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  1. 1

    "2032 is a dream for us": exploring amputee football players` understanding of classification in para-sport and its application to amputee football

    Engin, S. G., Haegele, J. A., Esatbeyoglu, F,
    Published in Qualitative Research in Sport, Exercise and Health (2025)
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  2. 2

    Sports injuries in elite football players: classification, prevention, and treatment strategies update

    Zeng, Y., Ji, W., Shi, Y., Liu, W., Ji, W.
    Published in Frontiers in Sports and Active Living (2025)
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  3. 3

    The impact of the academy classification model on coaching practices in Norwegian football: a Foucauldian analysis of governance and player development.

    Gagnås, H. L., Thue Bjørndal, C.
    Published in Sports Coaching Review (2025)
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  4. 4

    "2032 is a dream for us": exploring amputee football players` understanding of classification in para sport and its application to amputee football

    Esatbeyoglu, F., Gultekin, B., Kayiran, H.
    Published in 29th Annual Congress of the European College of Sport Science, 2-5 July 2024, Book of Abstracts (2024)
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  5. 5

    Evaluating the validity of tests to predict sprint and change of direction speed in para-athletes with brain impairments

    Reina, R., Beckman, E. M., Connick, M. J., Spathis, J. G., Tweedy, S. M.
    Published in Adapted Physical Activity Quarterly (2024)
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  6. 6

    The classification of technical devices in the training process of athletes playing games

    Guba V. P., Rodin A. V., Skripko A. D., Pleshakov A. A.
    Published in Theory and Practice of Physical Culture (2025)
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  7. 7

    Designing talent development in football - a document analysis of the Norwegian academy classification model

    Nilsen, A. K., Øvrevik Kjerland, G., Fusche Moe, V.
    Published in Soccer & Society (2024)
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  8. 8

    Anthropometrical features of cerebral palsy football players according to their impairment classification and playing position

    Borges, M., Faria, F. R. de, Buratti, J. R., Vieira, A. B., Sá, K. S. G. de, Vieira, I. B., Nogueira, C. D., Costa e Silva, A. de A., Gorla, J. I.
    Published in Revista Brasileira de Cineantropometria e Desempenho Humano (2024)
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  9. 9

    Enhancing sports injury risk assessment in soccer through machine learning and training load analysis

    Tsilimigkras, T., Kakkos, I., Matsopoulos, G. K., Bogdanis, G. C.
    Published in Journal of Sports Science & Medicine (2024)
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  10. 10

    Classification of recovery states in U15, U17, and U19 sub-elite football players: a machine learning approach

    Teixeira, J. E., Encarnação, S., Branquinho, L., Ferraz, R., Portella, D. L., Monteiro, D., Morgans, R., Barbosa, T. M., Monteiro, A. M., Forte, P.
    Published in Frontiers in Psychology (2024)
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  11. 11

    Classification of force-time metrics into lower-body strength domains

    Geneau, M. C., Carey, D. L., Gastin, P. B., Robertson, S., James, L. P.
    Published in The Journal of Strength and Conditioning Research (2024)
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  12. 12

    Using multiple machine learning algorithms to classify distinguishing characteristics between elite defenders and their sub-elite counterparts in professional men`s football

    Phatak, A., Schlenger, J., Jamil, M., Mehta, S., Biermann, H., Memmert, D.
    Published in 13th World Congress of Performance Analysis of Sport and 13th International Symposium on Computer Science in Sport. IACSS&ISPAS 2022 (2023)
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  13. 13

    Masked autoencoder pretraining for event classification in elite soccer

    Rudolph, Y., Brefeld, U.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
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  14. 14

    Deriving player types from soccer event data as a means to improve tactical flexibility

    Schmider, P., Meth, H., Syrianos, G.
    Published in Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference. PACSS 2021. Advances in Intelligent Systems and Computing, vol 1426 (2022)
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  15. 15

    Who are the best passing players in professional soccer? A machine learning approach for classifying passes with different levels of difficulty and discriminating the best passing...

    Merlin, M., Pinto, A., Moura, F. A., da Silva Torres, R., Cunha, S. A.
    Published in PLOS ONE (2024)
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  16. 16

    Performance analysis in soccer

    Link, D.
    Published in Sports technology. Fields of application, sports equipment and materials for sport (2024)
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  17. 17

    Groin injuries in women's premier league football in Norway: A two-season prospective cohort study describing clinical and imaging characteristics

    Thorarinsdottir, S., Amundsen, R., Larmo, A., Pedersen, R., Andersen, T. E., Bahr, R., Møller, M.
    Published in Scandinavian Journal of Medicine & Science in Sports (2024)
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  18. 18

    Analysis of the competitive demands in 7-a-side football players with cerebral palsy

    Gamonales, J. M., Hernández-Beltrán, V., Muñoz-Jiménez, J., Mendoza-Láiz, N., Espada, M. C., Ibáñez, S. J.
    Published in Apunts Sports Medicine (2024)
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  19. 19

    Estimating maturity status in elite youth soccer players: evaluation of methods

    Monasterio, X., Gil, S. M., Bidaurrazaga-Letona, I., Cumming, S. P., Malina, R. M., Williams, S., Lekue, J. A., Santisteban, J., Diaz-Beitia, G., Larruskain, J.
    Published in Medicine & Science in Sports & Exercise (2024)
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  20. 20

    The effects of simulated vision impairment on performance in football

    Runswick, O. R., Rawlinson, A., Allen, P. M., Sharpe, B. T., Pocock, C., Datson, N., Birch, P., Bruce, R., Mann, D. L.
    Published in Journal of Sports Sciences (2023)
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