This qualitative study explores professional team sport directors’ perceptions of the attributes required for successful Road Captains (RCs) in men’s elite road cycling representing a specific organizational context. Six sport directors from one UCI-ranked men’s professional cycling team participated in semi-structured interviews. Five of the participants had previously competed as professional cyclists, accumulating 57 years of racing experience across 19 elite cycling teams spanning UCI Continental, ProTeam, and World Tour levels. Transcripts were analyzed using thematic analysis, adopting a combined inductive–deductive approach within an interpretivist framework. The analysis yielded four primary themes and one overarching meta-theme. Personal characteristics included self-confidence, composure, and a strong work ethic. Race smartness comprised thorough preparation and tactical knowledge, enabling RCs to make rapid, high-quality decisions under pressure. Team competence encompassed effective communication, care and support, and bonding behaviors. Leadership behavior involved role-modelling, decisive action, and tailored motivational strategies. The meta-theme, “the hub of the team,” described the RC as the communication and operational link between sport directors in the team car and riders in the peloton. Participants emphasized that successful RCs combine tactical intelligence with interpersonal influence and in many ways, act as cultural architects who translate management strategy into coordinated team action and develop and maintain the interaction in the team. Findings are aligned and discussed with transformational and the social identity approach to leadership. The results provide factors to consider when selecting RCs and offer targets for development programs. Integrating principles from athlete- and coach-leadership training could help cultivate the identified competencies, improving intrateam communication, cohesion, and performance in the elite cycling context.
The rapid electrification of bicycles has fundamentally transformed drivetrain dynamics, leading to significantly higher loads on mechanical components such as chains. Unlike in traditional bicycles, where wear and efficiency losses primarily concerned competitive riders, the widespread adoption of e-bikes and other high-performance bicycles has made these issues critical for everyday cycling. Increased torque and sustained power assistance place unprecedented mechanical and tribological demands on drivetrains, making durability, friction reduction, and efficiency vital considerations for both manufacturers and users. As a result, research and testing methods that were once used mainly for industrial chain applications are increasingly relevant for the cycling industry. This study addresses these emerging challenges by adapting proven methodologies from mechanical and automotive engineering. Through controlled laboratory testing, bicycle chains and lubricants can be evaluated under standardized conditions that replicate real-world usage scenarios. Such testing does not only enable precise comparisons between different chain and lubricant systems but also provides insight into the fundamental wear mechanisms and efficiency losses occurring under varying loads, speeds, and environmental conditions. The approach supports the tailored design of drivetrain components for diverse cycling applications, including urban e-bikes, high-speed track bicycles, and rugged mountain bikes. By bridging disciplines, this work paves the way for innovations that enhance performance, reliability, and sustainability in modern cycling. A model procedure is presented here based on three exemplary high-speed track-bike scenarios. The focus is on the implementation of the experimental strategy and the derivation of the methodology. .
An underrecognized clinical condition that may afflict high level cyclists is external iliac artery endofibrosis (EIAE). EIAE is an intermittent claudication vascular condition that results from intimal narrowing most often of the external iliac artery (EIA). Symptoms are reported as thigh pain and loss of power that occur during high intensity efforts. EIAE is theorized to be a result of the mechanical and hemodynamic stress within the EIA heightened by psoas muscle hypertrophy in conjunction with the repetitive and extreme hip flexion coupled with high cardiac output. A combination of clinical tests (e.g. ankle-brachial index) in concert with imaging and vascular studies (e.g. duplex ultrasound) is necessary to arrive at an accurate diagnosis. The mean time from symptom onset to diagnosis is 3 years. Conservative interventions, which consist of bike hardware adjustments and/or posture modifications while riding, are generally not acceptable for a competitive cyclist. Surgical interventions take the form of percutaneous/endoscopic (e.g. balloon angioplasty, stent insertion) or open procedures (e.g. arterial release, endarterectomy, artery reconstruction) to restore arterial flow. Long-term outcomes following percutaneous procedures have followed a finite number of patients to date and are not recommended as a primary intervention for EIAE. Outcomes following open surgical procedures are strong with most riders being able to return to preinjury levels of competition. Greater awareness of EIAE among the scientific and medical community who work with cyclists is needed to improve the efficiency and overall management of EIAE.
