The influence of performance level, age and gender on pacing strategy during a 100-km ultramarathon

Pacing analysis and comparison of TOP-10 and NOT TOP-10 Ultra Trail Cape Town 100-km finishers

BACKGROUND

Pacing strategies during endurance efforts vary depending on athlete experience, race length, and terrain. In ultramarathon trail running the specific race route profile can have a significant impact on optimal pacing strategy. The aim of this study was to determine the relationship between uphill, downhill and level running with overall performance and to compare the difference in pacing strategies between top 10 (TOP-10) and non-top 10 (NOT TOP-10) finishers of a 100-km ultra-trail marathon with +5000-m elevation gain.

METHODS

Fifty male finishers (TOP-10: N.=6, NOT TOP-10, N.=44) and forty-six individual segments (1.5±1.2 km) were analyzed based on 2021 100-km UTCT STRAVA data. Relative segment speed and CV% were used to identify pacing strategies. Spearman Rank and Mann-Whitney U Tests were used to analyze the data. Significance was set at P<0.05.

RESULTS

Uphill running had the strongest relationship with overall performance (r=0.826, P<0.01). Substantially weaker relationships between overall running performance and level (r=0.402, P<0.01) and downhill (r=-0.382, P<0.01) running performance were found. The CV% was significantly lower in TOP-10 (32.10±1.81) than NOT TOP-10 (35.39±4.43) (U=24, r=0.46, P<0.01).

CONCLUSIONS

Uphill running performance remains a valuable measure of overall trail running performance as it represents a higher percentage of overall running demand. TOP-10 runners have diminished decay in initial running speed than NOT TOP-10 runners, despite a generally high variation in pace and net positive split in ultra-trail running.

Pacing strategies in marathons: A systematic review

Background

The pacing strategy embodies the tactical behavior of athletes in distributing their energy across different segments of a race; therefore, a quantitative analysis of pacing strategies in marathon races could deepen the understanding of both pacing behavior and physical capacity in marathon athletics.

Objective

The objective of this systematic review was to synthesize and characterize pacing strategies in marathon road races by exploring the categories of pacing strategies and the factors that influence these strategies during marathon events.

Methods

Preferred Reporting Items for Systematic Reviews guidelines were followed for systematic searches, appraisals, and syntheses of literature on this topic. Electronic databases such as Science Direct, SPORTDiscuss, PubMed, and Web of Science were searched up to July 2024. Records were eligible if they included pace performance measurements during competition, without experimental intervention that may influence their pace, in healthy, adult athletes at any level.

Results

A total of 39 studies were included in the review. Twenty-nine were observational studies, and 10 were experimental (randomized controlled trials). The assessment of article quality revealed an overall median NOS score of 8 (range 5-9). The included studies examined the pacing profiles of master athletes and finishers in half-marathon (n = 7, plus numbers compared to full marathon), full-marathon (n = 21), and ultramarathon (n = 11) road races. Considering that some studies refer to multiple pacing strategies, in general, 5 studies (∼13 %) reported even pacing, 3 (∼8 %) reported parabolic pacing, 7 (∼18 %) reported negative pacing, and 30 (∼77 %) reported positive pacing during marathon competitions. Gender, age, performance, pack, and physiological and psychological factors influence pacing strategies.

Conclusion

This study synthesized pacing performance in marathons and highlighted the significance of examining pacing strategies in these events, offering valuable insights for coaches and athletes. Several key findings were highlighted: (1) pacing profiles and pacing ranges were identified as the primary indicators of pacing strategies; (2) the pacing strategy was found to be dynamic, with the most substantial effects attributed to gender and distance; and (3) three distinct types of pacing strategies for marathons were classified: positive, negative, and even pacing. These findings advance the understanding of marathon pacing strategies by shedding light on the factors that influence athletes' pacing decisions and behaviors. Additionally, these findings offer practical benefits, aiding athletes in making well-informed tactical choices and developing effective pace plans to enhance marathon performance. However, due to the complex nature of marathon racing, further research is required to explore additional factors that might impact pacing strategies. A better grasp of optimal pacing strategies will foster progress in this area and serve as a basis for future research and advancements.

Pacing Variation in Multistage Ultramarathons: Internet-Based Cross-Sectional Study

BACKGROUND

Ultramarathon running is the most popular ultraendurance competition in terms of the number of races and runners competing annually worldwide; however, no study has compared pacing and performance over a long period.

OBJECTIVE

This study analyzes the pacing of successful finishers and nonfinishers in multistage ultramarathons worldwide.

METHODS

A total of 4079 athletes (men=3288; women=791) competing in 99 multistage ultramarathon events from 1983 to 2021 were analyzed, including the number of participants, age, gender, rank, and running speed of successful finishers.

