The ecological validity of laboratory cycling: Does body size explain the difference between laboratory- and field-based cycling performance?

J Sports Sci. 2007 Jan 1;25(1):3-9. doi: 10.1080/02640410500520526.


Previous researchers have identified significant differences between laboratory and road cycling performances. To establish the ecological validity of laboratory time-trial cycling performances, the causes of such differences should be understood. Hence, the purpose of the present study was to quantify differences between laboratory- and road-based time-trial cycling and to establish to what extent body size [mass (m) and height (h)] may help to explain such differences. Twenty-three male competitive, but non-elite, cyclists completed two 25 mile time-trials, one in the laboratory using an air-braked ergometer (Kingcycle) and the other outdoors on a local road course over relatively flat terrain. Although laboratory speed was a reasonably strong predictor of road speed (R2 = 69.3%), a significant 4% difference (P < 0.001) in cycling speed was identified (laboratory vs. road speed: 40.4 +/- 3.02 vs. 38.7 +/- 3.55 km x h(-1); mean +/- s). When linear regression was used to predict these differences (Diff) in cycling speeds, the following equation was obtained: Diff (km x h(-1)) = 24.9 - 0.0969 x m - 10.7 x h, R2 = 52.1% and the standard deviation of residuals about the fitted regression line = 1.428 (km . h-1). The difference between road and laboratory cycling speeds (km x h(-1)) was found to be minimal for small individuals (mass = 65 kg and height = 1.738 m) but larger riders would appear to benefit from the fixed resistance in the laboratory compared with the progressively increasing drag due to increased body size that would be experienced in the field. This difference was found to be proportional to the cyclists' body surface area that we speculate might be associated with the cyclists' frontal surface area.

MeSH terms

  • Adult
  • Bicycling / physiology*
  • Body Size / physiology*
  • Ergometry*
  • Humans
  • Linear Models
  • Male
  • Reproducibility of Results