Abstract
In cycling, performance models are used to investigate factors that determine performance and to optimise competition results. We present an innovative and easily applicable mathematical model describing time-resolved approaches for both the physical aspects of tractional resistance and the physiological side of propelling force generated by muscular activity and test its validity to reproduce and forecast time trials in track cycling. Six elite track cyclists completed a special preparation and two sprint time trials in an official velodrome under continuous measurement of crank force and cadence. Fatigue-free force-velocity profiles were calculated, and their fatigue-induced changes were determined by non-linear regression analysis using a monoexponential equation at a constant slope. Model parameters were calibrated based on pre-exercise performance testing and the first of the two time-trials and then used to predict the performance of the second sprint. Measured values for power output and cycling velocity were compared to the modelled data. The modelled results were highly correlated to the measured values (R2>0.99) without any difference between runs (p>0.05; d<0.1). Our mathematical model can accurately describe sprint track cycling time trial performance. It is simple enough to be used in practice yet sufficiently accurate to predict highly dynamic maximal sprint performances. It can be employed for the evaluation of completed runs, to forecast expected results with different setups, and to study various contributing factors and quantify their effect on sprint cycling performance.
Highlights
IntroductionIn track cycling time trial events (contre la montre, against the clock), cyclists compete for the shortest run-time over a given distance, typically 500 m, 1 km or 4 km, with a standing start
In track cycling time trial events, cyclists compete for the shortest run-time over a given distance, typically 500 m, 1 km or 4 km, with a standing start
Power output can be measured by power meters, and data can be applied to performance models in order to analyse the contributing factors and to optimise competition results
Summary
In track cycling time trial events (contre la montre, against the clock), cyclists compete for the shortest run-time over a given distance, typically 500 m, 1 km or 4 km, with a standing start. Sprint time trials (200 m, 500 m, 1 km) are usually executed in an all-out fashion until complete exhaustion and are indicated by very high maximal and mean power output [1,2]. Competition performance results from the balance of an athlete’s energy supply and physical demands [3]. The propulsive power output supplied by the athlete is directly consumed to overcome physical resistance, bearing and drive-train losses, the rolling resistance of the tires and the aerodynamic drag. Power output can be measured by power meters, and data can be applied to performance models in order to analyse the contributing factors and to optimise competition results. A numerical simulation of human locomotion requires modelling of the supply, as well as the demand side of the energy budget [4]. Different physical and mathematical models have been published since the late 1970s to model (track) cycling performance based on physiological, anthropometric and environmental parameters, which describe the fundamentals [5,6,7] and details [8] of cycling performance via mathematical equations and investigate the effect of changes in modelling parameters on performance [5,6,7,9,10]
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