Performance and ranking position evolution during 20 competitive seasons in elite 100 meter sprinters

  1. JOSÉ FERNANDO ARROYO-VALENCIA 1
  2. CARMEN RODRIGUEZ-FERNANDEZ 2
  3. ADRIÁN CASTAÑO-ZAMBUDIO 3
  4. MARÍA JOSÉ MARTINEZ-PATIÑO 4
  1. 1 Institución Universitaria Escuela Nacional del Deporte
  2. 2 Universidad de Sevilla
    info

    Universidad de Sevilla

    Sevilla, España

    ROR https://ror.org/03yxnpp24

  3. 3 Universidad Rey Juan Carlos
    info

    Universidad Rey Juan Carlos

    Madrid, España

    ROR https://ror.org/01v5cv687

  4. 4 Universidade de Vigo
    info

    Universidade de Vigo

    Vigo, España

    ROR https://ror.org/05rdf8595

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Revista:
Journal of Human Sport and Exercise: JHSE

ISSN: 1988-5202

Ano de publicación: 2021

Volume: 16

Número: 1

Páxinas: 166-173

Tipo: Artigo

DOI: 10.14198/JHSE.2021.161.15 DIALNET GOOGLE SCHOLAR lock_openRUA editor

Outras publicacións en: Journal of Human Sport and Exercise: JHSE

Resumo

The literature contains several researches seeking to analyse and predict the behaviour of 100-meter dash performance through different mathematical models. Although when analysing the historical records in their entirety these simple models fit largely to their behaviour of the historical series, these approximations are not valid when the focus is on the analysis of accumulated times over the past 2 decades. For this reason, this work proposes new alternatives such as polynomial gradient or smooth models capable of explaining with greater accuracy what has happened during the last 20 years for this modality. Therefore, in order to analyse the distribution of competitive marks relative to the top five and bottom five in the ranking over a period of 20 seasons, a total amount of 428 records corresponding to the marks obtained by international level male athletes who conformed the IAAF world ranking in the 100 m race during the 20 indicated seasons were considered for this goal. The main findings of this research conclude with the lack of fitting between the simple approaches (linear or exponential models) and the reported decline in the records -therefore better performance- throughout the analysed period. In return, this work reveals the existence of a tendency towards overall reduction of time records, denoting a positive evolution of the "competitive health" of the discipline. These evolutions, however, seem to be influenced by the position in which athletes qualify, thus showing greater reductions for athletes classified in the bottom five than for those classified in the top five.

Referencias bibliográficas

  • Berthelot, G., Sedeaud, A., Marck, A., Antero-Jacquemin, J., Schipman, J., Saulière, G., … Toussaint, J. F. (2015). Has Athletic Performance Reached its Peak? Sports Medicine, 45(9), 1263–1271. https://doi.org/10.1007/s40279-015-0347-2
  • Blazevich, A. J., & Jenkins, D. G. (2002). Effect of the movement speed of resistance training exercises on sprint and strength performance in concurrently training elite junior sprinters. Journal of Sports Sciences, 20(12), 981–990. https://doi.org/10.1080/026404102321011742
  • Costa, M. J., Marinho, D. A., Reis, V. M., Silva, A. J., Marques, M. C., Bragada, J. A., & Barbosa, T. M. (2010). Tracking the performance of world-ranked swimmers. Journal of Sports Science and Medicine, 9(3), 411–417.
  • Denny, M. W. (2008). Limits to running speed in dogs, horses and humans. Journal of Experimental Biology, 211(24), 3836–3849. https://doi.org/10.1242/jeb.024968
  • García-Manso, J. M., Martín-González, J. M., Dávila, N., & Arriaza, E. (2005). Middle and long distance athletics races viewed from the perspective of complexity. Journal of Theoretical Biology, 233(2), 191–198. https://doi.org/10.1016/j.jtbi.2004.10.014
  • Haake, S. J. (2009). The impact of technology on sporting performance in olympic sports. Journal of Sports Sciences, 27(13), 1421–1431. https://doi.org/10.1080/02640410903062019
  • Haugen, T. A., Solberg, P. A., Foster, C., Morán-Navarro, R., Breitschädel, F., & Hopkins, W. G. (2018). Peak age and performance progression in world-class track-And-field athletes. International Journal of Sports Physiology and Performance, 13(9), 1122–1129. https://doi.org/10.1123/ijspp.2017-0682
  • Kuper, G. H., & Sterken, E. (2007). Modelling the development of world records in running. In Statistical Thinking in Sports. https://doi.org/10.1201/9781584888697.ch2
  • Lippi, G., Banfi, G., Favaloro, E. J., Rittweger, J., & Maffulli, N. (2008). Updates on improvement of human athletic performance: Focus on world records in athletics. British Medical Bulletin, 87(1), 7–15. https://doi.org/10.1093/bmb/ldn029
  • Liu, Y., Paul, S., & Fu, F. H. (2012, July 1). Accomplishments and compromises in prediction research for world records and best performances in track and field and swimming. Measurement in Physical Education and Exercise Science, Vol. 16, pp. 167–182. https://doi.org/10.1080/1091367X.2012.700252
  • Moravec, P., Ruzicka, J., Susanka, P., Dostal, E., Kodejs, M., & Nosek, M. (1988). 99. The 1987 international athletic foundation/IAAF scientific project report: Time analysis of the 100 Metres events at the II world championships in athletics. New Studies in Athletics.
  • Nevill, A. M., & Whyte, G. (2005). Are there limits to running world records? Medicine and Science in Sports and Exercise, 37(10), 1785–1788. https://doi.org/10.1249/01.mss.0000181676.62054.79
  • Okičić, T., Madić, D., Dopsaj, M., & Đorđević, M. (2007). the Math Modeling of the Stages of Result Development in High Profile Elite Swimmers. Physical Education and Sport Vol., 5(2), 121–137.
  • Prendergast, K. (2001). A mathematica model of the 100m and what it means. New Studies in Athletics, 16(3), 31–36.
  • Shaw, C. (2012). Mathematical Forecasting of Running Limitations C Shaw. (March).
  • Whipp, B. J., & Ward, S. A. (1992). Will women soon outrun men? Nature, Vol. 355, p. 25. https://doi.org/10.1038/355025a0
Fonte de datos: Dialnet