Anantha Narayanan
A 100 random numbers that tell stories - loads of fun in store. Plus, another Bradman surprise
This is one heck of a "fun article": a completely irreverent look at cricket numbers. It is possible that the readers might get some additional insights. But that is not the objective. Time to have a chuckle, laugh, guffaw and look for your own number! Readers are encouraged to put in their own numbers and I will compile those, add some of my own and come out with a follow-up article on the same lines. The whackier the number is, the better.
I have selected, or rather I should say "the numbers selected themselves", 100 unique numbers and added descriptive elements for each. There is nothing structured about the selection. It has been done from all areas of cricketing numbers. Thus this allows you to do a similar thing and throw completely unexpected numbers at me. Of course, they should be verifiable. The 100th number in this article is a license given, only, to me. I stopped when I felt I had enough and the deadline approached, that is all.
0: The most famous zero in Test history. Bradman b Hollies 0 (2 balls). God's way of reminding us that everyone is fallible and imprinting the more romantic number 99.94 in everyone's minds.
: Number of runs scored by Ajit Agarkar in seven consecutive innings against Australia.
: Number of runs conceded by Brian Langford in a John Player League 40-overs match. His analysis was 8-8-0-0.
1: Runs needed by Tom Hayward to reach 2000 Test runs.
: Number of runs conceded by Courtney Walsh while capturing five ODI wickets
: Runs scored in six innings by Mohinder Amarnath.
1.008: India's scoring rate (RpO) in the Bridgetown Test during 1962. This was achieved over two days of batting and 185.3 overs.
1.31: William Attewell's Test career economy rate. Across 475 overs.
2.36: Chris Martin's batting average, in 104 innings.
3: Number of runs conceded by Phil Simmons against Pakistan in ten overs.
3.00: Scoring rate achieved by Kenya in a T20 match against Afghanistan during 2013.
4: Runs needed by Bradman in his last Test innings, to reach average of 100. Also the runs he fell short by.
4.15: Shahadat Hossain's Test career economy rate. Across 896 overs.
5: Number of times a batsman has been "timed out" in a first-class match.
5.803: Australia's scoring rate (RpO) in the Wanderers Test during 1902. This was achieved over 51 overs.
6: Number of times India crossed 400 in consecutive Test innings during 1986.
: The innings total of "The Bs" against England during 1810. Declared a first-class match? There were 9 Bs, one W and one L (Good they found the W since John Wells top-scored with 4). Incidentally there was a team called "Over 38s" in this tournament.
7: Number of hat-tricks achieved by Doug Wright.
8: Number of maidens bowled by Bishan Bedi and Simmons in an ODI innings.
9: Number of wicketkeeping dismissals by Tahir Rashid/Wayne James in an innings.
9.41: Bowling average of Samuel Cosstick who captured 106 first-class wickets.
10: Runs conceded by Hedley Verity while capturing ten wickets against Nottinghamshire.
: Number of catches taken by Wally Hammond in a match.
: Number of first-class 400s scored so far.
12: Most sixes in a Test innings: By Wasim Akram.
: Oxford University score vs MCC. Also Northamptonshire vs Gloucestershire.
: Estimated number of days it would have needed for the RPS, Colombo Test during 1997 between Sri Lanka and India to have a result.
12.52: Runs per over conceded by Lasith Malinga in an ODI match vs India.
15.00: New Zealand's scoring rate (RpO) in the T20 match against Scotland: Across 6.0 overs.
15.83: New Zealand's scoring rate (RpO) in an ODI match against Bangladesh: Across 6.0 overs.
17: Number of sixes scored by Australia against Zimbabwe in a Test innings during 2003.
19: Balls required by Ernie Toshack to capture five wickets.
: Number of times Glenn McGrath dismissed Mike Atherton.
20.50: R Ashwin's economy rate when he bowled two T20 overs against Australia.
21: Number of ODI matches Australia went through during 2003, undefeated.
22: Number of balls Bradman took to score 100 in a local match: 10x6s and 9x4s.
27: Number of Test matches West Indies went through during 1982-84, undefeated.
30: Number of players used by England in a five-Test series during 1921.
31: Number of innings Dera Ismail Khan would have needed to make Railways bat again. Scores: Railways 910. DIK 32 & 29.
32: Number of tied matches in ODI history.
34: Runs scored by Border against Natal, both innings put together in a match.
36: Pick a player: Sunil Gavaskar, Ravi Shastri, Garry Sobers, Yuvraj Singh or Herschelle Gibbs.
37: Number of 200s scored by Bradman.
49: Balls bowled by George Lohmann when he captured eight Test wickets.
52: Most fours in a Test innings. John Edrich 52x4s.
53: Balls Warwickshire needed to dismiss Hampshire.
62: The number of zeroes scored by Chris Martin.
67.34: Percentage of innings runs scored by Charles Bannerman in the very first Test ever played.
70.92: career bowling average of Mark Lawrence who captured 42 wickets.
72: Balls bowled by George Lohmann when he captured nine Test wickets.
76: Number of Extras conceded by Pakistan in a Test innings against India.
77: Runs conceded by Bert Vance in a single over on instructions from his captain in 1989-90.
: Balls played by Geoff Allott while scoring 0.
78: Test innings played by AB de Villiers before first duck.
87: The number of bowlers who have captured 10 wickets in an innings.
90: Balls remaining when Sri Lanka won a T20 match against Netherlands during 2014.
95: Runs scored by Australia and Pakistan in a full day during 1956.
: Number of c Marsh b Lillee dismissals.
109: Number of fours scored by Sri Lanka against India in a Test innings during 1997.
109.2: Total number of overs bowled in the Test won by Australia against South Africa during 1932.
140: Number of times Tich Freeman captured ten wickets in a match.
153: Number of runs scored by Brian Lara in the historic Bridgetown win against Australia.
168: Balls it took Nathan Astle to score 222.
175: Number of Kapil Dev runs at Tunbridge Wells. One of the greatest international innings ever.
189: The number imprinted in the minds of all cricket followers: Viv Richards' all-time classic at Old Trafford.
199: first-class hundreds scored by Jack Hobbs.
201.50: Bradman's average against South Africa in 1931-32.
216: Number of ODI matches played at Sharjah.
229: The lowest score at which a batsman is yet to be dismissed.
238: Most runs in boundaries in a Test innings. By Edrich: 52x4s + 5x6s.
247: The days taken for travel from Melbourne to Melbourne during the Australian tour of England in 1938. They left on Feb 25 and returned on Oct 29.
277: Balls remaining when England won an ODI match against Canada during 1979.
287: Highest debut innings ever: By Tip Foster.
290: New Zealand's record ODI win by runs over Ireland.
292: Runs scored by England when they won by innings and 202 runs.
299: For Martin Crowe, a never-to-be-reached target missed. For Bradman, only the third landmark missed.
303.00: Naeem Islam's Test bowling average. One wicket for 303.
304: Number of wickets captured in a single season by Tich Freeman.
307: Runs added by Alan Kippax and Hal Hooker for the tenth wicket.
331: Record partnership between Sachin Tendulkar and Rahul Dravid in ODIs.
350: Number of balls Trevor Bailey took to score his fifty against Australia.
362: Runs conceded by Arthur Mailey while bowling 64 8-ball overs and capturing 4 wickets.
375.00: Not the number you are thinking of. Highest first-class bowling average. SM Krishnakumar captured 1 wicket for 375 runs.
432: Number of balls bowled by Denis Atkinson without capturing a single wicket.
418: Number of stumpings effected by Les Ames in his first-class career.
434: Record ODI score by Australia: Lasted for less than four hours.
438: Second occurrence of 400-plus ODI score: On the same day.
501: Forget about hundreds, let us talk of "half a thousand" by one player: Highest first-class score, by Brian Lara.
522: Balls bowled by Chuck Fleetwood-Smith while capturing a single wicket.
551: Number of runs by which Pakistan exceeded their first innings at Bridgetown during 1958.
579: Biggest Test-win by an innings in history.
588: Most balls bowled by Sonny Ramadhin in a single Test innings.
624: Record Test partnership of Mahela Jayawardene and Kumar Sangakkara.
625: Runs scored by Bradman in three consecutive Test innings.
654: England's record fourth-innings total in 1939.
675: Biggest Test win by runs.
737: Runs added for the loss of a single wicket: By Sri Lanka.
847: Number of balls played by Len Hutton during his 364.
907.5: Number of overs bowled in the "timeless" Test played in Durban during 1939.
974: Test runs scored by Bradman in the 1930 series.
981: Balls faced by Hanif Mohammad during his 337, arrived at using simple extrapolation.
1015: Minutes taken by Rajeev Nayyar in his innings for HP against J&K.
1107: Record Victoria score against New South Wales.
1110: Number of first-Class matches played by Wilfred Rhodes.
1710: Test runs in a calendar year by Richards - a record that stood for 29 years.
1788: Test runs by Mohammad Yousuf in 2006.
2376: Runs scored in one match: Maharashtra v Bombay.
2833: International runs scored by Ricky Ponting during 2005.
11273: The duration, in days, of the Test career of Wilfred Rhodes. He made his debut on 1 June 1899 and ended his Test career on 12 April 1930. His debut Test was also the debut Test of Victor Trumper and the last Test of WG Grace.
34357: Total Number of international runs scored by Sachin Tendulkar.
44039: Number of balls bowled by Muttiah Muralitharan.
61237: First-class runs scored by Jack Hobbs.
106996: Number of people who thronged Eden Gardens for the India-Pakistan Test during 1998-99. You do not agree with me? Prove me wrong! Quite tough, though, with no turnstiles. The official record says "around" 100000, not including the spectators who might have sneaked through various routes.
Articles like this are bound to have a follow-up one and I am certain there will be one. I would like that article to have as many reader contributions as possible. Let us go for another 100 numbers. Look for outliers and off-the-beaten-track ideas. For this article, I would any day prefer the 375.00 as Krishnakumar's average than 375 as Lara's record-breaker.
Now for the Bradman memorabilia. This time I have scanned Bradman's 1930 England tour matrix. Look and marvel at the extraordinary number of matches that were played. To view the scan, please click HERE. The visiting team played 34 matches over four-and-a-half months. Bradman batted in 28 of these and averaged over hundred runs per match.
Detailed analyses of the scoring trends in ODIs, beginning with the 1999 World Cup. Plus, a Bradman surprise
Ball-by-ball data for ODI matches is available for 1784 matches, just over 50% of the matches played till date. The data is available for the 43 matches of the 1999 World Cup and then for 1741 matches from match no. 1719 onwards. For 70 matches in this lot, either there is no ball-by-ball data available or the available data is quite incorrect. This massive data-gathering exercise has been completed through Milind's sterling efforts, especially for the first 1700 matches or so.
Two articles, one part-analytical, part-anecdotal and the second one completely anecdotal, based on over as an entity were published recently. In this third part, I will look at this data from a purely analytical point of view.
The classifications are by Teams, Periods and OverGroups. There are eight teams (apologies to Bangladeshi and Irish followers et al), four time periods (with World Cups as group separators) and seven over groups. As anyone with an analytical bent will know this is a three-dimensional database and presents huge problems presenting data in the conventional two-dimensional tables. Graphs will be laborious to present and difficult to comprehend, which may also end up confusing the readers.
Hence I have adopted a via-media approach. For each of these three analytical areas, I will present a summary table and then present combinations of two in two-dimensional tables. Teams will be combined with remaining classifications. I will also present the Period and OverGroup combination.
The bowling analyses will contain both bowling strike rate (BpW) and bowling average (Avge) measures. This will let the readers look at different aspects of the analyses.
Over Group | Inns1-RpO | Inns2-RpO | Inns1-BpW | Inns1-Avge | Inns2-BpW | Inns2-Avge |
---|---|---|---|---|---|---|
1 - 10 | 4.35 | 4.74 | 44.7 | 32.39 | 41.3 | 32.61 |
11 - 15 | 4.49 | 4.70 | 45.2 | 33.87 | 44.0 | 34.41 |
16 - 25 | 4.31 | 4.52 | 49.8 | 35.74 | 47.1 | 35.45 |
26 - 35 | 4.63 | 4.85 | 50.9 | 39.28 | 40.9 | 33.11 |
36 - 40 | 5.37 | 5.28 | 36.3 | 32.44 | 29.7 | 26.17 |
41 - 45 | 6.22 | 5.87 | 25.7 | 26.67 | 23.2 | 22.73 |
46 - 50 | 8.38 | 7.02 | 13.3 | 18.59 | 14.8 | 17.34 |
The OverGroups have been determined based on information needs as well as current ODI laws. Thus overs 1-10 is the first PowerPlay (PP) and overs 11-15 is almost always the second PP. Overs 16-35 are split into two groups of middle overs. Overs 36-40 is separated since most of the times, the batting PP is taken during these overs. Then the last two sets of overs: one in which teams press the accelerator pedal and the concluding one in which the pedal stays at the floor.
During the first PP, the second innings scoring rate is about 10% higher. This is a reflection of the first innings situation: the uncertainty of the target. The bowler PP overs continue on similar lines but at a lower differential. In fact this trend of 4.xx scoring rates in the first innings and around 5-10% increased scoring rates in the second innings continue up to the fourth OverGroup: Overs 26-35. Then the Batting PP appears, hastening scoring rates for both sides. Teams batting first move couple of gears, averaging 5.36. Teams batting second move up by a lower value: by less than 10%. The first of the 40s overs has scoring rates either side of 6.0. In fact the last ten overs show a much higher first innings scoring rate: again a reflection of the first-innings scores being higher by winning margins.
The BpW starts at a middle level and increases to a maximum in the 26-35 OverGroup. There is a huge difference in this OverGroup between the first and second innings. The wickets continue to fall more rapidly in the second innings until the last group. There is a sudden drop in the second innings. The other OverGroups are comparable. But overs 26-35 are intriguing. A wicket falls every 51 balls in the first innings and every 41 balls in the second innings. Why? Is it because the second batting teams bat too cautiously in the first 25 overs and want to make amends? Is it because spinners bowl during these overs and chances are taken?
Period | Inns1-RpO | Inns2-RpO | Inns1-BpW | Inns1-Avge | Inns2-BpW | Inns2-Avge |
---|---|---|---|---|---|---|
WC1999-2003 | 4.86 | 4.70 | 37.1 | 30.03 | 37.9 | 29.70 |
WC2003-2007 | 4.94 | 4.83 | 36.5 | 30.03 | 37.5 | 30.25 |
WC2007-2011 | 5.10 | 4.95 | 35.2 | 29.94 | 36.6 | 30.18 |
WC2011-2014 | 5.18 | 5.02 | 35.9 | 30.95 | 36.2 | 30.23 |
Now, for the period analysis. From now onwards, I will define the periods based on World Cup events. This will be better than arbitrary 5-10 year periods. Also, World Cups launch new strategies for teams: Examples are the way Martin Crowe used Mark Greatbatch in the 1992 World Cup, the all-out attack by the openers in the 1996 World Cup, the no-score-is-safe chases in the last two World Cups.
Although this analysis could have been done for the first six World Cups also (three periods), I have been consistent in restricting myself to the ball-by-ball data period only. I will summarise by saying that the scoring rates during the period from 1971 to 1999 was around 4.5. The overall scoring rates have moved up in the last-four periods steadily. What does this move signify? The average 50-over first innings score between 1999-2003 was 243 and the post-2011 period, 259. Over thousands of matches this is quite significant. The second-innings scoring rates are reflective of the lower target scores.
Surprisingly there is very little variation in the BpW values. The average BpW value oscillates around the 36-mark. The eight values range between 35.2 and 37.9. This is remarkable. Through thousands of matches the overall value to be either side 36.
Team | First Inns | Inns1-RpO | Second Inns | Inns2-RpO | Inns1-BpW | Inns1-Avge | Inns2-BpW | Inns2-Avge |
---|---|---|---|---|---|---|---|---|
Australia | 217 | 5.38 | 149 | 5.28 | 33.2 | 26.19 | 32.1 | 26.06 |
India | 186 | 5.47 | 219 | 5.23 | 37.6 | 32.37 | 34.7 | 30.06 |
Sri Lanka | 205 | 5.04 | 163 | 5.04 | 35.5 | 29.23 | 34.5 | 27.32 |
Pakistan | 173 | 5.11 | 163 | 4.89 | 36.2 | 29.85 | 35.5 | 28.70 |
South Africa | 143 | 5.41 | 152 | 5.10 | 35.3 | 28.50 | 32.8 | 25.80 |
West Indies | 135 | 4.97 | 159 | 5.00 | 36.5 | 30.35 | 39.0 | 31.75 |
England | 150 | 5.14 | 155 | 5.02 | 34.9 | 28.96 | 38.5 | 33.46 |
New Zealand | 133 | 5.09 | 150 | 5.01 | 35.6 | 29.16 | 37.6 | 30.49 |
I have selected the top eight teams for this analysis. There are too many teams to present a complete analysis. The sequence of presentation is based on World Cup performances. Australia, with three World Cup wins is at the top, followed by India, with one World Cup win and one runner-up position. They are followed by Sri Lanka, with two runners-up positions and Pakistan, with one runner-up position.
The number of matches between batting first and second for Australia is dramatically lopsided. Australia batted first 60% of the times. They are quite confident of defending totals, with their bowling and fielding strengths. It could also be because the other big team, India, prefer to chase. Australia's average during the first-innings score is around 270. They have the best second-innings scoring rate. To boot, their wicket-taking rates are spectacular. The best amongst all teams. It is no wonder that they have been the most successful team, by the proverbial mile.
India averaged around 273 runs in the first innings. But their bowling in the first innings has been the worst amongst all teams featured here. They bowl better in the second innings. This is a paradox. Based on these numbers one should think that India would have been better off batting first and defending. Maybe MS Dhoni is too obsessed with his preconceived ideas. They bat first about 45% of the time.
The absence of heavy hitters is reflected in Sri Lanka's numbers. But their bowling has been excellent. Pakistan are also like Sri Lanka. Fair batting and good bowling. South Africa's numbers are excellent. Batting nearly as good as India and much better bowling. They should be sitting with a World Cup trophy or two. Let us see what happens next year. They should be joint favourites with Australia once they learn how to dismiss ten and Jack.
England's second-innings bowling lets them down. West Indies are average in batting and bowling. New Zealand's batting and bowling are right in the middle.
Period | Over Group | Inns1-RpO | Inns2-RpO | Inns1-BpW | Inns1-Avge | Inns2-BpW | Inns2-Avge |
---|---|---|---|---|---|---|---|
WC1999-2003 | 1 - 10 | 4.21 | 4.60 | 47.0 | 32.95 | 42.0 | 32.18 |
WC1999-2003 | 11 - 15 | 4.72 | 4.80 | 41.2 | 32.48 | 44.1 | 35.26 |
WC1999-2003 | 16 - 25 | 4.20 | 4.25 | 55.6 | 38.94 | 50.8 | 35.98 |
WC1999-2003 | 26 - 35 | 4.58 | 4.68 | 52.3 | 39.94 | 47.3 | 36.88 |
WC1999-2003 | 36 - 40 | 4.99 | 4.88 | 38.1 | 31.71 | 29.0 | 23.60 |
WC1999-2003 | 41 - 45 | 5.73 | 5.20 | 24.2 | 23.07 | 21.9 | 19.03 |
WC1999-2003 | 46 - 50 | 8.07 | 6.05 | 13.5 | 18.18 | 16.9 | 17.03 |
WC2003-2007 | 1 - 10 | 4.26 | 4.60 | 42.6 | 30.20 | 40.3 | 30.91 |
WC2003-2007 | 11 - 15 | 4.51 | 4.78 | 44.4 | 33.36 | 42.9 | 34.15 |
WC2003-2007 | 16 - 25 | 4.25 | 4.52 | 48.9 | 34.63 | 49.8 | 37.53 |
WC2003-2007 | 26 - 35 | 4.41 | 4.69 | 52.5 | 38.57 | 40.7 | 31.78 |
WC2003-2007 | 36 - 40 | 5.15 | 5.07 | 39.1 | 33.59 | 32.7 | 27.66 |
WC2003-2007 | 41 - 45 | 6.16 | 5.85 | 27.3 | 28.01 | 25.9 | 25.24 |
WC2003-2007 | 46 - 50 | 8.82 | 6.39 | 13.2 | 19.48 | 16.3 | 17.41 |
WC2007-2011 | 1 - 10 | 4.53 | 4.96 | 44.8 | 33.80 | 41.2 | 34.03 |
WC2007-2011 | 11 - 15 | 4.46 | 4.73 | 44.8 | 33.31 | 42.7 | 33.66 |
WC2007-2011 | 16 - 25 | 4.30 | 4.49 | 46.4 | 33.27 | 44.9 | 33.66 |
WC2007-2011 | 26 - 35 | 4.73 | 4.88 | 49.4 | 38.92 | 40.0 | 32.52 |
WC2007-2011 | 36 - 40 | 5.36 | 5.20 | 35.6 | 31.78 | 29.7 | 25.74 |
WC2007-2011 | 41 - 45 | 6.35 | 5.89 | 26.7 | 28.22 | 24.0 | 23.51 |
WC2007-2011 | 46 - 50 | 9.08 | 6.59 | 11.7 | 17.70 | 15.8 | 17.30 |
WC2011-2014 | 1 - 10 | 4.31 | 4.72 | 46.1 | 33.15 | 42.2 | 33.21 |
WC2011-2014 | 11 - 15 | 4.38 | 4.49 | 49.8 | 36.37 | 47.1 | 35.26 |
WC2011-2014 | 16 - 25 | 4.46 | 4.69 | 52.4 | 38.99 | 45.0 | 35.13 |
WC2011-2014 | 26 - 35 | 4.83 | 5.07 | 50.0 | 40.22 | 39.7 | 33.53 |
WC2011-2014 | 36 - 40 | 5.89 | 5.72 | 33.0 | 32.37 | 27.9 | 26.63 |
WC2011-2014 | 41 - 45 | 6.40 | 5.97 | 24.0 | 25.60 | 21.6 | 21.47 |
WC2011-2014 | 46 - 50 | 9.16 | 6.81 | 12.4 | 18.89 | 15.4 | 17.47 |
This is first of the multi-classification pseudo three-dimensional analyses. Here I take the Period as the base and represent the Over groups at the next levels. This is linearly presented with each Period shown separately.
There are many numbers and I will come out with a few insights. I will present the data and let the readers come out with their own derivations.
Overs 36-40 deserve a careful look. The scoring rate has moved from 4.99 through 5.15, 5.36 to the current 5.89. The 10% jump in the last period is the effect of PP3. In the second innings the number moves up from 5.20 to 5.72. What about the bowling average? It hovers around the 32-mark. So there is no great change because of the PP, contrary to popular belief.
The last ten overs have seen a huge jump from around 6.8 during the first period, through 7.4, 7.6 to 7.7 currently. That is a significant change and reflects the current high average scores. The first ten overs has seen a drop in scoring rate during the current period.
The trend of BpW movements continues across the periods. However, there is a 10% drop in the first over values between the first and second periods. This is a significant increase in the number of wickets which were captured. Right through the years, the overs 26-35 have seen least number of wickets falling. However this trend seems to change during times with more wickets falling. The BpW figure has fallen from around 50 to 40.
