | 80.8 |
1696 | 2004 | GJ Batty | BC Lara | 161 | 130 | 80.7 |
2095 | 2013 | P Utseya | Younis Khan | 108 | 84 | 77.8 |
2003 | 2011 | S Sreesanth | AN Cook | 103 | 80 | 77.7 |
1634 | 2002 | SCG MacGill | MP Vaughan | 102 | 79 | 77.5 |
1661 | 2003 | RW Price | ML Hayden | 116 | 89 | 76.7 |
2027 | 2012 | I Sharma | MJ Clarke | 121 | 92 | 76.0 |
.... | ||||||
1563 | 2001 | CW Henderson | DD Ebrahim | 115 | 18 | 15.7 |
2006 | 2011 | RW Price | Younis Khan | 112 | 17 | 15.2 |
2061 | 2012 | NM Lyon | F du Plessis | 172 | 20 | 11.6 |
1585 | 2002 | M Muralitharan | SV Carlisle | 121 | 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.
Test | Year | Bowler | Batsman | Balls | InnsBowlerBalls | % |
---|---|---|---|---|---|---|
2009 | 2011 | TM Dilshan | Taufeeq Umar | 134 | 192 | 69.8% |
1735 | 2005 | Enamul Haque jnr | T Taibu | 144 | 222 | 64.9% |
1639 | 2003 | VC Drakes | RT Ponting | 124 | 198 | 62.6% |
1971 | 2010 | Wahab Riaz | IJL Trott | 102 | 164 | 62.2% |
1952 | 2010 | A Mishra | HM Amla | 148 | 240 | 61.7% |
1786 | 2006 | Mohammad Rafique | WU Tharanga | 118 | 192 | 61.5% |
2027 | 2012 | I Sharma | MJ Clarke | 121 | 198 | 61.1% |
1572 | 2001 | M Muralitharan | BC Lara | 135 | 222 | 60.8% |
1913 | 2009 | PL Harris | PJ Hughes | 113 | 186 | 60.8% |
2037 | 2012 | CS Martin | AN Petersen | 102 | 168 | 60.7% |
1748 | 2005 | UDU Chandana | L Vincent | 102 | 168 | 60.7% |
1640 | 2003 | Enamul Haque | HH Dippenaar | 119 | 198 | 60.1% |
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.
Test | Year | Bowler | Batsman | Balls | Runs | Sc Rate |
---|---|---|---|---|---|---|
1641 | 2003 | M Muralitharan | SP Fleming | 265 | 118 | 44.5 |
1572 | 2001 | M Muralitharan | BC Lara | 240 | 164 | 68.3 |
2061 | 2012 | NM Lyon | F du Plessis | 227 | 34 | 15.0 |
1810 | 2006 | N Boje | DPMD Jayawardene | 221 | 125 | 56.6 |
1743 | 2005 | A Kumble | Younis Khan | 208 | 123 | 59.1 |
1735 | 2005 | Enamul Haque jnr | T Taibu | 202 | 101 | 50.0 |
2058 | 2012 | R Ashwin | AN Cook | 195 | 80 | 41.0 |
1563 | 2001 | RW Price | JH Kallis | 189 | 68 | 36.0 |
1909 | 2009 | M Muralitharan | Younis Khan | 187 | 111 | 59.4 |
1952 | 2010 | A Mishra | HM Amla | 187 | 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.
Test | Year | Bowler | Batsman | Balls | Runs | Sc Rate |
---|---|---|---|---|---|---|
1572 | 2001 | M Muralitharan | BC Lara | 240 | 164 | 68.3 |
1977 | 2010 | S Randiv | CH Gayle | 154 | 143 | 92.9 |
1696 | 2004 | GJ Batty | BC Lara | 161 | 130 | 80.7 |
1810 | 2006 | N Boje | DPMD Jayawardene | 221 | 125 | 56.6 |
1743 | 2005 | A Kumble | Younis Khan | 208 | 123 | 59.1 |
1973 | 2010 | NM Hauritz | SR Tendulkar | 168 | 121 | 72.0 |
1641 | 2003 | M Muralitharan | SP Fleming | 265 | 118 | 44.5 |
1909 | 2009 | M Muralitharan | Younis Khan | 187 | 111 | 59.4 |
1600 | 2002 | DL Vettori | Inzamam-ul-Haq | 114 | 109 | 95.6 |
1966 | 2010 | S Randiv | SR Tendulkar | 153 | 105 | 68.6 |
1852 | 2007 | Danish Kaneria | SC Ganguly | 177 | 105 | 59.3 |
2074 | 2013 | NM Lyon | MS Dhoni | 85 | 104 | 122.4 |
1850 | 2007 | Sohail Tanvir | W Jaffer | 119 | 101 | 84.9 |
1673 | 2003 | SCG MacGill | R Dravid | 174 | 101 | 58.0 |
1735 | 2005 | Enamul Haque jnr | T Taibu | 202 | 101 | 50.0 |
1870 | 2008 | PL Harris | V Sehwag | 108 | 100 | 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.
Test | Year | Bowler | Batsman | Balls | Runs | Sc Rate |
---|---|---|---|---|---|---|
2074 | 2013 | NM Lyon | MS Dhoni | 85 | 104 | 122.4 |
1600 | 2002 | DL Vettori | Inzamam-ul-Haq | 114 | 109 | 95.6 |
1977 | 2010 | S Randiv | CH Gayle | 154 | 143 | 92.9 |
1870 | 2008 | PL Harris | V Sehwag | 108 | 100 | 92.6 |
1850 | 2007 | Sohail Tanvir | W Jaffer | 119 | 101 | 84.9 |
1696 | 2004 | GJ Batty | BC Lara | 161 | 130 | 80.7 |
1973 | 2010 | NM Hauritz | SR Tendulkar | 168 | 121 | 72.0 |
.... | ||||||
2014 | 2011 | HMRKB Herath | Misbah-ul-Haq | 172 | 36 | 20.9 |
1672 | 2003 | M Muralitharan | GP Thorpe | 159 | 33 | 20.8 |
1974 | 2010 | DL Vettori | VVS Laxman | 166 | 28 | 16.9 |
2061 | 2012 | NM Lyon | F du Plessis | 227 | 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.
Test | Year | Bowler | Batsman | Balls | TestBowlerBalls | % |
---|---|---|---|---|---|---|
1786 | 2006 | Mohammad Rafique | WU Tharanga | 158 | 246 | 64.2 |
1981 | 2010 | XJ Doherty | AN Cook | 172 | 293 | 58.7 |
1994 | 2011 | HMRKB Herath | IJL Trott | 152 | 264 | 57.6 |
1810 | 2006 | N Boje | DPMD Jayawardene | 221 | 390 | 56.7 |
1572 | 2001 | M Muralitharan | BC Lara | 240 | 438 | 54.8 |
1973 | 2010 | NM Hauritz | SR Tendulkar | 168 | 311 | 54.0 |
1977 | 2010 | S Randiv | CH Gayle | 154 | 290 | 53.1 |
1743 | 2005 | A Kumble | Younis Khan | 208 | 402 | 51.7 |
1696 | 2004 | GJ Batty | BC Lara | 161 | 312 | 51.6 |
1799 | 2006 | Mohammad Rafique | JN Gillespie | 150 | 291 | 51.5 |
1952 | 2010 | A Mishra | HM Amla | 187 | 366 | 51.1 |
1641 | 2003 | HDPK Dharmasena | SP Fleming | 169 | 336 | 50.3 |
1678 | 2003 | A Kumble | RT Ponting | 173 | 344 | 50.3 |
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.
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.
Wicket | AllInns | ****** | FirstInns | ****** | SecondInns | ****** |
---|---|---|---|---|---|---|
ResUtilized | ResAvlbl | ResUtilized | ResAvlbl | ResUtilized | ResAvlbl | |
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% |
10 | 100.00% | 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.
Match Id | Score | Wkt-Res % | T1-Score | T2-Score | Target-% | TRF-W | Equation | Req-RpO | Exp-RpO | TRF-B | TRF-S |
---|---|---|---|---|---|---|---|---|---|---|---|
Featured | |||||||||||
3080 | 188/8 | 11.1% | 190/10 | 189/10 | 1.6% | 0.141 | 3 in 46 | 0.39 | 5.66 | 0.069 | 0.117 |
2600 | 192/3 | 54.0% | 210/ 8 | 209/ 6 | 9.0% | 0.167 | 19 in 28 | 4.07 | 6.77 | 0.602 | 0.312 |
3120 | 164/8 | 11.1% | 171/10 | 165/10 | 4.7% | 0.418 | 8 in 17 | 2.82 | 5.66 | 0.498 | 0.445 |
1450 | 249/8 | 11.1% | 252/ 9 | 249/10 | 1.6% | 0.142 | 4 in 7 | 3.43 | 5.66 | 0.605 | 0.297 |
2642 | 199/4 | 43.0% | 233/ 9 | 219/10 | 15.0% | 0.348 | 35 in 57 | 3.68 | 6.49 | 0.568 | 0.421 |
2269 | 196/9 | 5.1% | 198/10 | 196/10 | 1.5% | 0.297 | 3 in 11 | 1.64 | 5.50 | 0.298 | 0.297 |
2734 | 271/4 | 43.0% | 282/ 8 | 281/ 6 | 4.2% | 0.099 | 12 in 16 | 4.50 | 6.49 | 0.693 | 0.297 |
2243 | 281/6 | 25.2% | 284/ 6 | 283/10 | 1.4% | 0.056 | 4 in 6 | 4.00 | 6.05 | 0.661 | 0.257 |
1344 | 272/4 | 43.0% | 307/ 6 | 301/10 | 11.7% | 0.272 | 36 in 39 | 5.54 | 6.49 | 0.853 | 0.466 |
1514 | 196/8 | 11.1% | 196/10 | 196/10 | 0.5% | 0.046 | 1 in 6 | 1.00 | 5.66 | 0.177 | 0.089 |
Included | |||||||||||
1283 | 221/5 | 33.3% | 241/ 9 | 235/10 | 8.7% | 0.260 | 21 in 25 | 5.04 | 6.27 | 0.804 | 0.441 |
1294 | 125/0 | 100.0% | 228/ 7 | 227/ 9 | 45.4% | 0.454 | 104 in 170 | 3.67 | 7.00 | 0.524 | 0.478 |
1405 | 198/4 | 43.0% | 232/ 8 | 222/10 | 15.0% | 0.350 | 35 in 46 | 4.57 | 6.49 | 0.703 | 0.468 |
1722 | 196/3 | 54.0% | 242/ 8 | 240/10 | 19.3% | 0.358 | 47 in 59 | 4.78 | 6.77 | 0.707 | 0.474 |
1941 | 216/6 | 25.2% | 229/ 7 | 224/10 | 6.1% | 0.241 | 14 in 17 | 4.94 | 6.05 | 0.817 | 0.433 |
2520 | 235/5 | 33.3% | 257/ 8 | 252/ 9 | 8.9% | 0.267 | 23 in 26 | 5.31 | 6.27 | 0.847 | 0.460 |
2535 | 203/5 | 33.3% | 221/ 9 | 221/10 | 8.6% | 0.257 | 19 in 38 | 3.00 | 6.27 | 0.478 | 0.331 |
2682 | 301/3 | 54.0% | 340/ 6 | 340/ 7 | 11.7% | 0.217 | 40 in 38 | 6.32 | 6.77 | 0.934 | 0.456 |
2826 | 212/3 | 54.0% | 270/ 7 | 244/ 7 | 14.2% | 0.262 | 35 in 34 | 6.18 | 6.77 | 0.913 | 0.479 |
3135 | 222/6 | 25.2% | 243/10 | 225/10 | 9.0% | 0.358 | 22 in 52 | 2.54 | 6.05 | 0.420 | 0.378 |
3215 | 155/3 | 54.0% | 200/10 | 174/10 | 22.9% | 0.423 | 46 in 73 | 3.78 | 6.15 | 0.615 | 0.487 |
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.
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%
Target Score-at-FoW Target-% BallsRes% TRF-B WktRes-% TRF-W
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.
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*
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.
MatchId | FoW Scr | Balls | DL | Tgt | Max | FB Scr | SB Scr | BlsF | TRF-B | TgtF | WktF | TRF-W |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Featured | ||||||||||||
3065 | 107/8 | 152 | 240 | 300 | 239/8 | 243/9 | 0.493 | 1.123 | 0.554 | 0.098 | 5.632 | |
26 | 203/9 | 0 | 267 | 360 | 266/7 | 267/9 | 0.000 | 0.000 | 0.240 | 0.047 | 5.133 | |
2499 | 231/9 | 262 | 285 | 300 | 284/4 | 286/9 | 0.127 | 1.496 | 0.189 | 0.047 | 4.057 | |
1028 | 74/7 | 0 | 173 | 258 | 172/9 | 173/9 | 0.000 | 0.000 | 0.572 | 0.156 | 3.661 | |
1976 | 135/8 | 226 | 205 | 300 | 204/8 | 208/8 | 0.247 | 1.384 | 0.341 | 0.098 | 3.470 | |
2922 | 187/9 | 269 | 222 | 300 | 221/9 | 222/9 | 0.103 | 1.526 | 0.158 | 0.047 | 3.376 | |
3323 | 140/8 | 193 | 209 | 300 | 208 ao | 209/9 | 0.357 | 0.926 | 0.330 | 0.098 | 3.355 | |
2182 | 147/8 | 202 | 218 | 300 | 217 ao | 218/8 | 0.327 | 0.997 | 0.326 | 0.098 | 3.310 | |
241 | 92/7 | 0 | 178 | 300 | 177/8 | 180/9 | 0.000 | 0.000 | 0.483 | 0.156 | 3.091 | |
2794 | 6/5 | 48 | 153 | 300 | 152 ao | 153/8 | 0.840 | 1.144 | 0.961 | 0.312 | 3.083 | |
Included | ||||||||||||
2617 | 114/7 | 143 | 213 | 300 | 212 ao | 213/7 | 0.523 | 0.888 | 0.465 | 0.156 | 2.974 | |
2632 | 64/6 | 113 | 194 | 300 | 193 ao | 195/8 | 0.623 | 1.075 | 0.670 | 0.226 | 2.966 | |
1799 | 82/6 | 129 | 246 | 300 | 245/8 | 248/8 | 0.570 | 1.170 | 0.667 | 0.226 | 2.951 | |
2455 | 178/9 | 230 | DL | 206 | 252 | 223/8 | 205/9 | 0.087 | 1.557 | 0.136 | 0.047 | 2.911 |
2797 | 44/6 | 118 | 125 | 300 | 124 ao | 127/8 | 0.607 | 1.068 | 0.648 | 0.226 | 2.869 | |
1537 | 71/6 | 130 | 196 | 294 | 195 ao | 196/8 | 0.558 | 1.143 | 0.638 | 0.226 | 2.823 | |
2403 | 134/8 | 228 | 185 | 300 | 184 ao | 185/8 | 0.240 | 1.149 | 0.276 | 0.098 | 2.802 | |
83 | 61/6 | 0 | 164 | 300 | 163 ao | 164/8 | 0.000 | 0.000 | 0.628 | 0.226 | 2.780 | |
679 | 158/8 | 0 | 216 | 300 | 215 ao | 217/9 | 0.000 | 0.000 | 0.269 | 0.098 | 2.729 | |
676 | 152/9 | 0 | 174 | 330 | 173/8 | 175/9 | 0.000 | 0.000 | 0.126 | 0.047 | 2.707 | |
2375 | 89/7 | 175 | DL | 154 | 264 | 157/9 | 153/7 | 0.337 | 1.252 | 0.422 | 0.156 | 2.700 |
3358 | 133/7 | 222 | 230 | 300 | 229/9 | 230/8 | 0.260 | 1.622 | 0.422 | 0.156 | 2.698 | |
88 | 80/6 | 0 | 204 | 300 | 203/7 | 207/9 | 0.000 | 0.000 | 0.608 | 0.226 | 2.691 | |
3161 | 92/6 | 134 | 226 | 300 | 225/8 | 228/7 | 0.553 | 1.072 | 0.593 | 0.226 | 2.625 | |
31 | 39/6 | 0 | 94 | 360 | 93 ao | 94/6 | 0.000 | 0.000 | 0.585 | 0.226 | 2.590 | |
3127 | 169/8 | 238 | 226 | 300 | 225 ao | 227/8 | 0.207 | 1.220 | 0.252 | 0.098 | 2.563 | |
2634 | 49/5 | 65 | 231 | 300 | 230 ao | 233/6 | 0.783 | 1.006 | 0.788 | 0.312 | 2.528 | |
2265 | 95/6 | 156 | 221 | 300 | 220/8 | 221/6 | 0.480 | 1.188 | 0.570 | 0.226 | 2.524 |
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.
