Application of Big Data’s Association Rules in the Analysis of Sports Competition Tactics

Abstract

The problem of low accuracy and poor ability of tactical analysis of current tournament analysis strategy, to improve the statistical intelligent analysis ability of the tactical analysis of sports games, it is necessary to carry out the tactical analysis and statistics of the sports games, and put forward a game strategy analysis and statistical model based on a large data association rule mining. firstly, a data acquisition and diagnosis analysis model of a sports game strategy analysis is constructed, and a sports game tactical analysis data information flow model is constructed, and the statistic characteristic quantity in the sports game tactical analysis is extracted, the method of fuzzy correlation fusion is used to analyze the interference of the statistical data in the tactical analysis of the sports game, and a plurality of known interference frequency components are removed. in that method, a large-data association rule mining algorithm is adopted to carry out statistical data identification and characteristic analysis in a sports game and tactical analysis, an optimization characteristic solution of the game and tactical statistical information analysis is established, and a self-adaptive optimization of the game and tactical statistical information analysis is carried out by adopting a simplified gradient algorithm, the feature analysis and data optimization recognition of the game tactics analysis are realized by combining the self-correlation feature matching method. The simulation results show that the method is used to carry out the tactical analysis of sports games and the accuracy of the statistics, so as to improve the ability of the tactical analysis of the sports games, so as to improve the effect of the competition.