Performance Analysis of ML Algorithm in Cricket Score Prediction

Abstract

Cricket score prediction has emerged as a significant application of machine learning due to the increasing availability of structured match data and the growing interest in sports analytics. This study focuses on the performance analysis of various machine learning algorithms in predicting cricket scores, particularly in limited-overs formats such as One Day Internationals (ODIs) and T20 matches. The primary objective is to evaluate and compare the accuracy, efficiency, and reliability of different predictive models using historical match data.
The dataset typically includes features such as team statistics, player performance metrics, venue conditions, weather factors, toss results, and match situations (overs, wickets, run rate).