Predicting the names of the best teams after the knock-out phase of a cricket series.
Cricket players' performances can best be judged after a large number of matches had been played. For test or one-day international (ODI) players, career data are normally used to calculate performance measures. These are normally good indicators of future performances, although various factors influence the performance of a player in a specific match. It is often necessary to judge players' performances based on a small number of scores, e.g. to identify the best players after a short series of matches. The challenge then is to use the best available criteria in order to assess performances as accurately and fairly as possible. In the present study the results of the knock-out phase of an International Cricket Council (ICC) World Cup ODI Series are used to predict the names of the best teams by means of a suitably formulated logistic regression model. Despite using very sparse data, the methods used are reasonably successful. It is also shown that if the same technique is applied to career ratings, very good results are obtained.
a Department of Statistics , University of Johannesburg , Johannesburg , South Africa.
Hermanus Hofmeyr
HH
Lemmer
D056352:Athletes / Q000706:statistics & numerical data*; D054874:Athletic Performance / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D013177:Sports / Q000706:statistics & numerical data*