Clustering tennis players’ anthropometric and individual features helps to reveal performance fingerprints-Reference-Cited by-同舟云学术

Clustering tennis players’ anthropometric and individual features helps to reveal performance fingerprints

Published:2019-02-18 Issue:8 Volume:19 Page:1032-1044
ISSN:1746-1391
Container-title:European Journal of Sport Science
language:en
Short-container-title:European Journal of Sport Science

Author:

Cui Yixiong¹^ORCID,Gómez Miguel-Ángel²^ORCID,Gonçalves Bruno³^ORCID,Sampaio Jaime³^ORCID

Affiliation:

1. AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing, People’s Republic of China

2. Faculty of Physical Activity and Sport Sciences – INEF, Universidad Politécnica de Madrid, Madrid, Spain

3. Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), CreativeLab Research Community, Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal

Funder

China Scholarship Council Postdoctoral Science Foundation

Portuguese Foundation for Science and Technology

European Regional Development Fund

Publisher

Informa UK Limited

Subject

Orthopedics and Sports Medicine,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/17461391.2019.1577494

Reference33 articles.

1. Effects of experience and relative quality in tennis match performance during four Grand Slams

2. Performance profiles of professional female tennis players in grand slams

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