A Novel Method to Choose the Best Playing 11 for a Cricket Team Using a Machine Learning Algorithm

Abstract

Team sledging is a crucial role of team management in cricket because it helps the coach and skipper win the match. Depending on the ground conditions, the player's performance against the opposition and the recent form is to take into account when choosing the XI playing. Machine learning algorithms can improve automatically through experience and data utilization. This research paper aims at determining whether the player will perform well or not in this match. Here, we applied the random forest classification algorithm as a model for the formation and testing of sample data for forecasting. The following variables are considered for analysing the example data set: Player Name, Opposing Team, Location, Runs Scored, Wickets Taken, Innings Batted, Runs Conceded, and Performance. Our model is measured using evaluation parameters such as accuracy, accuracy, recall, f1-score and support. In our model, we use 70 per cent of the data for training and 30 per cent for testing. Using our model, we get 100% accuracy when it comes to predicting results. We visualised each player's performance in each venue using the matplotlib tool, including how many points each player scored there. As a result, the proposed approach minimizes the team selection workload of team management, coach and skipper to choose the best XI game.