Junhua Zhang and  Haiyang Wei. Athlete Training Performance Prediction Based on Markov Mathematical Model. Dynamic Systems and Applications 29 (2020) No. 5, 1730 – 1736

https://doi.org/10.46719/dsa20202953

ABSTRACT. 
The Markov chain model, through the performance prediction of the outcome of various strategic operations to succeed in the different athletes, the numerical calculation of the probability of success is determined by the different conditions of the game and the changes between them. The technique known in this test requires improving the ritual pattern by ignoring the problems of strategic behavior that are controlled continuously by reproduction as long as the impact of risky activities affects the chances of success in various competitive conditions at Track and Field, Track Events, Sprints applications. We identify the method of person analysis and consider the outcome of person-related activities, client organization results in purchasing practices, and the request for specific model approvals experienced. The purpose of presenting social aspects is not equivalent to the strategies underlying it. In particular, the developed method of a Markov model to demonstrate the impact of connection connections on state and purchasing behavior. In the proposed model, one aspect of progress time-fluctuations between states is based on how the conditions experienced by the organization can have a lasting effect by moving clients to other (invisible)activates.

Keywords: Markov Mathematical Model, Athlete, Performance Prediction, Mathematical calculation model.