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  1. 1

    Tribological devices in cycling: A review

    Aubert, R., Roizard, X., Grappe, F., Lallemand, F.
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  2. 2

    Investigation of supervised machine learning for IMU-based swimming activity recognition

    Aram, S., Thompson, I. M., Hudson, D. A., Banks, J.
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  3. 3

    Development curve of the best results of female para swimmers in the 200 individual medley in the SM8 class

    Perzel, I., Zoretic, D., Milanovic, D.
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  4. 4

    Nutritional ergogenic aids in cycling: a systematic review

    Valiño-Marques, A., Lamas, A., Miranda, J. M., Cepeda, A., Regal, P.
    Published in Nutrients (2024)
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  5. 5

    Towards personalised performance prediction in road cycling through machine learning

    Kholkine, L., de Leeuw, A. W., Verdonck, T., Latré, S.
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  6. 6

    The relationship between visual function and performance in para swimming

    Fortin-Guichard, D., Ravensbergen, H. J. C., Krabben, K., Allen, P. M., Mann, D. L.
    Published in Sports Medicine - Open (2022)
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  7. 7

    Impact of menstrual cycle or combined oral contraception on elite female cyclists' training responses through a clustering analysis of training sessions

    Carlin, H., Dupuit, M., Storme, F., Chassard, T., Meignié, A., Sachet, I., Brunet, E., Toussaint, J.-F., Antero, J.
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  8. 8

    Classification of middle- and long-distance runners based upon their performance

    Iljukov, S., Iljukov, P., Kauppi, J.-P., Uusitalo, A. L. T., Peltonen, J. E., Schumacher, Y. O.
    Published in Journal of Sports Sciences (2023)
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  9. 9

    Classification of elite female cyclists sessions and the impact of menstrual cycles

    Carlin, H., Storme, F., Chassard, T., Durmion, G., Toussaint, J. F., Antero, J.
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  10. 10

    Classification of middle- and long-distance runners based on their competition results

    Iljukov, S.
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  11. 11

    Clustering classification of cyclists according to the acute fatigue outcomes produced by an ultra-endurance event

    Sanchez-Jimenez, J. L., Gandia-Soriano, A., Perez-Soriano, P., Priego-Quesada, J. I., Encarnacion-Martinez, A.
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  12. 12

    Identifying differences in swimming speed fluctuation in age-group swimmers by statistical parametric mapping: a biomechanical assessment for performance development

    Morais, J. E., Marinho, D. A., Cobley, S., Barbosa, T. M.
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  13. 13

    Race analysis and determination of stroke frequency - stroke length combinations during the 50-m freestyle event

    Morais, J. E., Barbosa, T. M., Bragada, J. A., Nevill, A. M., Marinho, D. A.
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  14. 14

    Performance progression and variability in 100 m freestyle Paralympic swimmers: A comparison of medallists and para classifications

    Thomson, E., Milligan, M.
    Published in Journal of Sports Sciences (2023)
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  15. 15

    A new model of performance classification to standardize the research results in swimming

    Ruiz-Navarro, J. J., López-Belmonte, Ó., Gay, A., Cuenca-Fernández, F., Arellano, R.
    Published in European Journal of Sport Science (2023)
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  16. 16

    Performance characteristics of TOP5 versus NOT-TOP5 races in female professional cycling

    Lamberts, R. P., van Erp, T.
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  17. 17

    Para sport development experiences: perspectives of para swimmers and parents

    Sales, D., Misener, L.
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  18. 18

    Do handcycling time-trial velocities achieved by para-cycling athletes vary across handcycling classes?

    Muchaxo, R. E., de Groot, S., van der Woude, L. H., Janssen, T. W., Nooijen, C.
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  19. 19

    What`s in a sport class? The classification experiences of paraswimmers

    Van Dornick, K., Spencer, N. L.
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  20. 20

    National sports reserve training system: coaching resource flow analysis

    Savenkova, E. A., Mochalova, M. S., Chaikovskaya, O. O., Lukmanova, N. B.
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