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Validity and reliability of critical power field testing
Abstract and Figures
Purpose:
To test the validity and reliability of field critical power (CP).
Method:
Laboratory CP tests comprised three exhaustive trials at intensities of 80, 100 and 105 % maximal aerobic power and CP results were compared with those determined from the field. Experiment 1: cyclists performed three CP field tests which comprised maximal efforts of 12, 7 and 3 min with a 30 min recovery between efforts. Experiment 2: cyclists performed 3 × 3, 3 × 7 and 3 × 12 min individual maximal efforts in a randomised order in the field. Experiment 3: the highest 3, 7 and 12 min power outputs were extracted from field training and racing data.
Results:
Standard error of the estimate of CP was 4.5, 5.8 and 5.2 % for experiments 1-3, respectively. Limits of agreement for CP were -26 to 29, 26 to 53 and -34 to 44 W for experiments 1-3, respectively. Mean coefficient of variation in field CP was 2.4, 6.5 and 3.5 % for experiments 1-3, respectively. Intraclass correlation coefficients of the three repeated trials for CP were 0.99, 0.96 and 0.99 for experiments 1-3, respectively.
Conclusions:
Results suggest field-testing using the different protocols from this research study, produce both valid and reliable CP values.
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... All cyclists were familiarized with the 10point Borg scale CR-10 (Borg, 1998). On the next visit, they performed a time-trial test (TT) to calculate CP and W´ (Karsten et al., 2015(Karsten et al., , 2018. On the last visit, the W´BAL-INT model training session was performed (Galán-Rioja et al., 2022) to determine physiological responses (VȮ2, HR and [BLa¯]), and perceptual responses (RPE) in each of the work and recovery intervals. ...
... The TT used were 12-, 7-and 3-min maximal efforts, with a 30-min low intensity recovery period in between. Linear regression was used to calculate CP and W′ using the power-1/time (P = W′(1/t) + CP) model (Karsten et al., 2015(Karsten et al., , 2018. VȮ2 and HR data were continuously collected throughout the entire test. ...
This study aimed to compare acute physiological responses during the W prime (W´) balance training model (W´BAL-INT) with performance in the critical power test (CPTest). Additionally, the study sought to determine the extent of neuromuscular and metabolic fatigue associated with severe and extreme intensity domains. Fourteen road master cyclists (13 male, 1 female) completed graded incremental exercise tests to determine their maximum oxygen uptake and 12−, 7− and 3-min maximal efforts to assess CP and W´ (CPTest). Additionally, they participated in a reconstitutive intermittent training session following the W´BAL-INT model. Physiological responses including oxygen uptake (V˙O2), the heart rate (HR), blood lactate (BLa̅) concentration, and perceptual responses (RPE), were measured and compared to CPTest performance data. The W´BAL-INT induced steady-state physiological responses in V˙O2mean (F = 0.76, p = 0.655) and absolute HR, relative HR and HRCP (F = 0.70, p = 0.704; F = 1.11, p = 0.359; F = 1.70, p = 0.095, respectively) comparable to CPTest. During the 3-min work intervals in the training session, V˙O2 was stable and similar to V˙O2peak (54.2 ± 6.7 to 59.3 ± 4.9 ml·kg⁻¹·min⁻¹) in the CPTest. Furthermore, 4-min rest intervals facilitated recovery up to moderate fatigue levels (80–100% of W´ balance). HR responses were sensitive to interval intensity and accumulated time. Meanwhile, BLa̅ responses and the RPE increased fatigue development during W´BAL-INT. The W´BAL-INT training model generates consistent physiological responses in mean oxygen kinetics, the percentage of CP and the HR, similar to those observed during the CPTest. However, different physiological responses were observed in peak oxygen kinetics and W´ energy balance.
... The estimation requires data from a sufficiently large number of maximal efforts (i.e. efforts to exhaustion) over different distances or durations with a time to exhaustion between 2 and 15 min (Karsten et al. 2015). ...
