Research on the Application of Intelligent Computing Methods in the Analysis of Sports Competitive Tactics in an Interdisciplinary Collaborative Environment

Abstract

Traditional tactical analysis in competitive sports relies heavily on individual experience and event sensitivity, and lacks the full utilization of competitive event data. Relying on the inspiration of interdisciplinary synergistic ideas, tactical knowledge base and gray situation decision-making methods are mined in this study. Among them, the construction of the tactical knowledge base for sports and athletics is mainly accomplished through knowledge learning based on state space representation, and the acquired tactical knowledge representation states are presented into the tactical knowledge relationship knowledge base in a complete way with the help of mapping of domain ontology. The gray situation decision-making method, on the other hand, decides the theoretically optimal tactics for each tournament stage by abstracting the decision-making events in the knowledge states, and decides the tactics through situation measurement, measurement unification, and optimal ordering. In the study of a women's volleyball tournament, it was found that the frequency of “one attack” tactics in each stage of the tournament was as follows: strong attack (66.64%) > fast attack (18.53%) > three-dimensional attack (11.86%) > two attacks (2.97%). Gray decision-making calculates the effect measure of strong attack tactics corresponding to the win or loss in the previous game as (0.55875, 0.5085), which provides a visual reference for selecting tactics in each offensive round. The gray situation decision-making method built on a tactical knowledge base is powerful as an interdisciplinary and synergistic tool for strategic analysis of competitive tactics in sports.