Cricket Players Performance Prediction and Evaluation Using Machine Learning Algorithms

Machine learning (ML) techniques are used to complete the difficult tasks in a timely manner. Presently, ML models are used for decision making in a different sectors like healthcare, agriculture, weather forecasting analysis, transportation, sports etc. Sports plays vital role in a human life and it involves crores of investment. Hence, player’s performance analysis is an essential and required task in sports sectors. In a proposed system, the performance of cricket players will be analyzed and determine the performance of specific athletic to form team and plan for training. By using linear regression, K-means, and random forest models etc. the performance of cricket players are analyzed. Cricket players’ performance can be predicted and regressed with a linear line using linear regression. The K-means classification divides the variables into ‘n’ clusters based on the same player characteristics. The clusters accuracy over test data is then validated using random forest based classification. Based on this analysis, the best players on the list are selected for team formation and increase the likelihood of winning matches. This work will aid in the preparation of the player rank for gamerelated applications.