Research on the Design of Sports Injury Estimation Model based on Big Data

Abstract

In order to accurately estimate the sports injury risk of athletes during sports training, this paper divides the sports injury risk into three levels, designs the sports injury estimation index, selects RBF neural network as the model framework, and uses big data analysis technology to construct the sports injury estimation model. Bayesian model and Lagrange model are selected as the control group to test the accuracy and efficiency of this model in sports injury estimation. The test results show that compared with other models, this model can improve the accuracy and efficiency of sports injury estimation significantly, and can be used as a sports injury estimation tool.