Analyzing Brain Waves of Table Tennis Players with Machine Learning for Stress Classification

The Responses of Physiological Stress during Table Tennis Competition in Elite Female Players

Stress is inevitable in competitive sports. Table tennis in the world known as a fastest ball game that requires attention and control stress. The main purpose of this study was investigation of physiological stress responses in elite table tennis players during competition. 16 female table tennis players (age average of 18.7 ± 3.8, height average of 161.6 ± 3.4 cm and weight aver...

Machine Learning for Analyzing Human Brain Function

Classification of top male tennis players

The main objective of this study was to define different quality groups of tennis players based on their position on the ATP ranking list. Ranking data on the top 300 players from 1990 to 2008 were used to conduct the study. The classification into quality groups was performed using six machine learning algorithms suiting such a task. Quality groups were formed better for each year separately t...

Investigation of Underlying Psychological Factors in Elite Table Tennis Players

The importance of psychological factors in successful sports performance has been acknowledged both academically and anecdotally. Yet the amount of time that coaches and athletes actually spend on mental practice as compared to physical practice belies its significance. A key component in developing a foundation for psychological intervention programs is to understand the psychological status o...

Prediction of the Successfulness of Tennis Players with Machine Learning Methods

The aim of the study was to examine the predictability of the competitive performance of Slovene tennis players by using the most promising morphological measures and motor tests selected by automatic computer methods and by experienced tennis coaches by means of machine learning methods. The analysis included altogether 1,002 male and female tennis players who had undergone regular testing by ...