Critical power: How different protocols and models affect its determination

High-dose short-term creatine supplementation without beneficial effects in professional cyclists: a randomized controlled trial

BACKGROUND

Growing evidence supports the ergogenic effects of creatine supplementation on muscle power/strength, but its effects on endurance performance remain unclear. We assessed the effects of high-dose short-term creatine supplementation in professional cyclists during a training camp.

METHODS

The study followed a double-blind, randomized parallel design. Twenty-three professional U23 cyclists (19 ± 1 years, maximum oxygen uptake: 73.0 ± 4.6 mL/kg/min) participated in a 6-day training camp. Participants were randomized to consume daily either a recovery drink (containing carbohydrates and protein) with a 20-g creatine supplement (creatine group, n = 11) or just the recovery drink (placebo group, n = 12). Training loads and dietary intake were monitored, and indicators of fatigue/recovery (Hooper index, countermovement jump height), body composition, and performance (10-second sprint, 3-, 6-, and 12-minute time trials, respectively, as well as critical power and W') were assessed as study outcomes.

RESULTS

The training camp resulted in a significant (p < 0.001) increase of training loads (+50% for total training time and + 61% for training stress score, compared with the preceding month) that in turn induced an increase in fatigue indicators (significant time effect [p < 0.001] for delayed-onset muscle soreness, fatigue, and total Hooper index) and a decrease in performance (significant time effect [p = 0.020] for critical power, which decreased by -3.8%). However, no significant group-by-time interaction effect was found for any of the study outcomes (all p > 0.05).

CONCLUSIONS

High-dose short-term creatine supplementation seems to exert no consistent beneficial effects on recovery, body composition or performance indicators during a strenuous training period in professional cyclists.

Intensity Matters: Effect of Different Work-Matched Efforts on Subsequent Performance in Cyclists

PURPOSE

To assess the effect of 2 work-matched efforts of different intensities on subsequent performance in well-trained cyclists.

METHODS

The present study followed a randomized controlled crossover design. Twelve competitive junior cyclists volunteered to participate (age, 17 [1] y; maximum oxygen uptake, 71.0 [4.7] mL·kg-1·min-1). The power-duration relationship was assessed through 2-minute, 5-minute, and 12-minute field tests under fresh conditions (control). On subsequent days and following a randomized order, participants repeated the aforementioned tests after 2 training sessions matched for mechanical work (∼15 kJ/kg) of different intensities (ie, a moderate-intensity continuous-training [60%-70% of critical power; CP] session or a session including high-intensity intervals [3-min repetition bouts at 110%-120% of the CP interspersed by 3-min rest periods]).

RESULTS

A significantly lower power output was found in the 2-minute test after the high-intensity training session compared not only with the control condition (-8%, P < .001) but also with the moderate-intensity continuous-training session (-7%, P = .003), with no significant differences between the latter conditions. No significant differences between conditions were found for the remaining tests. As a consequence, the high-intensity training session resulted in significantly lower W' values compared to both the control condition (-27%, P = .001) and the moderate-intensity continuous-training session (-26%, P = .012), with no differences between the 2 latter conditions and with no differences for CP.

CONCLUSION

A session including high-intensity intermittent efforts induces a greater fatigue, particularly in short-duration efforts and W', than a work-matched continuous-training session of moderate intensity.

Heart Rate Variability Thresholds: Agreement with Established Approaches and Reproducibility in Trained Females and Males

PURPOSE

To determine in trained females and males i) the agreement between the gas exchange threshold (GET), lactate threshold 1 (LT1), and heart rate variability threshold 1 (HRVT1), as well as between the respiratory compensation point (RCP), lactate threshold 2 (LT2), and heart rate variability threshold 2 (HRVT2), and ii) the reproducibility of HRVT1 and HRVT2 during 2-min incremental step protocols.

METHODS

Fifty-seven trained participants (24 females) completed a 2-min step incremental test to task failure. Nineteen participants (eight females) completed a second test to evaluate reproducibility. Gas exchange and ventilatory responses, blood lactate concentration, and RR time series were recorded to assess the oxygen consumption (V̇O 2 ) and heart rate (HR) associated with the GET, RCP, LT1, LT2, HRVT1, and HRVT2.

RESULTS

V̇O 2 -GET versus V̇O 2 -HRVT1 and HR-GET versus HR-HRVT1 were statistically different for females (29.5 ± 4.0 vs 34.6 ± 6.1 mL·kg -1 ·min -1 ; 154 ± 11 vs 166 ± 12 bpm) and for males (33.9 ± 4.2 vs 42.7 ± 4.6 mL·kg -1 ·min -1 ; 145 ± 11 vs 165 ± 9 bpm; P < 0.001). V̇O 2 and HR at HRVT1 were greater than at LT1 ( P < 0.05). V̇O 2 -RCP versus V̇O 2 -HRVT2 and HR-RCP versus HR-HRVT2 were not statistically different for females (40.1 ± 4.7 vs 39.5 ± 6.7 mL·kg -1 ·min -1 ; 177 ± 9 vs 176 ± 9 bpm) and males (48.4 ± 5.4 vs 47.8 ± 4.8 mL·kg -1 ·min -1 ; 176 ± 8 vs 175 ± 9 bpm; P > 0.05). V̇O 2 and HR responses at LT2 were similar to HRVT2 ( P > 0.05). Intraclass correlation coefficient for V̇O 2 -HRVT1, HR-HRVT1, V̇O 2 -HRVT2, and HR-HRVT2 indicated good reproducibility when comparing the two different time points to standard methods.

CONCLUSIONS

Whereas HRVT2 is a valid and reproducible estimate of the RCP/LT2, current approaches for HRVT1 estimation did not show good agreement with outcomes at GET and LT1.

Agreement Between Maximal Lactate Steady State and Critical Power in Different Sports: A Systematic Review and Bayesian's Meta-Regression

ABSTRACT

Borszcz, FK, de Aguiar, RA, Costa, VP, Denadai, BS, and de Lucas, RD. Agreement between maximal lactate steady state and critical power in different sports: A systematic review and Bayesian's meta-regression. J Strength Cond Res 38(6): e320-e339, 2024-This study aimed to systematically review the literature and perform a meta-regression to determine the level of agreement between maximal lactate steady state (MLSS) and critical power (CP). Considered eligible to include were peer-reviewed and "gray literature" studies in English, Spanish, and Portuguese languages in cyclical exercises. The last search was made on March 24, 2022, on PubMed, ScienceDirect, SciELO, and Google Scholar. The study's quality was evaluated using 4 criteria adapted from the COSMIN tool. The level of agreement was examined by 2 separate meta-regressions modeled under Bayesian's methods, the first for the mean differences and the second for the SD of differences. The searches yielded 455 studies, of which 36 studies were included. Quality scale revealed detailed methods and small samples used and that some studies lacked inclusion/exclusion criteria reporting. For MLSS and CP comparison, likely (i.e., coefficients with high probabilities) covariates that change the mean difference were the MLSS time frame and delta criteria of blood lactate concentration, MLSS number and duration of pauses, CP longest predictive trial duration, CP type of predictive trials, CP model fitting parameters, and exercise modality. Covariates for SD of the differences were the subject's maximal oxygen uptake, CP's longest predictive trial duration, and exercise modality. Traditional MLSS protocol and CP from 2- to 15-minute trials do not reflect equivalent exercise intensity levels; the proximity between MLSS and CP measures can differ depending on test design, and both MLSS and CP have inherent limitations. Therefore, comparisons between them should always consider these aspects.

Energetics of sinusoidal exercise below and across critical power and the effects of fatigue

PURPOSE

Previous studies investigating sinusoidal exercise were not devoted to an analysis of its energetics and of the effects of fatigue. We aimed to determine the contribution of aerobic and anaerobic lactic metabolism to the energy balance and investigate the fatigue effects on the cardiorespiratory and metabolic responses to sinusoidal protocols, across and below critical power (CP).

METHODS

Eight males (26.6 ± 6.2 years; 75.6 ± 8.7 kg; maximum oxygen uptake 52.8 ± 7.9 ml·min-1·kg-1; CP 218 ± 13 W) underwent exhausting sinusoidal cycloergometric exercises, with sinusoid midpoint (MP) at CP (CPex) and 50 W below CP (CP-50ex). Sinusoid amplitude (AMP) and period were 50 W and 4 min, respectively. MP, AMP, and time-delay (tD) between mechanical and metabolic signals of expiratory ventilation (V ˙ E ), oxygen uptake (V ˙ O 2 ), and heart rate ( f H ) were assessed sinusoid-by-sinusoid. Blood lactate ([La-]) and rate of perceived exertion (RPE) were determined at each sinusoid.

RESULTS

V ˙ O 2 AMP was 304 ± 11 and 488 ± 36 ml·min-1 in CPex and CP-50ex, respectively. Asymmetries between rising and declining sinusoid phases occurred in CPex (36.1 ± 7.7 vs. 41.4 ± 9.7 s forV ˙ O 2 tD up and tD down, respectively; P < 0.01), with unchanged tDs.V ˙ O 2 MP and RPE increased progressively during CPex. [La-] increased by 2.1 mM in CPex but remained stable during CP-50ex. Anaerobic contribution was larger in CPex than CP-50ex.

