Intelligent Computing based Soccer Sports Management for Effective Estimation of Match Outcome

The integration of intelligent computing with sports management can give new dimensions to sports globally. In this paper, a comprehensive study of major intelligent computing techniques for addressing various challenges and issues in sports management is presented. An experimental study has been conducted by implementing three machine learning techniques, i.e., SVM, Decision tree and Random forest for estimating the match outcome on different match scenarios. This experimental study has been performed on a standard dataset on English Premier League soccer tournament to estimation the match outcome. The estimation of match outcome in soccer is a difficult task as it is stochastic process and many probabilistic factors can affect the final results.