A Simulator for Twenty20 Cricket. (12th March 2015)

• Record Type: Journal Article
• Authors: Davis, Jack; Perera, Harsha; Swartz, Tim B.
• Is Part Of: Australian & New Zealand journal of statistics. Volume 57:Number 1(2015:Mar.)
• Page Start: 55
• Page End: 71
• Publication Date: 2015-03-12
• Subjects: empirical bayes -- Markov Chain Monte Carlo; Statistics -- Periodicals; 519.5
• DOI: 10.1111/anzs.12109
• Languages: English
• ISSNs: 1369-1473

Abstract

Summary: This paper develops a Twenty20 cricket simulator for matches between sides belonging to the International Cricket Council. As input, the simulator requires the probabilities of batting outcomes which are dependent on the batsman, the bowler, the number of overs consumed and the number of wickets lost. The determination of batting probabilities is based on an amalgam of standard classical estimation techniques and a hierarchical empirical Bayes approach where the probabilities of batting outcomes borrow information from related scenarios. Initially, the probabilities of batting outcomes are obtained for the first innings. In the second innings, the target score obtained from the first innings affects the aggressiveness of batting during the second innings. We use the target score to modify batting probabilities in the second innings simulation. This gives rise to the suggestion that teams may not be adjusting their second innings batting aggressiveness in an optimal way. The adequacy of the simulator is addressed through various goodness‐of‐fit diagnostics.