... Rather, most of the other data points likely come from sub-maximal efforts. Indeed, 3, 7 and 12 min are often-recommended test durations for the hyperbolic model(Karsten et al. 2015). Note also that these data were "mined" from training history so that multiple points may correspond to the same activity and then cannot all represent maximal efforts.Content courtesy of Springer Nature, terms of use apply. ...
The power–duration relationship describes the time to exhaustion for exercise at different intensities. It is believed to be a “fundamental bioenergetic property of living systems” that this relationship is hyperbolic. Indeed, the hyperbolic (a.k.a. critical-power) model which formalises this belief is the dominant tool for describing and predicting high-intensity exercise performance, e.g. in cycling, running, rowing or swimming. However, the hyperbolic model is now the focus of a heated debate in the literature because it unrealistically represents efforts that are short (< 2 min) or long (> 15 min). We contribute to this debate by demonstrating that the power–duration relationship is more adequately represented by an alternative, power-law model. In particular, we show that the often-observed good fit of the hyperbolic model between 2 and 15 min should not be taken as proof that the power–duration relationship is hyperbolic. Rather, in this range, a hyperbolic function just happens to approximate a power law fairly well. We also prove mathematical results which suggest that the power-law model is a safer tool for pace selection than the hyperbolic model and that the former more naturally models fatigue than the latter.
... The demarcation of Z2 and Z3 was established on the basis of habitual training data to estimate CS, instead of more conventional laboratorybased protocols [54]. However, previous investigations have shown comparable estimates of CS derived from time trials and habitual training data [55,56]. The demarcation of Z1 and Z2, however, was estimated on the basis of a systematic review, and the percentage at which the first threshold occurs was kept constant. ...
Background
The training characteristics and training intensity distribution (TID) of elite athletes have been extensively studied, but a comprehensive analysis of the TID across runners from different performance levels is lacking.
Methods
Training sessions from the 16 weeks preceding 151,813 marathons completed by 119,452 runners were analysed. The TID was quantified using a three-zone approach (Z1, Z2 and Z3), where critical speed defined the boundary between Z2 and Z3, and the transition between Z1 and Z2 was assumed to occur at 82.3% of critical speed. Training characteristics and TID were reported based on marathon finish time.
Results
Training volume across all runners was 45.1 ± 26.4 km·week⁻¹, but the fastest runners within the dataset (marathon time 120–150 min) accumulated > three times more volume than slower runners. The amount of training time completed in Z2 and Z3 running remained relatively stable across performance levels, but the proportion of Z1 was higher in progressively faster groups. The most common TID approach was pyramidal, adopted by > 80% of runners with the fastest marathon times. There were strong, negative correlations (p < 0.01, R² ≥ 0.90) between marathon time and markers of training volume, and the proportion of training volume completed in Z1. However, the proportions of training completed in Z2 and Z3 were correlated (p < 0.01, R² ≥ 0.85) with slower marathon times.
Conclusion
The fastest runners in this dataset featured large training volumes, achieved primarily by increasing training volume in Z1. Marathon runners adopted a pyramidal TID approach, and the prevalence of pyramidal TID increased in the fastest runners.
... Additionally, by tracking the power output over time, cyclists and coaches can monitor the progress, make data-driven adjustments to training plans, and set realistic goals [3]. The power output can be measured during field tests [4,5] or in laboratory settings [6,7]. ...
The power output in cycling is one of the most important factors for athletes and coaches. The cycling community has several commercial gears that can be used. One of the most used is the TACX Neo 2T (TN2T) smart trainer. The objective of this study was to investigate the metrological proprieties of the TN2T (accuracy and reliability), as well as its agreement with the Garmin Vector 3 (GV3) pedals at different power stages. The sample consisted of ten regional-level cyclists with a mean age of 45.6 ± 6.4 years, who regularly participated in regional and national competitions. Residual relative differences were found between the two devices. Both devices showed good reliability with coefficients of variation and intraclass correlation coefficients ranging from 0.03% to 0.15% and from 0.731 to 0.968, respectively. Independent samples t-test comparison between devices showed no significant differences in all power stages (p > 0.05). Bland–Altman plots showed that more than 80% of the plots were within the 95% confidence intervals in all power stages. The present data showed that there were non-significant differences between the two devices at power stages between 100W
and 270W, with a strong agreement. Therefore, they can be used simultaneously.