CONCLUSION

The lower aerobic component during CPex than CP-50ex associated with lactate accumulation explained lowerV ˙ O 2 AMP in CPex. The asymmetries in CPex suggest progressive decline of muscle phosphocreatine concentration, leading to fatigue, as witnessed by RPE.

Is all work the same? Performance after accumulated work of differing intensities in male professional cyclists

OBJECTIVES

Although the ability to attenuate power output (PO) declines after accumulated work (i.e., 'durability') is increasingly recognized as a major determinant of cycling performance, the potential role of the intensity of the previous work is unclear. We assessed the effect of work-matched levels of accumulated work at different intensities on performance in male professional cyclists.

DESIGN

Observational field-based study.

METHODS

PO data was registered in 17 cyclists during a competition season, and the critical power (CP) was repeatedly determined every 4 weeks from training sessions and competitions. Participants' maximum mean power (MMP) for different durations (5 s, 5 min, 10 min, and 20 min) and the CP were determined under 'fresh' conditions (0 kJ·kg-1) and after varying levels of accumulated work (2.5, 5.0 and 7.5 kJ·kg-1) at intensities below and above the CP.

RESULTS

A significant decline was found for all MMP values following all levels of accumulated work above the CP (-4.0 %, -1.7 %, -1.8 %, and -3.2 % for 30s, 5 min, 10 min and 20 min-MMP, respectively; all p < 0.001), versus no change after any level of accumulated work below the CP (all p > 0.05). Similar results were observed for the CP, which decreased after all levels of accumulated work above (-2.2 %, -6.1 %, and -16.2 %, after 2.5, 5.0 and 7.5 kJ·kg-1, p < 0.001) but not below this indicator (p > 0.05).

CONCLUSIONS

In male professional cyclists, accumulated work above the CP impairs performance compared with work-matched, albeit less intense efforts. This raises concerns on the use of mechanical work per se as a single fatigue/stress indicator in these athletes.

Combining Near-Infrared Spectroscopy and Heart Rate Variability Derived Thresholds to Estimate the Critical Intensity of Exercise

ABSTRACT

Fleitas-Paniagua, PR, de Almeida Azevedo, R, Trpcic, M, Murias, JM, and Rogers, B. Combining near-infrared spectroscopy and heart rate variability derived thresholds to estimate the critical intensity of exercise. J Strength Cond Res 38(1): e16-e24, 2024-Critical intensity determination often requires costly tools and several testing sessions. Alternative approaches display relatively large individual variation. Therefore, simpler estimations with improved precision are needed. This study evaluated whether averaging the heart rate (HR) and oxygen uptake (V̇O 2 ) responses associated with the muscle deoxyhemoglobin concentration breakpoint ([HHb] BP ) and the heart rate variability (HRV) given by the detrended fluctuation analysis second threshold (HRVT2) during ramp incremental (RI) test improved the accuracy of identifying the HR and V̇O 2 at the respiratory compensation point (RCP). Ten female and 11 male recreationally trained subjects performed a 15 W·minute -1 RI test. Gas exchange, near-infrared spectroscopy (NIRS), and RR interval were recorded to assess the RCP, [HHb] BP , and HRVT2. Heart rate (mean ± SD : 158 ± 14, 156 ± 13, 160 ± 14 and, 158 ± 12 bpm) and V̇O 2 (3.08 ± 0.69, 2.98 ± 0.58, 3.06 ± 0.65, and 3.02 ± 0.60 L·minute -1 ) at the RCP, [HHb] BP , HRVT2, and HRVT2&[HHb] BP average (H&H Av ), respectively, were not significantly different ( p > 0.05). The linear relationship between H&H Av and RCP was higher compared with the relationship between [HHb] BP vs RCP and HRVT2 vs RCP for both HR ( r = 0.85; r = 0.73; r = 0.79, p > 0.05) and V̇O 2 ( r = 0.94; r = 0.93; r = 0.91, p > 0.05). Intraclass correlation between RCP, [HHb] BP , HRVT2, and H&H AV was 0.93 for V̇O 2 and 0.79 for HR. The [HHb] BP and the HRVT2 independently provided V̇O 2 and HR responses that strongly agreed with those at the RCP. Combining [HHb] BP and the HRVT2 resulted in estimations of the V̇O 2 and HR at the RCP that displayed smaller variability compared with each modality alone.

Effect of acute heat exposure on the determination of critical power and W' in women and men

The goal of this study was to investigate to what extent acute heat exposure would affect the parameters of the power-duration relationship, i.e. CP and W', using multiple constant workload tests to task failure, in women and men. Twenty four young physically active participants (12 men, 12 women) performed 3-5 constant load tests to determine CP and W', both in temperate (TEMP; 18°C) and hot (HOT; 36°C) environmental conditions. A repeated-measures ANOVA was executed to find differences between TEMP and HOT, and between women and men. In HOT, CP was reduced by 6.5% (227 ± 50 vs. 212 ± 47 W), while W' increased 12.4% (16.4 ± 4.4 vs. 18.5 ± 5.6 kJ). No significant two-way sex × temperature interactions were observed, indicating that the environmental conditions did not have a different effect in men compared with women. The intersection of the average curvatures in TEMP and HOT occurred at 137 s and 280 W in women, and 153 s and 397 W in men. Acute heat exposure had an impact on the parameters CP and W', i.e. CP decreased whereas W' increased. The increase in W' might be a consequence of the mathematical modelling for the used test methodology, rather than a physiological accurate value of W' in HOT. No differences induced by heat exposure were observed between women and men.

Running Critical Power: A Comparison Of Different Theoretical Models

This study aimed (i) to compare the critical power (CP) and work capacity over CP (W´) values reported by the different CP models available in current analysis software packages (Golden Cheetah and Stryd platform), (ii) to locate the CP values in the power-duration curve (PDC), and (iii) to determine the influence of the CP model used on the W´ balance. Fifteen trained athletes performed four time trials (i. e., 3, 5, 10, 20 minutes) to define their PDC through different CP models: work-time (CPwork), power-1/time (CP1/time), Morton hyperbolic (CPhyp), Stryd platform (CPstryd), and Bioenergetic Golden Cheetah (CPCheetah). Three additional time trials were performed: two to locate the CP values in the PDC (30 and 60 minutes), and one to test the validity of the W' balance model (4 minutes). Significant differences (p<0.001) were reported between models for the estimated parameters (CP, W´). CPcheetah was associated with the power output developed between 10 to 20 minutes, CP1/time, CPstryd CPwork and CPhyp. The W´ reported by the three-parameter CP models overestimated the actual 4 minutes time to exhaustion, with CPwork (0.48 [- 0.19 to 1.16] minutes); and CP1/time (0.40 [- 0.13 to 0.94] minutes) being the only valid models (p≥0.240).

Prediction of Exercise Tolerance in the Severe and Extreme Intensity Domains by a Critical Power Model

This study aimed to assess the predictive capability of different critical power (CP) models on cycling exercise tolerance in the severe- and extreme-intensity domains. Nineteen cyclists (age: 23.0 ± 2.7 y) performed several time-to-exhaustion tests (Tlim) to determine CP, finite work above CP (W'), and the highest constant work rate at which maximal oxygen consumption was attained (IHIGH). Hyperbolic power-time, linear power-inverse of time, and work-time models with three predictive trials were used to determine CP and W'. Modeling with two predictive trials of the CP work-time model was also used to determine CP and W'. Actual exercise tolerance of IHIGH and intensity 5% above IHIGH (IHIGH+5%) were compared to those predicted by all CP models. Actual IHIGH (155 ± 30 s) and IHIGH+5% (120 ± 26 s) performances were not different from those predicted by all models with three predictive trials. Modeling with two predictive trials overestimated Tlim at IHIGH+5% (129 ± 33 s; p = 0.04). Bland-Altman plots of IHIGH+5% presented significant heteroscedasticity by all CP predictions, but not for IHIGH. Exercise tolerance in the severe and extreme domains can be predicted by CP derived from three predictive trials. However, this ability is impaired within the extreme domain.

