Construction of Selection and Evaluation Algorithm for High-Level Tennis Students in Colleges and Universities Based on Random Matrix Model

The evaluation method of tennis students’ ability has an important influence on optimizing the selection and training of high-level tennis students. Based on the random matrix model theory, this paper constructs an evaluation algorithm for high-level tennis students in colleges and universities. Based on the literature and expert opinions, the model selects professional technical ability, knowledge learning ability, comprehensive development ability, and sustainable development ability as weighting factors and constructs the ability evaluation index system for high-level tennis students in colleges and universities. During the simulation process, the visualization system uses springboot, mybatis, and shiro as the back-end development framework to realize the modules of matrix management, role management, resource management, grade management, course management, student management, model management, etc. It adopts the MATLAB software platform to construct that the tennis learning evaluation includes 6 first-level indicators and 24 second-level indicators. The experimental results show that the final weights of the first-level indicators of tennis learning evaluation are as follows: tennis specific quality is 0.15, tennis sports skill is 0.3, tennis theoretical knowledge is 0.1, progress score is 0.15, attitude to learning tennis is 0.2, emotional performance and the spirit of cooperation is 0.1, and the results are visualized, which effectively improves the effectiveness of the random matrix algorithm in the field of selection evaluation.