RESULTS

The results showed a significant increase in the number of events (n=338) and a significant increase in the number of finishers and nonfinishers (n=5575) in the ultramarathons worldwide during this period. The general linear models (GLMs) of pacing variation showed nonsignificant effects for gender (F1,36.2=2.5; P=.127; ηp2=0.063) and age group (F10,10=0.6; P=.798; ηp2=0.367), but it showed a significant interaction (gender × age) effect (F10,2689=2.3; P=.008; ηp2=0.009). Post hoc analyses showed that men have a higher pacing variation than women in the under 30 years (U30), U35, U45, and U50 groups. Additionally, the fastest women's age group (U35) had the lowest pacing variation. The GLM of pacing variation by gender and event distance showed significant effects for both gender (F1,3=18.5; P<.001; ηp2=0.007) and distance (F2,3=20.1; P<.001; ηp2=0.015). Post hoc analyses showed a growing pacing variation with increasing race distance for both men and women. In addition, men had a higher variation in long events. Furthermore, there was a significant main effect for both genders (F1,3=33.7; P<.001; ηp2=0.012) and rank (F1,3=136.6; P<.001; ηp2=0.048) on performance, with men being faster than women. Pacing varied greatly due to gender (F1,3=4.0; P=.047; ηp2=0.001), with a lower (ie, more even) pacing variation for male athletes in the top 3 finishers. Male nonfinishers showed a higher performance than female nonfinishers (F1,1340=25.6; P<.001), and no difference was identified for pacing variation (F1,789=1.5; P=.228) based on gender. In addition, a weak but significant correlation (r=-0.130; P<.001) was identified between the average running speed and pacing variation for both female and male nonfinishers.

CONCLUSIONS

In summary, multistage ultramarathon competitions showed an increasing number of competitors and a higher performance challenge. Men have a higher pacing (ie, less even) variation than women, especially observed in longer events. A higher pacing variation was associated with lower performance for men, women, and nonfinishers.

Participation and performance trends in short-, medium, and long-distance duathlon

Participation and performance trends of male and female athletes have been thoroughly analyzed in various endurance sports. Knowing these trends can help coaches and athletes prepare for competitions and may influence their training strategy and career planning. However, duathlon events-consisted of two splits of running (Run1 and Run2) interspersed by a split of cycling (Bike)-have not been thoroughly studied, unlike other endurance sports. The present study aimed to compare participation and performance trends in duathletes who competed in duathlon races hosted by World Triathlon or affiliated National Federations between 1990 and 2021. A total of 25,130 results of age group finishers who competed in run-bike-run duathlon races of varying distances were analyzed with different general linear models. Races were divided into three distances: short-distance (up to 5.5 km run, 21 km bike, 5 km run), medium-distance (5-10 km run, 30-42 km bike, 7-11 km run) and long-distance (at least 14 km run, 60 km bike, 25 km run). On average, women represented 45.6% of all finishers in short-distance, 39.6% in medium-distance and 24.9% in long-distance duathlon races. Throughout the years, men were consistently faster than women in all three race legs (Run 1, Bike, and Run 2) in all three distances across all age groups, and women could not reduce the performance gap. Concerning the age of peak performance, duathletes of the age group 30-34 finished most often in the top three in short- and medium-distance duathlons, whereas male duathletes of the age group 25-29 and female duathletes of the age group 30-34 finished most often in the top three in long-distance duathlons. Women participated less, especially in longer distances, and were constantly slower than men. Duathletes of the age group 30-34 finished most often in the top three. Future studies should analyze participation and performance trends in further subgroups (e.g., elite athletes) and pacing behaviours.

Is There Evidence for the Development of Sex-Specific Guidelines for Ultramarathon Coaches and Athletes? A Systematic Review

BACKGROUND

There is evidence of sex differences in the physiology of endurance exercise, yet most of the advice and guidelines on training, racing, nutrition, and recovery for ultramarathons are based on research that has largely excluded female athletes. The objective was therefore to review the current knowledge of sex differences in ultramarathon runners and determine if sufficient evidence exists for providing separate guidelines for males and females.

METHODS

This systematic review was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Three databases were searched for studies investigating differences in elite and recreational male and female ultramarathon runners. Studies were included if they compared males and females and looked at outcomes relating to the performance or health of ultramarathon runners. The quality of the included studies was determined using the Grading of Recommendations Assessment Development and Evaluation (GRADE) approach.

RESULTS

The search strategy identified 45 studies that met the inclusion criteria. Most studies were observational in design, with only three papers based on randomised controlled trials. The overall quality of the evidence was low. Sex differences in the predictors of ultramarathon performance; physiological responses to training, racing, and recovery; chronic and acute health issues; and pacing strategies were found. There were areas with contradictory findings, and very few studies examined specific interventions.

CONCLUSION

The results from this review suggest that the development of sex-specific guidelines for ultramarathon coaches and athletes could have a significant effect on the performance and health of female runners. At present, there is insufficient high-quality evidence on which to formulate these guidelines, and further research is required.

The Effects of Sex, Age and Performance Level on Pacing in Ultra-Marathon Runners in the ‘Spartathlon’

Background

Pacing has been investigated in different kinds of ultra-marathon races, but not in one of the toughest ultra-marathons in the world, the ‘Spartathlon’.

Objective

The aim of the present study was to analyse the pacing of female and male finishers competing in the ‘Spartathlon’ in regards to their age and performance groups.

Methods

A total of 2598 runners (2255 men and 343 women) finishing ‘Spartathlon’ between 2011 and 2019 were analysed. We selected 10 checkpoints with split times corresponding to important race sections. Average running speed was calculated for each participant and the average checkpoint running speed for each of the 10 race checkpoints. Furthermore, to assess the pacing strategy of each runner, the percentage of change in checkpoint speed (CCS) in relation to the average race speed was calculated (for each of 10 checkpoints). Finally, the average change in checkpoint speed (ACCS) was calculated for each participant as a mean of the 10 CCSs.