Functional Threshold Power Field Test Exceeds Laboratory Performance in Junior Road Cyclists

Vinetti, G, Rossi, H, Bruseghini, P, Corti, M, Ferretti, G, Piva, S, Taboni, A, and Fagoni, N. The functional threshold power field test exceeds laboratory performance in junior road cyclists. J Strength Cond Res 37(9): 1815–1820, 2023—The functional threshold power (FTP) field test is appealing for junior cyclists, but it was never investigated in this age category, and even in adults, there are few data on FTP collected in field conditions. Nine male junior road cyclists (16.9 ± 0.8 years) performed laboratory determination of maximal aerobic power (MAP), 4-mM lactate threshold (P4mM), critical power (CP), and the curvature constant (W ′), plus a field determination of FTP as 95% of the average power output during a 20-minute time trial in an uphill road. The level of significance was set at p < 0.05. Outdoor FTP (269 ± 34 W) was significantly higher than CP (236 ± 24 W) and P4mM (233 ± 23 W). The V ˙ O 2 peak of the field FTP test (66.9 ± 4.4 ml·kg−1·min−1) was significantly higher than the V ˙ O 2 peak assessed in the laboratory (62.7 ± 3.7 ml·kg−1·min−1). Functional threshold power was correlated, in descending order, with MAP (r = 0.95), P4mM (r = 0.94), outdoor and indoor V ˙ O 2 peak (r = 0.93 and 0.93, respectively), CP (r = 0.84), and W ′ (r = 0.66). It follows that in junior road cyclists, the FTP field test was feasible and related primarily to aerobic endurance parameters and secondarily, but notably, to W ′. However, the FTP field test significantly exceeded all laboratory performance tests. When translating laboratory results to outdoor uphill conditions, coaches and sport scientists should consider this discrepancy, which may be particularly enhanced in this cycling age category.

An improved methodology for estimating critical power from mean maximal power output data

The aim of this study was to determine if Critical Power (CP) and W' can be estimated from mean maximal power output (MMP) data collected in cycling races. Data were collected from 13 under 23 professional cyclists (mean ± SD; age, 19.5 ± 1.1 y; body mass, 66.3 ± 5.0 kg; height, 180.0 ± 5.0 cm; CP, 5.7 ± 0.3 W · kg-1). Participants conducted a CP test in the field to determine CPTest and W'Test. MMP data were then collected in races for the subsequent 90 days. CP and W' were estimated from MMP values in two ways, using fixed MMP durations, 2, 5 and 12 min (CPFixed and W'Fixed), and via a novel filtering of second-by-second MMP data (CPFiltered and W'Filtered). CPFixed and CPFiltered were not significantly different from CPTest (Mean Difference (MD) 5 W and 7 W, respectively, p > 0.05). W'Fixed and W'Filtered were not significantly different from W'Test (MD 2.68 kJ and 0.89 kJ, respectively, p > 0.05). CPFixed and CPFiltered correlated significantly with CPTest (r = 0.872 and 0.922, respectively, p < 0.0001 for both). Neither W'Fixed nor W'Filtered correlated significantly with W'Test (p > 0.05). Both CPFixed and CPFiltered provide valid estimates of CPTest.; however, CPFiltered provides a better estimate.

Modeling the Power-Duration Relationship in Professional Cyclists During the Giro d'Italia

ABSTRACT

Vinetti, G, Pollastri, L, Lanfranconi, F, Bruseghini, P, Taboni, A, and Ferretti, G. Modeling the power-duration relationship in professional cyclists during the Giro d'Italia. J Strength Cond Res 37(4): 866-871, 2023-Multistage road bicycle races allow the assessment of maximal mean power output (MMP) over a wide spectrum of durations. By modeling the resulting power-duration relationship, the critical power ( CP ) and the curvature constant ( W' ) can be calculated and, in the 3-parameter (3-p) model, also the maximal instantaneous power ( P0 ). Our aim is to test the 3-p model for the first time in this context and to compare it with the 2-parameter (2-p) model. A team of 9 male professional cyclists participated in the 2014 Giro d'Italia with a crank-based power meter. The maximal mean power output between 10 seconds and 10 minutes were fitted with 3-p, whereas those between 1 and 10 minutes with the 2- model. The level of significance was set at p < 0.05. 3-p yielded CP 357 ± 29 W, W' 13.3 ± 4.2 kJ, and P0 1,330 ± 251 W with a SEE of 10 ± 5 W, 3.0 ± 1.7 kJ, and 507 ± 528 W, respectively. 2-p yielded a CP and W' slightly higher (+4 ± 2 W) and lower (-2.3 ± 1.1 kJ), respectively ( p < 0.001 for both). Model predictions were within ±10 W of the 20-minute MMP of time-trial stages. In conclusion, during a single multistage racing event, the 3-p model accurately described the power-duration relationship over a wider MMP range without physiologically relevant differences in CP with respect to 2-p, potentially offering a noninvasive tool to evaluate competitive cyclists at the peak of training.

Interaction of Factors Determining Critical Power

The physiological determinants of high-intensity exercise tolerance are important for both elite human performance and morbidity, mortality and disease in clinical settings. The asymptote of the hyperbolic relation between external power and time to task failure, critical power, represents the threshold intensity above which systemic and intramuscular metabolic homeostasis can no longer be maintained. After ~ 60 years of research into the phenomenon of critical power, a clear understanding of its physiological determinants has emerged. The purpose of the present review is to critically examine this contemporary evidence in order to explain the physiological underpinnings of critical power. Evidence demonstrating that alterations in convective and diffusive oxygen delivery can impact upon critical power is first addressed. Subsequently, evidence is considered that shows that rates of muscle oxygen utilisation, inferred via the kinetics of pulmonary oxygen consumption, can influence critical power. The data reveal a clear picture that alterations in the rates of flux along every step of the oxygen transport and utilisation pathways influence critical power. It is also clear that critical power is influenced by motor unit recruitment patterns. On this basis, it is proposed that convective and diffusive oxygen delivery act in concert with muscle oxygen utilisation rates to determine the intracellular metabolic milieu and state of fatigue within the myocytes. This interacts with exercising muscle mass and motor unit recruitment patterns to ultimately determine critical power.

Use of Exercise Training to Enhance the Power-Duration Curve: A Systematic Review

ABSTRACT

Hurd, KA, Surges, MP, and Farrell, JW. Use of exercise training to enhance the power-duration curve: a systematic review. J Strength Cond Res 37(3): 733-744, 2023-The power/velocity-duration curve consists of critical power (CP), the highest work rate at which a metabolic steady state can obtained, and W' (e.g., W prime), the finite amount of work that can be performed above CP. Significant associations between CP and performance during endurance sports have been reported resulting in CP becoming a primary outcome for enhancement following exercise training interventions. This review evaluated and summarized the effects of different exercise training methodologies for enhancing CP and respective analogs. A systematic review was conducted with the assistance of a university librarian and in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Ten studies met the criteria for inclusion and were reviewed. Four, 2, 2, 1, and 1 articles included swimming, cycling, resistance training, rowing, and running, respectively. Improvements in CP, and respective analogs, were reported in 3 swimming, 2 cycling, and 1 rowing intervention. In addition, only 2 cycling and 1 swimming intervention used CP, and respective analogs, as an index of intensity for prescribing exercise training, with one cycling and one swimming intervention reporting significant improvements in CP. Multiple exercise training modalities can be used to enhance the power/velocity-duration curve. Significant improvements in CP were often reported with no observed improvements in W' or with slight decreases. Training may need to be periodized in a manner that targets enhancements in either CP or W' but not simultaneously.

Improved Estimation of Exercise Intensity Thresholds by Combining Dual Non-Invasive Biomarker Concepts: Correlation Properties of Heart Rate Variability and Respiratory Frequency

Identifying exercise intensity boundaries has been shown to be important during endurance training for performance enhancement and rehabilitation. Unfortunately, even though surrogate markers show promise when assessed on a group level, substantial deviation from gold standards can be present in each individual. The aim of this study was to evaluate whether combining two surrogate intensity markers improved this agreement. Electrocardiogram (ECG) and gas exchange data were obtained from 21 participants who performed an incremental cycling ramp to exhaustion and evaluated for first (VT1) and second (VT2) ventilatory thresholds, heart rate (HR) variability (HRV), and ECG derived respiratory frequency (EDR). HRV thresholds (HRVT) were based on the non-linear index a1 of a Detrended Fluctuation Analysis (DFA a1) and EDR thresholds (EDRT) upon the second derivative of the sixth-order polynomial of EDR over time. The average of HRVT and EDRT HR was set as the combined threshold (Combo). Mean VT1 was reached at a HR of 141 ± 15, HRVT1 at 152 ± 14 (p < 0.001), EDRT1 at 133 ± 12 (p < 0.001), and Combo1 at 140 ± 13 (p = 0.36) bpm with Pearson's r of 0.83, 0.78, and 0.84, respectively, for comparisons to VT1. A Bland-Altman analysis showed mean biases of 8.3 ± 7.9, -8.3 ± 9.5, and -1.7 ± 8.3 bpm, respectively. A mean VT2 was reached at a HR of 165 ± 13, HRVT2 at 167 ± 10 (p = 0.89), EDRT2 at 164 ± 14 (p = 0.36), and Combo2 at 164 ± 13 (p = 0.59) bpm with Pearson's r of 0.58, 0.95, and 0.94, respectively, for comparisons to VT2. A Bland-Altman analysis showed mean biases of -0.3 ± 8.9, -1.0 ± 4.6, and -0.6 ± 4.6 bpm, respectively. Both the DFA a1 and EDR intensity thresholds based on HR taken individually had moderate agreement to targets derived through gas exchange measurements. By combining both non-invasive approaches, there was improved correlation, reduced bias, and limits of agreement to the respective corresponding HRs at VT1 and VT2.

