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  1. 1

    A multidimensional prediction model for overtraining risk in youth soccer players: integrating physiological and psychological markers

    Qian, H., Lee, S.
    Published in Journal of Sports Sciences (2025)
    “…mathematic-logical model…”
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  2. 2

    Early specialization in formative basketball: A machine learning analysis of shooting patterns in U14 and professional players

    Contreras-García, J. M., Courel-Ibáñez, J., Piñar-López, M. I., Ibáñez, S. J.
    Published in Journal of Sports Sciences (2024)
    “…mathematic-logical model…”
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  3. 3

    Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach

    Altmann, S., Ruf, L., Thiem, S., Beckmann, T., Wohak, O., Romeike, C., Härtel, S.
    Published in Journal of Sports Sciences (2024)
    “…mathematic-logical model…”
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  4. 4

    "There is more that unites us than divides us". Optimizing talent transfer processes by clustering 34 sports by their task, individual and environmental similarities

    Teunissen, J. W., De Bock, J., Schasfoort, D., Slembrouck, M., Verstockt, S., Lenoir, M., Pion, J.
    Published in Frontiers in Sports and Active Living (2024)
    “…mathematic-logical model…”
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  5. 5

    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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  6. 6

    School-age talent identification in female handball by a mathematical model: Equation proposed from anthropometry, maturity offset, fitness, and technical field-tests

    Caporal, G., Gaya, A. C. A., Pedretti, A., Mello, J. B.
    Published in Research Quarterly for Exercise and Sport (2024)
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  7. 7

    Physical fitness and motor ability parameters as predictors for skateboarding performance: A logistic regression modelling analysis

    Ab Rasid, A. M., Muazu Musa, R., Abdul Majeed, A. P., Musawi Maliki, A. B. H., Abdullah, M. R., Mohd Razmaan, M. A., Abu Osman, N. A.
    Published in PLOS ONE (2024)
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  8. 8

    Gold score athletics: talent detection model for track and field

    van Keulen, G. E., Werneck, F. Z., Coelho, E. F., Aguiar, C. M., Miranda, L., de Lima, J. R. P.
    Published in Revista Brasileira de Medicina do Esporte (2023)
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  9. 9

    Predicting 6000m performance time in junior rowers using a 500m indoor rowing test

    da Silva, L. F., de Almeida-Neto, P. F., Gama, D., Miarka, B., Aidar, F. J., dos Santos Silva, T., Sabido, V., Neto, R. B., Slimani, M., Dantas, P. M. S., de Araujo Tinoco Cabral, B. G.
    Published in Preprints (2023)
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  10. 10

    Peak Height Velocity affects injury burden in circa-PHV soccer players

    Monasterio, X., Gil, S., Bidaurrazaga-Letona, I., Lekue, J. A., Diaz-Beitia, G., Santisteban, J. M., Lee, D.-J., Zumeta-Olaskoaga, L., Martin-Garetxana, I., Larruskain, J.
    Published in International Journal of Sports Medicine (2023)
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  11. 11

    Prediction of aerobic and anaerobic capacity from selected oxidative stress parameters, muscle damage indices and inflammatory markers in soccer and hockey players

    Sarkar, S., Kr Dey, S., Datta, G., Bandyopadhyay, A.
    Published in Polish Journal of Sport and Tourism (2023)
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  12. 12

    Validity and reliability of new equations for the prediction of maximal oxygen uptake in male and female elite adolescent rowers

    Cherouveim, E. D., Methenitis, S. K., Simeonidis, T., Georginis, P., Tsekouras, Y. E., Biskitzi, C., Tsolakis, C., Koulouvaris, P.
    Published in Journal of Human Kinetics (2022)
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  13. 13

    Importance of anthropometric features to predict physical performance in elite youth soccer: a machine learning approach

    Bongiovanni, T., Trecroci, A., Cavaggioni, L., Rossi, A., Perri, E., Pasta, G., Iaia, F. M., Alberti, G.
    Published in Research in Sports Medicine (2021)
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  14. 14

    Mathematical models to identify high-performance players for the Brazilian under-19 men`s volleyball team

    Schons, P., Berriel, G. P., Preissler, A. A. B., Caporal, G. C., Costa, R. R., da Silva, L. C. R., Kruel, L. F. M.
    Published in Journal of Sports Sciences (2022)
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  15. 15

    Framework for intelligent swimming analytics with wearable sensors for stroke classification

    Costa, J., Silva, C., Santos, M., Fernandes, T., Faria, S.
    Published in Sensors (2021)
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  16. 16

    Mobile computing with a smart cricket ball: Discovery of novel performance parameters and their practical application to performance analysis, advanced profiling, talent identifica...

    Fuss, F. K., Doljin, B., Ferdinands, R. E. D.
    Published in Sensors (2021)
    “…mathematic-logical model…”
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  17. 17

    Predicting youth athlete sleep quality and the development of a translational tool to inform practitioner decision making

    Suppiah, H. T., Swinbourne, R., Wee, J., He, Q., Pion, J., Driller, M. W., Gastin, P. B., Carey, D. L.
    Published in Sports Health: A Multidisciplinary Approach (2022)
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  18. 18

    Descriptive and kinetic analysis of two different vertical jump tests among youth and adolescent male basketball athletes using a supervised machine learning approach

    Gillett, J., De Witt, J., Stahl, C. A., Martinez, D., Dawes, J. J.
    Published in The Journal of Strength and Conditioning Research (2021)
    “…mathematic-logical model…”
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  19. 19

    Nutzung multikriterieller und unscharfer (FUZZY-)Analysen zum Talentscreening im Sport (Use of multi-criteria and fuzzy (FUZZY) analyses for talent screening in sport)

    Ester, J., Zinner, J., Utesch, T., Büsch, D.
    Published in Informatik-Spektrum (2020)
    “…mathematic-logical model…”
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  20. 20

    The application of Artificial Neural Network and k-Nearest Neighbour classification models in the scouting of high-performance archers from a selected fitness and motor skill perfo...

    Muazu Musa, R., Abdul Majeed, A. P. P., Taha, Z., Abdullah, M. R., Husin Musawi Maliki, A. B., Azura Kosni, N.
    Published in Science & Sports (2019)
    “…mathematic-logical model…”
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