Team | Period | Inns1-RpO | Inns2-RpO | Inns1-BpW | Inns1-Avge | Inns2-BpW | Inns2-Avge | |
---|---|---|---|---|---|---|---|---|
Australia | WC1999-2003 | 5.06 | 5.23 | 34.4 | 25.64 | 32.0 | 23.31 | |
Australia | WC2003-2007 | 5.48 | 5.24 | 32.9 | 25.23 | 31.4 | 25.64 | |
Australia | WC2007-2011 | 5.40 | 5.29 | 31.7 | 25.95 | 30.7 | 24.92 | |
Australia | WC2011-2014 | 5.34 | 5.43 | 34.5 | 29.11 | 35.4 | 29.73 | |
India | WC1999-2003 | 5.20 | 4.92 | 38.4 | 31.33 | 37.3 | 30.69 | |
India | WC2003-2007 | 5.25 | 5.14 | 35.9 | 30.43 | 35.5 | 29.50 | |
India | WC2007-2011 | 5.70 | 5.34 | 38.0 | 33.44 | 34.7 | 31.59 | |
India | WC2011-2014 | 5.70 | 5.40 | 38.4 | 33.68 | 32.0 | 28.72 | |
Sri Lanka | WC1999-2003 | 4.86 | 4.77 | 35.7 | 29.52 | 36.7 | 27.47 | |
Sri Lanka | WC2003-2007 | 4.96 | 4.82 | 34.2 | 25.94 | 37.6 | 29.55 | |
Sri Lanka | WC2007-2011 | 5.13 | 5.14 | 34.5 | 29.04 | 31.8 | 24.96 | |
Sri Lanka | WC2011-2014 | 5.13 | 5.27 | 37.7 | 32.40 | 32.8 | 27.41 | |
Pakistan | WC1999-2003 | 5.15 | 4.56 | 34.2 | 26.20 | 33.8 | 27.17 | |
Pakistan | WC2003-2007 | 5.01 | 5.03 | 36.9 | 30.81 | 36.4 | 29.51 | |
Pakistan | WC2007-2011 | 5.42 | 4.99 | 36.7 | 32.03 | 35.9 | 29.85 | |
Pakistan | WC2011-2014 | 4.89 | 4.82 | 36.2 | 28.97 | 35.5 | 27.77 | |
South Africa | WC1999-2003 | 5.35 | 4.74 | 36.6 | 27.32 | 32.4 | 23.97 | |
South Africa | WC2003-2007 | 5.11 | 5.12 | 35.5 | 28.37 | 36.4 | 28.02 | |
South Africa | WC2007-2011 | 5.66 | 5.35 | 35.1 | 29.54 | 33.0 | 27.28 | |
South Africa | WC2011-2014 | 5.53 | 5.08 | 33.8 | 28.50 | 29.7 | 23.55 | |
West Indies | WC1999-2003 | 4.89 | 5.22 | 33.2 | 25.68 | 40.1 | 30.90 | |
West Indies | WC2003-2007 | 4.91 | 4.93 | 38.1 | 31.35 | 39.0 | 31.95 | |
West Indies | WC2007-2011 | 5.08 | 4.97 | 37.0 | 31.03 | 39.8 | 33.56 | |
West Indies | WC2011-2014 | 4.99 | 5.06 | 35.1 | 30.37 | 37.8 | 30.71 | |
England | WC1999-2003 | 5.08 | 4.59 | 38.3 | 31.51 | 39.0 | 33.24 | |
England | WC2003-2007 | 4.92 | 5.04 | 34.1 | 26.47 | 41.9 | 35.21 | |
England | WC2007-2011 | 5.27 | 4.99 | 34.4 | 29.00 | 36.6 | 32.32 | |
England | WC2011-2014 | 5.30 | 5.26 | 35.0 | 30.74 | 36.6 | 32.99 | |
New Zealand | WC1999-2003 | 4.55 | 4.39 | 35.8 | 27.64 | 37.6 | 28.91 | |
New Zealand | WC2003-2007 | 5.00 | 5.05 | 38.1 | 31.62 | 36.5 | 28.81 | |
New Zealand | WC2007-2011 | 5.14 | 5.29 | 34.0 | 27.72 | 40.6 | 32.96 | |
New Zealand | WC2011-2014 | 5.64 | 5.17 | 32.8 | 28.37 | 35.6 | 31.34 |
This is the first of two team-based tables. The first is Team-Period and the second is Team-OverGroup.
What is obvious?
- Australia's recent decline in bowling standards.
- India's growing batting strengths, offset by poor first innings bowling.
- Sri Lanka's predicament similar to India: Good batting and poor first innings bowling.
- Pakistan's drop in batting but maintenance of good bowling.
- South Africa's outstanding numbers. They are the best ODI team in the world now. No weakness in sight.
- England and New Zealand in similar situations: good batting and poor defence of targets.
This is the Team-OverGroup analysis. I have split this into two tables: Four teams each because there are seven OverGroups.
Team | Over Group | Inns1-RpO | Inns2-RpO | Inns1-BpW | Inns1-Avge | Inns2-BpW | Inns2-Avge |
---|---|---|---|---|---|---|---|
Australia | 1 - 10 | 4.80 | 5.42 | 38.6 | 25.68 | 34.9 | 24.98 |
Australia | 11 - 15 | 4.90 | 5.15 | 41.3 | 30.42 | 36.6 | 27.91 |
Australia | 16 - 25 | 4.58 | 4.84 | 46.7 | 32.24 | 46.6 | 35.12 |
Australia | 26 - 35 | 4.85 | 5.06 | 42.3 | 31.34 | 35.8 | 29.02 |
Australia | 36 - 40 | 5.51 | 5.30 | 35.5 | 30.18 | 26.5 | 24.69 |
Australia | 41 - 45 | 6.70 | 6.02 | 22.4 | 22.65 | 19.7 | 19.58 |
Australia | 46 - 50 | 8.70 | 7.14 | 12.5 | 16.42 | 13.9 | 16.57 |
India | 1 - 10 | 4.85 | 5.07 | 47.9 | 36.25 | 41.6 | 35.86 |
India | 11 - 15 | 5.04 | 4.89 | 43.3 | 33.42 | 38.9 | 31.14 |
India | 16 - 25 | 4.73 | 4.75 | 54.8 | 40.49 | 42.5 | 33.03 |
India | 26 - 35 | 5.05 | 5.30 | 51.3 | 40.82 | 40.2 | 34.05 |
India | 36 - 40 | 5.72 | 5.71 | 34.9 | 32.82 | 28.6 | 26.18 |
India | 41 - 45 | 6.55 | 6.08 | 30.0 | 32.05 | 23.1 | 23.23 |
India | 46 - 50 | 8.87 | 7.24 | 13.2 | 18.44 | 14.8 | 18.09 |
Sri Lanka | 1 - 10 | 4.56 | 5.21 | 39.5 | 28.49 | 37.5 | 28.87 |
Sri Lanka | 11 - 15 | 4.56 | 4.79 | 48.8 | 35.29 | 41.3 | 32.54 |
Sri Lanka | 16 - 25 | 4.42 | 4.55 | 43.3 | 31.59 | 43.2 | 31.55 |
Sri Lanka | 26 - 35 | 4.83 | 4.72 | 49.1 | 38.38 | 36.2 | 28.22 |
Sri Lanka | 36 - 40 | 5.27 | 5.36 | 34.6 | 29.88 | 29.1 | 24.20 |
Sri Lanka | 41 - 45 | 5.94 | 5.86 | 29.8 | 29.96 | 22.3 | 20.89 |
Sri Lanka | 46 - 50 | 7.71 | 7.34 | 14.0 | 18.57 | 15.4 | 16.74 |
Pakistan | 1 - 10 | 4.08 | 4.50 | 41.1 | 30.43 | 45.0 | 35.46 |
Pakistan | 11 - 15 | 4.27 | 4.32 | 41.8 | 32.19 | 47.2 | 37.27 |
Pakistan | 16 - 25 | 4.36 | 4.31 | 55.7 | 39.85 | 45.1 | 33.52 |
Pakistan | 26 - 35 | 4.93 | 5.07 | 51.9 | 38.62 | 39.6 | 30.58 |
Pakistan | 36 - 40 | 5.48 | 5.68 | 41.7 | 35.21 | 25.3 | 20.84 |
Pakistan | 41 - 45 | 6.62 | 6.25 | 25.5 | 24.57 | 21.2 | 20.42 |
Pakistan | 46 - 50 | 8.78 | 6.86 | 13.2 | 18.22 | 13.9 | 16.72 |
- Australia's outstanding bowling efforts right through the innings.
- India move into higher gears early in the innings.
- India's opening bowling attack lacks sting. A wicket every 36 balls only.
- Sri Lanka's finish is quite ordinary.
Team | Over Group | Inns1-RpO | Inns2-RpO | Inns1-BpW | Inns1-Avge | Inns2-BpW | Inns2-Avge |
---|---|---|---|---|---|---|---|
South Africa | 1 - 10 | 4.50 | 4.86 | 47.6 | 32.61 | 37.0 | 26.12 |
South Africa | 11 - 15 | 4.93 | 5.29 | 53.9 | 40.17 | 42.5 | 30.91 |
South Africa | 16 - 25 | 4.53 | 4.62 | 49.9 | 35.44 | 41.9 | 30.47 |
South Africa | 26 - 35 | 5.09 | 4.94 | 49.0 | 37.66 | 35.4 | 28.89 |
South Africa | 36 - 40 | 5.75 | 5.44 | 28.7 | 25.23 | 27.5 | 25.08 |
South Africa | 41 - 45 | 6.51 | 5.76 | 24.8 | 23.80 | 18.4 | 16.96 |
South Africa | 46 - 50 | 9.36 | 7.67 | 12.5 | 16.23 | 15.9 | 17.11 |
West Indies | 1 - 10 | 4.16 | 4.58 | 44.4 | 31.88 | 39.5 | 30.98 |
West Indies | 11 - 15 | 4.19 | 4.82 | 49.2 | 37.18 | 44.0 | 34.26 |
West Indies | 16 - 25 | 4.09 | 4.68 | 46.2 | 33.45 | 50.3 | 37.77 |
West Indies | 26 - 35 | 4.66 | 4.90 | 60.6 | 47.16 | 45.4 | 36.74 |
West Indies | 36 - 40 | 5.85 | 5.73 | 38.0 | 33.50 | 34.0 | 28.49 |
West Indies | 41 - 45 | 6.52 | 6.21 | 26.6 | 27.44 | 31.5 | 31.17 |
West Indies | 46 - 50 | 8.52 | 7.11 | 12.5 | 16.89 | 14.2 | 16.27 |
England | 1 - 10 | 4.61 | 4.77 | 43.9 | 30.76 | 45.4 | 38.96 |
England | 11 - 15 | 4.85 | 5.20 | 38.2 | 27.66 | 56.6 | 47.44 |
England | 16 - 25 | 4.50 | 4.67 | 48.2 | 35.03 | 44.1 | 34.53 |
England | 26 - 35 | 4.55 | 4.82 | 52.2 | 40.65 | 43.2 | 36.92 |
England | 36 - 40 | 5.59 | 5.20 | 36.6 | 32.31 | 32.7 | 30.35 |
England | 41 - 45 | 6.22 | 5.91 | 24.5 | 26.63 | 23.2 | 22.81 |
England | 46 - 50 | 8.31 | 7.27 | 12.7 | 16.91 | 16.7 | 19.83 |
New Zealand | 1 - 10 | 4.26 | 4.87 | 42.1 | 30.22 | 42.7 | 33.44 |
New Zealand | 11 - 15 | 4.70 | 4.50 | 47.1 | 34.81 | 42.9 | 32.48 |
New Zealand | 16 - 25 | 4.25 | 4.60 | 44.2 | 31.15 | 53.1 | 38.57 |
New Zealand | 26 - 35 | 4.68 | 5.04 | 46.6 | 35.01 | 41.0 | 32.67 |
New Zealand | 36 - 40 | 5.59 | 5.33 | 35.5 | 30.56 | 31.5 | 28.05 |
New Zealand | 41 - 45 | 6.25 | 6.02 | 24.4 | 24.64 | 22.8 | 23.00 |
New Zealand | 46 - 50 | 9.04 | 7.43 | 14.3 | 21.26 | 14.0 | 16.75 |
- South Africa's finish is spectacular. Well above 9 RpO.
- New Zealand are also quite good.
- South Africa's defence of targets is extraordinary.
- England's defence is awful. Look at the first 15 overs.
For the time being this concludes my ODI overs-based analyses. There is a lot more that can be done. I will keep these for a later day.
A bonus for the readers. I have a rare two-volume collection of Bradman memorabilia. It is a fantastic set of books and contains scorecards, telegrams, photographs, letters et al. Along with each article I will scan one such rare document and attach for user viewing. I had presented the chart for Bradman's 334 in the previous article. To view the next scan, please click HERE. This is a 1931 telegram offering Bradman £500 for a five-month playing assignment, by Accrington, a Lancashire club. This was after Bradman's successful tour during 1930. Note the £2 per week charge for accommodation. Did Bradman accept the offer? There is a story behind this and I will provide the answer if some reader scans and elicits a query.
Alternately here are a few links, courtesy Milind, on this topic.
A look at various interesting high and low-scoring sequences in ODIs with the help of ball-by-ball data. Plus, a Bradman surprise
I planned to complete the ODI Overs analysis in two parts. However I have come to the conclusion, after the responses and my own study of the data available, that the anecdotal elements of the analysis were important and deserved a separate article. The readers are also interested in such light-hearted articles. So I will present the second part as a completely anecdotal one. The third part will complete the analytical views.
A lovely surprise awaits the readers at the end of the article. A fun-filled article wrapped up by an evocative nostalgic trip into the '30s. What more does one want?
The reports are current up to and including match No. 3535: the fourth ODI at Dharamsala.
Desc | Inns | ODI Match | Batting team | Bow | Inns | Start ball | No of balls |
---|---|---|---|---|---|---|---|
Fastest 50 | 1 | 3123 | New Zealand | Pak | 1 | 47.4 | 11 |
Fastest 50 | 2 | 1963 | West Indies | Can | 2 | 8.2 | 14 |
Fastest 100 | 1 | 2169 | New Zealand | Usa | 1 | 45.0 | 28 |
Fastest 100 | 2 | 1963 | West Indies | Can | 2 | 3.6 | 40 |
For this and the next analysis I have followed the often used common sense approach. A wide is unreachable by the batsman and should not be treated as a countable ball. A no-ball is playable and can be scored off. Hence a no-ball is counted. That is all. With this preamble let us look at some extreme scoring instances.
In the match between Pakistan and New Zealand, the New Zealand batsmen went on the greatest scoring sequence ever. In 11 balls, starting from 47.4, they reached 50. The sequence was 1wd, 1, 1, 6, 4, 6, 1wd, 6, 1wd, 2, 4, 6, 6 and 6. Ross Taylor and Jacob Oram tore apart Abdur Rehman and Abdul Razzaq.
The teams do not indulge in such heavy hitting in the second innings, pacing their innings, in view of the availability of a clear target score. This was shown clearly in Part 1 of this article. The fastest 50-run sequence was achieved by West Indies against Canada, when they were chasing 203. They achieved this in a mere 20.3 overs. Embedded in this furious run chase was a 14-ball sequence when 50 runs were reached. The carnage started in ball No. 8.2. The sequence went "1, 1, 6, 1, 5nb, 1wd, 1, 4, 6, 4, 6, 6, 0, 4 and 4". Brian Lara and Wavell Hinds decimated Nicholas Ifill and Barry Seebaran.
The fastest 100 in the first innings was when New Zealand finished the innings with a 28-ball carnage of exactly 100 runs. The sequence is too long to be laid out here. In the second innings the sequence was more staid, in the West Indies match we have already seen. West Indies reached 100 in 40 balls, starting with the last ball of the fourth over.
Desc | Inns | ODI Match | Batting team | Bow | Inns | Start ball | No of balls |
---|---|---|---|---|---|---|---|
Slowest 50 | 1 | 2063 | England | Slk | 1 | 2.3 | 190 |
Slowest 50 | 2 | 2797 | Zimbabwe | Bng | 2 | 11.1 | 164 |
Slowest 100 | 1 | 2059 | Bangladesh | Eng | 1 | 0.1 | 271 |
Slowest 100 | 2 | 2797 | Zimbabwe | Bng | 2 | 0.1 | 274 |
This is the other end of the spectrum. People who paid money to watch these matches should have asked for a refund. England's 190-ball 50 against Sri Lanka during 2003 in Dambulla defies description. England finished with 88 in 46.2 overs. Embedded in this run-drought was a 164-ball sequence in which England crawled at around 1.5 runs per over (RpO). There were six maidens and 11 one-run overs during this phase of the innings. The batsmen, not exactly novices: Marcus Trescothick, Andrew Strauss, Michael Vaughan, Paul Collingwood and Andrew Flintoff. Muttiah Muralitharan returned bowling figures of 10-0-15-1, Chaminda Vaas 9.1-2-15-3, Dilhara Fernando 7-2-13-2, Nuwan Kulasekara 9-1-19-1. All bowlers went for less than 2 runs an over.
The other members of this part of the analysis are not the leading teams. Zimbabwe scored 50 in 164 balls against Bangladesh: Note relatively the faster scoring in the second innings. Bangladesh and Zimbabwe both needed over 45 overs each to compile 100 runs.
Over | First Innings | Second Innings | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
ODI Match | Batting team | Bow | Score | Run Rate | Odi Match | Batting team | Bow | Score | S/R | |
1 | 2035 | South Africa | Eng | 19 | 19.0 | 2149 | India | Bng | 22 | 22.0 |
2 | 2498 | Canada | Ber | 32 | 16.0 | 2660 | New Zealand | Bng | 28 | 14.0 |
3 | 2054 | Australia | Ind | 40 | 13.3 | 2389 | Sri Lanka | Eng | 46 | 15.3 |
4 | 2934 | Sri Lanka | Ind | 58 | 14.5 | 2660 | New Zealand | Bng | 62 | 15.5 |
5 | 2934 | Sri Lanka | Ind | 59 | 11.8 | 2660 | New Zealand | Bng | 78 | 15.6 |
6 | 3151 | Australia | Bng | 66 | 11.0 | 2660 | New Zealand | Bng | 95 | 15.8 |
7 | 3451 | New Zealand | Win | 80 | 11.4 | 2389 | Sri Lanka | Eng | 86 | 12.3 |
8 | 3451 | New Zealand | Win | 86 | 10.8 | 2389 | Sri Lanka | Eng | 100 | 12.5 |
9 | 3451 | New Zealand | Win | 100 | 11.1 | 2389 | Sri Lanka | Eng | 108 | 12.0 |
10 | 3451 | New Zealand | Win | 104 | 10.4 | 2389 | Sri Lanka | Eng | 133 | 13.3 |
11 | 3451 | New Zealand | Win | 116 | 10.5 | 2389 | Sri Lanka | Eng | 141 | 12.8 |
12 | 3451 | New Zealand | Win | 135 | 11.2 | 2389 | Sri Lanka | Eng | 149 | 12.4 |
13 | 3451 | New Zealand | Win | 159 | 12.2 | 2389 | Sri Lanka | Eng | 155 | 11.9 |
14 | 3451 | New Zealand | Win | 168 | 12.0 | 2389 | Sri Lanka | Eng | 159 | 11.4 |
15 | 3451 | New Zealand | Win | 194 | 12.9 | 2389 | Sri Lanka | Eng | 165 | 11.0 |
16 | 3451 | New Zealand | Win | 208 | 13.0 | 2389 | Sri Lanka | Eng | 170 | 10.6 |
17 | 3451 | New Zealand | Win | 223 | 13.1 | 2389 | Sri Lanka | Eng | 177 | 10.4 |
18 | 3451 | New Zealand | Win | 250 | 13.9 | 1963 | West Indies | Can | 182 | 10.1 |
19 | 3451 | New Zealand | Win | 264 | 13.9 | 1963 | West Indies | Can | 190 | 10.0 |
20 | 3451 | New Zealand | Win | 275 | 13.8 | 1963 | West Indies | Can | 201 | 10.1 |
21 | 3451 | New Zealand | Win | 283 | 13.5 | 1963 | West Indies | Can | 206 | 9.8 |
22 | 3187 | India | Eng | 182 | 8.3 | 2389 | Sri Lanka | Eng | 202 | 9.2 |
23 | 2112 | India | Pak | 189 | 8.2 | 2389 | Sri Lanka | Eng | 216 | 9.4 |
24 | 2112 | India | Pak | 194 | 8.1 | 2389 | Sri Lanka | Eng | 219 | 9.1 |
25 | 2932 | India | Slk | 209 | 8.4 | 2389 | Sri Lanka | Eng | 233 | 9.3 |
26 | 2932 | India | Slk | 216 | 8.3 | 2389 | Sri Lanka | Eng | 245 | 9.4 |
27 | 2932 | India | Slk | 227 | 8.4 | 2389 | Sri Lanka | Eng | 262 | 9.7 |
28 | 2932 | India | Slk | 232 | 8.3 | 2389 | Sri Lanka | Eng | 263 | 9.4 |
29 | 2932 | India | Slk | 247 | 8.5 | 2389 | Sri Lanka | Eng | 274 | 9.4 |
30 | 2932 | India | Slk | 261 | 8.7 | 2349 | South Africa | Aus | 279 | 9.3 |
31 | 2932 | India | Slk | 267 | 8.6 | 2349 | South Africa | Aus | 286 | 9.2 |
32 | 2932 | India | Slk | 280 | 8.8 | 2349 | South Africa | Aus | 299 | 9.3 |
33 | 2932 | India | Slk | 288 | 8.7 | 2349 | South Africa | Aus | 303 | 9.2 |
34 | 2932 | India | Slk | 296 | 8.7 | 2349 | South Africa | Aus | 311 | 9.1 |
35 | 2932 | India | Slk | 308 | 8.8 | 2349 | South Africa | Aus | 315 | 9.0 |
36 | 2932 | India | Slk | 311 | 8.6 | 2349 | South Africa | Aus | 321 | 8.9 |
37 | 2272 | New Zealand | Zim | 315 | 8.5 | 2932 | Sri Lanka | Ind | 326 | 8.8 |
38 | 2272 | New Zealand | Zim | 325 | 8.6 | 2932 | Sri Lanka | Ind | 330 | 8.7 |
39 | 2272 | New Zealand | Zim | 332 | 8.5 | 2932 | Sri Lanka | Ind | 339 | 8.7 |
40 | 2537 | South Africa | Net | 353 | 8.8 | 2932 | Sri Lanka | Ind | 343 | 8.6 |
41 | 2272 | New Zealand | Zim | 357 | 8.7 | 2932 | Sri Lanka | Ind | 347 | 8.5 |
42 | 2272 | New Zealand | Zim | 374 | 8.9 | 2932 | Sri Lanka | Ind | 355 | 8.5 |
43 | 2272 | New Zealand | Zim | 386 | 9.0 | 2932 | Sri Lanka | Ind | 364 | 8.5 |
44 | 2272 | New Zealand | Zim | 396 | 9.0 | 2932 | Sri Lanka | Ind | 375 | 8.5 |
45 | 2420 | South Africa | Zim | 367 | 8.2 | 2349 | South Africa | Aus | 388 | 8.6 |
46 | 2349 | Australia | Saf | 374 | 8.1 | 2349 | South Africa | Aus | 397 | 8.6 |
47 | 2932 | India | Slk | 386 | 8.2 | 2349 | South Africa | Aus | 405 | 8.6 |
48 | 2349 | Australia | Saf | 409 | 8.5 | 2349 | South Africa | Aus | 422 | 8.8 |
49 | 2349 | Australia | Saf | 420 | 8.6 | 2349 | South Africa | Aus | 428 | 8.7 |
50 | 2349 | Australia | Saf | 434 | 8.7 | 2349 | South Africa | Aus | 438 | 8.8 |
These tables are created in response to a specific request by Prateek who wanted to know the highest and lowest scores reached at the end of each over. There are two tables: One for the highest scores and another for the lowest scores.
