Big Data and VR Technology in University Sports Stadium Training

Sports training is the most important function of university sports stadiums in China, especially the physical fitness of university students is closely related to sports training. In this regard, reasonable data mining technology and further analysis of related information technology can play a positive role in helping the university sports stadium maximize the training effectiveness. This paper uses the ID3 algorithm (ID3A) in the big data decision tree (DT), and the core idea is to use information gain to test each feature attribute in the data set at all levels. The experiment uses a data collection method to investigate a total of 200 students from a local university. The data obtained from the survey is merged and cleaned in a unified structure to form the data set required for analysis. Taking the attribute of the number of students’ participation as an example, its information gain value is 0.234 and the information gain rate is 0.632. This research is a useful attempt to apply DT data mining technology and VR technology in the field of university sports stadium utilization.