Aerobic fitness variables do not predict the professional career of young cyclists

Med Sci Sports Exerc. 2010 Apr;42(4):805-12. doi: 10.1249/MSS.0b013e3181ba99bc.


Purpose: The aim of this study was to examine the discriminant ability of aerobic fitness measures among junior cyclists of different competitive levels and to examine whether these variables were able to predict the cyclists who reached the professional level.

Methods: A total of 309 young cyclists (mean ± SD, age = 17.5 ± 0.5 yr, height = 178 ± 6 cm, weight = 66 ± 7 kg) performed an incremental maximal test to determine peak oxygen uptake (VO2peak) and respiratory compensation point. To examine the discriminant and predictive ability of these parameters, the cyclists were classified according to their competitive level and specialty: 1) national team (NAT) and nonnational team (non-NAT); 2) nonprofessionals (NP), and professional flat specialists and professional climbers; and 3) nonprofessionals (NP), professional continental, and ProTour. A logistic regression was used to test the accuracy of models generated using as predictors the laboratory measures of aerobic fitness and anthropometric data.

Results: The mean absolute and relative VO2peak were 4.7 ± 0.6 L·min(-1) and 71 ± 7 mL·kg(-1)·min(-1), respectively. NAT displayed higher VO2 values than non-NAT. Professional flat specialists showed higher absolute VO2 values than NP. Professional climbers showed higher relative VO2 values than NP. ProTour showed higher aerobic fitness measures than NP. Using the receiver operating characteristic curve, body mass, absolute VO2peak, and VO2 at respiratory compensation point were found to discriminate NAT from non-NAT. Although some of these variables influenced the odds of becoming professionals (odds ratios from 1.10 to 2.86), no models were able to correctly identify the cyclists who became professionals.

Conclusions: Traditional physiological measures of aerobic fitness are useful to identify junior cyclists who can excel in their category. However, these variables cannot be used for talent identification, if "talent" is interpreted as a young cyclist who will succeed in becoming a professional.

MeSH terms

  • Adolescent
  • Adult
  • Anthropometry
  • Aptitude / physiology*
  • Athletic Performance*
  • Bicycling*
  • Cross-Sectional Studies
  • Exercise Test
  • Forecasting
  • Humans
  • Logistic Models
  • Male
  • Occupations
  • Odds Ratio
  • Oxygen Consumption / physiology
  • Physical Fitness*
  • Young Adult