Analysis and optimization of athlete performance based on deep learning

The application of deep learning technology in the analysis and optimization of athlete performance has garnered increasing attention. This paper reviews the research progress of deep learning in areas such as motion capture and recognition, physical fitness and health monitoring, competition data analysis, training plan generation and adjustment, movement and tactical improvement, as well as injury prevention and recovery. Through experimental studies, deep learning models have demonstrated the ability to automatically extract key features from massive sports data, generate intelligent analysis results, and provide optimization suggestions, thus offering robust technical support for athletes and coaches. Despite facing challenges in applying deep learning to practical sports scenarios, these research findings have opened up new directions for sports science research. In the future, deep learning technology is expected to continue playing an important role in the field of sports, promoting the scientific and modern development of sports.