The aim of this study was to assess the test–retest reliability of the Cyclotronics Smart Trainer during a graded exercise test (GXT) and a power profile test (PPT) in trained cyclists. For the GXT reliability analysis, 22 cyclists performed three GXTs, each separated by seven days. For the PPT reliability assessment, a smaller group of 10 trained participants (2 females, including 1 triathlete and 7 cyclists) completed one GXT followed by three PPTs, also separated by seven days. The first test in each protocol was used for familiarization and excluded from the reliability analysis. During the GXT, the coefficient of variation (CV) ranged from 5.5% at the lowest workload (100 W) to 1.6% at the highest workload (300 W), demonstrating reduced variability at higher intensities. A very low CV was also observed for peak power output (PPO), indicating high consistency in maximal performance measures. Regarding the PPT, acceptable test–retest reliability was observed, particularly for efforts lasting 120 seconds or more. As expected, shorter efforts showed slightly greater variability, which is common in high-intensity performance tests with a smaller sample size. In conclusion, the Cyclotronics Smart Trainer demonstrated reliable measurements during both GXT and PPT protocols. These findings support its use in repeated testing scenarios where measurement consistency is essential.
The purpose of this study was to identify whether cycling time trial (TT) performance and cycling metrics are affected by small changes in crank arm length (CAL). Fourteen subjects (8 male; 6 female) completed three cycling TTs with different CALs (i.e., 165, 170, and 175 mm) on three separate occasions along a designated virtual course (distance: 11.65 km, elevation: 34.1 m) using a smart bike integrated with augmented reality (AR) software. A repeated measures ANOVA was conducted to analyze the effect of CAL on various cycling metrics: cadence (rpm), pace (m×s-1), power (W×kg-1), TT performance (min), energy expenditure (kJ), heart rate (bpm), and rate of perceived exertion (RPE), with appropriate post hoc tests as needed. Cadence, pace, and TT performance showed significant main effects across CALs (p < 0.05). However, no statistical differences were observed in cycling power, energy expenditure, average heart rate, or RPE (p > 0.05). Smallest worthwhile change (SWC) analysis revealed that performance differences between 165 and 170 mm may still hold practical significance despite statistically non-significant post hoc comparisons (p > 0.05). These findings suggest that a shorter CAL is associated with faster completion time under controlled conditions due to higher cadence and faster pace without increasing physiological strain. Practically, recreational cyclists and novice triathletes may consider slightly shorter crank arms to improve short-to-moderate distance cycling performance. In addition, an augmented reality platform combined with a smart bike provides a reproducible and ecologically valid method for training and applied performance assessment.
Cyclist’s Knee or Patellofemoral Pain Syndrome is the most frequently reported lower extremity repetitive stress injury incurred by cyclists. With a 40% recurrence rate after 2 years and 50% of the patients are still symptomatic or have functional impairments 5-8 years post treatment, makes this a frustrating and perplexing condition for both athletes and medical professionals. Numerous extrinsic and intrinsic risk factors have been theorized and researched. To date, no definitive etiology has been determined. Historically, cycling research and treatment has taken a cause-and-effect approach to this repetitive stress injury focusing on factors responsible for patellar maltracking. This pathomechanical action was felt to result from muscle imbalances. Research has also found malalignment and/or dysfunction at either end of the kinetic chain, the foot/ankle or pelvis/hip complex may negatively impact the functioning of the LE as a whole. The purpose of this clinical commentary is to elucidate evidence substantiating patellofemoral pain syndrome may be a simultaneous multifactorial repetitive stress injury due to the complex regional interdependent biomechanical nature of the LE. With this knowledge the development of more effective treatment protocols may bring about better outcomes.