Results

Both women and men slowed down through the first 7 checkpoints but increased running speed towards the end of the race (reverse J-shaped pacing). Men showed a significantly greater CCS in the first and second checkpoint (p < 0.01 and p < 0.05, respectively), whereas women showed a more significant change in CCS in the last checkpoint (p < 0.05). Furthermore, age and sex showed no effect on ACCS, whereas ACCS differed between the performance groups. In particular, the slowest and the fastest runners showed a more minor change in ACCS than the two medium groups of both men and women (p < 0.01).

Conclusions

In summary, successful finishers in ‘Spartathlon’ showed a reverse J-shaped pacing curve with a decrease in running speed from the start to the 7th checkpoint and an increase in running speed thereafter. This strategy was most probably due to the profile of the race course. Men showed a more significant change in checkpoint speed in the first two checkpoints, whereas women showed a more substantial change in the last checkpoint. Age and sex did not affect average checkpoint speed, whereas this speed was different between the different performance groups. The slowest and the fastest runners showed fewer changes in average checkpoint speed than the two medium groups in men and women.

Downhill Sections Are Crucial for Performance in Trail Running Ultramarathons-A Pacing Strategy Analysis

Trail running is an increasingly popular discipline, especially over long-distance races (>42.195 km). Pacing strategy, i.e., how athletes modulate running speed for managing their energies during a race, appears to have a significant impact on overall performance. The aims of this study were to investigate whether performance level, terrain (i.e., uphill or downhill) and race stage affect pacing strategy and whether any interactions between these factors are evident. Race data from four race courses, with multiple editions (total races = 16), were retrieved from their respective events websites. A linear mixed effect model was applied to the full dataset, as well as to two subgroups of the top 10 male and female finishers, to assess potential differences in pacing strategy (i.e., investigated in terms of relative speed). Better finishers (i.e., athletes ranking in the best positions) tend to run downhill sections at higher relative speeds and uphill sections at lower relative speeds than slower counterparts (p < 0.001). In the later race stages, the relative speed decrease is larger in downhill sections than in uphill ones (p < 0.001) and in downhill sections, slower finishers perform systematically worse than faster ones, but the performance difference (i.e., between slower and faster finishers) becomes significantly larger in the later race stages (p < 0.001). Among elite athletes, no difference in pacing strategy between faster and slower finishers was found (p > 0.05). Both men (p < 0.001) and women (p < 0.001), in the later race stages, slow down more in downhill sections than in uphill ones. Moreover, elite women tend to slow down more than men (p < 0.001) in the later race stages, regardless of the terrain, in contrast to previous studies focusing on road ultramarathons. In conclusion, running downhill sections at higher relative speeds, most likely due to less accentuated fatigue effects, as well as minimizing performance decrease in the later race stages in downhill sections, appears to be a hallmark of the better finishers.

Ultramarathon Evaluation above 180 km in relation to Peak Age and Performance

BACKGROUND

Ultramarathons with distances over 180 km might lead to different results regarding participation, performance, and age compared to shorter runs of 50 and 100 km.

OBJECTIVE

To evaluate ultramarathons with distances above 180 km in relation to runners' peak age and performance.

METHOD

s. Verification of the quantity of competitions in runs over 180 km by continents in the period 2000 to 2020 and evaluation of the individual results of 13,300 athletes after 2010.

RESULTS

Europe stood out with the largest number of organized events, followed by Asia and North America. The age peak performance (PP) in men and women averaged 45 years old with relationship between sex × years (F = 3.612, p < 0.001; η2 = 0.003). Men accounted for more than 80% of the runners and showed a reduction in PP from 2015 onwards (p < 0.001). Competitions between 180 and 240 km were the most frequent, particularly after 2016, surpassing the number of marathons over 360 km (p < 0.001). Men and women showed higher velocity in distances (p < 0.001) from 180 to 240 km when compared to 241 to 300 k m, 301 to 360 km, and >360 km courses.

CONCLUSIONS

The decade between 2010 and 2020 showed an increase in the number of Ultramarathon running events. Europe had the highest number. Women had low participation. Performance progression fell, a fact associated with an increase in the number of participants and not specifically related to a decline in athletic performance over the years.

Sex Differences in Endurance Running

In recent years, there has been a significant expansion in female participation in endurance (road and trail) running. The often reported sex differences in maximal oxygen uptake (VO_2max) are not the only differences between sexes during prolonged running. The aim of this narrative review was thus to discuss sex differences in running biomechanics, economy (both in fatigue and non-fatigue conditions), substrate utilization, muscle tissue characteristics (including ultrastructural muscle damage), neuromuscular fatigue, thermoregulation and pacing strategies. Although males and females do not differ in terms of running economy or endurance (i.e. percentage VO_2max sustained), sex-specificities exist in running biomechanics (e.g. females have greater non-sagittal hip and knee joint motion compared to males) that can be partly explained by anatomical (e.g. wider pelvis, larger femur-tibia angle, shorter lower limb length relative to total height in females) differences. Compared to males, females also show greater proportional area of type I fibres, are more able to use fatty acids and preserve carbohydrates during prolonged exercise, demonstrate a more even pacing strategy and less fatigue following endurance running exercise. These differences confer an advantage to females in ultra-endurance performance, but other factors (e.g. lower O₂ carrying capacity, greater body fat percentage) counterbalance these potential advantages, making females outperforming males a rare exception. The present literature review also highlights the lack of sex comparison in studies investigating running biomechanics in fatigue conditions and during the recovery process.

