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Finally I have come around to my first T20 analysis. I had to do some serious T20 ratings analysis work related to another project and as part of that work, I looked at T20 matches from a totally different angle. One aspect of this analysis was to determine a reasonable target score for the first innings (the target score for the second innings is no problem, even when the learned professors, M/s Duckworth and Lewis come in with their umbrellas!). The team’s achievement in terms of exceeding or falling short of the dynamically computed target score is determined to compute one segment of the individual ratings. It also allows me to allocate the credits between bowlers and batsmen.
Let me add that my database, current upto the West Indies - England game, is limited to T20 International matches and as of now I have no intention of building a Database of other club-based T20 matches.
First some facts about T20 matches. Let me say that I have completely ignored team strengths, pitch conditions et al since there is not enough data and in this short version of the game, there is lot more evening out between the two teams.
1. A total of 84 matches have been played and completed. Out of these, 4 have been tied. 2 matches outside these 84 have been washed out.
2. 34 (out of 80) matches have been won by the team batting first. This represents 42.5% of the completed matches. One of these wins has been through D/L method.
3. 46 (out of 80) matches have been won by the team chasing. This represents 57.5% of the completed matches. One of these wins has been through D/L method.
4. Out of these 46 matches, the top 4 run chases have been against scores of 165 and above. These four succesful run chases are detailed below. In other words, any team scoring 165 and above has a 90+ % chance of winning the game. This seems to be true irrespective of the relative team strengths. It is also possible that the weaker team might bat first more often than not.
020 2007 Win 205/ 6 (20.0) Lost to Saf 208/ 2 (17.4) at Wanderer's, Jo'burg 082 2009 Slk 171/ 4 (20.0) Lost to Ind 174/ 7 (19.2) at Premadasa, Colombo 016 2007 Win 169/ 7 (20.0) Lost to Eng 173/ 5 (19.3) at Oval, London 047 2007 Aus 166/ 5 (20.0) Lost to Ind 167/ 3 (18.1) at Brabourne, Mumbai
5. It is a reasonable assumption to make that the team batting first should set themselves a Target score of 165 runs to have a 90+ % chance of winning. Anything more would obviously further increase the chance of winning. However we are not looking at a Target score with 100% chance, which, at the current moment is 206.
6. If we drop the number from 165 to 160, the number of losses is more than doubled since 5 more matches are won by batting teams chasing 164, 164, 164, 162 and 162 successfully. The win % drops to 80% so there is a need to retain the Target score at 165.
It is possible that in the next 5 matches, 170+ scores would have been chased. However that does not make the idea of working on a Target score invalid and as things stand, 165 seems to be a very good number for a captain to write on the team sheet.
The reason this score is very relevant is because of what happened in the two T20 matches between New Zealand and India. Each time India had an explosive start, looked good to score 200, tried to score 200 and finished with 162 and 149. Both scores were chased down with ease, although New Zealand were too cautious in the middle overs in the scond T20 and almost threw the match away. They should have won more comfortably with the explosive start set by the openers.
The importance of not aiming for too much cannot be over-emphasized especially in T20 matches. In T20 it is paramount for the captains to understand the nuances of the game. It is possible that Dhoni is aware of this. However his batsmen, Gambhir, Sehwag, Yuvraj, Sharma et al tried to attack without a clear understanding of the par score.
In ODIs, nowadays even scores of 300+ are chased quite comfortably. However even there a reasonable target score should be aimed at. The 100% winning score is 435. However the par Target score might very well be 285. But it must be remembered that data is available for 2822 matches for us to make a facts-based determination of a par Target score for a venue.
Just to sum up the first batting wins. Out of the 34 wins, 8 teams have won by putting up a total of 200 and above, 11 by posting wins of between 180 and 200, 10 by posting between 150 and 180 and 4 have been bowling wins with sub-150 totals. One has been an amazing defence by Ireland of a total of 43 for 7 in a D/L match.
It is impossible to infuse the other Test/ODI parameters such as Ground/Pitch conditions, Team strengths, Average scores et al because of the low number of matches, the absence of any meaningful statistics and the very nature of the game.
