A machine learning approach for the classification of sports based on a coaches’ perspective of environmental, individual and task requirements: A sports profile analysis

Author:

Teunissen Jan Willem12ORCID,Faber Irene R.34,De Bock Jelle5,Slembrouck Maarten5,Verstockt Steven5,Lenoir Matthieu2,Pion Johan12

Affiliation:

1. Institute for Studies in Sports and Exercise, HAN University of Applied Sciences, Nijmegen, The Netherlands

2. Faculty of Medicine and Health Sciences, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium

3. Institute of Sport Science, University of Oldenburg, Oldenburg, Germany

4. Department of Sport Pedagogy, University of Applied Sciences Windesheim, Zwolle, The Netherlands

5. UGent-imec ELIS Department, Research group IDLab, Ghent University—IMEC, Ghent, Belgium

Publisher

Informa UK Limited

Subject

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

Reference25 articles.

1. Allaoui, M., Kherfi, M. L., & Cheriet, A. (2020). Considerably improving clustering algorithms using umap dimensionality reduction technique: A comparative study. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12119 LNCS, 317–325. https://doi.org/10.1007/978-3-030-51935-3_34

2. A model for the teaching of games in secondary schools;Bunker D.;Bulletin of Physical Education,1982

3. Clark, J. E., & Metcalfe, J. S. (2002). The mountain of motor development. In J. E. Clark & J. Humphrey (Eds.), Motor development: Research and reviews (Vol. 2, pp. 163–190). NASPE Publications.

4. Change of plans: an evaluation of the effectiveness and underlying mechanisms of successful talent transfer

5. Methodological Review and Evaluation of Research in Expert Performance in Sport

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