Scientific approach to the 1-h cycling world record: a case study

Exploring the Potential Benefits of Interventions When Addressing Simulated Altitude Hypoxia during Male Cyclist Sports: A Systematic Review

Training in hypoxic environments enhances endurance, but the various influences of training protocols and supplementation for efficient performance are not yet clear. This systematic review explored the effects of different supplementations and interventions used to optimize the aerobic and anaerobic performance of cyclists. Data were collected from the following sources: PubMed, Google Scholar, EMBASE, WOS, Cochrane Central Register of Controlled Trials, and randomized controlled trials (RCTs). Studies that explored the effects of supplementation or intervention during cycling were selected for analysis. Five studies (67 male cyclists; mean age, 23.74–33.56 years) reported different outcomes from supplementation or intervention during the acute hypoxia of cyclists. Three studies (42 male cyclists; mean age, 25.88–36.22 years) listed the benefits of beetroot juice in preserving SpO2 (pulse oxygen saturation) and enhancing high-intensity endurance performance, effectively preventing the reduction in power output. This systematic review provided evidence that the different effects of ischemic preconditioning (IPC), sildenafil, and beetroot (BR) supplementation and intervention did not present a statistically greater benefit than for normoxia groups, but BR supplementation promoted the benefits of SpO2. Future research should evaluate the duration and higher FiO2 (simulated altitude, hypoxia) levels of hypoxia in training protocols for cyclists. This is important when determining the effectiveness of supplements or interventions in hypoxic conditions and their impact on sports performance, particularly in terms of power output.

Making History in 1 h: How Sex, Aging, Technology, and Elevation Affect the Cycling Hour Record

PURPOSE

The purpose of this article was to analyze more than a century of cycling hour records (CHR) to examine the effects of sex, age, and altitude on cycling performance. Our hypotheses were that men's performance (distance) would exceed those of women by more than 10% but would decline at similar rates with aging and that altitude would have a small benefit, which might reach a maximum.

METHODS

Data were cultivated from the Facebook World Hour Record Discussion Group's crowd-sourced database of more than 600-known-hour records and verified through extensive online research and/or personal communication. Regression and statistical modeling were produced using STATA v15.0. R2 values were used to ascertain model quality, with four distinct models being produced for comparisons. Alpha was set at 0.05 significance for all tests.

RESULTS

R2 values ranged from 65% to 74.9%. Women's distances were 10.8% shorter ( P < 0.001) than those of men, but the difference was narrower than either the historical elite women's difference of 14.2% or the 2022 record difference of 13.3%. Age-related decline modeling indicates performance declines significantly past age 40 yr at a rate of 1.08% per year. Altitude had a significant ( P < 0.001) marginal improvement up to 1000 m before declining. The marginal benefits of altitude were small, but this is consistent with the finding benefits reach a maximum at a moderate altitude with "benefits" becoming ambiguous starting at ~1000 m. Technological advancement was estimated to be a small but significant ( P < 0.001) improvement of ~0.18% per year.

CONCLUSIONS

Across decades of CHR data in well-trained endurance cyclists, men are only ~11% faster, and this difference remains stable until at least age 80 yr. CHR attempts greater than 500 m likely offer at best a small advantage. Despite small year-on-year improvements, the CHR has likely improved more than 10 km because of technological advancements.

Modelling human endurance: power laws vs critical power

The power-duration relationship describes the time to exhaustion for exercise at different intensities. It is believed to be a "fundamental bioenergetic property of living systems" that this relationship is hyperbolic. Indeed, the hyperbolic (a.k.a. critical-power) model which formalises this belief is the dominant tool for describing and predicting high-intensity exercise performance, e.g. in cycling, running, rowing or swimming. However, the hyperbolic model is now the focus of a heated debate in the literature because it unrealistically represents efforts that are short (< 2 min) or long (> 15 min). We contribute to this debate by demonstrating that the power-duration relationship is more adequately represented by an alternative, power-law model. In particular, we show that the often-observed good fit of the hyperbolic model between 2 and 15 min should not be taken as proof that the power-duration relationship is hyperbolic. Rather, in this range, a hyperbolic function just happens to approximate a power law fairly well. We also prove mathematical results which suggest that the power-law model is a safer tool for pace selection than the hyperbolic model and that the former more naturally models fatigue than the latter.

The Fine-Tuning Approach for Training Monitoring

PURPOSE

Monitoring is a fundamental part of the training process to guarantee that the programmed training loads are executed by athletes and result in the intended adaptations and enhanced performance. A number of monitoring tools have emerged during the last century in sport. These tools capture different facets (eg, psychophysiological, physical, biomechanical) of acute training bouts and chronic adaptations while presenting specific advantages and limitations. Therefore, there is a need to identify what tools are more efficient in each sport context for better monitoring of training process.

