Accuracy of SRM and Power Tap Power Monitoring Systems for Bicycling

Performance analysis and mechanical determinants of the opening lap of the team sprint in elite-level track cycling

The team sprint (TS) is a three-lap pursuit and the most revered event in track sprint cycling. The opening lap of the TS is an important determinant to the overall performance. But despite it being the most controlled and repeatable task in track sprint cycling, very little data are available to better understand the performance of the opening lap. The aim of this study was split into three-parts: part one, to better understand the profile and the indices thought to be determinants of the opening lap of the TS in elite sprint track cyclists. Part two of the study examined all available timing splits (15, 65, 125 and 250 m) from 36 standing-start laps. Part three of the study examined the peak torque outputs and peak power outputs of different various starts performed over a 3-month period. The results showed time to 125 m exhibited a near perfect relationship with starter lap performance. Very strong relationships were seen with 15 and 65 m split times and final lap performance. Peak torque of the lead starting leg and peak power output were shown to be highly predictive 15 m, 65 and 125 m performance in training. These data suggested the first 15 m is highly important and predicts a disproportionately high level of final opening lap time performance. Therefore, it is likely that peak power output normalised to system mass and peak torque of lead leg is a strong determinant of overall performance in the TS.

Concurrent Validity and Reliability of Two Portable Powermeters (Power2Max vs. PowerTap) to Measure Different Types of Efforts in Cycling

The purpose was to assess the concurrent validity and reliability of two portable powermeters (PowerTap vs. Power2Max) in different types of cycling efforts. Ten cyclists performed two submaximal, one incremental maximal and two supramaximal sprint tests on an ergometer, while pedaling power and cadence were registered by both powermeters and a cadence sensor (GarminGSC10). During the submaximal and incremental maximal tests, significant correlations were found for power and cadence data (r = 0.992-0.997 and 0.996-0.998, respectively, p < 0.001), with a slight power underestimation by PowerTap (0.7-1.8%, p < 0.01) and a high reliability of both powermeters (p < 0.001) for measurement of power (ICC = 0.926 and 0.936, respectively) and cadence (ICC = 0.969 and 0.970, respectively). However, during the supramaximal sprint test, their agreement to measure power and cadence was weak (r = 0.850 and -0.253, p < 0.05) due to the low reliability of the cadence measurements (ICC between 0.496 and 0.736, and 0.574 and 0.664, respectively; p < 0.05) in contrast to the high reliability of the cadence sensor (ICC = 0.987-0.994). In conclusion, both powermeters are valid and reliable for measuring power and cadence during continuous cycling efforts (~100-450 W), but questionable during sprint efforts (>500 W), where they are affected by the gear ratio used (PowerTap) and by their low accuracy in cadence recording (PowerTap and Power2Max).

Interchangeability between the Data Obtained by Two Powermeters during Road Cycling Competitions: A Case Study

Various power meters are used to assess road-cycling performance in training and competition, but no previous study has analyzed their interchangeability in these conditions. Therefore, the purpose was to compare the data obtained from two different power meters (PowerTap vs. Power2Max) during cycling road races. A national-level under-23 male competitive cyclist completed six road-cycling official competitions (five road races and one individual time trial), in which power output was simultaneously registered with the two power meters. After this, the main power output variables were analyzed with the same software. The average and critical power obtained from the PowerTap power meter were slightly lower than from the Power2Max power meter (3.56 ± 0.68 and 3.62 ± 0.74 W·kg^-1, 5.06 and 5.11 W·kg^-1, respectively), and the correlations between both devices were very high (r ≥ 0.996 and p < 0.001). In contrast, the PowerTap power meter registered a significantly higher (p < 0.05) percentage of time at <0.75 and >7.50 W·kg^-1 and power profile at 1, 5 and 10 s. In conclusion, the data obtained in competitions by the two power meters were interchangeable. Nevertheless, the Power2Max power meter underestimated the pedaling power during short and high-intensity intervals (≤10.0 s and >7.50 W·kg^-1) compared to the PowerTap power meter. Therefore, the analysis of these efforts should be treated with caution.

Effect of Two Different Training Interventions on Cycling Performance in Mountain Bike Cross-Country Olympic Athletes

To improve performance in endurance sports, it is important to include both high-intensity and low-intensity training, but there is neither a universally accepted practice nor clear scientific evidence that allows reliable statements about the predominance of a specific training method. This randomized controlled trial compared the effects of a polarized training model (POL) to a low-intensity training model (LIT) on physiological parameters and mountain bike cross-country Olympic (XCO) race performance in eighteen competitive XCO athletes (17.9 ± 3.6 years). The superiority of one of the two methods could not be shown in this study. The results did not show statistically significant differences between POL and LIT, as both interventions led to slight improvements. However, a small tendency toward better effects for POL was seen for cycling power output during the race (4.4% vs. –2.2%), at the 4 mmol/L (6.1% vs. 2.8%) and individual anaerobic lactate threshold (5.1% vs. 2.3%), and for maximal aerobic performance (4.4% vs. 2.6%), but not for maximal efforts lasting 10 to 300 s. Despite the lack of significant superiority in this and some other studies, many athletes and coaches prefer POL because it produces at least equivalent effects and requires less training time.

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.

Caveats and Recommendations to Assess the Validity and Reliability of Cycling Power Meters: A Systematic Scoping Review

A large number of power meters have become commercially available during the last decades to provide power output (PO) measurement. Some of these power meters were evaluated for validity in the literature. This study aimed to perform a review of the available literature on the validity of cycling power meters. PubMed, SPORTDiscus, and Google Scholar have been explored with PRISMA methodology. A total of 74 studies have been extracted for the reviewing process. Validity is a general quality of the measurement determined by the assessment of different metrological properties: Accuracy, sensitivity, repeatability, reproducibility, and robustness. Accuracy was most often studied from the metrological property (74 studies). Reproducibility was the second most studied (40 studies) property. Finally, repeatability, sensitivity, and robustness were considerably less studied with only 7, 5, and 5 studies, respectively. The SRM power meter is the most used as a gold standard in the studies. Moreover, the number of participants was very different among them, from 0 (when using a calibration rig) to 56 participants. The PO tested was up to 1700 W, whereas the pedalling cadence ranged between 40 and 180 rpm, including submaximal and maximal exercises. Other exercise conditions were tested, such as torque, position, temperature, and vibrations. This review provides some caveats and recommendations when testing the validity of a cycling power meter, including all of the metrological properties (accuracy, sensitivity, repeatability, reproducibility, and robustness) and some exercise conditions (PO range, sprint, pedalling cadence, torque, position, participant, temperature, vibration, and field test).

