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

Associations between environmental factors and running performance: An observational study of the Berlin Marathon

Extensive research has delved into the impact of environmental circumstances on the pacing and performance of professional marathon runners. However, the effects of environmental conditions on the pacing strategies employed by marathon participants in general remain relatively unexplored. This study aimed to examine the potential associations between various environmental factors, encompassing temperature, barometric pressure, humidity, precipitation, sunshine, cloud cover, wind speed, and dew point, and the pacing behavior of men and women. The retrospective analysis involved a comprehensive dataset comprising records from a total of 668,509 runners (520,521 men and 147,988 women) who participated in the 'Berlin Marathon' events between the years 1999 and 2019. Through correlations, Ordinary Least Squares (OLS) regression, and machine learning (ML) methods, we investigated the relationships between adjusted average temperature values, barometric pressure, humidity, precipitation, sunshine, cloud cover, wind speed, and dew point, and their impact on race times and paces. This analysis was conducted across distinct performance groups, segmented by 30-minute intervals, for race durations between 2 hours and 30 minutes to 6 hours. The results revealed a noteworthy negative correlation between rising temperatures and declining humidity throughout the day and the running speed of marathon participants in the 'Berlin Marathon.' This effect was more pronounced among men than women. The average pace for the full race showed positive correlations with temperature and minutes of sunshine for both men and women. However, it is important to note that the predictive capacity of our model, utilizing weather variables as predictors, was limited, accounting for only 10% of the variance in race pace. The susceptibility to temperature and humidity fluctuations exhibited a discernible increase as the marathon progressed. While weather conditions exerted discernible influences on running speeds and outcomes, they did not emerge as significant predictors of pacing.

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.

Performance and pacing of professional IRONMAN triathletes: the fastest IRONMAN World Championship ever-IRONMAN Hawaii 2022

Pacing during cycling and running in an IRONMAN triathlon has been investigated in only one study with elite IRONMAN triathletes. We have, however, no knowledge of how professional triathletes pace during an IRONMAN World Championship. To investigate the split-by-split speed, pacing strategies and pacing variability in professional female and male IRONMAN World Championship participants in the fastest IRONMAN World Championship ever in IRONMAN Hawaii 2022. For both cycling and running, 25 specific split times were recorded in each discipline. The best 30 men and 30 women overall were chosen from the official IRONMAN website database for further analysis. They were divided into three performance groups: Top 10, 11-20th place, and 21st-30th place. Mean speed, individual linear regressions with the corresponding correlation coefficients, and coefficient of variation were calculated to assess split-by-split speed, pacing strategies, and pacing variability, respectively. In both men's and women's cycling and running segments, the top ten participants exhibited faster split times compared to the slower performance groups. Notably, no discernible differences existed between the 11-20th and 21st-30th place in men's cycling and women's running times. Conversely, in men's running and women's cycling segments, those in the 11-20th place displayed quicker times than those in the 21st-30th place. In the cycling segment across all groups, men demonstrated a more negative pacing pattern (indicating an increase in speed), whereas women exhibited more consistent pacing. In the running segment, the top 10 men and all women's groups showcased relatively similar slightly positive pacing profiles. However, men ranking 11-20th and 21st-30th displayed more pronounced positive pacing strategies, implying a more significant decline in speed over time. In terms of cycling, the variability in pacing remained relatively consistent across the three performance groups. Conversely, during the running segment, the top ten male triathletes and those in the 11-20th place displayed lower pacing variability than their counterparts in the 21st-30th position place and all women's groups. In summary, performance and pacing were examined in professional male and female IRONMAN World Championship participants during IRONMAN Hawaii 2022. Top performers showed faster cycling and running split times, with differences in pacing strategies between sexes. The pacing was more consistent in cycling, while running pacing varied more, particularly among male triathletes in different performance groups.

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.

Effects of Age on Physical Match Performance in Professional Soccer Players

ABSTRACT

Rey, E, Costa, PB, Corredoira, FJ, and Sal de Rellán Guerra, A. Effects of age on physical match performance in professional soccer players. J Strength Cond Res 35(10): 2790-2795, 2021-This study aimed to evaluate the effects of age using a large-scale analysis of match physical performance in professional soccer players. A total of 10,739 individual match observations were undertaken on outfield players competing in the first and second divisions of the Spanish soccer professional leagues during the 2017-2018 season, using a computerized tracking system (TRACAB, Chyronhego, New York, NY). The players were classified into five positions and into 5 age groups (<20 years, 20-24.9 years, 25-29.9 years, 30-34.9 years, and ≥35 years). The results showed that (a) professional soccer players aged ≥30 years exhibit a significant decrease ( p < 0.01) in the total distance covered, medium-speed running distance, high-speed running (HSR) distance, very HSR (VHSR) distance, sprint distance, and maximum running speed compared with younger players (<30 years); (b) professional soccer players aged ≥35 years exhibit a significant decrease ( p < 0.01) in the number of HSR, number of VHSR, and number of sprints compared with younger players (<35 years); and (c) all playing positions reduced their physical performance; however, external midfielders were less affected by age effects. In conclusion, this study demonstrates players' physical match performance reduces with increasing age. Such findings may help coaches and managers to better understand the effects of age on match-related physical performance and may have the potential to assist in decisions regarding recruitment and player list management within professional soccer clubs.

