The predictive power of game-related statistics for the final result under the rule changes introduced in the men’s world water polo championship: a classification-tree approach

Abstract

ABSTRACTThe objectives of this study were (i) to compare water polo game-related statistics by match outcome (winning and losing teams) after the application of the new rules, and (ii) to develop a classification tree model explaining the performance in elite men’s water polo. Forty-eight matches that were played in the 18th FINA World Championships were analysed. The dependent variable was match outcome and the independent variables were the game-related statistics. To determine the differences between the winning and losing teams, a parametric (paired-sample t-test) or non-parametric (Wilcoxon signed-rank test) test was applied, depending on whether or not the variable satisfied normality. The effect sizes (ES) of the differences were calculated. In order to determine which variables best predict the final outcome, a decision tree was constructed. This was a tree based on the supervised learning method called QUEST (Quick, Unbiased, Efficient, Statistical Tree). Ten variables differentiated between winning and losing teams (ES ≥ 0.80): four were related to the effectiveness of throwing, three to the effectiveness of the goalkeeper, and three to other actions. The decision tree correctly classified 83.9% of the teams with the variables GB shots, actions goals, time-outs, and steals.