Effects of 7-week Resistance Training on Handcycle Performance in Able-bodied Males

The effect of an upper body resistance training program on maximal and submaximal handcycling performance in able-bodied males was explored. Eighteen able-bodied men were randomly assigned to a training group (TG: n=10) and a control group (CG: n=8). TG received 7 weeks of upper body resistance training (60% of 1 repetition maximum (1RM), 3×10 repetitions, 6 exercise stations, 2 times per week). CG received no training. Peak values for oxygen uptake (V˙O_2peak), power output (PO_peak), heart rate (HR_peak), minute ventilation (V˙O_Epeak) and respiratory exchange ratio (RER_peak), submaximal values (HR, V˙O₂, RER, PO, and gross mechanical efficiency (GE)), and time to exhaustion (TTE) were determined in an incremental test pre- and post-training. Maximal isokinetic arm strength and 1RM tests were conducted. Ratings of perceived exertion (RPE) were assessed. A two-way repeated measures ANOVA and post-hoc comparisons were performed to examine the effect of time, group and its interaction (p<0.05). TG improved on PO_peak (8.55%), TTE (10.73%), and 1RM (12.28-38.98%). RPE at the same stage during pre- and post-test was lower during the post-test (8.17%). Despite no improvements in V˙O_2peak, training improved PO_peak, muscular strength, and TTE. Upper body resistance training has the potential to improve handcycling performance.

Maximal muscular power: lessons from sprint cycling

Maximal muscular power production is of fundamental importance to human functional capacity and feats of performance. Here, we present a synthesis of literature pertaining to physiological systems that limit maximal muscular power during cyclic actions characteristic of locomotor behaviours, and how they adapt to training. Maximal, cyclic muscular power is known to be the main determinant of sprint cycling performance, and therefore we present this synthesis in the context of sprint cycling. Cyclical power is interactively constrained by force-velocity properties (i.e. maximum force and maximum shortening velocity), activation-relaxation kinetics and muscle coordination across the continuum of cycle frequencies, with the relative influence of each factor being frequency dependent. Muscle cross-sectional area and fibre composition appear to be the most prominent properties influencing maximal muscular power and the power-frequency relationship. Due to the role of muscle fibre composition in determining maximum shortening velocity and activation-relaxation kinetics, it remains unclear how improvable these properties are with training. Increases in maximal muscular power may therefore arise primarily from improvements in maximum force production and neuromuscular coordination via appropriate training. Because maximal efforts may need to be sustained for ~15-60 s within sprint cycling competition, the ability to attenuate fatigue-related power loss is also critical to performance. Within this context, the fatigued state is characterised by impairments in force-velocity properties and activation-relaxation kinetics. A suppression and leftward shift of the power-frequency relationship is subsequently observed. It is not clear if rates of power loss can be improved with training, even in the presence adaptations associated with fatigue-resistance. Increasing maximum power may be most efficacious for improving sustained power during brief maximal efforts, although the inclusion of sprint interval training likely remains beneficial. Therefore, evidence from sprint cycling indicates that brief maximal muscular power production under cyclical conditions can be readily improved via appropriate training, with direct implications for sprint cycling as well as other athletic and health-related pursuits.

Are the Assioma Favero Power Meter Pedals a Reliable Tool for Monitoring Cycling Power Output?

This study aimed to examine the validity and reliability of the recently developed Assioma Favero pedals under laboratory cycling conditions. In total, 12 well-trained male cyclists and triathletes (VO_2max = 65.7 ± 8.7 mL·kg⁻¹·min⁻¹) completed five cycling tests including graded exercises tests (GXT) at different cadences (70–100 revolutions per minute, rpm), workloads (100–650 Watts, W), pedaling positions (seated and standing), vibration stress (20–40 Hz), and an 8-s maximal sprint. Tests were completed using a calibrated direct drive indoor trainer for the standing, seated, and vibration GXTs, and a friction belt cycle ergometer for the high-workload step protocol. Power output (PO) and cadence were collected from three different brand, new pedal units against the gold-standard SRM crankset. The three units of the Assioma Favero exhibited very high within-test reliability and an extremely high agreement between 100 and 250 W, compared to the gold standard (Standard Error of Measurement, SEM from 2.3–6.4 W). Greater PO produced a significant underestimating trend (p < 0.05, Effect size, ES ≥ 0.22), with pedals showing systematically lower PO than SRM (1–3%) but producing low bias for all GXT tests and conditions (1.5–7.4 W). Furthermore, vibrations ≥ 30 Hz significantly increased the differences up to 4% (p < 0.05, ES ≥ 0.24), whereas peak and mean PO differed importantly between devices during the sprints (p < 0.03, ES ≥ 0.39). These results demonstrate that the Assioma Favero power meter pedals provide trustworthy PO readings from 100 to 650 W, in either seated or standing positions, with vibrations between 20 and 40 Hz at cadences of 70, 85, and 100 rpm, or even at a free chosen cadence.

A Field-Based Cycling Test to Assess Predictors of Endurance Performance and Establishing Training Zones

Sanders, D, Taylor, RJ, Myers, T, and Akubat, I. A field-based cycling test to assess predictors of endurance performance and establishing training zones. J Strength Cond Res 34(12): 3482-3488, 2020-This study evaluates the relationship between a field-based 8-minute time trial (8MTT) and physiological endurance variables assessed with an incremental laboratory test. Second, lactate thresholds assessed in the laboratory were compared with estimated functional threshold power (FTP) from the 8MTT. Nineteen well-trained road cyclists (aged 22 ± 2 years, height 185.9 ± 4.5 cm, body mass 72.8 ± 4.6 kg, V[Combining Dot Above]O2max 64 ± 4 ml·min·kg) participated. Linear regression revealed that mean 8MTT power output (PO) was strongly to very strongly related to PO at 4 mmol·L, PO at initial rise of 1.00 mmol·L, PO at Dmax and modified (mDmax) (r = 0.61-0.82). Mean 8MTT PO was largely to very largely different compared with PO at fixed blood lactate concentration of 2 mmol·L (ES = 3.20) and 4 mmol·L (ES = 1.90), PO at initial rise 1.00 mmol·L (ES = 2.33), PO at Dmax (ES = 3.47) and mDmax (ES = 1.79) but only trivially different from maximal PO (Wmax) (ES = 0.09). The 8MTT based estimated FTP was moderate to very largely different compared with PO at initial rise of 1 mmol·L (ES = 1.37), PO at Dmax (ES = 2.42), PO at mDmax (ES = 0.77) and PO at 4 mmol·L (ES = 0.83). Therefore, even though the 8MTT can be valuable as a performance test in cycling shown through its relationships with predictors of endurance performance, coaches should be cautious when using FTP and PO at laboratory-based thresholds interchangeably to inform training prescription.

Aerobic and Anaerobic Power Distribution During Cross-Country Mountain Bike Racing

PURPOSE

To determine aerobic and anaerobic demands of mountain bike cross-country racing.

METHODS

Twelve elite cyclists (7 males; V˙O2max = 73.8 [2.6] mL·min-1·kg-1, maximal aerobic power [MAP] = 370 [26] W, 5.7 [0.4] W·kg-1, and 5 females; V˙O2max = 67.3 [2.9] mL·min-1·kg-1, MAP = 261 [17] W, 5.0 [0.1] W·kg-1) participated over 4 seasons at several (119) international and national races and performed laboratory tests regularly to assess their aerobic and anaerobic performance. Power output, heart rate, and cadence were recorded throughout the races.

