A Descriptive Analysis of the Seasonal Patterns of Bone Stress Injury Incidence in Division I Collegiate Distance Runners

BACKGROUND

A bone stress injury (BSI) is a common overuse injury in collegiate athletes, particularly cross-country and track and field runners. Limited work describes the seasonality of BSIs or the differences in rates and anatomic locations of BSIs in collegiate runners.

PURPOSE

To describe seasonally related trends in anatomic locations of BSIs in National Collegiate Athletic Association (NCAA) Division I male and female middle- and long-distance runners.

STUDY DESIGN

Descriptive epidemiological study.

METHODS

Data from a 7-year prospective study of 2 NCAA Division I cross-country and track and field programs characterized BSIs over the years 2013 to 2020. Femoral neck, pelvic, sacral, lumbar spine, and calcaneal BSIs were considered trabecular-rich. All remaining BSIs were classified as cortical-rich. Total athlete-years of follow-up were calculated by subtracting the number of days an athlete was unable to run from the number of total study participation days. Annual incidence rates were calculated by dividing the number of BSIs by the total athlete-years of follow-up for that year, and monthly incidence rates were calculated by dividing the number of BSIs in a given month by the total athlete-years of follow-up for that month.

RESULTS

Participants included 221 collegiate distance runners (114 female, 107 male). There were 154 BSIs across 482 total athlete-years, resulting in an incidence rate of 32 BSIs per 100 athlete-years. The female BSI rate was more than double that of the male BSI rate: 45 versus 20 BSIs per 100 athlete-years, respectively. The highest monthly BSI rates occurred during competitive months, with the lowest monthly BSI rates occurring during noncompetitive months. Tibial and femoral shaft BSI rates peaked during the early competitive phases of each season, whereas metatarsal BSI rates remained relatively constant. Cortical-rich BSI rates varied by sex and seasonal phase, whereas trabecular-rich BSI rates remained relatively consistent.

CONCLUSION

BSIs were common in collegiate distance runners, especially among female athletes, with higher rates during the competitive phases of the running season. Tibial and femoral shaft BSI rates were highest during the competitive phases and lowest during the noncompetitive phases, while metatarsal BSI rates remained consistent throughout the season. Cortical-rich BSI rates varied by seasonal phase and sex, whereas trabecular-rich BSI rates were relatively constant.

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.

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 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.

Pacing Behaviour Development and Acquisition: A Systematic Review

BACKGROUND

The goal-directed decision-making process of effort distribution (i.e. pacing) allows individuals to efficiently use energy resources as well as to manage the impact of fatigue on performance during exercise. Given the shared characteristics between pacing behaviour and other skilled behaviour, it was hypothesized that pacing behaviour would adhere to the same processes associated with skill acquisition and development.

METHODS

PubMed, Web of Science and PsycINFO databases between January 1995 and January 2022 were searched for articles relating to the pacing behaviour of individuals (1) younger than 18 years of age, or (2) repeatedly performing the same exercise task, or (3) with different levels of experience.

RESULTS

The search resulted in 64 articles reporting on the effect of age (n = 33), repeated task exposure (n = 29) or differing levels of experience (n = 13) on pacing behaviour. Empirical evidence identifies the development of pacing behaviour starts during childhood (~ 10 years old) and continues throughout adolescence. This development is characterized by an increasingly better fit to the task demands, encompassing the task characteristics (e.g. duration) and environment factors (e.g. opponents). Gaining task experience leads to an increased capability to attain a predetermined pace and results in pacing behaviour that better fits task demands.

CONCLUSIONS

Similar to skilled behaviour, physical maturation and cognitive development likely drive the development of pacing behaviour. Pacing behaviour follows established processes of skill acquisition, as repeated task execution improves the match between stimuli (e.g. task demands and afferent signals) and actions (i.e. continuing, increasing or decreasing the exerted effort) with the resulting exercise task performance. Furthermore, with increased task experience attentional capacity is freed for secondary tasks (e.g. incorporating opponents) and the goal selection is changed from achieving task completion to optimizing task performance. As the development and acquisition of pacing resemble that of other skills, established concepts in the literature (e.g. intervention-induced variability and augmented feedback) could enrich pacing research and be the basis for practical applications in physical education, healthcare, and sports.

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.

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.

Age- and Sex-Based Differences in Exertional Heat Stroke Incidence in a 7-Mile Road Race

CONTEXT

Sex, age, and wet-bulb globe temperature (WBGT) have been proposed risk factors for exertional heat stroke (EHS) despite conflicting laboratory and epidemiologic evidence.

OBJECTIVE

To examine differences in EHS incidence while accounting for sex, age, and environmental conditions.

DESIGN

Observational study.