The tables are self-explanatory. However one seeming anomaly has to be explained. The highest score reached in 21 overs is 283. This was the recent Ryder-Anderson bloodbath. Then for 22 overs the highest drops nearly 100 runs. This was because the New Zealand innings ended at 21 overs. This explains why the scoring rate is well above 10 for the first 21 overs only. In fact this match monopolises the top of the table.
West Indies' batting against Canada makes its mark here also in the second innings table. The run rate for the second half of the innings is higher due to a measured approach, chasing set target. The famous Wanderers run-chase is the last entry, for over 50, in both tables. There is one higher total: Sri Lanka's 443 for 9 against Netherlands. Unfortunately there is no ball-by-ball data for this Amstelveen (mis)match.
Over | First Innings | Second Innings | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
ODI Match | Batting team | Bow | Score | Run Rate | Odi Match | Batting team | Bow | Score | S/R | |
1 | 1805 | New Zealand | Saf | 0 | 0.0 | 2298 | India | Saf | 0 | 0.0 |
2 | 1805 | New Zealand | Saf | 0 | 0.0 | 2298 | India | Saf | 0 | 0.0 |
3 | 1805 | New Zealand | Saf | 0 | 0.0 | 2298 | India | Saf | 0 | 0.0 |
4 | 1805 | New Zealand | Saf | 0 | 0.0 | 3527 | Ireland | Sco | 1 | 0.2 |
5 | 1726 | England | Aus | 1 | 0.2 | 3410 | Scotland | Aus | 2 | 0.4 |
6 | 3418 | Kenya | Afg | 4 | 0.7 | 2794 | Sri Lanka | Bng | 5 | 0.8 |
7 | 3418 | Kenya | Afg | 5 | 0.7 | 2276 | Zimbabwe | Nzl | 5 | 0.7 |
8 | 3418 | Kenya | Afg | 5 | 0.6 | 2794 | Sri Lanka | Bng | 6 | 0.8 |
9 | 1465 | Scotland | Win | 6 | 0.7 | 2346 | West Indies | Nzl | 7 | 0.8 |
10 | 3418 | Kenya | Afg | 7 | 0.7 | 2345 | Australia | Saf | 7 | 0.7 |
11 | 3418 | Kenya | Afg | 8 | 0.7 | 2345 | Australia | Saf | 7 | 0.6 |
12 | 3418 | Kenya | Afg | 8 | 0.7 | 2345 | Australia | Saf | 11 | 0.9 |
13 | 3418 | Kenya | Afg | 8 | 0.6 | 2345 | Australia | Saf | 17 | 1.3 |
14 | 3418 | Kenya | Afg | 11 | 0.8 | 2884 | New Zealand | Slk | 21 | 1.5 |
15 | 3418 | Kenya | Afg | 12 | 0.8 | 2884 | New Zealand | Slk | 24 | 1.6 |
16 | 3418 | Kenya | Afg | 16 | 1.0 | 2146 | U.A.E. | Slk | 25 | 1.6 |
17 | 3418 | Kenya | Afg | 16 | 0.9 | 2345 | Australia | Saf | 28 | 1.6 |
18 | 3418 | Kenya | Afg | 18 | 1.0 | 2345 | Australia | Saf | 29 | 1.6 |
19 | 3418 | Kenya | Afg | 23 | 1.2 | 3389 | West Indies | Pak | 35 | 1.8 |
20 | 1465 | Scotland | Win | 25 | 1.2 | 3389 | West Indies | Pak | 37 | 1.9 |
21 | 1465 | Scotland | Win | 28 | 1.3 | 3389 | West Indies | Pak | 40 | 1.9 |
22 | 1465 | Scotland | Win | 29 | 1.3 | 3389 | West Indies | Pak | 41 | 1.9 |
23 | 1465 | Scotland | Win | 35 | 1.5 | 3389 | West Indies | Pak | 42 | 1.8 |
24 | 1465 | Scotland | Win | 37 | 1.5 | 3389 | West Indies | Pak | 47 | 2.0 |
25 | 1465 | Scotland | Win | 43 | 1.7 | 3389 | West Indies | Pak | 48 | 1.9 |
26 | 1465 | Scotland | Win | 44 | 1.7 | 3389 | West Indies | Pak | 50 | 1.9 |
27 | 1465 | Scotland | Win | 45 | 1.7 | 3389 | West Indies | Pak | 51 | 1.9 |
28 | 1465 | Scotland | Win | 46 | 1.6 | 3389 | West Indies | Pak | 51 | 1.8 |
29 | 2063 | England | Slk | 50 | 1.7 | 3389 | West Indies | Pak | 53 | 1.8 |
30 | 2063 | England | Slk | 52 | 1.7 | 3389 | West Indies | Pak | 55 | 1.8 |
31 | 2063 | England | Slk | 53 | 1.7 | 3389 | West Indies | Pak | 55 | 1.8 |
32 | 2063 | England | Slk | 54 | 1.7 | 3389 | West Indies | Pak | 59 | 1.8 |
33 | 2063 | England | Slk | 55 | 1.7 | 3389 | West Indies | Pak | 59 | 1.8 |
34 | 2063 | England | Slk | 58 | 1.7 | 3389 | West Indies | Pak | 61 | 1.8 |
35 | 2063 | England | Slk | 59 | 1.7 | 3389 | West Indies | Pak | 65 | 1.9 |
36 | 2063 | England | Slk | 60 | 1.7 | 3389 | West Indies | Pak | 76 | 2.1 |
37 | 2063 | England | Slk | 61 | 1.6 | 2143 | Hong Kong | Bng | 80 | 2.2 |
38 | 2063 | England | Slk | 66 | 1.7 | 2143 | Hong Kong | Bng | 80 | 2.1 |
39 | 2063 | England | Slk | 67 | 1.7 | 2797 | Zimbabwe | Bng | 86 | 2.2 |
40 | 2063 | England | Slk | 72 | 1.8 | 2797 | Zimbabwe | Bng | 89 | 2.2 |
41 | 2063 | England | Slk | 73 | 1.8 | 2797 | Zimbabwe | Bng | 92 | 2.2 |
42 | 2063 | England | Slk | 78 | 1.9 | 2797 | Zimbabwe | Bng | 94 | 2.2 |
43 | 2063 | England | Slk | 80 | 1.9 | 2797 | Zimbabwe | Bng | 95 | 2.2 |
44 | 2063 | England | Slk | 82 | 1.9 | 2797 | Zimbabwe | Bng | 96 | 2.2 |
45 | 2063 | England | Slk | 85 | 1.9 | 2797 | Zimbabwe | Bng | 100 | 2.2 |
46 | 2063 | England | Slk | 88 | 1.9 | 2143 | Hong Kong | Bng | 105 | 2.3 |
47 | 2063 | England | Slk | 88 | 1.9 | 2797 | Zimbabwe | Bng | 114 | 2.4 |
48 | 2059 | Bangladesh | Eng | 116 | 2.4 | 2797 | Zimbabwe | Bng | 115 | 2.4 |
49 | 2059 | Bangladesh | Eng | 121 | 2.5 | 2797 | Zimbabwe | Bng | 119 | 2.4 |
50 | 2674 | England | Nzl | 130 | 2.6 | 2797 | Zimbabwe | Bng | 127 | 2.5 |
The first four bowlers bowled by South Africa against New Zealand in match No. 1805 were maidens and this fact is reflected in this table. Similarly the first three overs bowled by South Africa against India in the second innings of match No. 2298 were also maidens. The lowest scores at the end of 25th over are 43 and 47 respectively. The lowest score at the end of the full 50 overs is 130 and 127. It is obvious that many an innings would have folded for sub-100 totals around over 40-45.
ODI Match | Bowling team | Bat | Inns | Over no | Bowler | Runs | Over | Bowler | Runs |
---|---|---|---|---|---|---|---|---|---|
1794 | Bangladesh | Pak | 2 | 9 | Enamul Haque | 28 | 10 | Tareq Aziz | 0 |
1837 | India | Win | 2 | 6 | AB Agarkar | 0 | 7 | T Yohannan | 25 |
2362 | India | Eng | 1 | 17 | RP Singh | 1 | 18 | VRV Singh | 26 |
2537 | Netherlands | Saf | 1 | 30 | DLS van Bunge | 36 | 31 | LP van Troost | 5 |
2584 | Sri Lanka | Pak | 2 | 38 | SL Malinga | 0 | 39 | CM Bandara | 32 |
2814 | Zimbabwe | Ken | 1 | 48 | E Chigumbura | 27 | 49 | AG Cremer | 1 |
2981 | Zimbabwe | Ind | 1 | 3 | CB Mpofu | 0 | 4 | E Chigumbura | 26 |
3398 | South Africa | Slk | 2 | 32 | JP Duminy | 1 | 33 | RJ Peterson | 35 |
3398 | South Africa | Slk | 2 | 33 | RJ Peterson | 35 | 34 | JP Duminy | 0 |
3416 | England | Aus | 1 | 43 | BA Stokes | 3 | 44 | JE Root | 28 |
3421 | India | Aus | 2 | 48 | I Sharma | 30 | 49 | R Ashwin | 5 |
These are chalk and cheese overs. The difference in runs scored is greater than 25. The maximum difference between overs is the 35 between the famous Robin Peterson over and the following JP Duminy over which was a maiden. In fact this is an amazing sequence and is represented in two consecutive entries in this table. The sequence was Duminy (1) - Peterson (35) - Duminy (0). How could Peterson bowl a 35-run over between two near-maidens?
Herschelle Gibbs' famous 36-run over off Daan van Bunge was followed by the frugal five-run over by Luuk van Troost. Lasith Malinga's maiden over was followed by Malinga Bandara's 32-run extravaganza. And so on. And readers will note that these are not that frequent. In 1700 matches there are only ten matches in which this has happened.
ODI Match | Bowling team | Bat | Inns | Over-1 | Bowler | Over-2 | Bowler | Over-3 | Bowler | Over-4 | Bowler |
---|---|---|---|---|---|---|---|---|---|---|---|
1805 | South Africa | Nzl | 1 | 1 | SM Pollock | 2 | M Ntini | 3 | SM Pollock | 4 | M Ntini |
2066 | West Indies | Zim | 2 | 6 | VC Drakes | 7 | R Rampaul | 8 | VC Drakes | 9 | R Rampaul |
2216 | South Africa | Eng | 2 | 11 | SM Pollock | 12 | A Nel | 13 | SM Pollock | 14 | A Nel |
2258 | England | Aus | 1 | 22 | SP Jones | 23 | SJ Harmison | 24 | SP Jones | 25 | SJ Harmison |
2345 | South Africa | Aus | 2 | 8 | M Ntini | 9 | SM Pollock | 10 | M Ntini | 11 | SM Pollock |
2719 | West Indies | Aus | 1 | 10 | DBL Powell | 11 | JE Taylor | 12 | DBL Powell | 13 | DJ Bravo |
2742 | Sri Lanka | Ind | 1 | 26 | BAW Mendis | 27 | M Muralitharan | 28 | BAW Mendis | 29 | M Muralitharan |
3313 | Bangladesh | Win | 1 | 4 | Shafiul Islam | 5 | Sohag Gazi | 6 | Shafiul Islam | 7 | Sohag Gazi |
3313 | Bangladesh | Win | 1 | 5 | Sohag Gazi | 6 | Shafiul Islam | 7 | Sohag Gazi | 8 | Shafiul Islam |
3389 | West Indies | Pak | 1 | 11 | DJG Sammy | 12 | JO Holder | 13 | DJG Sammy | 14 | JO Holder |
Four maiden overs in a row! I can hear someone saying whether I am serious. Yes, I am. When I did three maidens in a row, I had over 30 entries. When I did five maidens, I had one entry. So I plumped for four. Let us not forget that these are Maidens. No run accrued to the teams.
Shaun Pollock and Makhaya Ntini opened the proceedings with four maidens in a row against New Zealand. This is the only instance of four consecutive maidens starting from the first over of the innings. Pollock was involved in another four-maiden series, this time with Andre Nel, against England. And then Pollock achieved this again, once again with Ntini. He is some bowler!
But the most amazing sequence was the recent Bangladesh-West Indies sequence. West Indies reached 17 for 1 in three overs. Then Kieran Powell, Chris Gayle and Marlon Samuels played five consecutive maiden overs against Sohag Gazi and Shafiul Islam. This was Samuels of Delhi vintage, not the Kochi player. These three seemingly attacking players played 33 consecutive dot balls, and lost two wickets. Strange indeed.
Let us not forget that these are for part of the recent 1700 matches or so. Phil Simmons, in his spell of 10-8-3-4, Bishan Bedi in his spell of 12-8-6-1, Sunil Joshi in his spell of 10-6-6-5 and Richard Hadlee in his spell of 12-6-10-0 could as well have bowled five consecutive maidens in tandem with other bowlers.
ODI Match | Bowling team | Bat | Inns | Over no | Bowler | Runs | Over | Bowler | Runs |
---|---|---|---|---|---|---|---|---|---|
1994 | Zimbabwe | Pak | 1 | 49 | SM Ervine | 24 | 50 | DT Hondo | 23 |
2046 | South Africa | Pak | 1 | 49 | SM Pollock | 22 | 50 | JH Kallis | 20 |
2140 | West Indies | Eng | 1 | 45 | DJ Bravo | 21 | 46 | DR Smith | 27 |
2169 | USA | Nzl | 1 | 47 | HR Johnson | 27 | 48 | LC Romero | 27 |
2411 | England | Pak | 1 | 49 | SI Mahmood | 26 | 50 | J Lewis | 21 |
2506 | Pakistan | Saf | 1 | 46 | Abdul Razzaq | 22 | 47 | Mohammad Asif | 28 |
2807 | Kenya | Zim | 1 | 48 | PJ Ongondo | 26 | 49 | NN Odhiambo | 20 |
3046 | England | Pak | 1 | 49 | JM Anderson | 21 | 50 | TT Bresnan | 21 |
3221 | India | Win | 1 | 49 | A Mithun | 23 | 50 | UT Yadav | 20 |
3336 | England | Nzl | 1 | 42 | CR Woakes | 21 | 43 | SCJ Broad | 20 |
3359 | Netherlands | Saf | 1 | 47 | Mudassar Bukhari | 20 | 48 | PA van Meekeren | 23 |
3362 | New Zealand | Eng | 1 | 48 | KD Mills | 22 | 49 | MJ McClenaghan | 20 |
3362 | New Zealand | Eng | 1 | 49 | MJ McClenaghan | 20 | 50 | TG Southee | 22 |
3428 | Australia | Ind | 1 | 47 | XJ Doherty | 26 | 48 | JP Faulkner | 20 |
These are consecutive overs in which 20 runs were crossed. Not many instances are there, with none during the second innings. However one match stands out. That is the recent Trent Bridge ODI between England and New Zealand. All the last three overs of the England exceeded 20 runs. This is the only such instance. The main destroyer was Jos Buttler, with his 16-ball 47.
The others are instances where two consecutive overs exceeded 20 runs. It is surprising to note that Pollock, who has been part of many maiden-over sequences, is present, along with Jacques Kallis. Surprisingly the fastest scoring innings of all time, the 21-over 283 by New Zealand, contains no such sequence. Similarly the famous Wanderers match does not contain such a sequence.
It is almost certain that there would be very few such sequences during the first half of the ODI matches. Bowlers were not treated like third-class citizens then.
ODI Match | Bowling team | Bow | Inns | Over | MaxOvers | Team Score | Bowler | Runs | % of TS |
---|---|---|---|---|---|---|---|---|---|
1473 | Australia | Ind | 2 | 37 | 49 | 205 | SK Warne | 21 | 10.24% |
1794 | Bangladesh | Pak | 2 | 9 | 36 | 221 | Enamul Hoque | 28 | 12.67% |
1801 | New Zealand | Saf | 1 | 49 | 50 | 270 | JEC Franklin | 27 | 10.00% |
1837 | India | Win | 2 | 7 | 23 | 124 | T Yohannan | 25 | 20.16% |
1873 | Australia | Pak | 1 | 48 | 50 | 227 | JN Gillespie | 24 | 10.57% |
1889 | India | Slk | 1 | 10 | 50 | 222 | AB Agarkar | 23 | 10.36% |
1928 | India | Nzl | 2 | 5 | 27 | 109 | J Srinath | 22 | 20.18% |
1963 | Canada | Win | 2 | 7 | 21 | 206 | D Joseph | 21 | 10.19% |
1963 | Canada | Win | 2 | 10 | 21 | 206 | BB Seebaran | 26 | 12.62% |
1984 | New Zealand | Zim | 1 | 50 | 50 | 252 | AR Adams | 26 | 10.32% |
2217 | Zimbabwe | Bng | 2 | 8 | 33 | 202 | E Chigumbura | 24 | 11.88% |
2335 | West Indies | Nzl | 2 | 17 | 42 | 204 | JE Taylor | 22 | 10.78% |
2395 | Zimbabwe | Bng | 1 | 11 | 50 | 206 | EC Rainsford | 21 | 10.19% |
2411 | England | Pak | 1 | 49 | 50 | 235 | SI Mahmood | 26 | 11.06% |
2435 | Sri Lanka | Saf | 1 | 49 | 50 | 219 | MF Maharoof | 22 | 10.05% |
2463 | Pakistan | Win | 1 | 6 | 47 | 207 | Naved-ul-Hasan | 21 | 10.14% |
2537 | Netherlands | Saf | 1 | 30 | 40 | 353 | DLS van Bunge | 36 | 10.20% |
2583 | India | Bng | 2 | 47 | 49 | 238 | D Mongia | 26 | 10.92% |
2584 | Sri Lanka | Pak | 2 | 39 | 42 | 239 | CM Bandara | 32 | 13.39% |
2671 | West Indies | Saf | 2 | 13 | 29 | 211 | DJ Bravo | 22 | 10.43% |
2706 | Bangladesh | Ind | 2 | 10 | 36 | 223 | Dolar Mahmud | 24 | 10.76% |
2764 | Bangladesh | Nzl | 1 | 50 | 50 | 212 | Abdur Razzak | 25 | 11.79% |
2792 | West Indies | Nzl | 2 | 2 | 35 | 211 | DBL Powell | 23 | 10.90% |
2809 | Kenya | Zim | 2 | 42 | 49 | 236 | PJ Ongondo | 26 | 11.02% |
2826 | England | Win | 2 | 40 | 47 | 244 | SJ Harmison | 26 | 10.66% |
2828 | England | Win | 2 | 7 | 15 | 117 | AD Mascerenhas | 24 | 20.51% |
3036 | Netherlands | Ire | 2 | 9 | 21 | 129 | Adeel Raja | 26 | 20.16% |
3049 | Zimbabwe | Ire | 1 | 50 | 50 | 238 | EC Rainsford | 24 | 10.08% |
3150 | Bangladesh | Aus | 2 | 22 | 26 | 232 | Suhrawadi Shuvo | 27 | 11.64% |
3311 | Bangladesh | Win | 2 | 45 | 47 | 228 | Rubel Hossain | 24 | 10.53% |
3331 | Australia | Win | 2 | 37 | 39 | 212 | GJ Maxwell | 24 | 11.32% |
3341 | Scotland | Afg | 2 | 30 | 34 | 203 | PL Mommsen | 25 | 12.32% |
3358 | Ireland | Pak | 2 | 47 | 49 | 230 | TJ Murtagh | 24 | 10.43% |
3398 | South Africa | Slk | 2 | 33 | 44 | 167 | RJ Peterson | 35 | 20.96% |
3434 | Sri Lanka | Nzl | 2 | 23 | 23 | 203 | HMRKB Herath | 25 | 12.32% |
These are the overs in which the overs comprised of high percentage of team scores. The criteria are 10% of 200-plus innings, 15% of 150-plus innings and 20% of 100-plus innings. Quite a few overs qualify.
There are five overs in which over 20% of team runs were scored. Four of these are 100-plus scores. The one noteworthy exception is the Peterson over in which he conceded 35 runs in a team total of 167: that is nearly 21%. Another over that stands out is the Bandara over to Pakistan. On a fair score of 239, Bandara conceded 32 runs in an over, which worked out to 13.4%.
In the next part, I will do the concluding analysis. I will look at over groups across countries and periods. That will be pure analysis and one tough analysis to present because of the three dimensional nature of data.
A bonus for the readers. I have a rare two-volume collection of Bradman memorabilia. It is a fantastic set of books and contains scorecards, telegrams, photographs, letters et al. Along with each article I will scan one such rare document and attach for user viewing. To view the first such scan, please click HERE. This is a chart of Bradman's record-breaking 334. I will leave it to the discerning readers to summarise the chart in their own inimitable ways. The one thing that stands out is the 360 degrees coverage. Look at the number of boundaries in the "V".
An analysis using ball-by-ball data to identify scoring and wicket-taking patterns through the 50-over innings in ODIs
I had earlier done a head-to-head analysis on ODI batsmen. This is the first part of a series of articles where I will take an anecdotal look at the overs and look at the over as a single entity. In the second (and possibly the third) part, I will look at over groups, possibly incorporating teams and periods. I will analyse bowlers later.
Redefinition of the dot ball and maiden over
I have made a very significant and common-sense based redefinition of one of the pillars of bowling analysis. Henceforth I will treat a dot ball as one in which no run was added to the opposing team. Thus a maiden over comprises of six such tougher-defined dot balls. I am sure most readers will agree with me. The current definition of dot ball and maiden over dating back to 1877, is outdated and archaic for the modern ODI game.A bowler should earn his maiden today. Already we have amendments to the law that do not allow wide and no-ball to be exempt while looking at dot balls and maiden overs. I have simply extended this concept to byes and leg byes. When Irfan Pathan bowled six balls to Ravi Bopara in Cuttack in 2008 and conceded eight leg byes, he, good bowler though he is, did not deserve a maiden. There is no denying that eight runs were accrued to the England total which is all that matters. This over should never be treated as a maiden.
The bottom line as far as I am concerned is that it is the runs conceded to the other team that matter, not the runs conceded to the batsmen. This is to emphasise the team game concept. I have talked about this in depth since I know that the point will be raised by readers. I will accept and post all such comments but will not change my interpretation.
First let us see some interesting overs bowled in ODIs. It is a pity that this cannot be done for the first half of the ODI matches but readers may jog their memory cells and come out with gems during the first 30 years or so.
A. 30+ run overs
1. Match# 2537/39: Daan van Bunge to Herschelle Gibbs. The sequence is a pure and perfect domination: "6 6 6 6 6 6". Nothing more needs to be said. Gibbs joins Garry Sobers, Ravi Shastri and Yuvraj Singh, and, on the flip side, van Bunge joins Malcolm Nash, Tilak Raj and Stuart Broad.2. Match# 3398/33: Robin Peterson to Thisara Perera. The unbelievable sequence was "6 1wd 6 6 6 4 6". A near-perfect over spoiled by the solitary wide, but still comes in second.