METHODS AND RESULTS

We present and discuss the fine-tuning approach for training monitoring, which consists of identifying and combining the best monitoring tools with experts' knowledge in different sport settings, designed to improve (1) the control of actual training loads and (2) understanding of athletes' training adaptations. Instead of using single-tool approaches or merely subjective decision making, the identification of the best combination of monitoring tools to assist experts' decisions in each specific context (ie, triangulation) is necessary to better understand the link between acute and chronic adaptations and their impact on health and performance. Future studies should elaborate on the identification of the best combination of monitoring tools for each specific sport setting.

CONCLUSION

The fine-tuning monitoring approach requires the simultaneous use of several valid and practical tools, instead of a single tool, to improve the effectiveness of monitoring practices when added to experts' knowledge.

Prescription of High-intensity Aerobic Interval Training Based on Oxygen Uptake Kinetics

Endurance training results in diverse adaptations that lead to increased performance and health benefits. A commonly measured training response is the analysis of oxygen uptake kinetics, representing the demand of a determined load (speed/work) on the cardiovascular, respiratory, and metabolic systems, providing useful information for the prescription of constant load or interval-type aerobic exercise. There is evidence that during high-intensity aerobic exercise some interventions prescribe brief interval times (<1-min), which may lead to a dissociation between the load prescribed and the oxygen uptake demanded, potentially affecting training outcomes. Therefore, this review explored the time to achieve a close association between the speed/work prescribed and the oxygen uptake demanded after the onset of high-intensity aerobic exercise. The evidence assessed revealed that at least 80% of the oxygen uptake amplitude is reached when phase II of oxygen uptake kinetics is completed (1 to 2 minutes after the onset of exercise, depending on the training status). We propose that the minimum work-time during high-intensity aerobic interval training sessions should be at least 1 minute for athletes and 2 minutes for non-athletes. This suggestion could be used by coaches, physical trainers, clinicians and sports or health scientists for the prescription of high-intensity aerobic interval training.

A quadriceps femoris motor pattern for efficient cycling

In cycling, propulsion is generated by the muscles of the lower limbs and hips. After the first reports of pedal/crank force measurements in the late 1960s, it has been assumed that highly trained athletes have better power transfer to the pedals than recreational cyclists. However, motor patterns indicating higher levels of performance are unknown. To compare leg muscle activation between trained (3.5-4.2 W/kgbw) and highly trained (4.3-5.1 W/kgbw) athletes we applied electromyography, lactate, and bi-pedal/crank force measurements during a maximal power test, an individual lactate threshold test and a constant power test. We show that specific activation patterns of the rectus femoris (RF) and vastus lateralis (VL) impact on individual performance during high-intensity cycling. In highly trained cyclists, we found a strong activation of the RF during hip flexion. This results in reduced negative force in the fourth quadrant of the pedal cycle. Furthermore, we discovered that pre-activation of the RF during hip flexion reduces force loss at the top dead center (TDC) and can improve force development during subsequent leg extension. Finally, we found that a higher performance level is associated with earlier and more intense coactivation of the RF and VL. This quadriceps femoris recruitment pattern improves force transmission and maintains propulsion at the TDC of the pedal cycle. Our results demonstrate neuromuscular adaptations in cycling that can be utilized to optimize training interventions in sports and rehabilitation.

Biomarker Changes in Oxygen Metabolism, Acid-Base Status, and Performance after the Off-Season in Well-Trained Cyclists

During the off-season, cyclists reduce their volume and intensity of training in order to recover the body from the high workload during the competitive season. Some studies have examined the effects of the off-season on cardiovascular, metabolic, and performance levels but have not evaluated oxygen metabolism, acid-base status, and electrolytes in cyclists. Therefore, our main objective was to analyze these markers in the off-season period (8 weeks) via finger capillary blood gasometry in well-trained cyclists. We found an increase in oxygen saturation (sO2) and oxyhemoglobin (O2Hb) (p ≤ 0.05) and a decrease in fat oxidation at maximum fat oxidation (FatMax) (p ≤ 0.05). In addition, we observed a decreasing trend of VO2 in the ventilatory threshold 2 (VT2) and maximum oxygen consumption (VO2MAX) (p ≤ 0.06) after the off-season in well-trained cyclists. Negative correlations were found between the pre-post off-season differences in the VO2 at ΔFatMax and ΔHCO3- (bicarbonate ion) and between power generated at the ΔeFTP (functional power threshold) and the ΔVO2MAX with the pH (r ≥ -0.446; p ≤ 0.05). After the off-season period, well-trained cyclists had increased markers of oxygen metabolism, decreased fat oxidation at low exercise intensities, and decreased VO2 at the VT2 and VO2MAX. Relationships were found between changes in the ΔeFTP and VO2MAX with changes in the pH and between the pH and HCO3- with changes in La-.

