The Application of Data Mining Algorithm Based on Association Rules in the Analysis of Football Tactics

In this paper, an improved association rule data mining algorithm is proposed, and by applying this algorithm to the analysis of football tactics, the training level of football players is improved. Firstly, the problem of mining association rules is explained, and the concept of support and confidence is defined in advance. Secondly, for a given transaction database and a target object, top K direct association rules can be extracted using our proposed algorithm. Finally, to verify the effectiveness, we choose the final match in European Cup 2008 (that is Spain vs Germany) as the testing data, and the toolbox Adobe Premiere Pro is exploited to obtain soccer ball possession and pass time, and the football tactical information from the data of two samples is mined based on association rule mining algorithm, and experimental results demonstrate that the proposed association rule data mining algorithm can effectively extract football tactics from the testing data.