Could middle- and long-distance running performance of well-trained athletes be best predicted by the same aerobic parameters?

The prediction of running performance at different competitive distances is a challenge, since it can be influenced by several physiological, morphological and biomechanical factors. In experienced male runners heterogeneous for maximal oxygen uptake (VO₂max), endurance running performance can be well predicted by several key parameters of aerobic fitness such as VO₂max and its respective velocity (vVO₂max), running economy, blood lactate response to exercise, oxygen uptake kinetics and critical velocity. However, for a homogeneous group of well-trained endurance runners, the relationship between aerobic fitness parameters and endurance running performance seems to be influenced by the duration of the race (i.e., middle vs. long). Although middle-distance and ultramarathon runners present high aerobic fitness levels, there is no accumulating evidence showing that the aerobic key parameters influence both 800-m and ultramarathon performance in homogeneous group of well-trained runners. The vVO₂max seems to be the best predictor of performance for 1500 m. For 3000 m, both vVO₂max and blood lactate response to exercise are the main predictors of performance. Finally, for long distance events (5000 m, 10,000 m, marathon and ultramarathon), blood lactate response seems to be main predictor of performance. The different limiting/determinants factors and/or training-induced changes in aerobic parameters can help to explain this time- or distance-dependent pattern.

•

Endurance running performance can be well predicted by several key parameters of aerobic fitness.

•

The prediction of running exercise performance is crucial to elaborate the evaluation processes and training prescription.

•

The contribution of key aerobic parameters to running performance of well-trained athletes presents a time- or distance-dependent pattern.

Pacing and Body Weight Changes During a Mountain Ultramarathon: Sex Differences and Performance

The study was aimed at comparing pacing adopted by males and females in a 107-km mountain ultramarathon and assessing whether pacing-related variables were associated with intracompetition body weight changes and performance. Forty-seven athletes (29 males; 18 females) were submitted to a cardiopulmonary exercise test before the race. Athletes were also weighted before the start of the race, at three midpoints (33 km, 66 km and 84 km) and after the race. Pacing was analyzed using absolute and relative speeds and accelerometry-derived sedentary time spent during the race. Results showed that females spent less sedentary time (4.72 ± 2.91 vs. 2.62 ± 2.14%; p = 0.035; d = 0.83) and displayed a smaller body weight loss (3.01 ± 1.96 vs. 4.37 ± 1.77%; p = 0.048; d = 0.77) than males. No significant sex differences were revealed for speed variability, absolute and relative speed. In addition, finishing time was correlated with: speed variability (r = 0.45; p = 0.010), index of pacing (r = -0.63; p < 0.001) and sedentary time (r = 0.64; p < 0.001). Meanwhile, intracompetition body weight changes were related with both the absolute and relative speed in the first and the last race section. These results suggest that females, as compared with males, take advantage of shorter time breaks at aid stations. Moreover, performing a more even pacing pattern may be positively associated with performance in mountain ultramarathons. Finally, intracompetition body weight changes in those races should be considered in conjunction with running speed fluctuations.

Do Sex Differences in Physiology Confer a Female Advantage in Ultra-Endurance Sport?

Ultra-endurance has been defined as any exercise bout that exceeds 6 h. A number of exceptional, record-breaking performances by female athletes in ultra-endurance sport have roused speculation that they might be predisposed to success in such events. Indeed, while the male-to-female performance gap in traditional endurance sport (e.g., marathon) remains at ~ 10%, the disparity in ultra-endurance competition has been reported as low as 4% despite the markedly lower number of female participants. Moreover, females generally outperform males in extreme-distance swimming. The issue is complex, however, with many sports-specific considerations and caveats. This review summarizes the sex-based differences in physiological functions and draws attention to those which likely determine success in extreme exercise endeavors. The aim is to provide a balanced discussion of the female versus male predisposition to ultra-endurance sport. Herein, we discuss sex-based differences in muscle morphology and fatigability, respiratory-neuromechanical function, substrate utilization, oxygen utilization, gastrointestinal structure and function, and hormonal control. The literature indicates that while females exhibit numerous phenotypes that would be expected to confer an advantage in ultra-endurance competition (e.g., greater fatigue resistance, greater substrate efficiency, and lower energetic demands), they also exhibit several characteristics that unequivocally impinge on performance (e.g., lower O₂-carrying capacity, increased prevalence of GI distress, and sex-hormone effects on cellular function/injury risk). Crucially, the advantageous traits may only manifest as ergogenic in the extreme endurance events which, paradoxically, are those that females less often contest. The title question should be revisited in the coming years, when/if the number of female participants increases.

The Impact of Sex and Performance Level on Pacing Behavior in a 24-h Ultramarathon

Purpose: We analyzed the impact of sex, performance level and substantial speed reductions (SSR) on pacing in the VI Rio 24-h Marines Ultramarathon. This will provide insights into the importance of minimizing speed variations in relation to optimal pacing in endurance events.

Methods: Runners (30 males and 21 females), classified as high- (HP) and low-performance (LP) ran the race while having their time recorded every 400 m. The pacing was analyzed as the first 10% (initial epoch), the following 80% (intermediate epoch) and the last 10% of the race (final epoch). The time percentage spent at speeds <3.5 km·h⁻¹ (SSR), 3.5 to 5.9 km·h⁻¹ (walking speed), 6.0 to 8.0 km·h⁻¹ (walk-to-running transition speed) and > 8.0 km·h⁻¹ (running speed) was calculated.