Characteristics of Pacing Strategies among Elite Cross-Country Skiers According to Final Rank

The purpose of this study is to explore differences in pacing strategies between successful and less successful male elite cross-country skiers during a 15 km interval-start race involving different techniques. The final rank, split times and final times were extracted individually for the top 100 finishers in the 15 km individual time trial races from the Norwegian national season opener races over two years. The same course was used in all the competitions. The athletes were divided into four groups according to final rank: Q1: 1st–25th; Q2: 26th–50th; Q3: 51st–75th; Q4: 76th–100th. The relative change in speed was used for the time spent on lap 1, to an average for laps 2 and 3. Significant correlation between placement and speed reduction after the first lap was found in three out of four races. In Race 2 (skating), both Q1 and Q2 had lower speed decreases between laps than Q4 did. In year 2, both races (classical and skating) had lower speed reduction between laps for the first quartile compared to that of the last. Overall, this study shows that lower-level cross-country skiers started out relatively faster in the first lap and achieved a greater reduction in speed in the subsequent laps when compared to their faster opponents.

Aerodynamic analysis of uphill drafting in cycling

Some teams aiming for victory in a mountain stage in cycling take control in the uphill sections of the stage. While drafting, the team imposes a high speed at the front of the peloton defending their team leader from opponent’s attacks. Drafting is a well-known strategy on flat or descending sections and has been studied before in this context. However, there are no systematic and extensive studies in the scientific literature on the aerodynamic effect of uphill drafting. Some studies even suggested that for gradients above 7.2% the speeds drop to 17 km/h and the air resistance can be neglected. In this paper, uphill drafting is analyzed and quantified by means of drag reductions and power reductions obtained by computational fluid dynamics simulations validated with wind tunnel measurements. It is shown that even for gradients above 7.2%, drafting can yield substantial benefits. Drafting allows cyclists to save over 7% of power on a slope of 7.5% at a speed of 6 m/s. At a speed of 8 m/s, this reduction can exceed 16%. Sensitivity analyses indicate that significant power savings can be achieved, also with varying bicycle, cyclist, road and environmental characteristics.

A Model for World-Class 10,000 m Running Performances: Strategy and Optimization

The distribution of energetic resources in world-class distance running is a key aspect of performance, with athletes relying on aerobic and anaerobic metabolism to greater extents during different parts of the race. The purpose of this study is to model 10,000 m championship performances to enable a deeper understanding of the factors affecting running speed and, given that more than half the race is run on curves, to establish the effect of the bends on performance. Because a limitation of time split data is that they are typically averaged over 100-m or 1,000-m segments, we simulate two 10,000 m runners' performances and thus get access to their instantaneous speed, propulsive force and anaerobic energy. The numerical simulations provide information on the factors that affect performance, and we precisely see the effect of parameters that influence race strategy, fatigue, and the ability to speed up and deal with bends. In particular, a lower anaerobic capacity leads to an inability to accelerate at the end of the race, and which can accrue because of a reliance on anaerobic energy to maintain pace in an athlete of inferior running economy. We also see that a runner with a worse running economy is less able to speed up on the straights and that, in general, the bends are run slower than the straights, most likely because bend running at the same pace would increase energy expenditure. Notwithstanding a recommendation for adopting the accepted practices of improving aerobic and anaerobic metabolism through appropriate training methods, coaches are advised to note that athletes who avoid mid-race surges can improve their endspurt, which are the differentiating element in closely contested championship races.

Successful Pacing Profiles of Olympic Men and Women 3,000 m Steeplechasers

The presence of barriers in the steeplechase increases energy cost and makes successful pacing more difficult. This was the first study to analyze pacing profiles of successful (qualifiers for the final/Top 8 finalists) and unsuccessful (non-qualifiers/non-Top 8 finalists) Olympic steeplechasers across heats and finals, and to analyze differences between race sections (e.g., water jump vs. home straight). Finishing and section splits were collected for 77 men and 84 women competing at the 2008 and 2016 Olympic Games. Competitors were divided into groups based on finishing position (in both rounds analyzed). After a quick opening 228 m (no barriers), men who qualified for the final or finished in the Top 8 in the final had even paces for the first half with successive increases in speed in the last three laps; unsuccessful pacing profiles were more even. Successful women had mostly even paces for the whole race, and less successful athletes slowed after Lap 2. Women started the race relatively quicker than men, resulting in slower second half speeds. The best men completed most race sections at the same speed, but less successful men were slower during the water jump section, suggesting less technically proficiency. Similarly, women were slower during this section, possibly because its landing dimensions are the same as for men and have a greater effect on running speed. Coaches should note the different pacing profiles adopted by successful men and women steeplechasers, and the importance of technical hurdling skills at the water jump.