... Thirty minutes later, participants performed three separate field-based TT of 3, 6, and 12 minutes, respectively (consistently in this order) and the PO attained during each TT was registered. The TT were interspersed by 30 minutes of passive recovery, as done in previous studies [38][39][40][41]. No specific pacing strategy was recommended, although participants were encouraged to achieve the highest mean PO possible. ...
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.
... Use of training and racing data to estimate CP and W′ is likely to lead to underestimation of CP, W′, or both. Indeed, W′ has not shown high agreement between training and racing and laboratory estimates (Karsten et al. 2015, Leo et al. 2020). ...
The studies in this thesis investigated the physiological determinants of 4-km team-pursuit (TP) track cycling performance and critically evaluated the use of modelling finite work capacity (W′) and its dynamic balance (W′BAL) during the TP. This thesis also examined the integration of blood flow restriction (BFR) into high-intensity interval training (HIIT) as an intervention to improve factors related to TP performance. A series of related investigations were conducted with trained cyclists up to the Olympic level. Study One recruited male TP squads from International, National, and Regional performance levels. The TP squads were assessed for their critical power (CP) and W′. Maximal 4-km TP efforts confirmed different performance times of 3:49.9, 3:56.7, and 4:05.4 (minutes:s) for International, National, and Regional, respectively. Four TP simulation trials quantified W′ reconstitution from 0 to 100 W below CP. Results showed that the International squad were differentiated from National and Regional performance levels with greater CP (p < 0.05), likely preserving W′ for leading efforts. Furthermore, the International team possessed the fastest rates of W′ reconstitution at recovery intensities within 50 W of CP (p < 0.05), demonstrating the importance of W′ reconstitution at intensities near CP for recovery in the TP. The International team also expended a greater total quantity of W′ than its initial size (104 ± 5%), further demonstrating the capacity to utilise the reconstituted W′. In conclusion, we found that the TP relies on high aerobic capacity and rapid metabolic recovery abilities. An intervention was conceived based on the demands of the TP and the existing training sessions of elite TP cyclists. The training intervention included principles of TP training philosophy where cyclists repeatedly practice competition demands, at their TP lead intensity. As elite TP cyclists engage in substantial training volumes, it was important not to substantially exceed current training workloads. Based on previous BFR research with trained cyclists, an intervention integrating BFR into the recovery between TP efforts was devised. The intervention was performed on an ergometer to enable greater control over conditions and intensity. To evaluate the metabolic demands of the BFR intervention, the Study Two assessed the acute physiological responses in 11 male and female highly-trained cyclists (V̇O2PEAK 65 ± 9 mL·kg-1·minute-1). Using a within-subject design, participants performed two work- and duration-matched HIIT sessions. The HIIT consisted of six high-intensity repetitions with BFR occlusion between work bouts at 200 mmHg for 2-minutes applied proximally on the thighs (BFR) or HIIT alone without BFR (CON). Work intensity was set as 85% of the mean power output of a maximal 30-s test to simulate TP lead intensity. Cardiopulmonary variables (O2 uptake, V̇O2; carbon dioxide production V̇CO2; and ventilation, V̇E) and muscle oxygenation responses were measured during the HIIT, and vascular endothelial growth factor (VEGF) was measured pre- and 3-hours post-HIIT. Results demonstrated that BFR increased V̇CO2 and V̇E (both p < 0.05) during work bouts but did not affect V̇O2 and TSI (both p>0.05). Compared to CON, the BFR intervention significantly decreased V̇O2, V̇CO2, V̇E, and TSI during BFR occlusion (all p<0.05). Following cuff release, there were significantly higher values of V̇O2, V̇CO2, and V̇E, whereas TSI was suppressed (all p < 0.05). There were significant enhancements of serum VEGF concentration at 3-hours post-HIIT after BFR when compared to CON. As BFR appeared to delay recovery, it was hypothesised that BFR may increase metabolic and oxidative stress by delaying recovery processes. The delay in recovery may enhance the adaptations to HIIT without increasing training workload. After demonstrating that applying BFR during recovery in high-intensity work