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.
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.
Name | Ctry | ODIs | RpI | Sc/R | St/R | RpO | RpI-Idx | Sc/R-Idx | St/R-Idx | RpO-Idx | A/R-Index |
---|---|---|---|---|---|---|---|---|---|---|---|
RN ten Doeschate | Ned | 33 | 48.15 | 87.7 | 28.72 | 5.04 | 24.08 | 20.10 | 26.11 | 14.88 | 85.17 |
A Flintoff | Eng | 141 | 27.81 | 88.8 | 33.27 | 4.40 | 13.90 | 20.36 | 22.54 | 17.06 | 73.86 |
SR Watson | Aus | 160 | 34.25 | 88.5 | 36.34 | 4.78 | 17.12 | 20.28 | 20.64 | 15.68 | 73.72 |
IVA Richards | Win | 187 | 40.24 | 90.2 | 47.83 | 4.49 | 20.12 | 20.67 | 15.68 | 16.69 | 73.16 |
V Sehwag | Ind | 251 | 33.76 | 104.3 | 45.75 | 5.26 | 16.88 | 23.91 | 16.39 | 14.25 | 71.43 |
DS Lehmann | Aus | 117 | 30.47 | 81.3 | 34.48 | 4.84 | 15.23 | 18.64 | 21.75 | 15.50 | 71.13 |
KJ O'Brien | Ire | 72 | 28.89 | 83.3 | 34.13 | 4.91 | 14.44 | 19.10 | 21.97 | 15.28 | 70.80 |
Shahid Afridi | Pak | 359 | 21.99 | 114.6 | 43.86 | 4.61 | 10.99 | 26.27 | 17.10 | 16.26 | 70.63 |
JH Kallis | Saf | 321 | 37.45 | 73.0 | 39.39 | 4.83 | 18.73 | 16.72 | 19.04 | 15.54 | 70.03 |
GS Chappell | Aus | 74 | 32.37 | 75.7 | 43.16 | 4.05 | 16.18 | 17.35 | 17.38 | 18.53 | 69.44 |
CH Gayle | Win | 253 | 35.11 | 84.2 | 44.77 | 4.74 | 17.56 | 19.31 | 16.75 | 15.82 | 69.44 |
L Klusener | Saf | 171 | 26.10 | 89.9 | 38.19 | 4.70 | 13.05 | 20.61 | 19.64 | 15.94 | 69.24 |
SR Tendulkar | Ind | 463 | 40.76 | 86.2 | 52.33 | 5.10 | 20.38 | 19.76 | 14.33 | 14.70 | 69.17 |
A Symonds | Aus | 198 | 31.60 | 92.4 | 44.62 | 5.01 | 15.80 | 21.18 | 16.81 | 14.97 | 68.76 |
ME Waugh | Aus | 244 | 36.01 | 76.9 | 43.37 | 4.78 | 18.00 | 17.62 | 17.29 | 15.69 | 68.61 |
Shakib Al Hasan | Bng | 129 | 29.74 | 78.2 | 40.85 | 4.31 | 14.87 | 17.92 | 18.36 | 17.39 | 68.54 |
N Kapil Dev | Ind | 225 | 19.10 | 95.1 | 44.27 | 3.72 | 9.55 | 21.79 | 16.94 | 20.17 | 68.45 |
ST Jayasuriya | Slk | 444 | 31.01 | 91.2 | 46.03 | 4.79 | 15.51 | 20.90 | 16.29 | 15.66 | 68.37 |
RJ Hadlee | Nzl | 115 | 17.86 | 75.5 | 39.12 | 3.31 | 8.93 | 17.30 | 19.17 | 22.69 | 68.09 |
SM Pollock | Saf | 303 | 17.16 | 86.7 | 39.97 | 3.68 | 8.58 | 19.87 | 18.76 | 20.39 | 67.60 |
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.
Name | Ctry | ODIs | RpI | Bow-Avge | A-R Ratio |
---|---|---|---|---|---|
RN ten Doeschate | Ned | 33 | 48.15 | 24.13 | 1.9957 |
SR Watson | Aus | 160 | 34.25 | 28.98 | 1.1818 |
JH Kallis | Saf | 321 | 37.45 | 31.70 | 1.1815 |
A Flintoff | Eng | 141 | 27.81 | 24.38 | 1.1405 |
IVA Richards | Win | 187 | 40.24 | 35.83 | 1.1231 |
GS Chappell | Aus | 74 | 32.37 | 29.12 | 1.1114 |
DS Lehmann | Aus | 117 | 30.47 | 27.81 | 1.0957 |
ME Waugh | Aus | 244 | 36.01 | 34.56 | 1.0418 |
KJ O'Brien | Ire | 72 | 28.89 | 27.93 | 1.0343 |
Shakib Al Hasan | Bng | 129 | 29.74 | 29.37 | 1.0125 |
CH Gayle | Win | 253 | 35.11 | 35.38 | 0.9925 |
SC Ganguly | Ind | 311 | 37.87 | 38.51 | 0.9834 |
MJ Clarke | Aus | 227 | 35.62 | 37.54 | 0.9490 |
Imran Khan | Pak | 175 | 24.56 | 26.62 | 0.9226 |
SR Tendulkar | Ind | 463 | 40.76 | 44.51 | 0.9157 |
WJ Cronje | Saf | 188 | 31.80 | 34.79 | 0.9141 |
AR Border | Aus | 273 | 25.88 | 28.37 | 0.9122 |
L Klusener | Saf | 171 | 26.10 | 29.95 | 0.8714 |
NJ Astle | Nzl | 223 | 32.67 | 38.46 | 0.8494 |
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.
Name | Ctry | ODIs | Runs | Wickets | Equalised value | Per Match |
---|---|---|---|---|---|---|
RN ten Doeschate | Ned | 33 | 1541 | 55 | 3301 | 100.0 |
Shakib Al Hasan | Bng | 129 | 3688 | 161 | 8840 | 68.5 |
JH Kallis | Saf | 321 | 11498 | 270 | 20138 | 62.7 |
GS Chappell | Aus | 74 | 2331 | 72 | 4635 | 62.6 |
A Flintoff | Eng | 141 | 3394 | 169 | 8802 | 62.4 |
SR Watson | Aus | 160 | 4795 | 156 | 9787 | 61.2 |
RJ Hadlee | Nzl | 115 | 1751 | 158 | 6807 | 59.2 |
IK Pathan | Ind | 120 | 1544 | 173 | 7080 | 59.0 |
IT Botham | Eng | 116 | 2113 | 145 | 6753 | 58.2 |
L Klusener | Saf | 171 | 3576 | 192 | 9720 | 56.8 |
IVA Richards | Win | 187 | 6721 | 118 | 10497 | 56.1 |
HH Streak | Zim | 189 | 2943 | 239 | 10591 | 56.0 |
Wasim Akram | Pak | 356 | 3717 | 502 | 19781 | 55.6 |
DJ Bravo | Win | 146 | 2495 | 173 | 8031 | 55.0 |
Imran Khan | Pak | 175 | 3709 | 182 | 9533 | 54.5 |
CH Gayle | Win | 253 | 8743 | 157 | 13767 | 54.4 |
ST Jayasuriya | Slk | 444 | 13430 | 323 | 23766 | 53.5 |
SM Pollock | Saf | 303 | 3519 | 393 | 16095 | 53.1 |
CL Cairns | Nzl | 215 | 4950 | 201 | 11382 | 52.9 |
M Prabhakar | Ind | 130 | 1858 | 157 | 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.
Name | Ctry | ODIs | Runs | Wickets | Equalised value |
---|---|---|---|---|---|
ST Jayasuriya | Slk | 444 | 13430 | 323 | 23766 |
SR Tendulkar | Ind | 463 | 18426 | 154 | 23354 |
JH Kallis | Saf | 321 | 11498 | 270 | 20138 |
Wasim Akram | Pak | 356 | 3717 | 502 | 19781 |
Shahid Afridi | Pak | 359 | 7303 | 358 | 18759 |
SM Pollock | Saf | 303 | 3519 | 393 | 16095 |
WPUJC Vaas | Slk | 324 | 2025 | 400 | 14825 |
SC Ganguly | Ind | 311 | 11363 | 100 | 14563 |
SR Waugh | Aus | 325 | 7569 | 195 | 13809 |
CH Gayle | Win | 253 | 8743 | 157 | 13767 |
Abdul Razzaq | Pak | 265 | 5080 | 269 | 13688 |
PA de Silva | Slk | 308 | 9284 | 106 | 12676 |
CL Hooper | Win | 227 | 5761 | 193 | 11937 |
N Kapil Dev | Ind | 225 | 3783 | 253 | 11879 |
Yuvraj Singh | Ind | 282 | 8211 | 112 | 11795 |
CL Cairns | Nzl | 215 | 4950 | 201 | 11382 |
V Sehwag | Ind | 251 | 8273 | 96 | 11345 |
ME Waugh | Aus | 244 | 8500 | 85 | 11220 |
DL Vettori | Nzl | 275 | 2110 | 284 | 11198 |
CZ Harris | Nzl | 250 | 4379 | 203 | 10875 |
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.
Name | Ctry | ODIs | RpI-Idx | Sc/R-Idx | Batting Index | St/R-Idx | RpO-Idx | Bowling Index | Ratio |
---|---|---|---|---|---|---|---|---|---|
WPUJC Vaas | Slk | 324 | 4.60 | 16.62 | 21.2 | 19.02 | 17.90 | 36.9 | 0.57 |
RJ Hadlee | Nzl | 115 | 8.93 | 17.30 | 26.2 | 19.17 | 22.69 | 41.9 | 0.63 |
M Prabhakar | Ind | 130 | 9.48 | 13.85 | 23.3 | 18.52 | 17.54 | 36.1 | 0.65 |
Wasim Akram | Pak | 356 | 6.64 | 20.24 | 26.9 | 20.71 | 19.25 | 40.0 | 0.67 |
Mudassar Nazar | Pak | 122 | 11.53 | 12.00 | 23.5 | 17.15 | 17.68 | 34.8 | 0.68 |
... | |||||||||
CL Hooper | Win | 227 | 13.98 | 17.56 | 31.5 | 15.12 | 17.20 | 32.3 | 0.98 |
SB Styris | Nzl | 188 | 13.92 | 18.20 | 32.1 | 16.79 | 15.81 | 32.6 | 0.99 |
Shoaib Malik | Pak | 216 | 14.22 | 17.94 | 32.2 | 15.62 | 16.50 | 32.1 | 1.00 |
GW Flower | Zim | 221 | 15.35 | 15.49 | 30.8 | 14.29 | 16.16 | 30.4 | 1.01 |
WJ Cronje | Saf | 188 | 15.90 | 17.53 | 33.4 | 15.96 | 16.88 | 32.8 | 1.02 |
... | |||||||||
A Symonds | Aus | 198 | 15.80 | 21.18 | 37.0 | 16.81 | 14.97 | 31.8 | 1.16 |
TM Dilshan | Slk | 267 | 15.79 | 19.74 | 35.5 | 12.92 | 15.97 | 28.9 | 1.23 |
IVA Richards | Win | 187 | 20.12 | 20.67 | 40.8 | 15.68 | 16.69 | 32.4 | 1.26 |
V Sehwag | Ind | 251 | 16.88 | 23.91 | 40.8 | 16.39 | 14.25 | 30.6 | 1.33 |
SR Tendulkar | Ind | 463 | 20.38 | 19.76 | 40.1 | 14.33 | 14.70 | 29.0 | 1.38 |
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.
