Beyond the Coach: Exploring the Efficacy of a Machine Learning Application for Improving Tennis Players' Performance


Jiawen Hao1 and Huijun Hu2, 1USA, 2California State Polytechnic University, USA


At some point in their lives, most tennis players are likely to encounter the dilemma in which they can't constantlyreceive guidance from a coach. Are there any alternatives that can provide players with the means to improve theirgame? For a tennis player, it is dif icult to always rely on a coach for tips and suggestions [4]. Mundane constraints oftenprevent players from consistently improving their techniques and strokes through the guidance of a professional figure [5]. In this paper, we discuss the prospect of using an application to act in the stead of a coach tohelpaspiring tennis players improve. Using machine learning, the application analyzes and compares two videos of corresponding strokes inputted by users [6]. The AI aligns the frames by clustering the motions of the strokes andthen outputs appropriate tips according to the results [7]. This application will allow tennis players to work onandimprove their performance on occasions where their coaches aren't available, improving both ef iciency andconsistency


Tennis players, Coach alternatives, Machine learning

Full Text  Volume 13, Number 9