A complex network analysis approach to compare the performance of batsmen across different formats

Abstract

Batsmen are accorded a certain precedence for better batting ability over their peers. The batsmen in cricket are assessed mostly based on their batting average. However, comparing players by batting average over different timelines does not yield the appropriate results, as the batting productivity of a particular player varies in unique ways across the different formats of the game. Using batting averages for comparison does not include factors such as the speed of scoring runs and the frequency of milestones achieved. The objective of this study is to present an effective knowledge-based mechanism for judging and comparing the batting strength of players in different formats of cricket. This methodology uses a complex network consisting of effective features that are subsequently integrated to formulate a Batting Precedence Score, which is further incorporated into an efficient Batting Precedence Score algorithm. In addition, we created a structured World Wide Batsman Dataset (WWBD) for our analysis based on the ESPN Cricinfo dataset. The results of extensive experiments demonstrate that the proposed method provides promising insights. The batting precedence of the proposed method is further compared with those of existing methods, and the proposed method displays better results.