SETTING

Falmouth Road Race, a warm-weather 7-mi (11.26-km) running road race.

PATIENTS OR OTHER PARTICIPANTS

We reviewed records from patients treated for EHS at medical tents.

MAIN OUTCOME MEASURE(S)

The relative risk (RR) of EHS between sexes and across ages was assessed with males as the reference population. Multivariate linear regression analyses were calculated to determine the relative contribution of sex, age, and WBGT to the incidence of EHS.

RESULTS

Among 343 EHS cases, the female risk of EHS was lower overall (RR = 0.71; 95% confidence interval [CI] = 0.58, 0.89; P = .002) and for age groups 40 to 49 years (RR = 0.43; 95% CI = 0.24, 0.77; P = .005) and 50 to 59 years (RR = 0.31; 95% CI = 0.13, 0.72; P = .005). The incidence of EHS did not differ between sexes in relation to WBGT (P > .05). When sex, age, and WBGT were considered in combination, only age groups <14 years (β = 2.41, P = .008), 15 to 18 years (β = 3.83, P < .001), and 19 to 39 years (β = 2.24, P = .014) significantly accounted for the variance in the incidence of EHS (R2 = .10, P = .006).

CONCLUSIONS

In this unique investigation of EHS incidence in a road race, we found a 29% decreased EHS risk in females compared with males. However, when sex was considered with age and WBGT, only younger age accounted for an increased incidence of EHS. These results suggest that road race medical organizers should consider participant demographics when organizing the personnel and resources needed to treat patients with EHS. Specifically, organizers of events with greater numbers of young runners (aged 19 to 39 years) and males should prioritize ensuring that medical personnel are adequately prepared to handle patients with EHS.

The interaction of competition and terrain on pacing during cross-county running races in junior athletes

The aim of this study was to assess pacing during cross-country racing in relation to race length, surface-terrain and racing dynamics. Athletes (n = 148) competed for school teams (U15, U17, U20) over 2.9, 4.2, 6.3 km, respectively. The course lap (2.067 m) was timed using UHF-RFID and divided into six sections based on surface-terrain and length (549, 619, 207, 338, 150, 156m). Overall pace differed between races (4.56 ± 0.30, 4.42 ± 0.38, 4.40 ± 0.31 m∙s^-1, p=0.042) but not for the top-20 of each race (p=0.174). Moreover, within lap pacing followed a repeated reverse-"J"-parabolic strategy for all races. Race length (no. of laps) and category affected pacing with regards to finish position banding (1st-10th, 11th-20th) where effect size differences showed large to extremely large (1.21 - >4.00) difference between top-10 and other bands. Exceptions to this included the finish sprint where it was typically trivial-moderate (<0.2-1.2) and in key areas where social facilitation occurred. Athlete/coaches need to be aware of between and within lap variations in pace/effort, the effects of race dynamics, and spectator influences, while all athletes need to be educated as part of their training to run their own optimal strategy for best performance.

Pacing behaviour of middle-long distance running & race-walking athletes at the IAAF U18 and U20 World Championship finals

ABSTRACTThe current study analysed the pacing behaviour of athletes competing in the middle-long track event finals of the IAAF Under 18 and Under 20 World Championships between 2015 and 2018. Official finishing times, 1000-m split times and positioning data of 116 female and 153 male athletes, competing in the middle-long distance running (3000 m, 5000 m and 10,000 m) and race walking (5000 m and 10,000 m) events, were gathered. Repeated measures analysis of variance, with 1000-m speed as within-subjects factor and final ranking (medallist, Top 8 or Top 12, rest of the field) as between-subjects factor, was performed to compare the pacing behaviour between athletes. Positioning of the athletes was analysed by Kendall tau-b (T_b) correlation between the intermediate position and final position. Overall, medallists increased their speed throughout a race, with the exception of the 5000 m running event, in which a parabolic pacing behaviour was exhibited. The 1000-m segment in which a significant (P > 0.05) difference in speed was exhibited between differently ranked athletes coincided with a strong (T_b> 0.7) correlation between intermediate and final positioning. These combined results point towards a separation between the athletes during the race, as the Top 8 or Top 12 and the rest of the field are unable to match the speed of the medallists. The distance, discipline, sex, age category and behaviour of competitors all influence the pacing behaviour of young track athletes during international level competition, emphasising the importance and complexity of developing adequate pacing behaviour in track athletes. HighlightsThe distribution of effort over an exercise task (i.e. pacing) is an important factor in endurance exercise competition. The pacing behaviour of athletes is determined by many aspects, such as the biomechanical characteristics of the task, the exercise environment and the age of the athleteSport specific competition data from youth athlete sports events can provide insight into the pacing behaviour of developing athletes. These insights could assist in the optimalisation of the development of pacing behaviour of young athletes in the future.The current study analysed the 1000-m split times and positioning data of athletes competing in the running (3000 m, 5000 m and 10,000) and racewalking (5000 m and 10,000m) finals of the U18 and U20 IAAF world-championship.The difference in final ranking impacted the pacing behaviour of the athletes, with the medallists increasing their speed throughout the race and the other athletes separating from the medallists either early (rest of field) or later in the race (Top 8 or Top 12 athletes).

