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The mining and application of data in sports training through intelligent computer-aided research, this paper proposes a system development and design method to improve the development and design efficiency of the data visualization system and reduce the development cost by using the Python language to handle the high efficiency of system programming and the convenience of charts. Thus, it further improves the efficiency and interactivity of the information management of training data and the convenience and stability of managing training data. This system is a preliminary exploration of Python language and Echarte technology in the management of training data of sports training programs. Because of the integration of training programs with computer application technology and data visualization technology, the system still needs to be strengthened in terms of data processing methods and the diversity of chart styles generated. In the future, the use of artificial intelligence, big data analysis, and other technologies in sports training data management and analysis has more room for development. The model only needs to measure 14 indicators of bipedal closed-eye standing and single-leg closed-eye standing movements to achieve the ability to predict the balance of motor training, and its accuracy meets the clinical requirements. This method has a shorter measurement time and fewer metrics than traditional methods.

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