RESULTS

The mean race time was 79 (12) minutes performed at a mean power output of 3.8 (0.4) W·kg-1; 70% (7%) MAP (3.9 [0.4] W·kg-1 and 3.6 [0.4] W·kg-1 for males and females, respectively) with a cadence of 64 (5) rev·min-1 (including nonpedaling periods). Time spent in intensity zones 1 to 4 (below MAP) were 28% (4%), 18% (8%), 12% (2%), and 13% (3%), respectively; 30% (9%) was spent in zone 5 (above MAP). The number of efforts above MAP was 334 (84), which had a mean duration of 4.3 (1.1) seconds, separated by 10.9 (3) seconds with a mean power output of 7.3 (0.6) W·kg-1 (135% [9%] MAP).

CONCLUSIONS

These findings highlight the importance of the anaerobic energy system and the interaction between anaerobic and aerobic energy systems. Therefore, the ability to perform numerous efforts above MAP and a high aerobic capacity are essential to be competitive in mountain bike cross-country.

Validity of the Favero Assioma Duo Power Pedal System for Measuring Power Output and Cadence

Cycling power meters enable monitoring external loads and performance changes. We aimed to determine the concurrent validity of the novel Favero Assioma Duo (FAD) pedal power meter compared with the crank-based SRM system (considered as gold standard). Thirty-three well-trained male cyclists were assessed at different power output (PO) levels (100-500 W and all-out 15-s sprints), pedaling cadences (75-100 rpm) and cycling positions (seating and standing) to compare the FAD device vs. SRM. No significant differences were found between devices for cadence nor for PO during all-out efforts (p > 0.05), although significant but small differences were found for efforts at lower PO values (p < 0.05 for 100-500 W, mean bias 3-8 W). A strong agreement was observed between both devices for mean cadence (ICC > 0.87) and PO values (ICC > 0.81) recorded in essentially all conditions and for peak cadence (ICC > 0.98) and peak PO (ICC > 0.99) during all-out efforts. The coefficient of variation for PO values was consistently lower than 3%. In conclusion, the FAD pedal-based power meter can be considered an overall valid system to record PO and cadence during cycling, although it might present a small bias compared with power meters placed on other locations such as SRM.

Using Field Based Data to Model Sprint Track Cycling Performance

Cycling performance models are used to study rider and sport characteristics to better understand performance determinants and optimise competition outcomes. Performance requirements cover the demands of competition a cyclist may encounter, whilst rider attributes are physical, technical and psychological characteristics contributing to performance. Several current models of endurance-cycling enhance understanding of performance in road cycling and track endurance, relying on a supply and demand perspective. However, they have yet to be developed for sprint-cycling, with current athlete preparation, instead relying on measures of peak-power, speed and strength to assess performance and guide training. Peak-power models do not adequately explain the demands of actual competition in events over 15-60 s, let alone, in World-Championship sprint cycling events comprising several rounds to medal finals. Whilst there are no descriptive studies of track-sprint cycling events, we present data from physiological interventions using track cycling and repeated sprint exercise research in multiple sports, to elucidate the demands of performance requiring several maximal sprints over a competition. This review will show physiological and power meter data, illustrating the role of all energy pathways in sprint performance. This understanding highlights the need to focus on the capacity required for a given race and over an event, and therefore the recovery needed for each subsequent race, within and between races, and how optimal pacing can be used to enhance performance. We propose a shift in sprint-cyclist preparation away from training just for peak power, to a more comprehensive model of the actual event demands.

Sprint Tactics in the Tour de France: A Case Study of a World-Class Sprinter (Part II)

PURPOSE

To describe the performance and tactical sprint characteristics of a world-class sprinter competing in the Tour de France. In addition, differences in the sprint tactics of 2 teams and won versus lost sprints are highlighted.

METHOD

Power output (PO) and video footage of 21 sprints were analyzed. Position in the peloton and number of teammates supporting the sprinter at different times before the finish line together with PO for different time intervals were determined. Sprints were classified as team Shimano (2013-2014) and team Quick-step (2016-2017), as well as won or lost.

RESULTS

The sprinter was highly successful, winning 14 out of the 21 sprints. At time intervals 10 to 5, 3 to 2, and 1.5 to 1 minute, POs were significantly lower in team Quick-step compared with team Shimano, but the sprinter was positioned further away from the front at 10, 2, 1.5, 1, and 0.5 minutes at team Quick-step compared with team Shimano. The PO was higher at time interval 0.5 to 0.25 minutes before the finish line with team Quick-step when compared with team Shimano. The position of the sprinter in the peloton in lost sprints was further away from the front at 0.5 minutes before the finish compared with won sprints, while no differences were noted for PO and the number of teammates between won and lost sprints.

CONCLUSIONS

Differences in sprint tactics (Shimano vs Quick-step) influence the PO and position in the peloton during the sprint preparation. In addition, the position at 0.5 minutes before the finish line influences the outcome (won or lost) of the sprint.

Demands of the Tour de France: A Case Study of a World-Class Sprinter (Part I)

PURPOSE

To describe the intensity, load, and performance characteristics of a world-class sprinter competing in the Tour de France (TdF).

METHOD

Power output (PO) data were collected from 4 editions of the TdF (2013, 2014, 2016, and 2017) and analyzed. Load, intensity distribution in 5 PO zones, and the maximal mean PO for multiple durations were quantified. Stages were divided in accordance with the 4 different editions of the TdF, as well as the 4 different stage types, that is, flat (FLAT), semimountainous (SMT), mountain (MT), and (team) time trials. In addition, based on their location within the stage, mountain passes were further classified as BEGINNING, MIDDLE, or END of the stage.

RESULTS

No differences in load, intensity, and performance characteristics were found when the 4 editions of the TdF were compared. Time trials were associated with higher intensities but a lower load compared to the other stage types. MT showed higher load and intensity values compared to FLAT and SMT stages. FLAT stages were higher in short maximal mean PO (≤1 min), whereas MT stages showed higher longer endurance maximal mean PO values (≥20 min). In addition, mountain passes situated at the BEGINNING of the stage were completed with a higher PO, cadence, and speed compared with mountain passes situated at the END.

CONCLUSIONS

A world-class sprinter sustains a higher load and spends more time in the high-intensity zones when competing in the TdF than previously reported values suggested. To finish the MT stages as efficiently as possible, sprinters adopt a reverse pacing strategy.