Self-Selected Pacing during a 24 h Track Cycling World Record

The present case study analyzed the pacing in a self-paced world record attempt during a 24 h track cycling event by the current world record holder. The cyclist completed 3767 laps on a 250 m long cycling track and covered a total distance of 941.873 km, breaking the existing world record by 37.99 km. The average cycling speed was 39.2 ± 1.9 km/h (range 35.5–42.8 km/h) and the power output measured was 214.5 ± 23.7 W (range 190.0–266.0 W) during the 24 h of cycling. We found a positive pacing result with negative correlations between cycling speed (r = −0.73, p < 0.001), power output (r = −0.66, p < 0.001), and laps per hour (r = −0.73, p < 0.001) and the covered distance. During the 24 h, we could identify four different phases: the first phase lasting from the start till the fourth hour with a relatively stable speed; the second phase from the fourth till the ninth hour, characterized by the largest decrease in cycling speed; the third phase from the ninth hour till the 22nd hour, showing relatively small changes in cycling speed; and the last phase from the 22nd hour till the end, presenting a final end spurt. The performance in the 24 h track cycling was 45.577 km better than in the 24 h road cycling, where the same athlete cycled slower but with higher power output. In summary, the current world-best ultracyclist covered more kilometers with less power output during the world record 24 h track cycling than during his world record 24 h road cycling. This was most probably due to the more favorable environmental conditions in the velodrome, which has no wind and stable temperatures.

Case Studies in Physiology: Temporal changes in determinants of aerobic performance in individual going from alpine skier to world junior champion time trial cyclist

This paper reports temporal changes in physiological measurements of exercise performance in a young man transitioning from alpine skiing until he became a world junior champion time trial cyclist after only 3 yr of bike-specific training. At the time he became World Champion he also achieved among the highest reported maximal oxygen uptake (V̇o_2max) value, 96.7 ml·min^-1·kg^-1, or 7,397 ml/min in absolute terms at 76.5 kg, which had increased by 29.6% from 74.6 ml·min^-1·kg^-1 pre-bike-specific training. After 15 mo with almost no structured exercise training, V̇o_2max returned to 77.0 mL·min^-1·kg^-1 and was similar to the value reported before specific bike training, albeit with absolute term (6,205 ml/min) still being 11.3% higher. Part of the explanation for his athletic achievements is likely also related to the up to 20.9% improvement in Power@4 mmol/l (W). Although genetic profiles of endurance athletes have not generated data suggesting a shared genetic signature associated with elite endurance performance, this case study highlights the importance of intrinsic biological factors in elite endurance performance.NEW & NOTEWORTHY This study shows that very high V̇o_2max values (>70 ml·min^-1·kg^-1) can be found in individuals not previously specializing in aerobic training and that values of >90 ml·min^-1·kg^-1, as well as a cycling world junior champion title, can be achieved in such individuals with just 3 yr of dedicated exercise training.

Similarities and Differences in Pacing Patterns in a 161-km and 101-km Ultra-Distance Road Race

Tan, PLS, Tan, FHY, and Bosch, AN. Similarities and differences in pacing patterns in a 161-km and 101-km ultra-distance road race. J Strength Cond Res 30(8): 2145-2155, 2016-The purpose of this study was to establish and compare the pacing patterns of fast and slow finishers in a tropical ultra-marathon. Data were collected from the Craze Ultra-marathon held on the 22nd and 21st of September in 2012 and 2013, respectively. Finishers of the 161-km (N = 47) and 101-km (N = 120) categories of the race were divided into thirds (groups A-C) by merit of finishing time. Altogether, 17 and 11 split times were recorded for the 161-km and 101-km finishers, respectively, and used to calculate the mean running speed for each distance segment. Running speed for the first segment was normalized to 100, with all subsequent splits adjusted accordingly. Running speed during the last 5 km was calculated against the mean race pace to establish the existence of an end spurt. A reverse J-shaped pacing profile was demonstrated in all groups for both distance categories and only 38% of the finishers executed an end spurt. In the 101-km category, in comparison with groups B and C, group A maintained a significantly more even pace (p = 0.013 and 0.001, respectively) and completed the race at a significantly higher percent of initial starting speed (p = 0.001 and 0.001, respectively). Descriptive data also revealed that the top 5 finishers displayed a "herd-behavior" by staying close to the lead runner in the initial portion of the race. These findings demonstrate that to achieve a more even pace, recreational ultra-runners should adopt a patient sustainable starting speed, with less competitive runners setting realistic performance goals whereas competitive runners with a specific time goal to consider running in packs of similar pace.