Pre-sleep protein supplementation in professional cyclists during a training camp: a three-arm randomized controlled trial

Background

The effects of pre-sleep protein supplementation on endurance athletes remain unclear, particularly whether its potential benefits are due to the timing of protein intake or solely to an increased total protein intake. We assessed the effects of pre-sleep protein supplementation in professional cyclists during a training camp accounting for the influence of protein timing.

Methods

Twenty-four professional U23 cyclists (19 ± 1 years, peak oxygen uptake: 79.8 ± 4.9 ml/kg/min) participated in a six-day training camp. Participants were randomized to consume a protein supplement (40 g of casein) before sleep (n = 8) or in the afternoon (n = 8), or an isoenergetic placebo (40 g of carbohydrates) before sleep (n = 8). Indicators of fatigue/recovery (Hooper index, Recovery-Stress Questionnaire for Athletes, countermovement jump), body composition, and performance (1-, 5-, and 20-minute time trials, as well as the estimated critical power) were assessed as study outcomes.

Results

The training camp resulted in a significant (p < 0.001) increase in training loads (e.g. training stress score of 659 ± 122 per week during the preceding month versus 1207 ± 122 during the training camp), which induced an increase in fatigue indicators (e.g. time effect for Hooper index p < 0.001) and a decrease in performance (e.g. time effect for critical power p = 0.002). Protein intake was very high in all the participants (>2.5 g/kg on average), with significantly higher levels found in the two protein supplement groups compared to the placebo group (p < 0.001). No significant between-group differences were found for any of the analyzed outcomes (all p > 0.05).

Conclusions

Protein supplementation, whether administered before sleep or earlier in the day, exerts no beneficial effects during a short-term strenuous training period in professional cyclists, who naturally consume a high-protein diet.

Field-Derived Maximal Power Output in Cycling: An Accurate Indicator of Maximal Performance Capacity?

PURPOSE

To determine the validity of field-derived mean maximum power (MMP) values for monitoring maximal cycling endurance performance.

METHODS

Twenty-seven male professional cyclists performed 3 timed trials (TTs) of 1-, 5-, and 20-minute duration that were used as the gold standard reference. Field-based power output data (3336 files; 124 [25] per cyclist) were registered during the preparatory (60 d pre-TT, including training data only) and specific period of the season (60 d post-TT, including both training and competitions). Comparisons were made between TT performance (mean power output) and MMP values obtained for efforts of the same duration as TT (MMP of 1-, 5-, and 20-min duration). The authors also compared TT- and MMP-derived values of critical power (CP) and anaerobic work capacity.

RESULTS

A large correlation (P < .001, r > .65) was found between MMP and TT performance regardless of the effort duration or season period. However, considerable differences (P < .05, standard error of measurement [SEM] > 5%) were found between MMP and TT values for all effort durations in the preparatory period, as well as for the derived CP and anaerobic work capacity. Significant differences were also found between MMP and TT of 1 minute in the specific period, as well as for anaerobic work capacity, yet with no differences for MMP of 5- and 20-minute duration or the derived CP (P > .05, SEM < 5%).

CONCLUSION

MMP values (for efforts ≥5 min) and the associated CP obtained from both training sessions and competitions can be considered overall accurate indicators of the cyclist's maximal capabilities, but specific tests might be necessary for shorter efforts or when considering training sessions only.

Determination of Critical Power Using Different Possible Approaches among Endurance Athletes: A Review

Critical power represents an important parameter of aerobic function and is the highest average effort that can be sustained for a period of time without fatigue. Critical power is determined mainly in the laboratory. Many different approaches have been applied in testing methods, and it is a difficult task to determine which testing protocol it the most suitable. This review aims to evaluate all possible tests on bicycle ergometers or bicycles used to estimate critical power and to compare them. A literature search was conducted in four databases (PubMed, Scopus, SPORTDiscus, and Web of Science) published from 2012 to 2022 and followed the PRISMA guidelines to process the review. Twenty-one articles met the eligibility criteria: records with trained or experienced endurance athletes (adults > 18), bicycle ergometer, a description of the testing protocol, and comparison of the tests. We found that the most widely used tests were the 3-min all-out tests set in a linear mode and the traditional protocol time to exhaustion. Some other alternatives could have been used but were not as regular. To summarize, the testing methods offered two main approaches in the laboratory (time to exhaustion test andthe 3-min all-out test with different protocols) and approach in the field, which is not yet completely standardized.

A longitudinal study on the interchangeable use of whole-body and local exercise thresholds in cycling

Purpose

This study longitudinally examined the interchangeable use of critical power (CP), the maximal lactate steady state (MLSS) and the respiratory compensation point (RCP) (i.e., whole-body thresholds), and breakpoints in muscle deoxygenation (m[HHb]_BP) and muscle activity (iEMG_BP) (i.e., local thresholds).

Methods

Twenty-one participants were tested on two timepoints (T1 and T2) with a 4-week period (study 1: 10 women, age = 27 ± 3 years, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{\text{peak}}}}$$\end{document}V˙O2peak = 43.2 ± 7.3 mL min⁻¹kg⁻¹) or a 12-week period (study 2: 11 men, age = 25 ± 4 years, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{\text{peak}}}}$$\end{document}V˙O2peak = 47.7 ± 5.9 mL min⁻¹ kg⁻¹) in between. The test battery included one ramp incremental test (to determine RCP, m[HHb]_BP and iEMG_BP) and a series of (sub)maximal constant load tests (to determine CP and MLSS). All thresholds were expressed as oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2) and equivalent power output (PO) for comparison.

Results

None of the thresholds were significantly different in study 1 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2: P = 0.143, PO: P = 0.281), but differences between whole-body and local thresholds were observed in study 2 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2: P < 0.001, PO: P = 0.024). Whole-body thresholds showed better 4-week test–retest reliability (TEM = 88–125 mL min⁻¹ or 6–10 W, ICC = 0.94–0.98) compared to local thresholds (TEM = 189–195 mL min⁻¹ or 15–18 W, ICC = 0.58–0.89). All five thresholds were strongly associated at T1 and T2 (r = 0.75–0.99), but their changes from T1 to T2 were mostly uncorrelated (r = − 0.41–0.83).

Conclusion

Whole-body thresholds (CP/MLSS/RCP) showed a close and consistent coherence taking into account a 3–6%-bandwidth of typical variation. In contrast, local thresholds (m[HHb]_BP/iEMG_BP) were characterized by higher variability and did not consistently coincide with the whole-body thresholds. In addition, we found that most thresholds evolved independently of each other over time. Together, these results do not justify the interchangeable use of whole-body and local exercise thresholds in practice.

Comparison of parameters derived from a three-minute all-out test with classical benchmarks for running exercise

This study aimed to compare four constructs from the three-minute all-out test (AO3)–end power (EP), the area above EP (WEP), maximum power (Pmax), and attained V˙O2peak−to those derived from the classical CP model in tethered running. Seventeen male recreational runners underwent two experiments to test for reliability and agreement of AO3 parameters with those obtained from the classical CP model (Wꞌ and CP), a graded exercise test (V˙O2max) and a 30-second all-out test (AO30s; Pmax); all performed on a non-motorized treadmill (NMT). Significance levels were set at p<0.05. There were no significant differences between test-retest for Pmax (p = 0.51), WEP (p = 0.39), and EP (p = 0.64), showing generally close to zero bias. Further, retest ICC were high for Pmax and EP (ICC > 0.86) but moderate for WEP (ICC = 0.69). Pmax showed no difference between AO3 and AO30s (p = 0.18; CV% = 9.5%). EP and WEP disagreed largely with their classical critical power model counterparts (p = 0.05; CV%>32.7% and p = 0.23; CV%>39.7%, respectively), showing greater error than their test-retest reliability. V˙O2peak from AO3 was not different (p = 0.13) and well related (CV% = 8.4; ICC = 0.87) to the incremental test V˙O2max. Under the studied conditions, the agreement of EP and WEP to CP and Wꞌ was not strong enough to assure their use interchangeably. Pmax and V˙O2max were closer to their criterion parameters.

A critical review of critical power

The elegant concept of a hyperbolic relationship between power, velocity, or torque and time to exhaustion has rightfully captivated the imagination and inspired extensive research for over half a century. Theoretically, the relationship's asymptote along the time axis (critical power, velocity, or torque) indicates the exercise intensity that could be maintained for extended durations, or the "heavy-severe exercise boundary". Much more than a critical mass of the extensive accumulated evidence, however, has persistently shown the determined intensity of critical power and its variants as being too high to maintain for extended periods. The extensive scientific research devoted to the topic has almost exclusively centered around its relationships with various endurance parameters and performances, as well as the identification of procedural problems and how to mitigate them. The prevalent underlying premise has been that the observed discrepancies are mainly due to experimental 'noise' and procedural inconsistencies. Consequently, little or no effort has been directed at other perspectives such as trying to elucidate physiological reasons that possibly underly and account for those discrepancies. This review, therefore, will attempt to offer a new such perspective and point out the discrepancies' likely root causes.

