TY - JOUR AU - AkhilAmudala, P Usif Dada Khan, SyamKiran Gannamani and Siva Shanmugam G, PY - 2020/05/15 Y2 - 2024/03/29 TI - Efficient Approach To Predict Performance Of Players Using Machine Learning JF - International Journal of Advanced Science and Technology JA - IJAST VL - 29 IS - 12s SE - Articles DO - UR - http://sersc.org/journals/index.php/IJAST/article/view/21939 SP - 314 - 324 AB - Selecting a player in a team sport is paramount task in whichever sport we take. Opponent team, venue, and current form are different factors that are used to validate the performance of the sports person in cricket. A Squad of 15 players is picked by the team management. Coach and captain select 11 players from the squad to play in the field. The classification problems like how many runs can a batsman make and how many wickets a bowler can get is predicted in this paper. We’ve used naive Bayes, random forest, multi-class SVM and decision tree classifiers to create predictive models for two classification problems. As a result, the most accurate one among them was Random Forest classifier. ER -