Lack of concordance amongst measurements of individual anaerobic threshold and maximal lactate steady state on a cycle ergometer

INTRODUCTION

The calculation of exertion intensity, in which a change is produced in the metabolic processes which provide the energy to maintain physical work, has been defined as the anaerobic threshold (AT). The direct calculation of maximal lactate steady state (MLSS) would require exertion intensities over a long period of time and with sufficient rest periods which would prove significantly difficult for daily practice. Many protocols have been used for the indirect calculation of MLSS.

OBJECTIVES

The aim of this study is to determine if the results of measurements with 12 different AT calculation methods and calculation software [Keul, Simon, Stegmann, Bunc, Dickhuth (TKM and WLa), Dmax, Freiburg, Geiger-Hille, Log-Log, Lactate Minimum] can be used interchangeably, including the method of the fixed threshold of Mader/OBLA's 4 mmol/l and then to compare them with the direct measurement of MLSS.

METHODS

There were two parts to this research. Phase 1: results from 162 exertion tests chosen at random from the 1560 tests. Phase 2: sixteen athletes (n = 16) carried out different tests on five consecutive days.

RESULTS

There was very high concordance among all the methods [intraclass correlation coefficient (ICC) > 0.90], except Log-Log in relation to the Stegamnn, Dmax, Dickhuth-WLa and Geiger-Hille. The Dickhuth-TKM showed a high tendency towards concordance, with Dmax (2.2 W) and Dickhuth-WLa (0.1 W). The Dickhuth-TKM method presented a high tendency to concordance with Dickhuth-WLa (0.5 W), Freiburg (7.4 W), MLSS (2.0 W), Bunc (8.9 W), Dmax (0.1 W). The calculation of MLSS power showed a high tendency to concordance, with Dickhuth-TKM (2 W), Dmax (2.1 W), Dickhuth-WLa (1.5 W).

CONCLUSION

The fixed threshold of 4 mmol/l or OBLA produces slightly different and higher results than those obtained with all the methods analyzed, including MLSS, meaning an overestimation of power in the individual anaerobic threshold. The Dickhuth-TKM, Dmax and Dickhuth-WLa methods defined a high concordance on a cycle ergometer. Dickhuth-TKM, Dmax, Dickhuth-WLa described a high concordance with the power calculated to know the MLSS.

The analysis and forecasting of male cycling time trial records established within England and Wales

The format of cycling time trials in England, Wales and Northern Ireland, involves riders competing individually over several fixed race distances of 10-100 miles in length and using time constrained formats of 12 and 24 h in duration. Drawing on data provided by the national governing body that covers the regions of England and Wales, an analysis of six male competition record progressions was undertaken to illustrate its progression. Future forecasts are then projected through use of the Singular Spectrum Analysis technique. This method has not been applied to sport-based time series data before. All six records have seen a progressive improvement and are non-linear in nature. Five records saw their highest level of record change during the 1950-1969 period. Whilst new record frequency generally has reduced since this period, the magnitude of performance improvement has generally increased. The Singular Spectrum Analysis technique successfully provided forecasted projections in the short to medium term with a high level of fit to the time series data.

Pacing profiles and pack running at the IAAF World Half Marathon Championships

The aim of this study was to describe the pacing profiles and packing behaviour of athletes competing in the IAAF World Half Marathon Championships. Finishing and split times were collated for 491 men and 347 women across six championships. The mean speeds for each intermediate 5 km and end 1.1 km segments were calculated, and athletes grouped according to finishing time. The best men and women largely maintained their split speeds between 5 km and 15 km, whereas slower athletes had decreased speeds from 5 km onwards. Athletes were also classified by the type of packing behaviour in which they engaged. Those who ran in packs throughout the race had smaller decreases in pace than those who did not, or who managed to do so only to 5 km. While some athletes' reduced speeds from 15 to 20 km might have been caused by fatigue, it was also possibly a tactic to aid a fast finish that was particularly beneficial to medallists. Those athletes who ran with the same competitors throughout sped up most during the finish. Athletes are advised to identify rivals likely to have similar abilities and ambitions and run with them as part of their pre-race strategy.

Factors influencing pacing in triathlon

Triathlon is a multisport event consisting of sequential swim, cycle, and run disciplines performed over a variety of distances. This complex and unique sport requires athletes to appropriately distribute their speed or energy expenditure (ie, pacing) within each discipline as well as over the entire event. As with most physical activity, the regulation of pacing in triathlon may be influenced by a multitude of intrinsic and extrinsic factors. The majority of current research focuses mainly on the Olympic distance, whilst much less literature is available on other triathlon distances such as the sprint, half-Ironman, and Ironman distances. Furthermore, little is understood regarding the specific physiological, environmental, and interdisciplinary effects on pacing. Therefore, this article discusses the pacing strategies observed in triathlon across different distances, and elucidates the possible factors influencing pacing within the three specific disciplines of a triathlon.

