Team selection after a short cricket series

Abstract

The selection of a cricket team cannot be fair unless the best available performance measures are used. The traditional batting average can be very unrealistic, especially in the case of a small number of scores with a high proportion of not out scores. In the present study the focus is on using the most suitable measures for the selection of a team after a small number of matches had been played. Provision is made for the fact that match conditions may influence the scoring rate of batsmen. These measures are used for illustration purposes to select a team from the players who played in the International Cricket Council (ICC) Champions Trophy 2009 One-Day International (ODI) Series. It is shown how an integer programming method can be used for the selection process. The approach is that a well balanced cricket team should include different kinds of specialists, namely batsmen, bowlers, all-rounders and a wicket-keeper. A selection committee may be able to rank batsmen in order of batting ability and bowlers according to bowling ability, but when it comes to all-rounders it is not so simple. The fact that an all-rounder is, by definition, a good batsman and also a good bowler, makes it difficult to rank allrounders. Furthermore, how many of each specialist type should be selected? The purpose of this paper is to show how integer optimisation, an objective scientific method, can be used to aid in selecting a cricket team. Guidelines are also given for the selection of a team if career performance data have to be used.

A Consistency Adjusted Measure for the Success of Prediction Methods in Cricket

“…The average batting performance measure of the opponents of the i th team is defined by, and the average bowling performance measure of the opponents of the i th team by, By letting for i = 1, 2,…, 9, the average ({a i }) = 1 with standard deviation of {a i } indicated by STA. The method explained in [21] is used to transform {b′ i }, {c′ i } and {d′ i } into {b i }, {c i } and {d i }, each set having the same average of 1 and the same standard deviation, STA.…”

Comparison of performance at the 2007 and 2015 Cricket World Cups

“…Any quantification of the differences between more and less successful teams ultimately relies on the relative strength of those teams. Researchers have proposed computational and statistical modelling techniques to more fairly select or better optimise team selection, 14 and also project how differences in relative team strength may influence the magnitude of a victory, 15 which is important for anyone interested in betting strategies.…”

A new Net Resource Factor Based Alternative Method to Calculate Revised Target in Interrupted One Day Cricket Matches

“…Detailed list of input and output measures to calculate player's efficiency is given in Table 1. For bowlers, Sharp et al [15] and Lemmer [16] used three parameters like bowler's economy rate, bowling average, and strike rate as outputs. Apart from these, number of wickets has been taken as additional output measure.…”