In 1984 Mader constructed a mathematical model of human energy metabolism to understand the metabolic origin behind the maximal lactate steady state. An integral parameter of Mader’s model requires knowledge of the maximal rate of glycolysis, which Mader derived from the maximal lactate formation rate within the muscle cell. However, in-vivo the maximal lactate formation rate within the muscle cannot be measured. Subsequently, Mader proposed the utility of measuring the rate of maximal blood lactate accumulation following supramaximal exercise as an indirect measure of glycolytic flux, termed νLamax. Recently, the νLamax has gained popularity amongst researchers and practitioners as an indirect assessment method to determine the maximal glycolytic rate. Currently, there is a distinct lack of continuity in methodological approaches between researchers. Therefore, the primary aim of this systematic review was to evaluate the current methodological approaches applied to test the νLamax. Based on the findings we make practical recommendations for researchers to adopt to promote standardisation of test procedures. Comprehensive searches of the databases; PubMed, SCOPUS, Google Scholar, and SPOLIT, identified 3545 articles for screening (1984-2024). In total 27 articles were included within this review, with seven different modalities identified. The results from this systematic review highlight several key considerations which need to be considered when testing the νLamax including; alactic timespan, test duration, baseline blood lactate concentration, modality specificity, movement velocity, recovery procedures, and post exercise blood lactate sampling times. Based on these findings this review provides detailed recommendations to standardise νLamax methods considering pre-test, test, and post-test factors.
The Tour de France stands as perhaps the most demanding endurance competition in the world, requiring athletes to sustain exceptional physiological performance over three weeks of racing. Central to success in this event is a remarkably high maximal oxygen uptake (V̇O₂max). The 2024 and 2025 Tour de France showcased unprecedented climbing performances, with new records set on iconic ascents. This brief report analyzes the physiological demands of these performances by estimating the V̇O₂ and power output required during six decisive climbs (Plateau de Beille, Isola 2000, Col de la Couillole, Hautacam, Peyragudes, Mont Ventoux) by the race winner, Tadej Pogačar. Using publicly available climb data, rider anthropometrics, and validated mechanical models of cycling power output, results indicate estimated mean power outputs of 442 ± 15 W and corresponding mean oxygen consumptions of 80 ± 3 mL·kg⁻¹·min⁻¹ sustained over ~40 min. Extrapolating from these efforts and known relationships between critical power and V̇O₂max suggests that Pogačar’s V̇O₂max during the race likely exceeded 90 mL·kg⁻¹·min⁻¹. These findings underscore the extraordinary aerobic capacity required to achieve record-breaking performances in Grand Tour cycling. They also highlight how ongoing improvements in training, equipment, and rider physiology continue to push the limits of human endurance performance to the enjoyment of the spectators.
Advances in bicycle instrumentation and social media applications make it possible to quantify training and racing. PURPOSE: The primary purpose was to compare training volume of USA Cycling (USAC) road racers, split out by racing category and gender. A secondary purpose was to compare power profiles of these groups. METHODS: Part 1. USAC racers with a Strava® account were selected. Using 2019 data uploaded from GPS head units, 543 racers (279 men, 264 women) were studied. Part 2. A subset of racers with power meters (N=346) were contacted to obtain demographic information and peak power data (5-s, 1-min, 5-min, 20-min, and 1-h). 92 racers (67 men, 25 women) agreed to participate. ANOVAS were used to compare annual training/racing metrics and power data across categories and genders. RESULTS: Part 1. Training/racing volumes (annual hours, distances, races, and ride days) rose significantly as the level of expertise increased. There were significant gender differences for pros (p<0.001) for all variables except ride days, but there were no gender differences within categories 2, 3, 4, and 5. Part 2. In terms of peak power (W·kg–1), there were significant main effects for category and gender (p<0.001), but no significant interactions. Overall, men produced more power than women. Categories 1/2 produced significantly more power than categories 3, 4, and 5, but the differences between categories 3, 4, and 5 were marginal. CONCLUSION: Cycling coaches can use this information to develop training programs for bicycle road racers at all levels, and for tracking their progress.
The COVID-19 pandemic of 2020 led governments around the world to respond by imposing lockdown restrictions, which limited the ability of cyclists to train and race as they typically would. While limited research describes the impact on professional and elite riders, less is known about the impact on recreational/sub-elite riders. Given that cyclists of this level contribute a high proportion of the cycling population, we set out to conduct a survey to determine the impact of COVID-19 on their training and racing practices. Questions covered their demographics and background, followed by their typical training, such as regular session type and frequency, training intensity distribution, and their racing practices. A total of 146 cyclists responded, and results revealed that despite decreases in the general population’s physical activity levels, 71.9% of respondents actually increased their cycling volume in 2020, with a significantly higher volume in every month in 2020 compared to 2019. Intensity distribution was also modified due to lockdowns, the volume of high intensity training was increased by 30.7% of respondents, while 37.3% decreased their high intensity training volume, often alongside an increase in overall volume. Racing practices were also altered, in-person racing dropped 56.6%, while e-racing on platforms such as Zwift increased by 114.7%. Despite the challenges, 67.9% of respondents reported feeling fitter in 2020, and 57.8% specifically felt the period of lockdown increased their fitness. These findings highlight the adaptability of recreational and sub-elite cyclists and their resilience to endure an unprecedented global pandemic.