3. Match# 2584/39: Malinga Bandara bowled an all-boundary over to Shahid Afridi. The scorecard read "4 4 6 6 6 6". No wide to spoil the lovely sequence.
4. Match# 2619/50: Yuvraj Singh to Dmitri Mascarenhas. I have moved this up even though it is a 30-run over. The sequence is wonderful: "0 6 6 6 6 6". After a dot ball, Mascarenhas dispatched every ball over the ropes.
5. Match# 3421/47: Ishant Sharma to James Faulkner. This was not an all-boundary over but close to it with a series of even number runs. The sequence was "4 6 6 2 6 6".
6. Match #3123/49: Abdul Razzaq to Ross Taylor in the 2011 World Cup. The sequence was "4 6 1wd 6 1wd 2 4 6". It was amazing how he kept strike.
7. Match# 3129: Rizwan Cheema and Harvir Baidwan to James Franklin and Kane Williamson. This was a messy over. The sequence will reveal what happened. "1 6 6 4 6 5(4+1nb) 1wd 2". The fifth ball was a high full toss which meant Cheema was banned from bowling and Baidwan completed the over. Overall very sloppy work by the Canadians.
8. . Match# 2537/39: This was later in the Gibbs innings. van Troost (the other van) bowled to Kallis and Boucher. The sequence was "4 1 2 5wd 6 6 6".
B. 4-wicket overs
1. Match#2071/37: It will be tough to take this over off the "best last over" perch. Mohammad Sami bowled Jacob Oram and Tama Canning to start with. Then he bowled two dot balls to Daniel Vettori. He finished the over off by dismissing Vettori and Paul Hitchcock. Four wickets to Sami, and a maiden over to boot.2. Match#1950/1: Almost certainly the best first over in history. Chaminda Vaas dismissed Hannan Sarkar, Mohammad Ashraful and Ehsanul Haq to get a hat-trick off the first three balls. Then he conceded a four and a wide and dismissed Alok Kapali lbw. There was finally a dot ball to finish the over. Four wickets and five runs. These two overs are the only ones in which the bowlers have captured all four wickets.
3. Match# 3275/43: Thisara Perera bowled a fantastic over to finish off the match. A dot ball to Younis Khan started the proceedings. Then he dismissed Younis, Afridi and Sarfraz Ahmed to get a hat-trick. Then a dot ball was followed by a run-out of Sohail Tanvir. A maiden over, three wickets and a run-out: and all this against a top team like Pakistan. It is of interest to note that Perera is the only player to find an entry in both 30-plus runs and four-plus wickets lists.
4. Match#2054/50: This was also against a top team, Australia. Ajit Agarkar bowled Damien Martyn, conceded a single to Michael Clarke, dismissed Michael Bevan, bowled a wide, conceded a single to Clarke, and then Clarke was run out, and finally Andy Bichel was dismissed by Agarkar. Three wickets, one run-out and three runs.
5. Match# 1969/50: Andrew Caddick started the over typically. He bowled a dot ball, conceded two wides and then a single. But he finished the over strongly: dismissing Mohammad Kaif, Rahul Dravid and Javagal Srinath with a run-out in between.
6. Match# 2140/50: The unlikely Chris Gayle got three wickets and there was a run-out in this last over. Gayle dismissed Andrew Flintoff, Andrew Strauss and Paul Collingwood and then Geraint Jones was run out. It must be conceded that there was a double-century stand between Flintoff and Strauss before this over. Gayle followed this magnificent over with an equally majestic 132.
7. Match# 1963/43: Vasbert Drakes claimed two wickets and conceded five runs in this over to finish off Canada's innings, aided by two run-outs.
8. Match# 3136/50: This was an extraordinary over by Kevin O'Brien. Two dot balls and a wide to Atse Buurman set the tone. This was followed by four run-outs. So Netherlands moved from 305 for 6 to 306 for 9, without a single bowler wicket.
C. Innings last over maidens
First innings:1. Match# 1891: Allan Donald for South Africa against Bangladesh.
2. Match# 2017: Daryl Tuffey for New Zealand against Pakistan.
Second innings:
3. Match# 1790: Inzamam-ul-Haq (yes, you read it correctly) for Pakistan against Bangladesh. I watched this on television. It was the most hilarious five minutes of my life. Inzamam bowled (no, threw, at an estimated 60 degrees elbow bend!) six balls, dismissed Enamul Haque, and millions, including the 15 players on ground, were in splits. It was like Buster Keaton meeting Laurel, Hardy, Abbot, Costello, Chaplin and Nagesh.
4. Match # 2837: Ryan ten Doeschate for Netherlands against Bermuda.
5. Match# 3337: Narsingh Deonarine for West Indies against Zimbabwe.
D. Great last overs: Truly wonderful overs that almost certainly won the game for the bowling team
1. Match# 3080: Munaf Patel had only three runs available when the last over started against South Africa. A South African win seemed certain. Then Munaf bowled, almost unarguably, the best last over in ODI history. The sequence was "1 W 0 1 0 W". Two wickets and two runs meant that India won by one run.2. Match# 2913: Peter Siddle, against India, had eight runs available to defend. He bowled a wonderful last over conceding three and capturing one wicket, leaving Australia winners by four runs.
3. Match# 2923: Lightning struck a few days later in Hyderabad. Australia scored 350 but then Sachin Tendulkar played, arguably, his greatest ODI innings, of 175. He fell a few runs short of the target. Shane Watson had only seven runs to defend in the last over. He conceded four singles, and a run-out meant Australia won a match of 697 runs, by three runs.
4. Match# 3425: Morne Morkel had only two runs available. He bowled a great trio of deliveries: A single, followed by a dot ball and then a wicket, to give South Africa a one-run win over Pakistan.
5. Match# 3058: Rubel Hossain had only seven runs to play with. He conceded a four off the first ball. Then bowled a dot ball and bowled Kyle Mills to take Bangladesh to an unexpected three-run win over New Zealand.
6. Match# 2302: Australia's Mick Lewis who, unfortunately, sank without a trace in the 438-run bloodbath, started the last over against New Zealand with five runs to defend. Three runs were scored but two run-outs were effected and Australia won by two runs.
For those who would like to refer to Tendulkar's last over against South Africa in Calcutta, there is no ball data for that match (a single to Brian McMillan, and Fanie de Villiers was run out trying for the second run that wasn't there, three dot balls to Donald, a single to Donald then a single to McMillan).
I have departed from my normal way of structuring the article. Normally I produce tables, explain them, produce graphs and add closing description. This time I have decided to use only the graphs, which are self-explanatory. The tables are too long and are available for downloading and perusal.
The first graph is the analysis of average runs scored in each over. Remember that the data for each over data is the compilation of thousands of overs across matches.
Some very interesting points emerge from the graph. The average runs scored per over, across all 50 overs, is just a fraction either side of 5.0 for the first and second innings. This is because the additional runs scored in the first-innings wins by runs is offset by fewer overs required to chase successfully. The average number of overs per innings for the first innings is 47.1 and for the second innings, 40.4.
However, there is considerable variation across the overs in the two innings. In the first innings, the teams start slowly during the first 15 overs, consolidate and then move into higher gears in the last few overs. Obviously the real reason is that they do not know what targets are to be set. The first over has an average of only 3.23 runs per over. The last three overs are well above 8.0 and even cross 10.0 for the 50th over.
The second innings is planned in a better manner. The teams know what the targets are. They start in the second gear in the initial overs, consolidate and finish on a more even keel, at around seven runs per over at the end. It is of interest to note that no second innings over even exceeds 8.0 runs per over. The graph clearly shows the even distribution.
The runs per over in the first innings crosses 5.0 only in the 36th over while in the second innings 5.0 gets crossed as early as sixth over. Once 5.0 is crossed in the first innings it stays above this for the remaining 14 overs. In the second innings the runs-per-over value stays above 5.0 for 17 overs. The dip in the middle overs is deeper in the first innings than in the second innings.
The Standard Deviation (SD) for the two innings confirms this. The SD for the first innings is 1.334 and for the second innings, 0.833.
Is there anything that stands out? Possibly the clear increase in runs per over in the first innings, 40th over onwards, and the caution-induced plateau in scoring between overs 41 and 45 in the second innings. While I will be covering groups of overs in the second article, it is pertinent to point out that the slight increase in tempo of scoring around the third Powerplay in both innings.
A look at the best ODI players and the most productive streaks in their careers
The number 52 was flashing in neon lights as I embarked on the Test streak analysis. That number, along with 6996 and 99.94, is embedded in every Test follower's minds. No further explanations are needed. For bowlers I had a less known number but one which would be familiar to the serious cricket enthusiasts. The number 27 might not have the same impact as 52, but it gave me a high enough bar to work with: Although Muttiah Muralitharan jumped over it. So I worked with 52 and 27. Both came out very well.
When I wanted to do a similar player streak analysis for ODIs, I realised that there were no such numbers which stood out. No one has dominated the ODI game like Don Bradman did in the Test arena. We can cut, slice and dice in every which way, but no one player is more than 10% ahead of the next best: whether in batting or bowling, especially in performance-related measures. So I have to adopt some special method to hang my hat on the cut-off numbers.
I could easily fix this as 50 ODIs. But that will be both inadequate and simplistic. So I approached this from the other end. What are my wickets and runs cut-offs? One hundred wickets seems to be adequate and represents a fairly decent career. Using the overall summary table, I see that the average RpW figure over 3500-plus matches is 27-plus. So 2500 (~ 27*100) runs seem fine. Both cut-offs would require careers to be well over 50 matches long.
Now I looked at the two tables with these cut-offs. There are 149 batsmen and 121 bowlers who qualify, which makes it a very good population of all the top players. Then I looked at the least number of matches played by these players. In batting, I had Zaheer Abbas, who had played 62 matches to compile just over 2500 runs. Dennis Lillee had played 63 matches to just cross 100 wickets. These are two top-flight players. Zaheer is in the top-ten batting average group and Lillee in the top-five bowling average group. There I had my answer. I decided that I will have a cut-off of 62 matches for batsmen and 63 matches for bowlers. The final tables bear out the strength of these cut-offs.
The rest is routine. The additional thing is that I would split the Average and RpI measures into lower level components and also do a table of win percentage achieved. The batting and bowling strike rates and bowling accuracy are important measures and have to be given their due recognition.
Let us move on to the tables. I have uploaded the complete tables and the readers could get complete information of all qualifying players by downloading these tables.
Runs | Batsman | Team | Best streak | Years | Worst streak | Runs | Best-Worst |
---|---|---|---|---|---|---|---|
3340 | HM Amla | Saf | 2759(2008)-3347(2013) | 4.5 | 3062(2010)-3524(2014) | 2955 | 113.0% |
3233 | AB de Villiers | Saf | 2804(2009)-3363(2013) | 4.4 | 2219(2005)-2666(2008) | 1961 | 164.9% |
3084 | SR Tendulkar | Ind | 1658(2000)-2077(2004) | 3.1 | 634(1990)- 881(1994) | 1625 | 189.8% |
3009 | V Kohli | Ind | 3219(2011)-3476(2014) | 2.2 | 2742(2008)-3189(2011) | 2224 | 135.3% |
2979 | BC Lara | Win | 936(1994)-1363(1998) | 4.0 | 2070(2003)-2464(2006) | 1579 | 188.7% |
2913 | DM Jones | Aus | 471(1987)- 672(1991) | 3.4 | 649(1990)- 902(1994) | 2137 | 136.3% |
2909 | G Kirsten | Saf | 937(1994)-1283(1998) | 3.3 | 1131(1996)-1549(2000) | 1731 | 168.1% |
2896 | SC Ganguly | Ind | 1385(1999)-1640(2000) | 1.8 | 1926(2002)-2267(2005) | 1823 | 158.9% |
2871 | CH Gayle | Win | 1727(2001)-2096(2004) | 2.6 | 2826(2009)-3509(2014) | 1635 | 175.6% |
2845 | KC Sangakkara | Slk | 3216(2011)-3481(2014) | 2.3 | 1610(2000)-1908(2002) | 1183 | 240.5% |
2820 | RT Ponting | Aus | 2256(2005)-2657(2007) | 2.5 | 1791(2002)-2084(2004) | 1932 | 146.0% |
2808 | ML Hayden | Aus | 2097(2004)-2627(2007) | 3.7 | 1976(2003)-2421(2006) | 2049 | 137.0% |
2798 | V Sehwag | Ind | 2672(2008)-3233(2012) | 4.0 | 2115(2004)-2379(2006) | 1645 | 170.1% |
2780 | GA Gooch | Eng | 145(1982)- 701(1992) | 9.9 | 518(1988)- 969(1995) | 1785 | 155.7% |
2780 | CG Greenidge | Win | 37(1976)- 300(1985) | 8.4 | 300(1985)- 677(1991) | 2267 | 122.6% |
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1252 | Moin Khan | Pak | 1193(1997)-1476(1999) | 2.2 | 679(1991)-1152(1996) | 617 | 202.9% |
1105 | SM Pollock | Saf | 2271(2005)-2650(2007) | 2.3 | 1555(2000)-1797(2002) | 305 | 362.3% |
971 | Wasim Akram | Pak | 1303(1998)-1594(2000) | 2.1 | 277(1984)- 527(1988) | 303 | 320.5% |
Look at the glittering array of batsmen in the top ten of the batsmen who have amassed the maximum runs in a 62-match streak. Three modern greats and two all-time greats adorn the top five. If a captain had these five and Viv Richards in the top six, he could very well have an unbeatable team.
Hashim Amla's Test exploits makes many a follower overlook his ODI achievements. He has the highest career average, in excess of 50, amongst all batsmen. During these 62 matches his average runs per match exceeded 50. That is something! AB de Villiers is not far behind. Hundred runs, which is all. South Africa should be accumulating all the top prizes with these two and Dale Steyn in their ranks. Maybe 2015 is their year. Then it is Sachin Tendulkar, who at his peak compiled a very impressive 3000-plus runs in 62 matches. This was just after 2000. Virat Kohli is the only other batsman to accumulate in excess of 3000 runs in the streak of 62 matches. This has been done during the past three years. He cannot buy a Test run nowadays but he is a king in ODIs. Brian Lara, who goes unnoticed when we talk of ODI cricket, scored nearly 3000 runs at the beginning of his career.
I have also indicated the number of years it took for these batsmen to play 62 ODI matches. Even Amla and de Villiers required over four years. During the early days, Graham Gooch and Gordon Greenidge took well over eight years. But Kohli took only 2.2 years, and Sourav Ganguly even less: only 1.8 years. India has played an average of 35-40 ODIs per year during the recent years.
I have also provided an additional comparison point. I have compiled the worst 62-match streak for each batsman and compared the best and worst streaks. Amla has the lowest ratio: only 113%. This indicates a very steady and consistent career. It could also be a reflection of the fewer matches Amla has played. Tendulkar's best streak is 189% of his worst streak, indicating lot of turbulence in his career: bound to happen when one plays over 400 matches. Lara comes close with 188%. But the number which stands out is Kumar Sangakkara's 240%. Compare the 2845 runs Sangakkara accumulated recently with the meagre 1183 runs around the turn of this century.
ARpI | Batsman | Team | Career-Inns | C-Runs | C-RpI | Best streak | A-Inns | Runs |
---|---|---|---|---|---|---|---|---|
55.61 | HM Amla | Saf | 92 | 4621 | 50.22 | 2759(2008)-3347(2013) | 60.06 | 3340 |
55.03 | AB de Villiers | Saf | 162 | 6780 | 41.85 | 2804(2009)-3363(2013) | 58.75 | 3233 |
52.97 | SR Tendulkar | Ind | 452 | 18426 | 40.76 | 1658(2000)-2077(2004) | 58.23 | 3084 |
52.76 | V Kohli | Ind | 130 | 5688 | 43.75 | 3219(2011)-3476(2014) | 57.03 | 3009 |
52.46 | IVA Richards | Win | 167 | 6721 | 40.24 | 208(1983)- 376(1986) | 51.51 | 2702 |
50.07 | BC Lara | Win | 289 | 10405 | 36.00 | 936(1994)-1363(1998) | 59.50 | 2979 |
49.05 | KC Sangakkara | Slk | 357 | 12844 | 35.97 | 3216(2011)-3481(2014) | 58.00 | 2845 |
48.54 | MS Dhoni | Ind | 216 | 8127 | 37.62 | 2670(2008)-2942(2010) | 50.78 | 2465 |
48.39 | S Chanderpaul | Win | 251 | 8778 | 34.97 | 2437(2006)-2987(2010) | 56.37 | 2728 |
48.00 | RT Ponting | Aus | 365 | 13704 | 37.54 | 2256(2005)-2657(2007) | 58.75 | 2820 |
47.75 | DM Jones | Aus | 161 | 6068 | 37.68 | 471(1987)- 672(1991) | 61.00 | 2913 |
47.28 | G Kirsten | Saf | 185 | 6798 | 36.74 | 937(1994)-1283(1998) | 61.52 | 2909 |
47.07 | CH Gayle | Win | 253 | 8810 | 34.82 | 1727(2001)-2096(2004) | 61.00 | 2871 |
46.79 | SC Ganguly | Ind | 300 | 11363 | 37.87 | 1506(1999)-1764(2001) | 61.00 | 2854 |
46.22 | ML Hayden | Aus | 155 | 6133 | 39.56 | 2097(2004)-2627(2007) | 60.76 | 2808 |
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23.91 | Moin Khan | Pak | 183 | 3266 | 17.84 | 1193(1997)-1476(1999) | 52.36 | 1252 |
23.80 | E Chigumbura | Zim | 151 | 3277 | 21.70 | 2459(2006)-2976(2010) | 60.00 | 1428 |
19.05 | Wasim Akram | Pak | 280 | 3717 | 13.27 | 1298(1998)-1593(2000) | 50.75 | 967 |
First let me explain about the ARpI (Adjusted Runs per Innings). The Batting average is an overstated measure. 3*, 77*, 400* et al., are all ignored. Because it has always been there, the flawed measure has continued to flourish. It could be called the Average per dismissed innings. It is too much slanted in favour of the middle-order batsmen, especially in limited-over matches. RpI (Runs per Innings) goes to the other extreme. Scores of 0, 7*, 97, 242*, 375 are all considered equal from the point of view of innings. It is too unfair to the middle order batsmen, especially in limited over matches.
So I have determined what is probably the most accurate measure called ARpI. The basis is simple, very logical and easy to understand and implement. In this measure, I add to the divisor an innings fraction based on the overall RpI value for those not outs below this RpI value. That means if the RpI is 40, an 11* will add 0.275 to the divisor, a 29* will add 0.725 and so on. A 123* will obviously be considered as a completed innings. Mathematically this is the almost perfect figure.
I will explain this with Tendulkar's streak. His streak figures are 60 inns, 9 not outs, 3084 runs. For Batting average, the divisor would be 51 and for RpI, the divisor would be 60. Both are incorrect. His not-out innings are 70*, 81*, 122*, 87*, 34*, 105*, 9*, 7* and 48*. His career RpI is 40.76. So there is no problem with six of these innings above 41. These are treated as completed innings. Now the real work starts. The equation for Tendulkar is 51(outs) + 6(completed inns) + (34/40.76 + 9/40.76 + 7/40.76), which works to 58.23: a reduction of 1.77 from the total number of innings. Nothing can be fairer than this. I would suggest that the readers understand this clearly since this will be the measure used going forward. My thanks to Milind and Ruchi for their incisive contributions in getting this important tweak going.
This table lists the best ARpI value achieved during any streak of 62 matches. The top four in this table are the same in the run aggregate table. Two South African batsmen lead with phenomenal values above 55. Two Indian batsmen have RpI values above 52.7. Finally Richards, the master, makes his appearance with a peak ARpI value of 52.5. In the middle of this streak was the most famous ODI innings of all time: the 189 at Manchester. Lara just slips out of the top five and has an ARpI value of just above 50. Do not forget that this is an ARpI table and not an RpM one; only those matches are considered where the player got a chance to bat. Despite his late-middle-order batting position, now benefited by the ARpI tweak, Dhoni breaks into the top ten with a very creditable ARpI value of 48.5.
BpI | Batsman | Team | Career-Inns | C-Balls | C-BpI | Best streak | Inns | Balls |
---|---|---|---|---|---|---|---|---|
77.2 | GR Marsh | Aus | 117 | 7790 | 66.6 | 503(1988)- 739(1992) | 60 | 4634 |
72.0 | GA Gooch | Eng | 125 | 6932 | 55.5 | 145(1982)- 701(1992) | 61 | 4394 |
70.8 | CG Greenidge | Win | 128 | 7908 | 61.8 | 41(1977)- 370(1986) | 62 | 4390 |
66.5 | DL Haynes | Win | 238 | 13707 | 57.6 | 234(1984)- 423(1987) | 61 | 4056 |
66.0 | KC Wessels | Saf | 109 | 6088 | 55.9 | 232(1984)- 800(1993) | 59 | 3892 |
64.8 | DM Jones | Aus | 164 | 8362 | 51.0 | 471(1987)- 672(1991) | 61 | 3953 |
64.8 | Javed Miandad | Pak | 233 | 11014 | 47.3 | 375(1986)- 589(1989) | 60 | 3887 |
64.2 | S Chanderpaul | Win | 267 | 12408 | 46.5 | 2437(2006)-2987(2010) | 58 | 3723 |
63.1 | AH Jones | Nzl | 87 | 4811 | 55.3 | 485(1988)- 776(1992) | 62 | 3914 |
61.1 | G Kirsten | Saf | 185 | 9436 | 51.0 | 937(1994)-1283(1998) | 62 | 3786 |
60.3 | SC Ganguly | Ind | 311 | 15416 | 49.6 | 1231(1997)-1444(1999) | 60 | 3616 |
60.3 | DC Boon | Aus | 181 | 9157 | 50.6 | 694(1991)- 932(1994) | 61 | 3680 |
60.0 | BC Lara | Win | 298 | 13086 | 43.9 | 749(1992)-1000(1995) | 61 | 3659 |
59.7 | HM Amla | Saf | 95 | 5177 | 54.5 | 2772(2008)-3367(2013) | 61 | 3642 |
59.5 | IJL Trott | Eng | 68 | 3658 | 53.8 | 2929(2009)-3373(2013) | 59 | 3509 |
----- | ||||||||
26.3 | SM Pollock | Saf | 303 | 4059 | 13.4 | 1099(1996)-1478(1999) | 45 | 1182 |
23.6 | N Kapil Dev | Ind | 225 | 3979 | 17.7 | 207(1983)- 416(1987) | 55 | 1299 |
21.9 | Wasim Akram | Pak | 356 | 4208 | 11.8 | 1312(1998)-1599(2000) | 52 | 1139 |
This is the first component of the RpI: the average Balls per Innings (BpI). The table is headed by the solid batsmen of the early period. Not one of them has a strike rate exceeding 65. So they figure in this table but would be way down in the RpI table. It is towards the end of the table that we see some interesting batsmen. The last three in the featured list, Lara, Amla and Jonathan Trott figure in the top of the RpI table. Amla has a strike rate around 90 throughout his career.