bouts increased markers of physiological stress, Study Three assessed the performance and physiological effects of the training as a chronic intervention. Using a between-subject design, ten performance-matched male trained cyclists (weekly volume >6-hours·week-1) were assigned to BFR or CON conditions. Participants performed pre- and post-intervention tests to determine lactate thresholds, 30-s maximal sprint cycling performance, and an intermittent test designed with high-intensity bouts comparable to the TP. Work bouts were performed at 85% of the mean power output of the maximal 30-s test. Muscle oxygenation and cardiopulmonary measures were continually assessed throughout the intermittent test. Participants performed four-weeks of work- and duration-matched HIIT either with 2-minutes of 200 mmHg thigh BFR between work bouts or HIIT alone (CON). Following BFR intervention, there were significant improvements in intermittent test time to exhaustion, 30-s mean power output, and submaximal lactate thresholds compared to CON (all p < 0.05). Furthermore, BFR led to significant intermittent test improvements for V̇O2PEAK and the rate of muscle tissue reoxygenation (all p < 0.05). There were no significant changes over the intervention period for CON, indicating that HIIT was ineffective in this cohort when BFR was not incorporated. Therefore, it was demonstrated that the integration of BFR between HIIT work bouts improves intermittent performance and a range of physiological factors associated with performance in trained cyclists. Finally, the BFR intervention was integrated into two HIIT sessions within a training camp of an elite TP squad preparing for the Olympic Games to test its potential efficacy and feasibility. As in the previous BFR studies, this case-study (Study Four) applied 2-minutes of 200 mmHg thigh BFR between high-intensity bouts. Work intensities were set at the individual cyclists’ TP lead intensity. A questionnaire was developed to assess the pain, tolerance, enjoyment, and compare the intervention to other training modalities. Questionnaire responses indicated that the elite cyclists enjoyed and positively perceived the intervention, appreciating the variety and efficiency of the training stimulus. All but one elite cyclist tolerated that intervention. Further investigation in conjunction with medical staff indicated that the intolerant cyclist had a pre-existing undiagnosed cardiovascular condition and presented with femoral artery claudication (discussed in the addendum). Thus, integrating BFR into HIIT for elite track cyclists was feasible and tolerable when no contraindications existed. In summary, elite TP performance relies on high sustained aerobic power output and rapid W′ recovery between efforts. This thesis showed integrating BFR between HIIT work bouts provides an additional training stimulus and can improve factors related to aerobic capacity and high-intensity intermittent performance in trained cyclists. The BFR intervention is tolerable within an elite cohort and may improve TP performance without increasing training workload.
... Other authors have investigated using field testing for critical power and while this may improve the ecological validity, it does add variables which are not controllable. Karstem Jobson, Hopker et al. (2015) however, have suggested that both lab and field based testing, using exhaustive bouts, produce valid measures of CP. Recently caution has been advised, as time to exhaustion trials appear to be superior to time trial (TT) protocols when determining critical power (Coakley and Passfield, 2017). ...
... 1 However, it has been shown that unintended, and uninstructed, efforts from training can be used to estimate CP and W′, which show a high level of agreement with laboratory-based measures. 30 Our results are also in agreement with Maunder et al, 11 who demonstrated the 3MT overestimates the maximal metabolic steady state, suggesting that the TT or HAB parameters provide a more accurate estimation. It is worth considering that in the current study, HAB was collected from 6 weeks, so that the best performance for the discrete times corresponding to 3, 7, and 12 minutes was derived from ∼30 training sessions. ...
Purpose:
This study aimed to compare estimations of critical speed (CS) and work completed above CS (D'), and their analogies for running power (critical power [CP] and W'), derived from raw data obtained from habitual training (HAB) and intentional maximal efforts in the form of time trials (TTs) and 3-minute all-out tests (3MTs) in recreational runners. The test-retest reliability of the 3MT was further analyzed.
