Search Results - "Prognose"

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  1. 1

    An analysis of the 6-h ultra-marathon race using a machine learning approach

    Thuany, M., Weiss, K., Valero, D., Villiger, E., Andrade, M. S., Nikolaidis, P. T., Scheer, V., de Lira, C. A. B., Vancini, R. L., Cuk, I., Braschler, L., Rosemann, T., Knechtle, B. “…Prognose…”
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  2. 2

    Using multilevel models to compare performance prediction and characterization abilities between power-law and critical-speed models in middle- and long-distance running

    Walt, M., Casado, A., Le Goff, J.-M. “…Prognose…”
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  3. 3

    The fourth dimension: physiological resilience as an independent determinant of endurance exercise performance

    Jones, A. M.
    Published in Journal of Physiology (2024)
    “…Prognose…”
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  4. 4

    Can ground reaction force variables preidentify the probability of a musculoskeletal injury in collegiate distance runners?

    Stewart, H. E., Alcantara, R. S., Farina, K. A., Hahn, M. E., Grabowski, A. M., Kram, R., Wilcox, R. R., McNitt-Gray, J. L.
    Published in Journal of Applied Biomechanics (2025)
    “…Prognose…”
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  5. 5

    Accuracy of smartwatches in predicting distance running performance

    Dai, J., Chen, G., Gu, Z., Qi, Y., Xu, K. “…Prognose…”
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  6. 6

    Predicting the potential of middle- and long-distance track runners by evaluating the performance improvement rate

    Lerebourg, L., Guignard, B., L´Hermette, M., Coquart, J. B. “…Prognose…”
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  7. 7

    Valid and accurate simple equation to predict 3,000-m steeplechase performance

    Barbry, A., Lerebourg, L., Racil, G., Jlid, M. C., Coquart, J. “…Prognose…”
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  8. 8

    Analysis of the 72-h ultramarathon using a predictive XG Boost model

    Knechtle, B., Villiger, E., Weiss, K., Valero, D., Gajda, R., Scheer, V., Barbosa de Lira, C. A., Braschler, L., Nikolaidis, P. T., Vancini, R. L., Cuk, I., Rosemann, T., Thuany, M.
    Published in Sport Sciences for Health (2024)
    “…Prognose…”
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  9. 9

    "Falling behind," "letting go," and being "outsprinted" as distinct features of pacing in distance running

    Foster, C., Barroso, R., Bok, D., Boullosa, D., Casado Alda, A., Cortis, C., Fusco, A., Hanley, B., Skiba, P., de Koning, J. J. “…Prognose…”
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  10. 10

    Are pre-race serum blood biomarkers associated with the 24-h ultramarathon race performance?

    Amatori, S., Sisti, D., Bertuccioli, A., Rocchi, M. B. L., Luchetti, F., Nasoni, M. G., Papa, S., Citarella, R., Perroni, F., Benedetti, S.
    Published in European Journal of Sport Science (2024)
    “…Prognose…”
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  11. 11

    Characteristic of elite male 800-m runner`s race performance based on hybrid computing methods

    Chen, C., Ma, J., Song, J., He, S., Tan, M.
    Published in Applied Bionics and Biomechanics (2023)
    “…Prognose…”
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  12. 12

    Retrospective and contemporary predictors of National Collegiate Athletic Association Division I cross-country performance are sex specific

    Carder, M. J., Scudamore, E. M., Savanna, K. N., Pribyslavska, V., Bowling, L. R., O'Neal, E. K. “…Prognose…”
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  13. 13

    Can we predict long-duration running power output? A matter of selecting the appropriate predicting trials and empirical model

    Ruiz-Alias, S., Ñancupil-Andrade, A. A., Pérez-Castilla, A., Garcia-Pinillos, F. “…Prognose…”
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  14. 14

    Running Energy Reserve Index (RERI) as a new model for assessment and prediction of world, elite, sub-elite, and collegiate running performances

    Balasekaran, G., Loh, M. K., Boey, P., Ng, Y. C.
    Published in Scientific Reports (2023)
    “…Prognose…”
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  15. 15

    Prediction of marathon performance using artificial intelligence

    Lerebourg, L., Saboul, D., Clémençon, M., Coquart, J. B. “…Prognose…”
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  16. 16

    Is maximal lactate accumulation rate promising for improving 5000-m prediction in running?

    Quittmann, O. J., Foitschik, T., Vafa, R., Freitag, F. J., Sparmann, N., Nolte, S., Abel, T. “…Prognose…”
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  17. 17

    Interaction of exercise bioenergetics with pacing behavior predicts track distance running performance

    Kirby, B. S., Winn, B. J., Wilkins, B. W., Jones, A. M.
    Published in Journal of Applied Physiology (2021)
    “…Prognose…”
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  18. 18

    Predictions of the distance running performances of female runners using different tools

    Lerebourg, L., Guignard, B., L'Hermette, M., Held, E., Coquart, J. B. “…Prognose…”
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  19. 19

    Mining marathon training data to generate useful user profiles

    Berndsen, J., Smyth, B., Lawlor, A. “…Prognose…”
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  20. 20

    Injury prediction in competitive runners with machine learning

    Lövdal, S. S., Den Hartigh, R. J. R., Azzopardi, G. “…Prognose…”
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