Correlates of simulated hill climb cycling performance

• Published in: Journal of sports sciences Vol. 18; no. 2; pp. 105 - 110
• Main Authors: Richard Davison, R.C., Swan, David, Coleman, Damian, Bird, Steve
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.02.2000; Taylor and Francis
• Subjects: Adaptation, Physiological - physiology; Adult; Bicycling; Bicycling - physiology; Biological and medical sciences; Energy Metabolism - physiology; Exercise Test - methods; Fundamental and applied biological sciences. Psychology; Heart Rate; Human Performance; Humans; Lactate Minimum; Lactic Acid - blood; Male; Maximal Aerobic Power; Models, Biological; Oxygen Consumption - physiology; Pedal Cadence; Physical Exertion - physiology; Predictive Value of Tests; Regression Analysis; Vertebrates: body movement. Posture. Locomotion. Flight. Swimming. Physical exercise. Rest. Sports; Wingate Test; Human; Maximum oxygen consumption; Pedalling; Physical performance; Cyclism; Prediction; Aptitude test; Rhythm; Athlete; Lactates; Soils; Sport; Physical fitness; Tilt
• ISSN: 0264-0414; 1466-447X
• DOI: 10.1080/026404100365171

The aim of this study was to assess the relationship between several commonly used aerobic and anaerobic cycle ergometer tests and performance during a treadmill cycling hill climb. Eight competitive cyclists (age 27 +/- 7 years; body mass 73.2 +/- 5.2 kg; height 177 +/- 6 cm; mean +/- s) completed six tests in random order: a lactate minimum test; a Wingate anaerobic power test; and two 6-km climbs at 6% and two 1-km climbs at 12% gradient performed on a motorized treadmill. The mean times and power outputs for the 6-km and 1-km climbs were 16:30 +/- 1:08 min:s and 330 +/- 17.8 W, and 4:19 +/- 0:27 min:s and 411 +/- 24.4 W, respectively. The best individual predictor of 6-km and 1-km performance times was the time for the corresponding climb at the other distance (r = 0.97). The next strongest predictor of both hill climb performances was the average power produced during the Wingate test divided by body mass. Stepwise regression analysis showed that the two variables contributing most to the prediction equation for both climbs were the Wingate average power per unit of body mass and maximal aerobic power divided by total mass (rider + bike), which together accounted for 92 and 96% of the variability in the 6-km and 1-km climbs. In conclusion, among competitive cyclists, the Wingate average power per unit of body mass was the best single predictor of simulated cycling hill climb performance at the distance and gradient used.