S/R | Batsman | Team | Career-Runs | C-Balls | C-S/R | Best streak | Runs | Balls |
---|---|---|---|---|---|---|---|---|
151.9 | Shahid Afridi | Pak | 7652 | 6614 | 115.7 | 2174(2004)-2639(2007) | 1162 | 765 |
124.8 | V Sehwag | Ind | 8273 | 7929 | 104.3 | 2705(2008)-3251(2012) | 2778 | 2226 |
110.0 | ST Jayasuriya | Slk | 13430 | 14725 | 91.2 | 1074(1996)-1346(1998) | 2498 | 2271 |
109.6 | AC Gilchrist | Aus | 9619 | 9922 | 96.9 | 2082(2004)-2366(2006) | 2383 | 2175 |
108.8 | N Kapil Dev | Ind | 3783 | 3979 | 95.1 | 332(1985)- 517(1988) | 1279 | 1176 |
108.2 | Wasim Akram | Pak | 3717 | 4208 | 88.3 | 426(1987)- 631(1990) | 676 | 625 |
107.1 | BB McCullum | Nzl | 5172 | 5696 | 90.8 | 2302(2005)-2731(2008) | 1677 | 1566 |
103.3 | Abdul Razzaq | Pak | 5079 | 6252 | 81.2 | 1828(2002)-2116(2004) | 1348 | 1305 |
102.4 | AB de Villiers | Saf | 6780 | 7128 | 95.1 | 2771(2008)-3347(2013) | 3131 | 3058 |
101.7 | SK Raina | Ind | 4823 | 5230 | 92.2 | 2962(2010)-3294(2012) | 1534 | 1508 |
100.9 | CH Gayle | Win | 8810 | 10482 | 84.0 | 2752(2008)-3380(2013) | 2152 | 2133 |
99.9 | MS Dhoni | Ind | 8127 | 9109 | 89.2 | 2201(2004)-2514(2007) | 1843 | 1845 |
99.6 | A Symonds | Aus | 5088 | 5504 | 92.4 | 2283(2005)-2685(2008) | 1903 | 1910 |
99.6 | MV Boucher | Saf | 4686 | 5528 | 84.8 | 2418(2006)-2841(2009) | 1280 | 1285 |
98.8 | IVA Richards | Win | 6721 | 7451 | 90.2 | 341(1985)- 556(1989) | 2064 | 2090 |
----- | ||||||||
60.1 | GR Marsh | Aus | 4357 | 7790 | 55.9 | 354(1986)- 550(1989) | 2333 | 3880 |
59.7 | KC Wessels | Saf | 3367 | 6088 | 55.3 | 174(1983)- 753(1992) | 2036 | 3411 |
56.2 | Mudassar Nazar | Pak | 2653 | 5130 | 51.7 | 151(1982)- 374(1986) | 1430 | 2544 |
This is the other component of ARpI. The leaders in the Strike Rate table should not surprise anyone. Shahid Afridi, with a 150-plus strike rate leads the table. But the more important batsman is Virender Sehwag, who scored 2778 runs at 125 at the peak of his career. That is something phenomenal. Sanath Jayasuriya scored nearly 2500 runs at 110. Adam Gilchrist, nearly 2400 runs at 110. Eleven batsmen scored more than a run a ball at the peak of their careers.
Now for the bowlers.
Wkts | Bowler | Team | Best streak | Years | WpM | Worst streak | Wkts | Best-Worst |
---|---|---|---|---|---|---|---|---|
136 | Saqlain Mushtaq | Pak | 1118(1996)-1353(1998) | 2.0 | 2.16 | 1482(1999)-2048(2003) | 85 | 160.0% |
129 | AA Donald | Saf | 1036(1996)-1468(1999) | 3.4 | 2.05 | 686(1991)-1122(1996) | 94 | 137.2% |
124 | B Lee | Aus | 1545(2000)-2013(2003) | 3.3 | 1.97 | 2021(2003)-2349(2006) | 100 | 124.0% |
120 | M Muralitharan | Slk | 1772(2001)-2264(2005) | 3.7 | 1.90 | 2351(2006)-2755(2008) | 67 | 179.1% |
119 | Waqar Younis | Pak | 625(1990)- 894(1994) | 3.9 | 1.89 | 1164(1997)-1720(2001) | 83 | 143.4% |
114 | SK Warne | Aus | 822(1993)-1155(1997) | 3.8 | 1.81 | 1488(1999)-1917(2002) | 80 | 142.5% |
114 | GD McGrath | Aus | 1365(1998)-1700(2001) | 2.4 | 1.81 | 2018(2003)-2479(2007) | 67 | 170.1% |
113 | M Ntini | Saf | 1886(2002)-2241(2005) | 2.6 | 1.79 | 2229(2005)-2592(2007) | 68 | 166.2% |
112 | SE Bond | Nzl | 1783(2002)-2526(2007) | 5.1 | 1.78 | 1949(2003)-2907(2009) | 100 | 112.0% |
112 | SCJ Broad | Eng | 2617(2007)-3047(2010) | 3.1 | 1.78 | 2411(2006)-2997(2010) | 93 | 120.4% |
111 | Shoaib Akhtar | Pak | 1365(1998)-1846(2002) | 3.6 | 1.76 | 2115(2004)-3063(2010) | 73 | 152.1% |
110 | D Gough | Eng | 962(1994)-1549(2000) | 5.1 | 1.75 | 1557(2000)-2164(2004) | 77 | 142.9% |
109 | Wasim Akram | Pak | 720(1992)- 929(1994) | 2.6 | 1.73 | 1365(1998)-1653(2000) | 73 | 149.3% |
108 | IK Pathan | Ind | 2077(2004)-2381(2006) | 2.4 | 1.71 | 2362(2006)-3294(2012) | 71 | 152.1% |
108 | CJ McDermott | Aus | 453(1987)- 830(1993) | 5.6 | 1.71 | 282(1985)- 548(1989) | 89 | 121.3% |
----- | ||||||||
39 | SR Tendulkar | Ind | 2095(2004)-2595(2007) | 3.4 | 0.62 | 2611(2007)-3143(2011) | 2 | 1950.0% |
37 | PA de Silva | Slk | 1004(1995)-1252(1997) | 2.1 | 0.59 | 661(1991)- 954(1994) | 9 | 411.1% |
31 | SC Ganguly | Ind | 1225(1997)-1428(1999) | 1.6 | 0.49 | 2087(2004)-2621(2007) | 6 | 516.7% |
Saqlain Mushtaq captured 136 wickets in the peak streak of 63 matches. Look at the top ten of this table. Makhaya Ntini is the only one who could be excused from an all-time great bowlers list. The top ten is also a nice mix of spinners and pace bowlers. Irfan Pathan's presence in the top 15 is indicative of what he could have achieved as a bowler until delusions of batting grandeur took care of his career. Two of these bowlers have captured more than two wickets per match.
Saqlain Mushtaq needed only two years to capture 136 wickets in 63 matches. Craig McDermott needed over five and half years.
Like Amla, Shane Bond has a maximum-minimum ratio of 110% possibly because of his short career. But the two bowlers to impress are Brett Lee and Bond, who captured 100 wickets even in their worst streak. That, especially for Lee, indicates a very high level of consistency.
Avge | Bowler | Team | Career wkts | C-Avge | Best streak | Wkts | Runs |
---|---|---|---|---|---|---|---|
14.79 | M Muralitharan | Slk | 534 | 23.08 | 1742(2001)-2150(2004) | 119 | 1760 |
15.38 | J Garner | Win | 146 | 18.85 | 126(1981)- 412(1987) | 106 | 1630 |
16.90 | Saqlain Mushtaq | Pak | 288 | 21.79 | 1118(1996)-1353(1998) | 136 | 2298 |
17.32 | RJ Hadlee | Nzl | 158 | 21.56 | 109(1981)- 372(1986) | 96 | 1663 |
17.57 | AA Donald | Saf | 272 | 21.79 | 1036(1996)-1468(1999) | 129 | 2267 |
18.18 | Waqar Younis | Pak | 416 | 23.85 | 588(1989)- 812(1993) | 118 | 2145 |
18.51 | GD McGrath | Aus | 381 | 22.02 | 1783(2002)-2228(2005) | 100 | 1851 |
18.92 | Wasim Akram | Pak | 502 | 23.53 | 720(1992)- 929(1994) | 109 | 2062 |
18.98 | SE Bond | Nzl | 147 | 20.88 | 1787(2002)-2557(2007) | 112 | 2126 |
19.17 | Shoaib Akhtar | Pak | 247 | 24.98 | 1410(1999)-1871(2002) | 109 | 2089 |
19.21 | BAW Mendis | Slk | 135 | 20.33 | 2718(2008)-3172(2011) | 87 | 1671 |
19.34 | Saeed Ajmal | Pak | 183 | 22.18 | 3043(2010)-3346(2013) | 88 | 1702 |
19.79 | MA Holding | Win | 142 | 21.37 | 61(1979)- 266(1984) | 96 | 1900 |
19.91 | CEL Ambrose | Win | 225 | 24.13 | 506(1988)- 721(1992) | 101 | 2011 |
19.97 | B Lee | Aus | 380 | 23.36 | 1940(2003)-2301(2005) | 118 | 2357 |
----- | |||||||
34.63 | TT Bresnan | Eng | 108 | 35.20 | 2878(2009)-3329(2013) | 82 | 2840 |
35.95 | P Utseya | Zim | 130 | 46.51 | 2653(2007)-3179(2011) | 63 | 2265 |
36.86 | G Wickramasinghe | Slk | 109 | 39.64 | 1006(1995)-1631(2000) | 58 | 2138 |
That guy Muralitharan again. To average below 15 in a stretch of 63 matches while capturing 119 wickets is indeed a wonderful performance. Finally we come to see one of the greatest ODI bowlers of all time: the gentle giant Joel Garner. His average is just over 15. Saqlain averaged just over 16. Then comes another giant, Richard Hadlee with 17.3. Allan Donald, Waqar Younis , Glenn McGrath, Wasim Akram, Bond and Shoaib Akhtar round off the top ten. What a collection of bowlers! Any four of these ten could complete our XI,, with a gentleman named Gilchrist separating the six batsmen and four bowlers. At the lower end of the top 15 we have the other greats of the '80s and '90s: Michael Holding and Curtly Ambrose.
RpO | Bowler | Team | Career RpO | Best streak | Balls | Runs |
---|---|---|---|---|---|---|
2.91 | J Garner | Win | 3.10 | 101(1980)- 364(1986) | 3358 | 1626 |
3.10 | RJ Hadlee | Nzl | 3.31 | 109(1981)- 372(1986) | 3214 | 1663 |
3.13 | M Muralitharan | Slk | 3.93 | 1688(2001)-2022(2003) | 3321 | 1734 |
3.21 | SM Pollock | Saf | 3.68 | 2288(2005)-2671(2008) | 3198 | 1711 |
3.26 | MD Marshall | Win | 3.54 | 210(1983)- 418(1987) | 3299 | 1792 |
3.28 | MA Holding | Win | 3.33 | 61(1979)- 266(1984) | 3474 | 1900 |
3.30 | CEL Ambrose | Win | 3.48 | 582(1989)- 840(1993) | 3419 | 1882 |
3.33 | EJ Chatfield | Nzl | 3.58 | 178(1983)- 454(1987) | 3272 | 1817 |
3.33 | Imran Khan | Pak | 3.90 | 66(1979)- 384(1986) | 2241 | 1244 |
3.50 | GD McGrath | Aus | 3.88 | 1728(2001)-2227(2005) | 3146 | 1837 |
3.51 | N Kapil Dev | Ind | 3.72 | 172(1983)- 401(1986) | 3179 | 1862 |
3.55 | Wasim Akram | Pak | 3.90 | 785(1992)-1059(1996) | 3409 | 2015 |
3.55 | Mohammad Hafeez | Pak | 4.06 | 3132(2011)-3427(2013) | 3049 | 1803 |
3.58 | DK Lillee | Aus | 3.58 | 2(1972)- 215(1983) | 3593 | 2145 |
3.61 | CA Walsh | Win | 3.83 | 376(1986)- 573(1989) | 3393 | 2043 |
----- | ||||||
5.40 | NLTC Perera | Slk | 5.47 | 3040(2010)-3485(2014) | 2443 | 2197 |
5.47 | Naved-ul-Hasan | Pak | 5.58 | 2174(2004)-2903(2009) | 2878 | 2623 |
5.62 | I Sharma | Ind | 5.72 | 2675(2008)-2918(2009) | 1710 | 1602 |
Garner stands supreme. He conceded fewer than 3 runs per over in the streak of 63 matches. Not surprising considering that he conceded 3.1 runs per over in his career. Hadlee follows next with 3.10. Muralitharan is in third place with 3.13. He is the only spinner in the top ten. The presence of Ewen Chatfield and Mohammad Hafeez may surprise a few but no surprise to see Ishant Sharma at the bottom of the table. He is the only specialist player to appear in the bottom three. How any team can sustain a bowler who concedes, right through his career, nearly 6 runs per over is beyond me. Don't forget that 5.62 is his best streak.
BpW | Bowler | Team | Career BpW | Best streak | Wkts | Balls |
---|---|---|---|---|---|---|
24.4 | Saqlain Mushtaq | Pak | 30.4 | 1118(1996)-1353(1998) | 136 | 3324 |
25.7 | AA Donald | Saf | 31.5 | 1036(1996)-1468(1999) | 129 | 3310 |
25.9 | Shoaib Akhtar | Pak | 31.4 | 1410(1999)-1871(2002) | 109 | 2819 |
26.0 | B Lee | Aus | 29.4 | 1545(2000)-2013(2003) | 124 | 3225 |
26.1 | Waqar Younis | Pak | 30.5 | 588(1989)- 812(1993) | 118 | 3085 |
26.9 | M Muralitharan | Slk | 35.2 | 2468(2006)-2803(2009) | 75 | 2016 |
27.0 | SE Bond | Nzl | 29.2 | 1787(2002)-2557(2007) | 112 | 3020 |
27.0 | BAW Mendis | Slk | 27.2 | 2718(2008)-3172(2011) | 87 | 2347 |
27.3 | M Ntini | Saf | 32.7 | 2035(2003)-2438(2006) | 101 | 2756 |
27.7 | SR Watson | Aus | 37.2 | 2257(2005)-2945(2010) | 82 | 2270 |
27.8 | SCJ Broad | Eng | 32.6 | 2622(2007)-3165(2011) | 111 | 3088 |
27.8 | SL Malinga | Slk | 31.3 | 2884(2009)-3255(2012) | 101 | 2803 |
27.9 | NLTC Perera | Slk | 29.0 | 2988(2010)-3470(2014) | 82 | 2287 |
28.1 | AB Agarkar | Ind | 32.9 | 1788(2002)-2291(2005) | 101 | 2838 |
28.2 | KD Mills | Nzl | 33.9 | 2430(2006)-3070(2010) | 103 | 2906 |
----- | ||||||
49.0 | PAJ DeFreitas | Eng | 49.7 | 418(1987)- 726(1992) | 73 | 3579 |
50.1 | P Utseya | Zim | 64.2 | 2653(2007)-3179(2011) | 63 | 3158 |
50.2 | RA Harper | Win | 51.8 | 412(1987)-1086(1996) | 60 | 3012 |
Saqlain is the king when it comes to bowling strike rate. Fewer than 25 balls per wicket. In a collection dominated by pace bowlers, Muralitharan, not surprisingly, and Ajantha Mendis, unexpectedly, are the spinners at the top. Ajit Agarkar is an unexpected entry, although his ODI wicket-taking skills were legendary. He created a few records, if I remember correctly. Kyle Mills and Ntini are two other surprise entries.
Win % | Player | Team | Best streak | Years | Matches | Wins |
---|---|---|---|---|---|---|
83.9% | DR Martyn | Aus | 1936(2003)-2234(2005) | 2.1 | 62 | 52 |
83.9% | ML Hayden | Aus | 1870(2002)-2176(2004) | 2.0 | 62 | 52 |
83.9% | G Kirsten | Saf | 1013(1995)-1332(1998) | 2.6 | 62 | 52 |
83.9% | A Symonds | Aus | 1670(2001)-2102(2004) | 3.1 | 62 | 52 |
82.3% | RT Ponting | Aus | 1877(2002)-2180(2004) | 2.0 | 62 | 51 |
82.3% | MG Bevan | Aus | 1799(2002)-2106(2004) | 2.1 | 62 | 51 |
82.3% | GD McGrath | Aus | 1667(2001)-2019(2003) | 2.4 | 62 | 51 |
80.6% | AC Gilchrist | Aus | 1799(2002)-2102(2004) | 2.1 | 62 | 50 |
80.6% | DS Lehmann | Aus | 1446(1999)-2176(2004) | 5.3 | 62 | 50 |
80.6% | WJ Cronje | Saf | 977(1995)-1283(1998) | 2.9 | 62 | 50 |
80.6% | JN Rhodes | Saf | 1036(1996)-1332(1998) | 2.4 | 62 | 50 |
80.6% | AL Logie | Win | 129(1981)- 427(1987) | 5.1 | 62 | 50 |
80.6% | DL Haynes | Win | 93(1980)- 296(1985) | 4.2 | 62 | 50 |
80.6% | MA Holding | Win | 129(1981)- 327(1985) | 3.3 | 62 | 50 |
80.6% | IVA Richards | Win | 22(1975)- 236(1984) | 8.6 | 62 | 50 |
----- | ||||||
33.9% | KC Wessels | Aus/Saf | 289(1985)- 901(1994) | 9.2 | 62 | 21 |
32.3% | C Pringle | Nzl | 636(1990)- 992(1995) | 4.4 | 62 | 20 |
27.4% | T Taibu | Zim | 2614(2007)-3209(2011) | 4.2 | 62 | 17 |
For ODIs I have created this special analysis. This lists the win percentage in the streak of 62 matches. This is a combined table for batsmen and bowlers. It is dominated by the Australians, who take eight of the top ten places. These are all first amongst equals. It is just a combination of matches which has put Damien Martyn and others at the top. Let us look at the Australians as a whole. These eight Australians have win-percentage values exceeding 80%.
There are three South Africans who average around the 80% mark. Then come four West Indians of the 1980s, who all had win percentage above 80%. No other player finds a place in the top 15. It is interesting to note that the first 32 players in this table are from these three countries. The first player from outside these three is Tillakaratne Dilshan, who has a winning percentage of 74.2%. He is followed by Zaheer Khan and Muralitharan with 72.6%.
The complete set of nine tables can be accessed by clicking HERE. This is only a text file. However it is a properly formatted one. So it can be exported to Excel in less time than it takes Daniel Vettori to bowl a maiden over. I would have said Ravindra Jadeja, but have to allow for MS Dhoni's three fielding changes during the over!
Amused by the recent exchanges in the comments section of the previous articles, Milind has come out with his own insight on sports following, in general and cricket following, in particular. A lot to be gained by perusing the document. Please click HERE to download/view the document.
Amla is the star in this analysis, closely followed by de Villiers. His high average makes many followers to group him with the openers of the past or the most recent openers like Alastair Cook, Ganguly, Matthew Hayden and others. They are way off the mark. Allow me to present ten batsmen.
Dhoni, Andrew Flintoff, Kevin Pietersen, Tendulkar, Chris Gayle, Graeme Smith, Saeed Anwar, Ponting, Lara and Hayden.
What is common between them?
It is amazing but true - Amla's career strike rate of 89.3 is higher than those of this illustrious ten. Food for thought indeed. de Villiers, with a career strike rate of 95.2, is ahead of Kapil Dev, Richards, Andrew Symonds et al. Only Afridi, Sehwag and Gilchrist have better strike rates than de Villiers.An analysis using a comprehensive methodology that identifies the best teams and their dominant periods in Test history
This is one of the most significant analyses I have ever done. It is a logical follow-up to the two earlier articles I had done on team streaks. I had used fixed periods in those articles and had mentioned that I would also a dynamic team performance analysis, incorporating floating number of Tests, strength of opposition, recent form and match location. After this article, all suppositions and conjectures should come to an end. The greatest period any Test team has gone through will be identified.
A few important points:
- The article is current up to and including West Indies' comfortable win over Bangladesh in St Vincent.
- Neutral matches are treated as away matches for both teams. This is the correct treatment for these 24 matches.
- Match# 1768 is handled only from the Australian point of view. No adjustments. ICC is treated as a middle-level team.
This is a very difficult article to present and explain. I do not want to give tens of paragraphs of explanations and lose the readers at an early stage of the article. Hence I will provide a basic description of the process, then explain everything about a single Test, and conclude with the important tables. For the first time ever, I have uploaded a detailed FAQs document in which I have answered a number of anticipated reader queries.
A brief explanation of the analysis workings
- For each Test, I will determine the team strength value for the two teams. This will be based on the performance of the concerned team over the past five years. The performances are weighted through a geometric decay basis to ensure that the recent matches carry the highest weight. This weighted average is called FYRAP (Five-Year Rolling Average Performance).
- Based on the Team Strength of the opposition team (FYRAP), TSF (Team Strength Factor) is determined. This varies between 0.80 and 1.20.
- Based on the other team's results during the immediately preceding one year, with a special tweak for the results in the anchor location (current Test's location-Home or Away), the LRFF (Location Recent Form Factor) is determined. This too varies between 0.80 and 1.20.
- The Team performance points are adjusted by TSF and LRFF for each Test. These calculations are carried out for all the 2100+ Tests. I would estimate that in a 198x PC-XT, this process would have taken the duration of a Test: maybe even the Durban Test of 1939. Now I get the results in a minute or so.
- Then the performance of a team is measured over a minimum of 30 Tests played within a maximum period of ten years. For each Test, the best average value is determined. A separate section under the FAQs area explains the reasons behind 30 Tests and ten years.
- The average of the value over 30-plus Tests is called RAAPP (Rolling Average of Adjusted Performance Points). This determines the team performance over the period identified.
A self-explanatory schematic of the complex system is presented below. No explanations are needed.
Everything about Test #1729
All readers should make sure that the four terms are clearly understood. FYRAP is a measure of the Team strength over the previous five years, excluding the current Test. TSF and LRFF are adjustments for the current match. RAAPP represents the best performance period, from the current Test onwards.
Australia and Pakistan played Test #1729 starting on December 26, 2004 at MCG. The complicated analysis forming the base of this article will be explained through this single Test. Every number associated with this Test will be explained. Those who want to know how this analysis is done should first go through it and understand this match. Maybe by reading this section a few times. Please do not rush with questions without going through this explanation. And if you do not want to go through the explanation, then please accept the findings of this analysis.
What is so special about 1729? It is one of my favourite numbers. It is the Ramanujam-Hardy number. The number of the taxi that Hardy took to see an ailing Ramanujam was 1729 and Hardy expressed the view that this was an unremarkable number. Ramanujam instantly responded with: "No, it is a very interesting number. It is the smallest number expressible as the sum of two (positive) cubes in two different ways." namely 1729 = 1^3 + 12^3 = 9^3 + 10^3.
First, I will explain the calculation of respective Team Strength Factors, using FYRAP values.
Australia played 59 Test matches during the five years preceding this match. The geometric decay value for 59, to reach a closing weight of 0.5, is 0.9883205 (in other words 0.9883205^59=0.5). Each of the 59 matches Australia played during these five years is geometrically decayed by this value, so that the weight at the end of 59 matches is exactly 0.5.