Caffeinated Chewing Gum Improves Bicycle Motocross Time-Trial Performance

This study aimed to identify the acute effects of caffeinated chewing gum (CAF) on bicycle motocross (BMX) time-trial (TT) performance. In a randomized, placebo-controlled, double-blind cross-over design, 14 male BMX riders (age = 20.0 ± 3.3 years; height = 1.78 ± 0.04 m; body mass = 72 ± 4 kg), consumed either (300 mg; 4.2 ± 0.2 mg/kg) caffeinated (300 mg caffeine, 6 g sugars) or a placebo (0 mg caffeine, 0 g sugars) gum, and undertook three BMX TTs. Repeated-measure analysis revealed that CAF has a large ergogenic effect on TT time, F(1, 14) = 33.570, p = .001, ηp2=.71; -1.5% ± 0.4 compared with the placebo. Peak power and maximal power to weight ratio also increased significantly compared with the placebo condition, F(1, 14) = 54.666, p = .001, ηp2=.79; +3.5% ± 0.6, and F(1, 14) = 57.399, p = .001, ηp2=.80; +3% ± 0.3, respectively. Rating of perceived exertion was significantly lower F(1, 14) = 25.020, p = .001, ηp2=.64 in CAF (6.6 ± 1.3) compared with the placebo (7.2 ± 1.7). Administering a moderate dose (300 mg) of CAF could improve TT time by enhancing power and reducing the perception of exertion. BMX coaches and riders may consider consuming CAF before a BMX race to improve performance and reduce rating of perceived exertion.

The GALNTL6 Gene rs558129 Polymorphism Is Associated With Power Performance

Díaz, J, Álvarez Herms, J, Castañeda, A, Larruskain, J, Ramírez de la Piscina, X, Borisov, OV, Semenova, EA, Kostryukova, ES, Kulemin, NA, Andryushchenko, ON, Larin, AK, Andryushchenko, LB, Generozov, EV, Ahmetov, II, and Odriozola, A. The GALNTL6 gene rs558129 polymorphism is associated with power performance. J Strength Cond Res 34(11): 3031-3036, 2020-The largest genome-wide association study to date in sports genomics showed that endurance athletes were 1.23 times more likely to possess the C allele of the single nucleotide polymorphism rs558129 of N-acetylgalactosaminyltransferase-like 6 gene (GALNTL6), compared with controls. Nevertheless, no further study has investigated GALNTL6 gene in relation to physical performance. Considering that previous research has shown that the same polymorphism can be associated with both endurance and power phenotypes (ACTN3, ACE, and PPARA), we investigated the association between GALNTL6 rs558129 polymorphism and power performance. According to this objective we conducted 2 global studies regarding 2 different communities of athletes in Spain and Russia. The first study involved 85 Caucasian physically active men from the north of Spain to perform a Wingate anaerobic test (WAnT). In the second study we compared allelic frequencies between 173 Russian power athletes (49 strength and 124 speed-strength athletes), 169 endurance athletes, and 201 controls. We found that physically active men with the T allele of GALNTL6 rs558129 had 5.03-6.97% higher power values compared with those with the CC genotype (p < 0.05). Consistent with these findings, we have shown that the T allele was over-represented in power athletes (37.0%) compared with endurance athletes (29.3%; OR = 1.4, p = 0.032) and controls (28.6%; OR = 1.5, p = 0.015). Furthermore, the highest frequency of the T allele was observed in strength athletes (43.9%; odds ratio [OR] = 1.9, p = 0.0067 compared with endurance athletes; OR = 2.0, p = 0.0036 compared with controls). In conclusion, our data suggest that the GALNTL6 rs558129 T allele can be favorable for anaerobic performance and strength athletes. In addition, we propose a new possible functional role of GALNTL6 rs558129, gut microbiome regarding short-chain fatty acid regulation and their anti-inflammatory and resynthesis functions. Nevertheless, further studies are required to understand the mechanisms involved.

Power Analysis of Field-Based Bicycle Motor Cross (BMX)

Introduction

Power meter is a useful tool for monitoring cyclists' training and race performance. However, limited data are available regarding BMX racing power output. The aim of this study was to characterise the power production of BMX riders and investigate its potential role on race performance.

Methods

Fourteen male riders (age: 20.3 ± 1.5 years, height: 1.75 ± 0.05 m, mass: 70.2 ± 6.4 kg) participated in this study. The tests consist of performing two races apart from 15-min recovery. SRM power meter was used to record power and cadence. Cyclists' fastest race was used for the data analysis. Heart rate was recorded at 1-s intervals using a Garmin HR chest strap. Lap time was recorded using four pairs of photocells positioned at the start gate, bottom of the start ramp, end of first corner (time cornering), and on the finish line.

Results

There was a large correlation between race time and relative peak power (r = -0.68, p < 0.01) as well as average power with zero value excluded (r = -0.52, p < 0.01). Race time was also significantly associated with time cornering (r = 0.58, p < 0.01). Peak power (1288.7 ± 62.6 W) was reached in the first 2.34 second of the race. With zero values included, the average power was 355.8 ± 25.4 W, which was about 28% of the peak power, compared to 62% when zero values were excluded (795.6 ± 63.5 W).

Conclusion

The post-race analysis of the power data might help the cyclists recognizing the need to apply certain strategies on pedalling rates and power production in certain portions of the BMX track, specially, at the start and around the first corner. BMX coaches must consider designing training programs based on the race intensity and power output zones.

Validity of the Stryd Power Meter in Measuring Running Parameters at Submaximal Speeds

This study assessed the Stryd running power meter validity at sub-maximal speeds (8 to 19 km/h). Six recreational runners performed an incremental indoor running test. Power output (PO), ground contact time (GCT) and leg spring stiffness (LSS) were compared to reference measures recorded by portable metabolic analyser, force platforms and motion capture system. A Bayesian framework was conducted for systems validity and comparisons. We observed strong and positive linear relationships between Stryd PO and oxygen consumption ( R 2 = 0.82 , B F 10 > 100 ), and between Stryd PO and external mechanical power ( R 2 = 0.88 , B F 10 > 100 ). Stryd power meter underestimated PO ( B F 10 > 100 ) whereas GCT and LSS values did not show any significant differences with the reference measures ( B F 10 = 0.008 , B F 10 = 0.007 , respectively). We conclude that the Stryd power meter provides valid measures of GCT and LSS but underestimates the absolute values of PO.

Cycling Performance in Short-term Efforts: Laboratory and Field-Based Data in XCO Athletes

Mountain bike cross-country Olympic has an intermittent performance profile, underlining the importance of short-term but high cycling power output. Previous findings indicate that power output during sprint tests differs between laboratory and field-based conditions and that cycling cadence rises with increasing workload. The aim was therefore to examine power output and cadence in short-term efforts under laboratory and field conditions. Twenty-three competitive athletes (17.9±3.7 years) performed a laboratory power profile test and a simulated race within one week. Power output and cadence during the power profile test were compared to corresponding short-term efforts during the race over durations of 10-300s (TT 10-300 ). Differences were TT 10 +8%, TT 30 +7%, TT 60 -15% and TT 300 -12% for power output and+10%,+8%,+19%,+21% for cadence respectively. Compared to the race, we found higher power output during the power profile test for the shorter efforts but lower for TT 60 and TT 300 . Confirming previous results, cadence was higher during the power profile test compared to the respective intervals of the race and increased with increasing workload or shorter time trial duration. Future research should take into account that compared to the field, a higher cadence is used in laboratory settings to produce similar power output.

Validity of the Velocomp PowerPod Compared With the Verve Cycling InfoCrank Power Meter

PURPOSE

To determine the validity of the Velocomp PowerPod power meter in comparison with the Verve Cycling InfoCrank power meter.