Erythropoietin doping in cycling: lack of evidence for efficacy and a negative risk-benefit

Imagine a medicine that is expected to have very limited effects based upon knowledge of its pharmacology and (patho)physiology and that is studied in the wrong population, with low-quality studies that use a surrogate end-point that relates to the clinical end-point in a partial manner at most. Such a medicine would surely not be recommended. The use of recombinant human erythropoietin (rHuEPO) to enhance performance in cycling is very common. A qualitative systematic review of the available literature was performed to examine the evidence for the ergogenic properties of this drug, which is normally used to treat anaemia in chronic renal failure patients. The results of this literature search show that there is no scientific basis from which to conclude that rHuEPO has performance-enhancing properties in elite cyclists. The reported studies have many shortcomings regarding translation of the results to professional cycling endurance performance. Additionally, the possibly harmful side-effects have not been adequately researched for this population but appear to be worrying, at least. The use of rHuEPO in cycling is rife but scientifically unsupported by evidence, and its use in sports is medical malpractice. What its use would have been, if the involved team physicians had been trained in clinical pharmacology and had investigated this properly, remains a matter of speculation. A single well-controlled trial in athletes in real-life circumstances would give a better indication of the real advantages and risk factors of rHuEPO use, but it would be an oversimplification to suggest that this would eradicate its use.

Performance analysis of a world-class sprinter during cycling grand tours

This investigation describes the sprint performances of the highest internationally ranked professional male road sprint cyclist during the 2008-2011 Grand Tours. Sprint stages were classified as won, lost, or dropped from the front bunch before the sprint. Thirty-one stages were video-analyzed for average speed of the last km, sprint duration, position in the bunch, and number of teammates at 60, 30, and 15 s remaining. Race distance, total elevation gain (TEG), and average speed of 45 stages were determined. Head-to-head performances against the 2nd-5th most successful professional sprint cyclists were also reviewed. In the 52 Grand Tour sprint stages the subject started, he won 30 (58%), lost 15 (29%), was dropped in 6 (12%), and had 1 crash. Position in the bunch was closer to the front and the number of team members was significantly higher in won than in lost at 60, 30, and 15 s remaining (P < .05). The sprint duration was not different between won and lost (11.3 ± 1.7 and 10.4 ± 3.2 s). TEG was significantly higher in dropped (1089 ± 465 m) than in won and lost (574 ± 394 and 601 ± 423 m, P < .05). The ability to finish the race with the front bunch was lower (77%) than that of other successful sprinters (89%). However, the subject was highly successful, winning over 60% of contested stages, while his competitors won less than 15%. This investigation explores methodology that can be used to describe important aspects of road sprint cycling and supports the concept that tactical aspects of sprinting can relate to performance outcomes.

The Tour de France: An Updated Physiological Review

From its initial inception in 1903 as a race premised on a publicity stunt to sell newspapers, the Tour de France had grown and evolved over time to become one of the most difficult and heralded sporting events in the world. Though sporting science and the Tour paralleled each other, it was not until the midlate 1980s, and especially the midlate 1990s (with the use of heart-rate monitors) that the 2 began to unify and grow together. The purpose of this brief review is to summarize what is currently known of the physiological demands of the Tour de France, as well as of the main physiological profile of Tour de France competitors.

The cycling physiology of Miguel Indurain 14 years after retirement

Age-related fitness declines in athletes can be due to both aging and detraining. Very little is known about the physiological and performance decline of professional cyclists after retirement from competition. To gain some insight into the aging and detraining process of elite cyclists, 5-time Tour de France winner and Olympic Champion Miguel Indurain performed a progressive cycle-ergometer test to exhaustion 14 y after retirement from professional cycling (age 46 y, body mass 92.2 kg). His maximal values were oxygen uptake 5.29 L/min (57.4 mL · kg-1 · min-1), aerobic power output 450 W (4.88 W/kg), heart rate 191 beats/min, blood lactate 11.2 mM. Values at the individual lactate threshold (ILT): 4.28 L/min (46.4 mL · kg-1 · min-1), 329 W (3.57 W/kg), 159 beats/min, 2.4 mM. Values at the 4-mM onset of blood lactate accumulation (OBLA): 4.68 L/min (50.8 mL · kg-1 · min-1), 369 W (4.00 W/kg), 170 beats/min. Average cycling gross efficiency between 100 and 350 W was 20.1%, with a peak value of 22.3% at 350 W. Delta efficiency was 27.04%. Absolute maximal oxygen uptake and aerobic power output declined by 12.4% and 15.2% per decade, whereas power output at ILT and OBLA declined by 19.8% and 19.2%. Larger declines in maximal and submaximal values relative to body mass (19.4-26.1%) indicate that body composition changed more than aerobic characteristics. Nevertheless, Indurain's absolute maximal and submaximal oxygen uptake and power output still compare favorably with those exhibited by active professional cyclists.