Pakistan played 44 Test matches during the five years preceding this match. The geometric decay value for 44, to reach a closing weight of 0.5, is 0.9843705 (in other words 0.9843705^44=0.5). Each of the 44 matches Pakistan played during these five years is decayed by this value so that the weight at the end of 44 matches is exactly 0.5. Please download and go through the document in which complete details are given of this match from the TSF point of view.
So for Australia, in match #1729, the opposition FYRAP is 34.441 and for Pakistan, the opposition FYRAP is 45.072. Note that this is done for every match. These numbers, per se, are not indicative of anything other than relative values since the actual performance points are decayed as the time is moved back. The TSF is determined for each team based on this FYRAP value. The range of the FYRAP is 6.8 to 49.2.
The TSF (Team Strength Factor) for Australia is 1.036 (0.80 + 0.40*(34.41-5.0)/50.0)). The TSF for Pakistan is 1.121 (0.80 + 0.40*(45.07-5.0)/50.0)).
Now, for the Location and Recent Form Factor; These two indices are intertwined and are determined through a complex process. The combined factor is called LRFF. The key limit is that only the Tests played by the teams during the exact preceding year are considered. This is to ensure that only the current form and recent matches are incorporated.
First let us fix the anchor locations for the current Test, which are Australia-Home and Pakistan-Away.
Let us consider Australia. Pakistan played a total of seven Tests during the preceding year. The results are LWLLWLW. However the anchor location for Pakistan is away. The previous Test was played away (anchor). The preceding five Tests were played at home. The seventh Test was played away (anchor). Hence this string is modified to L w l l w l W where upper case indicates an away match (anchor) and lower case indicates a match at home (non-anchor). A higher weight is given to matches in anchor locations. Pakistan's performance during these seven Tests is 43.8% (2*2 + 4*0 + 1*3)/(5*2 + 2*3). Since they played only seven Tests the factor range is narrowed. This is 0.85 + 0.3 * 0.438 which works out to 0.981. So Australia's LRFF is 0.981.
Now let us consider Pakistan. Australia played a total of 14 Tests during the preceding year. The results are WWWLWDWDWWWWDW. However the anchor location for Australia is home. Australia played seven Tests away and seven at home. Hence this string is modified to W W W l w d w D W w w w D W where upper case indicates a home match (anchor) and lower case indicates a match away (non-anchor). A higher weight is given to matches in anchor locations. Australia's performance during these 14 Tests is 82.9% (5*3 + 5*2 + 2*1.5 + 1*1 + 1*0)/(7*3 + 7*2). Since they played more than ten Tests the factor range is complete. This is 0.80 + 0.4 * 0.829 which works out to 1.131. So Pakistan's LRFF is 1.131.
So the final adjustment factor for Australia is 1.016 (1.036*0.981). For Pakistan the final adjustment factor is 1.268 (1.121*1.131). Australia won this Test by nine wickets and secured 71.181 performance points. This is adjusted to 72.33 (71.181*1.016). Pakistan secured 28.819 performance points and is adjusted to 36.54 (28.819*1.268).
Australia faced an above average Pakistan side but coming in with a slightly below average location-recent form. They gained slightly. Pakistan faced a rampant Australia with a strong home (anchor) record and a very strong home (anchor) record and gained heavily.
This calculation is done for each of the following 30-100 Tests, played within ten years and the average arrived at. The highest value for Australia is for 30 Tests between 1729 to 1855 (2008) and works out to 66.138. The highest value for Pakistan is for 31 Tests 1729 to 2098 (2013) and works out to 51.112. It would be easier for lower RAAPP values to be applicable for more Tests rather than higher values since it is tough to maintain higher value average sequences.
Well, my head reels. I am not sure about the status of the readers' heads.
Tables
A careful perusal of the tables indicates that the teams are divided into three groups. The first group consists of teams which have crossed a RAAPP value of 60.0 at some time in their history. Four teams qualify: Australia, West Indies, England and South Africa. No prizes for guessing this. The second group consists of teams which have crossed 50.0, but never reached 60.0. Again four teams comprise this group: Sri Lanka, India, Pakistan and New Zealand, which just about made it. The remaining two teams complete the roster.I will present separate tables for each group.
Presentation of the data presents its own challenges. There are 152 Test in which Australia's RAAPP values exceed 60.0. England has 44, South Africa 33 and West Indies 32. However many of these are overlapping and I have looked at the table every which way to locate all non-overlapping instances of RAAPP values exceeding 60. Australia has 4, England 3, South Africa 2 and West Indies 2. These 11 performance streaks are, inarguably, the best ever and will form my first table. In addition, the long streaks are identified and presented.
RAAPP | Team | First Test | Last Test | Weeks | Tests |
---|---|---|---|---|---|
69.261 | Australia | 1463 (1999) | 1629 (2002) | 162 | 38 |
67.042 | West Indies | 979 (1984) | 1072 (1987) | 158 | 30 |
67.012 | Australia | 1721 (2004) | 1855 (2008) | 161 | 33 |
64.693 | England | 392 (1954) | 457 (1958) | 187 | 30 |
63.085 | Australia | 198 (1930) | 259 (1937) | 340 | 31 |
62.863 | England | 1944 (2010) | 2044 (2012) | 125 | 30 |
62.297 | South Africa | 1985 (2010) | 2129 (2014) | 186 | 30 |
61.567 | Australia | 275 (1946) | 347 (1952) | 303 | 31 |
61.432 | England | 9 (1882) | 38 (1892) | 497 | 30 |
61.339 | South Africa | 1830 (2007) | 1951 (2010) | 158 | 30 |
61.268 | West Indies | 461 (1958) | 588 (1965) | 329 | 30 |
62.023 | Australia | 1372 (1997) | 1629 (2002) | 281 | 66 |
60.001 | South Africa | 1871 (2008) | 2111 (2014) | 298 | 51 |
59.463 | England | 346 (1952) | 457 (1958) | 340 | 51 |
57.966 | West Indies | 883 (1980) | 1056 (1986) | 327 | 50 |
Australia's 38-Test streak, bookended by the Harare Test in 1999 against Zimbabwe and Ashes Test in Perth in 2002, had an average RAAPP value of 69.26. West Indies averaged 67.04, a significant 2 points behind, in 1984-1987. This golden period started with the Georgetown Test against Australia, which was a drawn match almost won by West Indies. The last Test in this run was the close loss to New Zealand in Christchurch in 1987. England's best sequence was during the wonderful Hutton-May-Compton-Trueman-Statham days. They averaged a very respectable 64.69 points. South Africa had their two best streaks during the 2000s: the first one between 2010 and 2014 and the second one between 2007 and 2010.
Australia had a way-out 66-Test run over six years during which they averaged 62.02 points. The other three teams had their best sequences around the 60 and sub-60 mark. South Africa's was a third decimal point above 60.
Now we come to the middle-level teams. New Zealand have only two streaks with RAAPP values above 50. India have 130, Pakistan 100 and Sri Lanka 109. However Sri Lanka have the pride of place in this group since they have reached the highest RAAPP value of 58.55. India follow next, with a highest value 57.86 and then Pakistan with 53.15. Looking for non-overlapping and long streaks, I have selected two from Sri Lanka, two from India, two from Pakistan and one from New Zealand.
RAAPP | Team | First Test | Last Test | Weeks | Tests |
---|---|---|---|---|---|
58.554 | Sri Lanka | 1530 (2001) | 1699 (2004) | 168 | 33 |
57.864 | India | 1884 (2008) | 1997 (2011) | 150 | 30 |
55.384 | Sri Lanka | 1757 (2005) | 1886 (2008) | 158 | 30 |
53.153 | Pakistan | 1945 (2010) | 2098 (2013) | 197 | 32 |
52.881 | Pakistan | 1265 (1994) | 1391 (1997) | 173 | 31 |
52.304 | India | 1999 (2011) | 2130 (2014) | 158 | 30 |
50.409 | New Zealand | 950 (1983) | 1050 (1986) | 178 | 30 |
53.974 | India | 1697 (2004) | 1952 (2010) | 304 | 64 |
53.378 | Sri Lanka | 1585 (2002) | 1839 (2007) | 286 | 50 |
50.755 | Pakistan | 1754 (2005) | 2034 (2012) | 346 | 56 |
48.279 | New Zealand | 1478 (2000) | 1790 (2006) | 323 | 51 |
Sri Lanka achieved a very high average of 58.55 between 2001 and 2004. Inspired by Muttiah Muralitharan and supported by Kumar Sangakkara, Mahela Jayawardene, Sanath Jayasuriya and Aravinda D'Silva to start with. They also had another great sequence between 2005 and 2008. India's sequence between 2008 and 2011 was very close to Sri Lanka's run a few years earlier. Unfortunately, this was cut short by the England debacle. India have repeated this, albeit at a lower level, mostly riding on excellent home form. One of Pakistan's two sequences is recent and the other during the 1994-1997 period.
India had a run of 53.97 over 64 Tests. Sri Lanka were able to get near this value, averaging 53.34 in 50 Tests during the 2000s. Pakistan's sequence is around the 50-mark and New Zealand's, just below the 50-mark. Both are over 50 Tests.
Let me close this with brief comments on the two recent Test teams. Zimbabwe has a 30-Test streak, from Test #1378 (1997) to 1549 (2001) with RAAPP value of 40.03: the only period in which they exceeded 40.0. They had five wins in these 30 Tests, including three against the top Test-playing teams. Bangladesh has a 30-Test streak, from Test #1864 (2008) to 2099 (2013) with RAAPP value of 37.572.
Conclusions
I am not saying that all readers should accept these tables as the final ones. They have every right to plunk for a second or third placed streak as the best but only as a heart-driven decision since all relevant factors such as match locations, opposition strength, recent form and number of matches have been taken into account.
What do we conclude?
First let us summarise the middle-level teams. Sri Lanka's performances are to be admired and appreciated. Their 2000s performance gives them the top billing in this group. India have also been very good in the 2000s. India were the only team to pose any threat to the Australian dominance during the 2000s. However the very poor away performances have let India down. Pakistan have been quite good. In fact I was surprised to see that Pakistan did not reach 55.0. My feeling is that they have been inconsistent and have not sustained their top-level performances for seven to eight series at a stretch. New Zealand have just about managed to make this group.
There is no doubt that Australia, for 38 Tests between 1999 and 2002, were the best Team that ever played Test cricket. All relevant factors have been taken into consideration. Opposition strength, recent results, recent form, location, number of Tests et al. They were truly outstanding and posted a result sequence of 31 wins, three draws and four losses (all away). Let us not forget that this was achieved over 38 Tests. All three draws occurred in a home series against New Zealand. All the four losses were potential wins: two well-known against India in Kolkata and Chennai, one-off against England in Leeds and South Africa at Kingsmead, the normal dead-rubber matches.
Let us look at the second placed sequence of West Indies. During 30 Tests between 1984 and 1987, West Indies were magnificent. They had a results summary of 21 wins, seven draws and two losses. The two losses were to Pakistan, that 53-run-all out disaster in Faisalabad and New Zealand's five-wicket win ainChristchurch, inspired by Hadlee. Maybe one could say these were the days in which a draw could be planned and achieved.
The third best is another recent run of Tests by Australia. However Australian performance in 100 Tests between 1999 and 2008 is something for the Gods. This sequence started with the Lara-inspired loss at Barbados and ended with the 2008 New Year Test against India. The summary was 75 wins, 13 draws and 12 losses. And some of the losses were because Australia went for wins. To me this sequence is probably the most significant of the many Australian achievements. They were truly the most dominant team of all time. For the record this 100-Test streak has an outstanding RAAPP value of 63.066. It is just that there is a better streak of 65.304 for the 43 Tests starting with the Barbados Test.
Data Files: I have uploaded four important files. The first is a special file for Test #1729. It lists all the matches which were played during the five years before this specific match. The second contains the Performance points and adjusted Performance points for all matches played by all the teams, in Team order. The second contains the Performance points and adjusted Performance points for all matches played by all the teams, in Test order. These two are huge files. The fourth is the most important document. It contains the RAAPP values for all the teams, ordered by the RAAPP value for each team.
This is not an article that can be understood by perusing at surface level. It would take multiple readings and downloading and understanding all the documents, especially the FAQs document. Please take your time. Alternatively, if the reader has confidence in my work, he can go straight to the important Tpa_All.txt file.
Please download the zip file containing the four aforementioned files and the FAQs document by clicking HERE.
Some FAQs on the analysis: First time ever I have anticipated some questions from readers and attempted to answer those. Initially I had got these FAQs as part of the main article. However when the number of FAQs exceeded 20, I decided I would create a MS Word document and allow interested readers to download the document and peruse at leisure. Please do so by clicking HERE.
Stats review of the England-India Test series, including a look at sequences by teams that were as bad as, or worse than, India's five-innings streak of sub-200 scores in the recently concluded Test series
I had initially envisaged doing an exhaustive head-to-head analysis for the England-India Tests series. I have changed the emphasis of the article since Rajesh's complete statistical coverage of the series contains quite a few head-to-head numbers. I will still do a single table on what are the significant head-to-head confrontations. This will bring into focus where England gained and India lost.
Initially I will do a thorough analysis of the disastrous second half of the series, checking for some precedence during the many Tests which have been played so far.
By now everyone knows that India were dismissed for sub-200 totals in their last five innings. And some invisible forces made India go through the score of 66 for 6 in the last four innings. Henceforth India will not get shivers at 111 but at 66 too! My off-the-cuff take was that many teams would have gone through such a poor patch as five consecutive sub-200 innings.
First I considered only India matches. The two rules were simple. Consider all matches: home and away. Any innings in which fewer than ten wickets fell would break the sequence.
With the sorry state of Indian cricket during the first 25-30 years I expected at least two or three such sequences other than the current disaster achieved by a much-hyped team. Lo and behold! There was one such occurrence. Even though I knew that my program, inanimate though it is, would be angry at me, I was not sure about this and checked the entire lot of 483 matches. No, my trusted programming skills had not deserted me. There was only one other sequence: During the equally disastrous 1959 tour of England.
I was so fascinated by these two sequences occurring over half a century apart by two diametrically opposite teams that I decided to do a complete study. Mr Ravi Shastri would be well-advised to go through this article to know the tough task on hand: in Test matches. Let us now look at the comparisons in a table form.
Description | India 2014 | India 1959 | Comments | |
---|---|---|---|---|
Runs | 733 | 800 | 1959 slightly better | |
Avge Runs per innings | 146.6 | 160.0 | 1959 slightly better | |
Overs | 246 | 378 | 1959 much better | |
Avge Overs per innings | 49.2 | 76.6 | 2014 disaster | |
Wickets | 50 | 50 | ||
Avge RpW | 14.6 | 16.0 | 1959 slightly better | |
Avge BpW | 29.4 | 45.4 | 2014 disaster | |
Avge Opening partnership | 13.8 | 13.2 | Approximately same | |
Sum of 1-5 bat scores | 288 | 539 | 1959 way better | |
Avge of 1-5 batsmen (25) | 11.7 | 21.6 | 2014 disaster | |
Sum of 6-11 bat scores | 396 | 232 | ||
Avge of 6-11 batsmen (25) | 15.8 | 9.3 | 2014 tail wagged | |
50 Partnerships | 4 | 4 | Same | |
Fifties | 3 | 2 | Similar | |
Team Perf Points | 72 - 228 | 73 - 227 | Same | |
Span of 5 Tests | 41 | 80 | 1959-time for FC matches |
The damning indictment of the current Indian team is there for everyone to see. It is quite possible that the 1959 team, during the entire year 1959, earned less than what Virat Kohli earns during the course of a single Test match. However, there is no escape from the following revealing facts.
- The 1959 team scored more runs during the five innings: Consequently averaged more runs per innings (160.0 against 146.6).
- Thereby the average RpW for the 1959 team was slightly better (16.0 against 14.6).
- The 1959 team had great defensive skills and lasted many more overs: Consequently averaged more overs per innings (76.6 against 49.2).
- In other words, the 1959 team gave their wickets away much more dearly: An average of 45.4 balls per wicket as against the 2014 team's 29.4.
- The aggregate of the 1-5 batsmen of the 1959 team was nearly double that of the 2014 team. The 1-5 batsmen of 1959 averaged 21.6 against 11.7.
- The two teams were comparable in the areas of average opening partnerships, number of 50 partnerships, number of 50 scores and were almost dead-heated on the Team Performance points measure.
- There was only one consolation for the 2014 team. Their late-order batsmen played much better. Else we might have seen five sub-100 scores. But then MS Dhoni was at No. 6. The figures would be different if 1-6 was taken but what does it matter? 1-5 is expected to be the core of batting.
- There was one big difference. The five Tests in 1959 were spread over 80 days. This time the lapsed period was halved to 40 days. The 1959 team played quite a few first-class matches in between Tests. But what prevented Dhoni, the cricket Czar of India, from putting his foot down and insisting on a four-Test series and a couple of first-class games sandwiched in between?
Let us look at the personnel involved. Pankaj Roy, Arvind Apte, Jayasinghrao Ghorpade, Chandu Borde, Polly Umrigar, Datta Gaekwad, Naren Tamhane compared to M Vijay, Shikhar Dhawan, Kohli, Cheteshwar Pujara, Ajinkya Rahane, Dhoni, R Ashwin. Struggling against pace bowling: both teams. Lack of experience: in both teams; First-class experience: quite high with the 1959 teams, very little with the current IPL-bred 2014 players. Where did/do the two teams go after the series? The 1959 team went back to a full first-class season and then a home series against a tough Australia team. The current lot through an ODI series to Champions League T20 and a home Tests series against a weak team. And then Australia beckon.
What about the bowlers? Fred Trueman, Brian Statham, Alan Moss and Harold Rhodes against James Anderson, Stuart Broad, Chris Jordan and Chris Woakes. Only a fool would say that the 1959 attack is not comparable to the 2014 attack. In both cases, two among the greatest England produced, supported by two average bowlers.
Okay, enough is enough. But there are other teams. Some of them could have got quite a few five-innings sequence of sub-200 scores. First, let me explain why I had to exclude the 134 Tests before 1920. Scores under 200 were the order of the day and many of these were match-winning ones. Two forty-four of the 484 innings were sub-200 ones. So, including these Tests would have given a completely distorted picture.
How many such sequences should we expect when we consider the 1900-plus Tests from 1921 onwards? There are already two to India's account. Maybe there are another ten more, because of the very poor New Zealand, West Indian and Bangladesh teams at different times. Maybe a couple from the other teams also. Even one from a strong team like Australia.
Well, I have news for all. There are only four such sequences. And half the teams have never suffered the ignominy of such a sequence. Let us see the listing of such teams.
Teams with five or more sub-200 innings scores in consecutive innings
India-1959 (160.0): 157, 168, 165, 161, 149. India-2014 (146.6): 178, 152, 161, 168, 94. New Zealand-1958 ( 91.3): 94, 137, 47, 74, 67, 129. West Indies-1931 (124.0): 107, 90, 193, 148, 99, 107. Bangladesh-2001 (153.8): 108, 132, 135, 160, 152, 148, 148, 161, 184, 164, 184, 170. Australia-1979 (157.3): 111, 164, 160, 198, 143, 168.
We have already seen the two Indian sequences. New Zealand, during 1958, had a six-innings sequence, which was the worst in Test history. They had four sub-100 scores and averaged only 91 runs per innings. Right at the beginning of their Test days, West Indies had a six-innings sequence, averaging 124. Bangladesh, during the early years, had a 12-innings, yes, you read it right, streak of sub-200 scores at an average of 154. The point is that these were all decent sub-200 scores. Finally Australia, had a miserable six-innings sequence at an average of 158. They were shattered by the Packer defections and were a disorganised lot.
Needless to say that all these matches were lost by the teams concerned. And to close this topic, let me confirm that England, South Africa, Pakistan, Sri Lanka and Zimbabwe had no sub-200 sequences that were five innings long.
Now let me look at the head-to-head confrontations in the England-India series.
Bowler | Team | Batsman | Balls | Runs | Wickets | Average | BpW | Strike Rate |
---|---|---|---|---|---|---|---|---|
England dominant | ||||||||
RA Jadeja | Ind | GS Ballance | 215 | 83 | 1 | 83.0 | 215.0 | 38.6 |
B Kumar | Ind | GS Ballance | 198 | 105 | 1 | 105.0 | 198.0 | 53.0 |
I Sharma | Ind | JE Root | 167 | 112 | 1 | 112.0 | 167.0 | 67.1 |
B Kumar | Ind | AN Cook | 156 | 67 | 1 | 67.0 | 156.0 | 42.9 |
B Kumar | Ind | JE Root | 143 | 83 | 1 | 83.0 | 143.0 | 58.0 |
STR Binny | Ind | GS Ballance | 60 | 64 | 0 | 64.0 | 60.0 | 106.7 |
JM Anderson | Eng | V Kohli | 50 | 19 | 4 | 4.8 | 12.5 | 38.0 |
SCJ Broad | Eng | CA Pujara | 69 | 20 | 3 | 6.7 | 23.0 | 29.0 |
JM Anderson | Eng | S Dhawan | 78 | 32 | 3 | 10.7 | 26.0 | 41.0 |
SCJ Broad | Eng | AM Rahane | 139 | 41 | 3 | 13.7 | 46.3 | 29.5 |
Equal contests | ||||||||
JM Anderson | Eng | M Vijay | 337 | 106 | 4 | 26.5 | 84.2 | 31.5 |
India dominant | ||||||||
JM Anderson | Eng | MS Dhoni | 187 | 96 | 2 | 48.0 | 93.5 | 51.3 |
SCJ Broad | Eng | M Vijay | 266 | 88 | 1 | 88.0 | 266.0 | 33.1 |
LE Plunkett | Eng | M Vijay | 182 | 63 | 1 | 63.0 | 182.0 | 34.6 |
I Sharma | Ind | IR Bell | 40 | 19 | 3 | 6.3 | 13.3 | 47.5 |
B Kumar | Ind | IR Bell | 106 | 46 | 3 | 15.3 | 35.3 | 43.4 |
I have decided to highlight the significant H-t-H confrontations only. Gary Ballance floored Ravindra Jadeja. He faced over 250 balls, played carefully and lost a wicket just once. Ballance also handled Bhuvneshwar Kumar very well. Nearly 200 balls, over 100 runs and a single dismissal. Joe Root handled Ishant Sharma the best of all English batsmen: 167 balls, an excellent strike rate and a single dismissal. Alastair Cook was quiet against Bhuvneshwar but gave England the start they needed by being out just once in over 25 overs. Even though Stuart Binny was a second-line bowler, Ballance took him apart and finished with the only 50-plus ball confrontation with a better than a run-a-ball strike rate.
Anderson toyed with Kohli. Fifty balls and four dismissals meant Kohli's innings rarely went beyond 40/50 balls. Pujara was slightly better than Kohli against Anderson but still gave away his wicket every 23 balls. If Anderson took care of the two best Indian batsmen, Broad took care of the second level quite well. He dismissed Dhawan once every 26 balls and Rahane once every 43 balls.
The English supremacy can finally be traced back to these confrontations: Anderson, Broad and Root against Kohli, Pujara, Dhawan, Rahane and Sharma.
Vijay handled Anderson reasonably well. One could call that contest a draw. It took Anderson 84 balls to dismiss Vijay but contained him well and the average was only 26.