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

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

Pacing During 200-m Competitive Masters Swimming

Breen, D, Powell, C, and Anderson, R. Pacing during 200-m competitive masters swimming. J Strength Cond Res 34(7): 1903-1910, 2020-Pacing strategies are key to overall performance outcome, particularly in swimming given the large resistive properties of water. However, no studies examining how swimming stroke, gender, age, or performance level affect pacing strategies during 200-m races. This study aimed to examine masters athletes pacing strategies categorized by stroke, gender, age, and performance level. Data were retrieved from World and European masters swimming championships and contained data for 4,272 performances. Performances were coded for stroke, gender, age, and performance classification (PC). Performance classification was based on comparison to the appropriate masters world record. Performances were then normalized, with split times being expressed as a percentage faster or slower than average 50-m split time to determine relative pace. Coefficient of variation (CV) of 50-m time was examined across splits. The main effect for stroke was examined at each split, whereas gender, age, and PC were examined for split-1 pace and CV. An alpha level of 0.05 was set to denote statistical significance. A main effect for stroke was identified at each split (all p < 0.001; (Equation is included in full-text article.)-split-1 = 0.292; (Equation is included in full-text article.)-split-2 = 0.040; (Equation is included in full-text article.)-split-3 = 0.058; (Equation is included in full-text article.)-split-4 = 0.162). A main effect for PC was identified for split-1 pace and CV within all strokes (all p < 0.001), except for breaststroke (both p > 0.775). Masters athletes exhibit different pacing patterns across strokes, whereas lower ranked athletes also display less even pacing and a faster relative start compared with higher-ranked athletes. Individual analyses of pacing strategies may be necessary.

Optimal Development of Youth Athletes Toward Elite Athletic Performance: How to Coach Their Motivation, Plan Exercise Training, and Pace the Race

Elite athletes have invested many years in training and competition to reach the elite level. One very important factor on the road to elite performance is the decision-making process regarding the regulation of effort over time, termed as pacing behavior. The regulation of effort is vital for optimal athletic performance during a single race and over a longer period of time (e.g., a competitive season) as an inadequate regulation could result in a higher risk of injuries, overtraining, and drop-out. Despite this, there is limited knowledge on how young athletes learn and develop the abilities related to pacing. Pacing behavior of athletes develops from childhood throughout adolescence and is thought to be closely connected to physical maturation, the development of pre-frontal cortical related (meta-) cognitive functions, as well as the gathering of experience with exercise tasks. The motivation of an athlete can critically influence how an athlete paces a single race, but also how they distribute their effort over a longer period of time. Coaches are advised to closely monitor the development of pacing behavior during adolescence (e.g., by gathering split times, and related physiological measurement, during training and competition), as well as the underlying factors including physical maturation (meta-) cognitive development and the motivation of young athletes. Furthermore, pacing behavior development could be aided by providing training in which the task, individual, and environment are manipulated. Hereby, presenting athletes with the opportunity to gain experience in situations which closely resemble the perceptual-motor conditions of upcoming competitions.

The Differences in Pacing Among Age Groups of Amateur Cross-Country Skiers Depend on Performance

Pacing strategies have mainly been investigated for runners, but little is known for cross-country skiers. The aim of the present study was to examine the effects of performance and age on pacing strategies in cross-country skiing. All finishers (women, n = 19,375; men, n = 86,190) in the 'Engadin Ski Marathon' (42 km) between 1998 and 2016 were analysed for the percentage change of speed at 10 km (Change A), 20 km (Change B) and 35 km (Change C). They were classified in performance groups according to quartiles of average race speed (Q1, Q2, Q3 and Q4) and in 5-year age groups (<20, 20-24, 25-29… 85-89 years). Men were faster than women by +14.3% (15.2 ± 4.0 vs. 13.3 ± 3.3 km/h; p < 0.001, η² = 0.215). A small impact of age group × performance group interaction on Change A was shown in women (p < 0.001, η² = 0.026) and men (p < 0.001, η² = 0.025), where Q1 augmented and Q4 attenuated the decrease in speed with aging. However, the impact of age group × performance group interaction on Change B and C was trivial (p = 0.002, η² ≤ 0.010). Based on these findings, it was concluded that the differences in pacing among age groups depended on the performance level. Thus, the coaches and fitness trainers working with cross-country skiers should advise their athletes to consider both age and performance.

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.

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

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

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.

Marathon Pace Control in Masters Athletes

PURPOSE

Pacing strategies are key to overall performance outcome in distance-running events. Presently, no literature has examined pacing strategies used by masters athletes of all running levels during a competitive marathon. Therefore, this study aimed to examine masters athletes' pacing strategies, categorized by gender, age, and performance level.

METHODS

Data were retrieved from the 2015 TSC New York City Marathon for 31,762 masters athletes (20,019 men and 11,743 women). Seven performance-classification (PC) groupings were identified via comparison of overall completion time compared with current world records, appropriate to age and gender. Data were categorized via, age, gender, and performance level. Mean 5-km speed for the initial 40 km was calculated, and the fastest and slowest 5-km-split speeds were identified and expressed as a percentage faster or slower than mean speed. Pace range, calculated as the absolute sum of the fastest and slowest split percentages, was then analyzed.

RESULTS

Significant main effects were identified for age, gender, and performance level (P < .001), with performance level the most determining factor. Athletes in PC1 displayed the lowest pace range (14.19% ± 6.66%), and as the performance levels of athletes decreased, pace range increased linearly (PC2-PC7, 17.52% ± 9.14% to 36.42% ± 18.32%). A significant interaction effect was found for gender × performance (P < .001), with women showing a smaller pace range (-3.81%).

CONCLUSIONS

High-performing masters athletes use more-controlled pacing strategies than their lower-ranked counterparts during a competitive marathon, independent of age and gender.

Sex differences in pacing during 'Ultraman Hawaii'

Background

To date, little is known for pacing in ultra-endurance athletes competing in a non-stop event and in a multi-stage event, and especially, about pacing in a multi-stage event with different disciplines during the stages. Therefore, the aim of the present study was to examine the effect of age, sex and calendar year on triathlon performance and variation of performance by events (i.e., swimming, cycling 1, cycling 2 and running) in ‘Ultraman Hawaii’ held between 1983 and 2015.

Methods

Within each sex, participants were grouped in quartiles (i.e., Q1, Q2, Q3 and Q4) with Q1 being the fastest (i.e., lowest overall time) and Q4 the slowest (i.e., highest overall time). To compare performance among events (i.e., swimming, cycling 1, cycling 2 and running), race time in each event was converted in z score and this value was used for further analysis.

Results

A between-within subjects ANOVA showed a large sex × event (p = 0.015, η² = 0.014) and a medium performance group × event interaction (p = 0.001, η² = 0.012). No main effect of event on performance was observed (p = 0.174, η² = 0.007). With regard to the sex × event interaction, three female performance groups (i.e., Q2, Q3 and Q4) increased race time from swimming to cycling 1, whereas only one male performance group (Q4) revealed a similar trend. From cycling 1 to cycling 2, the two slower female groups (Q3 and Q4) and the slowest male group (Q4) increased raced time. In women, the fastest group decreased (i.e., improved) race time from swimming to cycling 1 and thereafter, maintained performance, whereas in men, the fastest group decreased race time till cycling 2 and increased it in the running.

Conclusion

In summary, women pace differently than men during ‘Ultraman Hawaii’ where the fastest women decreased performance on day 1 and could then maintain on day 2 and 3, whereas the fastest men worsened performance on day 1 and 2 but improved on day 3.

Pacing in age-group freestyle swimmers at The XV FINA World Masters Championships in Montreal 2014

Pacing strategies have been investigated for elite-standard freestyle swimmers, but little is known about pacing in age-group freestyle swimmers. We investigated changes in swimming time across distances in 4,481 women and men swimmers who competed in 100, 200, 400, and 800 m freestyle age groups from 25-29 years to 90-94 years in the FINA World Masters Championships 2014. In 100 to 800 m, there was a small lap×sex interaction (P < 0.001, 0.033 ≤ η² ≤ 0.045) whereby women had larger lap-to-lap changes in swimming time than men. From 100 to 800 m, there were moderate to large lap×age group interactions (P < 0.001, 0.054 ≤ η² ≤ 0.235), i.e., pacing patterns differed by age groups. There were small main effects of lap on time in 100, 200, 400 and 800 m freestyle events (P < 0.001, 0.033 ≤ η² ≤ 0.045). In summary, (i) the largest increase in swimming time occurred during the second lap and a decrease in time occurred during the last lap, except in the 100 m, and (ii) the effect of participants' sex on lap time indicated larger percentage changes of pacing in women than in men. These findings should help coaches to develop age- and event-tailored pacing strategies.