METHODS

This research involved 2 separate studies. In study 1, 12 recreational male road cyclists completed 7 maximal cycling efforts of a known duration (2 times 5 s and 15, 30, 60, 240, and 600 s). In study 2, 4 elite male road cyclists completed 13 outdoor cycling sessions. In both studies, power output of cyclists was continuously measured using both the PowerPod and InfoCrank power meters. Maximal mean power output was calculated for durations of 1, 5, 15, 30, 60, 240, and 600 seconds plus the average power output in study 2.

RESULTS

Power output determined by the PowerPod was almost perfectly correlated with the InfoCrank (r > .996; P < .001) in both studies. Using a rolling resistance previously reported, power output was similar between power meters in study 1 (P = .989), but not in study 2 (P = .045). Rolling resistance estimated by the PowerPod was higher than what has been previously reported; this might have occurred because of errors in the subjective device setup. This overestimation of rolling resistance increased the power output readings.

CONCLUSION

Accuracy of rolling resistance seems to be very important in determining power output using the PowerPod. When using a rolling resistance based on previous literature, the PowerPod showed high validity when compared with the InfoCrank in a controlled field test (study 1) but less so in a dynamic environment (study 2).

The aerodynamic impact of a range of prostheses designs when cycling with a trans-tibial amputation

Previous studies have proposed that an aerodynamically optimized prosthetic limb could provide performance enhancement for competitive paracyclists. Four different designs of prosthetic limbs were assessed for their impact upon the aerodynamic drag of an elite cyclist with a lower-limb amputation. The pylon area acted as the controlled location for the differences in design between the test prostheses. A validated field test method was used to derive the participant's total aerodynamic drag when using the prostheses designs. The field test method produced a repeatable experimental process and demonstrated that small changes in form made to the pylon region resulted in measurable differences to the participant's cycling performance. In addition, statistical significance was obtained between a baseline design and the prostheses prototype with the greatest aspect ratio (p= <.05). The magnitude of improvements recorded in this study could potentially influence a rider's finishing time at international sporting events like the Paralympic Games.Implications for RehabilitationSmall changes in form made to a cycling prostheses design can potentially deliver worthwhile performance enhancement.Prosthetists may obtain greater end-user satisfaction by taking a broader approach to sports prostheses design than just fit and biomechanical function alone.This study indicates that other regions of the cycling prosthesis could now benefit from aerodynamic optimization with the aim to further improve paracycling performance.

Is the Functional Threshold Power a Valid Surrogate of the Lactate Threshold?

PURPOSE

To analyze the relationship between functional threshold power (FTP) and the lactate threshold (LT).

METHODS

A total of 20 male cyclists performed an incremental test in which LT was determined. At least 48 h later, they performed a 20-min time trial, and 95% of the mean power output was defined as FTP. Participants were divided into recreational (peak power output < 4.5 W·kg-1; n = 11) or trained cyclists (peak power output > 4.5 W·kg-1; n = 9) according to their fitness status.

RESULTS

The FTP (240 [35] W) was overall not significantly different (effect size = 0.20; limits of agreement = -2.4% [11.5%]) from the LT (246 [24] W), and both markers were strongly correlated (r = .95; P < .0001). Accounting for the participants' fitness status, no significant differences were found between FTP and LT (effect size = 0.22; limits of agreement =2.1% [7.8%]) in trained cyclists, but FTP was significantly lower than the LT (P = .0004, effect size = 0.81; limits of agreement =-6.5% [8.3%]) in recreational cyclists. A significant relationship was found between relative peak power output and the bias between FTP and the LT markers (r = .77; P < .0001).

CONCLUSIONS

FTP is a valid field test-based marker for the assessment of endurance fitness. However, caution should be taken when using FTP interchangeably with LT, as the bias between markers seems to depend on the athlete's fitness status. Whereas FTP provides a good estimate of LT in trained cyclists, in recreational cyclists, it may underestimate LT.

Mechanisms of Performance Improvements Due to a Leading Teammate During Uphill Cycling

Purpose: To identify the impact of a leading teammate in front of a cyclist on psychological, physiological, biomechanical, and performance parameters during an uphill maximal effort. Methods: After familiarization, 12 well-trained competitive cyclists completed 2 uphill time trials (UTTs, 2.7 km at 7.4%) in randomized order; that is, 1 performed alone (control condition) and 1 followed a simulated teammate during the entire UTT (leader condition). Performance (UTT time) and mean power output (PO) were recorded for each UTT. For physiological parameters, mean heart rate and postexercise blood lactate concentration were recorded. Psychological parameters (rating of perceived exertion, pleasure, and attentional focus) were collected at the end of each trial. Results: Performance (UTT time) significantly improved by 4.2% (3.1%) in the leader condition, mainly due to drafting decrease of the aerodynamic drag (58% of total performance gains) and higher end spurt (+9.1% [9.1%] of mean PO in the last 10% of the UTT). However, heart rate and postexercise blood lactate concentration were not significantly different between conditions. From a psychological aspect, higher pleasure was observed in the leader condition (+41.1% [51.7%]), but attentional focus was not significantly different. Conclusions: The presence of a leading teammate during uphill cycling had a strong impact on performance, enabling higher speed for the same mean PO and greater end spurt. These results explain why the best teams competing for the general classification of the most prestigious and contested races like the Grand Tours tend to always protect their leader with teammates during decisive ascents.

Validity of PowerTap P1 Pedals during Laboratory-Based Cycling Time Trial Performance

The use of mobile power measuring devices has become widespread within cycling, with a number of manufacturers now offering power measuring pedals. This study aimed to investigate the validity of PowerTap P1 pedals by comparing them with the previously validated Wattbike ergometer. Ten trained cyclists performed three simulated 10-mile (16-km) time trials on a Wattbike, while using PowerTap P1 pedals. There were no statistically significant differences (p > 0.05) between PowerTap P1 pedals and a Wattbike for maximum, minimum, and mean power output, or for maximum, minimum, and mean cadence. There were good to excellent levels of agreement between the PowerTap P1 pedals and Wattbike (ICC > 0.8) for all measured variables except minimum cadence (ICC = 0.619). This suggests that PowerTap P1 pedals provide a valid measurement of power output.

Validity and Reliability of the Cycleops Hammer Cycle Ergometer

PURPOSE

To validate the new drive indoor trainer Hammer designed by Cycleops®.

METHODS

A total of 11 cyclists performed 44 randomized and counterbalanced graded exercise tests (100-500 W) at 70-, 85-, and 100-rpm cadences in seated and standing positions on 3 different Hammer units, while a scientific SRM system continuously recorded cadence and power output data.

