The Respiratory Compensation Point Predicts 19.2-km Cycling Performance in Trained Male Cyclists

ABSTRACT: So, YLI, Faricier, R, Guluzade, NA, Belfry, GR, Murias, JM, and Keir, DA. The respiratory compensation point predicts 19.2-km cycling performance in trained male cyclists. J Strength Cond Res XX(X): 000-000, 2026-This study tested the hypothesis that the step-ramp-step (SRS)-corrected cycling power output (PO) at the respiratory compensation point (RCP) predicts cycling time-trial performance and explored the independent and collective contributions to trial time of 4 physiological variables derived from single or repeated SRS protocols: peak oxygen uptake (V̇o2peak), cycling economy, RCP, and fatigue resistance. Twenty-eight trained male cyclists completed an SRS protocol before and after a 19.2-km virtual time trial (∼30 minutes) on their personal road bikes using a smart trainer. V̇o2peak, cycling economy, and SRS-corrected PO at RCP were derived from the pre-time-trial SRS protocol. Fatigue resistance was quantified as the change in peak ramp PO from pre- to post-time trial. Independent and multilinear regression evaluated the predictive strength of each variable. Relative SRS-corrected RCP (W·kg-1) showed the strongest independent correlation with time-trial completion time (r = -0.61, p < 0.001). Relative V̇o2peak (mL·kg-1·min-1) and cycling economy (%) were also moderately associated with time-trial performance (r = -0.42, p = 0.03; and r = -0.55, p < 0.001, respectively), whereas fatigue resistance was not significantly correlated. In the multilinear regression analysis, SRS-corrected RCP uniquely explained 30.9% of the model's total predictive variance (r = 0.68, p < 0.01) followed by cycling economy (21.3%), ΔPOpeak (2.1%), and absolute V̇o2peak (3.3%). Among trained male cyclists, relative PO at SRS-corrected RCP is a strong and independent predictor of ∼30-minute time-trial performance. The SRS protocol provides a practical, single-session method to assess key physiological determinants of endurance performance, with valuable applications for training prescription and athlete monitoring.