Results: Runners showed a reverse J-shaped pacing (P < 0.001) regardless of sex and performance level, although male (P < 0.004) and HP runners (P < 0.001) have preserved a higher mean speed throughout the race. Male and HP runners spent more time at running speed (P < 0.001) and less time at SSR (P < 0.001) than female and LP runners. Total distance was inversely correlated with the number of SSR and speed CV in male (r = −0.47 and r = −0.64, respectively) and female (r = −0.61 and r = −0.47, respectively).

Conclusion: Male, HP runners showed less SSR, conserving a higher mean speed with less variation throughout the race. Results suggest that conservative pacing strategies, with lower speeds in the beginning and higher speeds toward the end, may be the most adequate for different endurance running disciplines. Results also show different competition dynamics between men and women, which warrants further exploration in ultramarathons as well as other IAAF events.

Even Pacing Is Associated with Faster Finishing Times in Ultramarathon Distance Trail Running-The "Ultra-Trail du Mont Blanc" 2008-2019

In recent years, there has been an increasing number of investigations analyzing the effects of sex, performance level, and age on pacing in various running disciplines. However, little is known about the impact of those factors on pacing strategies in ultramarathon trail running. This study investigated the effects of age, sex, and performance level on pacing in the UTMB^® (Ultra-trail du Mont Blanc) and aimed to verify previous findings obtained in the research on other running disciplines and other ultramarathon races. Data from the UTMB^® from 2008 to 2019 for 13,829 race results (12,681 men and 1148 women) were analyzed. A general linear model (two-way analysis of variance (ANOVA)) was applied to identify a sex, age group, and interaction effect in pace average and pace variation. A univariate model (one-way ANOVA) was used to identify a sex effect for age, pace average, and pace variation for the fastest men and women. In our study, pace average and a steadier pace were positively correlated. Even pacing throughout the UTMB^® correlated with faster finishing times. The average pace depended significantly on sex and age group. When considering the top five athletes in each age group, sex and age group also had significant effects on pace variation. The fastest women were older than the fastest men, and the fastest men were faster than the fastest women. Women had a higher pace variation than men. In male competitors, younger age may be advantageous for a successful finish of the UTMB^®. Faster male runners seemed to be younger in ultramarathon trail running with large changes in altitude when compared to other distances and terrains.

Heart of the World's Top Ultramarathon Runner-Not Necessarily Much Different from Normal

The impact of ultramarathon (UM) runs on the organs of competitors, especially elite individuals, is poorly understood. We tested a 36-year-old UM runner before, 1–2 days after, and 10–11 days after winning a 24-h UM as a part of the Polish Championships (258.228 km). During each testing session, we performed an electrocardiogram (ECG), transthoracic echocardiography (TTE), cardiac magnetic resonance imaging (MRI), cardiac ³¹P magnetic resonance spectroscopy (³¹P MRS), and blood tests. Initially, increased cholesterol and low-density lipoprotein cholesterol (LDL-C) levels were identified. The day after the UM, increased levels of white blood cells, neutrophils, fibrinogen, alanine aminotransferase, aspartate aminotransferase, creatine kinase, C-reactive protein, and N-terminal type B natriuretic propeptide were observed. Additionally, decreases in hemoglobin, hematocrit, cholesterol, LDL-C, and hyponatremia were observed. On day 10, all measurements returned to normal levels, and cholesterol and LDL-C returned to their baseline abnormal values. ECG, TTE, MRI, and ³¹P MRS remained within the normal ranges, demonstrating physiological adaptation to exercise. The transient changes in laboratory test results were typical for the extreme efforts of the athlete and most likely reflected transient but massive striated muscle damage, liver cell damage, activation of inflammatory processes, effects on the coagulation system, exercise-associated hyponatremia, and cytoprotective or growth-regulatory effects. These results indicated that many years of intensive endurance training and numerous UMs (including the last 24-h UM) did not have a permanent adverse effect on this world-class UM runner’s body and heart. Transient post-competition anomalies in laboratory test results were typical of those commonly observed after UM efforts.

Influence of a slow-start on overall performance and running kinematics during 6-h ultramarathon races

The aim of this study was to describe the pacing during a 6-h ultramarathon (race 1) and to investigate whether a slow-start affects performance, running kinematic changes, ratings of perceived exertion (RPE) and fatigue (ROF) (race 2). After a critical speed test, participants completed two 6-h ultramarathons. Race 1 (n = 16) was self-paced, whereas in race 2 (n = 10), athletes performed the initial 36 min at speeds 18% below the mean speed of the initial 36 min of race 1. In race 1, participants adopted an inverse sigmoid pacing. Contact times increased after 1 h, and flight times decreased after 30 min (all P ≤ .009); stride length reduced after 1 h 30 min (all P = .022), and stride frequency did not change. Despite the lower speeds during the first 10% of race 2, and higher speeds at 50% and 90%, performance remained unchanged (57.5 ± 10.2 vs. 56.3 ± 8.5 km; P = .298). However, RPE and ROF were lowered for most of race 2 duration (all P < .001). For the comparison of kinematic variables between races, data were normalised by absolute running speed at each time point from 1 h onwards. No differences were found for any of the kinematic variables. In conclusion, decreasing initial speed minimises RPE and ROF, but does not necessarily affect performance. In addition, running kinematic changes do not seem to be affected by pacing manipulation.

