Predicting the Outcome of Cricket Matches
The game of Cricket, especially its limited overs version, is full of glorious uncertainties, which is what makes it so much fun to watch and follow. Because there are so many factors that determine the outcome of a match – team compositions, weather, pitch conditions, etc, it may appear on the surface that predicting the outcome of cricket matches might be hard. However, in this article we present an approach that has been used to predict the outcome of Cricket matches with at least two-thirds accuracy in the ongoing World Cup. The Methodology Our current approach is based solely on the team compositions. First, our method calculates a score for each player of the team based on their past performances. This score is calculated by looking at the one-on-one match-up between the batsmen and the bowlers in their previously played matches (more on this later). For a given match, we sum up the total score of the top eleven players in each team, and the resulting win probability of a team is proportional to its total score. The team with the higher win probability is the predicted winner of that match. As for computing the player scores, the objective is two fold. First, it should be able to combine both the batting and the bowling statistics of a player into one score that can be used in our prediction algorithm. The second is that it should be able to adjust the score of a player based on the quality of the opposition that player faced. That is, a player’s score should not be higher just because he boosted his statistics by playing against weaker teams. To ensure that both these objectives are met, we employ a “page-rank” type of an algorithm for computing the player scores, that uses the batsman versus bowler match-up data from previously played matches. More details about this methodology can be found on the Cricmetric website. For computing player scores for predicting the outcome of Cricket World Cup matches, we used the data of the ODIs played since April 1, 2004. Prediction accuracy For the World T20 tournament in 2014, our prediction method correctly predicted 15 out of 23 matches of the league stage of the tournament, for a success rate of 65%. It did quite well in the league stage of the tournament, correctly predicting the outcome of 15 out of 20 matches, but got all the three predictions wrong for the knock-out stage of the tournament. For the ongoing Cricket ODI World Cup 2015, so far we have correctly predicted 21 out of the first 31 matches of the tournament. A complete list of the previous and the future predictions (as of March 8, 2015) for the Cricket World Cup are given in the table below. Date Team 1 Team 2 Cricmetric’s prediction Actual result Feb 14, 2015 New Zealand Sri Lanka New Zealand (70%) New Zealand Feb 14, 2015 Australia England Australia (56%) Australia Feb 15, 2015 South Africa Zimbabwe South Africa (76%) South Africa Feb 15, 2015 India Pakistan India (59%) India Feb 16, 2015 West Indies Ireland West Indies (56%) Ireland Feb 17, 2015 Scotland New Zealand New Zealand (78%) New Zealand Feb 18, 2015 Bangladesh Afghanistan Afghanistan (80%) Bangladesh Feb 19, 2015 U.A.E. Zimbabwe Zimbabwe (70%) Zimbabwe Feb 20, 2015 England New Zealand New Zealand (59%) New Zealand Feb 21, 2015 West Indies Pakistan Pakistan (54%) West Indies Feb 21, 2015 Australia Bangladesh Australia (64%) ABANDONED Feb 22, 2015 Afghanistan Sri Lanka Sri Lanka (69%) Sri Lanka Feb 22, 2015 India South Africa South Africa (62%) India Feb 23, 2015 England Scotland England (73%) England Feb 24, 2015 West Indies Zimbabwe Zimbabwe (53%) West Indies Feb 25, 2015 U.A.E. Ireland Ireland (60%) Ireland Feb 26, 2015 Scotland Afghanistan Afghanistan (62%) Afghanistan Feb 26, 2015 Sri Lanka Bangladesh Sri Lanka (70%) Sri Lanka Feb 27, 2015 South Africa West Indies South Africa (70%) South Africa Feb 28, 2015 Australia New Zealand Australia (52%) New Zealand Feb 28, 2015 U.A.E. India India (78%) India Mar 01, 2015 England Sri Lanka Sri Lanka (59%) Sri Lanka Mar 01, 2015 Pakistan Zimbabwe Zimbabwe (54%) Pakistan Mar 03, 2015 South Africa Ireland South Africa (81%) South Africa Mar 04, 2015 Pakistan U.A.E. Pakistan (68%) Pakistan Mar 04, 2015 Australia Afghanistan Australia (62%) Australia Mar 05, 2015 Scotland Bangladesh Bangladesh (58%) Bangladesh Mar 06, 2015 West Indies India India (62%) India Mar 07, 2015 Pakistan South Africa South Africa (71%) Pakistan Mar 07, 2015 Ireland Zimbabwe Zimbabwe (63%) Ireland Mar 08, 2015 Afghanistan New Zealand New Zealand (60%) New Zealand Mar 08, 2015 Australia Sri Lanka Sri Lanka (57%) Australia Mar 09, 2015 England Bangladesh England (63%) Not started Mar 10, 2015 India Ireland India (69%) Not started Mar 11, 2015 Scotland Sri Lanka Sri Lanka (78%) Not started Mar 12, 2015 South Africa U.A.E. South Africa (84%) Not started Mar 13, 2015 New Zealand Bangladesh New Zealand (63%) Not started Mar 13, 2015 Afghanistan England England (59%) Not started Mar 14, 2015 India Zimbabwe India (59%) Not started Mar 14, 2015 Australia Scotland Australia (73%) Not started Mar 15, 2015 U.A.E. West Indies West Indies (69%) Not started Mar 15, 2015 Ireland Pakistan Pakistan (62%) Not started
The game of Cricket, especially its limited overs version, is full of glorious uncertainties, which is what makes it so much fun to watch and follow. Because there are so many factors that determine the outcome of a match – team compositions, weather, pitch conditions, etc, it may appear on the surface that predicting the […]
The game of Cricket, especially its limited overs version, is full of glorious uncertainties, which is what makes it so much fun to watch and follow.
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Shashi Mittal is the co-founder of Cricmetric, which he conceptualized with a fellow student when he was a graduate student in the Operations Research Center at Massachusetts Institute of Technology. He is currently based in Seattle, USA.