Now we come to the rare contests which were won by India. M Vijay mastered both Broad and Liam Plunkett very well, especially his handling of Broad: 266 balls and a single wicket. Against Plunkett it was 182 balls and a single wicket. These were the contests that kept India in the series during the first two Tests. Dhoni handled Anderson quite well too: two wickets in 187 balls tell the story.
Ian Bell was a disaster against both Ishant Sharma and Bhuvneshwar. Ishant needed only just over two overs to dismiss Bell and Bhuvneshwar needed a few more balls: once every six overs. Bell's two good innings were after Ishant departed.
One final comment. The Lord's win was a great one, no doubt. However, most people forget that the Indian bowlers were clueless for all but one ball during the first session of the last day. If Moeen Ali had not been dismissed, there was a good chance (no less than 50-50) that England would have won the match. Who knows what would have happened after lunch? Even at the end it was only a 55-45 Test in favour of India, as shown by the performance analysis summary for the series. The final margin could easily have been 4-0 instead of 3-1. And let me say that the analysis presented in this article will not be diluted or invalidated even if India does well in the ODI series. Scores of 300-plus in one format do not make up for scores of sub-200 in another format.
(An aside: With AB de Villiers' extraordinary innings against Australia on August 27, there are four current ODI batsmen who are averaging in excess of 50. And these are four of the five batsmen who have achieved career averages over 50.)
England IndiaMy next article will be a landmark analysis and has been asked for over the past few weeks by many readers. It will incorporate dynamic team performance analysis, including floating number of Tests, opposition team strengths, location performances and recent form. After that article, all suppositions and conjectures should come to an end. The greatest period any Test team has gone through will be identified. It may very well be a 4-1 outsider: who knows?
Nottingham 39.4 34.5 (England had the better of the draw) Lord's 44.6 55.4 (95-run win for India) Southampton 63.8 36.2 (266-run win for England) Manchester 77.6 22.4 (Big innings win for England) Oval 86.2 13.8 (Huge win: by 3 innings and 2 runs) 311.6 162.3 (England, by a few miles)
Incidentally the 1959 series went 351 - 149 in England's favour.
A look at Test teams across the years, measuring the peaks of each team, and the highest peak across teams
In this follow-up article I will analyse the teams' Performance points and Result points over the many periods. This will let us get a clear handle on the best teams across the years. This is the more important analysis as evidenced by the fact that most of the comments dwelt on the teams, rather than the individuals.
The team performances will be measured through the Team performance index (which is a contribution index developed jointly by Milind and me and was used extensively in the article on Test series) and the Results index, which has been specially developed by me for this article and will be the basis for many a future analysis. The features of the Team performance index is summarised in a Word document, which can be accessed HERE. Since there is a graph embedded in the document, you can download the same and study at leisure.
The Test performance index is the most composite measure reflecting the performance of the team in the match, taking into account every aspect of the match. As such it is an excellent measure of the overall performance of teams. The Result index, on the other hand, is a little more contextual in that the actual result and the match location are considered. However a five-run win is the same as an innings-and-200-runs win. But it is an equally valuable measure. I will do both and present the tables.
Just to give the readers an idea of the Team Performance index, I have given below the Team Performance index values for England and India in the on-going series. India, with their 150-minute non-performance, allowed me to add the Oval Test numbers.
England India
As I did this, I realised that this is not a peer analysis in that the comparisons to the period values do not make any sense. This has to be a direct analysis of the values. These analyses cover all matches up to and including Test #2135, the Harare match between the two African neighbours.
Team Performance Analysis
First let me look at the Test performance index measure since I can straightaway go into the tables. All explanations will be available in the downloadable document.
Perf Pts | 1877-1914 | 1920-1939 | 1946-1959 | 1960-1969 | 1970-1979 | 1980-1989 | 1990-1999 | 2000-2006 | 2007-2014 | All |
---|---|---|---|---|---|---|---|---|---|---|
Australia | 46.16(105) | 52.69(67) | 57.07 (75) | 47.74(67) | 46.47(83) | 44.58(97) | 53.18(108) | 62.62 (84) | 51.88(81) | 51.16 |
England | 52.24(123) | 47.24(120) | 50.35(115) | 49.50(100) | 48.75(95) | 38.90(104) | 41.12(107) | 48.54(92) | 49.96(95) | 47.45 |
South Africa | 35.93(40) | 37.20(50) | 42.60(47) | 48.41(31) | 50.00(4)** | 51.01(66) | 51.74(78) | 57.08 (71) | 47.88 | |
West Indies | 35.86(22) | 50.22(57) | 49.67(49) | 47.96(63) | 55.03 (82) | 46.44(81) | 40.49(82) | 41.32(62) | 46.69 | |
New Zealand | 29.09(14) | 28.74(38) | 40.32(43) | 37.30(41) | 42.69(59) | 40.52(81) | 45.70(56) | 41.28(62) | 39.80 | |
India | 31.57(7) | 36.26(57) | 40.32(52) | 43.56(64) | 38.65(81) | 44.68(69) | 47.37(72) | 48.84(80) | 42.95 | |
Pakistan | 41.46(29) | 36.15(30) | 43.19(46) | 44.27(80) | 46.91(76) | 47.50(66) | 45.70(54) | 44.57 | ||
Sri Lanka | 34.25(29) | 39.60(67) | 52.05 (71) | 46.70(65) | 44.73 | |||||
Zimbabwe | 36.82(39) | 33.86(44) | 39.55(11) | 35.75 | ||||||
Bangladesh | 26.32(44) | 33.28(39) | 29.59 | |||||||
Total | 47.42 | 44.56 | 46.16 | 45.69 | 45.68 | 43.34 | 45.09 | 47.21 | 47.18 | 45.84 |
The values presented here are the average Team performance points during the specified time period. It is agreed that the specific time periods might not be wholly fair to a particular team. But this is the basis for this analysis. At a later date I will do a more complex floating time period analysis in which we can look at the best period for any team. The period averages vary around 5% either side of the 45 mark. We can draw an overall inference that a higher value, such as the 47 during the 2000-14 period, indicates that more matches have ended in results.
It can be seen that achieving an average of 55.0 is extraordinary and only four teams in history have managed this feat. Australia 1946-59, West Indies 1980-89, Australia 2000-06 and South Africa 2007-14 form the elite group of such teams. Just to put these numbers in perspective, let me take the Australia 2000-06. Their performance index average is 62.62. This is the equivalent of winning all the 84 Test matches they played by 200 runs or six wickets in high-score matches. These comparisons are from actual matches. The average of 55.0 is, incidentally, equivalent to winning all matches by 100 runs or four wickets.
These numbers will stand out when I say that India and Pakistan have never crossed 50.0 in any time period. And Sri Lanka, once, during 2000-06, through that magician extraordinaire, Muralitharan.
Only one team, Australia, has got a performance index average of above 50.0 through the 137 years of Test cricket. Three teams, England, South Africa and West indies, have an average performance index value of 45.0.
Bangladesh have an average index value either side of 30. The lower figure finds matches involving New Zealand either side of the war. But New Zealand have since improved considerably and had their best period during 2000-06 with 45.7.
A look at the best and the worst Test teams of different eras
I have tackled the peer analysis of players in various forms during the years. However, I have never done a peer analysis of players within a group, i.e. teams.
Since cricket is primarily a team game and the players are there to contribute their bit to help the team to achieve the desired results (at least let us think it is that way), the team peer analysis is overdue. This pair of articles will redress the lacuna.
My first thoughts were to do a single article covering all aspects of team peer analysis. Then I realised that the article would be too long and it would be difficult for readers to assimilate all the information. Hence I have split the analysis into two parts.
The first one will look into the team comparisons using players, batsmen and bowlers, as the basis. In the second, I will compare the team performances using the Team performance index (which is a contribution index developed jointly by Milind and me, and which was covered in detail in the article on Test series) and the results, tweaked with properly derived home-away weights.
To handle this analysis I have split the 137 years of Test cricket into nine periods, not necessary of equal duration, but logical and with a reasonably equal distribution of Tests.
The periods are 1877-1914 (Pre WW1), 1920-39 (WW1-WW2), 1946-59 (the post-war years), 1960-69, 1970-79, 1980-89, 1990-99, 2000-06 and finally the current period, 2007-14. This is as logical a split as I can possibly arrive at.
I am sure some readers will have good reasons for fixing 1952-64 or 1984-1997 or something similar as the periods and support such propositions with valid ideas. But let us all agree that this is a logical grouping and move on.
There are no cut-off levels, no minimum requirements, no restrictions of any other kind.
All the 2132 Tests, including the recent Ageas Bowl non-contest, are included.
The table below is a support table to help interpret the following ones.
It summarises the Tests played by each team in the stated time periods.
Each table entry indicates the total number of Tests played, the home Tests played and the away Tests played. For this purpose a neutral location is strictly taken as an away Test for both teams.
This is fair and does not invoke any assumptions. This is the reason why in some of the time periods, the home Test count is different to the away Test count.
During the first period, the three Tests played in England during 1912 between Australia and South Africa cause the 131-137 split. The next neutral Test was only played during the 1990-99 period.
Between 2000 and 2006 five neutral Tests were played, and during the past seven years, 15 more, mostly by Pakistan. Thus there are in total 24 neutral Tests.
We seem to have a problem during 2000-2005. The difference between the home and away Tests is odd, which is illogical.
This is because Test #1768, played between Australia and ICC XI, is accounted only once: as a home Test for Australia. This also explains why the totals in the last column are 4263 and 2155 and not 4264 and 2156.
Even this mundane table is an interesting one in that it is a kaleidoscope of Test cricket as it unfolded. The loss of a decade and half for the South Africans, the recent virtual disappearance of Zimbabwe, the wide disparity in home and away Tests for Pakistan during the last period, the fact that England play at home more than away barring the first period when they travelled to South Africa quite often, and so on.
1877-1914 | 1920-1939 | 1946-1959 | 1960-1969 | 1970-1979 | 1980-1989 | 1990-1999 | 2000-2006 | 2007-2014 | All Tests | |
---|---|---|---|---|---|---|---|---|---|---|
All-H-A | All-H-A | All-H-A | All-H-A | All-H-A | All-H-A | All-H-A | All-H-A | All-H-A | All-H-A | |
Australia | 105-57-48 | 67-35-32 | 75-35-40 | 67-30-37 | 83-44-39 | 97-54-43 | 108-56-52 | 84-43-41 | 81-40-41 | 767-394-373 |
England | 123-48-75 | 120-58-62 | 115-64-51 | 100-53-47 | 95-47-48 | 104-57-47 | 107-57-50 | 92-49-43 | 94-52-42 | 950-485-465 |
South Africa | 40-26-14 | 50-28-22 | 47-25-22 | 31-15-16 | 4-4-0 | 66-36-30 | 78-38-40 | 70-36-34 | 386-208-178 | |
West Indies | 22-8-14 | 57-24-33 | 49-20-29 | 63-34-29 | 82-30-52 | 81-41-40 | 82-39-43 | 62-30-32 | 498-226-272 | |
New Zealand | 14-8-6 | 38-16-22 | 43-19-24 | 41-21-20 | 59-28-31 | 81-40-41 | 56-29-27 | 62-30-32 | 394-191-203 | |
India | 7-3-4 | 57-30-27 | 52-36-16 | 64-34-30 | 81-42-39 | 69-30-39 | 72-32-40 | 79-37-42 | 481-244-237 | |
Pakistan | 29-15-14 | 30-13-17 | 46-14-32 | 80-43-37 | 76-34-42 | 66-28-38 | 53-4-49 | 380-151-229 | ||
Sri Lanka | 29-12-17 | 67-30-37 | 71-39-32 | 64-34-30 | 231-115-116 | |||||
Zimbabwe | 39-22-17 | 44-22-22 | 10-7-3 | 93-51-42 | ||||||
Bangladesh | 44-21-23 | 39-22-17 | 83-43-40 | |||||||
Total | 268-131-137 | 280-140-140 | 418-209-209 | 372-186-186 | 396-198-198 | 532-266-266 | 694-346-348 | 689-340-349 | 614-292-322 | 4263-2108-2155 |
Now let us see the Batting tables.
Bat-All | 1877-1914 | 1920-1939 | 1946-1959 | 1960-1969 | 1970-1979 | 1980-1989 | 1990-1999 | 2000-2006 | 2007-2014 | |
---|---|---|---|---|---|---|---|---|---|---|
Australia | 24.62(103%) | 36.50(116%) | 34.30(118%) | 34.45(109%) | 31.77(97%) | 33.94(105%) | 35.26(114%) | 43.71(135%) | 37.31(109%) | |
England | 25.31(109%) | 36.33(120%) | 31.38(107%) | 36.13(117%) | 32.28(98%) | 29.87(90%) | 30.29(95%) | 34.23(102%) | 36.92(108%) | |
South Africa | 20.21(81%) | 27.99(83%) | 27.34(90%) | 33.01(103%) | 40.36(124%) | 33.72(108%) | 37.73(114%) | 39.90(117%) | ||
West Indies | 24.39(73%) | 36.16(125%) | 34.96(110%) | 36.49(114%) | 35.00(109%) | 29.85(94%) | 29.74(87%) | 30.34(86%) | ||
New Zealand | 25.55(77%) | 21.25(69%) | 24.14(72%) | 27.93(84%) | 30.01(91%) | 29.68(93%) | 32.94(98%) | 29.88(85%) | ||
India | 22.95(70%) | 27.13(89%) | 29.50(90%) | 31.91(97%) | 34.41(107%) | 35.24(113%) | 36.22(109%) | 38.13(112%) | ||
Pakistan | 25.50(84%) | 28.67(88%) | 34.88(108%) | 35.64(111%) | 30.93(98%) | 35.35(106%) | 30.62(88%) | |||
Sri Lanka | 25.89(78%) | 30.71(97%) | 34.36(103%) | 38.91(114%) | ||||||
Zimbabwe | 26.62(84%) | 26.44(77%) | 24.90(72%) | |||||||
Bangladesh | 20.78(60%) | 26.52(75%) | ||||||||
Total | 24.20 | 32.69 | 29.95 | 32.22 | 32.66 | 32.54 | 31.56 | 33.61 | 34.59 |
This table covers all Tests. The batting measure is simple and straightforward. It is really the Runs per Wicket value (RpW) with all runs and all wickets included. Extras are runs for teams and run-outs are dismissals by the bowling teams. This table compares the RpW for the concerned team with the total RpW value for all teams, excluding the concerned team. A percentage value above 100 indicates that the team has done very well. A percentage value below 100 indicates that the team has performed worse. Values higher than around 120% are highlighted in blue. Values below 75% are highlighted in red.
Only four teams during the 137-year long Test scene have a peer RpW ratio of greater than 120%. These are given below.
- Australia 2000-06 (135%). No surprise. Considered by many to be the greatest team ever.
- West Indies 1946-59 (125%). A surprise. Possibly the presence of the W's and the young giant Sobers helped. Also a low sub-30 batting RpW value for the rest, with bowlers ruling the roost.
- South Africa 1970-79 (124%). But only in four home Tests. So this can be ignored for all practical purposes. Probably more relevant is South Africa during 2007-14. South Africa scored at 117% on a high base of 34.6.
- England 1920-39 (120%). A top batting line-up, led by Hammond.
Now for the poor performers: The red lined entries.
- Bangladesh 2000-06 had the worst ratio - 60%. They were lambs to the slaughter. They improved slightly and finished the next (and current) period at 72%. Overall they have a ratio of around 65%.
- New Zealand, during the first two post-war periods, were very poor. Their ratios were 69% and 72%. Subsequently they have improved and are around the 90% mark now. It must be conceded that their home pitches were totally bowling-friendly ones.
- West Indies had a ratio of 73% when they started.
- Similarly India had a poor ratio of 70% during their first few years, albeit over seven Tests only.
- During the last period, Zimbabwe has been at around the 72% mark, but over ten Tests.
Now let us move on to the home and away performances of the teams.
Bat-Home | 1877-1914 | 1920-1939 | 1946-1959 | 1960-1969 | 1970-1979 | 1980-1989 | 1990-1999 | 2000-2006 | 2007-2014 | |
---|---|---|---|---|---|---|---|---|---|---|
Australia | 26.85(116%) | 34.78(103%) | 34.40(112%) | 38.15(119%) | 32.10(93%) | 33.98(99%) | 37.23(113%) | 48.84(141%) | 40.95(111%) | |
England | 25.49(104%) | 39.70(127%) | 34.59(115%) | 33.72(102%) | 33.64(99%) | 29.74(84%) | 31.92(94%) | 37.50(105%) | 39.53(106%) | |
South Africa | 19.57(74%) | 28.52(80%) | 25.12(78%) | 35.86(109%) | 40.36(120%) | 33.14(98%) | 39.40(110%) | 37.34(99%) | ||
West Indies | 32.81(96%) | 40.34(134%) | 36.96(113%) | 36.98(111%) | 40.03(120%) | 31.86(94%) | 33.20(91%) | 30.41(79%) | ||
New Zealand | 26.27(76%) | 17.69(54%) | 23.74(69%) | 27.30(79%) | 33.47(98%) | 32.50(96%) | 31.66(87%) | 34.82(92%) | ||
India | 22.58(66%) | 31.85(102%) | 31.25(93%) | 32.52(95%) | 36.55(108%) | 39.02(118%) | 36.12(100%) | 45.33(124%) | ||
Pakistan | 24.85(78%) | 31.93(96%) | 46.90(142%) | 39.44(118%) | 33.08(98%) | 39.80(111%) | 47.59(127%) | |||
Sri Lanka | 25.70(74%) | 34.88(104%) | 39.52(111%) | 41.49(112%) | ||||||
Zimbabwe | 29.10(86%) | 27.35(74%) | 29.95(79%) | |||||||
Bangladesh | 21.56(58%) | 28.72(75%) | ||||||||
Total | 24.80 | 34.06 | 31.30 | 33.18 | 33.85 | 34.13 | 33.65 | 36.11 | 37.60 |
England 1920-29 (Wally Hammond), West Indies 1946-59, Australia 2000-06, Pakistan 1970-79 (Javed Miandad/Zaheer Abbas) and Pakistan in the few Tests played recently were the teams that exceeded 125% at home. Pakistan were way off on the bowling front, however.
New Zealand in the fifties and sixties, India in their initial matches, Sri Lanka in their first few matches, Zimbabwe and Bangladesh in 2000-06 went below 75%.
Bat-Away | 1877-1914 | 1920-1939 | 1946-1959 | 1960-1969 | 1970-1979 | 1980-1989 | 1990-1999 | 2000-2006 | 2007-2014 | |
---|---|---|---|---|---|---|---|---|---|---|
Australia | 21.70(88%) | 38.92(131%) | 34.21(124%) | 31.22(100%) | 31.38(99%) | 33.89(111%) | 33.24(115%) | 39.08(128%) | 34.26(107%) | |
England | 25.21(117%) | 33.94(116%) | 28.12(97%) | 39.11(134%) | 31.05(98%) | 30.03(96%) | 28.44(95%) | 30.96(98%) | 33.94(106%) | |
South Africa | 21.40(90%) | 27.25(85%) | 29.74(104%) | 30.33(97%) | 34.47(118%) | 36.36(118%) | 42.56(136%) | |||
West Indies | 20.13(61%) | 33.17(119%) | 33.72(110%) | 35.94(117%) | 32.50(106%) | 27.97(94%) | 26.99(84%) | 30.28(93%) | ||
New Zealand | 24.78(78%) | 23.88(81%) | 24.46(75%) | 28.55(90%) | 27.43(87%) | 27.17(91%) | 34.29(110%) | 25.99(79%) | ||
India | 23.24(73%) | 22.87(77%) | 26.24(82%) | 31.26(99%) | 32.35(105%) | 32.61(111%) | 36.30(118%) | 33.25(104%) | ||
Pakistan | 26.14(90%) | 26.59(84%) | 30.87(98%) | 31.84(103%) | 29.45(99%) | 32.18(103%) | 29.78(91%) | |||
Sri Lanka | 26.01(83%) | 28.01(94%) | 29.26(93%) | 36.66(115%) | ||||||
Zimbabwe | 23.77(79%) | 25.53(80%) | 13.80(42%) | |||||||
Bangladesh | 20.07(62%) | 23.87(73%) | ||||||||
Total | 23.62 | 31.40 | 28.71 | 31.27 | 31.53 | 31.05 | 29.63 | 31.40 | 32.21 |
A look at the best batting and bowling streaks in Tests
A few years back I had done an analysis on streaks in Test cricket. I had done this work based on a notional number of consecutive Tests as the streak. Towards the end of the article there was an excellent suggestion that I could use 52 Tests as the basis. Unfortunately since this was a late suggestion, I could not do proper justice to the idea. Also, many current readers would not have seen the earlier article. Hence I have decided to revisit the Test streak scene.
Another important fact is that during the four years, top batsmen like Hashim Amla, AB de Villiers, Kevin Pietersen, Michael Clarke, Alastair Cook, Ross Taylor et al, had their highs and would surely make a significant impact on the tables. On the bowling front, we have Dale Steyn, Saeed Ajmal, Mitchell Johnson, James Anderson, Graeme Swann who have ruled the roost. Hence this article will, I am sure, break new ground.
For batsmen, 52 Tests forms the undisputed cut-off. An Air Guitar for guessing why. The colossus played 52 Tests. Any comparison will be against this number. So I will select only batsmen who have played a minimum of 52 Tests. There are 151 batsmen who qualify. My apologies to those who miss out: to name a few, Everton Weekes, Frank Worrell, Dennis Amiss and Jonathan Trott.
For bowlers, there is an equally dominant figure: Sydney Barnes. He played in 27 Tests only and captured 189 Test wickets, an average of seven wickets per Test. There are 158 bowlers who qualify. So we have a decent population in each category. Let us not forget that each batsman has many streaks of 52 Tests within his career. Sachin Tendulkar had 148 such streaks. Muttiah Muralitharan had 106 qualifying streaks. This means that we have a lot of data available.
Any player's career could be shaded by various textures. Years lost due to war, injuries, non-selections, boycotts, self-imposed exiles, WSC-type series, bans, non-bowling injuries, easy runs/wickets, tough runs/wickets. We have to take all these in our stride and work on the basis that these factors even out across the streaks of between four and 20 years. So this data has a lot going for it. It deserves a lot of respect.
I will be analysing a huge amount of data. However, to make the task of the reader easier, I have created only four relevant tables. For each batsman and bowler, I pick up the best streak embedded within his career. So I reduce tons of data, so to speak, into four tables. Further I will feature in this article the top ten and bottom five players in each table. The complete tables are available for downloading and viewing. The analysis is current up to and including India's historic win over England at Lord's.
