A Data-Driven Analytical System to Optimize Swimming Training and Competition Performance using Machine Learning and Big Data Analysis


Tony Zheng1 and Yu Sun2, 1USA, 2California State Polytechnic University, USA


Many swimmers are constantly incorporating new and different training regimes that would let them improve quickly [2]. However, it is difficult for a swimmer to see their progress instantly. This paper develops a tool for swimmers, specifically swimmers, to predict their future results. We applied machine learning and conducted a qualitative evaluation of the approach [3]. The results show that it is possible to determine their future performance with decent accuracy. This application considers the swimmer's performance history, age, weight, and height to predict the most accurate results.


Machine Learning, Mobile APP, database.

Full Text  Volume 12, Number 15