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
Bowler | Type | Bowling Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
M Muralitharan | rob | 22.73 | 9 | 709 | 373 | 3 | 52.6 | 124.33 | 236.3 |
Chaminda Vaas | LFM | 29.58 | 9 | 372 | 233 | 1 | 62.6 | 233.00 | 372.0 |
Andre Nel | RFM | 31.86 | 11 | 341 | 185 | 8 | 54.3 | 23.12 | 42.6 |
Makhaya Ntini | RF | 28.83 | 11 | 312 | 225 | 1 | 72.1 | 225.00 | 312.0 |
Steve Harmison | RFM | 31.82 | 13 | 303 | 146 | 4 | 48.2 | 36.50 | 75.8 |
Danish Kaneria | rlb | 34.80 | 8 | 298 | 260 | 3 | 87.2 | 86.67 | 99.3 |
Andrew Flintoff | RF | 32.79 | 10 | 263 | 109 | 4 | 41.4 | 27.25 | 65.8 |
Jacques Kallis | RFM | 32.43 | 8 | 251 | 148 | 0 | 59.0 | 148.00 | 251.0 |
Brett Lee | RF | 30.82 | 14 | 243 | 172 | 2 | 70.8 | 86.00 | 121.5 |
Stuart MacGill | rlb | 29.03 | 7 | 236 | 174 | 2 | 73.7 | 87.00 | 118.0 |
Glenn McGrath | RFM | 21.64 | 12 | 233 | 90 | 2 | 38.6 | 45.00 | 116.5 |
Jason Gillespie | RF | 26.14 | 8 | 214 | 82 | 0 | 38.3 | 82.00 | 214.0 |
Shaun Pollock | RFM | 23.12 | 6 | 192 | 63 | 1 | 32.8 | 63.00 | 192.0 |
Shahid Nazir | RFM | 35.33 | 4 | 181 | 88 | 0 | 48.6 | 88.00 | 181.0 |
Andy Bichel | RFM | 32.24 | 8 | 171 | 112 | 4 | 65.5 | 28.00 | 42.8 |
Shane Warne | rlb | 25.42 | 7 | 168 | 105 | 3 | 62.5 | 35.00 | 56.0 |
Abdul Razzaq | RFM | 36.93 | 6 | 168 | 110 | 0 | 65.5 | 110.00 | 168.0 |
Thilan Samaraweera | rob | 45.93 | 7 | 161 | 80 | 1 | 49.7 | 80.00 | 161.0 |
Gareth Batty | rob | 66.64 | 1 | 161 | 130 | 0 | 80.7 | 130.00 | 161.0 |
Matthew Hoggard | RFM | 30.50 | 10 | 159 | 137 | 1 | 86.2 | 137.00 | 159.0 |
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.
Bowler | Type | Bowling Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Mitchell Johnson | LF | 30.93 | 18 | 502 | 250 | 3 | 49.8 | 83.33 | 167.3 |
Paul Harris | lsp | 37.87 | 7 | 441 | 154 | 3 | 34.9 | 51.33 | 147.0 |
Brett Lee | RF | 30.82 | 19 | 432 | 242 | 5 | 56.0 | 48.40 | 86.4 |
M Muralitharan | rob | 22.73 | 14 | 366 | 196 | 6 | 53.6 | 32.67 | 61.0 |
James Anderson | RFM | 29.67 | 23 | 350 | 208 | 9 | 59.4 | 23.11 | 38.9 |
Ashley Giles | lsp | 40.60 | 5 | 348 | 125 | 1 | 35.9 | 125.00 | 348.0 |
Andrew Flintoff | RF | 32.79 | 17 | 342 | 133 | 2 | 38.9 | 66.50 | 171.0 |
Daniel Vettori | lsp | 34.42 | 12 | 314 | 95 | 3 | 30.3 | 31.67 | 104.7 |
Dale Steyn | RF | 22.66 | 11 | 310 | 149 | 3 | 48.1 | 49.67 | 103.3 |
Monty Panesar | lsp | 33.78 | 13 | 304 | 149 | 4 | 49.0 | 37.25 | 76.0 |
Matthew Hoggard | RFM | 30.50 | 13 | 292 | 182 | 3 | 62.3 | 60.67 | 97.3 |
Mohammad Sami | RF | 52.74 | 9 | 287 | 127 | 1 | 44.3 | 127.00 | 287.0 |
Mohammad Rafique | lsp | 40.76 | 5 | 283 | 140 | 1 | 49.5 | 140.00 | 283.0 |
Graeme Swann | rob | 28.14 | 14 | 279 | 150 | 4 | 53.8 | 37.50 | 69.8 |
Danish Kaneria | rlb | 34.80 | 8 | 269 | 151 | 1 | 56.1 | 151.00 | 269.0 |
Mervyn Dillon | RFM | 33.63 | 10 | 267 | 163 | 2 | 61.0 | 81.50 | 133.5 |
Ben Hilfenhaus | RFM | 28.51 | 10 | 250 | 161 | 0 | 64.4 | 161.00 | 250.0 |
Nathan Hauritz | rob | 34.98 | 5 | 236 | 179 | 1 | 75.8 | 179.00 | 236.0 |
Shakib Al Hasan | lsp | 32.75 | 5 | 234 | 119 | 1 | 50.9 | 119.00 | 234.0 |
Cameron Cuffy | RF | 33.67 | 8 | 233 | 107 | 2 | 45.9 | 53.50 | 116.5 |
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.
Bowler | Type | Bowling Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
M Muralitharan | rob | 22.73 | 16 | 688 | 326 | 5 | 47.4 | 65.20 | 137.6 |
Daniel Vettori | lsp | 34.42 | 12 | 609 | 275 | 2 | 45.2 | 137.50 | 304.5 |
Danish Kaneria | rlb | 34.80 | 13 | 583 | 305 | 5 | 52.3 | 61.00 | 116.6 |
Matthew Hoggard | RFM | 30.50 | 16 | 531 | 218 | 5 | 41.1 | 43.60 | 106.2 |
Andrew Flintoff | RF | 32.79 | 17 | 470 | 154 | 3 | 32.8 | 51.33 | 156.7 |
Mohammad Sami | RF | 52.74 | 14 | 454 | 205 | 2 | 45.2 | 102.50 | 227.0 |
James Anderson | RFM | 29.67 | 18 | 432 | 197 | 5 | 45.6 | 39.40 | 86.4 |
Brett Lee | RF | 30.82 | 16 | 389 | 153 | 5 | 39.3 | 30.60 | 77.8 |
Stuart MacGill | rlb | 29.03 | 8 | 357 | 225 | 0 | 63.0 | 225.00 | 357.0 |
Makhaya Ntini | RF | 28.83 | 13 | 345 | 149 | 3 | 43.2 | 49.67 | 115.0 |
Monty Panesar | lsp | 33.78 | 11 | 343 | 145 | 2 | 42.3 | 72.50 | 171.5 |
Pedro Collins | LFM | 34.62 | 11 | 341 | 178 | 0 | 52.2 | 178.00 | 341.0 |
Stuart Broad | RFM | 31.19 | 10 | 340 | 136 | 2 | 40.0 | 68.00 | 170.0 |
Devendra Bishoo | rlb | 39.55 | 9 | 339 | 165 | 2 | 48.7 | 82.50 | 169.5 |
Mitchell Johnson | LF | 30.93 | 13 | 324 | 113 | 4 | 34.9 | 28.25 | 81.0 |
Graeme Swann | rob | 28.14 | 9 | 318 | 163 | 3 | 51.3 | 54.33 | 106.0 |
Ashley Giles | lsp | 40.60 | 7 | 313 | 112 | 2 | 35.8 | 56.00 | 156.5 |
Jason Gillespie | RF | 26.14 | 12 | 300 | 84 | 4 | 28.0 | 21.00 | 75.0 |
Paul Harris | lsp | 37.87 | 8 | 300 | 107 | 1 | 35.7 | 107.00 | 300.0 |
Chris Martin | RFM | 33.81 | 10 | 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.
Bowler | Type | Bowling Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Harbhajan Singh | rob | 32.38 | 18 | 676 | 382 | 6 | 56.5 | 63.67 | 112.7 |
Danish Kaneria | rlb | 34.80 | 13 | 621 | 258 | 4 | 41.5 | 64.50 | 155.2 |
Shane Warne | rlb | 25.42 | 22 | 550 | 280 | 5 | 50.9 | 56.00 | 110.0 |
Brett Lee | RF | 30.82 | 21 | 528 | 199 | 3 | 37.7 | 66.33 | 176.0 |
Anil Kumble | rlb | 29.65 | 14 | 494 | 191 | 1 | 38.7 | 191.00 | 494.0 |
Daniel Vettori | lsp | 34.42 | 10 | 475 | 208 | 0 | 43.8 | 208.00 | 475.0 |
Abdur Rehman | lsp | 28.41 | 8 | 434 | 222 | 0 | 51.2 | 222.00 | 434.0 |
James Anderson | RFM | 29.67 | 22 | 419 | 177 | 7 | 42.2 | 25.29 | 59.9 |
Zaheer Khan | LFM | 32.36 | 14 | 382 | 157 | 2 | 41.1 | 78.50 | 191.0 |
Glenn McGrath | RFM | 21.64 | 16 | 378 | 133 | 3 | 35.2 | 44.33 | 126.0 |
Andrew Flintoff | RF | 32.79 | 15 | 372 | 139 | 4 | 37.4 | 34.75 | 93.0 |
Steve Harmison | RFM | 31.82 | 13 | 346 | 146 | 4 | 42.2 | 36.50 | 86.5 |
S Sreesanth | RFM | 37.61 | 12 | 328 | 150 | 4 | 45.7 | 37.50 | 82.0 |
Chris Martin | RFM | 33.81 | 15 | 319 | 158 | 4 | 49.5 | 39.50 | 79.8 |
Umar Gul | RFM | 34.07 | 10 | 303 | 165 | 1 | 54.5 | 165.00 | 303.0 |
Peter Siddle | RFM | 28.58 | 15 | 294 | 170 | 2 | 57.8 | 85.00 | 147.0 |
Graeme Swann | rob | 28.14 | 8 | 288 | 147 | 1 | 51.0 | 147.00 | 288.0 |
Ray Price | lsp | 36.06 | 3 | 277 | 143 | 0 | 51.6 | 143.00 | 277.0 |
Mitchell Johnson | LF | 30.93 | 12 | 269 | 88 | 5 | 32.7 | 17.60 | 53.8 |
Dwayne Bravo | RM | 39.70 | 9 | 267 | 132 | 2 | 49.4 | 66.00 | 133.5 |
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.
Bowler | Type | Bowling Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Anil Kumble | rlb | 29.65 | 17 | 504 | 287 | 5 | 56.9 | 57.40 | 100.8 |
Matthew Hoggard | RFM | 30.50 | 11 | 376 | 196 | 1 | 52.1 | 196.00 | 376.0 |
Steve Harmison | RFM | 31.82 | 7 | 355 | 235 | 2 | 66.2 | 117.50 | 177.5 |
Daniel Vettori | lsp | 34.42 | 8 | 315 | 110 | 2 | 34.9 | 55.00 | 157.5 |
Irfan Pathan | LM | 32.26 | 16 | 295 | 141 | 5 | 47.8 | 28.20 | 59.0 |
Monty Panesar | lsp | 33.78 | 7 | 291 | 145 | 3 | 49.8 | 48.33 | 97.0 |
Harbhajan Singh | rob | 32.38 | 11 | 263 | 155 | 3 | 58.9 | 51.67 | 87.7 |
Rangana Herath | lsp | 29.52 | 9 | 244 | 112 | 6 | 45.9 | 18.67 | 40.7 |
L Balaji | RM | 37.19 | 9 | 233 | 134 | 2 | 57.5 | 67.00 | 116.5 |
Dave Mohammed | lws | 51.38 | 3 | 228 | 132 | 1 | 57.9 | 132.00 | 228.0 |
Corey Collymore | RFM | 32.30 | 5 | 191 | 89 | 1 | 46.6 | 89.00 | 191.0 |
Zaheer Khan | LFM | 32.36 | 8 | 174 | 100 | 1 | 57.5 | 100.00 | 174.0 |
Andrew Flintoff | RF | 32.79 | 5 | 171 | 64 | 3 | 37.4 | 21.33 | 57.0 |
Jerome Taylor | RF | 35.65 | 5 | 169 | 121 | 0 | 71.6 | 121.00 | 169.0 |
Ray Price | lsp | 36.06 | 2 | 158 | 80 | 2 | 50.6 | 40.00 | 79.0 |
Chris Gayle | rob | 42.01 | 6 | 154 | 64 | 2 | 41.6 | 32.00 | 77.0 |
Dwayne Bravo | RM | 39.70 | 5 | 148 | 95 | 0 | 64.2 | 95.00 | 148.0 |
Iain O'Brien | RFM | 33.27 | 5 | 145 | 73 | 2 | 50.3 | 36.50 | 72.5 |
Daren Powell | RFM | 47.99 | 4 | 144 | 82 | 0 | 56.9 | 82.00 | 144.0 |
Enamul Haque | lsp | 57.11 | 3 | 140 | 89 | 0 | 63.6 | 89.00 | 140.0 |
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.
