The Application of Deep Learning in Sports Data Analysis

Main Article Content

Jin He

Abstract

In order to ensure that students have a deeper and more thorough understanding of knowledge and skills, the author takes deep learning as the direction and integrates it into the real-time evaluation of basketball classrooms, organically combining the two. Deep learning provides a new theoretical perspective and driving force for the optimization of real-time evaluation, and points out the direction for promoting evaluation effectiveness; The optimization of real-time evaluation provides a feasible path for achieving deep learning for students. After the implementation of the real-time evaluation plan between the experimental group and the control group, the comparison results of basketball skills tests were obtained: before and after the experiment, the experimental group’s 60 second self throwing and self grabbing, vigorous dribbling, comprehensive dribbling, teaching competitions, and teaching lectures all showed significant differences in test indicators; Before and after the experiment, the control group showed significant differences in the four test indicators of 60 second self throwing and self grabbing, vigorous dribbling, comprehensive dribbling, and teaching lectures. The teaching competition indicators also showed significant differences, all of which were improved. Comparison results of deep learning abilities: Before and after the experiment, there were significant differences in the dimensions of experimental combination ability and learning perseverance, while there were significant differences in the dimensions of communication ability, self-learning ability, and total score of deep learning ability; Before and after the experiment, there was a significant difference in the dimensions of control group work ability, while there was no significant difference in the dimensions of self-directed learning ability, learning perseverance, and communication ability. Overall, there was a very significant difference in deep learning ability. Overall, the experimental group showed a more significant improvement in deep learning ability compared to the control group. The real-time evaluation plan for sports education professional basketball classrooms based on deep learning is more effective in improving students’ basketball skills and deep learning abilities than the conventional real-time evaluation plan for sports education professional basketball classrooms. The design of the plan has certain effectiveness and feasibility.

Article Details

Section
Speciai Issue - Deep Learning in Healthcare