Functional threshold power is defined as the highest power output a cyclist can maintain in a quasi-steady state for approximately 60 min (FTP₆₀). In order to improve practicality for regular evaluations, FTP₆₀ could theoretically be determined as 95% of the mean power output in a 20-min time trial (FTP₂₀). This study tested this assumption and the validity of FTP₂₀ and FTP₆₀ against the individual anaerobic threshold (IAT). Twenty-three trained male cyclists performed an incremental test to exhaustion, 20- and 60-min time trials, and a time to exhaustion at FTP₂₀. Power output, heart rate and oxygen uptake representing FTP₂₀, FTP₆₀ and IAT were not different (p>0.05), and large to very large correlations were found (r=0.61 to 0.88). Bland-Altman plots between FTP₂₀, FTP₆₀ and IAT showed small bias (–1 to –5 W), but large limits of agreement ([–40 to 32 W] to [–62 to 60 W]). Time to exhaustion at FTP₂₀ was 50.9±15.7 min. In conclusion, FTP₂₀ and FTP₆₀ should not be used interchangeably on an individual basis and their validity against IAT should be interpreted with caution. We suggest that the mean power output in a 20-min time trial is used for training intensity prescription and regular performance monitoring.

Purpose: Functional threshold power (FTP), determined as 95% of the average power during a 20-min time trial, is suggested as a practical test for the determination of the maximal lactate steady state (MLSS) in cycling. Therefore, the objective of the present study was to determine the validity of FTP in predicting MLSS. Methods: A total of 15 cyclists, 7 classified as trained and 8 as well trained (mean [SD] maximal oxygen uptake 62.3 [6.4] mL·kg⁻¹·min⁻¹, maximal aerobic power 329 [30] W), performed an incremental test to exhaustion, an FTP test, and several constant-load tests to determine the MLSS. The bias ± 95% limits of agreement (LoA), typical error of the estimate (TEE), and Pearson coefficient of correlation (r) were calculated to assess validity. Results: For the power-output measures, FTP presented a bias ± 95% LoA of 1.4% ± 9.2%, a moderate TEE (4.7%), and nearly perfect correlation (r = .91) with MLSS in all cyclists together. When divided by training level, the bias ± 95% LoA and TEE were higher in the trained group (1.4% ± 11.8% and 6.4%, respectively) than in the well-trained group (1.3% ± 7.4% and 3.0%, respectively). For the heart-rate measurement, FTP presented a bias ± 95% LoA of −1.4% ± 8.2%, TEE of 4.0%, and very large correlation (r = .80) with MLSS. Conclusion: Therefore, trained and well-trained cyclists can use FTP as a noninvasive and practical alternative to estimate MLSS.

Purpose: Several studies have demonstrated that physiological variables predict cycling endurance performance. However, it is still unclear whether the predictors will change over different performance durations. The aim of this study was to assess the correlations between physiological variables and cycling time trials with different durations. Methods: Twenty trained male cyclists (maximal oxygen uptake [VO₂max] = 60.5 ± 5.6 mL/kg/min) performed 4 separate experimental trials during a 2-week period. Cyclists initially completed an incremental exercise test until volitional exhaustion followed by 3 maximal cycling time trials on separate days. Each time trial consisted of 3 different durations: 5 min, 20 min, and 60 min performed in a randomized order. Results: The main results showed that the physiological measures strongly correlated with long cycling performances rather than short and medium time trials. The time-trial mean power output was moderately high to highly correlated with peak power output and VO_2max (r = .61–.87, r = .72–.89, respectively), and was moderately to highly correlated with the lactate threshold Dmax method and second ventilatory threshold (r = .52–.75, r = .55–.82, respectively). Conclusions: Therefore, trained cyclists should develop maximal aerobic power irrespective of the duration of time trial, as well as enhancements in metabolic thresholds for long-duration time trials.

