A machine learning approach to analyze ODI cricket predictors - Jayalath, K. P. (Journal of Sports Analytics, 2018)
As one-day international (ODI) games rise in popularity, it is important to understand the possible predictors that affect the game outcome. The home-field advantage, coin-toss result, bat-first or second, and day vs day-night game format are such popular variables being considered in the cricket literature. This article focuses on a comprehensive study of quantifying the significance of those important predictors via graphical `classification and regression tree` (CART) and the popular logistic regression approaches. This study reveals the importance of the home-field advantage for major cricket playing nations in one-day international games but questions the uniformity of such factors under different playing conditions. Importantly, the home-field advantage is investigated further based on the opponent`s geographical location. Conclusively, the CART approach provides interesting and novel interpretations for popular predictors in ODI games.