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November 12, 2010

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ODI Outliers: Innings which were way out

Anantha Narayanan
Sanath Jayasuriya: surpassed aggregate of team and opposition  © Getty Images
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Little would Abhishek have realized what he unleashed when he made the comment on Jayasuriya's 189 being more than 50% of the combined team scores. A simple statement. However it opened up a chain reaction of multiple analysis of outlying performances.

I decided to first do the work related to what Abhishek suggested. This is really a player's performance compared with the other 21 players. Then I did some analysis of the player against the 11 players of the other team. Finally there is one analysis of the player compared to the other 10 members of his team. A few very interesting facts have come to light.

First the share of a batsman's score in the aggregate score of the two teams. For this share to be higher than 50%, quite a few factors have to come through. Barring an outrageous scoreline of "Team1: 75 a.o., Team 2: 80 for x (Player1 78)" this can only happen in matches won by the teams batting first. Even there the player has to outscore his own team-mates by a mile, enough to offset the other team score.

So much so, there is only one case of a player scoring over 50% of the combined match aggregate. That is Jayasuriya, whose 189 formed 53.5% of the total of 353 (299 + 54). Jayasuriya scored 63.2% of his team score and the very low score of India made sure the overall figure remained above 50%. As I have already said, there is necessity for a specific pattern of scores in this analysis. A batsman dominating his own team's innings AND a very low score by the opposing team.

I kept the cut-off at 33.33% and created the table. The table is given below.

SNo MtId Year For Batsman           Runs   Vs  Total  Score   Share%

1.1652 2000 Slk Jayasuriya S.T 189 vs Ind 353 (299+ 54) 53.54% 2.0264 1984 Win Richards I.V.A 189 vs Eng 440 (272+168) 42.95% 3.2660@2007 Nzl McCullum B.B 80 vs Bng 188 ( 95+ 93) 42.55% 4.1049 1996 Saf Kirsten G 188 vs Uae 473 (321+152) 39.75% 5.0020 1975 Nzl Turner G.M 171 vs Eaf 437 (309+128) 39.13% 6.1943 2003 Zim Wishart C.B 172 vs Nam 444 (340+104) 38.74% 7.0322 1985 Win Haynes D.L 145 vs Nzl 388 (259+129) 37.37% 8.0323@1985 Win Haynes D.L 85 vs Nzl 233 (117+116) 36.48% 9.0405 1986 Win Richardson R.B 109 vs Slk 303 (248+ 55) 35.97% 10.0747@1992 Pak Rameez Raja 119 vs Nzl 333 (167+166) 35.74% 11.2547 2007 Pak Imran Nazir 160 vs Zim 448 (349+ 99) 35.71% 12.2803 2009 Slk Dilshan T.M 137 vs Pak 384 (309+ 75) 35.68% 13.2299@2005 Saf Smith G.C 134 vs Ind 377 (189+188) 35.54% 14.1890 2002 Saf Gibbs H.H 153 vs Bng 434 (301+133) 35.25% 15.2447 2006 Saf Kallis J.H 119 vs Ind 339 (248+ 91) 35.10% 16.0216 1983 Ind Kapil Dev N 175 vs Zim 501 (266+235) 34.93% 17.0441@1987 Win Greenidge C.G 133 vs Nzl 383 (192+191) 34.73% 18.1736 2001 Nzl Astle N.J 117 vs Ind 338 (211+127) 34.62% 19.1832 2002 Pak Mohammad Yousuf 129 vs Slk 373 (295+ 78) 34.58% 20.0015@1974 Pak Zaheer Abbas 57 vs Eng 165 ( 84+ 81) 34.55% 21.2912 2009 Zim Masakadza H 178 vs Ken 516 (329+187) 34.50% 22.1964 2003 Ind Tendulkar S.R 152 vs Nam 441 (311+130) 34.47% 23.2088 2004 Saf Kallis J.H 109 vs Win 317 (263+ 54) 34.38% 24.0457 1987 Win Richards I.V.A 181 vs Slk 529 (360+169) 34.22% 25.2828@2009 Win Gayle C.H 80 vs Eng 234 (117+117) 34.19% 26.0549 1989 Aus Marsh G.R 125 vs Pak 366 (258+108) 34.15% 27.2427 2006 Bng Shahriar Nafees 123 vs Zim 361 (231+130) 34.07% 28.1981 2003 Win Gayle C.H 119 vs Ken 350 (246+104) 34.00% 29.1837@2002 Win Gayle C.H 84 vs Ind 247 (124+123) 34.01% 30.0638 1990 Pak Rameez Raja 114 vs Nzl 341 (223+118) 33.43% Note: @ indicates second innings.