Relationship between running performance and weather in elite marathoners competing in the New York City Marathon

It is well known that weather and pacing have an influence on elite marathon performance. However, there is limited knowledge about the effect of weather on running speed in elite marathoners. The aim of the present cross-sectional study was to investigate potential associations between running speed and weather variables in elite runners competing in the 'New York City Marathon' between 1999 and 2019. Data from all official female and male finishers with name, sex, age, calendar year, split times at 5 km, 10 km, 15 km, 20 km, 25 km, 30 km, 35 km, 40 km and finish and hourly values for temperature (°Celsius), barometric pressure (hPa), humidity (%) and sunshine duration (min) between 09:00 a.m. and 04:00 p.m. were obtained from official websites. A total of 560,731 marathon runners' records were available for analysis (342,799 men and 217,932 women). Pearson and Spearman correlation analyses were performed between the average running speed and the weather variables (temperature, pressure, humidity and sunshine). Ordinary Least Squares (OLS) regressions were also performed. The runner´s records were classified into four performance groups (all runners, top 100, top 10 and top 3) for comparison. Differences in running speed between the four performance groups were statistically significant (p < 0.05) for both men and women. Pearson (linear) correlation indicated a weak and positive association with humidity in the top 10 (r = 0.16) and top 3 (r = 0.13) performance groups that the running speed of the elite runners was positively correlated with humidity. Regarding sunshine duration, there was a weak and positive correlation with the running speed of the elite groups (r = 0.16 in the top 10 and r = 0.2 in the top 3). Spearman correlation (non-linear) identified a weak but negative correlation coefficient with temperature in all runners' groups. Also, non-linear positive correlation coefficients with humidity and sunshine can be observed in the Spearman matrixes. A Multivariate Ordinary Least Squares (OLS) regression analysis showed no predictive power of weather factors. For elite runners competing in the 'New York City Marathon' between 1999 and 2019, the main findings were that elite runners became faster with increasing humidity and sunshine duration while overall runners became slower with increasing temperature, increasing humidity and sunshine duration. Weather factors affected running speed and results but did not provide a significant predictive influence on performance.

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.

Pacing and packing behavior in elite and world record performances at Berlin marathon

The aim of this study was to compare pacing and packing behaviors between sex and performance level at elite Berlin marathon races. Official electronic split and finishing times from 279 (149 male and 130 female) marathon performances, including 5 male world records, were obtained from eleven Berlin marathon races held from 2008 to 2018, and from two previous world records and the second world all-time fastest performance also achieved at that same Berlin course. Male performances displaying an even pacing behavior were significantly faster than those adopting a positive behavior (p < 0.001; d = 0.75). Male world records were characterized by even profiles with fast endspurts, being especially remarkable at world all-time two fastest performances which were assisted by the use of a new shoe technology. Female marathon runners decreased their speed less than men during the second half marathon and especially from the 35^th km onwards (p < 0.001; 0.51 ≤ d≤0.55). The latest race stages were usually run individually in both sexes. Significant pace differences between performance groups at every race segment were found in women (p < 0.01; 1.0 ≤ d≤2.0), who also covered an important part of the race alone. Prior to participation in meet marathon races such as Berlin marathon, elite runners should select the group that they will join during the race according to their current performance level as a preassigned pace set by a pacemaker will be adopted. Therefore, they could follow an even rather than positive pacing behavior which will allow them to achieve a more optimal performance.

Gender and Age Differences in Performance of Over 70,000 Chinese Finishers in the Half- and Full-Marathon Events

(1) Background: The aim of the present study was to examine the characteristics of over 70,000 long-distance finishers over the last four years in Chinese half- and full-marathon events; (2) Methods: The available data of all finishers (n = 73,485; women, n = 17,134; men, n = 56,351) who performed half- and full-marathon events in Hangzhou from 2016 to 2019 were further analyzed for the characteristics of gender, age and average running speed; (3) Results: The total men-to-women ratio was the lowest in the half-marathon event (1.86) and the highest in the full-marathon event (17.42). Faster running performance in males than in females and faster average running speed in short-distance runners were shown. Gender and race distance were observed to have the most significant effects on average running speed (p < 0.01). For both male and female finishers, the slowest running speed was shown in older age groups (p < 0.01) during the full marathon. Our results indicated that the gender difference in performance was attenuated in the longer race distances and older age groups; (4) Conclusions: Understanding the participation and performances across different running distances would provide insights into physiological and biomechanical characteristics for training protocols and sports gear development in different groups.

Consistency of pacing profile according to performance level in three different editions of the Chicago, London, and Tokyo marathons

Running pacing has become a focus of interest over recent years due to its relationship with performance, however, it is still unknown the consistency of each race in different editions. The aim of this study is to analyze the consistency of pacing profile in three consecutive editions of three marathon races. A database of 282,808 runners, compiled from three different races (Chicago, London, and Tokyo Marathon) and three editions (2017, 2018, and 2019) was analyzed. Participants were categorized according to their time performance in the marathon, every 30 min from 2:30 h to sub-6 h. The relative speed of each section for each runner was calculated as a percentage of the average speed for the entire race. The intraclass correlation coefficients (ICC) of relative speed at the different pacing section, taking into account the runner time categories, was excellent over the three marathon editions (ICC > 0.93). The artificial intelligence model showed an accuracy of 86.8% to classify the runners' data in three marathons, suggesting a consistency between editions with identifiable differences between races. In conclusion, although some differences have been observed between editions in certain sections and marathon runner categories, excellent consistency of the pacing profile was observed. The study of pacing profile in a specific marathon can, therefore, be helpful for runners, coaches and marathon organizers for planning the race and improving its organization.