Even between-lap pacing despite high within-lap variation during mountain biking

PURPOSE

Given the paucity of research on pacing strategies during competitive events, this study examined changes in dynamic high-resolution performance parameters to analyze pacing profiles during a multiple-lap mountain-bike race over variable terrain.

METHODS

A global-positioning-system (GPS) unit (Garmin, Edge 305, USA) recorded velocity (m/s), distance (m), elevation (m), and heart rate at 1 Hz from 6 mountain-bike riders (mean±SD age=27.2±5.0 y, stature=176.8±8.1 cm, mass=76.3±11.7 kg, VO2max=55.1±6.0 mL·kg(-1)·min1) competing in a multilap race. Lap-by-lap (interlap) pacing was analyzed using a 1-way ANOVA for mean time and mean velocity. Velocity data were averaged every 100 m and plotted against race distance and elevation to observe the presence of intralap variation.

RESULTS

There was no significant difference in lap times (P=.99) or lap velocity (P=.65) across the 5 laps. Within each lap, a high degree of oscillation in velocity was observed, which broadly reflected changes in terrain, but high-resolution data demonstrated additional nonmonotonic variation not related to terrain.

CONCLUSION

Participants adopted an even pace strategy across the 5 laps despite rapid adjustments in velocity during each lap. While topographical and technical variations of the course accounted for some of the variability in velocity, the additional rapid adjustments in velocity may be associated with dynamic regulation of self-paced exercise.

Age, sex, and finish time as determinants of pacing in the marathon

Previous researchers have suggested that faster marathoners tend to run at a more consistent pace compared with slower runners. None has examined the influence of sex and age on pacing. Therefore, the purpose of this study was to determine the simultaneous influences of age, sex, and run time on marathon pacing. Pacing was defined as the mean velocity of the last 9.7 km divided by that of the first 32.5 km (closer to 1.0 indicates better pacing). Subjects were 186 men and 133 women marathoners from the 2005, 2006, and 2007 races of a midwestern U.S. marathon. The course was a 1.6 km (1 mile) loop with pace markers throughout, thus facilitating pacing strategy. Each 1.6-km split time was measured electronically by way of shoe chip. The ambient temperature (never above 5°C) ensured that hyperthermia, a condition known to substantially slow marathon times and affect pacing, was not likely a factor. Multiple regression analysis indicated that age, sex, and run time (p < 0.01 for each) were simultaneously independent determinants of pacing. The lack of any 2- or 3-way interactions (p > 0.05 for each) suggests that the effects of 1 independent variable is not dependent upon the levels of others. We conclude that older, women, and faster are better pacers than younger, men, and slower marathoners, respectively. Coaches can use these findings to overcome such tendencies and increase the odds of more optimal pacing.

Moderate association of anthropometry, but not training volume, with race performance in male ultraendurance cyclists

In 28 male Caucasian nonprofessional ultracyclists, we investigated whether anthropometry or training volume had an influence on race speed in the 600 km at the Swiss Cycling Marathon 2007. Anthropometric parameters (age, body mass, body height, skinfold thicknesses) were determined before the race to calculate body mass index and percent body fat. In addition, participants, using a training diary, recorded their training volume in hours and kilometers in the 3 months before the race. The influence of anthropometry and training volume on speed in the race as the dependent variable was investigated in a multiple linear regression model. Anthropometry showed a moderate association with speed in the race (r2 = .178, p < .05), whereas training volume showed no association (r2 = .000, p > .05). We concluded that anthropometry had a greater influence on race performance than training volume in recreational ultraendurance cyclists.

Adaptation of pedaling rate of professional cyclist in mountain passes

The aim of this study was to analyze the pedaling rate (PR) adopted by professional cyclists in different mountain passes. PR, heart rate (HR), velocity and power to overcome gravity were monitored during special (HM), 1st (M1), 2nd (M2) and 3rd (M3) category mountain passes. HM and M1 within high-mountain stages were classified into mountain passes before the final mountain pass of the stage (M-BF) and mountain passes placed in the final of the stage (M-F). PR was significantly higher (P < 0.05) in M3 (82 +/- 1 rpm) than that in M2 (75 +/- 3 rpm), M1 (75 +/- 2 rpm) and HM (73 +/- 1 rpm). Velocity and power output decreased in the following order: M3, M2, M1 and HM. Also, greater values (P < 0.05) were observed in M-BF (24.1 +/- 0.8 km h(-1) and 308.5 +/- 10.4 W) and in M-F (17.6 +/- 0.9 km h(-1) and 270.1 +/- 9.9 W). In addition, PR was higher (P < 0.05) in M-BF (79 +/- 2 rpm) than that in M-F (73 +/- 1 rpm). In conclusion, PR was modified according to the characteristics and the race strategies adopted by the cyclists, thus the cyclists chose higher PR to improve their performance.