Next to Jayasuriya's 189 is the other 189, almost certainly the greatest ODI innings played. By Viv Richards, whose 189 (out of 272+168) formed 42.95% of the aggregate. However the most breath-taking of the chasing innings of all, McCullum's 80 (out of 93+95) formed 42.55% of the aggregate. This bizarre (real-life) scoreline is almost close to the outrageous scoreline I had earlier talked about. For a near-100 target to be chased by a team and one batsman scoring over 84% is unreal. No other innings exceeds 40% of the aggregate. The next chasing innings is Haynes's 85 (out of 116+117) working out to 36.5%.

It is not surprising that 9 West Indian batsmen figure in this list. Gayle is the leading batsman with 3 such dominating performances. In general the top three batsmen dominate the table. It is surprising that there is a single Australian entry (that too from Geoff Marsh) and nothing from England.

The next set of outlier innings are the ones where a batsman has outscored the other team by a wide margin. Note the clear distinction. In the first one we looked at the share of the batsman out of the aggregate. Here we look at the factor by which he outscored the opponents. Let us look at the table.

SNo MtId Year For Batsman            Runs  Vs    Score Ratio

1.1652 2000 Slk Jayasuriya S.T 189 vs Ind 54/10 3.50 2.2088 2004 Saf Kallis J.H 109 vs Win 54/10 2.02 3.0405 1986 Win Richardson R.B 109 vs Slk 55/10 1.98 4.1970 2003 Aus Hayden M.L 88 vs Nam 45/10 1.96 5.2803 2009 Slk Dilshan T.M 137 vs Pak 75/10 1.83 6.1943 2003 Zim Wishart C.B 172 vs Nam 104/ 5 1.65 7.1832 2002 Pak Mohammad Yousuf 129 vs Slk 78/10 1.65 8.2547 2007 Pak Imran Nazir 160 vs Zim 99/10 1.62 9.2727 2008 Nzl McCullum B.B 166 vs Ire 112/10 1.48 10.2727 2008 Nzl Marshall J.A.H 161 vs Ire 112/10 1.44 11.1868 2002 Aus Hayden M.L 146 vs Pak 108/10 1.35 12.2001 2003 Ind Yuvraj Singh 102 vs Bng 76/10 1.34 13.0020 1975 Nzl Turner G.M 171 vs Eaf 128/ 8 1.34 14.1970 2003 Aus Symonds A 59 vs Nam 45/10 1.31 15.2447 2006 Saf Kallis J.H 119 vs Ind 91/10 1.31 16.0297 1985 Aus Border A.R 118 vs Slk 91/10 1.30 17.1049 1996 Saf Kirsten G 188 vs Uae 152/ 8 1.24 18.0405 1986 Win Greenidge C.G 67 vs Slk 55/10 1.22 19.0777 1992 Win Haynes D.L 96 vs Pak 81/10 1.19 20.1964 2003 Ind Tendulkar S.R 152 vs Nam 130/10 1.17


Here also Jayasuriya's 189 rules the roost. This innings was 3.5 times the Indian score of 54. Then, after a mile or two, comes Kallis's 109 against the West Indian score of 54, a factor of 2.02. These are the only two innings with a factor above 2.0. That puts the Jayasuriya innings in perspective. Readers can note how quickly the factor drops off. Needless to say that all these innings are when the team batting first wins.

In general the weaker teams have been at the receiving end. It is of interest that Sri Lanka has figured prominently at either end. For the few matches Namibia has played (6), they have been the victims 5 times (by two batsmen in a single match).

Now for the third analysis. This time against the batsman's own team mates. Taking the runs only would be quite silly since many a batsman has out-scored his team mates. Hence I have taken the scoring rate as the basis. I determined the following ratio and then ranked the players on that ratio.

Batsman's own scoring rate
Batsman outlier ratio = -------------------------------
Rest of the team's scoring rate

In order to avoid getting in a batsman scoring 10 in 2 balls and "outscoring" the rest of his team by a wide margin, I selected only innings of 50 and above. Also I have excluded the team extras from the rest of the team runs to be completely correct. Now for the table.

