Variable versus constant power strategies during cycling time-trials: Prediction of time savings using an up-to-date mathematical model

Abstract

Swain (1997 Swain, D. P. 1997. A model for optimizing cycling performance by varying power on hills and in wind. Medicine and Science in Sports and Exercise, 29: 1104–1108. Crossref], PubMed], Web of Science ®] , Google Scholar]) employed the mathematical model of Di Prampero et al. (1979 Di Prampero, P. E., Cortili, G., Mognoni, P. and Saibene, F. 1979. Equation of motion of a cyclist. Journal of Applied Physiology, 47: 201–206. PubMed], Web of Science ®] , Google Scholar]) to predict that, for cycling time-trials, the optimal pacing strategy is to vary power in parallel with the changes experienced in gradient and wind speed. We used a more up-to-date mathematical model with validated coefficients (Martin et al., 1998 Martin, J. C., Milliken, D. L., Cobb, J. E., McFadden, K. L. and Coggan, A. R. 1998. Validation of a mathematical model for road cycling power. Journal of Applied Biomechanics, 14: 276–291. Crossref], PubMed], Web of Science ®] , Google Scholar]) to quantify the time savings that would result from such optimization of pacing strategy. A hypothetical cyclist (mass = 70 kg) and bicycle (mass = 10 kg) were studied under varying hypothetical wind velocities (?10 to 10 m · s^?1), gradients (?10 to 10%), and pacing strategies. Mean rider power outputs of 164, 289, and 394 W were chosen to mirror baseline performances studied previously. The three race scenarios were: (i) a 10-km time-trial with alternating 1-km sections of 10% and ?10% gradient; (ii) a 40-km time-trial with alternating 5-km sections of 4.4 and ?4.4 m · s^?1 wind (Swain, 1997 Swain, D. P. 1997. A model for optimizing cycling performance by varying power on hills and in wind. Medicine and Science in Sports and Exercise, 29: 1104–1108. Crossref], PubMed], Web of Science ®] , Google Scholar]); and (iii) the 40-km time-trial delimited by Jeukendrup and Martin (2001 Jeukendrup, A. E. and Martin, J. 2001. Improving cycling performance: How should we spend our time and money?. Sports Medicine, 31: 559–569. Crossref], PubMed], Web of Science ®] , Google Scholar]). Varying a mean power of 289 W by ± 10% during Swain's (1997 Swain, D. P. 1997. A model for optimizing cycling performance by varying power on hills and in wind. Medicine and Science in Sports and Exercise, 29: 1104–1108. Crossref], PubMed], Web of Science ®] , Google Scholar]) hilly and windy courses resulted in time savings of 126 and 51 s, respectively. Time savings for most race scenarios were greater than those suggested by Swain (1997 Swain, D. P. 1997. A model for optimizing cycling performance by varying power on hills and in wind. Medicine and Science in Sports and Exercise, 29: 1104–1108. Crossref], PubMed], Web of Science ®] , Google Scholar]). For a mean power of 289 W over the “standard” 40-km time-trial, a time saving of 26 s was observed with a power variability of 10%. The largest time savings were found for the hypothetical riders with the lowest mean power output who could vary power to the greatest extent. Our findings confirm that time savings are possible in cycling time-trials if the rider varies power in parallel with hill gradient and wind direction. With a more recent mathematical model, we found slightly greater time savings than those reported by Swain (1997 Swain, D. P. 1997. A model for optimizing cycling performance by varying power on hills and in wind. Medicine and Science in Sports and Exercise, 29: 1104–1108. Crossref], PubMed], Web of Science ®] , Google Scholar]). These time savings compared favourably with the predicted benefits of interventions such as altitude training or ingestion of carbohydrate-electrolyte drinks. Nevertheless, the extent to which such power output variations can be tolerated by a cyclist during a time-trial is still unclear.