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

Running Functional Threshold versus Critical Power: Same Concept but Different Values

The aims of this study were (i) to estimate the functional threshold power (FTP) and critical power (CP) from single shorter time trials (TTs) (i. e. 10, 20 and 30 minutes) and (ii) to assess their location in the power-duration curve. Fifteen highly trained athletes randomly performed ten TTs (i. e. 1, 2, 3, 4, 5, 10, 20, 30, 50 and 60 minutes). FTP was determined as the mean power output developed in the 60-min TT, while CP was estimated in the running power meter platform according to the manufacturer's recommendations. The linear regression analysis revealed an acceptable FTP estimate for the 10, 20 and 30-min TTs (SEE≤12.27 W) corresponding to a correction factor of 85, 90 and 95%, respectively. An acceptable CP estimate was only observed for the 20-min TT (SEE=6.67 W) corresponding to a correction factor of 95%. The CP was located at the 30-min power output (1.0 [-5.1 to 7.1] W), which was over FTP (14 [7.0 to 21] W). Therefore, athletes and practitioners concerned with determining FTP and CP through a feasible testing protocol are encouraged to perform a 20-min TT and apply a correction factor of 90 and 95%, respectively.

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.

Functional threshold power and the critical-power controversy

Scrutinizing functional threshold power via controversial concepts leads to confusion and discreditation of a valuable performance marker. This letter attempts to sort out the controversies.

Effect of varying recovery intensities on power outputs during severe intensity intervals in trained cyclists during the Covid-19 pandemic

Purpose

The study aimed to investigate the effects of different recovery intensities on the power outputs of repeated severe intensity intervals and the implications for W' reconstitution in trained cyclists.

Methods

Eighteen trained cyclists (FTP 258.0 ± 42.7 W; weekly training 8.6 ± 1.7 h∙week-1) familiar with interval training, use of the Zwift® platform throughout the Covid-19 pandemic, and previously established FTP (95% of mean power output from a 20-min test), performed 5 × 3-min severe intensity efforts interspersed with 2-min recoveries. Recovery intensities were: 50 W (LOW), 50% of functional threshold power (MOD), and self-selected power output (SELF).

Results

Whilst power outputs declined as the session progressed, mean power outputs during the severe intervals across the conditions were not different to each other (LOW 300.1 ± 48.1 W; MOD: 296.9 ± 50.4 W; SELF: 298.8 ± 53.3 W) despite the different recovery conditions. Mean power outputs of the self-selected recovery periods were 121.7 ± 26.2 W. However, intensity varied during the self-selected recovery periods, with values in the last 15 s being greater than the first 15 s (p < 0.001) and decreasing throughout the session (128.7 ± 25.4 W to 113.9 ± 29.3 W).

Conclusion

Reducing recovery intensities below 50% of FTP failed to enhance subsequent severe intensity intervals, suggesting that a lower limit for optimal W' reconstitution had been reached. As self-selected recoveries were seen to adapt to maintain the severe intensity power output as the session progressed, adopting such a strategy might be preferential for interval training sessions.

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.

Bootstrapping Time-Varying Uncertainty Intervals for Extreme Daily Return Periods

This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping and backtest density forecasts, which are based on a weighted threshold and quantile of a continuously ranked probability score, are developed. Developed backtesting procedures revealed that an estimated Seasonal autoregressive integrated moving average-generalized autoregressive score-generalized extreme value distribution (SARIMA–GAS–GEVD) with a skewed student-t distribution had the best prediction performance in forecasting and bootstrapping VaR and ES. Extension of this non-stationary distribution in literature is quite complicated since it requires specifications not only on how the usual Bayesian parameters change over time but also those with bulk distribution components. This implies that the combination of a stochastic econometric model with extreme value theory (EVT) procedures provides a robust basis necessary for the statistical backtesting and bootstrapping density predictions for VaR and ES.

