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  1. 581

    Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

    Leckey, C., van Dyk, N., Doherty, C., Lawlor, A., Delahunt, E.
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  2. 582

    SkateboardAI: The coolest video action recognition for skateboarding (student abstract)

    Chen, H.
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  3. 583

    The use of extended reality technologies in sport perceptual-cognitive skill research: A systematic scoping review

    Kittel, A., Lindsay, R., Le Noury, P., Wilkins, L.
    Published in Sports Medicine - Open (2024)
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  4. 584

    An expected shot outcome model for points in elite Gaelic football

    McDaid, K., McGuigan, K., McDonnell, J., Collins, K.
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  5. 585

    Own goals in football: do they occur randomly or exhibit systematic patterns?

    Mehta, S., Schlenger, J., Memmert, D., Wunderlich, F.
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  6. 586

    Age-related biomechanical variations in vertical jumping and sprinting performance among basketball players

    Petrovic, M., Ramos, J., Hafsteinsson, T., Gisladottir, T.
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  7. 587

    Goal and shot prediction in ball possessions in FIFA Women`s World Cup 2023: a machine learning approach

    Iván-Baragaño, I., Ardá, A., Losada, J. L., Maneiro, R.
    Published in Frontiers in Psychology (2025)
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  8. 588

    Foot pod technology and their utility for change of direction testing: a technological review

    Albarrán, E. J., Cronin, J.
    Published in Strength and Conditioning Journal (2025)
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  9. 589

    Use of artificial neural networks to evaluate the interaction of confounding factors with discriminating factors during the selection of young athletes from different sports: A pil...

    Almeida-Neto, P., Gama de Matos, D., Felipe da Silva, L., Riechman, S., de Morais Ferreira, A. B., Bulhões-Correia, A., de Medeiros, J. A., Aidar, F. J., Dantas, P., Cabral, B.
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  10. 590

    The effectiveness of the training process of skiers using computer vision methods

    Novikova, N. B., Novikov, A. N., Ivanova, I. G., Belyova, A. N.
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  11. 591

    Test-retest reliability and concurrent validity of photoplethysmography finger sensor to collect measures of heart rate variability

    Rogers, D. W., Himariotis, A. T., Sherriff, T. J., Proulx, Q. J., Duong, M. T., Noel, S. E., Cornell, D. J.
    Published in Sports (2025)
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  12. 592

    Identification of athletic and sports profiles through machine learning applied to heart rate variability

    Estrella, T., Capdevila, L.
    Published in Sports (2025)
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  13. 593

    A novel balance training approach: Biomechanical study of virtual reality-based skateboarding

    Kantha, P., Hsu, W.-L., Chen, P.-J., Tsai, Y.-C., Lin, J.-J.
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  14. 594

    Random measurement and prediction errors limit the practical relevance of two velocity sensors to estimate the 1RM back squat

    Warneke, K., Skratek, J., Wagner, C.-M., Wirth, K., Keiner, M.
    Published in Frontiers in Physiology (2024)
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  15. 595

    Running economy with shoes that elicit an involuntary forefoot strike in the habitual rear and non-rear foot strike runners

    Yokoyama, S., Arita, K., Oshima, S., Otsuka, J., Okamoto, Y., Kato, H., Tazawa, S., Hirai, S., Kajiwara, Y., Kunimasa, Y., Amano, T.
    Published in Footwear Science (2024)
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  16. 596

    Evaluation of the Vmaxpro sensor for assessing movement velocity and load-velocity variables: accuracy and implications for practical use

    Dragutinovic, B., Jacobs, M. W., Feuerbacher, J. F., Goldmann, J.-P., Cheng, S., Schumann, M.
    Published in Biology of Sport (2024)
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  17. 597

    Assessment of scapular position measurement using ultrasound sensors to correct skin to bone artifacts from skin mounted motion capture

    Vicini, A., Sabick, M. B.
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  18. 598

    The next generation of strength and conditioning practice to enhance performance and reduce injury risk: virtual reality-based integration of neuromuscular, neurocognitive, and sen...

    McPherson, A. L., Hogg, J. A., Foreman, E., Riehm, C. D., Howell, D. R., Grooms, D. R., Myer, G. D.
    Published in Strength and Conditioning Journal (2025)
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  19. 599

    Performance analysis in SailGP: A machine learning approach

    Zentai, B., Toka, L.
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  20. 600

    Predicting handball matches with machine learning and statistically estimated team strengths

    Felice, F., Ley, C.
    Published in Journal of Sports Analytics (2025)
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