A longitudinal analysis of start position and the outcome of World Cup cross-country mountain bike racing

J Sports Sci. 2012;30(2):175-82. doi: 10.1080/02640414.2011.627368. Epub 2011 Nov 7.

Abstract

For any athlete competing at the highest level it is vital to understand the components that lead to successful performance. World cup cross-country mountain biking is a complex sport involving large numbers of athletes (100-200) competing for positional advantage over varied off-road terrain. The start has been deemed a major part of performance outcome in such races. The purpose of the present study was to establish the relationship between start and finish position in cross-country mountain bike World Cup events over a 10 year (1997-2007) period and to make comparisons with a model manipulating start position based on predicted athletic capabilities. Data collection and comparisons included results from World Cup events from 1997 to 2007 (males and females), and modelled race data based on potential performance capabilities over the same period. Analyses involved the association of annual plus pooled start and finish position (Kendall's tau) along with banded mean, standard deviation for number of changes in position, while non-constrained linear regression enabled comparison between seasons. Actual race data showed significant positive correlations between starting position and finishing position (P < 0.01) in all cases but less than the model. A mean 57.4% (s = 5.6) of males changed < 15 positions, while 62.9% (s = 9.1) of females changed < 10 positions compared with modelled data (83.6%, s = 0.8 and 91.6%, s = 1.5 for males and females respectively). Individual season comparisons show general patterns to be identical (P > 0.05) for both males and females. In conclusion, finishing position is highly dependent on start position and strategies need to be devised for competing athletes to progress in the sport.

MeSH terms

  • Athletic Performance*
  • Bicycling*
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Task Performance and Analysis*