As one of the most exciting events of the Winter Olympics, short track speed skating has received widespread attention. The performance of short track speed skating competition is often related to the indicators of athletes' physical state and sports level. How to dig out the key factors affecting performance from numerous indicators has become the most concerned issue for coaches and athletes. Traditional methods mainly use numerical statistics and correlation modeling to analyze the relationship between different indicators and grades. These methods cannot accurately and effectively analyze and evaluate indicators due to rough modeling granularity and incomplete assumptions. In view of this, we propose a comprehensive analysis method for short track speed skating state performance. Specifically, we design a comprehensive importance analysis model based on decision tree, which can be used to model the importance of different indicators to grades. Then, we build a comprehensive evaluation model to evaluate the competitive state and sports performance to help coaches intuitively judge the pros and cons of athletes' state performance. We conduct comprehensive experiments based on simulation dataset. The experiment analyzes the key factors that affect the comparison performance, and evaluates the state performance.
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