PREDICTING PLAYER PERFORMANCE USING FUTURE RANKING SYSTEM
Indraneel Ray, Naren Rajendran, S. Sharanya
Cricket is one of the most popular team sports, with billions being spent each year for competitions. Predicting the match outcomes and player performance can help the teams to move a step towards success. The advent of Artificial Intelligence (AI) and Machine Learning (ML) has changed the perception of games. This article aims to predict the performances and rank the players in Indian Premier League (IPL) teams using ML techniques. Career statistics, team performance including batting and bowling performances have been taken into account for predicting more accurate outcomes. The methodology proposed in this paper can guide the coaches to improve in the deficient area, which will contribute to overall team performance. A comparative study done in this paper indicates that Random Forest proves to a promising ML technique in game prediction.
Volume: Volume 24
Issues: Issue 8
Keywords: Regression, Feature Ranking, Player Performance.