Out of the 86 T20 matches, a whopping 34 have been played in South Africa, mainly because of the 2007 WC, in addition to one washed out match. 11 matches have been played in Ireland, in addition to one washed out match. 10 matches have been played in New Zealand. 8 matches have been played in Canada, all in one centre.
Wanderer's has staged the maximum of T20 matches, 16 in all. Just to give the readers an idea of the analyst's nightmare of determining a target score at Wanderer's, I have given below the 16 first innings scores. These seem to move like a yo-yo although there seems to be a recent trend for lower scores.
133, 201, 126, 129, 205, 164, 260, 164, 190, 189, 164, 147, 157, 129, 131 and 118.
Note: I stayed up to watch the interesting T20 match between Australia and South Africa. Australia scored 166 (just passing the par Target score mentioned) and lost a very close match. Strike 1 against me, I suppose.
This refers to the points raised by Aneesh and Kieran. They have correctly questioned my 90+% figure.
First let me say that the 90+% is based on all instances of chasing team winning, which is 46. Out of these 46, only 4 chases have been of scores of 165 and above. Thus the figure of 90% came in.
However stricly speaking, both Aneesh and Kieran are correct. My sample should be the teams which crossed 165 and not the successful chases. Let me work out that figure below.
26 teams crossed 165 (barring the last Saf-Aus match, which has been excluded for sake of consistency). Out of these, 4 teams lost and the other 22 won. So the winning % is 84 and not 90.
Hence I am going to change my Target score to 170, which would lead to 24 wins and 2 losses (win % of 92).
My thanks to Aneesh and Kieran.
T20 Batsman Strike Rates (Min 200 runs) - (Gokul)
No Batsman Ctry Mat Runs Balls S/R BatAvg
1 Symonds A Aus 13 337 198 170.2 56.17 2 Yuvraj Singh Ind 9 262 159 164.7 32.75 3 Gayle C.H Win 7 261 162 161.1 37.29 4 Oram J.D.P Nzl 13 293 187 156.6 36.62 5 Jayasuriya S.T Slk 11 341 221 154.3 34.10 6 Imran Nazir Pak 10 201 134 150.0 25.12 7 Sehwag V Ind 11 223 154 144.8 20.27 8 Pietersen K.P Eng 15 375 260 144.2 26.79 9 Hayden M.L Aus 9 308 214 143.9 51.33 10 Jayawardene M Slk 11 210 147 142.8 23.33 11 Duminy J.P Saf 9 256 181 141.4 32.00 12 Gilchrist A.C Aus 13 272 192 141.6 22.67 13 Morkel J.A Saf 15 270 193 139.9 24.55 14 Collingwood P.D Eng 15 344 246 139.8 24.57 15 Masakadza H Zim 7 258 190 135.7 36.86 16 Aftab Ahmed Bng 9 215 161 133.5 26.88 17 Ponting R.T Aus 14 375 283 132.5 34.09 18 Gibbs H.H Saf 13 225 171 131.5 18.75 19 Shah O.A Eng 11 241 186 129.5 26.78 20 Taylor R.L Nzl 17 323 253 127.6 21.53 21 Misbah-ul-Haq Pak 14 398 312 127.5 56.86 22 Smith G.C Saf 12 364 286 127.2 36.40 23 Gambhir G Ind 11 328 259 126.6 29.82 24 Kemp J.M Saf 8 203 160 126.8 50.75 25 McCullum B.B Nzl 21 582 464 125.4 34.24 26 Shoaib Malik Pak 16 383 307 124.7 31.92 27 Younis Khan Pak 15 260 223 116.5 18.57 28 Styris S.B Nzl 15 272 240 113.3 19.43 29 Dhoni M.S Ind 12 215 207 103.8 23.89 30 Salman Butt Pak 12 266 288 92.3 26.60
Anantha Narayanan has written for ESPNcricinfo and CastrolCricket and worked with a number of companies on their cricket performance ratings-related systemsFeeds: Anantha Narayanan
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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.