Pacing of Women and Men in Half-Marathon and Marathon Races

Background and objective: Half-marathon is the most popular endurance running race in terms of number of races and runners competing annually; however, no study has compared pacing strategies for this race distance with marathon. The aim of the present study was to profile pacing in half-marathon, compare half-marathon and marathon for pacing, and estimate sex differences in pacing. Materials and methods: A total of 9137 finishers in the half-marathon (n = 7258) and marathon race (n = 1853) in Ljubljana 2017 were considered for their pacing in five race segments (0–23.7%, 23.7–47.4%, 47.4–71.1%, 71.1–94.8%, and 94.8–100% of the race. Results: Half-marathon runners followed a positive pacing with every segment being slower than its previous one without the presence of an endspurt. Compared to marathon (where the average percent of change in speed (ACS) was 5.71%), a more even pacing was observed in half-marathon (ACS = 4.10%). Moreover, women (ACS = 4.11%) had similar pacing as men (ACS = 4.09%) in half-marathons. Conclusions: In summary, running a half-marathon followed a unique pattern that differentiated this race distance from marathon, with the former showing a more even pacing with an absence of endspurt, and sex difference compared to the latter. Consequently, runners should be advised to adopt a less variable pacing when competing in a half-marathon, regardless of their sex. To the best of our knowledge, the more even pacing in half-marathon, than in marathon, was a novel finding, as it was the first study to compare the two race distances for this characteristic.

Pacing during a cross-country mountain bike mass-participation event according to race performance, experience, age and sex

This study describes pacing strategies adopted in an 86-km mass-participation cross-country marathon mountain bike race (the 'Birkebeinerrittet'). Absolute (km·h^-1) and relative speed (% average race speed) and speed coefficient of variation (%CV) in five race sections (15.1, 31.4, 52.3, 74.4 and 100% of total distance) were calculated for 8182 participants. Data were grouped and analysed according to race performance, age, sex and race experience. The highest average speed was observed in males (21.8 ± 3.7 km/h), 16-24 yr olds (23.0 ± 4.8 km/h) and those that had previously completed >4 Birkebeinerrittet races (22.5 ± 3.4 km/h). Independent of these factors, the fastest performers exhibited faster speeds across all race sections, whilst their relative speed was higher in early and late climbing sections (Cohen's d = 0.45-1.15) and slower in the final descending race section (d = 0.64-0.98). Similar trends were observed in the quicker age, sex and race experience groups, who tended to have a higher average speed in earlier race sections and a lower average speed during the final race section compared to slower groups. In all comparisons, faster groups also had a lower %CV for speed than slower groups (fastest %CV = 24.02%, slowest %CV = 32.03%), indicating a lower variation in speed across the race. Pacing in a cross-country mountain bike marathon is related to performance, age, sex and race experience. Better performance appears to be associated with higher relative speed during climbing sections, resulting in a more consistent overall race speed.

The Effect of Sex and Performance Level on Pacing in Duathlon

The purpose of the present research was to study the effect of sex and performance on pacing in short (Run1-10 km, Bike-50 km and Run2-5 km) and long distance (Run1-10 km, Bike-150 km and Run2-30 km) in the Powerman World Championship ‘Powerman Zofingen’. All finishers (n = 6671; women, n = 1037; men, n = 5634) competing either in the short or long distance versions of ‘Powerman Zofingen’ from 2003 to 2017 were analyzed for the time spent in each discipline (Run1, Bike and Run2), and in transition (Tran) from Run1 to Bike (Tran1) and from Bike to Run2 (Tran2). Athletes were ranked in quartile (Q) groups (Q1, Q2, Q3 and Q4), with Q1 the fastest and Q4 the slowest. In short distance, in both sexes, a medium discipline/transition × quartile interaction on relative time was observed (p < 0.001, η²_p = 0.103 and η²_p = 0.119, respectively), where Q1 was relatively the fastest in Tran1, Tran2 and Run2, and the slowest in Bike (p < 0.001). In long distance, in both sexes, a large discipline/transition × quartile interaction on relative time was observed (p < 0.001, η²_p = 0.208 and η²_p = 0.180, respectively), where Q1 was relatively the fastest in Tran1, Tran2 and Run2, and the slowest in Bike (p < 0.001). In summary, a similar trend of variation of pacing by performance level was observed in both sexes and distances with the fastest duathletes being the fastest in Run2 and both transitions, and the slowest in Bike.

Pacing Decision Making in Sport and the Effects of Interpersonal Competition: A Critical Review

An athlete's pacing strategy is widely recognised as an essential determinant for performance during individual events. Previous research focussed on the importance of internal bodily state feedback, revealed optimal pacing strategies in time-trial exercise, and explored concepts such as teleoanticipation and template formation. Recently, human-environment interactions have additionally been emphasized as a crucial determinant for pacing, yet how they affect pacing is not well understood. Therefore, this literature review focussed on exploring one of the most important human-environment interactions in sport competitions: the interaction among competitors. The existing literature regarding the regulation of exercise intensity and the effect of competition on pacing and performance is critically reviewed in this paper. The PubMed, CINAHL and Web of Science electronic databases were searched for studies about pacing in sports and (interpersonal) competition between January 2000 to October 2017, using the following combination of terms: (1) Sports AND (2) Pacing, resulting in 75 included papers. The behaviour of opponents was shown to be an essential determinant in the regulation of exercise intensity, based on both observational (N = 59) and experimental (N = 16) studies. However, adjustment in the pacing response related to other competitors appears to depend on the competitive situation and the current internal state of the athlete. The findings of this review emphasize the importance of what is happening around the athlete for the outcome of the decision-making process involved in pacing, and highlight the necessity to incorporate human-environment interactions into models that attempt to explain the regulation of exercise intensity in sports and exercise.

