In maximal sprint cycling, the power-cadence relationship to assess the maximal power output (P (max)) and the corresponding optimal cadence (C (opt)) has been widely investigated in experimental studies. These studies have generally reported a quadratic power-cadence relationship passing through the origin. The aim of the present study was to evaluate an equivalent method to assess P (max) and C (opt) for endurance cycling. The two main hypotheses were: (1) in the range of cadences normally used by cyclists, the power-cadence relationship can be well fitted with a quadratic regression constrained to pass through the origin; (2) P (max) and C (opt) can be well estimated using this quadratic fit. We tested our hypothesis using a theoretical and an experimental approach. The power-cadence relationship simulated with the theoretical model was well fitted with a quadratic regression and the bias of the estimated P (max) and C (opt) was negligible (1.0 W and 0.6 rpm). In the experimental part, eight cyclists performed an incremental cycling test at 70, 80, 90, 100, and 110 rpm to yield power-cadence relationships at fixed blood lactate concentrations of 3, 3.5, and 4 mmol L(-1). The determined power outputs were well fitted with quadratic regressions (R (2) = 0.94-0.96, residual standard deviation = 1.7%). The 95% confidence interval for assessing individual P (max) and C (opt) was ±4.4 W and ±2.9 rpm. These theoretical and experimental results suggest that P (max), C (opt), and the power-cadence relationship around C (opt) could be well estimated with the proposed method.
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