The Influence of Environmental Conditions on Pacing in Age Group Marathoners Competing in the “New York City Marathon”

Background: The two aspects of the influence of environmental conditions on marathon running performance and pacing during a marathon have been separately and widely investigated. The influence of environmental conditions on the pacing of age group marathoners has, however, not been considered yet.

Objective: The aim of the present study was to investigate the association between environmental conditions (i.e., temperature, barometric pressure, humidity, precipitation, sunshine, and cloud cover), gender and pacing of age group marathoners in the “New York City Marathon”.

Methodology: Between 1999 and 2019, a total of 830,255 finishes (526,500 males and 303,755 females) were recorded. Time-adjusted averages of weather conditions for temperature, barometric pressure, humidity, and sunshine duration during the race were correlated with running speed in 5 km-intervals for age group runners in 10 years-intervals.

Results: The running speed decreased with increasing temperatures in athletes of age groups 20–59 with a pronounced negative effect for men aged 30–64 years and women aged 40–64 years. Higher levels of humidity were associated with faster running speeds for both sexes. Sunshine duration and barometric pressure showed no association with running speed.

Conclusion: In summary, temperature and humidity affect pacing in age group marathoners differently. Specifically, increasing temperature slowed down runners of both sexes aged between 20 and 59 years, whereas increasing humidity slowed down runners of &lt;20 and &gt;80 years old.

Influence of advanced shoe technology on the top 100 annual performances in men's marathon from 2015 to 2019

The NIKE Vaporfly shoe was introduced in May 2017 as part of the original #Breaking2 Project (an event aimed to run the first marathon under 2 h). This new advanced shoe technology (NAST) changed the footwear design conception. The aim of this study was (i) to analyse the effect of NAST in men's marathon performance, (ii) to analyse whether the changes in the environmental constraints (temperature and wind) and orography of the marathons, age and birthplace of the runners has changed from 2015 to 2019 and (iii) to analyse the impact of NAST on the historical 50 best performances. Data from top-100 men's marathon performances were collected in that timeframe. The shoes used by the athletes were identified (in 91.8% of the cases) by publicly available photographs. External and environmental conditions of each marathon and age and birthplace of the runners were also analysed. Marathon performances improved from 2017 onwards between 0.75 and 1.50% compared to 2015 and 2016 (p < 0.05). In addition, the improvement was greater in the upper deciles than in the lower ones (p < 0.001). Runners wearing NAST ran ~ 1% faster in marathon compared to runners that did not use it (p < 0.001). When conducting an individual analysis of athletes who ran with and without NAST, 72.5% of the athletes who completed a marathon wearing NAST improved their performance by 0.68% (p < 0.01). External and environmental conditions, age or birthplace of runners seems not to have influenced this performance improvement. NAST has had a clear impact on marathon performance unchanged in the environmental constraints (temperature and wind), orography, age, and birthplace of the runners but with differences between venues.

Pacing in Long-Distance Running: Sex and Age Differences in 10-km Race and Marathon

Background and objective: The recent availability of data from mass-participation running events has allowed researchers to examine pacing from the perspective of non-elite distance runners. Based on an extensive analysis of the literature, we concluded that no study utilizing mass-participation events data has ever directly compared pacing in the 10-km race, with other long-distance races. Therefore, the main aim of this study was to assess and compare pacing between 10-km runners and marathoners, in regards to their sex and age. Materials and methods: For the purpose of this study, official results from the Oslo marathon (n = 8828) and 10-km race (n = 16,315) held from 2015 to 2018 were included. Results: Both 10-km runners and marathoners showed positive pacing strategies. Moreover, two-way analysis of variance showed that women were less likely to slow in the marathon than men (9.85% in comparison to 12.70%) however, not in the 10-km race (3.99% in comparison to 3.38%). Finally, pace changing is more prominent in youngest and oldest marathoners comparing to the other age groups (12.55% in comparison to 10.96%). Conclusions: Based on these findings, practitioners should adopt different training programmes for marathoners in comparison to shorter long-distance runners.

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.

Different race pacing strategies among runners covering the 2017 Berlin Marathon under 3 hours and 30 minutes

The purposes of this study were 1) to analyse the different pacing behaviours based on athlete's performance and 2) to determine whether significant differences in each race split and the runner's performance implied different race profiles. A total of 2295 runners, which took part in Berlin's marathon (2017), met the inclusion criteria. 4 different groups were created based on sex and performance. Men: Elite (<02:19:00 h), Top 1 (<02:30:00 h), Top 2 (<02:45:00 h) and Top 3 (<03:00:00 h); women: Elite (02:45:00 h), Top 1 (<03:00:00 h), Top 2 (<03:15:00 h), Top 3 (<03:30:00 h). With the aim of comparing the pacing between sex and performance the average speed was normalized. In men, no statistically significant changes were found between performance group and splits. A large number of significant differences between splits and groups were found amongst women: 5-10 km Top 2 vs Top 3 (P = 0.0178), 10-15 km Top1 vs Top 2 (P = 0.0211), 15-20 km Top1 vs Top 2 (P = 0.0382), 20-21.1 km Elite vs Top 2 (P = 0.0129); Elite vs Top 3 (P = 0.0020); Top1 vs Top 2 (P = 0.0233); Top 1 vs Top 3 (P = 0.0007), 25-30 km Elite vs Top 2 (P = 0.0273); Elite vs Top 3 (P = 0.0156), 30-35 km Elite vs Top 2 (P = 0.0096); Top 1 vs Top 2 (P = 0.0198); Top2 vs Top3 (P = 0.0069). In men there were little significant differences based on athletes' performance which implied a similar pacing behaviour. Women presented numerous differences based on their performance which suggested different pacing behaviours.

