Physiological Responses and Performance During a 3-Minute Cycle Time Trial: Standard Paced Versus All-Out Paced

Abstract

Purpose: To compare performance and physiological responses between a standard-paced 3-minute time trial (TTSP, ie, pacing based on normal intention) and a consistently all-out-paced 3-minute time trial (TTAOP). Methods: Sixteen well-trained male cyclists completed the TTSP and TTAOP, on separate days of testing, on a cycling ergometer with power output and respiratory variables measured. Time trials were preceded by 7 × 4-minute submaximal stages of increasing intensity with the linear relationship between power output and metabolic rate used to estimate the contribution from aerobic and anaerobic energy resources. The time course of anaerobic and aerobic contributions to power output was analyzed using statistical parametric mapping. Results: Mean power output was not different between the 2 pacing strategies (TTSP = 417 [43] W, TTAOP = 423 [41] W; P = 0.158). TTAOP resulted in higher peak power output (P < .001), mean ventilation rate (P < .001), mean heart rate (P = .044), peak accumulated anaerobically attributable work (P = .026), post-time-trial blood lactate concentration (P = .035), and rating of perceived exertion (P = .036). Statistical parametric mapping revealed a higher anaerobic contribution to power output during the first ∼30 seconds and a lower contribution between ∼90 and 170 seconds for TTAOP than TTSP. The aerobic contribution to power output was higher between ∼55 and 75 seconds for TTAOP. Conclusions: Although there was no significant difference in performance (ie, mean power output) between the 2 pacing strategies, differences were found in the distribution of anaerobically and aerobically attributable power output. This implies that athletes can pace a 3-minute maximal effort very differently but achieve the same result.

Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review

“…All studies included in this review were mainly related to biomechanics, but one can argue that EMG data can also be considered within the physiological topic ( Kamen and Caldwell, 1996 ). Nonetheless, researchers about swimming performance must be aware that SPM can also be used to gather insights about other physiological variables as it was done per example in cycling ( Dobler et al, 2022 ). Based on SPM, the authors revealed important insights about the power output between two different pacing exercises, i.e., a standard-paced and a consistently all-out-paced 3-min cycle time trial.…”