Muscle recovery in athletes has been a progressively investigated topic and there has been growing concern about it. Due to more and more dense race calendars, using the best recovery method between training and events is crucial to the athlete's performance. The massage gun is an instrument that is becoming increasingly popular. Research has followed this growth trend, however the available information is still scarce with the need to explore the topic for different protocols and populations, namely in the cycling community. Therefore, the study aimed to evaluate the effects of a massage gun protocol and a static stretching protocol on fatigue parameters in experienced road cycling and mountain biking athletes. Sixteen cyclists performed two fatigue in-session protocols in which two random experimental recovery protocols (massage guns and static stretching), were applied between the fatigue protocols. Data relating to Heart rate, Power, Lactate concentration, VO2max, and Rate of perceived exertion were collected in four moments (M1 - baseline; M2 - after fatigue protocol; M3 - after the recovery protocol; M4 - after a second fatigue protocol). The athletes repeated the tests two weeks apart performing the other recovery protocol. From the collected data, it was found that the use of the massage gun and static stretching protocols causes positive effects in fatigue-related outcomes (Lactate concentration and Rate of perceived exertion). However, no statistically significant differences were found between the groups (p > 0.05). Therefore, although massage guns could be an effective instrument in decreasing fatigue related outcomes, they are not superior to others more commonly used and established recovery methods, such as static stretching.
Performing a warm-up in sport is generally seen as an essential part of any pre-race routine. However, studies have reported mixed findings on the benefits of such routines and few studies have looked at the influence of warm-up on BMX performance. Therefore, this study aimed to 1) ascertain if a warm-up had an effect on BMX performance 2) whether a rest period post warm-up affected performance, and 3) if a sub-maximal warm-up could influence performance to a greater extent. The study assessed 11 competitive BMX riders in a field-based environment on an indoor BMX track. Riders performed three trials. In trial one, they performed a maximal effort lap on the track without a warm-up. In trial two, riders performed a conventional warm-up, generally consisting of sprint intervals, then sat for 10-minutes in a holding area before performing another timed sprint lap. Lastly, for trial three, rider performed a structed sub-maximal warm-up then performed a final maximal effort sprint on the track. The results found no statistical differences between the trials (F(2,30)= .18; p ≥.05; ƞ2=.01). However, there was a difference in mean times when comparing trial 2 (34.1 ± 3.70 s) and 3 (34.2 ± 3.70 s) to the non-warm up trial (34.9 ± 3.58 s). The time differences may appear marginal, but when applied to race data they could have a potential impact. Research has shown that 0.49 ± 0.36 s faster lap times can result in a rider moving up at least one position or progressing to the next round in the heats.
Cycling kinematic analysis plays a central role in the bike fitting process, directly influencing decisions related to performance, comfort, and injury prevention. Consistency of measurements across evaluators is therefore essential for ensuring reliable outcomes in both clinical and performance contexts. This cross-sectional inter-observer agreement study evaluated inter-examiner variability in two-dimensional (2D) kinematic measurements obtained with Kinovea® software. A sample of 53 professional bike fitters from different regions of Brazil analyzed the same 40-second video of a cyclist pedaling on a stationary mountain bike. Each participant independently selected frames and measured seven predefined joint and positional angles. Statistical analyses included descriptive measures, Shapiro–Wilk normality testing, bootstrap confidence intervals, one-sided chi-square variance tests with Holm corrections, bias and empirical limits of agreement, Brown–Forsythe tests of dispersion, and Fleiss’ κ for categorical KOPS classification. The results showed notable inter-examiner variability, particularly for knee extension (CV = 6.2%), trunk flexion (CV = 5.8%), and plantar flexion (CV = 4.8%), which exceeded predefined tolerance thresholds of 2–4% of the mean. By contrast, hip flexion, knee flexion, and armpit angle showed greater consistency. Subgroup analyses revealed no significant effect of professional experience or software used on measurement variability. These findings highlight that, even under identical testing conditions, methodological differences among raters can substantially influence kinematic measurements. The study underscores the need for standardized protocols and structured training in 2D motion analysis to improve reliability in bike fitting practice and ensure safer, more effective adjustments for cyclists.