Impact of a Cold Environment on the Performance of Professional Cyclists: A Pilot Study

The practice of physical activity in a variable climate during the same competition is becoming more and more common due to climate change and increasingly frequent climate disturbances. The main aim of this pilot study was to understand the impact of cold ambient temperature on performance factors during a professional cycling race. Six professional athletes (age = 27 ± 2.7 years; height = 180.86 ± 5.81 cm; weight = 74.09 ± 9.11 kg; % fat mass = 8.01 ± 2.47%; maximum aerobic power (MAP) = 473 ± 26.28 W, undertook ~20 h training each week at the time of the study) participated in the Tour de la Provence under cold environmental conditions (the ambient temperature was 15.6 ± 1.4 °C with a relative humidity of 41 ± 8.5% and the normalized ambient temperature (T_awc) was 7.77 ± 2.04 °C). Body core temperature (T_co) was measured with an ingestible capsule. Heart rate (HR), power, speed, cadence and the elevation gradient were read from the cyclists’ onboard performance monitors. The interaction (multivariate analysis of variance) of the T_awc and the elevation gradient has a significant impact (F(1.5) = 32.2; p < 0.001) on the variables (cadence, power, velocity, core temperature, heart rate) and on each individual. Thus, this pilot study shows that in cold environmental conditions, the athlete’s performance was limited by weather parameters (ambient temperature associated with air velocity) and race characteristics. The interaction of T_awc and elevation gradient significantly influences thermal (T_co), physiological (HR) and performance (power, speed and cadence) factors. Therefore, it is advisable to develop warm-up, hydration and clothing strategies for competitive cycling under cold ambient conditions and to acclimatize to the cold by training in the same conditions to those that may be encountered in competition.

Functional Threshold Power Estimated from a 20-minute Time-trial Test is Warm-up-dependent

This study investigated the influence of different warm-up protocols on functional threshold power. Twenty-one trained cyclists (˙VO₂max=60.2±6.8 ml·kg^-1·min^-1) performed an incremental test and four 20-min time trials preceded by different warm-up protocols. Two warm-up protocols lasted 45 min, with a 5-min time trial performed either 15 min (Traditional) or 25 min (Reverse) before the 20-min time trial. The other two warm-up protocols lasted 25 min (High Revolutions-per minute) and 10 min (Self-selected), including three fast accelerations and self-selected intensity, respectively. The power outputs achieved during the 20-min time trial preceded by the Traditional and Reverse warm-up protocols were significantly lower than the High Revolutions-per-minute and Self-selected protocols (256±30; 257±30; 270±30; 270±30 W, respectively). Participants chose a conservative pacing strategy at the onset (negative) for the Traditional and Reverse but implemented a fast-start strategy (U-shaped) for the High revolutions-per-minute and Self-selected warm-up protocols. In conclusion, 20-min time-trial performance and pacing are affected by different warm-ups. Consequently, the resultant functional threshold power may be different depending on whether the original protocol with a 5-min time trial is followed or not.

What is known about the FTP20 test related to cycling? A scoping review

Functional Threshold Power (FTP) in cycling is increasingly used in exercise prescription, particularly with the rise in use of home trainers and virtual exercise platforms. FTP testing does not require biological sampling and is considered a more practical test than others. This scoping review investigated what is known about the 20-minute FTP (FTP²⁰) test. A three-step search strategy was used to identify studies in relevant databases (PubMed, CINAHL, SportDiscus, Google Scholar, Web of Science) and grey literature. Data were extracted and common themes identified which allowed for descriptive analysis and thematic summary. Fifteen studies were included. The primary focus fitted broadly into four themes: reliability, association with other physiological markers, other power-related concepts and performance prediction. The FTP²⁰ test was reported as a reliable test. Studies investigating the relationship of FTP²⁰ with other physiological markers and power-related concepts reported large limits of agreement suggesting parameters cannot be used interchangeably. Some findings indicate that FTP²⁰ may be useful in performance prediction. The majority of studies involved trained male cyclists. Overall, existing literature on the FTP²⁰ test is limited. Further investigation is needed to provide physiological justification for FTP²⁰ and inform use in exercise prescription in a range of populations.

Relationship Between Critical Power and Different Lactate Threshold Markers in Recreational Cyclists

Purpose: To analyze the relationship between critical power (CP) and different lactate threshold (LT2) markers in cyclists.

