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  1. 1

    Reliability and criterion validity of the concept 2 SkiErg™ to assess 1,000-m on-snow, time trial performance—a case study

    O`Brien, B. J., Worn, R., Clark, B., Spencer, M.
    Published in Frontiers in Sports and Active Living (2025)
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  2. 2

    Machine learning techniques for estimating the individual three-dimensional ground reaction forces during rugby scrummaging

    Pomarat, Z., Passieux, J.-C., Dufour, J.-E., Watier, B.
    Published in Journal of Biomechanics (2025)
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  3. 3

    The analysis method results in differences in the evaluation of drop jump kinetics: Proof of concept at three dropping heights

    Chalitsios, C., Panoutsakopoulos, V., Kollias, I. A.
    Published in ISBS Proceedings Archive: Vol. 43: Iss. 1 (2025)
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  4. 4

    A mini-review of mathematical methods in sprint performance

    Fan, Y.
    Published in Frontiers in Sports and Active Living (2025)
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  5. 5

    Azure Kinect for joint range of motion analysis: A validity and reliability evaluation in elite female weightlifters

    Örücü, S., Erdagi, K., Isik, B., Özbay, E., Osmanoglu, U. Ö.
    Published in PLOS ONE (2025)
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  6. 6

    Accuracy of three field-based devices for measuring counter movement jump performance in elite female volleyball players

    Wright, W. C., Fedewa, M. V., Aguiar, E. J., Winchester, L. J., Schumacker, R. E., Esco, M. R.
    Published in The Journal of Strength and Conditioning Research (2025)
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  7. 7

    Physical and biomechanical relationships with countermovement jump performance in team sports: Implications for athletic development and injury risk

    Bygate-Smith, M. K., Beaven, C. M., Drury, M.
    Published in Sports (2025)
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  8. 8

    Footstrike evaluation in male runners: a comparison of lateral and medial video views against traditional motion capture

    Mo, S., Chu, A. S. Y., Shao, S., Chen, Y., Hebert-Losier, K., Li, L., Cheung, R. T. H.
    Published in Journal of Biomechanics (2025)
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  9. 9

    Validation of step time and asymmetry detection algorithm in high-intensity running with Movesense IMU

    Martín Gómez, R., Kamstra, H., Allevard, E., Pollet-Villard, L., Cotter, J., Lamb, P.
    Published in Journal of Biomechanics (2025)
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  10. 10

    Assessing the practicality of using freely available AI-based GPT tools for coach learning and athlete development

    O'Brien, K. A., Prentice, S.
    Published in Frontiers in Sports and Active Living (2025)
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  11. 11

    Will artificial intelligence solve the riddle of athlete development? A critical review of how AI is being used for athlete identification, selection, and development

    Baker, J., Cattle, A., McAuley, A., Kelly, A., Johnston, K.
    Published in Psychology of Sport and Exercise (2025)
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  12. 12

    Prediction of perceived exertion ratings in national level soccer players using wearable sensor data and machine learning techniques

    Leppich, R., Kunz, P., Bauer, A., Kounev, S., Sperlich, B., Düking, P.
    Published in Journal of Sports Science & Medicine (2024)
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  13. 13

    How to assess leader capabilities: Applying AI algorithms to evaluate NBA head coaches

    Kim, P., Lee, S.
    Published in Journal of Sports Analytics (2025)
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  14. 14

    Editorial for sports performance section of Journal of Sports Sciences: moving match analysis forward - guidelines and perspectives

    Memmert, D.
    Published in Journal of Sports Sciences (2025)
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  15. 15

    Reliability of static and dynamic balance assessments using the FootWork Pro pressure® platform in a clinical setting

    van Gulick, D., van der Leeden, M., Lucas, C., Stuiver, M.
    Published in Journal of Science and Medicine in Sport (2025)
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  16. 16

    No train yet gain: towards generic multi-object tracking in sports and beyond

    Stanczyk, T., Yoon, S., Bremond, F.
    Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2025)
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  17. 17

    From beats to scores: a multi-modal framework for comprehensive figure skating assessment

    Wang, F., Wang, Q., Chen, D.
    Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2025)
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  18. 18

    Kinematics analysis of techniques in artistic gymnastics using the ai scoring system -switch leap to ring position on balance beam

    Ishikawa, M., Noro, H., Hata, K., Yamazaki, Y., Lee, R. Y., Yanagiya, T.
    Published in 29th Annual Congress of the European College of Sport Science, 2-5 July 2024, Book of Abstracts (2024)
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  19. 19

    FineCausal: a causal-based framework for interpretable fine-grained action quality assessment

    Han, R., Zhou, K., Atapour-Abarghouei, A., Liang, X., Shum, H. P. H.
    Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2025)
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  20. 20

    Machine learning-based classification of Taekwondo Poomsae side kick performance using kinematic parameters and physical characteristics

    Hwang, U.-J., Jung, S.-H., Ji, H.-C., Choi, S.-A., Bang, I.-J.
    Published in Sports Biomechanics (2025)
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