IIIT Hyderabad Publications
Predicting the Outcome of ODI Cricket Matches: A Team Composition Based Approach
Authors: Madan Gopal Jhawar,Vikram Pudi
Conference: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2016 2016)
Location Conference Center, Riva del Garda.
Report no: IIIT/TR/2016/32
With the advent of statistical modeling in sports, predicting the outcome of a game has been established as a fundamental problem. Cricket is one of the most popular team games in the world. With this article, we embark on predicting the outcome of a One Day International (ODI) cricket match using a supervised learning approach from a team composition perspective. Our work suggests that the relative team strength between the competing teams forms a distinctive feature for predicting the winner. Modeling the team strength boils down to modeling individual player’s batting and bowling performances, forming the basis of our approach. We use career statistics as well as the recent performances of a player to model him. Player independent factors have also been considered in order to predict the outcome of a match. We show that the k-Nearest Neighbor (kNN) algorithm yields better results as compared to other classifiers.
Full paper: pdf
Centre for Data Engineering
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