Evaluation Model of Improper Exertion and Injury in Track and Field Based on Big Data Network

Abstract

In order to reduce or avoid ankle joint injury in the training process of track and field athletes and take effective preventive measures, this paper constructs the evaluation model of ankle joint injury prevention measures in high-intensity track and field training based on big data and fuzzy comprehensive evaluation method. Through this model, we can find out the problems in training and put forward effective preventive measures. At the same time, according to the influencing factors of ankle joint injury in track and field training, this paper analyzes and constructs the evaluation index system of ankle joint injury prevention measures. The results show that big data technology combined with fuzzy comprehensive evaluation method can effectively obtain the effect of preventive measures in track and field training. At the same time, combined with the two-level early-warning mechanism, this paper establishes a dynamic chain model of track and field sports injury etiology early warning, which provides the relevant theoretical basis for the development of track and field athletes' injury early warning system based on data mining technology and mobile computing technology.