Methods: Seventeen male recreational cyclists [33 ± 5 years, peak power output (PO) = 4.5 ± 0.7 W/kg] were included in the study. The PO associated with four different fixed (onset of blood lactate accumulation) and individualized (Dmax_exp, Dmax_pol, and LT_Δ1) LT2 markers was determined during a maximal incremental cycling test, and CP was calculated from three trials of 1-, 5-, and 20-min duration. The relationship and agreement between each LT2 marker and CP were then analyzed.

Results: Strong correlations (r = 0.81–0.98 for all markers) and trivial-to-small non-significant differences (Hedges’ g = 0.01–0.17, bias = 1–9 W, and p > 0.05) were found between all LT2 markers and CP with the exception of Dmax_exp, which showed the strongest correlation but was slightly higher than the CP (Hedges’ g = 0.43, bias = 20 W, and p < 0.001). Wide limits of agreement (LoA) were, however, found for all LT2 markers compared with CP (from ±22 W for Dmax_exp to ±52 W for Dmax_pol), and unclear to most likely practically meaningful differences (PO differences between markers >1%, albeit <5%) were found between markers attending to magnitude-based inferences.

Conclusion: LT2 markers show a strong association and overall trivial-to-small differences with CP. Nevertheless, given the wide LoA and the likelihood of potentially meaningful differences between these endurance-related markers, caution should be employed when using them interchangeably.

Detection of the Anaerobic Threshold in Endurance Sports: Validation of a New Method Using Correlation Properties of Heart Rate Variability

Past attempts to define an anaerobic threshold (AnT) have relied upon gas exchange kinetics, lactate testing and field-based evaluations. DFA a1, an index of heart rate (HR) variability (HRV) fractal correlation properties, has been shown to decrease with exercise intensity. The intent of this study is to investigate whether the AnT derived from gas exchange is associated with the transition from a correlated to uncorrelated random HRV pattern signified by a DFA a1 value of 0.5. HRV and gas exchange data were obtained from 15 participants during an incremental treadmill run. Comparison of the HR reached at the second ventilatory threshold (VT2) was made to the HR reached at a DFA a1 value of 0.5 (HRVT2). Based on Bland-Altman analysis and linear regression, there was strong agreement between VT2 and HRVT2 measured by HR (r = 0.78, p < 0.001). Mean VT2 was reached at a HR of 174 (±12) bpm compared to mean HRVT2 at a HR of 171 (±16) bpm. In summary, the HR associated with a DFA a1 value of 0.5 on an incremental treadmill ramp was closely related to that of the HR at the VT2 derived from gas exchange analysis. A distinct numerical value of DFA a1 representing an uncorrelated, random interbeat pattern appears to be associated with the VT2 and shows potential as a noninvasive marker for training intensity distribution and performance status.

Relationship between functional threshold power, ventilatory threshold and respiratory compensation point in road cycling

BACKGROUND

The purpose of this study was to assess the relationship between power output and relative power output at the functional threshold power, ventilatory threshold and respiratory compensation point in road cyclists.

METHODS

Forty-six road cyclists (age 38 ± 9 years; height 177 ± 9 cm; body mass 71.4 ± 8.6 kg; body mass index 22.7 ± 2.2 kg·m-1; fat mass 7.8 ± 4%, VO2max 61.1 ± 9.1 ml·min-1·kg-1) performed a graded exercise test in which power output and relative power output at the ventilatory landmarks were identified. Functional threshold power was established as 95% of the power output during a 20-minute test.

RESULTS

Power output and relative power output at the functional threshold power were higher than at the ventilatory threshold (p < 0.001). There were very large to near perfect correlations for power output (95% CI for r from 0.71 to 0.9) and relative power output (95% CI for r from 0.79 to 0.93) at the functional threshold power and respiratory compensation point. Mean bias in power ouput and relative power output measured at RCP compared with FTP was not significant (mean bias 95% CI from -7 to 10 W and - 0.1 to 0.1 W/kg, respectively).

CONCLUSIONS

Power output and relative power output at the functional threshold power are higher than at the ventilatory threshold. Power output and relative power output at the functional threshold power and respiratory compensation point are strongly related, but caution is required when using both concepts indistinctly.