Devising a Pace-Based Definition for "The Wall": An Observational Analysis of Marathoners' Subjective Experiences of Fatigue

CONTEXT

Many runners report "hitting The Wall" (HTW) during a marathon (42.2 km). However, the performance manifestation of this subjectively experienced phenomenon remains unclear.

OBJECTIVE

To identify a pace-based classification for HTW by integrating subjective reports of fatigue and runners' pacing profiles during a marathon.

DESIGN

Cross-sectional study.

SETTING

Public race event (2018 Dublin Marathon).

PATIENTS OR OTHER PARTICIPANTS

Eighty-three runners (28 [34%] women, 55 [66%] men, age = 41.5 ± 9.1 years, height = 1.73 ± 0.09 m, mass = 70.2 ± 10.1 kg).

MAIN OUTCOME MEASURE(S)

The pacing profiles for respondents to our postrace questionnaire that concerned the phenomenon of HTW were evaluated. Receiver operating characteristic analyses were performed on discretized outcomes of the time series of marathoners' paces during the race.

RESULTS

Using the receiver operating characteristic analyses, we observed that runners could be classified as having experienced HTW if they ran any 1-km segment 11% slower than the average of the remaining segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.6) or if the standard deviation of the normalized 1-km split times exceeded 0.0532 (accuracy = 83%, sensitivity = 0.818, specificity = 0.8). Similarly, runners could be classified as having experienced HTW if they ran any 5-km segment 7.3% slower than the average of the remaining 5-km segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.644) or if the standard deviation of the normalized 5-km split times exceeded 0.0346 (accuracy = 82%, sensitivity = 0.909, specificity = 0.622).

CONCLUSIONS

These pace-based criteria could be valuable to researchers evaluating HTW prevalence in cohorts for whom they lack subjective questionnaire data.

Changes in performances/characteristics of French female runners over the last 12 years

This study investigated the changes in performance of five official track running distances (800m, 1500m, 3000m, 5000m and 10,000m) and the characteristics of French female runners between 2005 and 2016. 22,839 official track performances were scrutinized. For each performance, the race time, the indication of personal record, age, and performance level were recorded. The main results showed that: (1) the number of French track performances has increased in recent years (except for the 10,000m) and the level of these performances has improved significantly only for the longer distances (5000 and 10,000m), (2) the longest distances were generally performed by older athletes, and (3) the highest percentage of international athletes was for the 10,000m event. These findings may be explained by: (1) the development plan put into place by the Fédération France d'Athlétisme, (2) age-dependent physiological and psychological factors and environmental conditions, and (3) the minima to access the international level.

An evaluation of the training determinants of marathon performance: A meta-analysis with meta-regression

OBJECTIVES

Marathoners rely on expert-opinion and the anecdotal advice of their peers when devising their training plans for an upcoming race. The accumulation of results from multiple scientific studies has the potential to clarify the precise training requirements for the marathon. The purpose of the present study was to perform a systematic review, meta-analysis and meta-regression of available literature to determine if a dose-response relationship exists between a series of training behaviours and marathon performance.

DESIGN

Systematic review, meta-analysis and meta-regression.

METHODS

A systematic search of multiple literature sources was undertaken to identify observational and interventional studies of elite and recreational marathon (42.2km) runners.

RESULTS

Eighty-five studies which included 137 cohorts of runners (25% female) were included in the meta-regression, with average weekly running distance, number of weekly runs, maximum running distance completed in a single week, number of runs ≥32km completed in the pre-marathon training block, average running pace during training, distance of the longest run and hours of running per week used as covariates. Separately conducted univariate random effects meta-regression models identified a negative statistical association between each of the above listed training behaviours and marathon performance (R² 0.38-0.81, p<0.001), whereby increases in a given training parameter coincided with faster marathon finish times. Meta-analysis revealed the rate of non-finishers in the marathon was 7.27% (95% CI 6.09%-8.65%).

CONCLUSIONS

These data can be used by athletes and coaches to inform the development of marathon training regimes that are specific to a given target finish time.

