The Application of Information Technology for Athlete Data Analysis and Automatic Generation of Training Plans

Abstract

In response to the demand for scientific training of sports athletes, the author combined data mining technology to study an improved sports training mode decision support evaluation system. In this regard, the author analyzed the characteristics of association rule algorithms and elaborated on their functions in data preprocessing, data mining, and pattern evaluation. Based on the software design of decision support systems, the characteristics of system operation were analyzed. At the same time, the author focused on explaining the data fusion processing of association rules in sports evaluation decision support systems, and proposed an improved Apriori algorithm output mode to improve the effectiveness of system evaluation. Compared with other algorithms such as Apriori, DC Apriori and Apriori, this algorithm has higher reliability. When the minimum confidence is increased, the advantage of prior information will gradually disappear, and the final result will be obtained. Experimental results show that this method can effectively provide support for sports training decision-making.