Predicting performance in sub-10s f200 m male track sprint cyclists - Wackwitz, T.; Minahan, C.; Menaspa, P.; Crampton, M.; Wackwitz, A.; Bellinger, P. (Journal of Science and Cycling, 2023)
Maximal power output (Pmax) and the ability to sustain power output close to Pmax are primary determinants of track sprint cycling performance. Given Pmax is achieved at a specific optimal cadence (Fopt) the importance of gear selection is paramount. To optimise gear selection for a specific event, individualised fatigue rates (i.e., fatigue rate per maximal pedal stroke) and field-derived Torque- & Power-Cadence profiles can be used in combination with physics-based model of track cycling. The aim of this investigation was to produce a model of track sprint cycling that can accurately predict performance times of the f200-m. The model utilised mechanical profiles derived from laboratory and field testing as the input variable to optimise f200-m gear selection and performance in elite and world-class track sprint cyclists. Six elite male track-sprint cyclists (Pmax = 2146 ± 423W) completed two testing sessions to identify Torque-Cadence (T-C) and Power-Cadence (P-C) profiles, while fatigue rates were identified during maximal sprints performed at Fopt. The P-C and fatigue profiles were utilised to predict power output during a f200-m event and, in conjunction with a physics-based model of track cycling, predict performance times. This physics model was also utilised to simulate the f200-m performance with different gear ratios. The gear ratio that resulted in the fastest f200-m time was deemed to be theoretically optimal for each athlete. There was no significant difference between the modelled (10.23 ± 0.60s) and actual (10.23 ± 0.53s) f200-m times (p=0.9254). The model predicted that three of the athletes could theoretically improve f200-m performance by increasing the gear ratio, while three could theoretically benefit from a lower gear ratio. P-C and fatigue rate profiles in combination with a physics-based model of track cycling can be used to accurately predict f200-m times.