Multimodal approach towards understanding the changes in the autonomic nervous system induced by an ultramarathon

Purpose: Running an ultramarathon can be considered as a multifaceted, intense stressor inducing changes within the autonomic nervous system (ANS). The aim of this study was to examine changes within and across ANS modalities in response to an ultramarathon.Methods: Thirteen runners (44.3 ± 5.9 years) completed a 65 km run. Electrodermal activity (EDA), heart rate (HR), and skin temperature measured at wrist (Temp), were recorded before and after running. Three-minute intervals were analysed. Mean values were compared by t-tests for dependent samples. Joint principal component analysis-canonical correlation analysis (PCA-CCA) and multiset CCA techniques were employed to measure the interactions between either any two or among all modalities.Results: HR (p < 0.01) and EDA (p < 0.01) increased, while Temp decreased (p < 0.01). PCA-CCA revealed one significant component (p < 0.05) for each modality pair in pre and post measures. Component strength increased from pre (mean = 0.73) to post (mean = 0.92) test. Multiset CCA supported the assumption of increasing strength of correlations across modalities.Conclusion: Ultramarathon, an intense physical stressor, increases correlations across modalities pointing towards a reorganization of central ANS control to restore dynamic balance after physical load. This characterization of ANS-states might offer new avenues for training control.

Age Differences in Pacing in Endurance Running: Comparison between Marathon and Half-MarathonMen and Women

Background and Objective: The increased popularity of marathons and half-marathons has led to a significant increase in the number of master runners worldwide. Since the age-related decrease in performance is dependent on race duration, pacing in long distance running might also vary by race distance in both men and women. Therefore, the main aim of this study was to assess pacing differences between marathon and half-marathon runners with regard to the runners’ age group, and independently for men and women. Materials and Methods: In total, 17,465 participants in the Vienna City marathon in 2017 were considered for this study (marathon, N = 6081; half-marathon, N = 11,384). Pacing was expressed as two variables (i.e., pace range and end spurt). Results: All runners showed positive pacing strategies (i.e., a fast start with gradual decrease of speed). However, marathon runners showed greater variability in pacing than half-marathon runners. Furthermore, women showed no differences in pace variability in regard to the age group, whereas men younger than 30 years of age, as well as older men (over the age of 60), showed a greater variability in pace than other age groups. Finally, younger half-marathon men and women showed the fastest end spurt compared to older age groups and marathon runners. Conclusions: The presented findings could help sports and medicine practitioners to create age specific training plans and pacing strategies. This approach could help long distance runners to improve their physical fitness, achieve better race times, reduce the potential risk of musculoskeletal injuries and increase the overall pleasure of long distance running.

Performance and Pacing of Age Groups in Half-Marathon and Marathon

The aim of the present study was to examine the age-related differences in performance and pacing in a half-marathon compared to a marathon. All finishers (n = 9137) in the Ljubljana 2017 half-marathon (n = 7258) and marathon (n = 1853) with available data on split times during the races, were analysed for pacing. Half-marathoners were slower than marathoners among women, (2.77 ± 0.35 versus 2.86 ± 0.39 m·s⁻¹ respectively, p < 0.001), but faster among men (3.14 ± 0.45 versus 3.08 ± 0.46 m·s⁻¹ respectively, p < 0.001). In both race distances, the <25 age group was the fastest and the >54 age group the slowest (p < 0.001). All age groups presented a positive pacing in both race distances and genders, with each segment being slower than the previous one. However, an end spurt was observed in the marathon, but not in the half-marathon. A more even pace in the half-marathon than in the marathon was shown for most age groups. In summary, age-group finishers in the half-marathon decreased running speed across the race, presented a more even pacing than marathoners, and did not show an end spurt.

Force-velocity characteristics and maximal anaerobic power in male recreational marathon runners

The aim of the present study was to examine the relationship of force-velocity (F-v) characteristics with age and race time in marathon runners. One hundred thirty-five male marathon runners (age 44.2 ± 8.8 years, height 176 ± 6 cm, body mass 24.7 ± 2.6 kg.m^-2 and personal record 4:02 ± 0:45 h:min), separated into eight age groups (<30, 30-35, ., 55-60, >60 years), performed an F-v test on a cycle ergometer consisted of four 7s sprints. The older age groups had the lowest scores in maximal pedalling velocity (v₀; p < 0.001, η_p² = 0.244), relative (rPmax; p = 0.001, η_p² = 0.176) and absolute maximal power (Pmax; p = 0.009, η_p² = 0.135), whereas no difference in maximal force (F₀; p = 0.558, η_p² = 0.044) was shown. Race time correlated moderately with F₀ (r = 0.31, p < 0.001) and Pmax (r = 0.30, p = 0.001). The small magnitude of age-related differences in anaerobic power among most age groups indicated that humans without muscle strength/power training might maintain anaerobic power indices till their sixties.

The Effect of Aging on Pacing Strategies in Short and Long Distance Duathlon

Background/Study context: Many studies have been conducted on the triathlon during the last several years; however, less information exists with regards to duathlon (i.e., Run 1, Bike and Run 2). The aim of the present study was to examine the effect of age on pacing (i.e., the relative contribution - % - of each discipline and transition times - Transition 1 and Transition 2 - to overall race time) of duathletes competing either to short (i.e., 10 km Run 1, 50 km Bike and 5 km Run 2) or long distance (i.e., 10 km Run 1, 150 km Bike and 30 km Run 2).

METHODS

We analyzed 6,671 finishes (women's, n= 1,037, age 36.6 ± 9.1 years; men's, n= 5,634, 40.0 ± 10.0 years) of 3,881 duathletes competing in 'Powerman Zofingen', the World Championship, from 2003 to 2017, in both the short and the long distance race.