Batsman | Team | Tests | Runs | RpT | Best 52-Test streak | Runs | RpT | Worst 52-Test streak | Runs | Ratio |
---|---|---|---|---|---|---|---|---|---|---|
DG Bradman | Aus | 52 | 6996 | 134.5 | 176(1928) - 303(1948) | 6996 | 134.5 | 176(1928) - 303(1948) | 6996 | 100.0 |
RT Ponting | Aus | 168 | 13378 | 79.6 | 1595(2002)-1819(2006) | 5857 | 112.6 | 1324(1996)-1590(2002) | 3068 | 190.9 |
BC Lara | Win | 131 | 11953 | 91.2 | 1542(2001)-1816(2006) | 5576 | 107.2 | 1299(1995)-1541(2001) | 3944 | 141.4 |
Sangakkara | Slk | 125 | 11593 | 92.7 | 1804(2006)-2048(2012) | 5518 | 106.1 | 1504(2000)-1776(2005) | 3764 | 146.6 |
GS Sobers | Win | 93 | 8032 | 86.4 | 443(1957) - 636(1968) | 5468 | 105.2 | 529(1962) - 738(1974) | 4410 | 124.0 |
JH Kallis | Saf | 166 | 13289 | 80.1 | 1619(2002)-1856(2007) | 5311 | 102.1 | 1318(1995)-1563(2001) | 3340 | 159.0 |
Yousuf | Pak | 90 | 7530 | 83.7 | 1513(2000)-1844(2007) | 5247 | 100.9 | 1412(1998)-1726(2004) | 3744 | 140.1 |
Tendulkar | Ind | 200 | 15921 | 79.6 | 1365(1997)-1631(2002) | 5236 | 100.7 | 1127(1989)-1364(1997) | 3534 | 148.2 |
L Hutton | Eng | 79 | 6971 | 88.2 | 281(1947) - 386(1954) | 5114 | 98.3 | 276(1946) - 376(1953) | 4643 | 110.1 |
Jayawardene | Slk | 146 | 11506 | 78.8 | 1709(2004)-1968(2010) | 5102 | 98.1 | 1447(1999)-1699(2004) | 3559 | 143.4 |
ML Hayden | Aus | 103 | 8626 | 83.7 | 1520(2000)-1723(2004) | 5092 | 97.9 | 1688(2004)-1904(2009) | 3966 | 128.4 |
GA Gooch | Eng | 118 | 8900 | 75.4 | 1049(1986)-1260(1994) | 5025 | 96.6 | 760(1975)-1044(1986) | 3201 | 157.0 |
SM Gavaskar | Ind | 125 | 10122 | 81.0 | 683(1971) - 856(1979) | 5007 | 96.3 | 863(1979)-1025(1985) | 3380 | 148.1 |
............... | ||||||||||
HA Gomes | Win | 60 | 3171 | 52.9 | 822(1978)-1045(1986) | 3021 | 58.1 | 839(1979)-1070(1987) | 2658 | 113.7 |
CG Borde | Ind | 55 | 3061 | 55.7 | 465(1959) - 634(1968) | 3021 | 58.1 | 459(1958) - 631(1968) | 2925 | 103.3 |
JC Adams | Win | 54 | 3010 | 55.7 | 1188(1992)-1523(2000) | 2995 | 57.6 | 1208(1993)-1527(2001) | 2857 | 104.8 |
A Ranatunga | Slk | 93 | 5105 | 54.9 | 955(1983)-1293(1995) | 2990 | 57.5 | 1103(1988)-1394(1998) | 2653 | 112.7 |
GW Flower | Zim | 67 | 3457 | 51.6 | 1285(1995)-1625(2002) | 2872 | 55.2 | 1240(1993)-1581(2001) | 2643 | 108.7 |
I have presented the best 52-Test streak and the worst 52-Test streak. This will enable the readers to see the fluctuations in a batsman's career. It is obvious that the best and worst streaks will be wide apart for players with long careers.
It does not take rocket science to know who would lead the table. As day follows night follows day, one DG Bradman, the "Boy from Bowral" is certain to be there at the top with 6996 runs. No need to describe Bradman other than to say that he stands supreme and in a separate zone of his own. This streak, also coinciding with his career, lasted just under 20 years. If those seven years had not been lost, would Bradman have reached 10,000 runs at 100 or ended his career with 6000 at 90? There are no answers.
What is important is the collection of modern greats who come after Bradman. Ricky Ponting's purplest of patches lasted just under five years and he accumulated nearly 6000 runs. Against a career RpT (Runs per Test) value of 80, he scored over 110 runs per Test during this period. He was within 17% of Bradman in his aggregate. This is a magnificent achievement considering that most measures place the second-placed batsman at around 40% below Bradman.
He is followed by another modern great. Brian Lara scored over 5500 runs during his heyday of five and a half years. Since his career RpT is itself a high 91, the accumulation of 107 does not seem that high. Another significant fact is that this was achieved virtually towards the end of Lara's career.
Kumar Sangakkara's recent form has been outstanding and this is shown by his six-year accumulation of just over 5500 runs. Garry Sobers completes the top five with an aggregate of nearly 5500 runs. However this took over ten years, indicating the paucity of Tests during the '50s and '60s.
Jacques Kallis, Mohammad Yousuf, Sachin Tendulkar, Len Hutton and Mahela Jayawardene complete the top ten. Hutton is the only batsman belonging to the earlier generation. Three other batsmen, Matthew Hayden, Graham Gooch and Sunil Gavaskar, are featured here since they accumulated over 5000 Test runs during the 52-Test streak.
It can be seen that where the batsmen have had careers close to 52 Tests, their career RpT and the best streak RpT are close. However, where the batsman has played in many Tests, such as Tendulkar, Ponting et al, there is a wide gap between the values.
The years that the concerned player took to complete this streak is of interest. For the older players we have periods exceeding 20 years. Bradman was close to this figure. Some of the modern players have achieved this in four years. For the record, Jack Hobbs took 21 years to play 52 Tests. Hayden took only four years to play the same number of Tests.
A tweak was necessary to present a meaningful bottom-five batsmen. The last part of the table is full of allrounders and wicketkeepers. Hence I have selected five players who played purely as batsmen. Grant Flower accumulated only 2872 runs in his best streak. The other four batsmen - Arjuna Ranatunga, Jimmy Adams, Chandu Borde and Larry Gomes - also aggregated only around 3000 runs in their best streak of 52 Tests.
Ponting's best streak is nearly twice as productive as his worst streak. It is of interest to note that only Daniel Vettori, with a ratio of 250%, has a wider variance. This indicates the topsy-turvy nature of Ponting's career. Most other players with long careers are around the 150% mark, with Kallis' 159% being quite high. Steve Waugh has a ratio of 170%. It is interesting to note that Tendulkar's best streak starts right at the end of his worst.
Batsman | Team | Tests | Runs | Career RpFI-MA | Best 52-Test streak | Inns | Unf-Nos | Runs | Streak RpFI-MA |
---|---|---|---|---|---|---|---|---|---|
DG Bradman | Aus | 52 | 6996 | 89.50 | 176(1928) - 303(1948) | 80 | 4 | 6996 | 89.50 |
RT Ponting | Aus | 168 | 13378 | 47.72 | 1595(2002)-1819(2006) | 92 | 9 | 5857 | 66.50 |
GS Sobers | Win | 93 | 8032 | 51.33 | 443(1957) - 636(1968) | 88 | 5 | 5468 | 63.27 |
Sangakkara | Slk | 125 | 11593 | 55.22 | 1804(2006)-2048(2012) | 91 | 3 | 5518 | 61.82 |
Yousuf | Pak | 90 | 7530 | 48.96 | 1513(2000)-1844(2007) | 87 | 3 | 5247 | 61.44 |
Tendulkar | Ind | 200 | 15921 | 49.49 | 1365(1997)-1631(2002) | 88 | 4 | 5236 | 60.81 |
BC Lara | Win | 131 | 11953 | 51.85 | 1542(2001)-1816(2006) | 93 | 0 | 5576 | 59.96 |
Richards | Win | 121 | 8540 | 47.55 | 767(1976) - 987(1984) | 76 | 0 | 4514 | 59.39 |
JH Kallis | Saf | 166 | 13289 | 48.44 | 1619(2002)-1856(2007) | 91 | 5 | 5311 | 59.26 |
JB Hobbs | Eng | 61 | 5410 | 54.55 | 102(1909) - 194(1930) | 85 | 3 | 4897 | 59.23 |
ML Hayden | Aus | 103 | 8626 | 48.57 | 1520(2000)-1723(2004) | 91 | 6 | 5092 | 58.53 |
de Villiers | Saf | 93 | 7240 | 47.70 | 1871(2008)-2119(2014) | 82 | 4 | 4644 | 58.25 |
R Dravid | Ind | 164 | 13288 | 47.73 | 1515(2000)-1765(2005) | 86 | 5 | 4883 | 58.21 |
Jayawardene | Slk | 146 | 11506 | 47.73 | 1709(2004)-1968(2010) | 89 | 4 | 5102 | 58.18 |
Miandad | Pak | 124 | 8832 | 47.72 | 945(1983)-1130(1989) | 73 | 1 | 4240 | 58.14 |
............... | |||||||||
CG Borde | Ind | 55 | 3061 | 32.60 | 465(1959) - 634(1968) | 92 | 7 | 3021 | 34.07 |
AJ Lamb | Eng | 79 | 4656 | 33.87 | 978(1984)-1163(1991) | 91 | 3 | 3033 | 33.91 |
BE Congdon | Nzl | 61 | 3448 | 30.71 | 583(1965) - 818(1978) | 96 | 2 | 3171 | 33.65 |
GM Wood | Aus | 59 | 3374 | 31.11 | 816(1978)-1021(1985) | 99 | 3 | 3081 | 31.96 |
GW Flower | Zim | 67 | 3457 | 28.41 | 1285(1995)-1625(2002) | 98 | 2 | 2872 | 29.71 |
This table is ordered on the batting measure, "Runs per Fulfilled Innings - Milind-Ananth" (RpFI-MA). This is Milind's version of handling the non-fulfilled innings and has been discussed a few times already in my earlier articles. He has referred to this measure as 'µ' in his blogs. To recapitulate in a simple manner, we expand, in an indirect manner, all not out innings which are below the Out-Average to the Out-Average. This ensures that scores like 5*, 15* and 20* do not lower the RpI figures drastically. This method takes care of the problem in Batting Average with middle order batsmen remaining unbeaten in 15-20% of the innings they played in.
I have given the example of Bradman to illustrate this calculation. The average of the 70 innings in which he was dismissed is 83.83 (5868/70). His 10 not-outs are 37*, 299*, 103*, 144*, 102*, 56*, 127*, 57*, 30* and 173*. Out of these ten innings, six are higher than 83.83 and are considered "fulfilled innings". It is clear why. These innings have gone past the Out-Average. The other four innings - 37*, 56*, 57rh and 30* - are indirectly extended to the Out-Average, by tweaking the number 4 to a lower value 2.147(180/83.83). The value of RpFI-MA for Bradman is 6996/(76+2.147) which works out to 89.50. Hats off to Milind's awareness for maximum computing correctness.
It should be noted that the RpFI-MA value is derived for each streak and the best one presented here.
The first entry is the expected one. 99.94 would have been more easily recognisable. But let us start looking at Bradman's RpFI-MA figure carefully since that would appear quite frequently hereafter. The RpFI-MA is 89.50. Ponting continues to be in second place with an excellent RpFI-MA of 66.5. This is about 25% off Bradman's average and firmly places Ponting's streak on a fairly high pedestal.
Then we have changes from the earlier table. The increased number of not-outs, which are inherent in any middle order batsman's career, propels Sobers, with a RpFI-MA figure of 63.3 into third place. Sangakkara remains in the top five with 61.8 and the top five is completed by Yousuf, with 61.4.
Next in the list are the two modern legends: Tendulkar and Lara, who have almost identical figures either side of 60. Viv Richards is a surprise entry into the top ten. Kallis and Hobbs complete the top ten.
Grant Flower is comfortably propping up the table with a fairly low value of 29.7. Again, let me remind you that I have ignored allrounders and wicketkeepers. We also have four other batsmen who promised a lot but did not deliver much. Especially Graeme Hick.
Bowler | Team | Tests | Wkts | WpT | Best 27-Test streak | Wkts | WpT | Worst 27-Test streak | Wkts | WpT | Ratio |
---|---|---|---|---|---|---|---|---|---|---|---|
Muralitharan | Slk | 133 | 800 | 6.0 | 1670(2003)-1820(2006) | 205 | 7.6 | 1195(1992)-1359(1997) | 101 | 3.7 | 203.0 |
SF Barnes | Eng | 27 | 189 | 7.0 | 65(1901) - 133(1914) | 189 | 7.0 | 65(1901) - 133(1914) | 189 | 7.0 | 100.0 |
Younis | Pak | 87 | 373 | 4.3 | 1151(1990)-1268(1994) | 177 | 6.6 | 1442(1999)-1617(2002) | 82 | 3.0 | 215.9 |
SK Warne | Aus | 145 | 708 | 4.9 | 1615(2002)-1763(2005) | 173 | 6.4 | 1405(1998)-1556(2001) | 93 | 3.4 | 186.0 |
RJ Hadlee | Nzl | 86 | 431 | 5.0 | 959(1983)-1072(1987) | 164 | 6.1 | 710(1973) - 873(1980) | 118 | 4.4 | 139.0 |
MD Marshall | Win | 81 | 376 | 4.6 | 991(1984)-1100(1988) | 161 | 6.0 | 837(1978) - 988(1984) | 109 | 4.0 | 147.7 |
DK Lillee | Aus | 70 | 355 | 5.1 | 790(1977) - 908(1981) | 160 | 5.9 | 876(1980) - 955(1983) | 129 | 4.8 | 124.0 |
CV Grimmett | Aus | 37 | 216 | 5.8 | 195(1930) - 251(1936) | 159 | 5.9 | 166(1926) - 234(1934) | 138 | 5.1 | 115.2 |
DW Steyn | Saf | 73 | 371 | 5.1 | 1830(2007)-1951(2010) | 157 | 5.8 | 1913(2009)-2056(2012) | 129 | 4.8 | 121.7 |
R Benaud | Aus | 63 | 248 | 3.9 | 431(1956) - 507(1961) | 157 | 5.8 | 347(1952) - 433(1956) | 73 | 2.7 | 215.1 |
Imran Khan | Pak | 88 | 362 | 4.1 | 909(1981)-1058(1986) | 154 | 5.7 | 1067(1987)-1182(1992) | 78 | 2.9 | 197.4 |
A Kumble | Ind | 132 | 619 | 4.7 | 1574(2001)-1724(2004) | 153 | 5.7 | 1247(1994)-1387(1997) | 87 | 3.2 | 175.9 |
AK Davidson | Aus | 44 | 186 | 4.2 | 449(1958) - 537(1963) | 151 | 5.6 | 372(1953) - 483(1959) | 92 | 3.4 | 164.1 |
............... | |||||||||||
Bracewell | Nzl | 41 | 102 | 2.5 | 891(1980)-1093(1988) | 71 | 2.6 | 1000(1984)-1138(1990) | 59 | 2.2 | 120.3 |
Razzaq | Pak | 46 | 100 | 2.2 | 1584(2002)-1809(2006) | 67 | 2.5 | 1487(2000)-1716(2004) | 48 | 1.8 | 139.6 |
TE Bailey | Eng | 61 | 132 | 2.2 | 386(1954) - 440(1957) | 66 | 2.4 | 334(1951) - 412(1955) | 44 | 1.6 | 150.0 |
RJ Shastri | Ind | 80 | 151 | 1.9 | 962(1983)-1054(1986) | 63 | 2.3 | 1063(1986)-1177(1991) | 37 | 1.4 | 170.3 |
CL Hooper | Win | 102 | 114 | 1.1 | 1364(1997)-1553(2001) | 45 | 1.7 | 1096(1988)-1174(1991) | 11 | 0.4 | 409.1 |
For bowlers also, I have presented the best 27-Test streak as also the worst 27-Test streak. It is to be expected that the bowlers will have much wider fluctuations between their best and worst streaks. This can be seen later.
What do we have here? We would have expected Barnes, with his career average of seven wickets per Test, sitting comfortably at the top. No, not this time. Murali, that Lankan wizard, has comfortably overtaken Barnes and is perched on top with 205 wickets in 27 Tests during the 2003-2006 period. An extraordinary WpT figure of 7.6.
Do I hear the words Bangladesh and Zimbabwe and home conditions in Sri Lanka? I am a firm believer in the axiom that a Test wicket is a Test wicket. There have been weak teams right through the 137 years of Test cricket. Surely Bangladesh and Zimbabwe are no worse than many teams during the 1930s, 1950s, 1960s? Even many established teams were poor. How many 5-0 drubbings have teams endured? Not to forget the uncovered pitches during the first few decades of Test cricket. So let us keep our views upright and not try to belittle one player or group of players. One day I should do an analysis to prove the point I have briefly talked about.
The next five bowlers are contemporary greats. How else can one describe Waqar Younis, Shane Warne, Richard Hadlee, Malcolm Marshall and Dennis Lillee? All these bowlers have accumulated in excess of 160 wickets in their prime stretch of 27 Tests. A special mention should be made of Marshall, who has averaged around six wickets per Test in his prime despite the presence of so many world-class bowlers in his team.
The top ten is completed by Clarrie Grimmett, the surprise package - Richie Benaud - and Steyn. Benaud is indeed a surprise. To have accumulated over 150 wickets is praiseworthy and should let us revise our opinion of him.
Bill O'Reilly's 27 Tests took over 14 years since he played one Test after the war and this Test completed the tally of 27 Tests. Erapalli Prasanna took over 11 years to play 27 Tests. Mitchell Johnson, Tony Greig and Andrew Flintoff took less than two years to play the 27 Tests.
As has happened often, Ravi Shastri and Carl Hooper prop up the table with very poor aggregates below 65 wickets. Not one of these five is a pure bowler.
Wilfred Rhodes is in a freak situation. He went through a 27-Test streak with 95 wickets and another 27-streak with 15 wickets. Sobers had very striking contrasting streaks with 104 and 24 wickets respectively. Kallis has similar figures. The first real surprise is Ian Botham. He picked up 146 and 57 wickets respectively in his best and worst streaks. Murali picked up 205 and 101 wickets respectively. Thus it can be seen that about ten bowlers have ratios more than 200%. Surprisingly, despite the non-bowling Tests, Imran Khan finishes with 154 and 78 wickets respectively.
Bowler | Team | Tests | Wkts | Avge | Best 27-Test streak | Wkts | BowAvge |
---|---|---|---|---|---|---|---|
Imran Khan | Pak | 88 | 362 | 22.81 | 909(1981)-1058(1986) | 154 | 14.85 |
SF Barnes | Eng | 27 | 189 | 16.43 | 65(1901) - 133(1914) | 189 | 16.43 |
MD Marshall | Win | 81 | 376 | 20.95 | 991(1984)-1100(1988) | 161 | 17.09 |
Waqar Younis | Pak | 87 | 373 | 23.56 | 1151(1990)-1268(1994) | 177 | 17.32 |
JC Laker | Eng | 46 | 193 | 21.25 | 383(1954) - 464(1959) | 126 | 17.49 |
J Briggs | Eng | 33 | 118 | 17.75 | 23(1886) - 62(1899) | 118 | 17.64 |
Muralitharan | Slk | 133 | 800 | 22.73 | 1670(2003)-1820(2006) | 205 | 18.15 |
CEL Ambrose | Win | 98 | 405 | 20.99 | 1144(1990)-1257(1994) | 140 | 18.16 |
RJ Hadlee | Nzl | 86 | 431 | 22.30 | 959(1983)-1072(1987) | 164 | 18.46 |
AV Bedser | Eng | 51 | 236 | 24.90 | 317(1949) - 389(1954) | 149 | 18.56 |
AK Davidson | Aus | 44 | 186 | 20.53 | 449(1958) - 537(1963) | 151 | 18.95 |
Wasim Akram | Pak | 104 | 414 | 23.62 | 1134(1990)-1268(1994) | 149 | 19.24 |
IT Botham | Eng | 102 | 383 | 28.40 | 806(1977) - 881(1980) | 146 | 19.30 |
SM Pollock | Saf | 108 | 421 | 23.12 | 1380(1997)-1475(1999) | 130 | 19.38 |
AA Donald | Saf | 72 | 330 | 22.25 | 1320(1995)-1437(1998) | 148 | 19.72 |
RGD Willis | Eng | 90 | 325 | 25.20 | 780(1976) - 836(1978) | 117 | 19.89 |
............... | |||||||
Rafique | Bng | 33 | 100 | 40.76 | 1512(2000)-1832(2007) | 91 | 36.37 |
AF Giles | Eng | 54 | 143 | 40.60 | 1606(2002)-1728(2004) | 81 | 36.38 |
CL Hooper | Win | 102 | 114 | 49.43 | 1364(1997)-1553(2001) | 45 | 36.60 |
DVP Wright | Eng | 34 | 108 | 39.11 | 263(1938) - 326(1950) | 90 | 39.39 |
RJ Shastri | Ind | 80 | 151 | 40.96 | 962(1983)-1054(1986) | 63 | 39.44 |
I was almost certain that the average of Barnes would be the best, even though he was upstaged in the wickets tally by Murali. But there is another bowling giant who firmly shuts the door on Barnes. Imran Khan captured 154 wickets in the five-year period around early eighties at an unbelievable average of 14.85. Yes, that is true. This is the sort of average the demon bowlers around the turn of the 19th century used to get, bowling on uncovered wickets against teams new to Test cricket. I have carefully pondered over this. In my opinion the numbers of Murali and Imran Khan are two of the greatest bowling achievements ever. Imran's career figures changed from 128 at 29.45 to 282 at 21.48 during this memorable period.
The next three bowlers are Marshall, Younis and Jim Laker. All are wonderful bowlers. After Johnny Briggs appears Murali, who has an average of 18.15. Not bad for a spinner. Both Younis and Akram find a place in the top 12. What a period for Pakistan. Between 1990 and 1994, they had these two stalwarts picking up 320 wickets at an average of around 17.
The usual culprits prop up the table, including the ever-present table-proppers, Shastri and Hooper.
There is a case for increasing the bowling cut-off to a higher number of Tests. However, I am satisfied with this: after all 27 Tests have produced 150 wickets and more.
What do we conclude? Bradman was supreme, there has been no doubt about it and this analysis confirms this view. In his long career, scarred by six years of war and deliberate bodyline attack, he accumulated nearly 20% more runs at 25% higher RpFI-MA value than the next player who was playing at his prime. This one sentence confirms that his zone was beyond all other players' zones. This is the one analysis where there is a smaller gap between the master and the next best, Ponting. He is only around 20% off. Let us give him due credit. Lara and Sangakkara also stand out.
Murali, on the aggregate front, and Imran, on the average measure, have upstaged Barnes, considered by many to be one of the greatest, with career figures expected to be unreachable. That too, in modern conditions. Maybe all of us must give the modern bowlers their credit. We tend to put the batsmen on a pedestal and do not give the bowlers their right due.
An interesting add-on observation from Milind. If we define an alternate measure of consistency of a batsman as the ones with the lowest ratios, which would be close to 100%, between best and worst streaks (min 78 Tests considered - to have a career at least 150% of the streak length), then the top batsmen are given below.
NJ Astle (106.9%), MS Dhoni (109.4%), L Hutton (110.1%), GC Smith, N Hussain, Richardson, RJ Hadlee, GS Chappell, IR Bell, A Ranatunga, Tillakaratne, A Flintoff, Barrington, MW Gatting, Abbas, AJ Lamb, RB Kanhai (114.8%). A nice nugget: thank you, Milind.
The names that appear here which were well-placed in my earlier Consistency analysis are Hutton, Ken Barrington and Rohan Kanhai.
I have uploaded the Table containing the four full tables. To download/view this file, please CLICK HERE.