Athletic Races Represent Complex Systems, and Pacing Behavior Should Be Viewed as an Emergent Phenomenon

Pacing is the manner in which effort is distributed over the duration of an exercise bout, and is an important determinant of the extent to which individual potential is realized during athletic races. Observed pacing behaviors are thought to result from complex decision-making processes, and several models have been proposed that may explain the manner in which these decisions are made. In this article we argue that examination of individual factors implicated in the regulation of pacing is unlikely to allow full understanding of the events leading to pacing and performance. Rather than utilizing such a reductionist approach, it is suggested that athletic races be viewed as complex systems, and that pacing behavior is an emergent phenomenon that cannot be fully understood through study of components of the system in isolation. We describe and discuss known and potential interactions between determinants of pacing during races, and conclude with a call for the development of novel research methodologies that may further understanding of the manner in which observed behaviors emerge.

Pacing strategies by age in marathon cross-country skiing

OBJECTIVES

Pacing strategies have mainly been investigated for runners, but little is known for cross-country skiers. The aim of the present study was to investigate whether differences in pacing strategies do exist between younger and older cross-country skiers competing in the 42 km 'Engadin Ski Marathon'.

METHODS

Pacing was studied in 105,565 cross-country skiers (classified in 5-year age groups) competing between 1998 and 2016 in this race by examining changes of mean section velocity in 10 km (Change A, i.e. 100×(velocity in the 10-20 km section - velocity in the 0-10 km section)/velocity in the 0-10 km section), 20 km (Change B) and 35 km (Change C).

RESULTS

A small sex×distance (i.e. Change A versus Change B versus Change C) interaction on change of velocity was shown (P < .001, η² = 0.016), with women showing a less even pacing than men. In women, there was a trivial main effect of age group on Change A (P < .001, η² = 0.008) with a smaller decrease in velocity in age group <20 (-7.4%) and larger decrease in velocity in age group 75-79 (-12.8%), and Change B (P = .006, η² = 0.004) with smaller increase in velocity in age group 75-79 (+30.6%) and larger increase in velocity in age group 40-44 (+37.7%), but not on Change C (P = .784, η² = 0.003). In men, a small main effect of age group on Change A was shown (P < .001, η² = 0.019), with a smaller decrease of velocity in age group <20 (-3.5%) and larger in age group 70-74 (-10.5%). Trivial main effects of age group on Change B (P < .001, η² = .002), with a smaller increase of velocity in age group 85-89 (+25.8%) and larger increase in age group 70-74 (+33.0%), and Change C (P < .001, η² = 0.003), with smaller decrease of velocity in age group 85-89 (-38.2%) and larger decrease in age group 80-84 (-41.0%), were found.

CONCLUSIONS

Based on these findings, it was concluded that men and young cross-country skiers had a more even pacing than women and older cross-country skiers, which was in contrast with previous findings in other endurance sports, suggesting that the sex- and age-related differences in pacing might be sport-dependent.

Physiology and Pathophysiology in Ultra-Marathon Running

In this overview, we summarize the findings of the literature with regards to physiology and pathophysiology of ultra-marathon running. The number of ultra-marathon races and the number of official finishers considerably increased in the last decades especially due to the increased number of female and age-group runners. A typical ultra-marathoner is male, married, well-educated, and ~45 years old. Female ultra-marathoners account for ~20% of the total number of finishers. Ultra-marathoners are older and have a larger weekly training volume, but run more slowly during training compared to marathoners. Previous experience (e.g., number of finishes in ultra-marathon races and personal best marathon time) is the most important predictor variable for a successful ultra-marathon performance followed by specific anthropometric (e.g., low body mass index, BMI, and low body fat) and training (e.g., high volume and running speed during training) characteristics. Women are slower than men, but the sex difference in performance decreased in recent years to ~10–20% depending upon the length of the ultra-marathon. The fastest ultra-marathon race times are generally achieved at the age of 35–45 years or older for both women and men, and the age of peak performance increases with increasing race distance or duration. An ultra-marathon leads to an energy deficit resulting in a reduction of both body fat and skeletal muscle mass. An ultra-marathon in combination with other risk factors, such as extreme weather conditions (either heat or cold) or the country where the race is held, can lead to exercise-associated hyponatremia. An ultra-marathon can also lead to changes in biomarkers indicating a pathological process in specific organs or organ systems such as skeletal muscles, heart, liver, kidney, immune and endocrine system. These changes are usually temporary, depending on intensity and duration of the performance, and usually normalize after the race. In longer ultra-marathons, ~50–60% of the participants experience musculoskeletal problems. The most common injuries in ultra-marathoners involve the lower limb, such as the ankle and the knee. An ultra-marathon can lead to an increase in creatine-kinase to values of 100,000–200,000 U/l depending upon the fitness level of the athlete and the length of the race. Furthermore, an ultra-marathon can lead to changes in the heart as shown by changes in cardiac biomarkers, electro- and echocardiography. Ultra-marathoners often suffer from digestive problems and gastrointestinal bleeding after an ultra-marathon is not uncommon. Liver enzymes can also considerably increase during an ultra-marathon. An ultra-marathon often leads to a temporary reduction in renal function. Ultra-marathoners often suffer from upper respiratory infections after an ultra-marathon. Considering the increased number of participants in ultra-marathons, the findings of the present review would have practical applications for a large number of sports scientists and sports medicine practitioners working in this field.