RESULTS

A large discipline×distance interaction on relative time (%) was observed in the short distance (p < .001, η²_p = .936); 24.7%, 57.4%, and 15.8% were spent in Run 1, Bike, and Run 2, respectively. In the long distance, the relative contribution of disciplines was 8.0%, 59.0%, and 32.1%, respectively. A trivial discipline×sex interaction on relative time (%) was shown in the short (p < .001, η²_p = .007) and long distance (p < .001, η²_p = .016). In the short distance, a small discipline×age group interaction on relative time (%) was found (p < .001, η²_p = .030) with younger age groups spending less time (%) in Run 1, Transition 1 and Transition 2, and older groups less time (%) in Bike and Run 2. In the long distance, a moderate discipline×age group interaction on relative time (%) was observed (p < .001, η²_p = .077) with younger age groups spending less time (%) in Run 1, Transition 1, Transition 2 and Run 2, and older groups less time (%) in Bike.

CONCLUSIONS

These findings suggest that younger duathletes are relatively faster in Run 1 and transitions, and older duathletes in Bike in both distances. However, older duathletes are relatively faster in Run 2 in the short distance and younger duathletes are relatively faster in Run 2 in the long distance. The magnitude of the combined effect of discipline and age group on pacing was larger in the long than in the short distance. Therefore, athletes and coaches should be aware of the variation of pacing by age group and distance of a duathlon race such as 'Powerman Zofingen'.

Men vs. women world marathon records' pacing strategies from 1998 to 2018

The aim of this study was to analyse the pacing strategies adopted by elite male and female marathon runners when setting every world record since 1998. For data analysis, the total distance of the marathon was divided into eight sections of 5 km and a final section of 2.195 km, and the relative average speed of each section was calculated individually. Female athletes maintained similar speeds in the first and second half of the marathon (ES = 0.22, small effect, p = 0.705), whereas male athletes increased their speed as the marathon progressed (ES = 1.18, moderate effect, p = 0.011). However, no differences were observed between men and women in either the first (ES = 0.56, small effect, p = 0.290), or in the second half of the marathon (ES = 0.60, moderate effect, p = 0.266). When comparing the women's world records (1998-2003) vs. men's records (1998-2018) by sections, we observed differences at the beginning of the race (second section, ES = 0.89, moderate effect) and at the end (last section, ES = 0.87, moderate effect). The pace variations during the race were similar between male athletes and that of women with male pacemakers (1.53% ± 0.60 vs. 1.68% ± 0.84, respectively). However, a trend towards higher pace variations during the race in the female records with female pacemakers was observed (2.28% ± 0.95). This study shows how male and female marathon records in the last 20 years have been set using different pacing strategies. While men used a negative strategy (faster finishing), women used a less uniform pacing strategy.

Sex differences in pacing during half-marathon and marathon race

The main aim of the present study was to examine differences in pacing between half-marathon and marathon in men and women. A total of 17,525 finishers in the marathon (n = 4807 men; n = 1278 women) and half-marathon race (n = 7624 men; n = 3816 women) in Vienna 2017 were considered. Their pacing was assessed through 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. Compared to marathon (where absolute average change of speed [ACS] was 5.46% and 4.12% in men and women, respectively), a more even pacing was observed in half-marathon in both sexes (ACS = 3.60% and 3.36% in men and women, respectively). The more even pacing in women previously observed in marathon races was verified in half-marathon, too. However, the sex difference in pacing was smaller in half-marathon than in marathon. Since men and women endurance runners participate in both races, sport practitioners would have great benefit from these results since they could establish sex-based personalized race strategies and training programmes.

The "New York City Marathon": participation and performance trends of 1.2M runners during half-century

The aim of the present study was to examine trends in participation, performance, age and nationality during a ~ 50-years period in the largest dataset ever studied in the "New York City Marathon". We analysed 1,174,331 finishers (women, n= 349,145, age 39.7 ± 8.7 years; men, n= 825,186, 41.7 ± 9.2 years). The overall participation increased across calendar years for all nationalities, and this increase was more pronounced in women, which resulted in a decreasing men-to-women ratio. Men were faster and older than women. Ethiopians and Kenyans were the fastest and youngest in women and men, respectively. Japanese were the slowest and Germans were the oldest in both sexes. Race time increased across years. Coaches and fitness trainers should be aware of these trends and should emphasize the development of training programs for older and slower runners.

Exercise-Associated Hyponatremia During a Self-Paced Marathon Attempt in a 15-Year-Old Male Teenager