Introduction: The present study aimed to investigate the effects of two high-intensity interval training (HIIT) shuttle-run-based models, over 10 weeks on aerobic, anaerobic, and neuromuscular parameters, and the association of the training load and heart rate variability (HRV) with the change in the measures in young futsal players.Methods: Eleven young male futsal players (age: 18.5 ± 1.1 years; body mass: 70.5 ± 5.7 kg) participated in this study. This pre-post study design was performed during a typical 10 weeks training period. HIIT sessions were conducted at 86% (HIIT₈₆; n = 6) and 100% (HIIT₁₀₀; n = 5) of peak speed of the FIET. Additionally, friendly and official matches, technical-tactical and strength-power training sessions were performed. Before and after the training period, all players performed the FIET, treadmill incremental, repeated sprint ability (RSA), sprint 15-m, and vertical jump tests (CMJ and SJ), and the HRV was measured. Training load (TL) was monitored using the session rating of perceived effort. Data analysis was carried out using Bayesian inference methods.Results: The HIIT₈₆ model showed clear improvements for the peak oxygen uptake (VO₂peak), peak speed in the treadmill incremental test, first and second ventilatory thresholds, RSA best and mean times, CMJ, and SJ. The HIIT₁₀₀ model presented distinct advances in VO₂peak, peak speed in the treadmill incremental test, RSA mean time, and CMJ. Between HIIT models comparisons showed more favorable probabilities of improvement for HIIT₈₆ than HIIT₁₀₀ model in all parameters. TL data and HIIT models strongly explained the changes in the RSA mean and best times (R² = 0.71 and 0.87, respectively), as well as HRV changes, and HIIT models explained positively VO₂peak changes (R² = 0.72). All other changes in the parameters were low to moderately explained.Conclusion: The HIIT₈₆ proved to be more effective for improving aerobic, RSA, and neuromuscular parameters than HIIT₁₀₀ during a typical 10-week futsal training period. So, strength and conditioning specialists prescribing shuttle-run intermittent exercises at submaximal intensities can manage the individual acceleration load imposed on athlete increasing or decreasing either the set duration or the frequency of change of direction during HIIT programming.

Functional threshold power (FTP) is defined as the highest power that a cyclist can maintain in a quasi-steady state without fatigue for approximately 1 hour. To improve practicality, a 20-minute time-trial test was proposed, where FTP is represented by 95% of the mean power produced. It is preceded by a specific 45-min warm-up, with periods of low intensity, fast accelerations, and a 5-min time-trial. Thus, the aim of this study was to determine the reliability of this protocol, including the reliability of the warm-up, pacing strategy, and FTP determination. For this purpose, 25 trained cyclists performed a familiarization and two other tests separated by seven days. The coefficient of variation (CV [%]), intraclass correlation coefficient (ICC), and change in the mean between test and retest were calculated. The results show that the 20-min time-trial was reliable (CV=2.9%, ICC=0.97), despite a less reliable warm-up (CV=5.5%, ICC=0.84). The changes in the mean between the test and retest were trivial to small for all measurements, and the pacing strategy was consistent across all trials. These results suggest that FTP determination with a 20-min protocol was reliable in trained cyclists.

This study aimed to investigate the effects of eccentric cycling (ECC_CYC) training on performance, physiological, and morphological parameters in comparison to concentric cycling (CON_CYC) training. Searches were conducted using PubMed, Embase, and ScienceDirect. Studies comparing the effect of ECC_CYC and CON_CYC training regimens on performance, physiological, and/or morphological parameters were included. Bayesian multilevel meta-analysis models were used to estimate the population’s mean difference between chronic responses from ECC_CYC and CON_CYC training protocols. Group levels and meta-regression were used to evaluate the specific effects of subjects and study characteristics. Fourteen studies were included in this review. The meta-analyses showed that ECC_CYC training was more effective in increasing knee extensor strength, vastus lateralis fiber cross-sectional area, and six-minute walking distance compared to CON_CYC. Moreover, ECC_CYC was as effective as CON_CYC in decreasing body fat percentage. CON_CYC was more effective in increasing $\dot{V}{O}_{2\max }$ and peak power output attained during concentric incremental tests. However, group-level analyses revealed that ECC_CYC was more effective than CON_CYC in improving $\dot{V}{O}_{2\max }$ in patients with cardiopulmonary diseases. ECC_CYC is a viable modality for exercise interventions aiming to improve parameters of muscle strength, hypertrophy, functional capacity, aerobic power, and body composition, with more advantages than CON_CYC training in improving neuromuscular variables.