Relationship between neuromuscular fatigue, muscle activation and the work done above the critical power during severe intensity exercise

NEW FINDINGS

What is the central question of this study? Does the work done above critical power (W') or muscle activation determine the degree of peripheral fatigue induced by cycling time-trials performed in the severe intensity domain? What is the main finding and its importance? We found that peripheral fatigue increased when power output and muscle activation increased whereas W' did not change between the time-trials. Therefore, no relationship was found between W' and exercise-induced peripheral fatigue such as previously postulated in the literature. In contrast, we found a significant association between EMG amplitude during exercise and exercise-induced reduction in the potentiated quadriceps twitch, suggesting that muscle activation plays a key role in determining peripheral fatigue during severe intensity exercise.

ABSTRACT

In order to determine the relationship between peripheral fatigue, muscle activation and the total work done above critical power (W'), ten men and four women performed, on separated days, self-paced cycling time-trials of 3, 6, 10, and 15 min. Exercise-induced quadriceps fatigue was quantified using pre- to post-exercise (15 s through 15 min recovery) changes in maximal voluntary contraction peak force (MVC), voluntary activation (VA) and potentiated twitch force (QT). VA was measured using the interpolated twitch technique, and QT was evoked by electrical stimulations of the femoral nerve. Quadriceps muscle activation was determined using the root mean square of surface electromyography of vastus lateralis (VL_RMS ), vastus medialis (VM_RMS ) and rectus femoris (RF_RMS ). Critical power and W' were calculated from the power/duration relationship from the four time-trials. Mean power output and mean VL_RMS , VM_RMS and RF_RMS were greater during shorter compared to longer exercises (P<0.05) whereas no significant between-trials change in W' was found. The magnitude of exercise-induced reductions in QT increased with the increase in power output (P<0.001) and were associated with mean VL_RMS and VM_RMS (P<0.001, r² >0.369) but not W' (P>0.150, r² <0.044). Reduction in VA tended (P = 0.067) to be more pronounced with the lengthening in time-trial duration while no significant between-trials change in MVC were found. Our data suggest that peripheral fatigue is not related to the amount of work done above the critical power but rather to the level of muscle activation during exercise the severe intensity domain. This article is protected by copyright. All rights reserved.

Methodological Reconciliation of CP and MLSS and Their Agreement with the Maximal Metabolic Steady State

The critical power (CP) and maximal lactate steady state (MLSS) are operational surrogates of the maximal metabolic steady state (MMSS). However, their concordance and their agreement with MMSS remains variable likely due to methodological factors.

PURPOSE

To compare the concordance between CP and MLSS estimated by various models and criteria and their agreement with MMSS.

METHODS

After a ramp-test, ten recreationally active males performed four-to-five severe-intensity constant-power output (PO) trials to estimate CP, and three-to-four constant-PO trials to determine MLSS and identify MMSS. CP was computed using the 3-parameter hyperbolic (CP3-hyp), 2-parameter hyperbolic (CP2-hyp), linear (CPlin), and inverse of time (CP1/Tlim) models. In addition, the model with lowest combined parameter error identified the "best-fit" CP (CPbest-fit). MLSS was determined as an increase in blood lactate concentration ≤ 1 mM during constant-PO cycling from the 5th (MLSS10-30), 10th (MLSS10-30), 15th (MLSS15-30), 20th (MLSS20-30), or 25th (MLSS25-30) to 30th minute. MMSS was identified as the greatest PO associated with the highest submaximal steady state V[Combining Dot Above]O2 (MV[Combining Dot Above]O2ss).

RESULTS

Concordance between the various CP and MLSS estimates was greatest when MLSS was identified as MLSS15-30, MLSS20-30, and MLSS25-30. The PO at MV[Combining Dot Above]O2ss was 243 ± 43 W. Of the various CP models and MLSS criteria, CP2-hyp (244 ± 46 W) and CPlin (248 ± 46 W) and MLSS15-30 and MLSS20-30 (both 245 ± 46 W), respectively displayed, on average, the greatest agreement with MV[Combining Dot Above]O2ss. Nevertheless, all CP models and MLSS criteria demonstrated some degree of inaccuracies with respect to MV[Combining Dot Above]O2ss.

CONCLUSIONS

Differences between CP and MLSS can be reconciled with optimal methods of determination. When estimating MMSS, from CP the error margin of the model-estimate should be considered. For MLSS, MLSS15-30 and MLSS20-30 demonstrated the highest degree of accuracy.

Power profiling and the power-duration relationship in cycling: a narrative review

Emerging trends in technological innovations, data analysis and practical applications have facilitated the measurement of cycling power output in the field, leading to improvements in training prescription, performance testing and race analysis. This review aimed to critically reflect on power profiling strategies in association with the power-duration relationship in cycling, to provide an updated view for applied researchers and practitioners. The authors elaborate on measuring power output followed by an outline of the methodological approaches to power profiling. Moreover, the deriving a power-duration relationship section presents existing concepts of power-duration models alongside exercise intensity domains. Combining laboratory and field testing discusses how traditional laboratory and field testing can be combined to inform and individualize the power profiling approach. Deriving the parameters of power-duration modelling suggests how these measures can be obtained from laboratory and field testing, including criteria for ensuring a high ecological validity (e.g. rider specialization, race demands). It is recommended that field testing should always be conducted in accordance with pre-established guidelines from the existing literature (e.g. set number of prediction trials, inter-trial recovery, road gradient and data analysis). It is also recommended to avoid single effort prediction trials, such as functional threshold power. Power-duration parameter estimates can be derived from the 2 parameter linear or non-linear critical power model: P(t) = W′/t + CP (W′—work capacity above CP; t—time). Structured field testing should be included to obtain an accurate fingerprint of a cyclist’s power profile.

W' Recovery Kinetics after Exhaustion: A Two-Phase Exponential Process Influenced by Aerobic Fitness

PURPOSE

The aims of this study were 1) to model the temporal profile of W' recovery after exhaustion, 2) to estimate the contribution of changing V˙O2 kinetics to this recovery, and 3) to examine associations with aerobic fitness and muscle fiber type (MFT) distribution.

METHODS

Twenty-one men (age = 25 ± 2 yr, V˙O2peak = 54.4 ± 5.3 mL·min-1·kg-1) performed several constant load tests to determine critical power and W' followed by eight trials to quantify W' recovery. Each test consisted of two identical exhaustive work bouts (WB1 and WB2), separated by a variable recovery interval of 30, 60, 120, 180, 240, 300, 600, or 900 s. Gas exchange was measured and muscle biopsies were collected to determine MFT distribution. W' recovery was quantified as observed W' recovery (W'OBS), model-predicted W' recovery (W'BAL), and W' recovery corrected for changing V˙O2 kinetics (W'ADJ). W'OBS and W'ADJ were modeled using mono- and biexponential fitting. Root-mean-square error (RMSE) and Akaike information criterion (∆AICC) were used to evaluate the models' accuracy.

RESULTS

The W'BAL model (τ = 524 ± 41 s) was associated with an RMSE of 18.6% in fitting W'OBS and underestimated W' recovery for all durations below 5 min (P < 0.002). Monoexponential modeling of W'OBS resulted in τ = 104 s with RMSE = 6.4%. Biexponential modeling of W'OBS resulted in τ1 = 11 s and τ2 = 256 s with RMSE = 1.7%. W'ADJ was 11% ± 1.5% lower than W'OBS (P < 0.001). ∆AICC scores favored the biexponential model for W'OBS, but not for W'ADJ. V˙O2peak (P = 0.009) but not MFT distribution (P = 0.303) was associated with W'OBS.

CONCLUSION

We showed that W' recovery from exhaustion follows a two-phase exponential time course that is dependent on aerobic fitness. The appearance of a fast initial recovery phase was attributed to an enhanced aerobic energy provision resulting from changes in V˙O2 kinetics.

Steady-state [Formula: see text] above MLSS: evidence that critical speed better represents maximal metabolic steady state in well-trained runners

The metabolic boundary separating the heavy-intensity and severe-intensity exercise domains is of scientific and practical interest but there is controversy concerning whether the maximal lactate steady state (MLSS) or critical power (synonymous with critical speed, CS) better represents this boundary. We measured the running speeds at MLSS and CS and investigated their ability to discriminate speeds at which \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 was stable over time from speeds at which a steady-state \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 could not be established. Ten well-trained male distance runners completed 9–12 constant-speed treadmill tests, including 3–5 runs of up to 30-min duration for the assessment of MLSS and at least 4 runs performed to the limit of tolerance for assessment of CS. The running speeds at CS and MLSS were significantly different (16.4 ± 1.3 vs. 15.2 ± 0.9 km/h, respectively; P < 0.001). Blood lactate concentration was higher and increased with time at a speed 0.5 km/h higher than MLSS compared to MLSS (P < 0.01); however, pulmonary \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 did not change significantly between 10 and 30 min at either MLSS or MLSS + 0.5 km/h. In contrast, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 increased significantly over time and reached \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2\,\,\max }$$\end{document}V˙O2max at end-exercise at a speed ~ 0.4 km/h above CS (P < 0.05) but remained stable at a speed ~ 0.5 km/h below CS. The stability of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 at a speed exceeding MLSS suggests that MLSS underestimates the maximal metabolic steady state. These results indicate that CS more closely represents the maximal metabolic steady state when the latter is appropriately defined according to the ability to stabilise pulmonary \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2.