This study aimed to characterize the performance at the 2023 UCI Cycling E-Sports World Championships in 18 women and 27 men competing in this three-race knockout series with a direct elimination finale. We evaluated their power profile, critical power (women: 249 ± 29 W; men: 362 ± 26 W) and W′ (women: 14.4 ± 1.5 kJ; men: 23.5 ± 4.2 kJ) over the 12 months preceding the competition and during the event. Energy depletion during races was analyzed using Bartram’s W′ balance models. Women and men advancing to the next race developed respectively ~15% and ~16% more power (W/Kg) compared to those eliminated in Race 1, for durations of ≤1 min (p < 0.001). In women, similar W′ depletion was observed in Race 1 and Race 2 (p = 0.35). In men, greater depletion was observed at the end of Race 1 compared to Race 2 (8 ± 8% difference, p = 0.007). The direct-elimination format of Race 3, involving repeated sprints, led to lower W′ depletion for both sexes. The results suggest that power developed for efforts up to 60 seconds and the ability to recover across races are pivotal for performance at the 2023 Cycling E-Sports World Championships.
The Wattbike Pro ergometer (Wattbike) is readily available and widely used by athletes, coaches, and researchers as a tool for cycling performance assessment. To-date, no literature has reported the test-reliability of relevant performance criterion using the Wattbike and a 10-mile (16.1 km) TT - which is the most prevalent race distance, often completed in the summer race season. Therefore, the aim of this study was to assess the reliability of 16.1 km TT performance in the heat using the Wattbike Pro ergometer. A cohort of trained cyclists volunteered to take part in this study (n = 16, mean ± SD age 36.4 ± 14.0 y, height, 1.77 ± 0.09 m, body mass 75.2 ± 7.3 kg, PPO 365.1 ± 55.2 W, V̇O2max 55.0 ± 9.5 mL.kg-1.min-1. Participants performed a familiarisation, prior to two 16.1 km TT on the Wattbike Pro ergometer separated by 3-7 days. Differences in mean completion time, power output, and speed were determined using paired samples T-tests, with quartile data assessed using repeated-measures ANOVA. Reproducibility of the performance measures was performed using the coefficient of variation (CV), intraclass correlations, technical error (rTE and sTE) and, Cronbach’s α. There were no significant differences between TT1 and TT2 for time, power output and speed (mean difference = 3.25 s, 3.2 W, and 0.15 km·h-1, respectively). All performance data demonstrated excellent reproducibility (CV range = 0.8 – 1.9%) with trivial sTE (0.16 – 0.20). The 16.1 km cycling TT when conducted on a Wattbike Pro ergometer demonstrates a very reliable performance criteria in cohorts of trained cyclists, when exercising in hot conditions. Athletes, coaches, and researchers alike, should be aware of the inter-bike reliability which has been previously reported, and ensure that the same ergometer is used when measuring performance, thereby ensuring the reliability of the 16.1 km TT.
This editorial presents a comprehensive account of cycling’s historical and conceptual evolution from the traditional and empirically-based Cycling 1.0, through the collaborative, ethical and evidence-driven Cycling 2.0 (Zabala & Atkinson, 2012), to a proposed Cycling 3.0 era shaped by artificial intelligence (AI). Drawing on original sources, publications, and later empirical studies, it argues that the sport’s ethical and scientific progression should remain grounded in transparency, collaboration, and athlete education. The Cycling 3.0 paradigm can amplify the benefits of 2.0, provided that its algorithms, data systems, and governance frameworks can respect the humanistic and ethical foundations that rescued cycling from its 1.0 crises.
