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  1. 1

    Biomechanical determinants of elite high jump performance in Egypt: Part 2, the percentage contributions of biomechanical indicators and special factors to achievement level

    Atta, I. I., Bursais, A. K., Alibrahim, M. S., Alhumaid, M. M., Hassan, A. K., Frikha, M., Al-Nuaim, A.
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  2. 2

    Analyzing angular momentum in the takeoff phase of medium-hill ski jumping

    Funato, Y., Nakashima, H., Sakurai, S.
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  3. 3

    Kinetic keys to alpine skiing performance: a 3-D analysis of ground reaction forces and torques

    Delhaye, C., Cross, M. R., Bowen, M., Morel, B., Samozino, P., Hintzy, F.
    Published in Journal of Sports Sciences (2025)
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  4. 4

    Machine learning in rugby union: predicting and identifying key performance indicators for professional rugby union players in match play based workload

    Ren, X., Boisbluche, S., Philippe, K., Demy, M., Äyrämö, S., Rautiainen, I., Ding, S., Prioux, J.
    Published in European Journal of Sport Science (2025)
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  5. 5

    Quantification of workload and characterisation of key performance factors in elite adolescent female volleyball players using machine learning

    Bouzigues, T., Candau, R., Äyrämö, S., Maurelli, O., Prioux, J.
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  6. 6

    Technologies in biathlon: The role of equipment and innovations in performance enhancement

    Alferova, A.
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  7. 7

    Influence of kinetic factors on javelin throw performance

    Palaniyappan, R., Sundar, V., Dhamodharan, V.
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  8. 8

    Towards personalised performance prediction in road cycling through machine learning

    Kholkine, L., de Leeuw, A. W., Verdonck, T., Latré, S.
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  9. 9

    Automatic segmentation and contextualization of elite handball matches with machine learning

    Bassek, M., Raabe, D., Banning, A., Memmert, D.
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  10. 10

    Accuracy of three global positioning systems for determining speed and distance parameters in professional soccer

    Schmidt, M., Nolte, K., Kolodziej, M., Ulbricht, A., Jaitner, T.
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  11. 11

    Applying unsupervised machine learning models to identify serve performance related indicators in women`s volleyball

    Casimiro-Artés, M. Á., Hileno, R., Garcia-de-Alcaraz, A.
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  12. 12

    The influence of "Super-Shoes" and foot strike pattern on metabolic cost and joint mechanics in competitive female runners

    Martinez, E., Hoogkamer, W., Powell, D. W., Paquette, M. R.
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  13. 13

    Influence of selected variables of athletes` special physical fitness on sports performance in pole vaulting

    Gebski, A., Perkowski, K.
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  14. 14

    A rigorous and integrated on-water monitoring system for performance and technique improvement in rowing

    Mpimis, T., Gikas, V., Gourgoulis, V.
    Published in Sensors (2023)
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  15. 15

    The good, the bad, and the ugly of consumer sleep technologies use among athletes: A call for action

    Trabelsi, K., BaHammam, A. S., Chtourou, H., Jahrami, H., Vitiello, M. V.
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  16. 16

    A longitudinal analysis and data mining of the most representative external workload indicators of the whole elite Mexican soccer clubs

    Rojas-Valverde, D., Gómez-Carmona, C. D., Castillo, A. B., Nakamura, F. Y., Giménez-Martínez, E., Matabosch-Pijuán, M., Bernal, J. R., Pino-Ortega, J.
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  17. 17

    Forecasting the competitive performance of young athletes based on artificial intelligence technology

    Nagovitsyn, R. S., Gibadullin, I. G., Batsina, O. N., Mokrushina, I. A.
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  18. 18

    Performance diagnostics in elite biathlon: key factors and predictors

    Sattlecker, G., Dirnberger, J., Wiesinger, H.-P., Birklbauer, J., Buchecker, M.
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  19. 19

    Limiting radial pedal forces greatly reduces maximal power output and efficiency in sprint cycling: an optimal control study

    Kistemaker, D. A., Terwiel, T. M., Reuvers, E. D., Bobbert, M. F.
    Published in Journal of Applied Physiology (2023)
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  20. 20

    Key performance indicators in boxing: a 3D markerless protocol based on action cameras

    Pagnon, D., Domalain, M., Robert, T., Lahkar, B. K., Moussa, I., Sauliere, G., Goyallon, T., Reveret, L.
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