No MtId Year For Batsman            Vs  Score   S/R   Others  S/R Ratio

1.1093 1996 Slk Jayasuriya S.T Pak 76( 28) 2.71 81(169) 0.48 5.66 2.0182 1983 Nzl Cairns B.L Aus 52( 25) 2.08 92(214) 0.43 4.84 3.0657 1990 Slk Ranatunga A Ind 58( 27) 2.15 135(267) 0.51 4.25 4.0152 1982 Ind Kapil Dev N Eng 60( 37) 1.62 115(293) 0.39 4.13 5.3039 2010 Nzl Mills K.D Ind 52( 35) 1.49 53(146) 0.36 4.09 6.0225 1983 Ind Patil S.M Pak 51( 28) 1.82 106(216) 0.49 3.71 7.0053 1978 Nzl Cairns B.L Eng 60( 43) 1.40 79(205) 0.39 3.62 8.0216 1983 Ind Kapil Dev N Zim 175(138) 1.27 79(222) 0.36 3.56 9.0576 1989 Aus Border A.R Eng 84( 44) 1.91 140(256) 0.55 3.49 10.2365 2006 Aus Gilchrist A.C Bng 76( 46) 1.65 103(218) 0.47 3.50 11.1901 2002 Zim Ervine S.M Pak 61( 41) 1.49 67(157) 0.43 3.49 12.0608 1990 Pak Wasim Akram Aus 86( 76) 1.13 69(211) 0.33 3.46 13.1660 2000 Ind Agarkar A.B Zim 67( 25) 2.68 213(275) 0.77 3.46 14.2239 2005 Pak Shahid Afridi Ind 102( 46) 2.22 134(207) 0.65 3.43 15.2687 2008 Aus Gilchrist A.C Slk 83( 50) 1.66 116(239) 0.49 3.42 16.2252 2005 Bng Mohammad Ashraful Eng 94( 52) 1.81 117(220) 0.53 3.40 17.0015 1974 Pak Zaheer Abbas Eng 57( 61) 0.93 13( 47) 0.28 3.38 18.1963 2003 Can Davison J.M Win 111( 76) 1.46 79(181) 0.44 3.35 19.2638 2007 Ber Cann L.O.B Ken 52( 32) 1.62 106(216) 0.49 3.31 20.0245 1984 Win Holding M.A Aus 64( 39) 1.64 110(222) 0.50 3.31 21.2660 2007 Nzl McCullum B.B Bng 80( 28) 2.86 7( 8) 0.88 3.27 22.2875 2009 Can Rizwan Cheema Ken 76( 38) 2.00 37( 60) 0.62 3.24 23.0547 1989 Pak Imran Khan Win 67( 41) 1.63 132(259) 0.51 3.21 24.2752 2008 Can Rizwan Cheema Win 61( 45) 1.36 102(236) 0.43 3.14 25.0481 1987 Ind Kapil Dev N Win 87( 64) 1.36 89(204) 0.44 3.12 26.1864 2002 Pak Shahid Afridi Saf 62( 40) 1.55 125(251) 0.50 3.11 27.2059 2003 Eng Flintoff A Bng 70( 47) 1.49 57(119) 0.48 3.11 28.0221 1983 Ind Patil S.M Eng 51( 32) 1.59 152(296) 0.51 3.11 29.2828 2009 Win Gayle C.H Eng 80( 43) 1.86 27( 45) 0.60 3.11 30.0622 1990 Aus Jones D.M Nzl 102( 91) 1.12 52(144) 0.36 3.11 31.2980 2010 Win Sammy D.J.G Saf 58( 24) 2.42 206(265) 0.78 3.11 32.0344 1985 Win Richards I.V.A Pak 66( 39) 1.69 111(201) 0.55 3.06 33.1814 2002 Zim Marillier D.A Ind 56( 24) 2.33 209(274) 0.76 3.06 34.2735 2008 Ind Sehwag V Slk 60( 36) 1.67 110(201) 0.55 3.05 35.2584 2007 Pak Shahid Afridi Slk 73( 34) 2.15 156(218) 0.72 3.00


Ah! how can you get this guy off the top. This is the third time, out of three, in this article that the "Matara marauder" has been at the top. At least it is for a different innings. His 76 in 28 balls against Pakistan had a scoring rate of 2.71 and the rest of his team scored at 0.48, giving this innings the stupendous ratio of 5.66. Then comes "father" Cairns whose 52 in 25 balls was scored 4.84 times faster than his team mates. Ranatunga's 58 in 27 balls gives this innings a ratio of 4.25. The century with the highest ratio is for Kapil Dev's 175 which scores 3.56. Anything said about this gem is an under-statement Afridi's 102 comes in next, clocking in at 3.43.