Bowler | Type | Bowling Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Harbhajan Singh | rob | 32.38 | 18 | 790 | 260 | 2 | 32.9 | 130.00 | 395.0 |
Anil Kumble | rlb | 29.65 | 13 | 500 | 232 | 6 | 46.4 | 38.67 | 83.3 |
Steve Harmison | RFM | 31.82 | 18 | 464 | 239 | 1 | 51.5 | 239.00 | 464.0 |
Andre Nel | RFM | 31.86 | 12 | 428 | 185 | 3 | 43.2 | 61.67 | 142.7 |
Makhaya Ntini | RF | 28.83 | 16 | 413 | 197 | 5 | 47.7 | 39.40 | 82.6 |
Danish Kaneria | rlb | 34.80 | 11 | 403 | 207 | 6 | 51.4 | 34.50 | 67.2 |
Monty Panesar | lsp | 33.78 | 8 | 392 | 179 | 2 | 45.7 | 89.50 | 196.0 |
Javagal Srinath | RFM | 30.47 | 11 | 382 | 139 | 3 | 36.4 | 46.33 | 127.3 |
Paul Harris | lsp | 37.87 | 9 | 359 | 179 | 1 | 49.9 | 179.00 | 359.0 |
Zaheer Khan | LFM | 32.36 | 9 | 355 | 136 | 2 | 38.3 | 68.00 | 177.5 |
James Anderson | RFM | 29.67 | 14 | 339 | 151 | 2 | 44.5 | 75.50 | 169.5 |
Jacques Kallis | RFM | 32.43 | 17 | 334 | 113 | 2 | 33.8 | 56.50 | 167.0 |
Graeme Swann | rob | 28.14 | 10 | 330 | 122 | 5 | 37.0 | 24.40 | 66.0 |
Brett Lee | RF | 30.82 | 16 | 329 | 126 | 3 | 38.3 | 42.00 | 109.7 |
Ashley Giles | lsp | 40.60 | 9 | 310 | 138 | 3 | 44.5 | 46.00 | 103.3 |
Stuart MacGill | rlb | 29.03 | 9 | 283 | 210 | 3 | 74.2 | 70.00 | 94.3 |
Daniel Vettori | lsp | 34.42 | 8 | 277 | 116 | 3 | 41.9 | 38.67 | 92.3 |
Matthew Hoggard | RFM | 30.50 | 14 | 269 | 146 | 4 | 54.3 | 36.50 | 67.2 |
Stuart Broad | RFM | 31.19 | 10 | 268 | 89 | 5 | 33.2 | 17.80 | 53.6 |
Ashish Nehra | LM | 42.41 | 6 | 261 | 108 | 0 | 41.4 | 108.00 | 261.0 |
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
Batsman | Type | Batting Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Brian Lara | LHB | 52.89 | 9 | 709 | 373 | 3 | 52.6 | 124.33 | 236.3 |
Rahul Dravid | rhb | 52.31 | 16 | 688 | 326 | 5 | 47.4 | 65.20 | 137.6 |
Ramnaresh Sarwan | rhb | 40.01 | 13 | 597 | 222 | 7 | 37.2 | 31.71 | 85.3 |
Mohammad Ashraful | rhb | 24.01 | 17 | 563 | 276 | 7 | 49.0 | 39.43 | 80.4 |
VVS Laxman | rhb | 45.97 | 15 | 496 | 240 | 2 | 48.4 | 120.00 | 248.0 |
Stephen Fleming | LHB | 40.07 | 5 | 453 | 171 | 0 | 37.7 | 171.00 | 453.0 |
Alastair Cook | LHB | 48.45 | 8 | 450 | 152 | 2 | 33.8 | 76.00 | 225.0 |
Paul Collingwood | rhb | 40.57 | 15 | 393 | 136 | 7 | 34.6 | 19.43 | 56.1 |
Graham Thorpe | LHB | 44.66 | 8 | 387 | 110 | 5 | 28.4 | 22.00 | 77.4 |
Sachin Tendulkar | rhb | 53.87 | 14 | 366 | 196 | 6 | 53.6 | 32.67 | 61.0 |
Mark Butcher | LHB | 34.58 | 7 | 357 | 106 | 2 | 29.7 | 53.00 | 178.5 |
Sourav Ganguly | LHB | 42.18 | 13 | 323 | 141 | 8 | 43.7 | 17.62 | 40.4 |
Michael Vaughan | rhb | 41.44 | 12 | 320 | 97 | 6 | 30.3 | 16.17 | 53.3 |
Jacob Oram | LHB | 36.33 | 11 | 296 | 107 | 5 | 36.1 | 21.40 | 59.2 |
Damien Martyn | rhb | 46.38 | 6 | 291 | 122 | 3 | 41.9 | 40.67 | 97.0 |
Shoaib Malik | rhb | 33.46 | 4 | 288 | 62 | 0 | 21.5 | 62.00 | 288.0 |
Gautam Gambhir | LHB | 44.19 | 10 | 271 | 137 | 4 | 50.6 | 34.25 | 67.8 |
Ashwell Prince | LHB | 41.65 | 6 | 267 | 88 | 3 | 33.0 | 29.33 | 89.0 |
Marcus Trescothick | LHB | 43.76 | 11 | 266 | 110 | 8 | 41.4 | 13.75 | 33.2 |
Daniel Vettori | LHB | 30.11 | 10 | 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.
Batsman | Type | Batting Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Jacques Kallis | rhb | 56.10 | 22 | 550 | 280 | 5 | 50.9 | 56.00 | 110.0 |
Kevin Pietersen | rhb | 48.31 | 18 | 521 | 308 | 5 | 59.1 | 61.60 | 104.2 |
Ashwell Prince | LHB | 41.65 | 18 | 466 | 164 | 11 | 35.2 | 14.91 | 42.4 |
Mark Boucher | rhb | 30.30 | 22 | 417 | 219 | 9 | 52.5 | 24.33 | 46.3 |
Andrew Flintoff | rhb | 31.78 | 19 | 407 | 225 | 7 | 55.3 | 32.14 | 58.1 |
Ian Bell | rhb | 46.58 | 13 | 396 | 177 | 5 | 44.7 | 35.40 | 79.2 |
Neil McKenzie | rhb | 37.39 | 11 | 366 | 153 | 4 | 41.8 | 38.25 | 91.5 |
Herschelle Gibbs | rhb | 41.95 | 14 | 347 | 166 | 6 | 47.8 | 27.67 | 57.8 |
Nathan Astle | rhb | 37.02 | 15 | 333 | 141 | 2 | 42.3 | 70.50 | 166.5 |
Paul Collingwood | rhb | 40.57 | 10 | 317 | 165 | 2 | 52.1 | 82.50 | 158.5 |
Alec Stewart | rhb | 39.56 | 12 | 294 | 160 | 5 | 54.4 | 32.00 | 58.8 |
Stephen Fleming | LHB | 40.07 | 8 | 294 | 125 | 2 | 42.5 | 62.50 | 147.0 |
Mark Butcher | LHB | 34.58 | 12 | 287 | 151 | 4 | 52.6 | 37.75 | 71.8 |
Michael Vaughan | rhb | 41.44 | 10 | 285 | 131 | 3 | 46.0 | 43.67 | 95.0 |
Nasser Hussain | rhb | 37.19 | 10 | 278 | 109 | 3 | 39.2 | 36.33 | 92.7 |
Jacques Rudolph | LHB | 35.43 | 10 | 260 | 114 | 4 | 43.8 | 28.50 | 65.0 |
Shaun Pollock | rhb | 32.32 | 13 | 252 | 172 | 2 | 68.3 | 86.00 | 126.0 |
Andrew Strauss | LHB | 40.91 | 12 | 241 | 141 | 8 | 58.5 | 17.62 | 30.1 |
Gary Kirsten | LHB | 45.27 | 5 | 238 | 128 | 1 | 53.8 | 128.00 | 238.0 |
Thilan Samaraweera | rhb | 48.77 | 7 | 226 | 78 | 0 | 34.5 | 78.00 | 226.0 |
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.
Batsman | Type | Batting Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Herschelle Gibbs | rhb | 41.95 | 17 | 492 | 191 | 3 | 38.8 | 63.67 | 164.0 |
Marcus Trescothick | LHB | 43.76 | 24 | 438 | 184 | 6 | 42.0 | 30.67 | 73.0 |
Jacques Kallis | rhb | 56.10 | 16 | 378 | 133 | 3 | 35.2 | 44.33 | 126.0 |
Mark Butcher | LHB | 34.58 | 15 | 365 | 174 | 5 | 47.7 | 34.80 | 73.0 |
Michael Vaughan | rhb | 41.44 | 14 | 348 | 193 | 6 | 55.5 | 32.17 | 58.0 |
Andrew Strauss | LHB | 40.91 | 15 | 336 | 168 | 3 | 50.0 | 56.00 | 112.0 |
Nathan Astle | rhb | 37.02 | 10 | 297 | 189 | 3 | 63.6 | 63.00 | 99.0 |
Ian Bell | rhb | 46.58 | 13 | 293 | 108 | 5 | 36.9 | 21.60 | 58.6 |
Kevin Pietersen | rhb | 48.31 | 13 | 270 | 135 | 5 | 50.0 | 27.00 | 54.0 |
Brian Lara | LHB | 52.89 | 12 | 233 | 90 | 2 | 38.6 | 45.00 | 116.5 |
Ramnaresh Sarwan | rhb | 40.01 | 9 | 232 | 82 | 2 | 35.3 | 41.00 | 116.0 |
Graeme Smith | LHB | 48.63 | 12 | 224 | 81 | 5 | 36.2 | 16.20 | 44.8 |
Stephen Fleming | LHB | 40.07 | 13 | 222 | 63 | 7 | 28.4 | 9.00 | 31.7 |
Mike Atherton | rhb | 37.70 | 10 | 210 | 86 | 6 | 41.0 | 14.33 | 35.0 |
Paul Collingwood | rhb | 40.57 | 11 | 199 | 54 | 2 | 27.1 | 27.00 | 99.5 |
Gary Kirsten | LHB | 45.27 | 10 | 196 | 75 | 4 | 38.3 | 18.75 | 49.0 |
Mark Richardson | LHB | 44.77 | 9 | 193 | 58 | 1 | 30.1 | 58.00 | 193.0 |
Nasser Hussain | rhb | 37.19 | 12 | 192 | 41 | 4 | 21.4 | 10.25 | 48.0 |
Chris Gayle | LHB | 42.46 | 8 | 177 | 63 | 4 | 35.6 | 15.75 | 44.2 |
Neil McKenzie | rhb | 37.39 | 10 | 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.
Batsman | Type | Batting Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Marcus Trescothick | LHB | 43.76 | 18 | 381 | 126 | 4 | 33.1 | 31.50 | 95.2 |
Michael Vaughan | rhb | 41.44 | 18 | 367 | 91 | 5 | 24.8 | 18.20 | 73.4 |
Matthew Hayden | LHB | 50.74 | 11 | 356 | 152 | 2 | 42.7 | 76.00 | 178.0 |
Justin Langer | LHB | 45.27 | 11 | 352 | 137 | 3 | 38.9 | 45.67 | 117.3 |
Andrew Strauss | LHB | 40.91 | 9 | 336 | 121 | 2 | 36.0 | 60.50 | 168.0 |
Michael Hussey | LHB | 51.53 | 8 | 312 | 122 | 1 | 39.1 | 122.00 | 312.0 |
Ricky Ponting | rhb | 51.87 | 14 | 291 | 151 | 3 | 51.9 | 50.33 | 97.0 |
Rahul Dravid | rhb | 52.31 | 11 | 277 | 69 | 5 | 24.9 | 13.80 | 55.4 |
Taufeeq Umar | LHB | 38.72 | 8 | 277 | 72 | 1 | 26.0 | 72.00 | 277.0 |
Ramnaresh Sarwan | rhb | 40.01 | 9 | 241 | 108 | 4 | 44.8 | 27.00 | 60.2 |
Mark Butcher | LHB | 34.58 | 10 | 233 | 66 | 1 | 28.3 | 66.00 | 233.0 |
Chris Gayle | LHB | 42.46 | 6 | 224 | 117 | 1 | 52.2 | 117.00 | 224.0 |
Damien Martyn | rhb | 46.38 | 8 | 223 | 72 | 2 | 32.3 | 36.00 | 111.5 |
Virender Sehwag | rhb | 49.34 | 8 | 206 | 120 | 3 | 58.3 | 40.00 | 68.7 |
Mahela Jayawardene | rhb | 49.57 | 8 | 195 | 58 | 2 | 29.7 | 29.00 | 97.5 |
Brian Lara | LHB | 52.89 | 6 | 192 | 63 | 1 | 32.8 | 63.00 | 192.0 |
Sachin Tendulkar | rhb | 53.87 | 10 | 186 | 85 | 3 | 45.7 | 28.33 | 62.0 |
Graham Thorpe | LHB | 44.66 | 10 | 185 | 69 | 2 | 37.3 | 34.50 | 92.5 |
Marvan Atapattu | rhb | 39.02 | 8 | 183 | 55 | 3 | 30.1 | 18.33 | 61.0 |
Andrew Flintoff | rhb | 31.78 | 10 | 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.
Batsman | Type | Batting Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Younis Khan | rhb | 50.74 | 13 | 661 | 332 | 5 | 50.2 | 66.40 | 132.2 |
Ricky Ponting | rhb | 51.87 | 13 | 579 | 295 | 4 | 50.9 | 73.75 | 144.8 |
Mohammad Yousuf | rhb | 52.29 | 17 | 504 | 287 | 5 | 56.9 | 57.40 | 100.8 |
S Chanderpaul | LHB | 51.82 | 13 | 500 | 232 | 6 | 46.4 | 38.67 | 83.3 |
Jacques Kallis | rhb | 56.10 | 14 | 494 | 191 | 1 | 38.7 | 191.00 | 494.0 |
Michael Clarke | rhb | 51.59 | 14 | 469 | 276 | 6 | 58.8 | 46.00 | 78.2 |
Michael Vaughan | rhb | 41.44 | 11 | 459 | 272 | 2 | 59.3 | 136.00 | 229.5 |
Simon Katich | LHB | 45.03 | 15 | 439 | 265 | 6 | 60.4 | 44.17 | 73.2 |
Matthew Hayden | LHB | 50.74 | 15 | 399 | 256 | 5 | 64.2 | 51.20 | 79.8 |
Ramnaresh Sarwan | rhb | 40.01 | 12 | 394 | 151 | 3 | 38.3 | 50.33 | 131.3 |
Kamran Akmal | rhb | 30.79 | 15 | 379 | 201 | 5 | 53.0 | 40.20 | 75.8 |
Mahela Jayawardene | rhb | 49.57 | 8 | 370 | 161 | 3 | 43.5 | 53.67 | 123.3 |
Inzamam-ul-Haq | rhb | 49.61 | 10 | 352 | 234 | 5 | 66.5 | 46.80 | 70.4 |
Paul Collingwood | rhb | 40.57 | 10 | 324 | 146 | 3 | 45.1 | 48.67 | 108.0 |
Misbah-ul-Haq | rhb | 43.20 | 6 | 320 | 125 | 0 | 39.1 | 125.00 | 320.0 |
Damien Martyn | rhb | 46.38 | 12 | 317 | 178 | 5 | 56.2 | 35.60 | 63.4 |
Kevin Pietersen | rhb | 48.31 | 11 | 310 | 176 | 2 | 56.8 | 88.00 | 155.0 |
Nasser Hussain | rhb | 37.19 | 9 | 288 | 147 | 4 | 51.0 | 36.75 | 72.0 |
Michael Hussey | LHB | 51.53 | 7 | 276 | 170 | 1 | 61.6 | 170.00 | 276.0 |
Mohammad Sami | rhb | 11.60 | 13 | 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.
