Analyzing and predicting the performance of players using machine learning

The ensemble method employs a combination of logistic regression and random forest classification to analyze cricket player performance. Using datasets from the Indian Premier League (IPL) and India T20 series, key performance metrics such as batting average and strike rate are examined. This strategic approach enhances the precision of player assessment, providing insights into individual proficiency as well as broader implications for team composition and match strategies. The research highlights the critical role of logistic regression and random forest classification in advancing cricket analytics.