A Cluster Analysis Approach to Profile Men and Women s Volley Positions in Professional Tennis Matches (Doubles)
[EN] Background: Tennis ball tracking technology allows the aquirement of novel and reliable data about several performance indicators, such as volley positions. This information is key to understand match dynamics in doubles tennis and to better help preparing players for the demands they will face...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/205322 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/205322 |
| Access Level: | acceso abierto |
| Palavra-chave: | Racquet sports Match analysis Tactics Analytics |
| Resumo: | [EN] Background: Tennis ball tracking technology allows the aquirement of novel and reliable data about several performance indicators, such as volley positions. This information is key to understand match dynamics in doubles tennis and to better help preparing players for the demands they will face in match play. As such, the purpose of this study was to describe and compare the different types of volley positions in men's and women's doubles professional tennis. (2) Methods: Ball tracking data were collected for 46 women (Billie Jean King Cup) and 96 men's doubles matches (Davis Cup). The variables used were the distance to the net, the distance to the centre of the court and the height of the impact. A K-Means cluster analysis was used to identify in each subsample different profiles of volley locations. (3) Results: The inferential analysis revealed differences in men's (distance to the net eta(2) = 0.72, distance to the centre of the court eta(2) = 0.77 and impact height eta(2) = 0.63) and women's subsamples (distance to the net eta(2) = 0.48, distance to the centre of the court eta(2) = 0.52 and impact height eta(2) = 0.51). (4) Conclusions: The results allowed the suggestion of a higher variability in men's matches, as there were seven different clusters identified, and only four in women's. |
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