Background and objective: The increased participation in endurance sports such as marathon running has attracted scientific interest especially with regard to adult athletes. However, few studies have examined the impact of a marathon race on children and adolescents. Therefore, the aim of the present case study was two-fold: first, to describe pacing during a marathon race, and second, to examine acute responses of blood physiology and biochemistry parameters during the race (i.e., pre- and post-race) as well as five consecutive days after the race. Materials and Methods: Participant was a 15-year-old boy who completed a self-paced marathon attempt for the first time and finished in 5 h 19 m 53 s. Positive pacing (i.e., a running speed that decreased throughout race) with a final end spurt was observed. Results: An increase in fluid intake across race was shown. Exercise-associated hyponatremia (EAH, i.e., plasma sodium concentration <135 mmol/L) was found post-race. C-reactive protein (CRP) did not correlate either with creatine kinase (CK) (r = 0.457, p = 0.302) or with lactate dehydrogenase (LDH) (r = 0.156, p = 0.739); however, leukocytes correlated very largely with LDH (r = 0.889, p = 0.007) but not with CK (r = 0.696, p = 0.082). CK and LDH related almost perfectly with creatinine (r = 0.937, p = 0.002 and r = 0.959, p = 0.001, respectively); also, creatinine clearance correlated very largely with CK (r = −0.782, p = 0.038) but not with LDH (r = −0.733, p = 0.061). Leukocytes, aspartate aminotransferase, LDH, and CK deviated from physiological range post-race, but returned to normal values during the five-day recovery period. Conclusions: In summary, a male teenager at the age of 15 years was able to run a marathon in under 6 h without significant harmful effects on health. He developed mild and asymptomatic EAH and an increase in leucocytes, CRP, CK, and LDH as markers of inflammation and skeletal muscle damage. EAH after the marathon was resolved within one day of recovery.

The Combined Effect of Aging and Performance Level on Pacing in Duathlon - the "ITU Powerman Long Distance Duathlon World Championships"

The role of age and performance level has been investigated in runners such as marathoners, but not in multi-sports athletes such as duathletes (running, cycling, and running). Thus, the aim of the present study was to examine the combined effects of aging and performance level on pacing of duathletes competing in two different race distances. Pacing (defined as the relative contribution of cycling time, %, to the overall race time) was analyzed for 6,671 duathletes competing from 2003 to 2017 in the short distance race (10 km first run, 50 km cycling and 5 km second run) or long distance race (10 km first run, 150 km cycling and 30 km second run) of “Powerman Zofingen,” the “ITU Powerman Long Distance Duathlon World Championships.” Men were faster, older, and spent less time (%) in cycling than women in both distances races (p < 0.001). Younger age groups spent more time (%) in cycling than their older counterparts in women (both short and long distance, p = 0.036, η_p² = 0.031, p = 0.025, η_p² = 0.044, respectively) and men (long distance race, p < 0.001, η_p² = 0.016). Fast performance groups spent more time (%) in cycling than their slower counterparts in short (women, p < 0.001, η_p² = 0.057; men, p < 0.001, η_p² = 0.035) and long distance (women, p < 0.001, η_p² = 0.070; men, p < 0.001, η_p² = 0.052). A small age group × performance group interaction on cycling time (%) was observed in the men’s short distance (p = 0.001, η_p² = 0.020) – but not in the long distance or in women – with smaller differences between performance groups in the older than in the younger age groups. Women, young and fast duathletes were relatively slower in cycling than men, old and slow duathletes; that was, old duathletes were relatively faster in cycling than in running. Moreover, there was indication that the difference in pacing among performance groups might be attenuated with aging. Since fast duathletes were relatively faster in running than in cycling, slow duathletes should be encouraged to cycle slower and run faster.

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 and Physiological Response After a 12-Hour Ultra-Marathon in a 95-Year-Old Male Runner

In recent years, outstanding performances of elderly people up to 100 years have been reported. In this case study, pacing during and recovery after a 12-h ultra-marathon were described for a 95-year old runner. The athlete achieved a total distance of 52.987 km. Pacing followed a parabolic pattern (U-shaped), where the speed decreased till the middle of the race and then increased. However, no end spurt was observed. A large main effect of lap quartile on speed was observed, where the second quartile was slower than the first quartile and forth. The smallest variability was shown in the first quartile and the largest in the second quartile. During recovery, erythrocytes, hemoglobin and hematocrit increased whereas thrombocytes and leucocytes decreased. CRP, GOT, GPT, y-GT, CK, and LDH were increased post-race and decreased to reference range during recovery. Also, creatinine and urea decreased during recovery. Creatinine clearance increased during recovery. Sodium increased during recovery and remained constantly within the reference range. During recovery body fat and visceral fat mass decreased, whereas body water and lean body mass increased. In summary, a 95-year-old man was able to run during 12 h using a U-shaped pacing and achieving a total distance of nearly 53 km. Increased selected hematological and biochemical parameters returned to pre-race values within a recovery phase of 5 days.

The effect of sex, age and performance level on pacing of Ironman triathletes

The aim of the present study was to examine the effect of sex, age and performance level on pacing of Ironman triathletes. Split times (i.e. swimming, cycling, and running) and overall race times of 343,345 athletes competing between 2002 and 2015 in 253 different Ironman triathlon races were analyzed. Participants were classified into nine performance groups according to their overall race time. Times in swimming, cycling, running and transition were expressed as percentage of the overall race time. Women spent relatively less time (%) in swimming, running and transition time, and more time (%) in cycling than men (p < 0.001). The fastest performance group was relatively faster in running (34.8 ± 1.4 versus 40.3 ± 3.0%, η²= 0.098) and transition time (0.9 ± 0.3 versus 2.2 ± 0.6%, η²= 0.178), and relatively slower in swimming (10.2 ± 0.8 versus 9.8 ± 1.5%, η²= 0.018) and cycling (54.1 ± 1.4 versus 47.8 ± 2.8%, η²= 0.138) than the slowest performance group (p < 0.001). The younger age groups were relatively faster in swimming, running and transition time, but relatively slower in cycling. In summary, the fastest Ironman triathletes were the relatively fastest in running and transition times. Thus, race tactics in an Ironman triathlon should focus on saving energy during swimming and cycling for the running split.

