Player Performance Analysis Using Various Data Mining Approaches

The usage of machine learning in sports is increasing day by day. Cricket, as a sport centered around statistics and performance metrics, presents an abundant repository of data that holds the potential to reveal valuable insights into players’ skills and contributions during matches. Machine learning models analyze data produced from sports and provide game insights. Machine learning models are helpful in analyzing player performance and winner prediction. These models can also be used in players’ injury management and prevention. The data evaluated by machine learning models can guide the recruiters at the time of selecting the best team. The results of this study provide a sizable contribution to the body of information expanding on the revolutionary potential of machine learning in cricket. The idea behind this is to be able to forecast future events such as how many wickets a bowler will pick up and runs a batsman will accomplish.