Ir al contenido

Documat


The Elimination Race in Track Cycling: Patterns and Predictors of Performance

  • Dwyer, Daniel B [1] ; Ofoghi, Bahadoreza [2] ; Huntsman, Emy [2] ; Rossitto, Daniel [2] ; McMahon, Clare [2] ; Zeleznikow, John [2]
    1. [1] Deakin University

      Deakin University

      Australia

    2. [2] Victoria University

      Victoria University

      Australia

  • Localización: Journal of Science & Cycling: Breakthroughs in Cycling & Triathlon Sciences, ISSN-e 2254-7053, Vol. 2, Nº. 2, 2013, págs. 6-12
  • Idioma: inglés
  • Enlaces
  • Resumen
    • The track cycling Omnium is a multi-event competition that has recently been expanded to include the Elimination Race (ER), which presents a unique set of physical and tactical demands. The purpose of this research was to characterise the performance attributes of successful and unsuccessful cyclists in the ER, that are also predictive of performance. Video recordings of four international level ERs were analysed. The performance attributes measured related to the cyclists’ velocity and two dimensional position in the peloton. The average velocity of the peloton up to lap 30 (of 50) was relatively high and consistent (52.2±1.5 km/h). After lap 30, there was a significant (p<0.001) change in velocity (49.9±2.4 km/h), characterised by more fluctuations in lap-to-lap velocity. Successful ER cyclists adopted a tactic of remaining in the middle of the peloton, in the lower lanes of the velodrome, thus avoiding the risk of elimination at the rear and the extra effort required to remain on the front of the peloton. Unsuccessful cyclists tended to reside in the rear and upper (higher) portions of the peloton, risking elimination more often and having to ride faster than those in the lower lanes of the velodrome. The physiological demands of the Elimination Race that are determined by velocity, vary throughout the Elimination Race and the pattern of movement within the peloton is different for successful and unsuccessful cyclists. The findings of the present study may confirm some aspects of race tactics that are currently thought to be optimal, but they also reveal novel information that is useful to coaches and cyclists who compete in the Elimination Race.

  • Referencias bibliográficas
    • Forman G (2003) An extensive empirical study of feature selection metrics for text classification. Journal of Machine Learning Research:1298-1305.
    • George HJ, Langley P (1995) Estimating continuous distributions in Bayesian classifiers. Proceedings of the Eleventh Conference on Uncertainty...
    • Hall MA (1998) Correlation-based Feature Subset Selection for Machine Learning. PhD Dissertation, University of Waikato, Department of Computer...
    • Hall MA, Smith LA (1998) Practical feature subset selection for machine learning. Computer Science '98 Proceedings of the 21st Australasian...
    • Hall MA, Smith LA (1999) Feature Selection for machine learning: Comparing a correlation-based filter approach to the wrapper. Twelfth International...
    • Kohavi R, John GH (1997) Wrappers for feature subset selection. Artif Intell 97:273-324.
    • MacQueen JB (1967) Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical...
    • Mardia KV, Kent JT, Bibby JM (1979) Multivariate analysis. Academic Press, London.
    • Ofoghi B, Zeleznikow J, MacMahon C (2011) Probabilistic modelling to give advice about rowing split measures to support strategy and pacing...
    • Ofoghi B, Zeleznikow J, MacMahon C, Dwyer D (2010) A Machine Learning Approach to Predicting Winning Patterns in Track Cycling Omnium. Ifip...
    • Ofoghi B, Zeleznikow J, MacMahon C, Dwyer DB (2012) Modeling and Analyzing Track Cycling Omnium Performances Using Statistical and Machine...
    • Press WH, Flannery BP, Teukolski SA, Vetterling WT (1988) Numerical recipes in C: the art of scientific computing. Cambridge University Press,...

Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno