Fast men slow more than fast women in a 10 kilometer road race

Fractional utilization of the 10-minute treadmill test velocity in running performance

This study aimed to evaluate the applicability of the 10-minute submaximal treadmill test (T10 test), a self-paced test, in determining critical speed (CS) and predicting running performance. Specifically, we sought to identify the percentage of T10 velocity (vT10) that runners performed in official distance races, and to compare physiological and performance indicators between sexes. 60 recreational runners (n=34 males and n=26 females) underwent a maximum incremental test, the novel T10 test, and ran 1200-m and 2400-m on the track. Runners self-reported their best performance times. Generalized Linear Model was used to compare running performances between sexes. For both males and females, the %vT10 in 5 km, 10 km, and half-marathon races occurred at 107.5% and 106.5%, 99.9% and 100.8%, and 92.6% and 97.1%, respectively. There was no interaction effect (p=0.520) and no main effect of sex (p=0.443). There was a main effect of distance (p<0.001), indicating that %vT10 in the 5km race differed from that found in the 10 km race (p=0.012), as well as in the half-marathon (p<0.001). Our findings suggest that %vT10 values can be used to determine pace in recreational endurance runners for race distances regardless of sex.

Case Report: Differences in self-selected pacing in 20, 40, and 60 ironman-distance triathlons: a case study

Background

Triathletes are pushing their limits in multi-stage Ironman-distance triathlons. In the present case study, we investigated the pacing during 20, 40, and 60 Ironman-distance triathlons in 20, 40, and 60 days, respectively, of one professional IRONMAN® triathlete.

Case study

Event 1 (20 Ironman-distance triathlons in 20 days), Event 2 (40 Ironman-distance triathlons in 40 days), and Event 3 (60 Ironman-distance triathlons in 60 days) were analyzed by discipline (swimming, cycling, running, and overall event time), by Deca intervals (10 days of consecutive Ironman-distance triathlons) and additional data (sleep duration, body mass, heart rate in cycling and running). To test differences between Events and Deca intervals within the same discipline, T-tests (2 groups) or one-way ANOVAs (3 or more groups) were used.

Results

Swimming splits were fastest in Event 1, (ii) cycling and running splits were fastest in both Event 2 and 3, (iii) overall speed was fastest in Event 3, (iv) sleep duration increased during Event 2 but decreased in Event 3, (v) body mass decreased in Event 2, but increased in Event 3 and (vi) heart rate during cycling was similar in both Event 2 and 3. In contrast, heart rate during running was greater in Event 3.

Conclusion

In a professional IRONMAN® triathlete finishing 20, 40, and 60 Ironman-distance triathlons in 20, 40, and 60 days, respectively, split performances and both anthropometrical and physiological changes such as body mass and heart rate differed depending upon the duration of the events.

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.

The Use of a Just Noticeable Difference Approach to Improve Perceptual Acuity Ability in Male Runners

We were interested in micro-variations in an athlete's psychophysical state that separate peak exertion from physiological collapse. Thus, we measured perceptual acuity in runners using a classic psychophysical approach, the just noticeable difference (JND) on two standard stimuli runs at treadmill speed corresponding to 70%VO2max and 80%VO2max. Thirty-four male runners (M age = 35.26, SD = 7.33 years) first performed a maximal treadmill test to determine the speed of a standard exercise bout for the JND trials. The JND trials consisted of four 5-minute running bouts on a treadmill with 5-minute rests between bouts. For bouts 1 and 3, participants ran at the standard stimuli pace, but for bouts 2 and 4, they adjusted their speeds to achieve a level of exertion at a JND above/below the SS. They achieved differences in the final 30 seconds of the VO2 between each JND bout and the previous standard stimuli at just above (JND-A) and just below (JND-B) the JND perceived exertions. We used a Generalized Linear Model analysis to compare the JND-A and JND-B within and between ventilatory threshold groups (lower/higher) in absolute and relative VO2 and in terms of the total JND magnitude. The magnitude of JND-A was greater than that of JND-B at 70%VO2max and 80%VO2max in absolute units (70%VO2 Δ = 2.62; SE = 0.37; p < .001; 80%VO2 Δ = 1.67; SE = 0.44; p = .002) and in relative units (70%VO2max Δ = 4.70; SE = 0.66; p < .001; 80%VO2max Δ = 2.96; SE = 0.80; p = .002). The total magnitude was greater in the 70%VO2max trial than 80%VO2max in absolute units (70%VO2 M = 3.78, SE = 0.31 mL·kg-1·min-1; 80%VO2 M = 2.62, SE = 0.37 mL·kg-1·min-1; p = .020) and in relative units (70%VO2max M = 6.57, SE = 0.53%VO2max; 80%VO2max M = 4.71, SE = 0.64%VO2max; p = .030). The JND range narrowed when physiologic demand increased, for both physical (speed) and psychological (RPE) variables.

An analysis of the São Silvestre race between 2007-2021: An increase in participation but a decrease in performance

This study aimed to investigate the trends of finishers in the São Silvestre race in Brazil, taking into account sex, age, and performance levels. A total of 31 ​775 runners (women, n ​= ​13 ​847; men, n ​= ​17 ​928), aged (45.2 ​± ​16.8) years, finishers in the São Silvestre race between 2007 and 2021, were considered in the present analysis. Data (event year, date of birth, sex, and race times) were downloaded from the official race website. The man-Whitney U test, Spearman correlation, and robust regression model were computed. Participation increased over time for both sexes. Regarding age groups, "31-40 years" (women) and "> 60 years" (men) were those with the highest number of finishers. We found a decrease in performance across the years (β ​= ​2.45; p ​< ​0.005), as well as significant differences in race times for both sexes (U ​= ​42.844; p ​< ​0.001), with men presenting better performances than women. Over time, it was observed an increase in the performance gap between the sexes, but in general, the performance decreased (β ​= ​1.76; p ​< ​0.001). Stakeholders should consider improving the strategies to improve women and young people's participation in running events.

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.

Elderly female ultra-marathoners reduced the gap to male ultra-marathoners in Swiss running races

Recent studies showed that female runners reduced the performance gap to male runners in endurance running with increasing age and race distance. However, the investigated samples were generally small. To investigate this further, the present study examined sex differences by age across various race distances (5, 10 km, half-marathon, marathon, and ultra-marathon) using a large dataset of over 1,100,000 race records from Switzerland over two decades (1999-2019). The study explored performance and participation disparities between male and female runners by employing diverse methods, such as descriptive statistics, histograms, scatter and line plots, correlations, and a predictive machine learning model. The results showed that female runners were more prevalent in shorter races (5, 10 km, half-marathon) and outnumbered male runners in 5 km races. However, as the race distance increased, the male-to-female ratio declined. Notably, the performance gap between sexes reduced with age until 70 years, after which it varied depending on the race distance. Among participants over 75 years old, ultra-marathon running exhibited the smallest sex difference in performance. Elderly female ultra-marathoners (75 years and older) displayed a performance difference of less than 4% compared to male ultra-marathoners, which may be attributed to the presence of highly selected outstanding female performers.

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.

Variable Pacing Is Associated with Performance during the OCC® Ultra-Trail du Mont-Blanc® (2017-2021)

The current evidence suggests that pacing may not be affected by performance level or sex in trail-running races as may occur in road running races. However, the previous studies included races of >100 km. Therefore, we aimed to verify the influence of performance level and sex on pacing in the last four (2017, 2018, 2019, and 2021) editions of a shorter (56.3 km) ultra-trail running race (i.e., Orsières-Champex-Chamonix; OCC®) that maintained the same race profile. The mean finishing time for the 5656 participants was 10 h 20 min 33 s ± 2 h 01 min 19 s. Pacing variability (CV%) was higher in high-level participants, thus showing a greater ability to adapt their pace to the race profile than low-level runners. Males also had a higher pacing variability than females although the effect sizes were small. Based on the current findings, we may recommend for non-elite OCC® participants to adapt their pace to the race profile with a slower pace during uphills and a faster pace during downhills. Further studies including participants' experience are necessary to confirm the effectiveness of this suggestion in trail-running races of variable distances.

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.

Expanding the Gap: An Updated Look Into Sex Differences in Running Performance

Males consistently outperform females in athletic endeavors, including running events of standard Olympic distances (100 m to Marathon). The magnitude of this percentage sex difference, i.e., the sex gap, has evolved over time. Two clear trends in sex gap evolution are evident; a narrowing of the gap during the 20th century, followed by a period of stability thereafter. However, an updated perspective on the average sex gap from top 20 athlete performances over the past two decades reveals nuanced trends over time, indicating the sex gap is not fixed. Additionally, the sex gap varies with performance level; the difference in absolute running performance between males and females is lowest for world record/world lead performances and increases in lower-ranked elite athletes. This observation of an increased sex gap with world rank is evident in events 400 m and longer and indicates a lower depth in female competitive standards. Explanations for the sex difference in absolute performance and competition depth include physical (physiological, anatomical, neuromuscular, biomechanical), sociocultural, psychological, and sport-specific factors. It is apparent that females are the disadvantaged sex in sport; therefore, measures should be taken to reduce this discrepancy and enable both sexes to reach their biological performance potential. There is scope to narrow the sex performance gap by addressing inequalities between the sexes in opportunities, provisions, incentives, attitudes/perceptions, research, and media representation.

Pacing Profiles of Middle-Distance Running World Records in Men and Women

The aims of the current study were to compare the pacing patterns of all-time 800 m, 1500 m and mile running world records (WRs) and to determine whether differences exist between sexes, and if 800 m and 1500 m WRs were broken during championship or meet races. Overall and lap times for men and women’s 800 m, 1500 m, and mile WRs from World Athletics were collected when available and subsequently compared. A fast initial 200 m segment and a decrease in speed throughout was found during 800 m WRs. Accordingly, the first 200 m and 400 m were faster than the last 200 m and 400 m, respectively (p < 0.001, 0.77 ≤ ES ≤ 1.86). The first 400 m and 409 m for 1500 m and mile WRs, respectively, were faster than the second lap (p < 0.001, 0.74 ≤ ES ≤ 1.46). The third 400 m lap was slower than the last 300 m lap and 400 m lap for 1500 m and mile WRs, respectively (p < 0.001, 0.48 ≤ ES ≤ 1.09). No relevant sex-based differences in pacing strategy were found in any event. However, the first 409 m lap was faster than the last 400 m lap for men but not for women during mile WRs. Women achieved a greater % of WRs than men during championships (80% vs. 45.83% in the 800 m, and 63.63% vs. 31.58% in the 1500 m, respectively). In conclusion, positive, reverse J-shaped and U-shaped pacing profiles were used to break 800 m, men’s mile and 1500 m, and women’s mile WRs, respectively. WRs are more prone to be broken during championships by women than men.

Longer Disciplined Tapers Improve Marathon Performance for Recreational Runners

For marathoners the taper refers to a period of reduced training load in the weeks before race-day. It helps runners to recover from the stresses of weeks of high-volume, high-intensity training to enhance race-day performance. The aim of this study was to analyse the taper strategies of recreational runners to determine whether particular forms of taper were more or less favorable to race-day performance.

Methods: We analyzed the training activities of more than 158,000 recreational marathon runners to define tapers based on a decrease in training volume (weekly distance). We identified different types of taper based on a combination of duration (1–4 weeks of decreasing training) and discipline (strict tapers progressively decrease training in the weeks before the marathon, relaxed tapers do not) and we grouped runners based on their taper type to determine the popularity of different types of taper and their associated performance characteristics.

Results: Kruskal-Wallis tests (H(7)≥ 521.11, p < 0.001), followed by posthoc Dunns tests with a Bonferroni correction, confirmed that strict tapers were associated with better marathon performance than relaxed tapers (p < 0.001) and that longer tapers of up to 3 weeks were associated with better performance than shorter tapers (p < 0.001). Results indicated that strict 3-week tapers were associated with superior marathon finish-time benefits (a median finish-time saving of 5 min 32.4 s or 2.6%) compared with a minimal taper (p < 0.001). We further found that female runners were associated with greater finish-time benefits than men, for a given taper type ( ≤ 3-weeks in duration), based on Mann Whitney U tests of significance with p < 0.001.

Conclusion: The findings of this study for recreational runners are consistent with related studies on highly-trained athletes, where disciplined tapers were associated with comparable performance benefits. The findings also highlight how most recreational runners (64%) adopt less disciplined (2-week and 3-week) tapers and suggest that shifting to a more disciplined taper strategy could improve performance relative to the benefits of a less disciplined taper.

Pacing profiles and tactical behaviors of elite runners

The pacing behaviors used by elite athletes differ among individual sports, necessitating the study of sport-specific pacing profiles. Additionally, pacing behaviors adopted by elite runners differ depending on race distance. An "all-out" strategy, characterized by initial rapid acceleration and reduction in speed in the later stages, is observed during 100 m and 200 m events; 400 m runners also display positive pacing patterns, which is characterized by a reduction in speed throughout the race. Similarly, 800 m runners typically adopt a positive pacing strategy during paced "meet" races. However, during championship races, depending on the tactical approaches used by dominant athletes, pacing can be either positive or negative (characterized by an increase in speed throughout). A U-shaped pacing strategy (characterized by a faster start and end than during the middle part of the race) is evident during world record performances at meet races in 1500 m, 5000 m, and 10,000 m events. Although a parabolic J-shaped pacing profile (in which the start is faster than the middle part of the race but is slower than the endspurt) can be observed during championship 1500 m races, a negative pacing strategy with microvariations of pace is adopted by 5000 m and 10,000 m runners in championship races. Major cross country and marathon championship races are characterized by a positive pacing strategy; whereas a U-shaped pacing strategy, which is the result of a fast endspurt, is adopted by 3000 m steeplechasers and half marathoners. In contrast, recent world record marathon performances have been characterized by even pacing, which emphasizes the differences between championship and meet races at distances longer than 800 m. Studies reviewed suggest further recommendations for athletes. Throughout the whole race, 800 m runners should avoid running wide on the bends. In turn, during major championship events, 1500 m, 5000 m, and 10,000 m runners should try to run close to the inside of the track as much as possible during the decisive stages of the race when the speed is high. Staying within the leading positions during the last lap is recommended to optimize finishing position during 1500 m and 5000 m major championship races. Athletes with more modest aims than winning a medal at major championships are advised to adopt a realistic pace during the initial stages of long-distance races and stay within a pack of runners. Coaches of elite athletes should take into account the observed difference in pacing profiles adopted in meet races vs. those used in championship races: fast times achieved during races with the help of one or more pacemakers are not necessarily replicated in winner-takes-all championship races, where pace varies substantially. Although existing studies examining pacing characteristics in elite runners through an observational approach provide highly ecologically valid performance data, they provide little information regarding the underpinning mechanisms that explain the behaviors shown. Therefore, further research is needed in order to make a meaningful impact on the discipline. Researchers should design and conduct interventions that enable athletes to carefully choose strategies that are not influenced by poor decisions made by other competitors, allowing these athletes to develop more optimal and successful behaviors.

How recreational marathon runners hit the wall: A large-scale data analysis of late-race pacing collapse in the marathon

INTRODUCTION

In the marathon, how runners pace and fuel their race can have a major impact on race outcome. The phenomenon known as hitting the wall (HTW) refers to the iconic hazard of the marathon distance, in which runners experience a significant slowing of pace late in the race, typically after the 20-mile mark, and usually because of a depletion of the body's energy stores.

AIM

This work investigates the occurrence of significant late-race slowing among recreational marathoners, as a proxy for runners hitting the wall, to better understand the likelihood and nature of such slowdowns, and their effect on race performance.

METHODS

Using pacing data from more than 4 million race records, we develop a pacing-based definition of hitting the wall, by identifying runners who experience a sustained period of slowing during the latter stages of the marathon. We calculate the cost of these slowdowns relative to estimates of the recent personal-best times of runners and compare slowdowns according to runner sex, age, and ability.

RESULTS

We find male runners more likely to slow significantly (hit the wall) than female runners; 28% of male runners hit the wall compared with 17% of female runners, χ2(1, N = 1, 928, 813) = 27, 693.35, p < 0.01, OR = 1.43. Such slowdowns are more frequent in the 3 years immediately before and after a recent personal-best (PB) time; for example, 36% of all runners hit the wall in the 3 years before a recent PB compared with just 23% in earlier years, χ2(1, N = 509, 444) = 8, 120.74, p < 0.01, OR = 1.31. When runners hit the wall, males slow more than females: a relative slowdown of 0.40 vs. 0.37 is noted, for male and female runners, when comparing their pace when they hit the wall to their earlier race (5km-20km) pace, with t(475, 199) = 60.19, p < 0.01, d = 0.15. And male runners slow over longer distances than female runners: 10.7km vs. 9.6km, respectively, t(475, 199) = 68.44, p < 0.01, d = 0.17. Although, notably the effect size of these differences is small. We also find the finish-time costs of hitting the wall (lost minutes) to increase with ability; r2(7) = 0.91, p < 0.01 r2(7) = 0.81, p < 0.01 for male and female runners, respectively.

CONCLUSIONS

While the findings from this study are consistent with qualitative results from earlier single-race or smaller-scale studies, the new insights into the risk and nature of slowdowns, based on the runner sex, age, and ability, have the potential to help runners and coaches to better understand and calibrate the risk/reward trade-offs that exist as they plan for future races.

Pacing Profiles of Olympic and IAAF World Championship Long-Distance Runners

ABSTRACT

Filipas, L, La Torre, A, and Hanley, B. Pacing profiles of Olympic and International Association of Athletics Federations World Championship long-distance runners. J Strength Cond Res 35(4): 1134-1140, 2021-The aim of this study was to analyze the pacing profiles of Olympic and International Association of Athletics Federations (IAAF) World Championship long-distance finalists, including the relationship with their recent best times. The times for each 1,000-m split were obtained for 394 men and women in 5,000- and 10,000-m finals at 5 championships. Athletes' best times from the previous 32 months were also obtained. Similar pacing profiles were used by athletes grouped by finishing position in 5,000-m races. Women adopted a more even pacing behavior, highlighting a possible sex-based difference over this distance. Pacing behavior over 10,000 m was more similar between men and women compared with over 5,000 m. The main difference between men and women was that in the men's 10,000 m, as in the men's 5,000 m, more athletes were able to follow the leading group until the final stages. There were large or very large correlations between athletes' best times from the previous 32 months and their result; the fastest finishers also ran closer to their previous 32 months' best times. Despite differences in pacing behavior between events, long-distance runners should nonetheless stay close to the front from the beginning to win a medal.

Training and Racing Behavior of Recreational Runners by Race Distance-Results From the NURMI Study (Step 1)

The present study investigated pre-race preparation of a large sample of recreational runners competing in different race distances (e.g., shorter than half-marathon, half-marathon, marathon and ultra-marathon). An online questionnaire was used and a total of 3,835 participants completed the survey. Of those participants, 2,864 (75%) met the inclusion criteria and 1,628 (57%) women and 1,236 (43%) men remained after data clearance. Participants were categorized according to race distance in half-marathon (HM), and marathon/ultra-marathon (M/UM). Marathon and ultra-marathon data were pooled since the marathon distance is included in an ultra-marathon. The most important findings were (i) marathon and ultra-marathon runners were more likely to seek advice from a professional trainer, and (ii) spring was most commonly reported across all subgroups as the planned season for racing, (iii) training volume increased with increasing race distance, and (iv) male runners invested more time in training compared to female runners. In summary, runners competing in different race distances prepare differently for their planned race.

Clinical Trial Registration:www.ClinicalTrials.gov, identifier ISRCTN73074080. Retrospectively registered 12th June 2015.

Tower Running-Participation, Performance Trends, and Sex Difference

Though there are exhaustive data about participation, performance trends, and sex differences in performance in different running disciplines and races, no study has analyzed these trends in stair climbing and tower running. The aim of the present study was therefore to investigate these trends in tower running. The data, consisting of 28,203 observations from 24,007 climbers between 2014 and 2019, were analyzed. The effects of sex and age, together with the tower characteristics (i.e., stairs and floors), were examined through a multivariable statistical model with random effects on intercept, at climber’s level, accounting for repeated measurements. Men were faster than women in each age group (p < 0.001 for ages ≤69 years, p = 0.003 for ages > 69 years), and the difference in performance stayed around 0.20 km/h, with a minimum of 0.17 at the oldest age. However, women were able to outperform men in specific situations: (i) in smaller buildings (<600 stairs), for ages between 30 and 59 years and >69 years; (ii) in higher buildings (>2200 stairs), for age groups <20 years and 60–69 years; and (iii) in buildings with 1600–2200 stairs, for ages >69 years. In summary, men were faster than women in this specific running discipline; however, women were able to outperform men in very specific situations (i.e., specific age groups and specific numbers of stairs).

Number of finishers and performance of age group women and men in long-distance running: comparison among 10km, half-marathon and marathon races in Oslo

The aim of the present study was to examine the number of finishers and performance trends in 10 km, half-marathon and marathon races in Oslo. Data (total 115,725 finishers; women, n = 50,595; men, n = 65,130) from 10 km, half-marathon and marathon races in Oslo from 2008 to 2018 were analysed considering number, sex, age and running speed of finishers. The total men-to-women ratio was the smallest in the 10 km race (0.60) and the largest in the marathon (3.86) (p < 0.01, φ = 0.28). In both women and men, the slowest running speed was shown in the older age groups (p < 0.01). Based on the findings of the present study, it was concluded that relatively more women finished a 10 km and less a half-marathon and a marathon. Our results indicated that the sex difference in performance was attenuated in the longer race distances and older age groups.

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.

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.

Elite Male and Female 800-m Runners' Display of Different Pacing Strategies During Season-Best Performances

PURPOSE

To analyze the pacing profiles of the world's top 800-m annual performances between 2010 and 2016, comparing men's and women's strategies.

METHODS

A total of 142 performances were characterized for overall race times and 0-to-200-m, 200-to-400-m, 400-to-600-m, and 600-to-800-m split times using available footage from YouTube. Only the best annual performance for each athlete was considered. Overall race and split speed were calculated so that each lap speed could be expressed as a percentage of the mean race speed.

RESULTS

The mean speed of the men's 800-m was 7.73 (0.06) m·s-1, with the 0-to-200-m split faster than the others. After the first split, the speed decreased significantly during the 3 subsequent splits (P < .001). The mean speed of the women's 800-m was 6.77 (0.05) m·s-1, with a significative variation in speed during the race (P < .001). The first split was faster than the others (P < .001). During the rest of the race, speed was almost constant, and no difference was observed between the other splits. Comparison between men and women revealed that there was an interaction between split and gender (P < .001), showing a different pacing behavior in 800-m competitions.

CONCLUSIONS

The world's best 800-m performances revealed an important difference in the pacing profile between men and women. Tactics could play a greater role in this difference, but physiological and behavioral characteristics are likely also important.

The effect of sex and performance level on pacing in cross-country skiers: Vasaloppet 2004-2017

BACKGROUND

Pacing, defined as percentage changes of speed between successive splits, has been extensively studied in running and cycling endurance sports; however, less information about the trends in change of speed during cross-country (XC) ski racing is available. Therefore, the aim of the present study was to examine the effect of performance (quartiles of race time (Q), with Q1 the fastest and Q4 the slowest) level on pacing in the Vasaloppet ski race, the largest XC skiing race in the world.

METHODS

For this purpose, we analyzed female (n = 19,465) and male (n = 164,454) finishers in the Vasaloppet ski race from 2004 to 2017 using a one-way (2 sexes) analysis of variance with repeated measures to examine percentage changes of speed between 2 successive splits. Overall, the race consisted of 8 splits.

RESULTS

The race speeds of Q1, Q2, Q3, and Q4 were 13.6 ± 1.8, 10.6 ± 0.5, 9.2 ± 0.3, and 8.1 ± 0.4 km/h, respectively, among females and 16.7 ± 1.7, 13.1 ± 0.7, 10.9 ± 0.6, and 8.9 ± 0.7 km/h, respectively, among males. The overall pacing strategy of finishers was variable. A small sex × split interaction on speed was observed (η ² = 0.016, p < 0.001), with speed difference between sexes ranging from 14.9% (Split 7) to 27.0% (Split 1) and larger changes in speed between 2 successive splits being shown for females (p < 0.001, η ² = 0.004). A large performance × split interaction on speed, with Q1 presenting the smallest changes of speed between splits, was shown for females (η ² = 0.149, p < 0.001) and males (η ² = 0.169, p < 0.001).

CONCLUSION

Male and fast XC skiers are more even pacers. Coaches and athletes should develop tailored sex- and performance-level pacing strategies; for instance, they should advise fast XC skiers to start fast and maintain their speed, rather than starting slowly and trying to make up time by going faster at times during the race.

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.

Sex Differences in World-Record Performance: The Influence of Sport Discipline and Competition Duration

The current review summarizes scientific knowledge concerning sex differences in world-record performance and the influence of sport discipline and competition duration. In addition, the way that physiological factors relate to sex dimorphism is discussed. While cultural factors played a major role in the rapid improvement of performance of women relative to men up until the 1990s, sex differences between the world’s best athletes in most events have remained relatively stable at approximately 8–12%. The exceptions are events in which upper-body power is a major contributor, where this difference is more than 12%, and ultraendurance swimming, where the gap is now less than 5%. The physiological advantages in men include a larger body size with more skeletal-muscle mass, a lower percentage of body fat, and greater maximal delivery of anaerobic and aerobic energy. The greater strength and anaerobic capacity in men normally disappear when normalized for fat-free body mass, whereas the higher hemoglobin concentrations lead to 5–10% greater maximal oxygen uptake in men with such normalization. The higher percentage of muscle mass in the upper body of men results in a particularly large sex difference in power production during upper-body exercise. While the exercise efficiency of men and women is usually similar, women have a better capacity to metabolize fat and demonstrate better hydrodynamics and more even pacing, which may be advantageous, in particular during long-lasting swimming competitions.