Methods:
Twenty-three recreational runners (4 female) used a foot pod to record speed, altitude, and power output for 8 consecutive weeks. CS and D', and CP and W', were calculated from the best 3-, 7-, and 12-minute segments recorded in the first 6 weeks of their HAB and in random order in weeks 7 and 8 from 3 TTs (3, 7, and 12 min) and three 3MTs (to assess test-retest reliability).
Results:
There was no difference between estimations of CS or CP derived from HAB, TT, and 3MT (3.44 [0.63], 3.42 [0.53], and 3.76 [0.57] m · s-1 and 281 [41], 290 [45], and 305 [54] W, respectively), and strong agreement between HAB and TT for CS (r = .669) and CP (r = .916). Limited agreement existed between estimates of D'/W'. Moderate reliability of D'/W' was demonstrated between the first and second 3MTs, whereas excellent reliability was demonstrated for CS/CP.
Conclusion:
These data suggest that estimations of CS/CP can be derived remotely, from either HAB, TT, or 3MT, although the lower agreement between D'/W' warrants caution when using these measures interchangeably.
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.
The power-time relationship is an important concept in exercise physiology because it provides a systematic framework for understanding the mechanical bases of fatigue and exhaustion during exercise, as well as a tool for diagnosing physical fitness and monitoring training. This relationship is well known during high intensity exercise, sustainable with stable critical power (CP) values, reaching maximum work rates over time until exercise intolerance is reached. This amount of work above the CP (W ́) is constant at different speeds depending on the proximity of the power output to CP. The appeal of this concept of CP in recent years has been broadened through its application to high intensity intermittent exercise, however, there are no intermittent training programs (IWC) based on CP/W ́ that can evaluate and optimize the exercise. athletic performance in road cycling.
Therefore, the objective of this Doctoral Thesis is to analyze the power-time relationship (CP) and the metabolic thresholds for the evaluation and optimization of sports performance during intermittent exercise through a reconstitutive model (W'BAL) in road cyclists. For this, a systematic review and Meta-Analysis has been carried out that determines the degree of correspondence between CP and VT1, MLSS, VT2 and RCP (Article I), in addition a study has been carried out that determines the influence between the load based on the weight body and muscle mass during the WAnT performance test above CP in the severe intensity domain (Article II), in order to develop a reconstitutive intermittent training program (Article III), which can estimate, evaluate and monitor the CP during training (Article IV).
The main results of this Doctoral Thesis suggest that a) VT1 and MLSS underestimate CP while RCP and VT2 overestimate it, and MLSS and MMSS do not mean the same thing. b) In the WAnT test, the protocols can be used interchangeably in the conditions of body weight (BW) and muscle mass or fat-
XIII
free (LBM) that evaluate anaerobic capacity above CP. c) IWC significantly improves CP and MMP in field tests TT12min, TT7min and TT3min after 4 weeks of training. d) Estimated CP3p and CP2p of the MMP values during the sessions of the IWC training program, differ from the CP extracted from the formal field test. e) IWC can estimate CP from 7min MMP values, track and monitor its changes during 4 weeks of training.
This Doctoral Thesis shows that the development of a CP training program applied to intermittent reconstitutive exercise (WBAL) has important applications in the optimization of sports performance in road cyclists.
For high-intensity muscular exercise, the time-to-exhaustion (t) increases as a predictable and hyperbolic function of decreasing power (P) or velocity (V). This relationship is highly conserved across diverse species and different modes of exercise and is well described by two parameters: the 'critical power' (CP or CV), which is the asymptote for power or velocity, and the curvature constant (W') of the relationship such that t = W'/(P-CP). CP represents the highest rate of energy transduction (oxidative ATP production, V? O2) that can be sustained without continuously drawing on the energy store W' (composed in part of anaerobic energy sources and expressed in kilojoules). The limit of tolerance (time t) occurs when W' is depleted. The CP concept constitutes a practical framework in which to explore mechanisms of fatigue and help resolve crucial questions regarding the plasticity of exercise performance and muscular systems physiology. This brief review presents the practical and theoretical foundations for the CP concept, explores rigorous alternative mathematical approaches, and highlights exciting new evidence regarding its mechanistic bases and its broad applicability to human athletic performance.
