Evaluation and optimization of basketball tactics training effect in physical education: Application research using Decision Tree (DT) algorithm

Abstract

In this study, the decision tree (DT) technique is developed to assess the basketball strategies’ training impact on physical education (PE). The recommended DT method effectively guesses the tactics of two teams based on the locations of basketball players with only a small amount of training data. Next, using data concerning ball possession, the interaction of these teams’ tactics, and the distinctive features of basketball strategies, the DT approach changes the team’s strategies. Therefore, effective findings from prediction could be produced because the suggested DT approach predicts the team strategies that meet these requirements. The suggested DT approach is implemented using the Python platform to analyze efficiency in terms of several metrics. Additionally, the DT method’s effectiveness is contrasted with that of other approaches. Based on the results of the experiments, the suggested approach outperforms the current approaches in assessing the impact of basketball strategy instruction in physical education.