In recent years, big data analysis has received extensive attention in the field of education. It can be said that using sports big data system for sports research will play a more important role in scientifically analyzing the physical and technical characteristics of elite athletes, selecting high-quality athletes, improving the mobility of physical technology, building and optimizing the management of modern sports science. According to the scientific and operable characteristics of big data collection, a large number of random and sampling data collected in the past have been changed to make it more accurate and reliable. The main research methods of this paper are: literature reference, AHP and investigation methods. This paper uses big data to analyze and study sports, and then establishes a simulation system. Firstly, the AHP method is used to analyze the model, and then the data is used to modify the model to improve the accuracy of system simulation. The experimental results show that AHP not only improves the analysis efficiency by 23%, but also reduces the probability of error. The last part expounds the influence of big data analysis technology on the research of physical exercise risk management by comparing the advantages of big data application in physical exercise risk management.

Chen Wang, Lipeng Zhang. Physical Training Risk Management Based on Big Data Analysis Technology. Frontiers in Exercise Physiology (2021), Vol. 2, Issue 1: 1-8. https://doi.org/10.38007/FEP.2021.020101.

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