Teaching Platform for Physical Training of Track and Field Events in Colleges and Universities Based on Data Mining Technology

To a large extent, track and field sports require strong physical fitness of athletes, and athletes’ physical fitness determines their competition results. With the improvement of people’s living standards, athletes can get better nutritional supplements, but competition in track events has gradually become fierce, and physical fitness is extremely important for athletes. Physical training can improve athletes’ endurance, sports coordination, and sensitivity, but coaches should arrange the training intensity reasonably, not exceeding the athlete’s tolerance, to avoid problems such as overloading training causing athletes to be injured and sports age shortened. Traditional track and field training methods are no longer suitable for the physical development of modern athletes. This paper mainly studies the college track and field sports training teaching platform based on data mining technology. By using data mining technology, this paper constructs a track and field training platform in colleges and universities. Therefore, this paper designs a teaching platform for physical training in track and field events and puts the teaching platform into training teaching. It uses data mining technology to collect athletes’ sports characteristics and analyze athletes. The physical parameters and movement norms of the people develop a personalized training program for them.