Classification and Bayes Probability Approach for Evaluating the Performance of T-20 Batsmen
Abstract
This thesis presents a comprehensive analysis of the performance dynamics of top-ranked T20I batsmen in the ICC rankings. By considering factors such as player probabilities against specific teams, physical attributes like height and weight, and the implications of Bayesian probabilities, a multifaceted understanding of player achievements and their associations has been revealed. Through individual player probability examinations, distinctive insights emerged, such as Babar Azam's varying probabilities against different teams, highlighting the diverse challenges faced. Aiden Kyle Markram's strong performances against Sri Lanka underscored the opponent's influence on achievements. The study identified players excluded due to low probabilities against top-ranked teams, emphasizing strict "Man of the Match" criteria and the need for consistent excellence. Nicholas Pooran's mixed performance outcomes demonstrated the limitation of singular matches for assessing overall prowess. The investigation of height and weight correlation among T20I batsmen unveiled a lack of statistical significance, challenging assumptions. The classification tree visually portrayed attributes and performance across continents, affirming the influence of regional factors on player characteristics and achievements. This research underscores the complexity of player success and calls for a holistic evaluation of performances in diverse contexts.
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