Batsman | Type | Batting Avge | Inns | Balls | Runs | Wickets | Batsman Scoring Rate | HtH Average | Bowler Strike Rate |
---|---|---|---|---|---|---|---|---|---|
Rahul Dravid | rhb | 52.31 | 12 | 283 | 91 | 2 | 32.2 | 45.50 | 141.5 |
Virender Sehwag | rhb | 49.34 | 8 | 212 | 177 | 3 | 83.5 | 59.00 | 70.7 |
Justin Langer | LHB | 45.27 | 8 | 174 | 127 | 0 | 73.0 | 127.00 | 174.0 |
Marcus Trescothick | LHB | 43.76 | 7 | 165 | 73 | 2 | 44.2 | 36.50 | 82.5 |
Sourav Ganguly | LHB | 42.18 | 9 | 164 | 100 | 2 | 61.0 | 50.00 | 82.0 |
VVS Laxman | rhb | 45.97 | 10 | 154 | 80 | 1 | 51.9 | 80.00 | 154.0 |
Sachin Tendulkar | rhb | 53.87 | 8 | 140 | 79 | 2 | 56.4 | 39.50 | 70.0 |
Sanath Jayasuriya | LHB | 40.07 | 4 | 137 | 103 | 1 | 75.2 | 103.00 | 137.0 |
Ian Bell | rhb | 46.58 | 6 | 129 | 84 | 2 | 65.1 | 42.00 | 64.5 |
Matthew Hayden | LHB | 50.74 | 7 | 115 | 55 | 3 | 47.8 | 18.33 | 38.3 |
Ricky Ponting | rhb | 51.87 | 8 | 111 | 65 | 2 | 58.6 | 32.50 | 55.5 |
Wasim Jaffer | rhb | 34.11 | 6 | 109 | 47 | 2 | 43.1 | 23.50 | 54.5 |
Habibul Bashar | rhb | 30.88 | 5 | 102 | 95 | 1 | 93.1 | 95.00 | 102.0 |
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.
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
Bowler | Type | BowAvge | Inns | Balls | Runs | Wickets | StrikeRate | AvgeVsBowler |
---|---|---|---|---|---|---|---|---|
James Anderson | RFM | 29.70 | 21 | 267 | 157 | 7 | 38.1 | 22.43 |
Dale Steyn | RF | 22.66 | 19 | 376 | 253 | 7 | 53.7 | 36.14 |
Ishant Sharma | RFM | 37.99 | 19 | 435 | 273 | 7 | 62.1 | 39.00 |
Steve Harmison | RFM | 31.82 | 17 | 270 | 140 | 6 | 45.0 | 23.33 |
Anil Kumble | rlb | 29.65 | 14 | 469 | 276 | 6 | 78.2 | 46.00 |
Zaheer Khan | LFM | 32.36 | 19 | 460 | 260 | 5 | 92.0 | 52.00 |
Ravindra Jadeja | lsp | 19.85 | 6 | 190 | 72 | 5 | 38.0 | 14.40 |
Rangana Herath | lsp | 29.52 | 8 | 309 | 192 | 4 | 77.2 | 48.00 |
Matthew Hoggard | RFM | 30.50 | 12 | 243 | 158 | 4 | 60.8 | 39.50 |
Mohammad Asif | RFM | 24.37 | 8 | 198 | 87 | 4 | 49.5 | 21.75 |
Total for 10 batsmen | 3217 | 1868 | 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.
Bowler | Type | BowAvge | Inns | Balls | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|
Harbhajan Singh | rob | 32.38 | 23 | 527 | 372 | 70.6% | 135 | 25.6% | 20 | 3.8% |
Anil Kumble | rlb | 29.65 | 14 | 469 | 335 | 71.4% | 98 | 20.9% | 36 | 7.7% |
Zaheer Khan | LFM | 32.36 | 19 | 460 | 334 | 72.6% | 94 | 20.4% | 32 | 7.0% |
Ishant Sharma | RFM | 37.99 | 19 | 435 | 309 | 71.0% | 92 | 21.1% | 37 | 8.5% |
Dale Steyn | RF | 22.66 | 19 | 376 | 253 | 67.3% | 94 | 25.0% | 30 | 8.0% |
Morne Morkel | RF | 29.98 | 12 | 375 | 254 | 67.7% | 79 | 21.1% | 42 | 11.2% |
Andrew Flintoff | RFM | 32.79 | 17 | 375 | 280 | 74.7% | 75 | 20.0% | 20 | 5.3% |
R Ashwin | rob | 28.53 | 8 | 355 | 227 | 63.9% | 100 | 28.2% | 29 | 8.2% |
Daniel Vettori | lsp | 34.42 | 11 | 336 | 238 | 70.8% | 80 | 23.8% | 18 | 5.4% |
Graeme Swann | rob | 28.73 | 11 | 332 | 253 | 76.2% | 65 | 19.6% | 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.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|---|
Andrew Flintoff | RFM | 66.2 | 17 | 375 | 0 | 375.0 |
R Ashwin | rob | 59.1 | 8 | 355 | 1 | 355.0 |
Tim Southee | RFM | 65.1 | 7 | 273 | 0 | 273.0 |
Chris Martin | RFM | 60.2 | 10 | 257 | 1 | 257.0 |
Virender Sehwag | rob | 93.3 | 8 | 234 | 0 | 234.0 |
Jacques Kallis | RFM | 68.9 | 11 | 229 | 0 | 229.0 |
Ashley Giles | lsp | 85.2 | 9 | 222 | 1 | 222.0 |
Makhaya Ntini | RF | 53.4 | 9 | 204 | 0 | 204.0 |
M Muralitharan | rob | 55.0 | 4 | 178 | 0 | 178.0 |
Mohammad Amir | RF | 56.2 | 6 | 171 | 1 | 171.0 |
Total for 10 batsmen | 2498 | 4 | 624.5 |
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.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike 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 | 57.8 | 21 | 267 | 7 | 38.1 |
Amit Mishra | rlb | 81.3 | 3 | 121 | 3 | 40.3 |
Steve Harmison | RFM | 59.2 | 17 | 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 | 41.2 | 19 | 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?
Bowler | Type | CareerScRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Imran Tahir | rlb | 55.7 | 5 | 109 | 119 | 109.2 | 50 | 45.9% | 42 | 38.5% | 17 | 15.6% |
Umesh Yadav | RFM | 55.7 | 6 | 153 | 122 | 79.7 | 102 | 66.7% | 34 | 22.2% | 18 | 11.8% |
Morne Morkel | RF | 55.7 | 12 | 375 | 277 | 73.9 | 254 | 67.7% | 79 | 21.1% | 42 | 11.2% |
R Ashwin | rob | 55.7 | 8 | 355 | 247 | 69.6 | 227 | 63.9% | 100 | 28.2% | 29 | 8.2% |
Danish Kaneria | rlb | 55.7 | 8 | 221 | 152 | 68.8 | 135 | 61.1% | 73 | 33.0% | 13 | 5.9% |
Dale Steyn | RF | 55.7 | 19 | 376 | 253 | 67.3 | 253 | 67.3% | 94 | 25.0% | 30 | 8.0% |
Ashley Giles | lsp | 55.7 | 9 | 222 | 149 | 67.1 | 143 | 64.4% | 60 | 27.0% | 19 | 8.6% |
Chris Martin | RFM | 55.7 | 10 | 257 | 174 | 67.7 | 185 | 72.0% | 49 | 19.1% | 24 | 9.3% |
Chanaka Welegedara | rob | 55.7 | 7 | 123 | 83 | 67.5 | 92 | 74.8% | 18 | 14.6% | 13 | 10.6% |
Monty Panesar | lsp | 55.7 | 4 | 136 | 89 | 65.4 | 89 | 65.4% | 36 | 26.5% | 11 | 8.1% |
Total for 10 batsmen | 2327 | 1665 | 71.6 |
Clarke dismissed Imran Tahir from his presence. Look at the good scoring rates against Dale Steyn and Morne Morkel.
Bowler | Type | CarScrRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Ravindra Jadeja | lsp | 55.7 | 6 | 190 | 72 | 37.9 | 154 | 81.1% | 27 | 14.2% | 9 | 4.7% |
Paul Harris | lsp | 55.7 | 11 | 324 | 127 | 39.2 | 242 | 74.7% | 71 | 21.9% | 11 | 3.4% |
Darren Sammy | RFM | 55.7 | 7 | 125 | 49 | 39.2 | 95 | 76.0% | 27 | 21.6% | 3 | 2.4% |
Dwayne Bravo | RFM | 55.7 | 8 | 156 | 64 | 41.0 | 124 | 79.5% | 27 | 17.3% | 6 | 3.8% |
Fidel Edwards | RF | 55.7 | 6 | 124 | 52 | 41.9 | 94 | 75.8% | 25 | 20.2% | 5 | 4.0% |
Amit Mishra | rlb | 55.7 | 3 | 121 | 52 | 43.0 | 95 | 78.5% | 21 | 17.4% | 5 | 4.1% |
Mohammad Asif | RFM | 55.7 | 8 | 198 | 87 | 43.9 | 159 | 80.3% | 28 | 14.1% | 11 | 5.6% |
Doug Bracewell | RFM | 55.7 | 3 | 102 | 44 | 43.1 | 82 | 80.4% | 14 | 13.7% | 6 | 5.9% |
Mohammad Amir | RF | 55.7 | 6 | 171 | 76 | 44.4 | 136 | 79.5% | 27 | 15.8% | 9 | 5.3% |
Iain O'Brien | RFM | 55.7 | 3 | 109 | 48 | 44.0 | 85 | 78.0% | 17 | 15.6% | 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
Bowler | Type | BowAvge | Inns | Balls | Runs | Wickets | StrikeRate | AvgeVsBowler |
---|---|---|---|---|---|---|---|---|
M Muralitharan | rob | 22.73 | 9 | 235 | 168 | 6 | 39.2 | 28.00 |
Brett Lee | RF | 30.82 | 17 | 324 | 228 | 6 | 54.0 | 38.00 |
Glenn McGrath | RFM | 21.64 | 13 | 270 | 135 | 5 | 54.0 | 27.00 |
Shane Warne | rlb | 25.42 | 18 | 521 | 308 | 5 | 104.2 | 61.60 |
S Sreesanth | RFM | 37.61 | 13 | 231 | 142 | 5 | 46.2 | 28.40 |
Morne Morkel | RF | 29.98 | 15 | 241 | 172 | 5 | 48.2 | 34.40 |
Peter Siddle | RFM | 28.23 | 11 | 208 | 103 | 5 | 41.6 | 20.60 |
Saeed Ajmal | rob | 27.60 | 7 | 104 | 64 | 5 | 20.8 | 12.80 |
Shakib Al Hasan | lsp | 32.75 | 7 | 172 | 110 | 4 | 43.0 | 27.50 |
Daniel Vettori | lsp | 34.42 | 8 | 282 | 114 | 4 | 70.5 | 28.50 |
Total for 10 batsmen | 2588 | 1544 | 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.
Bowler | Type | BowAvge | Inns | Balls | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|
Shane Warne | rlb | 25.42 | 18 | 521 | 362 | 69.5% | 126 | 24.2% | 35 | 6.7% |
Brett Lee | RF | 30.82 | 17 | 324 | 218 | 67.3% | 81 | 25.0% | 28 | 8.6% |
Anil Kumble | rlb | 29.65 | 11 | 310 | 224 | 72.3% | 62 | 20.0% | 24 | 7.7% |
Ishant Sharma | RFM | 37.99 | 9 | 306 | 200 | 65.4% | 75 | 24.5% | 32 | 10.5% |
Daniel Vettori | lsp | 34.42 | 8 | 282 | 217 | 77.0% | 54 | 19.1% | 11 | 3.9% |
Glenn McGrath | RFM | 21.64 | 13 | 270 | 206 | 76.3% | 46 | 17.0% | 18 | 6.7% |
Harbhajan Singh | rob | 32.38 | 10 | 264 | 164 | 62.1% | 82 | 31.1% | 18 | 6.8% |
Zaheer Khan | LFM | 32.36 | 11 | 250 | 190 | 76.0% | 45 | 18.0% | 18 | 7.2% |
Danish Kaneria | rlb | 34.80 | 11 | 249 | 154 | 61.8% | 67 | 26.9% | 28 | 11.2% |
Stuart Clark | RFM | 23.86 | 10 | 247 | 187 | 75.7% | 54 | 21.9% | 7 | 2.8% |
This list is led by the older bowlers.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|---|
Ishant Sharma | RFM | 68.4 | 9 | 306 | 1 | 306.0 |
Stuart Clark | RFM | 54.7 | 10 | 247 | 1 | 247.0 |
Daren Powell | RFM | 83.4 | 9 | 196 | 0 | 196.0 |
Amit Mishra | rlb | 81.3 | 4 | 169 | 0 | 169.0 |
Praveen Kumar | RFM | 59.7 | 4 | 164 | 1 | 164.0 |
Anil Kumble | rlb | 66.0 | 11 | 310 | 2 | 155.0 |
Chris Martin | RFM | 60.2 | 8 | 155 | 0 | 155.0 |
Harbhajan Singh | rob | 68.5 | 10 | 264 | 2 | 132.0 |
Makhaya Ntini | RF | 53.4 | 8 | 129 | 1 | 129.0 |
Zaheer Khan | LFM | 59.7 | 11 | 250 | 2 | 125.0 |
Total for 10 batsmen | 2190 | 10 | 219.0 |
There are six Indian bowlers in this table indicating that the Indian bowlers found it difficult to dismiss Pietersen quickly.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|---|
Saeed Ajmal | rob | 62.1 | 7 | 104 | 5 | 20.8 |
M Muralitharan | rob | 55.0 | 9 | 235 | 6 | 39.2 |
Peter Siddle | RFM | 56.6 | 11 | 208 | 5 | 41.6 |
Shakib Al Hasan | lsp | 68.3 | 7 | 172 | 4 | 43.0 |
Fidel Edwards | RF | 58.2 | 12 | 175 | 4 | 43.8 |
S Sreesanth | RFM | 62.3 | 13 | 231 | 5 | 46.2 |
Umar Gul | RFM | 58.9 | 10 | 139 | 3 | 46.3 |
Morne Morkel | RF | 55.1 | 15 | 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.