RESULTS

No significant differences were detected between the 3 Hammer devices and the SRM for any workload, cadence, or pedaling condition (P value between 1.00 and .350), except for some minor differences (P = .03 and .04) found in the Hammer 1 at low workloads and for Hammer 2 and 3 at high workloads, all in seated position. Strong intraclass correlation coefficients were found between the power output values recorded by the Hammers and the SRM (≥.996; P = .001), independently from the cadence condition and seated position. Bland-Altman analysis revealed low bias (-5.5 to 3.8) and low SD of bias (2.5-5.3) for all testing conditions, except marginal values found for the Hammer 1 at high cadences and seated position (9.6 [6.6]). High absolute reliability values were detected for the 3 Hammers (150-500 W; coefficient of variation <1.2%; SEM <2.1).

CONCLUSIONS

This new Cycleops trainer is a valid and reliable device to drive and measure power output in cyclists, providing an alternative to larger and more expensive laboratory ergometers and allowing cyclists to use their own bicycles.

The Critical Power Model as a Potential Tool for Anti-doping

Existing doping detection strategies rely on direct and indirect biochemical measurement methods focused on detecting banned substances, their metabolites, or biomarkers related to their use. However, the goal of doping is to improve performance, and yet evidence from performance data is not considered by these strategies. The emergence of portable sensors for measuring exercise intensities and of player tracking technologies may enable the widespread collection of performance data. How these data should be used for doping detection is an open question. Herein, we review the basis by which performance models could be used for doping detection, followed by critically reviewing the potential of the critical power (CP) model as a prototypical performance model that could be used in this regard. Performance models are mathematical representations of performance data specific to the athlete. Some models feature parameters with physiological interpretations, changes to which may provide clues regarding the specific doping method. The CP model is a simple model of the power-duration curve and features two physiologically interpretable parameters, CP and W′. We argue that the CP model could be useful for doping detection mainly based on the predictable sensitivities of its parameters to ergogenic aids and other performance-enhancing interventions. However, our argument is counterbalanced by the existence of important limitations and unresolved questions that need to be addressed before the model is used for doping detection. We conclude by providing a simple worked example showing how it could be used and propose recommendations for its implementation.

Reliability of Power Settings of the Wahoo KICKR Power Trainer After 60 Hours of Use

PURPOSE

To assess the reliability of power-output measurements of a Wahoo KICKR Power Trainer (KICKR) on 2 separate occasions separated by 14 mo of regular use (∼1 h/wk).

METHODS

Using the KICKR to set power outputs, powers of 100-600 W in increments of 50 W were assessed at cadences of 80, 90, and 100 rpm that were controlled and validated by a dynamic calibration rig.

RESULTS

A small ratio bias of 1.002 (95% limits of agreement [LoA] 0.992-1.011) was observed over 100-600 W at 80-100 rpm between trials 1 and 2. Similar ratio biases with acceptable limits of agreement were observed at 80 rpm (1.003 [95% LoA 0.987-1.018]), 90 rpm (1.000 [0.996-1.005]), and 100 rpm (1.002 [0.997-1.007]). The intraclass correlation coefficient with 95% confidence interval (CI) for mean power between trials was 1.00 (95% CI 1.00-1.00) with a typical error (TE) of 3.1 W and 1.6% observed between trials 1 and 2.

CONCLUSION

When assessed at 2 separate time points 14 mo apart, the KICKR has acceptable reliability for combined power outputs of 100-600 W at 80-100 rpm, reporting overall small ratio biases with acceptable LoA and low TE. Coaches and sport scientists should feel confident in the power output measured by the KICKR over an extended period of time when performing laboratory training and performance assessments.

Considerations on the Assessment and Use of Cycling Performance Metrics and their Integration in the Athlete's Biological Passport

Over the past few decades the possibility to capture real-time data from road cyclists has drastically improved. Given the increasing pressure for improved transparency and openness, there has been an increase in publication of cyclists' physiological and performance data. Recently, it has been suggested that the use of such performance biometrics may be used to strengthen the sensitivity and applicability of the Athlete Biological Passport (ABP) and aid in the fight against doping. This is an interesting concept which has merit, although there are several important factors that need to be considered. These factors include accuracy of the data collected and validity (and reliability) of the subsequent performance modeling. In order to guarantee high quality standards, the implementation of well-structured Quality-Systems within sporting organizations should be considered, and external certifications may be required. Various modeling techniques have been developed, many of which are based on fundamental intensity/time relationships. These models have increased our understanding of performance but are currently limited in their application, for example due to the largely unaccounted effects of environmental factors such as, heat and altitude. In conclusion, in order to use power data as a performance biometric to be integrated in the biological passport, a number of actions must be taken to ensure accuracy of the data and better understand road cycling performance in the field. This article aims to outline considerations in the quantification of cycling performance, also presenting an alternative method (i.e., monitoring race results) to allow for determination of unusual performance improvements.

Ketone Diester Ingestion Impairs Time-Trial Performance in Professional Cyclists

We investigated the effect of pre- “race” ingestion of a 1,3-butanediol acetoacetate diester on blood ketone concentration, substrate metabolism and performance of a cycling time trial (TT) in professional cyclists. In a randomized cross-over design, 10 elite male cyclists completed a ~31 km laboratory-based TT on a cycling ergometer programmed to simulate the 2017 World Road Cycling Championships course. Cyclists consumed a standardized meal [2 g/kg body mass (BM) carbohydrate (CHO)] the evening prior to a trial day and a CHO breakfast (2 g/kg BM CHO) with 200 mg caffeine on the morning of a trial day. Cyclists were randomized to consume either the ketone diester (2 × 250 mg/kg) or a placebo drink, followed immediately by 200 mL diet cola, given ~ 30 min before and immediately prior to commencing a 20 min incremental warm-up. Blood samples were collected prior to and during the warm-up, pre- and post- TT and at regular intervals after the TT. Urine samples were collected pre- and post- warm-up, immediately post TT and 60 min post TT. Pre-exercise ingestion of the diester resulted in a 2 ± 1% impairment in TT performance that was associated with gut discomfort and higher perception of effort. Serum β-hydroxybutyrate, serum acetoacetate, and urine ketone concentrations increased from rest following ketone ingestion and were higher than placebo throughout the trial. Ketone ingestion induces hyperketonemia in elite professional cyclists when in a carbohydrate fed state, and impairs performance of a cycling TT lasting ~50 min.

The Validation of a Paddle Power Meter for Slalom Kayaking

The ability to quantify power within the sport of slalom kayaking would provide coaches and athletes objective data to monitor performance. This study determined the validity of a kayak paddle power meter and subsequent relationship between work rate and stroke kinetics. One participant completed multiple trials of a flat-water, straight-line sprint and a sequence of slalom gates at numerous intensities to attain the velocity:power relationship. Laboratory results identified the kayak paddles’ strain gauges were valid and reliable, and field tests presented a cubic relationship for power as a function of velocity in the straight-line sprint (R ² =0.982) and the slalom-specific test (R ² =0.993). Further analysis of stroke kinetics identified velocity of hand movement at individual peak force capability to be critical in the highest work rates achieved for both slalom and flat-water sprinting. It was concluded that the kayak paddle power meter tested is a valid means of recording work rate and stroke kinetics during kayaking in the field.