Comparison of different theoretical models estimating peak power output and maximal oxygen uptake in trained and elite triathletes and endurance cyclists in the velodrome

The aim of this study was to assess which of the equations that estimate peak power output and maximal oxygen uptake (VO2max) in the velodrome adapt best to the measurements made by reference systems. Thirty-four endurance cyclists and triathletes performed one incremental test in the laboratory and two tests in the velodrome. Maximal oxygen uptake and peak power output were measured with an indirect calorimetry system in the laboratory and with the SRM training system in the velodrome. The peak power output and VO2max of the field test were estimated by means of different equations. The agreement between the estimated and the reference values was assessed with the Bland-Altman method. The equation of Olds et al. (1995) showed the best agreement with respect to the peak power output reference values, and that of McCole et al. (1990) was the only equation to show good agreement with respect to the VO2max reference values. The VO2max values showed a higher coefficient of determination with respect to maximal aerobic speed when they were expressed in relative terms. In conclusion, the equations of Olds et al. (1995) and McCole et al. (1990) were best at estimating peak power output and VO2max in the velodrome, respectively.

Aerodynamic Characteristics as Determinants of the Drafting Effect in Cycling

PURPOSE

To determine whether cyclists' individual aerodynamic characteristics influence the magnitude of the drafting effect in cycling.

METHODS

Thirteen competitive male cyclists performed two field protocols (individual and drafting). Hub-based power meters were used to measure power output and velocity, from which drag area (Ad) was calculated. The three subjects obtaining maximum (MAX), intermediate (INT), and minimum (MIN) values for Ad during the individual protocol acted as leaders during the drafting protocol. Measures of Ad were then made while subjects drafted each of the three leaders. The drafting effect was specifically quantified as the decrement on measured drag coefficient (Cd) and power output.

RESULTS

The mean drafting effect increased with leader Ad (DeltaCd: MIN = 35.55%, INT = 41.31%, MAX = 50.47%; Delta power: MIN = 111.1 W, INT = 124.05 W, MAX = 159.23 W; P < 0.0001). Regressions between leader Ad and drafting effect for individual drafters indicated substantial interdrafter variability (slope ranged from 29.4 to 190.5%.m) but little intradrafter variability (mean r = 0.9689), suggesting an interaction between leader and drafter. Correlating leader:drafter ratios for Ad, Ap, and body mass to the drafting effect supported this interaction (r = 0.69-0.78, P < 0.01), but only when data for all three groups were pooled.

CONCLUSIONS

Alteration of leader Ad elicits a linear increase in the drafting effect. However, the Ad of the leader does not explain all of the interdrafter variability in the drafting effect, which is specific to the drafting subject but is minimally explained by their aerodynamic characteristics. This interdrafter variability may be attributable to the drafter's skill in obtaining maximum benefit from drafting.

Gene expression in working skeletal muscle

A number of molecular tools enable us to study the mechanisms of muscle plasticity. Ideally, this research is conducted in view of the structural and functional consequences of the exercise-induced changes in gene expression. Muscle cells are able to detect mechanical, metabolic, neuronal and hormonal signals which are transduced over multiple pathways to the muscle genome. Exercise activates many signaling cascades--the individual characteristic of the stress leading to a specific response of a network of signaling pathways. Signaling typically results in the transcription of multiple early genes among those of the well known for and jun family, as well as many other transcription factors. These bind to the promoter regions of downstream genes initiating the structural response of muscle tissue. While signaling is a matter of minutes, early genes are activated over hours leading to a second wave of transcript adjustments of structure genes that can then be effective over days. Repeated exercise sessions thus lead to a concerted accretion of mRNAs which upon translation results in a corresponding protein accretion. On the structural level, the protein accretion manifests itself for instance as an increase in mitochondrial volume upon endurance training or an increase in myofibrillar proteins upon strength training. A single exercise stimulus carries a molecular signature which is typical both for the type of stimulus (i.e. endurance vs. strength) as well as the actual condition of muscle tissue (i.e. untrained vs. trained). Likewise, it is clearly possible to distinguish a molecular signature of an expressional adaptation when hypoxic stress is added to a regular endurance exercise protocol in well-trained endurance athletes. It therefore seems feasible to use molecular tools to judge the properties of an exercise stimulus much earlier and at a finer level than is possible with conventional functional or structural techniques.