Bowler | Type | CareerScRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Dwayne Bravo | RFM | 62.5 | 4 | 122 | 103 | 84.4 | 71 | 58.2% | 38 | 31.1% | 13 | 10.7% |
Dale Steyn | RF | 62.5 | 11 | 187 | 155 | 82.9 | 135 | 72.2% | 24 | 12.8% | 30 | 16.0% |
Jerome Taylor | RF | 62.5 | 9 | 121 | 99 | 81.8 | 72 | 59.5% | 35 | 28.9% | 14 | 11.6% |
Danish Kaneria | rlb | 62.5 | 11 | 249 | 201 | 80.7 | 154 | 61.8% | 67 | 26.9% | 28 | 11.2% |
Makhaya Ntini | RF | 62.5 | 8 | 129 | 103 | 79.8 | 90 | 69.8% | 24 | 18.6% | 17 | 13.2% |
Amit Mishra | rlb | 62.5 | 4 | 169 | 130 | 76.9 | 105 | 62.1% | 44 | 26.0% | 20 | 11.8% |
Fidel Edwards | RF | 62.5 | 12 | 175 | 129 | 73.7 | 107 | 61.1% | 53 | 30.3% | 16 | 9.1% |
Chris Gayle | rob | 62.5 | 8 | 165 | 120 | 72.7 | 86 | 52.1% | 71 | 43.0% | 8 | 4.8% |
Morne Morkel | RF | 62.5 | 15 | 241 | 172 | 71.4 | 169 | 70.1% | 51 | 21.2% | 24 | 10.0% |
M Muralitharan | rob | 62.5 | 9 | 235 | 168 | 71.5 | 151 | 64.3% | 63 | 26.8% | 21 | 8.9% |
Total for 10 batsmen | 1793 | 1380 | 77.0 |
To score at nearly 5 runs per over against Steyn must be Pietersen's crowning achievement.
Bowler | Type | CarScrRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Jacob Oram | RM | 62.5 | 6 | 114 | 34 | 29.8 | 95 | 83.3% | 17 | 14.9% | 3 | 2.6% |
Ben Hilfenhaus | RFM | 62.5 | 8 | 194 | 75 | 38.7 | 157 | 80.9% | 29 | 14.9% | 8 | 4.1% |
Stuart Clark | RFM | 62.5 | 10 | 247 | 96 | 38.9 | 187 | 75.7% | 54 | 21.9% | 7 | 2.8% |
Daniel Vettori | lsp | 62.5 | 8 | 282 | 114 | 40.4 | 217 | 77.0% | 54 | 19.1% | 11 | 3.9% |
Praveen Kumar | RFM | 62.5 | 4 | 164 | 76 | 46.3 | 122 | 74.4% | 33 | 20.1% | 9 | 5.5% |
Chaminda Vaas | LFM | 62.5 | 10 | 159 | 74 | 46.5 | 124 | 78.0% | 25 | 15.7% | 10 | 6.3% |
Sulieman Benn | lsp | 62.5 | 7 | 168 | 79 | 47.0 | 118 | 70.2% | 43 | 25.6% | 7 | 4.2% |
Peter Siddle | RFM | 62.5 | 11 | 208 | 103 | 49.5 | 163 | 78.4% | 31 | 14.9% | 15 | 7.2% |
Glenn McGrath | RFM | 62.5 | 13 | 270 | 135 | 50.0 | 206 | 76.3% | 46 | 17.0% | 18 | 6.7% |
Kyle Mills | RM | 62.5 | 6 | 104 | 54 | 51.9 | 78 | 75.0% | 20 | 19.2% | 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
Bowler | Type | BowAvge | Inns | Balls | Runs | Wickets | StrikeRate | AvgeVsBowler |
---|---|---|---|---|---|---|---|---|
Ishant Sharma | RFM | 37.99 | 12 | 350 | 130 | 7 | 50.0 | 18.57 |
Morne Morkel | RF | 29.98 | 18 | 428 | 175 | 6 | 71.3 | 29.17 |
Umar Gul | RFM | 34.07 | 14 | 262 | 120 | 6 | 43.7 | 20.00 |
Stuart Clark | RFM | 23.86 | 8 | 132 | 35 | 5 | 26.4 | 7.00 |
Zaheer Khan | LFM | 32.36 | 15 | 384 | 200 | 4 | 96.0 | 50.00 |
Mitchell Johnson | LFM | 30.93 | 12 | 268 | 206 | 4 | 67.0 | 51.50 |
Peter Siddle | RFM | 28.23 | 15 | 386 | 146 | 4 | 96.5 | 36.50 |
R Ashwin | rob | 28.53 | 7 | 510 | 221 | 4 | 127.5 | 55.25 |
Trent Boult | RFM | 29.12 | 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 | 3089 | 1364 | 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.
Bowler | Type | BowAvge | Inns | Balls | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|
R Ashwin | rob | 28.53 | 7 | 510 | 396 | 77.6% | 87 | 17.1% | 27 | 5.3% |
M Muralitharan | rob | 22.73 | 8 | 450 | 358 | 79.6% | 78 | 17.3% | 14 | 3.1% |
Ben Hilfenhaus | RFM | 28.51 | 15 | 440 | 350 | 79.5% | 65 | 14.8% | 27 | 6.1% |
Morne Morkel | RF | 29.98 | 18 | 428 | 337 | 78.7% | 76 | 17.8% | 19 | 4.4% |
Peter Siddle | RFM | 28.23 | 15 | 386 | 307 | 79.5% | 63 | 16.3% | 17 | 4.4% |
Zaheer Khan | LFM | 32.36 | 15 | 384 | 300 | 78.1% | 54 | 14.1% | 32 | 8.3% |
Ishant Sharma | RFM | 37.99 | 12 | 350 | 293 | 83.7% | 38 | 10.9% | 21 | 6.0% |
Jerome Taylor | RF | 35.65 | 15 | 349 | 257 | 73.6% | 62 | 17.8% | 30 | 8.6% |
Fidel Edwards | RF | 37.87 | 17 | 335 | 242 | 72.2% | 71 | 21.2% | 22 | 6.6% |
Dale Steyn | RF | 22.66 | 12 | 329 | 259 | 78.7% | 52 | 15.8% | 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.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|---|
Ben Hilfenhaus | RFM | 61.4 | 15 | 440 | 1 | 440.0 |
Pragyan Ojha | lsp | 70.9 | 7 | 317 | 1 | 317.0 |
S Sreesanth | RFM | 62.3 | 10 | 308 | 0 | 308.0 |
Harbhajan Singh | rob | 68.5 | 8 | 291 | 1 | 291.0 |
Danish Kaneria | rlb | 67.8 | 7 | 265 | 1 | 265.0 |
Tim Southee | RFM | 65.1 | 10 | 264 | 0 | 264.0 |
Suranga Lakmal | RFM | 108.2 | 7 | 252 | 1 | 252.0 |
Sulieman Benn | lsp | 85.9 | 6 | 239 | 1 | 239.0 |
M Muralitharan | rob | 55.0 | 8 | 450 | 2 | 225.0 |
Xavier Doherty | lsp | 131.1 | 3 | 200 | 0 | 200.0 |
Total for 10 batsmen | 3026 | 8 | 378.2 |
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.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike 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 | 58.9 | 14 | 262 | 6 | 43.7 |
Kyle Mills | RM | 66.0 | 8 | 148 | 3 | 49.3 |
Ishant Sharma | RFM | 68.4 | 12 | 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 | 52.0 | 10 | 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.
Bowler | Type | CareerScRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Mitchell Johnson | LFM | 47.4 | 12 | 268 | 206 | 76.9 | 167 | 62.3% | 77 | 28.7% | 25 | 9.3% |
S Sreesanth | RFM | 47.4 | 10 | 308 | 201 | 65.3 | 222 | 72.1% | 55 | 17.9% | 32 | 10.4% |
Abdur Razzak | lsp | 47.4 | 4 | 115 | 73 | 63.5 | 68 | 59.1% | 41 | 35.7% | 6 | 5.2% |
Chanaka Welegedara | rob | 47.4 | 5 | 134 | 82 | 61.2 | 100 | 74.6% | 21 | 15.7% | 13 | 9.7% |
Jerome Taylor | RF | 47.4 | 15 | 349 | 207 | 59.3 | 257 | 73.6% | 62 | 17.8% | 30 | 8.6% |
Shakib Al Hasan | lsp | 47.4 | 4 | 114 | 67 | 58.8 | 72 | 63.2% | 36 | 31.6% | 6 | 5.3% |
Paul Harris | lsp | 47.4 | 8 | 184 | 107 | 58.2 | 128 | 69.6% | 45 | 24.5% | 11 | 6.0% |
Tillakaratne Dilshan | rob | 47.4 | 8 | 116 | 64 | 55.2 | 82 | 70.7% | 26 | 22.4% | 8 | 6.9% |
Neil Wagner | RFM | 47.4 | 8 | 165 | 92 | 55.8 | 120 | 72.7% | 34 | 20.6% | 11 | 6.7% |
Dilhara Fernando | RFM | 47.4 | 5 | 176 | 98 | 55.7 | 129 | 73.3% | 34 | 19.3% | 13 | 7.4% |
Total for 10 batsmen | 1929 | 1197 | 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.
Bowler | Type | CarScrRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Stuart Clark | RFM | 47.4 | 8 | 132 | 35 | 26.5 | 112 | 84.8% | 17 | 12.9% | 3 | 2.3% |
Trent Boult | RFM | 47.4 | 9 | 221 | 62 | 28.1 | 193 | 87.3% | 22 | 10.0% | 7 | 3.2% |
Chris Gayle | rob | 47.4 | 8 | 259 | 85 | 32.8 | 197 | 76.1% | 59 | 22.8% | 3 | 1.2% |
M Muralitharan | rob | 47.4 | 8 | 450 | 152 | 33.8 | 358 | 79.6% | 78 | 17.3% | 14 | 3.1% |
Saeed Ajmal | rob | 47.4 | 5 | 254 | 88 | 34.6 | 210 | 82.7% | 33 | 13.0% | 11 | 4.3% |
Danish Kaneria | rlb | 47.4 | 7 | 265 | 91 | 34.3 | 209 | 78.9% | 49 | 18.5% | 7 | 2.6% |
Jacques Kallis | RFM | 47.4 | 10 | 169 | 62 | 36.7 | 136 | 80.5% | 25 | 14.8% | 8 | 4.7% |
Dwayne Bravo | RFM | 47.4 | 5 | 134 | 50 | 37.3 | 110 | 82.1% | 21 | 15.7% | 4 | 3.0% |
Ishant Sharma | RFM | 47.4 | 12 | 350 | 130 | 37.1 | 293 | 83.7% | 38 | 10.9% | 21 | 6.0% |
Rangana Herath | lsp | 47.4 | 7 | 247 | 93 | 37.7 | 184 | 74.5% | 56 | 22.7% | 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
Bowler | Type | BowAvge | Inns | Balls | Runs | Wickets | StrikeRate | AvgeVsBowler |
---|---|---|---|---|---|---|---|---|
S Sreesanth | RFM | 37.61 | 15 | 234 | 155 | 6 | 39.0 | 25.83 |
Mitchell Johnson | LFM | 30.93 | 17 | 374 | 245 | 6 | 62.3 | 40.83 |
Harbhajan Singh | rob | 32.38 | 14 | 606 | 291 | 5 | 121.2 | 58.20 |
Mohammad Asif | RFM | 24.37 | 8 | 129 | 60 | 5 | 25.8 | 12.00 |
Peter Siddle | RFM | 28.23 | 17 | 465 | 173 | 4 | 116.2 | 43.25 |
Steve Harmison | RFM | 31.82 | 5 | 68 | 38 | 3 | 22.7 | 12.67 |
Stuart Broad | RFM | 30.94 | 15 | 437 | 226 | 3 | 145.7 | 75.33 |
Abdur Rehman | lsp | 28.41 | 6 | 232 | 117 | 3 | 77.3 | 39.00 |
Shane Shillingford | rob | 31.23 | 5 | 102 | 42 | 3 | 34.0 | 14.00 |
Daniel Vettori | lsp | 34.42 | 8 | 320 | 133 | 2 | 160.0 | 66.50 |
Total for 10 batsmen | 2967 | 1480 | 40 | 74.2 | 37.00 |
Bowler | Type | BowAvge | Inns | Balls | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|
Harbhajan Singh | rob | 32.38 | 14 | 606 | 423 | 69.8% | 159 | 26.2% | 24 | 4.0% |
Peter Siddle | RFM | 28.23 | 17 | 465 | 394 | 84.7% | 45 | 9.7% | 27 | 5.8% |
Stuart Broad | RFM | 30.94 | 15 | 437 | 339 | 77.6% | 73 | 16.7% | 31 | 7.1% |
James Anderson | RFM | 29.70 | 15 | 429 | 310 | 72.3% | 84 | 19.6% | 37 | 8.6% |
Graeme Swann | rob | 28.73 | 6 | 375 | 261 | 69.6% | 95 | 25.3% | 19 | 5.1% |
Mitchell Johnson | LFM | 30.93 | 17 | 374 | 264 | 70.6% | 79 | 21.1% | 34 | 9.1% |
Amit Mishra | rlb | 43.30 | 3 | 326 | 262 | 80.4% | 54 | 16.6% | 10 | 3.1% |
Daniel Vettori | lsp | 34.42 | 8 | 320 | 234 | 73.1% | 74 | 23.1% | 12 | 3.8% |
Zaheer Khan | LFM | 32.36 | 10 | 280 | 205 | 73.2% | 51 | 18.2% | 24 | 8.6% |
Saeed Ajmal | rob | 27.60 | 7 | 274 | 174 | 63.5% | 87 | 31.8% | 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.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|---|
Amit Mishra | rlb | 81.3 | 3 | 326 | 0 | 326.0 |
Chris Martin | RFM | 60.2 | 11 | 251 | 0 | 251.0 |
James Anderson | RFM | 57.8 | 15 | 429 | 2 | 214.5 |
Danish Kaneria | rlb | 67.8 | 8 | 202 | 0 | 202.0 |
Doug Bracewell | RFM | 60.3 | 7 | 195 | 1 | 195.0 |
Graeme Swann | rob | 59.2 | 6 | 375 | 2 | 187.5 |
Umar Gul | RFM | 58.9 | 10 | 184 | 0 | 184.0 |
Ben Hilfenhaus | RFM | 61.4 | 7 | 164 | 1 | 164.0 |
Daniel Vettori | lsp | 79.7 | 8 | 320 | 2 | 160.0 |
Stuart Broad | RFM | 60.6 | 15 | 437 | 3 | 145.7 |
Total for 10 batsmen | 2883 | 11 | 262.1 |
There are quality spinners in this lot, indicating the comfort with which Amla played spinners.
Bowler | Type | BowCarStRate | Inns | Balls | Wickets | Strike 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 | 62.3 | 15 | 234 | 6 | 39.0 |
Mitchell Johnson | LFM | 55.3 | 17 | 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.