Validation of the virtual elevation field test method when assessing the aerodynamics of para-cyclists with a uni-lateral trans-tibial amputation

Lower-limb amputees typically require some form of prosthetic limb to ride a bicycle for recreation or when competing. At elite-level racing speeds, aerodynamic drag can represent the majority of the resistance acting against a cyclists' forward motion. As a result, the reduction of such resistance is beneficial to an amputee whereby the form and function of the prosthetic limb can be optimized through engineering. To measure the performance of such limbs, field testing provides a cost-effective and context-specific method of aerodynamic drag measurement. However, few methods have been formally validated and none have been applied to amputees with lower-limb amputations. In this paper, an elite level para-cyclist wore two different prosthetic limb designs and had their total aerodynamic drag of a wind tunnel reference method statistically correlated against a velodrome-based virtual elevation field test method. The calculated coefficient of variation was in the range of 0.7-0.9% for the wind tunnel method and 2-3% for the virtual elevation method. A 0.03 m² difference was identified in the absolute values recorded between the two methods. Ultimately, both methods exhibited high levels of precision, yet relative results to each other. The virtual elevation method is proposed as a suitable technique to assess the aerodynamic drag of amputee para-cyclists. Implications for rehabilitation This assessment method will provide practitioners a reliable means of assessing the impact of changes made to prosthetics design for cyclists with limb absence. The proposed method offers a low cost and geographically accessible solution compared to others proposed in the past. This assessment method has significant potential for impact among prosthetic limb users looking to improve their cycling performance whereas previous attention in this field has been extremely limited.

Comparison of ergometer- and track-based testing in junior track-sprint cyclists. Implications for talent identification and development

Talent identification (TID) and talent development (TDE) programmes in track sprint cycling use ergometer- and track-based tests to select junior athletes and assess their development. The purpose of this study was to assess which tests are best at monitoring TID and TDE. Ten male participants (16.2 ± 1.1 year; 178.5 ± 6.0 cm and 73.6 ± 7.6 kg) were selected into the national TID squad based on initial testing. These tests consisted of two 6-s maximal sprints on a custom-built ergometer and 4 maximal track-based tests (2 rolling and 2 standing starts) using 2 gear ratios. Magnitude-based inferences and correlation coefficients assessed changes following a 3-month TDE programme. Training elicited meaningful improvements (80-100% likely) in all ergometer parameters. The standing and rolling small gear, track-based effort times were likely and very likely (3.2 ± 2.4% and 3.3 ± 1.9%, respectively) improved by training. Stronger correlations between ergometer- and track-based measures were very likely following training. Ergometer-based testing provides a more sensitive tool than track-based testing to monitor changes in neuromuscular function during the early stages of TDE. However, track-based testing can indicate skill-based improvements in performance when interpreted with ergometer testing. In combination, these tests provide information on overall talent development.

The midpoint between ventilatory thresholds approaches maximal lactate steady state intensity in amateur cyclists

The aim was to determine whether the midpoint between ventilatory thresholds (MPVT) corresponds to maximal lactate steady state (MLSS). Twelve amateur cyclists (21.0 ± 2.6 years old; 72.2 ± 9.0 kg; 179.8 ± 7.5 cm) performed an incremental test (25 W·min^-1) until exhaustion and several constant load tests of 30 minutes to determine MLSS, on different occasions. Using MLSS determination as the reference method, the agreement with five other parameters (MPVT; first and second ventilatory thresholds: VT1 and VT2; respiratory exchange ratio equal to 1: RER = 1.00; and Maximum) was analysed by the Bland-Altman method. The difference between workload at MLSS and VT1, VT2, RER=1.00 and Maximum was 31.1 ± 20.0, -86.0 ± 18.3, -63.6 ± 26.3 and -192.3 ± 48.6 W, respectively. MLSS was underestimated from VT1 and overestimated from VT2, RER = 1.00 and Maximum. The smallest difference (-27.5 ± 15.1 W) between workload at MLSS and MPVT was in better agreement than other analysed parameters of intensity in cycling. The main finding is that MPVT approached the workload at MLSS in amateur cyclists, and can be used to estimate maximal steady state.

Increase in Maximal Cycling Power With Acute Dietary Nitrate Supplementation

Muscle-shortening velocity and hence power have been shown to increase in the presence of nitric oxide (NO). NO availability increases after consuming nitrate (NO₃^-). Ingestion of NO₃^-rich beetroot juice (BRJ) has increased muscle power in untrained adults.

PURPOSE

This study determined whether NO₃^- supplementation could acutely enhance maximal power in trained athletes.

METHODS

In this double-blind, crossover study, 13 trained athletes performed maximal inertial-load cycling trials (3-4 s) immediately before (PRE) and after (POST) consuming either NO₃^-rich (NO3) or NO₃^-depleted (PLA) BRJ to assess acute changes (ie, within the same day) in maximal power (P_MAX) and optimal pedaling rate (RPM_opt). Participants also performed maximal isokinetic cycling (30 s) to assess performance differences after supplementation.

RESULTS

2 x 2 repeated-measures ANOVA indicated a greater increase in P_MAX from PRE to POST NO3 (PRE 1160 ± 301 W to POST 1229 ± 317 W) than with PLA (PRE 1191 ± 298 W to POST 1213 ± 300 W) (P = .009; η_p² = 0.45). A paired t-test verified a greater relative change in P_MAX after NO3 (6.0% ± 2.6%) than with PLA (2.0% ± 3.8%) (P = .014; d = 1.21). RPM_opt remained unchanged from PRE (123 ± 14 rpm) to POST PLA (122 ± 14 rpm) but increased from PRE (120 ± 14 rpm) to POST NO3 (127 ± 13 rpm) (P = .043; η_p² = 0.30). There was no relative change in RPM_opt after PLA (-0.3% ± 4.1%), but there was an increase after NO3 (6.5% ± 11.4%) (P = .049; d = 0.79). No differences were observed between the 30-s isokinetic trials.

CONCLUSIONS

Acute NO₃^- supplementation can enhance maximal muscle power in trained athletes. These findings may particularly benefit power-sport athletes who perform brief explosive actions.

Knowledge is power: Issues of measuring training and performance in cycling

Mobile power meters provide a valid means of measuring cyclists' power output in the field. These field measurements can be performed with very good accuracy and reliability making the power meter a useful tool for monitoring and evaluating training and race demands. This review presents power meter data from a Grand Tour cyclist's training and racing and explores the inherent complications created by its stochastic nature. Simple summary methods cannot reflect a session's variable distribution of power output or indicate its likely metabolic stress. Binning power output data, into training zones for example, provides information on the detail but not the length of efforts within a session. An alternative approach is to track changes in cyclists' modelled training and racing performances. Both critical power and record power profiles have been used for monitoring training-induced changes in this manner. Due to the inadequacy of current methods, the review highlights the need for new methods to be established which quantify the effects of training loads and models their implications for performance.