Holding deserves a special mention. His 64 off 39 balls compared to his team total of 197 in 43.3 overs is one of only two instances of a bowler in this exalted company. It is all the more commendable since the other teams included the greats and the bowling was Lawson/Alderman/Hogg/Rackemann. Kyle's 52 also deserves equal credit. Also spare a thought for L'O.B Cann, playing for unfancied Bermuda.

Overall it can be said that Sri Lanka and West Indies have often been at either end of the spectrum. English batsmen have rarely figured in such dominating innings. Also, with Gilchrist at the top, Australia has not appeared that frequently as expected.

This only shows the influence Jayasuriya had on the game. He outscored 21 other players, outscored 11 of his opposite team players by a factor of 3.50 and scored at a rate 5.66 times that of his 10 team-mates. He comes through on top on all three measures. Also note the daylight which exists between Jayasuriya and the second placed innings in the first two tables. When we talk of the greatest ODI players we almost always talk of Tendulkar and Richards. I think Jayasuriya needs to be included in this company.

It should be noted that these differ from the "PIF" based on the "Alex Factor" quite a lot although the third one comes near that analysis.

My thanks to Abhishek for providing the spark.

Anantha Narayanan has written for ESPNcricinfo and CastrolCricket and worked with a number of companies on their cricket performance ratings-related systems

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Posted by gruzoperevozki on (May 8, 2011, 4:14 GMT)

Интересная статейка, но как по мне, можно было бы и глубже капнуть..)

Posted by saadjarral on (December 5, 2010, 17:15 GMT)

jaysuria was very agressive opner and sirilankan cricket is still waiting for his replacement

Posted by Alex on (November 20, 2010, 16:01 GMT)

Ananth - I agree with Unni on the glorification of the 4th. Not that I am attacking you - the innings-wise analysis is quite revealing. However, since a test often comprises 2 innings, an additional column for the same metric applied to the total # runs scored in both innings would be even better.

E.g., consider SRT's runs in the match (across both innings) at Mohali vs Aus '10 and at Chennai vs Eng '08. But VVS bagged the glory at Mohali and Sehwag got the honors at Chennai. (Mind you, I am all for VVS & Viru, and they both did play amazing innings.) [[ My only point is not to have a fixed antipathy towards a certain class of things. Judge each innings separately. All these will be taken care of in the MVP analysis, sometime in the future. Ananth: ]]

Posted by unni on (November 20, 2010, 15:16 GMT)

Regarding your last statement, irrespective of the index discussion, I very much agree. It was always my opinion that the guys who lay the foundations by playing size-able first innings are the true value-adds to the team. I always feel dejected on the 4th innings glories and glorification of 'come-back-from-behind' sagas... Why did they risk it to the last moment? [[ Unni I must defer. It is mostly because the so-called match-winners in the first innings fail that there is need to play the coming-from-behind innings. Why have strong negative feelings towars a type of innings. Judge each innings on its merit. Ananth: ]]

Posted by unni on (November 20, 2010, 15:10 GMT)

@Abhi : I think there is some misunderstanding. I didn't propose to divide considering opposite team's batsman's average. So, still it is only w.r.t own batsman's against opposition bowlers. So, I'm not sure if the 'peer analysis' suggestion holds with that understanding.

As regarding your other comment on '% of runs', as Ananth mentioned, it is not very much different.

However, (incidently) this is very much related to Alex's comment below. Whatever Alex felt missed is the weightage factor. When somebody reduces a continuous quantity like runs(let us assume it is continuous due to the sheer size of the numbers) to discrete indices, large information will be lost. Then as you commented, whether we need only the skeleton or full flesh is not easy to decide. Anyway, my point was that it is precisely the difference between % calculation and an index calculation. [[ Unni My preliminary calculations show that the Inns Index is more robust that the % of TS, which is easy to determine, however. Ananth: ]]

Posted by Alex on (November 20, 2010, 5:47 GMT)

Ananth - Unni's metric will weigh a strong performance in one innings more than a strong performance in a match. E.g. consider the following:

Scenario 1: Batsman scores 100 while all his team-mates score 90. Thus, Unni's Index=10. In the second innings, he scores zero while others average 20. Thus, Unni's index = 0. Combined Index in the match =(10+0)/2=5.