Peak Running Velocity or Critical Speed Under Field Conditions: Which Best Predicts 5-km Running Performance in Recreational Runners?

This study aimed to examine which variable, between the peak running velocity determined on the track field (V_{peak_TF}) and critical speed (CS), is the best predictor of the 5-km running performance in recreational runners. Twenty-five males performed three tests to determine the V_{peak_TF}, CS, and 5-km running performance on the track field, with a minimal interval of 48 h between each test. The V_{peak_TF} protocol started with a velocity of 8 km⋅h^–1, followed by an increase of 1 km⋅h^–1 every 3 min until volitional exhaustion, which was controlled by sound signals, with cones at every 25 m indicating when the participants were required to pass the cone’s position to maintain the required velocity. The participants performed three time trials (TTs) (1: 2,600 m; 2: 1,800 m; and 3: 1,000 m) on the same day, with a 30-min rest period to determine the CS through the combinations of three (CS₁,₂,₃) and two TTs (CS₁,₂, CS₁,₃, and CS₂,₃). The 5-km running performance time was recorded to determine the test duration, and the mean velocity (MV) was calculated. There was a significant difference observed between the V_{peak_TF} and the MV 5-km running performance. However, no differences were found between the CS values and the MV 5-km running performance. A correlation was observed between the V_{peak_TF} (R = −0.90), CS₁,₂,₃ (R = −0.95), CS₁,₃ (R = −0.95), and the 5-km running performance time. Linear regression indicated that the V_{peak_TF} (R² = 0.82), CS₁,₂,₃ (R² = 0.90), and CS₁,₃ (R² = 0.90) significantly predicted the 5-km running performance time. The CS results showed a higher predictive power for the 5-km running performance, slightly better than the V_{peak_TF}. Also, CS₁,₂,₃ and the CS₁,₃ presented the highest predictive power for the 5-km running performance of recreational runners.

Critical speed estimated by statistically appropriate fitting procedures

PURPOSE

Intensity domains are recommended when prescribing exercise. The distinction between heavy and severe domains is made by the critical speed (CS), therefore requiring a mathematically accurate estimation of CS. The different model variants (distance versus time, running speed versus time, time versus running speed, and distance versus running speed) are mathematically equivalent. Nevertheless, error minimization along the correct axis is important to estimate CS and the distance that can be run above CS (d'). We hypothesized that comparing statistically appropriate fitting procedures, which minimize the error along the axis corresponding to the properly identified dependent variable, should provide similar estimations of CS and d' but that different estimations should be obtained when comparing statistically appropriate and inappropriate fitting procedure.

METHODS

Sixteen male runners performed a maximal incremental aerobic test and four exhaustive runs at 90, 100, 110, and 120% of their peak speed on a treadmill. Several fitting procedures (a combination of a two-parameter model variant and regression analysis: weighted least square) were used to estimate CS and d'.

RESULTS

Systematic biases (P < 0.001) were observed between each pair of fitting procedures for CS and d', even when comparing two statistically appropriate fitting procedures, though negligible, thus corroborating the hypothesis.

CONCLUSION

The differences suggest that a statistically appropriate fitting procedure should be chosen beforehand by the researcher. This is also important for coaches that need to prescribe training sessions to their athletes based on exercise intensity, and their choice should be maintained over the running seasons.

The ramp and all-out exercise test to determine critical power: validity and robustness to manipulations in body position

Purpose

The purpose of the present study was to determine whether a contiguous ramp and all-out exercise test could accurately determine critical power (CP) in a single laboratory visit during both upright and supine cycle exercise.

Methods

Healthy males completed maximal ramp-incremental exercise on a cycle ergometer in the upright (n = 15) and supine positions (n = 8), with task failure immediately followed by a 3-min all-out phase for determination of end-test power (EP). On separate days, participants undertook four constant-power tests in either the upright or supine positions with the limit of tolerance ranging from ~ 2 to 15 min for determination of CP.

Results

During upright exercise, EP was highly correlated with (R² = 0.93, P < 0.001) and not different from CP (CP = 221 ± 40 W vs. EP = 226 ± 46 W, P = 0.085, 95% limits of agreement − 30, 19 W). During supine exercise, EP was also highly correlated with (R² = 0.94, P < 0.001) and not different from CP (CP = 140 ± 42 W vs. EP = 136 ± 40 W, P = 0.293, 95% limits of agreement − 16, 24 W).

Conclusion

The present data suggest that EP derived from a contiguous ramp all-out exercise test is not different from the gold-standard method of CP determination during both upright and supine cycle exercise when assessed at the group level. However, the wide limits of agreement observed within the present study suggest that EP and CP should not be used interchangeably.

W' Reconstitution Accelerates More with Decreasing Intensity in the Heavy- versus the Moderate-Intensity Domain

INTRODUCTION

The purpose of this study was to investigate the effect of the recovery intensity domain on W' reconstitution. We used the W'BAL model as a framework and tested its predictive capabilities (W'PRED) across the different intensity domains.

METHODS

Twelve young men (51.7 ± 5.9 mL·kg-1·min-1) completed a ramp incremental test, three to five constant power output (PO) tests to determine critical power (CP) and W', and minimally two trials to verify the maximal lactate (La-) steady state. During four experimental trials, subjects performed two work bouts (WB1 and WB2) at P6 (i.e., PO that predicts exhaustion within 6 min) separated by a recovery interval at CP-10 W, Δgas exchange threshold (GET)-CP, GET, and 50% GET, respectively. WB1 was designed to deplete 75% W', and the recovery time varied to replenish 50% W'. WB2 was performed to exhaustion (W'ACT). W'PRED was compared with W'ACT to evaluate the accuracy of the W'BAL model. Excess postexercise oxygen consumption was calculated as the difference between the measured and the predicted oxygen uptake during recovery.

RESULTS

W'ACT averaged 49% ± 24%, 69% ± 24%, 81% ± 28%, and 93% ± 21% for CP-10 W, ΔGET-CP, GET, and 50% GET, respectively (P = 0.002). W'PRED overestimated W'ACT in CP-10 W (34% ± 32%, P = 0.004) and underestimated W'ACT in 50% GET (24% ± 28%, P = 0.013). Excess postexercise oxygen consumption was lowest in CP-10 W (P < 0.01) and higher in GET compared with ΔGET-CP (P = 0.01).

CONCLUSION

We demonstrated that W'PRED overestimated and underestimated W'ACT in the heavy- and moderate-intensity domain, respectively. Therefore, the practical applicability of a single recovery time constant, which only relies on the difference between the recovery PO and the CP, is questionable.

Critical oxygenation: Can muscle oxygenation inform us about critical power?

The power-duration relationship is well documented for athletic performance and is formulated out mathematically in the critical power (CP) model. The CP model, when applied properly, has great predictive power, e.g. pedaling at a specific power output on an ergometer the model precisely calculates the time over which an athlete can sustain this power. However, CP presents physiological inconsistencies and process-oriented problems. The rapid development of near-infrared spectroscopy (NIRS) to measure muscle oxygenation (SmO₂) dynamics provides a physiological exploration of the CP model on a conceptual and empirical level. Conceptually, the CP model provides two components: first CP is defined as the highest metabolic rate that can be achieved through oxidative means. And second, work capacity above CP named W'. SmO₂ presents a steady-state in oxygen supply and demand and thereby represents CP specifically at a local level of analysis. Empirically, exploratory data quickly illustrates the relationship between performance and SmO₂, as shown during 3-min all-out cycling tests to assess CP. During these tests, performance and SmO₂ essentially mirror each other, and both CP and W' generate solid correlation with what would be deemed their SmO₂ counterparts: first, the steady-state of SmO₂ correlates with CP. And second, the tissue oxygen reserve represented in SmO₂, when calculated as an integral corresponds to W'. While the empirical data presented is preliminary, the proposition of a concurring physiological model to the current CP model is a plausible inference. Here we propose that SmO₂ steady-state representing CP as critical oxygenation or CO. And the tissue oxygen reserve above CO would then be identified as O'. This new CO model could fill in the physiological gap between the highly predictive CP model and at times its inability to track human physiology consistently. For simplicity's sake, this would include acute changes in physiology as a result of changing climate or elevation with travel, which can affect performance. These types of acute fluctuations, but not limited to, would be manageable when applying a CO model in conjunction with the CP model. Further, modeling is needed to investigate the true potential of NIRS to model CP, with a focus on repeatability, recovery, and systemic vs local workloads.