To compare critical speed measured from a single-visit field test of the distance-time relationship with the 'traditional' treadmill time to exhaustion multi-visit protocol.
Ten male distance runners completed treadmill and field-tests in order to calculate critical speed (CS) and the maximum distance performed above CS (D'). The field-test involved 3 runs on a single visit to an outdoor athletics track over 3600 m, 2400 m and 1200 m. Two field-test protocols were evaluated using either a 30-min recovery or 60-min recovery between runs. The treadmill test involved runs to exhaustion at 100, 105 and 110% of velocity at VO2max, with 24-hours recovery between runs.
There was no difference in CS measured with the treadmill, 30-min and 60-min recovery field tests, (P<0.05). CS from the treadmill test was highly correlated with CS from the 30 and 60-min field tests (r=0.89; r=0.82, P<0.05). However there was a difference and no correlation in D' between the treadmill test and the 30 and 60-min field tests (r=0.13; r=0.33, P>0.05). A typical error of the estimate of 0.14 m·s-1 (95% confidence limits: 0.09-0.26 m·s-1) was seen for CS and 88 m (95% confidence limits: 60-169 m) for D'. A coefficient of variation of 0.4% (95% confidence limits: 0.3-0.8%) was found for repeat tests of CS and 13% (95% confidence limits: 10-27%) for D'.
The single-visit method provides a useful alternative for assessing CS in the field.
The purpose of this study was to investigate the level of agreement between laboratory-based estimates of critical power (CP) and results taken from a novel field test. Subjects were fourteen trained cyclists (age 40±7 yrs; body mass 70.2±6.5 kg; V̇O2max 3.8±0.5 L · min-1). Laboratory-based CP was estimated from 3 constant work-rate tests at 80%, 100% and 105% of maximal aerobic power (MAP). Field-based CP was estimated from 3 all-out tests performed on an outdoor velodrome over fixed durations of 3, 7 and 12 min. Using the linear work limit (Wlim) vs. time limit (Tlim) relation for the estimation of CP1 values and the inverse time (1/t) vs. power (P) models for the estimation of CP2 values, field-based CP1 and CP2 values did not significantly differ from laboratory-based values (234±24.4 W vs. 234±25.5 W (CP1); P<0.001; limits of agreement [LOA], -10.98-10.8 W and 236±29.1 W vs. 235±24.1 W (CP2); P<0.001; [LOA], -13.88-17.3 W. Mean prediction errors for laboratory and field estimates were 2.2% (CP) and 27% (W'). Data suggest that employing all-out field tests lasting 3, 7 and 12 min has potential utility in the estimation of CP.
Power output and heart rate were monitored for 11 months in one female (V(.)O(2max): 71.5 mL · kg⁻¹ · min⁻¹) and ten male (V(.)O(2max): 66.5 ± 7.1 mL · kg⁻¹ · min⁻¹) cyclists using SRM power-meters to quantify power output and heart rate distributions in an attempt to assess exercise intensity and to relate training variables to performance. In total, 1802 data sets were divided into workout categories according to training goals, and power output and heart rate intensity zones were calculated. The ratio of mean power output to respiratory compensation point power output was calculated as an intensity factor for each training session and for each interval during the training sessions. Variability of power output was calculated as a coefficient of variation. There was no difference in the distribution of power output and heart rate for the total season (P = 0.15). Significant differences were observed during high-intensity workouts (P < 0.001). Performance improvements across the season were related to low-cadence strength workouts (P < 0.05). The intensity factor for intervals was related to performance (P < 0.01). The variability in power output was inversely associated with performance (P < 0.01). Better performance by cyclists was characterized by lower variability in power output and higher exercise intensities during intervals.