Bowler | Type | CareerScRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Nathan Lyon | rob | 52.6 | 8 | 134 | 106 | 79.1 | 77 | 57.5% | 47 | 35.1% | 10 | 7.5% |
S Sreesanth | RFM | 52.6 | 15 | 234 | 155 | 66.2 | 172 | 73.5% | 37 | 15.8% | 25 | 10.7% |
Mitchell Johnson | LFM | 52.6 | 17 | 374 | 245 | 65.5 | 264 | 70.6% | 79 | 21.1% | 34 | 9.1% |
Ishant Sharma | RFM | 52.6 | 7 | 258 | 165 | 64.0 | 177 | 68.6% | 58 | 22.5% | 23 | 8.9% |
Tim Bresnan | RFM | 52.6 | 3 | 128 | 79 | 61.7 | 89 | 69.5% | 29 | 22.7% | 10 | 7.8% |
Shahadat Hossain | RFM | 52.6 | 5 | 106 | 64 | 60.4 | 76 | 71.7% | 22 | 20.8% | 9 | 8.5% |
Virender Sehwag | rob | 52.6 | 5 | 113 | 68 | 60.2 | 79 | 69.9% | 24 | 21.2% | 10 | 8.8% |
Umar Gul | RFM | 52.6 | 10 | 184 | 110 | 59.8 | 130 | 70.7% | 41 | 22.3% | 14 | 7.6% |
Mark Gillespie | RFM | 52.6 | 4 | 103 | 61 | 59.2 | 79 | 76.7% | 16 | 15.5% | 9 | 8.7% |
Saeed Ajmal | rob | 52.6 | 7 | 274 | 164 | 59.9 | 174 | 63.5% | 87 | 31.8% | 13 | 4.7% |
Total for 10 batsmen | 1908 | 1217 | 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.
Bowler | Type | CarScrRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Amit Mishra | rlb | 52.6 | 3 | 326 | 99 | 30.4 | 262 | 80.4% | 54 | 16.6% | 10 | 3.1% |
James Pattinson | RFM | 52.6 | 3 | 103 | 37 | 35.9 | 86 | 83.5% | 16 | 15.5% | 3 | 2.9% |
Danish Kaneria | rlb | 52.6 | 8 | 202 | 74 | 36.6 | 149 | 73.8% | 47 | 23.3% | 6 | 3.0% |
Peter Siddle | RFM | 52.6 | 17 | 465 | 173 | 37.2 | 394 | 84.7% | 45 | 9.7% | 27 | 5.8% |
Anil Kumble | rlb | 52.6 | 7 | 224 | 83 | 37.1 | 173 | 77.2% | 44 | 19.6% | 7 | 3.1% |
Mohammad Hafeez | rob | 52.6 | 7 | 129 | 52 | 40.3 | 93 | 72.1% | 31 | 24.0% | 5 | 3.9% |
Shane Shillingford | rob | 52.6 | 5 | 102 | 42 | 41.2 | 77 | 75.5% | 20 | 19.6% | 5 | 4.9% |
Daniel Vettori | lsp | 52.6 | 8 | 320 | 133 | 41.6 | 234 | 73.1% | 74 | 23.1% | 12 | 3.8% |
Chris Martin | RFM | 52.6 | 11 | 251 | 108 | 43.0 | 201 | 80.1% | 37 | 14.7% | 14 | 5.6% |
Mohammad Asif | RFM | 52.6 | 8 | 129 | 60 | 46.5 | 105 | 81.4% | 14 | 10.9% | 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.
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
Balls bowled: Sangakkara -Ajmal 906
Shivnarine Chanderpaul-Harbhajan Singh 790
Kumar Sangakkara -Harbhajan Singh 742
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.
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
Batsman | BatAvge | Inns | Balls | Runs | Wickets | StrikeRate | AvgeVsBowler |
---|---|---|---|---|---|---|---|
Mohammad Hafeez | 35.12 | 14 | 130 | 87 | 8 | 16.2 | 10.88 |
MJ Clarke | 52.34 | 19 | 376 | 253 | 7 | 53.7 | 36.14 |
MEK Hussey | 51.53 | 17 | 228 | 89 | 7 | 32.6 | 12.71 |
IJL Trott | 50.01 | 11 | 150 | 65 | 7 | 21.4 | 9.29 |
V Sehwag | 49.34 | 16 | 257 | 208 | 7 | 36.7 | 29.71 |
Harbhajan Singh | 18.36 | 10 | 59 | 34 | 7 | 8.4 | 4.86 |
BB McCullum | 35.39 | 15 | 224 | 129 | 6 | 37.3 | 21.50 |
Younis Khan | 50.74 | 13 | 293 | 149 | 5 | 58.6 | 29.80 |
SM Katich | 45.03 | 12 | 291 | 162 | 5 | 58.2 | 32.40 |
RT Ponting | 51.87 | 14 | 228 | 144 | 4 | 57.0 | 36.00 |
Total for 10 batsmen | 2236 | 1320 | 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.
Batsman | BatAvge | Inns | Balls | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|
MJ Clarke | 52.34 | 19 | 376 | 253 | 67.3% | 94 | 25.0% | 30 | 8.0% |
AJ Strauss | 40.91 | 16 | 360 | 281 | 78.1% | 51 | 14.2% | 28 | 7.8% |
AN Cook | 49.18 | 12 | 329 | 259 | 78.7% | 52 | 15.8% | 19 | 5.8% |
IR Bell | 45.58 | 13 | 310 | 241 | 77.7% | 49 | 15.8% | 20 | 6.5% |
SR Tendulkar | 53.87 | 11 | 310 | 239 | 77.1% | 50 | 16.1% | 21 | 6.8% |
Younis Khan | 50.74 | 13 | 293 | 225 | 76.8% | 51 | 17.4% | 19 | 6.5% |
SM Katich | 45.03 | 12 | 291 | 214 | 73.5% | 59 | 20.3% | 19 | 6.5% |
V Sehwag | 49.34 | 16 | 257 | 172 | 66.9% | 51 | 19.8% | 34 | 13.2% |
S Chanderpaul | 51.82 | 9 | 231 | 182 | 78.8% | 44 | 19.0% | 7 | 3.0% |
RT Ponting | 51.87 | 14 | 228 | 166 | 72.8% | 45 | 19.7% | 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.
Batsman | BatAvge | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
MJ Clarke | 52.34 | 19 | 376 | 253 | 67.3 | 253 | 67.3% | 94 | 25.0% | 30 | 8.0% |
V Sehwag | 49.34 | 16 | 257 | 208 | 80.9 | 172 | 66.9% | 51 | 19.8% | 34 | 13.2% |
AJ Strauss | 40.91 | 16 | 360 | 182 | 50.6 | 281 | 78.1% | 51 | 14.2% | 28 | 7.8% |
SM Katich | 45.03 | 12 | 291 | 162 | 55.7 | 214 | 73.5% | 59 | 20.3% | 19 | 6.5% |
KP Pietersen | 49.01 | 11 | 187 | 155 | 82.9 | 135 | 72.2% | 24 | 12.8% | 30 | 16.0% |
Younis Khan | 50.74 | 13 | 293 | 149 | 50.9 | 225 | 76.8% | 51 | 17.4% | 19 | 6.5% |
PJ Hughes | 33.00 | 10 | 220 | 149 | 67.7 | 154 | 70.0% | 43 | 19.5% | 23 | 10.5% |
SR Tendulkar | 53.87 | 11 | 310 | 149 | 48.1 | 239 | 77.1% | 50 | 16.1% | 21 | 6.8% |
AN Cook | 49.18 | 12 | 329 | 147 | 44.7 | 259 | 78.7% | 52 | 15.8% | 19 | 5.8% |
IR Bell | 45.58 | 13 | 310 | 144 | 46.5 | 241 | 77.7% | 49 | 15.8% | 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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|
Azhar Ali | 99.6 | 8 | 228 | 1 | 228.0 |
PJ Hughes | 60.0 | 10 | 220 | 1 | 220.0 |
KC Sangakkara | 97.1 | 8 | 203 | 1 | 203.0 |
AJ Strauss | 80.8 | 16 | 360 | 2 | 180.0 |
W Jaffer | 69.7 | 8 | 161 | 1 | 161.0 |
PD Collingwood | 79.7 | 5 | 153 | 0 | 153.0 |
TT Samaraweera | 88.2 | 6 | 150 | 0 | 150.0 |
S Chanderpaul | 100.5 | 9 | 231 | 2 | 115.5 |
AN Cook | 97.1 | 12 | 329 | 3 | 109.7 |
SP Fleming | 82.8 | 8 | 215 | 2 | 107.5 |
Total for 10 batsmen | 2250 | 13 | 173.1 |
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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike 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 | 60.3 | 14 | 130 | 8 | 16.2 |
AF Giles | 37.9 | 5 | 53 | 3 | 17.7 |
GP Swann | 25.4 | 8 | 78 | 4 | 19.5 |
IJL Trott | 98.2 | 11 | 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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike 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 | 23.8 | 10 | 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 | 28.3 | 11 | 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.
Batsman | CareerScRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
CH Gayle | 59.8 | 9 | 122 | 115 | 94.3 | 76 | 62.3% | 31 | 25.4% | 18 | 14.8% |
MG Johnson | 58.6 | 11 | 148 | 133 | 89.9 | 99 | 66.9% | 29 | 19.6% | 21 | 14.2% |
KP Pietersen | 62.8 | 11 | 187 | 155 | 82.9 | 135 | 72.2% | 24 | 12.8% | 30 | 16.0% |
V Sehwag | 82.2 | 16 | 257 | 208 | 80.9 | 172 | 66.9% | 51 | 19.8% | 34 | 13.2% |
DL Vettori | 58.1 | 10 | 127 | 94 | 74.0 | 88 | 69.3% | 24 | 18.9% | 15 | 11.8% |
MJ Prior | 63.0 | 9 | 135 | 101 | 74.8 | 89 | 65.9% | 31 | 23.0% | 15 | 11.1% |
MJ Clarke | 55.8 | 19 | 376 | 253 | 67.3 | 253 | 67.3% | 94 | 25.0% | 30 | 8.0% |
PJ Hughes | 53.8 | 10 | 220 | 149 | 67.7 | 154 | 70.0% | 43 | 19.5% | 23 | 10.5% |
Mohammad Hafeez | 53.6 | 14 | 130 | 87 | 66.9 | 97 | 74.6% | 19 | 14.6% | 14 | 10.8% |
KC Sangakkara | 54.0 | 8 | 203 | 131 | 64.5 | 150 | 73.9% | 33 | 16.3% | 21 | 10.3% |
Total for 10 batsmen | 1905 | 1426 | 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.
Batsman | CarScrRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
D Ganga | 38.9 | 6 | 106 | 23 | 21.7 | 91 | 85.8% | 14 | 13.2% | 1 | 0.9% |
KS Williamson | 40.3 | 8 | 151 | 37 | 24.5 | 130 | 86.1% | 18 | 11.9% | 3 | 2.0% |
Misbah-ul-Haq | 40.7 | 10 | 207 | 58 | 28.0 | 183 | 88.4% | 16 | 7.7% | 9 | 4.3% |
TT Samaraweera | 46.9 | 6 | 150 | 50 | 33.3 | 127 | 84.7% | 18 | 12.0% | 6 | 4.0% |
MHW Papps | 35.3 | 7 | 101 | 37 | 36.6 | 86 | 85.1% | 9 | 8.9% | 6 | 5.9% |
S Chanderpaul | 42.9 | 9 | 231 | 90 | 39.0 | 182 | 78.8% | 44 | 19.0% | 7 | 3.0% |
MJ Guptill | 43.4 | 10 | 190 | 73 | 38.4 | 160 | 84.2% | 18 | 9.5% | 12 | 6.3% |
Junaid Siddique | 41.4 | 7 | 114 | 45 | 39.5 | 91 | 79.8% | 17 | 14.9% | 6 | 5.3% |
MEK Hussey | 50.1 | 17 | 228 | 89 | 39.0 | 185 | 81.1% | 33 | 14.5% | 12 | 5.3% |
W Jaffer | 48.1 | 8 | 161 | 67 | 41.6 | 132 | 82.0% | 21 | 13.0% | 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
Batsman | BatAvge | Inns | Balls | Runs | Wickets | StrikeRate | AvgeVsBowler |
---|---|---|---|---|---|---|---|
SR Tendulkar | 53.87 | 23 | 350 | 208 | 9 | 38.9 | 23.11 |
JH Kallis | 56.10 | 22 | 419 | 177 | 7 | 59.9 | 25.29 |
KC Sangakkara | 56.99 | 10 | 241 | 147 | 6 | 40.2 | 24.50 |
MJ Clarke | 52.34 | 19 | 255 | 153 | 6 | 42.5 | 25.50 |
GC Smith | 48.63 | 27 | 701 | 411 | 6 | 116.8 | 68.50 |
MV Boucher | 30.30 | 21 | 273 | 161 | 6 | 45.5 | 26.83 |
R Dravid | 52.31 | 18 | 432 | 197 | 5 | 86.4 | 39.40 |
V Sehwag | 49.34 | 14 | 109 | 120 | 5 | 21.8 | 24.00 |
AG Prince | 41.65 | 13 | 247 | 113 | 5 | 49.4 | 22.60 |
RT Ponting | 51.87 | 19 | 347 | 233 | 4 | 86.8 | 58.25 |
Total for 10 batsmen | 3374 | 1920 | 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.
Batsman | BatAvge | Inns | Balls | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|
GC Smith | 48.63 | 27 | 701 | 504 | 71.9% | 142 | 20.3% | 57 | 8.1% |
R Dravid | 52.31 | 18 | 432 | 349 | 80.8% | 50 | 11.6% | 33 | 7.6% |
HM Amla | 52.12 | 15 | 429 | 310 | 72.3% | 84 | 19.6% | 37 | 8.6% |
SR Watson | 35.34 | 15 | 427 | 338 | 79.2% | 55 | 12.9% | 34 | 8.0% |
MEK Hussey | 51.53 | 17 | 424 | 323 | 76.2% | 75 | 17.7% | 26 | 6.1% |
JH Kallis | 56.10 | 22 | 419 | 337 | 80.4% | 60 | 14.3% | 23 | 5.5% |
G Gambhir | 44.19 | 16 | 398 | 331 | 83.2% | 43 | 10.8% | 24 | 6.0% |
AB de Villiers | 50.51 | 16 | 393 | 303 | 77.1% | 66 | 16.8% | 26 | 6.6% |
SR Tendulkar | 53.87 | 23 | 350 | 260 | 74.3% | 56 | 16.0% | 34 | 9.7% |
RT Ponting | 51.87 | 19 | 347 | 245 | 70.6% | 70 | 20.2% | 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.
