Statistical Analysis of Cricket Leagues Using Principal Component Analysis

Abstract

Any sport has statistics and cricket is one of the sports where statistics are significantly important because, on the based on these statistics, players are ranked. These statistics include individual runs, wickets, and highest scores, etc. Based on statistics, players are selected for any tournament around the world. This research uses Principal Component Analysis by evaluating cricket facts and figures. This analysis tests the precise co-variation among different measurements relating to the batting and bowling abilities of players in the Pakistan Super League PSL T-20 (2016-2019) and IPL T-20 (2016-2019) utilizing the progressed factual system Principal Component Analysis. In the current investigation, PCA was utilized to rank the top ten best-performing batsmen and bowlers of the PSL and IPL. Principal Component Analysis is a dimension reduction technique that is used to reduce dataset dimensions into smaller variables. We can presume that batting ability rules over bowling capacity. This exploration is the first report in Pakistan that features the highlights of the PSL and IPL.