The effect of aging on pacing strategies of cross-country skiers and the role of performance level

Background

The participation of master cross-country (XC) skiers in training and competition has increased during the last decades; however, little is known yet about whether these athletes differ from their younger counterparts in aspects of performance such as pacing. Therefore, the aim of the present study was to examine the combined effect of age and performance (race time) on pacing in cross-country (XC) skiing. We analyzed all finishers (n = 79,722) in ‘Vasaloppet’ from 2012 to 2017, the largest cross-country skiing race in the world, classified according to their race time into 10 groups: 3-4 h, 4-5 h, ..., 12-13 h.

Results

A trivial main effect of sex on total pace range was observed (p < 0.001, η² = 0.002), where women (44.1 ± 10.2%) had larger total pace range than men (40.9 ± 11.8%). A large main effect of performance group on total pace range was shown (p < 0.001, η² = 0.160), where the smallest total pace range was 21.8 ± 1.9% (3-4 h group) and the largest 50.1 ± 9.9% (10-11 h group). A trivial sex×performance group interaction on total pace range was found (p < 0.001, η² = 0.001) with the largest sex difference in pacing shown in 9-10 h group. A trivial and small main effect of age was found in women (p < 0.001, η² = 0.005) and men (p < 0.001, η² = 0.011), respectively, where the masters had smaller total pace range than their younger counterparts. A trivial age group×performance group interaction on total pace range was observed in both women (p < 0.001, η² = 0.008) and men (p < 0.001, η² = 0.006) with smaller differences among age groups in the faster performance groups.

Conclusions

In summary, master XC skiers adopted a relatively even pacing independently from their race time and the differences in pacing from the younger XC skiers were more pronounced in the slower masters. These findings suggest that exercise attenuates the decline of performance in master XC skiers as shown by the similar pacing strategies between fast master XC skiers and their younger counterparts.

Cardiac Autonomic Modulations and Psychological Correlates in the Yukon Arctic Ultra: The Longest and the Coldest Ultramarathon

Studies on human physical performance in extreme environments have effectively approached the investigation of adaptation mechanisms and their physiological limits. As scientific interest in the interplay between physiological and psychological aspects of performance is growing, we aimed to investigate cardiac autonomic control, by means of heart rate variability, and psychological correlates, in competitors of a subarctic ultramarathon, taking place over a 690 km course (temperatures between +5 and -47°C). At baseline (PRE), after 277 km (D1), 383 km (D2), and post-race (POST, 690 km), heart rate (HR) recordings (supine, 15 min), psychometric measurements (Profile of Mood States/POMS, Borg fatigue, and Karolinska Sleepiness Scale scores both upon arrival and departure) were obtained in 16 competitors (12 men, 4 women, 38.6 ± 9.5 years). As not all participants reached the finish line, comparison of finishers (FIN, n = 10) and non-finishers (NON, n = 6), allowed differential assessment of performance. Resting HR increased overall significantly at D1 (FIN +15.9; NON +14.0 bpm), due to a significant decrease in parasympathetic drive. This decrease was in FIN only partially recovered toward POST. In FIN only, baseline HR was negatively correlated with mean velocity [r -0.63 (P.04)] and parasympathetic drive [pNN50+: r -0.67 (P.03)], a lower HR and a higher vagal tone predicting a better performance. Moreover, in FIN, a persistent increase of the long-term self-similarity coefficient, assessed by detrended fluctuation analysis (DFAα2), was retrieved, possibly due to higher alertness. As for psychometrics, at D1, POMS Vigor decreased (FIN: -7.0; NON: -3.8), while Fatigue augmented (FIN: +6.9; NON: +5.0). Sleepiness increased only in NON, while Borg scales did not exhibit changes. Baseline comparison of mood states with normative data for athletes displayed significantly higher positive mood in our athletes. Results show that: the race conditions induced early decreases in parasympathetic drive; the extent of vagal withdrawal, associated to the timing of its recovery, is crucial for success; pre-competition lower resting HR predicts a better performance; psychological profile is reliably depicted by POMS, but not by Borg fatigue scales. Therefore, assessment of heart rate variability and psychological profile may monitor and partly predict performance in long-duration ultramarathon in extreme cold environment.

Pacing in age group marathoners in the "New York City Marathon"

The aim of the study was to investigate how women and men age group runners pace during a large city marathon. We analysed changes in running speed by splits of 5 km in 20,283 women and 28,282 men age group runners competing in the 2015 edition of the "New York City Marathon". A moderate split×sex interaction on running speed (p < 0.001, η² = 0.108) was observed with men showing a larger decrease in speed from the fastest split (5-10 km) to the slowest one (35-40 km) than women (21.1 vs. 16.7%), and a different pattern was observed in the 25-30 km split (increase in women, decrease in men). A trivial split×age group interaction on speed was observed in women (p < 0.001, η² = 0.003) and men (p < 0.001, η² = 0.004). In summary, men and women of all age groups reduced running speed during the marathon with a final spurt in the last segment (i.e. 40-42.2 km).