Batsman | BatAvge | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
GC Smith | 48.63 | 27 | 701 | 411 | 58.6 | 504 | 71.9% | 142 | 20.3% | 57 | 8.1% |
HM Amla | 52.12 | 15 | 429 | 254 | 59.2 | 310 | 72.3% | 84 | 19.6% | 37 | 8.6% |
RT Ponting | 51.87 | 19 | 347 | 233 | 67.1 | 245 | 70.6% | 70 | 20.2% | 33 | 9.5% |
SR Watson | 35.34 | 15 | 427 | 217 | 50.8 | 338 | 79.2% | 55 | 12.9% | 34 | 8.0% |
MEK Hussey | 51.53 | 17 | 424 | 214 | 50.5 | 323 | 76.2% | 75 | 17.7% | 26 | 6.1% |
SR Tendulkar | 53.87 | 23 | 350 | 208 | 59.4 | 260 | 74.3% | 56 | 16.0% | 34 | 9.7% |
MS Dhoni | 39.71 | 19 | 347 | 201 | 57.9 | 258 | 74.4% | 59 | 17.0% | 32 | 9.2% |
R Dravid | 52.31 | 18 | 432 | 197 | 45.6 | 349 | 80.8% | 50 | 11.6% | 33 | 7.6% |
AB de Villiers | 50.51 | 16 | 393 | 193 | 49.1 | 303 | 77.1% | 66 | 16.8% | 26 | 6.6% |
RR Sarwan | 40.01 | 11 | 312 | 190 | 60.9 | 233 | 74.7% | 48 | 15.4% | 32 | 10.3% |
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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|
RR Sarwan | 81.1 | 11 | 312 | 1 | 312.0 |
HM Amla | 90.9 | 15 | 429 | 2 | 214.5 |
TT Samaraweera | 88.2 | 8 | 204 | 1 | 204.0 |
AB de Villiers | 82.0 | 16 | 393 | 2 | 196.5 |
SM Katich | 85.7 | 9 | 183 | 1 | 183.0 |
AN Petersen | 72.7 | 5 | 172 | 1 | 172.0 |
S Chanderpaul | 100.5 | 14 | 339 | 2 | 169.5 |
G Kirsten | 95.4 | 7 | 167 | 0 | 167.0 |
CA Pujara | 101.9 | 5 | 160 | 0 | 160.0 |
MN Samuels | 71.3 | 4 | 158 | 0 | 158.0 |
Total for 10 batsmen | 2517 | 10 | 251.7 |
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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike 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 | 58.0 | 14 | 109 | 5 | 21.8 |
SK Raina | 49.7 | 4 | 70 | 3 | 23.3 |
DG Brownlie | 63.5 | 7 | 102 | 4 | 25.5 |
JM How | 43.7 | 10 | 140 | 4 | 35.0 |
SPD Smith | 61.3 | 6 | 110 | 3 | 36.7 |
SR Tendulkar | 89.6 | 23 | 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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|
Umar Gul | 18.0 | 5 | 48 | 3 | 16.0 |
Z Khan | 18.6 | 7 | 49 | 3 | 16.3 |
PM Siddle | 28.3 | 10 | 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.
Batsman | CareerScRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
V Sehwag | 82.2 | 14 | 109 | 120 | 110.1 | 61 | 56.0% | 26 | 23.9% | 22 | 20.2% |
BB McCullum | 60.4 | 12 | 132 | 136 | 103.0 | 78 | 59.1% | 36 | 27.3% | 19 | 14.4% |
LRPL Taylor | 57.7 | 13 | 225 | 187 | 83.1 | 155 | 68.9% | 41 | 18.2% | 32 | 14.2% |
HH Gibbs | 50.3 | 8 | 190 | 159 | 83.7 | 137 | 72.1% | 25 | 13.2% | 31 | 16.3% |
BJ Haddin | 57.4 | 12 | 206 | 151 | 73.3 | 144 | 69.9% | 41 | 19.9% | 22 | 10.7% |
HD Rutherford | 65.7 | 8 | 137 | 97 | 70.8 | 98 | 71.5% | 22 | 16.1% | 17 | 12.4% |
RT Ponting | 58.7 | 19 | 347 | 233 | 67.1 | 245 | 70.6% | 70 | 20.2% | 33 | 9.5% |
G Kirsten | 43.4 | 7 | 167 | 111 | 66.5 | 123 | 73.7% | 26 | 15.6% | 18 | 10.8% |
CH Gayle | 59.8 | 11 | 160 | 101 | 63.1 | 119 | 74.4% | 26 | 16.2% | 16 | 10.0% |
JM How | 50.4 | 10 | 140 | 86 | 61.4 | 107 | 76.4% | 19 | 13.6% | 15 | 10.7% |
Total for 10 batsmen | 1813 | 1381 | 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.
Batsman | CarScrRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
D Ramdin | 48.3 | 7 | 182 | 45 | 24.7 | 156 | 85.7% | 22 | 12.1% | 4 | 2.2% |
MJ North | 48.1 | 8 | 195 | 50 | 25.6 | 173 | 88.7% | 16 | 8.2% | 7 | 3.6% |
PG Fulton | 42.4 | 9 | 295 | 88 | 29.8 | 257 | 87.1% | 26 | 8.8% | 12 | 4.1% |
AN Petersen | 50.9 | 5 | 172 | 52 | 30.2 | 147 | 85.5% | 17 | 9.9% | 8 | 4.7% |
Imran Farhat | 48.3 | 8 | 152 | 49 | 32.2 | 131 | 86.2% | 12 | 7.9% | 9 | 5.9% |
Azhar Ali | 39.1 | 10 | 241 | 81 | 33.6 | 203 | 84.2% | 28 | 11.6% | 11 | 4.6% |
Misbah-ul-Haq | 40.7 | 4 | 107 | 36 | 33.6 | 86 | 80.4% | 18 | 16.8% | 3 | 2.8% |
HAPW Jayawardene | 50.1 | 7 | 102 | 37 | 36.3 | 85 | 83.3% | 13 | 12.7% | 4 | 3.9% |
BP Nash | 43.3 | 8 | 121 | 44 | 36.4 | 100 | 82.6% | 16 | 13.2% | 6 | 5.0% |
MN Samuels | 48.5 | 4 | 158 | 60 | 38.0 | 128 | 81.0% | 22 | 13.9% | 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.
Batsman | BatAvge | Inns | Balls | Runs | Wickets | StrikeRate | AvgeVsBowler |
---|---|---|---|---|---|---|---|
ML Hayden | 50.74 | 15 | 356 | 226 | 7 | 50.9 | 32.29 |
JH Kallis | 56.10 | 18 | 676 | 382 | 6 | 112.7 | 63.67 |
DW Steyn | 13.97 | 8 | 75 | 35 | 6 | 12.5 | 5.83 |
HM Amla | 52.12 | 14 | 606 | 291 | 5 | 121.2 | 58.20 |
RT Ponting | 51.87 | 16 | 340 | 227 | 5 | 68.0 | 45.40 |
SM Katich | 45.03 | 14 | 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 | 30.79 | 10 | 227 | 119 | 5 | 45.4 | 23.80 |
M Morkel | 13.69 | 8 | 123 | 54 | 5 | 24.6 | 10.80 |
Total for 10 batsmen | 3239 | 1710 | 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.
Batsman | BatAvge | Inns | Balls | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|
S Chanderpaul | 51.82 | 18 | 790 | 632 | 80.0% | 138 | 17.5% | 20 | 2.5% |
KC Sangakkara | 56.99 | 18 | 742 | 574 | 77.4% | 144 | 19.4% | 27 | 3.6% |
JH Kallis | 56.10 | 18 | 676 | 412 | 60.9% | 242 | 35.8% | 22 | 3.3% |
DPMD Jayawardene | 49.57 | 20 | 649 | 395 | 60.9% | 217 | 33.4% | 38 | 5.9% |
HM Amla | 52.12 | 14 | 606 | 423 | 69.8% | 159 | 26.2% | 24 | 4.0% |
Younis Khan | 50.74 | 10 | 541 | 368 | 68.0% | 130 | 24.0% | 43 | 7.9% |
MJ Clarke | 52.34 | 23 | 527 | 372 | 70.6% | 135 | 25.6% | 20 | 3.8% |
MEK Hussey | 51.53 | 14 | 482 | 356 | 73.9% | 109 | 22.6% | 17 | 3.5% |
SM Katich | 45.03 | 14 | 432 | 336 | 77.8% | 75 | 17.4% | 21 | 4.9% |
AB de Villiers | 50.51 | 12 | 394 | 267 | 67.8% | 109 | 27.7% | 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.
Batsman | BatAvge | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
DPMD Jayawardene | 49.57 | 20 | 649 | 431 | 66.4 | 395 | 60.9% | 217 | 33.4% | 38 | 5.9% |
JH Kallis | 56.10 | 18 | 676 | 382 | 56.5 | 412 | 60.9% | 242 | 35.8% | 22 | 3.3% |
Younis Khan | 50.74 | 10 | 541 | 332 | 61.4 | 368 | 68.0% | 130 | 24.0% | 43 | 7.9% |
HM Amla | 52.12 | 14 | 606 | 291 | 48.0 | 423 | 69.8% | 159 | 26.2% | 24 | 4.0% |
KC Sangakkara | 56.99 | 18 | 742 | 287 | 38.7 | 574 | 77.4% | 144 | 19.4% | 27 | 3.6% |
S Chanderpaul | 51.82 | 18 | 790 | 260 | 32.9 | 632 | 80.0% | 138 | 17.5% | 20 | 2.5% |
MJ Clarke | 52.34 | 23 | 527 | 239 | 45.4 | 372 | 70.6% | 135 | 25.6% | 20 | 3.8% |
RT Ponting | 51.87 | 16 | 340 | 227 | 66.8 | 207 | 60.9% | 108 | 31.8% | 25 | 7.4% |
ML Hayden | 50.74 | 15 | 356 | 226 | 63.5 | 238 | 66.9% | 91 | 25.6% | 28 | 7.9% |
TM Dilshan | 40.99 | 13 | 308 | 221 | 71.8 | 188 | 61.0% | 97 | 31.5% | 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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike rate |
---|---|---|---|---|---|
S Chanderpaul | 100.5 | 18 | 790 | 2 | 395.0 |
AN Cook | 97.1 | 8 | 291 | 1 | 291.0 |
GW Flower | 81.4 | 8 | 277 | 0 | 277.0 |
Younis Khan | 89.4 | 10 | 541 | 2 | 270.5 |
MP Vaughan | 76.1 | 6 | 264 | 0 | 264.0 |
BB McCullum | 55.1 | 8 | 252 | 1 | 252.0 |
Misbah-ul-Haq | 88.6 | 6 | 248 | 0 | 248.0 |
KC Sangakkara | 97.1 | 18 | 742 | 3 | 247.3 |
AB de Villiers | 82.0 | 12 | 394 | 2 | 197.0 |
IR Bell | 79.7 | 9 | 181 | 1 | 181.0 |
Total for 10 batsmen | 3980 | 12 | 331.7 |
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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike 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.
Batsman | Career Balls/Inns | Inns | Balls | Wickets | Strike 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 | 10.9 | 10 | 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.
Batsman | CareerScRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
AC Gilchrist | 82.0 | 9 | 139 | 112 | 80.6 | 77 | 55.4% | 51 | 36.7% | 11 | 7.9% |
JL Langer | 54.2 | 5 | 170 | 128 | 75.3 | 107 | 62.9% | 46 | 27.1% | 17 | 10.0% |
TM Dilshan | 65.5 | 13 | 308 | 221 | 71.8 | 188 | 61.0% | 97 | 31.5% | 23 | 7.5% |
MJ Prior | 63.0 | 6 | 149 | 104 | 69.8 | 81 | 54.4% | 60 | 40.3% | 8 | 5.4% |
HAPW Jayawardene | 50.1 | 10 | 236 | 156 | 66.1 | 150 | 63.6% | 72 | 30.5% | 14 | 5.9% |
RT Ponting | 58.7 | 16 | 340 | 227 | 66.8 | 207 | 60.9% | 108 | 31.8% | 25 | 7.4% |
KP Pietersen | 62.8 | 10 | 264 | 176 | 66.7 | 164 | 62.1% | 82 | 31.1% | 18 | 6.8% |
Inzamam-ul-Haq | 54.0 | 4 | 109 | 72 | 66.1 | 68 | 62.4% | 33 | 30.3% | 8 | 7.3% |
DPMD Jayawardene | 51.5 | 20 | 649 | 431 | 66.4 | 395 | 60.9% | 217 | 33.4% | 38 | 5.9% |
ML Hayden | 60.1 | 15 | 356 | 226 | 63.5 | 238 | 66.9% | 91 | 25.6% | 28 | 7.9% |
Total for 10 batsmen | 2720 | 1853 | 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.
Batsman | CarScrRt | Inns | Balls | Runs | Scoring Rate | Dot Balls | % of total | 1/2/3 run balls | % of total | Boundary balls | % of total |
---|---|---|---|---|---|---|---|---|---|---|---|
Salman Butt | 47.2 | 6 | 146 | 21 | 14.4 | 132 | 90.4% | 13 | 8.9% | 1 | 0.7% |
BJ Haddin | 57.4 | 6 | 110 | 28 | 25.5 | 89 | 80.9% | 20 | 18.2% | 1 | 0.9% |
MH Richardson | 37.7 | 4 | 162 | 44 | 27.2 | 130 | 80.2% | 29 | 17.9% | 3 | 1.9% |
MJ Guptill | 43.4 | 4 | 114 | 33 | 28.9 | 93 | 81.6% | 19 | 16.7% | 2 | 1.8% |
GW Flower | 34.5 | 8 | 277 | 83 | 30.0 | 224 | 80.9% | 46 | 16.6% | 7 | 2.5% |
TR Gripper | 32.7 | 2 | 100 | 29 | 29.0 | 82 | 82.0% | 15 | 15.0% | 3 | 3.0% |
AJ Hall | 46.1 | 3 | 133 | 41 | 30.8 | 111 | 83.5% | 19 | 14.3% | 3 | 2.3% |
AG Prince | 43.7 | 11 | 229 | 69 | 30.1 | 187 | 81.7% | 36 | 15.7% | 6 | 2.6% |
JEC Franklin | 37.4 | 4 | 126 | 38 | 30.2 | 108 | 85.7% | 13 | 10.3% | 5 | 4.0% |
MA Butcher | 42.9 | 7 | 269 | 82 | 30.5 | 218 | 81.0% | 44 | 16.4% | 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.
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 20An 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.