Machine learning-based Selection of Optimal sports Team based on the Players Performance

This paper is about a model that can select best playing 11 in the Indian cricket team. The performance of each player depends on several factors like the pitch type, the opposition team, the ground, and several others. The proposed model contains data from the One Day International of the past several years of team India. The dataset used for this model created using data from trusted sites like espn.com. This method is distinct in the sense that it gives you a 360-degree view of the player's skill set, be it, batting, bowling, and fielding. The vital part of this model is to find the best all-rounder player. Random forest algorithm used for predicting performance. The player performance classified into several classes, and a random forest classifier used to predict the player's performance. This model gives 76% accuracy for batsmen, around 67% accuracy for bowlers, and 95% for an all-rounder. A model is developed with some extra features like weather, matches played that have not considered in any existing model. Using this model, the best team can be selected to play in given conditions.