Introduction
The majority of interval training studies are conducted on ergometers to control external variables and exercise intensity. The differences between laboratory and outdoor cycling have been discussed recently (Jobson et al., 2007) suggesting different physiological demands. With the use of mobile power meters, exercise intensity can be monitored in the field, which improves the ecological validity of the measurements. This study tested the effects of low-cadence (60 rpm) uphill (Int60) or high-cadence (100 rpm) level-ground (Int100) interval training on power output (PO) during 20-min uphill (TTup) and flat (TTflat) time-trials as well as on performance during a laboratory graded exercise test (GXT).
Methods
Eighteen male cyclists (VO2max: 58.6 ± 5.4 mL/min/kg) were randomly assigned to Int60, Int100 or a control group (Con). The interval training comprised of two training sessions per week over 4 weeks, which consisted of 6x5 min at the PO corresponding to the respiratory compensation point (RCP). For the control group, no interval training was conducted. During the interval training sessions and the time-trials, PO was measured with mobile power-meters (SRM).
Results
A two-factor ANOVA revealed significant increases on performance measures obtained from GXT (Pmax: 2.8 ± 3.0%; p<0.01; PO and VO2 at RCP: 3.6 ± 6.3% and 4.7 ± 8.2%, respectively; p<0.05), with no significant group effects. Significant interactions between group and uphill and flat time-trial, pre vs. post-training on PO were observed (p<0.05). Int60 increased PO during both TTup (4.4 ± 5.3%) and TTflat (1.5 ± 4.5%). The changes were -1.3 ± 3.6%, 2.6 ± 6.0% for Int100 and 4.0 ± 4.6%, -3.5 ± 5.4% for Con during TTup and TTflat, respectively. PO was significantly higher during TTup than TTflat (4.4 ± 6.0%; 6.3 ± 5.6%; pre and post-training, respectively; p<0.001).
Discussion
The performance improvements during TTup and TTflat have shown specific adaptations in response to the interval training sessions and indicate the ecological validity of the time-trials. The application of higher pedaling forces via low cadences provides a potentially higher training stimulus with a cross-over effect to flat time-trials. When evaluating power output data or prescribing training zones, it is important to note that trained cyclists are able to produce higher power outputs during uphill compared to flat time-trial conditions.
The main purpose of the study was to investigate the relationships between the Lactate Threshold (LT), maximal oxygen uptake (KO2max), performance time, and Critical Aerobic Power (CAP) during a simulated 20 km cycling time trial (20 kmTT). CAP was operationally defined as the average oxygen uptake sustained during the 20 kmTT. The subjects were 11 experienced male cyclists (mean±SD age: 29±7.2 yr; VO2max: 4.51±0.11 (L · min−1). Each subject completed two 20 kmTT using their own racing bicycle on a custom designed, computerized roller system. Elapsed time for the best trial averaged 34.58 ±3.29 min. Test‐retest reliability estimates for elapsed time, average heart rate and VO2 during the two trials were 0.92, 0.98 and 0.98, respectively. Oxygen uptake during the 20 kmTT averaged 115% of VO2 at LT and 86% of FO2max· A significant correlation was found between CAP and performance time (r= —0.81, p ≤ 0.01). Significant correlations were found between CAP and VO2 at LT (r = 0.62, p ≤ 0.05) and CAP and VO2max (r = 0.97, p ≤ 0.05). Using stepwise regression, VO2max was the strongest predictor of CAP with no further contribution from VO2 at LT. It was concluded that CAP is a strong determinant of cycling performance for 30–40 min duration. In this study, CAP was dependent more on VO2max than on the LT.
The purpose of physiological testing (J.D. MacDougall and H.A. Wenger) what do tests measure? (H.J. Green) testing strength and power (D.G. Sale) testing aerobic power (J.S. Thoden) testing anaerobic power and capacity (C. Bouchard, Albert W. Taylor, Jean-Aime Simoneau, and Serge Dulac) Kknanthropometry (WD. Ross and M.J. Marfell-Jones) testing flexibility (C.L. Hubley-Kozey) evaluating the health status of the athlete (R. Backus and D.C. Reid) modelling elite athletic performance (E.W. Banister).