Scenario 2: Batsman scores 50 while all his team-mates score 90. Thus, Unni's Index = 5. In the second innings, though, he scores 50 while others average 20. Thus, Unni's index = 2.5. Combined index in the match = (5+2.5)/2=3.75.

In both cases, the batman scored 100 runs in the match. However, Unni's index rates him higher in the first scenario. Is that acceptable? Well, that is a matter of opinion. Something similar happened at Mohali vs Aus this year. I guess VVS' contribution in that match (1 & 74*) will rate higher than SRT's (98 & 38) on this metric but, IMO, SRT's 136 runs in that match laid the basis for the win.

Posted by Abhi on (November 20, 2010, 4:23 GMT)

Ananth, Just another thought. The average ,like all stats , though not a perfect metric is at least a direct measure of "batsman vs. opposition bowlers" ...It doesn't include performance of "opposition" batting and bowling or "own" team bowling etc.

However, again average is best when used as a "peer ratio" since peers would face more or less similar bowling/pitches/conditions etc.

So,perhaps doing some sort of a "peer" analysis of "unni's metric" may be better? [[ Abhi Let us get this going before doing a Peer analysis. I would include the batsman's career years in the table so that people can do their own rough peer analysis. Ananth: ]]

Posted by Abhi on (November 20, 2010, 4:01 GMT)

Unni, I feel there is a slight flaw when you say that we are analysing 'the contribution of a batsman in the matches'... This bit has previously been adequately covered in "% of own team runs scored". [[ From what I can see there is a strong correlation between % of Team runs and the (Unni) Innings index. Ananth: ]]

What happens here is when the "opposition" team average is included you are not only including the batting quality of "opposition" team but effectively also including an "own" bowling vs "opposition" bowling factor.

Posted by Abhi on (November 20, 2010, 3:53 GMT)

Ananth,Unni Right ho. I think Hayden does well because the bulk of his run with the Aussie team was for most part when they were both right at their peak- especially the bowling.

Hayden played just a handful of matches in the '90s when Aus were'nt yet totally dominant- Just 7 matches to be precise in the '90s where he fared poorly, averaging 21.8.

Then a whopping 85 matches from 2000-07 (arguably the Aussie peak), where he averaged 55.7.

Then 11 matches avg. 32.7 from 2008 to retirement… Must say a well timed retirement before it really started hurting his stats.

So, the great bulk of his career with him and Aus at their peaks would have resulted in simultaneously for the most part having the additional effect of the peak Aussie bowling lineup beating up on the opposition- thereby effectively reducing the averaging of opposition batsmen. Also being an opener- he had the additional "luxury" of getting full "play" in his innings.

As rgds.Lara,Flower, Chanders etc. generally obvious. Lara carried the WI batting in the 2000s, Flower in the 90s and Chanders has always been "robin" to everyone – First Lara and now seemingly Gayle.

Posted by unni on (November 19, 2010, 17:16 GMT)

@Abhi : Your point is valid. However, we have to be clear with what aspect we are analyzing. Here it is only 'the contribution of a batsman in the matches'. Hence if a batsman was in a poor team definitely he will have higher number. Definitely this cannot be used to compare 'how good a batsman is' (whatever it is ;-) ). [[ Unni is right. Also the minute I open the door to Other batsmen quality, we have to listen to others who would want Result, Home/Away, BowlingQuality etc. Ultimately any such add-on table should be used to derive additional insights, not to say that "my batsman is superior to your batsman". I will make sure that the necessary toning down of conclusions is done. Ananth: ]]

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ABOUT THE AUTHOR

Anantha Narayanan
Anantha spent the first half of his four-decade working career with corporates like IBM, Shaw Wallace, NCR, Sime Darby and the Spinneys group in IT-related positions. In the second half, he has worked on cricket simulation, ratings, data mining, analysis and writing, amongst other things. He was the creator of the Wisden 100 lists, released in 2001. He has written for ESPNcricinfo and CastrolCricket, and worked extensively with Maruti Motors, Idea Cellular and Castrol on their performance ratings-related systems. He is an armchair connoisseur of most sports. His other passion is tennis, and he thinks Roger Federer is the greatest sportsman to have walked on earth.

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