Power Profiling in U23 Professional Cyclists During a Competitive Season

PURPOSE

The aim of this study was to investigate changes in the power profile of U23 professional cyclists during a competitive season based on maximal mean power output (MMP) and derived critical power (CP) and work capacity above CP (W') obtained during training and racing.

METHODS

A total of 13 highly trained U23 professional cyclists (age = 21.1 [1.2] y, maximum oxygen consumption = 73.8 [1.9] mL·kg-1·min-1) participated in this study. The cycling season was split into pre-season and in-season. In-season was divided into early-, mid-, and late-season periods. During pre-season, a CP test was completed to derive CPtest and W'test. In addition, 2-, 5-, and 12-minute MMP during in-season were used to derive CPfield and W'field.

RESULTS

There were no significant differences in absolute 2-, 5-, and 12-minute MMP, CPfield, and W'field between in-season periods. Due to changes in body mass, relative 12-minute MMP was higher in late-season compared with early-season (P = .025), whereas relative CPfield was higher in mid- and late-season (P = .031 and P = .038, respectively) compared with early-season. There was a strong correlation (r = .77-.83) between CPtest and CPfield in early- and mid-season but not late-season. Bland-Altman plots and standard error of estimates showed good agreement between CPtest and in-season CPfield but not between W'test and W'field.

CONCLUSION

These findings reveal that the power profile remains unchanged throughout the in-season, except for relative 12-minute MMP and CPfield in late-season. One pre-season and one in-season CP test are recommended to evaluate in-season CPfield and W'field.

Determination of the speed-time relationship during handcycling in spinal cord injured athletes

This study aimed to determine the critical speed (CS) and the work above CS (D') from three mathematical models of para-athletes during a treadmill handcycling exercise. Nine hand-cyclists with spinal cord injuries performed a maximal incremental handcycling test and three tests to exhaustion at a constant speed to determine the speed-time relationship. The three tests to exhaustion were performed at intensities between 90% and 105% of peak speed derived from the incremental test. Then, the determination of CS and D' was modelled by linear and hyperbolic models. CS and D' did not present any significant differences among the three mathematical models. Low values in the standard error of estimate for CS were found for the three models (Linear: Distance-time: 1.7 ± 0.5%; Linear: Speed-1/time: 3.0 ± 1.9% and Hyperbolic: 1.2 ± 0.6%). Based on the simplicity to calculate, the CS modelled by linear-distance-time can be a practical method for handcyclist coaches.

Agreement of maximal lactate steady state with critical power and physiological thresholds in rowing

The aim of this study was threefold: (a) to compare the maximal lactate steady state (MLSS) with critical power (CP); (b) to describe the relationship of MLSS with rowing performances; and (c) to verify the agreement of MLSS with several exercise intensity thresholds in rowers. Fourteen male rowers (mean [SD]: age = 26 [13] years; height = 1.82 [0.05] m; body mass = 81.0 [7.6] kg) performed on a rowing ergometer: (I) discontinuous incremental test with 3 min stages and 30-s recovery intervals (INC_3min); (II) continuous incremental test with 60-s stages (INC_1min); (III) two to four constant workload tests to determine MLSS; and (IV) performance tests of 500, 1000, 2000 and 6000 m to determine CP. Twenty-seven exercise intensity thresholds based on blood lactate, heart rate and ventilatory responses were determined by incremental tests, and then compared with MLSS. CP (257 [38] W) was higher than MLSS (187 [25] W; p < 0.001), with a very large mean difference (37%), large typical error of estimate (14%) and moderate correlation (r = 0.48). Despite the correlations between MLSS and most intensity thresholds (r > 0.70), all presented low correspondence (TEE > 5%), with a lower bias found between MLSS and the first intensity thresholds (-12.5% to 4.1%). MLSS was correlated with mean power during 500 m (r = 0.65), 1000 m (r = 0.86) and 2000 m (r = 0.78). In conclusion, MLSS intensity is substantially lower than CP and presented low agreement with 27 incremental-derived thresholds, questioning their use to estimate MLSS during rowing ergometer exercise.Highlights MLSS was substantially lower than CP in rowing exercise with a mean difference of 37%, much larger than the difference commonly found in running and cycling exercise (i.e., ?10%).A clear disagreement was reported between MLSS and 27 physiological thresholds determined in different incremental tests.There is a positive association of MLSS with 500, 1000 and 2000 m rowing ergometer performance tests.

Relationship Between the Critical Power Test and a 20-min Functional Threshold Power Test in Cycling

To investigate the agreement between critical power (CP) and functional threshold power (FTP), 17 trained cyclists and triathletes (mean ± SD: age 31 ± 9 years, body mass 80 ± 10 kg, maximal aerobic power 350 ± 56 W, peak oxygen consumption 51 ± 10 mL⋅min^-1⋅kg^-1) performed a maximal incremental ramp test, a single-visit CP test and a 20-min time trial (TT) test in randomized order on three different days. CP was determined using a time-trial (TT) protocol of three durations (12, 7, and 3 min) interspersed by 30 min passive rest. FTP was calculated as 95% of 20-min mean power achieved during the TT. Differences between means were examined using magnitude-based inferences and a paired-samples t-test. Effect sizes are reported as Cohen's d. Agreement between CP and FTP was assessed using the 95% limits of agreement (LoA) method and Pearson correlation coefficient. There was a 91.7% probability that CP (256 ± 50 W) was higher than FTP (249 ± 44 W). Indeed, CP was significantly higher compared to FTP (P = 0.041) which was associated with a trivial effect size (d = 0.04). The mean bias between CP and FTP was 7 ± 13 W and LoA were -19 to 33 W. Even though strong correlations exist between CP and FTP (r = 0.969; P < 0.001), the chance of meaningful differences in terms of performance (1% smallest worthwhile change), were greater than 90%. With relatively large ranges for LoA between variables, these values generally should not be used interchangeably. Caution should consequently be exercised when choosing between FTP and CP for the purposes of performance analysis.

Field-Derived Power-Duration Variables to Predict Cycling Time-Trial Performance

PURPOSE

To evaluate the predictive validity of critical power (CP) and the work above CP (W') on cycling performance (mean power during a 20-min time trial; TT20).

METHODS

On 3 separate days, 10 male cyclists completed a TT20 and 3 CP and W' prediction trials of 1, 4, and 10 min and 2, 7, and 12 min in field conditions. CP and W' were modeled across combinations of these prediction trials with the hyperbolic, linear work/time, and linear power inverse-time (INV) models. The agreement and the uncertainty between the predicted and actual TT20 were assessed with 95% limits of agreement and a probabilistic approach, respectively.

RESULTS

Differences between the predicted and actual TT20 were "trivial" for most of the models if the 1-min trial was not included. Including the 1-min trial in the INV and linear work/time models "possibly" to "very likely" overestimated TT20. The INV model provided the smallest total error (ie, best individual fit; 6%) for all cyclists (305 [33] W; 19.6 [3.6] kJ). TT20 predicted from the best individual fit-derived CP, and W' was strongly correlated with actual TT20 (317 [33] W; r = .975; P < .001). The bias and 95% limits of agreement were 4 (7) W (-11 to 19 W).

CONCLUSIONS

Field-derived CP and W' accurately predicted cycling performance in the field. The INV model was most accurate to predict TT20 (1.3% [2.4%]). Adding a 1-min-prediction trial resulted in large total errors, so it should not be included in the models.

Maximal Lactate Steady State Versus the 20-Minute Functional Threshold Power Test in Well-Trained Individuals: "Watts" the Big Deal?

PURPOSE

To (1) compare the power output (PO) for both the 20-minute functional threshold power (FTP20) field test and the calculated 95% (FTP95%) with PO at maximal lactate steady state (MLSS) and (2) evaluate the sensitivity of FTP95% and MLSS to training-induced changes.

METHODS

Eighteen participants (12 males: 37 [6] y and 6 females: 28 [6] y) performed a ramp-incremental cycling test to exhaustion, 2 to 3 constant-load MLSS trials, and an FTP20 test. A total of 10 participants returned to repeat the test series after 7 months of training.

RESULTS

The PO at FTP20 and FTP95% was greater than that at MLSS (P = .00), with the PO at MLSS representing 88.5% (4.8%) and 93.1% (5.1%) of FTP and FTP95%, respectively. MLSS was greater at POST compared with PRE training (12 [8] W) (P = .002). No increase was observed in mean PO at FTP20 and FTP95% (P = .75).

CONCLUSIONS

The results indicate that the PO at FTP95% is different to MLSS, and that changes in the PO at MLSS after training were not reflected by FTP95%. Even when using an adjusted percentage (ie, 88% rather than 95% of FTP20), the large variability in the data is such that it would not be advisable to use this as a representation of MLSS.