The mixed-team super-sprint triathlon relay (~300m swimming, ~6.6km cycling and ~1.5km running) performed in teams of four athletes, is the newest Olympic triathlon discipline. Until today, no scientific data is available on the specific physiological attributes. Our study aims to predict a super-sprint triathlon performance from physiological exercise testing. Fourteen national level triathletes performed physiological tests in swimming and running and competed in a super-sprint triathlon. The physiological profile in swimming and running was calculated and applied to predict triathlon performance. The speed at VO2max_swim corresponded well to the swimming speed during the triathlon (0.013 m·s-1, n.s.), whereas the running speed was similar to the running speed at metabolic steady state (MMSSrun) (0.05 m·s-1, n.s.). Stepwise multiple regression analysis selected MMSSrun as the primary predictor of triathlon performance (r2 = 0.66, p<0.05). The swimming speed at metabolic steady state (MMSSswim) (r2 = 0.84, p<0.05) and the amount of work that can be performed above MMSSrun (W’run) were also included in the prediction model (r2 = 0.91, p<0.05). Our data indicate that MMSSrun, MSSswim, and W’run allow for a precise prediction of a super-sprint triathlon performance. This information can be used to optimize training and pacing strategies.
A fast and stable launch is decisive in Bicycle Moto-Cross (BMX) racing, yet the underlying interplay between rider power production, bicycle gearing and ramp geometry has received little attention in the engineering literature. Using high-frequency field measurements gathered on the Olympic track of Saint Quentin-en-Yvelines (France), we develop and validate a physics-based model that predicts the rider’s velocity profile over the start ramp. The formulation combines (i) a Hill-type linear torque–cadence relationship fitted to instrumented-crank data, (ii) an energy balance that accounts for aerodynamic and rolling losses, and (iii) the measured track slope. Model predictions agree with experiments for three gear ratios. We then explore two practical optimisation criteria—minimum time to the first bump and maximum mean acceleration on the ramp—to identify gearing strategies tailored to individual athletes. The framework illustrates how on-track sensing can be translated into actionable engineering guidelines for coaches and riders.
Analyses of 1-km time trial (TT) racing profiles specifically for high school cyclists are lacking. This study aimed to clarify the racing profiles of male high school cyclists in a 1-km TT. The 1-km TT performance was analyzed in 50 male high school cyclists who participated in competitions held on the same track (333.3 m). The cyclists were divided into the High (n = 25, 72.9 ± 2.0 seconds) and Low (n = 25, 79.9 ± 3.1 seconds) groups based on their 1-km TT performance. We obtained panning shots of cyclists during the 1-km TT race and calculated the section velocity at every 83 m, average velocity, peak velocity, normalized velocity, and fatigue index from lap times. Analysis of variance showed significant main effects for section velocities and group, as well as a significant interaction in the 1-km TT velocity curve. The peak velocity was significantly higher in the High group than in the Low group (p = 0.000). However, the fatigue index did not differ between the groups. Significant negative correlations were found between 1-km TT record and velocity in each section and peak velocity in both groups (p < 0.05 or p < 0.01). In conclusion, the racing profiles of 1-km TT related to better performance are determined by higher peak velocity but are not influenced by the rate of velocity decline after reaching the peak velocity in male high school cyclists.
The functional threshold power (FTP) 20-min test (FTP20) is popular amongst cyclists and coaches due to the theory it can predict the power output that can be sustained for 60-mins. However, little is known in terms of the reliability and validity of this construct, therefore the aim of this study was to assess the reliability of the FTP20 test and the construct validity of this test to predict 60-min power. Twenty-two male trained cyclists (age = 32 ± 10 years, body mass (BM) = 77.2 ± 6.8 kg, maximal oxygen uptake (V̇O2max) = 59.4 ± 5.6 ml.kg-1.min-1 BM) completed five trials consisting of a V̇O2max test, a familiarisation trial of the FTP20, two experimental FTP20 tests, and a time to volitional exhaustion (TLIM) at 95% FTP20. The repeatability for mean power output (MPO) during the FTP20 was excellent (r = 0.94, CI 0.82, 0.98, p<0.001). Mean TLIM (at 95% FTP20) was 42 ± 17-min, with six participants within 10-min of the 60-min suggested threshold. These results suggest that the FTP20 is reliable, however it does not predict 60-min power with a high level of validity. Future research should explore adapting the calculation of FTP whereby the intensity may be lowered (i.e., 80-90% MPO of FTP20), particularly as most participants’ TLIM was far below the suggested 60-min time frame.
