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  1. 1

    Game-related statistics and performance trends in the FIBA Under-17 Basketball World Cup

    Mattakottil, A. T., Kumar, D., Perumal, J. S. R., Sundar, V., Narayanasamy, K. V.
    Published in Journal of Human Sport & Exercise (2025)
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  2. 2

    A synthetic data-driven machine learning approach for athlete performance attenuation prediction

    Cordeiro, M. C., Cathain, C. O., Daly, L., Kelly, D. T., Rodrigues, T. B.
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  3. 3

    The application of artificial intelligence techniques in predicting game outcomes of professional basketball league: A systematic review

    Li, C., Zhang, H., Zhang, Y., Shen, J., An, R.
    Published in PLOS ONE (2025)
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  4. 4

    What the eyes don`t see: an objective assessment of players` contribution to team success in men`s rugby league

    Cameron, S., Radwan, I., Mara, J.
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  5. 5

    Analytics auf dem Eis: Wie Daten die Spielanalyse im Eishockey bereichern (Analytics on the ice: How data enriches game analysis in ice hockey)

    Schürmann, R., Bandemer, R., Madauß, L., Wohak, O., Schwarzenbrunner, K., Danielsmeier, C.
    Published in Leistungssport (2025)
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  6. 6

    Eis-Insights (Ice insights)

    Redaktion Zeitschrift LEISTUNGSSPORT
    Published in Leistungssport (2025)
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  7. 7

    Establishing reliable acceleration-speed profiles: Minimum data requirements in rugby union matches

    Maviel, C., Couderc, A., Duché, P., Morin, J. B., Vercruyssen, F.
    Published in Journal of Sports Sciences (2024)
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  8. 8

    Differences in injury and concussion rates in a cohort of Canadian female and male youth Rugby Union: a step towards targeted prevention strategies

    Shill, I. J., West, S. W., Sick, S., Schneider, K. J., Wiley, J. P., Hagel, B. E., Black, A. M., Emery, C. A.
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  9. 9

    Monitoring external load during real competition in male handball players through big data analytics: Differences by playing positions

    Manchado, C., Tortosa-Martinez, J., Marcos-Jorquera, D., Gilart-Iglesias, V., Pueo, B., Chirosa-Rios, L. J.
    Published in Kinesiology (2024)
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  10. 10

    Effect of data-processing methods on acceleration summary metrics of GNSS devices in elite australian football

    Ellens, S., Carey, D. L., Gastin, P. B., Varley, M. C.
    Published in Sensors (2024)
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  11. 11

    What data should be collected for a good handball expected goal model?

    Mortelier, A., Rioult, F., Komar, J.
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  12. 12

    Quantitative analysis of professional basketball: A qualitative discussion

    Zhou, Y., Li, T.
    Published in Journal of Sports Analytics (2023)
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  13. 13

    A comprehensive overview of artificial intelligence applications in basketball

    Agbozo, E., Pandya, K., Jovanovic, P., Suvorova, E. A.
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  14. 14

    Evaluating the impact of a digitally implemented subjective standard on professional rugby union player management decision-making

    Ranaweera, J., Weaving, D., Zanin, M., Roe, G.
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  15. 15

    Data-driven analytics for decision making in game sports

    Seidenschwarz, P. G.
    Published 2021
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  16. 16

    Missing data in sport science: a didactic example using wearables in american football

    Tenan, M. S.
    Published in Sports Medicine (2023)
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  17. 17

    How fast is fast? Defining velocity zones in women`s rugby league

    Cummins, C., Charlton, G., Paul, D., Buxton, S., Murphy, A.
    Published in Science and Medicine in Football (2023)
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  18. 18

    Multi-season injury surveillance in rugby union: addressing the challenges of data collection

    Rubio del Castillo, E., Fortington, L., Nimphius, S., Toohey, L., McDonald, W.
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  19. 19

    Machine learning in sports industry: Discover promising athletes for the future of handball

    Nunes, M. C.
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  20. 20

    A survey on video action recognition in sports: Datasets, methods and applications

    Wu, F., Wang, Q., Bian, J., Xiong, H., Ding, N., Lu, F., Cheng, J., Dou, D.
    Published in arXiv e-print repository (2022)
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