Modeling Match Performance in Elite Volleyball Players: Importance of Jump Load and Strength Training Characteristics

Autor: Arie-Willem de Leeuw, Rick van Baar, Arno Knobbe, Stephan van der Zwaard

Publikováno v: Sensors, Vol 22, Iss 20, p 7996 (2022)

In this study, we investigated the relationships between training load, perceived wellness and match performance in professional volleyball by applying the machine learning techniques XGBoost, random forest regression and subgroup discovery. Physical

Externí odkaz: https://doaj.org/article/40b03fb6fbc94649898a4cec40811c33

Capturing the Complex Relationship Between Internal and External Training Load: A Data-Driven Approach

Autor: Stephan van der Zwaard, Ruby T.A. Otter, Matthias Kempe, Arno Knobbe, Inge K. Stoter

Publikováno v: International Journal of Sports Physiology and Performance, 1-9. Human Kinetics Publishers Inc.
STARTPAGE=1;ENDPAGE=9;ISSN=1555-0265;TITLE=International Journal of Sports Physiology and Performance
van der Zwaard, S, Otter, R T A, Kempe, M, Knobbe, A & Stoter, I K 2023, ' Capturing the Complex Relationship Between Internal and External Training Load : A Data-Driven Approach ', International Journal of Sports Physiology and Performance, vol. 18, no. 6, pp. 634-642 . https://doi.org/10.1123/ijspp.2022-0493
International Journal of Sports Physiology and Performance, 18(6), 634-642. Human Kinetics Publishers Inc.

Background: Training load is typically described in terms of internal and external load. Investigating the coupling of internal and external training load is relevant to many sports. Here, continuous kernel-density estimation (KDE) may be a valuable

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc9305b08445024eb75e4706945e840b
https://doi.org/10.1123/ijspp.2022-0493

Exploiting sensor data in professional road cycling: personalized data-driven approach for frequent fitness monitoring

Autor: Arie-Willem de Leeuw, Mathieu Heijboer, Tim Verdonck, Arno Knobbe, Steven Latré

Publikováno v: Data Mining and Knowledge Discovery. SPRINGER
Data Mining and Knowledge Discovery
Data mining and knowledge discovery

We present a personalized approach for frequent fitness monitoring in road cycling solely relying on sensor data collected during bike rides and without the need for maximal effort tests. We use competition and training data of three world-class cycl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53adffae51b385bd4cacfb4e333a444f
http://hdl.handle.net/1887/3512191

Unlocking the potential of big data to support tactical performance analysis in professional soccer

Autor: Ricardo da Silva Torres, Felipe Arruda Moura, Koen A.P.M. Lemmink, F R Goes, Daniele C. Uchoa Maia Rodrigues, Murilo José de Oliveira Bueno, Laurentius Antonius Meerhoff, Marije T. Elferink-Gemser, Arno Knobbe, Sergio Augusto Cunha, Michel Brink

Publikováno v: European Journal of Sport Science. TAYLOR & FRANCIS LTD
European Journal of Sport Science

In professional soccer, increasing amounts of data are collected that harness great potential when it comes to analysing tactical behaviour. Unlocking this potential is difficult as big data challenges the data management and analytics methods common

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c39f654a82bf8f8eb27fc1b0002605a
https://hdl.handle.net/11370/1c250537-8956-4279-8594-aeb93b48fe1b

Personalized machine learning approach to injury monitoring in elite volleyball players

Autor: Stephan van der Zwaard, Arno Knobbe, Arie-Willem de Leeuw, Rick van Baar

Publikováno v: European journal of sport science, 22(4), 511-520. Taylor and Francis Ltd.
European Journal of Sport Science, 22(4), 511-520. Informa UK Limited
de Leeuw, A-W, van der Zwaard, S, van Baar, R & Knobbe, A 2022, ' Personalized machine learning approach to injury monitoring in elite volleyball players ', European journal of sport science, vol. 22, no. 4, pp. 511-520 . https://doi.org/10.1080/17461391.2021.1887369

We implemented a machine learning approach to investigate individual indicators of training load and wellness that may predict the emergence or development of overuse injuries in professional volleyball. In this retrospective study, we collected data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11d790bbd97f9c57a70edc960b61384f
https://research.vu.nl/en/publications/8cae57c1-6c5f-4785-8e5e-e1f48412b04b