Modeling the joint influence of key factors on score contribution and ball utilization in limited-overs cricket for ranking player and team batting performance

Abstract

This study develops a modeling framework to evaluate both player and team batting performances in One Day International (ODI) and Twenty20 (T20) cricket formats. The model jointly analyzes two key measures of batting performance; score contribution and ball utilization. A joint beta mixed-effects model was fitted using the PROC NLMIXED procedure in SAS to capture the inherent relationship between productivity and efficiency that traditional univariate models fail to represent effectively. At the player level, the model identifies significant predictors of batting success including match strike rate, batting position and player experience. These variables consistently influence individual outcomes and their joint estimation of score contribution and ball utilization provide a more accurate and interpretable understanding of batting behavior. This framework has practical applications in player ranking, talent identification and decision-making in cricket analytics. At the team level, the findings indicate that wickets taken and run rate emerge as the key predictors of team batting performance. Run rate has a positive influence on performance in both formats highlighting the importance of scoring efficiency. The joint beta model provides more accurate and reliable estimates by jointly analyzing correlated performance measures rather than modeling them separately.