Predicting the outcome of ICC cricket world cup matches

Abstract

The purpose of the study was to develop a model to predict the outcome of ICC Cricket World Cup ODI matches (Limited Overs) on the basis of first innings data. These probabilities can assist a team captain or management in considering a certain aggressive or defensive batting or bowling strategy for the next innings. The data was collected from last two world cup tournaments i.e. 2011 and 2015. Data of 98 matches were recorded, out of which 8 matches were not taken into consideration due to three reasons which were 1. Match Abandoned 2. Match Tied 3. Matches resolved by Duckworth Lewis Method. The dependent variable selected for this study was Match Outcome (Win/Loss). Team score, Total Wickets Lost, Toss, Runs Scored in Powerplay, Wickets lost in Powerplay, Team Run Rate and the Total number of Dot balls were selected as the predictor variables. For the purpose of this study only the first innings data was used and in statistical technique Binary Logistic regression was used to predict the outcome of a match (Win/Loss). It was found that the developed Logistic regression Model was significant. According to the statistical significance of the predictor variables, they were numerically weighted and can be used to predict the match outcome. Out of seven predictor variables only the variable Team score was included in the prediction model with coefficient of determination (R2) of.272 (Cox & Snell) and.363 (Nagelkerke). 72.2% of match results were correctly classified by the model.