Best Eleven Forecast for Bangladesh Cricket Team with Machine Learning Techniques

Cricket is one of the most well-known team sports in the world. Machine learning algorithms have a significant impact on sports analysis, and cricket is no exception. With the help of Machine learning algorithms, we may create new methodologies, predict the outcome of a game, measure the player’s performance, and pick the squad for the next matches by anticipating the player’s performance. As a result, predicting individual and team performance became an intriguing topic for researchers, and only a few works have been done on it, with a few downsides. This study attempts to anticipate the most suitable players for a particular game to be organized. To predict the perfect players for the match to be played, we suggest a machine learning approach. This study and project aimed to identify the squad of eleven players for the Bangladesh (ODI) cricket team. We forecast the squad for Bangladesh (ODI) cricket team using Support Vector Machine, Naive Bayes, and Random Forest machine learning algorithms. We obtained 94% accuracy for the batsman and 93% for the bowler.