Validity and Reliability of the PowerCal Device for Estimating Power Output During Cycling Time Trials

Costa, VP, Guglielmo, LGA, and Paton, CD. Validity and reliability of the PowerCal device for estimating power output during cycling time trials. J Strength Cond Res 31(1): 227-232, 2017-This study assessed the validity and reproducibility of the PowerCal device for estimating power output (PO) during cycling hilly time trials (TTs). Twenty-one well-trained men cyclists performed an incremental exercise test and three 20-km TTs (34.1 ± 10.6 years; 73.2 ± 3.2 kg, 176.8 ± 6.2 cm; maximal PO, 334 ± 31 W; maximal oxygen uptake, 61.0 ± 4.2 ml·kg·min). The first TT was used for familiarization, and the tests were separated by at least 72 hours. Mean PO over the 20-km TT was significantly greater for the Velotron (282 ± 27 W) than for the PowerCal (242 ± 28 W). The mean power over each kilometer of the trial ranged from 5.8 to 23.4% greater on the Velotron than on the PowerCal. High within-subject variation between the trials was substantially greater for the PowerCal (4.9%) than for the Velotron (1.8%). High coefficients of variation scores for the Velotron test-retest were found to be concentrated in the beginning and final meters of the TT (∼6.0%), whereas the scores were lower in the middle of the trials (∼3.0%). In contrast, the PowerCal test-retest achieved a high coefficient of variation (∼6.0%) in each km over the TT. Thus, the PowerCal device should be used with caution during cycling activities because it is not reliable and underestimates PO.

Time course of natural heat acclimatization in well-trained cyclists during a 2-week training camp in the heat

The aim of this study was to determine the time course of physiological adaptations and their relationship with performance improvements during 2 weeks of heat acclimatization. Nine trained cyclists completed 2 weeks of training in naturally hot environment (34 ± 3 °C; 18 ± 5% relative humidity). On days 1, 6, and 13, they performed standardized heat response tests (HRT-1, 2, 3), and 43.4-km time trials in the heat (TTH-1, 2, 3) were completed on days 2, 7, and 14. Within the first 5-6 days, sweat sodium concentration decreased from 75 ± 22 mmol/L to 52 ± 24 mmol/L, sweat rate increased (+20 ± 15%), and resting hematocrit decreased (-5.6 ± 5.4%), with no further changes during the remaining period. In contrast, power output during TTHs gradually improved from TTH-1 to TTH-2 (+11 ± 8%), and from TTH-2 to TTH-3 (+5 ± 4%). Individual improvements in performance from TTH-1 to TTH-2 correlated with individual changes in hematocrit (assessed after the corresponding HRT; r = -0.79, P < 0.05), however, were not related to changes in performance from TTH-2 to TTH-3. In trained athletes, sudomotor and hematological adaptations occurred within 5-6 days of training, whereas the additional improvement in performance after the entire acclimatization period did not relate to changes in these parameters.

Performance differences when using 26- and 29-inch-wheel bikes in Swiss National Team cross-country mountain bikers

The purpose of this study was to analyse the effect of bike type - the 26-inch-wheel bike (26" bike) and the 29-inch-wheel bike (29" bike) - on performance in elite mountain bikers. Ten Swiss National Team athletes (seven males, three females) completed six trials with individual start on a simulated cross-country course with 35 min of active recovery between trials (three trials on a 26" bike and three trials on a 29" bike, alternate order, randomised start-bike). The course consisted of two separate sections expected to favour either the 29" bike (section A) or the 26" bike (section B). For each trial performance, power output, cadence and heart rate were recorded and athletes' experiences were documented. Mean overall performance (time: 304 ± 27 s vs. 311 ± 29 s; P < 0.01) and performance in sections A (P < 0.001) and B (P < 0.05) were better when using the 29" bike. No significant differences were observed for power output, cadence or heart rate. Athletes rated the 29" bike as better for performance in general, passing obstacles and traction. The 29" bike supports superior performance for elite mountain bikers, even on sections supposed to favour the 26" bike.

Impact of Altitude on Power Output during Cycling Stage Racing

PURPOSE

The purpose of this study was to quantify the effects of moderate-high altitude on power output, cadence, speed and heart rate during a multi-day cycling tour.

METHODS

Power output, heart rate, speed and cadence were collected from elite male road cyclists during maximal efforts of 5, 15, 30, 60, 240 and 600 s. The efforts were completed in a laboratory power-profile assessment, and spontaneously during a cycling race simulation near sea-level and an international cycling race at moderate-high altitude. Matched data from the laboratory power-profile and the highest maximal mean power output (MMP) and corresponding speed and heart rate recorded during the cycling race simulation and cycling race at moderate-high altitude were compared using paired t-tests. Additionally, all MMP and corresponding speeds and heart rates were binned per 1000 m (<1000 m, 1000-2000, 2000-3000 and >3000 m) according to the average altitude of each ride. Mixed linear modelling was used to compare cycling performance data from each altitude bin.

RESULTS

Power output was similar between the laboratory power-profile and the race simulation, however MMPs for 5-600 s and 15, 60, 240 and 600 s were lower (p ≤ 0.005) during the race at altitude compared with the laboratory power-profile and race simulation, respectively. Furthermore, peak power output and all MMPs were lower (≥ 11.7%, p ≤ 0.001) while racing >3000 m compared with rides completed near sea-level. However, speed associated with MMP 60 and 240 s was greater (p < 0.001) during racing at moderate-high altitude compared with the race simulation near sea-level.

CONCLUSION

A reduction in oxygen availability as altitude increases leads to attenuation of cycling power output during competition. Decrement in cycling power output at altitude does not seem to affect speed which tended to be greater at higher altitudes.

Comparison of power output during ergometer and track cycling in adolescent cyclists

The aim of this study is to establish the level of agreement between test performance of young elite cyclists in a laboratory and a track field-based trial. Fourteen adolescent cyclists (age: 14.8 ± 1.1 years; (Equation is included in full-text article.): 63.5 ± 5.6 ml·min(-1)·kg(-1)) performed 3 tests of 10 seconds, 1 minute, and 3 minutes on an air-braked ergometer (Wattbike) and on a 250-m track using their own bikes mounted with mobile power meters (SRM). The agreement between the maximum and mean power output (Pmax and Pmean) measured on the Wattbike and SRM was assessed with the 95% limits of agreement (LoA). Power output was strongly correlated between Wattbike and SRM for all tests (r = 0.94-0.96; p < 0.001). However, power output was significantly higher on the Wattbike compared with track cycling during all tests. The bias and 95% LoA were 76 ± 78 W (8.8 ± 9.5%; p = 0.003, d = 0.38) for Pmax10s and 82 ± 55 W (10.9 ± 7.9%; p < 0.001, d = 0.46) for Pmean10s. During the 1- and 3-minute test, the bias and 95% LoA were 72 ± 30 W (17.9 ± 7.1%; p < 0.001, d = 0.84) and 28 ± 20 W (9.6 ± 6.1%; p < 0.001, d = 0.51), respectively. Laboratory tests, as assessed using a stationary ergometer, resulted in maximal and mean power output scores that were consistently higher than a track field-based test using a mobile ergometer. These results might be attributed to the technical ability of the riders and their experience to optimize gearing and cadence to maximize performance. Prediction of field-based testing on the track from laboratory tests should be used with caution.