Pacing Strategies in the 'Athens Classic Marathon': Physiological and Psychological Aspects

Despite the increased scientific interest in the relationship between pacing and performance in marathon running, little information is available about the association of pacing with physiological and psychological parameters. Therefore, the aim of the present study was to examine the role physical fitness and training characteristics on pacing in the 'Athens Classic Marathon.' Finishers in this race in 2017 (women, n = 26, age 40.8 ± 9.4 years; men, n = 130, age 44.1 ± 8.6 years) were analyzed for their pacing during the race, completed the Motivation of Marathon Scale (MOMS) and performed a series of physiological tests. Women and faster recreational runners adopted a more even pacing. A more even pacing was related with a higher aerobic capacity and lower muscle strength in men, but not in women. Men with more even pacing scored higher in psychological coping, self-esteem, life meaning, recognition and competition than their counterparts with less even pacing. Considering the increasing number of participants in marathon races, these findings might help a wide range of professionals (fitness trainers, physiologists, and psychologists) working with runners to optimize the pacing of their athletes.

Pacing and Changes in Body Composition in 48 h Ultra-Endurance Running-A Case Study

Pacing has been investigated in elite and master runners competing in marathon and ultra-marathon races up to 100 km and 100 miles, but not in longer ultra-marathons. In this case study, a 54-year-old master ultra-marathoner—intending to achieve as many kilometers as possible in a 48 h run—was examined. The changes in running speed during the race and selected anthropometric characteristics using bioelectrical impedance analysis (i.e., body mass and body water), during and after the race, were analyzed. The runner achieved a total distance of 230 km and running speed decreased non-linearly during the race. Body mass decreased, while percent body water increased, non-linearly, across the race. There was no statistically significant relationship between the decrease in body mass and the increase in percent body water. Considering the popularity of ultra-endurance running races, the findings of the present study offered valuable insight in the pacing and changes of body mass and body water during a 48 h run, and this information can be used by ultra-endurance runners and practitioners working with them.

Jumping and throwing performance in the World Masters' Athletic Championships 1975-2016

Participation and performance of elite age group athletes from 35-39 to 95-99 years competing in World Masters Athletics (WMA) Championships 1975-2016 were examined for throwing (discus, hammer, javelin and shot put) and jumping (high jump, long jump, pole vault and triple jump) events. Overall, 21,723 observations from 8,974 master athletes were analysed. A mixed regression model with sex, age group, calendar year and interactions terms (sex-age group; sex-year) defined as fixed effects was performed for each event separately. Performances over time were increasing overall for each event, with a cubic trend. Compared with women, men had better performances (e.g. in triple jump the estimated difference was 3.378 meters, p < 0.001). However, women improved their performance more than men across calendar years. Performances declined with age for each event (e.g. in triple jump, compared with age group 45-49 years, performance in age group 35-39 years was 1.041 meter better and in age group 85-89 years was 5.342 meter worse). In summary, performance in jumping and throwing events of WMA Championships improved across calendar years, whereas the decline of performance with age was dependent on sex and event.

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.

Pacing in a 94-year-old runner during a 6-hour run

It is well known that elderly people up to 90 years of age are able to finish a marathon. We have no knowledge, however, how runners at the age of 90 years or older pace during a long run. In this case report, we describe the pacing of a 94-year-old man competing in a 6-hour run in order to prepare for a marathon at the age of 95 years in category M95. In the “6-Stunden-Lauf ” held in Brugg, Switzerland, participants have to run as many laps of 0.934 km as possible on a completely flat circuit within 6 hours to achieve as many kilometers as possible. Before and after the competition we measured body weight, percentage of body fat, fat-free mass and percentage of body water using a bioelectrical impedance scale. On the day before the start, 24 hours after the finish and then every 24 hours for the following 4 days, capillary blood samples at a fingertip were drawn to determine hemoglobin, hematocrit, leukocytes, platelets, C-reactive protein, creatine kinase, creatinine and potassium and sodium. The runner achieved 26 laps during the 6 hours, equal to 24.304 km. Lap times increased continuously and running speed decreased nearly linearly. A large main effect of time point (hours) of the race on running speed was observed (p=0.015, η²=0.48) with running speed being slower in the last hour than that in the first hour (3.5±1.4 km/h versus 5.3±0.4 km/h). Body mass decreased by 0.6%, percent body fat by 1.4% and fat-free mass by 0.7%. During recovery, hemoglobin, hematocrit and the number of thrombocytes increased, whereas the number of leukocytes remained unchanged. C-reactive protein was highest on day 1 after the race and decreased by day 4 nearly to zero. Creatine kinase was slightly elevated pre-race, highest the day after the race and remained slightly elevated until day 4. Creatinine and potassium were increased pre-race but returned to normal values during recovery. Sodium remained within normal values on all days. Based on the linear decrease in running speed, we extrapolated for the marathon distance to run a marathon in age group M95 (i.e., male marathoners aged 95–99 years). In the worst-case scenario (i.e., the athlete develops maximal fatigue), he would stop the race before 40 km, in the best scenario (i.e., the athlete develops minimal fatigue), he would achieve an overall race time of ~8.3 hours and in the most probable scenario (i.e., the athlete can continue in the same manner), the final race time will be longer than 11 hours.