Development and field validation of an omni-domain power-duration model

Purpose: To validate and compare a novel model based on the critical power (CP) concept that describes the entire domain of maximal mean power (MMP) data from cyclists.Methods: An omni-domain power-duration (OmPD) model was derived whereby the rate of W' expenditure is bound by maximum sprint power and the power at prolonged durations declines from CP log-linearly. The three-parameter CP (3CP) and exponential (Exp) models were likewise extended with the log-linear decay function (Om3CP and OmExp). Each model bounds W' using a different nonconstant function, W'eff (effective W'). Models were fit to MMP data from nine cyclists who also completed four time-trials (TTs).Results: The OmPD and Om3CP residuals (4 ± 1%) were smaller than the OmExp residuals (6 ± 2%; P < 0.001). W'eff predicted by the OmPD model was stable between 120-1,800 s, whereas it varied for the Om3CP and OmExp models. TT prediction errors were not different between models (7 ± 5%, 8 ± 5%, 7 ± 6%; P = 0.914).Conclusion: The OmPD offers similar or superior goodness-of-fit and better theoretical properties compared to the other models, such that it best extends the CP concept to short-sprint and prolonged-endurance performance.

Time to exhaustion during cycling is not well predicted by critical power calculations

Three to 5 cycling tests to exhaustion allow prediction of time to exhaustion (TTE) at power output based on calculation of critical power (CP). We aimed to determine the accuracy of CP predictions of TTE at power outputs habitually endured by cyclists. Fourteen endurance-trained male cyclists underwent 4 randomized cycle-ergometer TTE tests at power outputs eliciting (i) mean Wingate anaerobic test (WAnT_mean), (ii) maximal oxygen consumption, (iii) respiratory compensation threshold (VT₂), and (iv) maximal lactate steady state (MLSS). Tests were conducted in duplicate with coefficient of variation of 5%-9%. Power outputs were 710 ± 63 W for WAnT_mean, 366 ± 26 W for maximal oxygen consumption, 302 ± 31 W for VT₂ and 247 ± 20 W for MLSS. Corresponding TTE were 00:29 ± 00:06, 03:23 ± 00:45, 11:29 ± 05:07, and 76:05 ± 13:53 min:s, respectively. Power output associated with CP was only 2% lower than MLSS (242 ± 19 vs. 247 ± 20 W; P < 0.001). The CP predictions overestimated TTE at WAnT_mean (00:24 ± 00:10 mm:ss) and MLSS (04:41 ± 11:47 min:s), underestimated TTE at VT₂ (-04:18 ± 03:20 mm:ss; P < 0.05), and correctly predicted TTE at maximal oxygen consumption. In summary, CP accurately predicts MLSS power output and TTE at maximal oxygen consumption. However, it should not be used to estimate time to exhaustion in trained cyclists at higher or lower power outputs (e.g., sprints and 40-km time trials). Novelty CP calculation enables to predict TTE at any cycling power output. We tested those predictions against measured TTE in a wide range of cycling power outputs. CP appropriately predicted TTE at maximal oxygen consumption intensity but err at higher and lower cycling power outputs.

Training-Induced Changes in the Respiratory Compensation Point, Deoxyhemoglobin Break Point, and Maximal Lactate Steady State: Evidence of Equivalence

PURPOSE

To evaluate whether the coherence in the oxygen uptake (V˙O2) associated with the respiratory compensation point (RCP), near-infrared spectroscopy-derived muscle deoxyhemoglobin ([HHb]) break point ([HHb]BP), and maximal lactate steady state (MLSS) would persist at the midpoint and endpoint of a 7-month training and racing season.

METHODS

Eight amateur male cyclists were tested in 3 separate phases over the course of a cycling season (PRE, MID, and POST). Testing at each phase included a ramp-incremental test to exhaustion to determine RCP and [HHb]BP. The PRE and POST phases also included constant power output rides to determine MLSS.

RESULTS

Compared with PRE, V˙O2 at both RCP and [HHb]BP was greater at MID (delta: RCP 0.23 [0.14] L·min-1, [HHb]BP 0.33 [0.17] L·min-1) and POST (delta: RCP 0.21 [0.12], [HHb]BP 0.30 [0.14] L·min-1) (P < .05). V˙O2 at MLSS also increased from PRE to POST (delta: 0.17 [12] L·min-1) (P < .05). V˙O2 was not different at RCP, [HHb]BP, and MLSS at PRE (3.74 [0.34], 3.64 [0.40], 3.78 [0.23] L·min-1) or POST (3.96 [0.25], 3.95 [0.32], 3.94 [0.18] L·min-1) respectively, and RCP (3.98 [0.33] L·min-1) and [HHb]BP (3.97 [0.34] L·min-1) were not different at MID (P > .05). PRE-MID and PRE-POST changes in V˙O2 associated with RCP, [HHb]BP, and MLSS were strongly correlated (range: r = .85-.90) and demonstrated low mean bias (range = -.09 to .12 L·min-1).

CONCLUSIONS

At all measured time points, V˙O2 at RCP, [HHb]BP, and MLSS were not different. Irrespective of phase comparison, direction, or magnitude of V˙O2 changes, intraindividual changes between each index were strongly related, indicating that interindividual differences were reflected in the group mean response and that their interrelationships are beyond coincidental.

Establishing the V̇o2 versus constant-work-rate relationship from ramp-incremental exercise: simple strategies for an unsolved problem

The dissociation between constant work rate of O₂ uptake (V̇o₂) and ramp V̇o₂ at a given work rate might be mitigated during slowly increasing ramp protocols. This study characterized the V̇o₂ dynamics in response to five different ramp protocols and constant-work-rate trials at the maximal metabolic steady state (MMSS) to characterize 1) the V̇o₂ gain (G) in the moderate, heavy, and severe domains, 2) the mean response time of V̇o₂ (MRT), and 3) the work rates at lactate threshold (LT) and respiratory compensation point (RCP). Eleven young individuals performed five ramp tests (5, 10, 15, 25, and 30 W/min), four to five time-to-exhaustions for critical power estimation, and two to three constant-work-rate trials for confirmation of the work rate at MMSS. G was greatest during the slowest ramp and progressively decreased with increasing ramp slopes (from ~12 to ~8 ml·min^-1·W^-1, P < 0.05). The MRT was smallest during the slowest ramp slopes and progressively increased with faster ramp slopes (1 ± 1, 2 ± 1, 5 ± 3, and 10 ± 4, 15 ± 6 W, P < 0.05). After "left shifting" the ramp V̇o₂ by the MRT, the work rate at LT was constant regardless of the ramp slope (~150 W, P > 0.05). The work rate at MMSS was 215 ± 55 W and was similar and highly correlated with the work rate at RCP during the 5 W/min ramp (P > 0.05, r = 0.99; Lin's concordance coefficient = 0.99; bias = -3 W; root mean square error = 6 W). Findings showed that the dynamics of V̇o₂ (i.e., G) during ramp exercise explain the apparent dichotomy existing with constant-work-rate exercise. When these dynamics are appropriately "resolved", LT is constant regardless of the ramp slope of choice, and RCP and MMSS display minimal variations between each other.NEW & NOTEWORTHY This study demonstrates that the dynamics of V̇o₂ during ramp-incremental exercise are dependent on the characteristics of the increments in work rate, such that during slow-incrementing ramp protocols the magnitude of the dissociation between ramp V̇o₂ and constant V̇o₂ at a given work rate is reduced. Accurately accounting for these dynamics ensures correct characterizations of the V̇o₂ kinetics at ramp onset and allows appropriate comparisons between ramp and constant-work-rate exercise-derived indexes of exercise intensity.

Effects of Submaximal Performances on Critical Speed and Power: Uses of an Arbitrary-Unit Method with Different Protocols

The effects of submaximal performances on critical speed (S_Crit) and critical power (P_Crit) were studied in 3 protocols: a constant-speed protocol (protocol 1), a constant-time protocol (protocol 2) and a constant-distance protocol (protocol 3). The effects of submaximal performances on S_Crit and P_Crit were studied with the results of two theoretical maximal exercises multiplied by coefficients lower or equal to 1 (from 0.8 to 1 for protocol 1; from 0.95 to 1 for protocols 2 and 3): coefficient C₁ for the shortest exercises and C₂ for the longest exercises. Arbitrary units were used for exhaustion times (t_lim), speeds (or power-output in cycling) and distances (or work in cycling). The submaximal-performance effects on S_Crit and P_Crit were computed from two ranges of t_lim (1–4 and 1–7). These effects have been compared for a low-endurance athlete (exponent = 0.8 in the power-law model of Kennelly) and a high-endurance athlete (exponent = 0.95). Unexpectedly, the effects of submaximal performances on S_Crit and P_Crit are lower in protocol 1. For the 3 protocols, the effects of submaximal performances on S_Crit, and P_Crit, are low in many cases and are lower when the range of t_lim is longer. The results of the present theoretical study confirm the possibility of the computation of S_Crit and P_Crit from several submaximal exercises performed in the same session.