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

Pacing strategies in marathons: A systematic review

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

The effect of advanced footwear technology on elite male marathon race speed

PURPOSE

The aim of this study was to explore the ergogenic effect of advanced footwear technology (AFT) upon world-class male marathon running speed.

METHOD

A retrospective analysis of 99 world-class male marathon runners' performances between 2012 and 2021 was undertaken, providing a sample size of 971 performances, split into two footwear groups: AFT (n = 299) and traditional (n = 672). Additionally, details regarding the year of the marathon performance and racecourse were extracted. A mixed model for repeated measures (MMRM) analysis were undertaken identifying athlete (Wald Z = 2.821; p = .005) and course (Wald Z = 4.111; p < 0.001) as significant contributors to the variance in marathon running speed and as such were included as random factors with footwear type set as a fixed factor.

RESULTS

World-class male marathon running speeds were significantly faster (p < 0.001) when running in AFT (5.441 m.s-1) when compared with traditional shoes (5.386 m.s-1) with a mean difference of 0.055 m.s-1 (95% CI 0.039-0.071 m.s-1), translating to an improvement in marathon speed of 1.0% or a 79 s improvement in marathon race time.

CONCLUSION

Our findings demonstrate an improvement in world-class male marathon running speed of 1% when running in AFT, a near identical degree of improvement to the male marathon world record ran in AFT. Whilst a 1% improvement in marathon running times associated with AFT is smaller than previously predicted utilizing laboratory-based models, this still reflects a significant degree of improvement at the elite level.

The pacing differences in performance levels of marathon and half-marathon runners

Introduction

Many studies indicate a considerable impact of optimal pacing on long-distance running performance. Given that the amount of carbohydrates in metabolic processes increases supralinearly with the running intensity, we may observe differences between the pacing strategies of two long-distance races and different performance levels of runners. Accordingly, the present study aimed to examine the differences in pacing strategies between marathon and half-marathon races regarding the performance levels of runners.

Methods

The official results and split times from a total of 208,760 (marathon, N = 75,492; half-marathon, N = 133,268) finishers in the "Vienna City Marathon" between 2006 and 2018 were analyzed. The percentage of the average change of speed for each of the five segments (CS 1-5), as well as the absolute change of speed (ACS) were calculated. The CS 1-5 for the marathon are as follows: up to the 10th km, 10th - 20th km, 20th - 30th km, 30th - 40th km, and from the 40th km to the 42.195 km. For the half-marathon, the CS 1-5 are half of the marathon values. Four performance groups were created as quartiles of placement separately for sexes and races: high-level (HL), moderate to high-level (MHL), moderate to low-level (MLL), and low-level (LL).

Results

Positive pacing strategies (i.e., decrease of speed) were observed in all performance groups of both sex and race. Across CS 1-5, significant main effects (p < 0.001) were observed for the segment, performance level, and their interaction in both sex and race groups. All LL groups demonstrated higher ACS (men 7.9 and 6.05%, as well as women 5.83 and 5.49%, in marathon and half-marathon, respectively), while the HL performance group showed significantly lower ACS (men 4.14 and 2.97%, as well as women 3.16 and 2.77%, in marathon and half-marathon, respectively). Significant main effects (p < 0.001) for the race were observed but with a low effect size in women (ŋ2 = 0.001).

Discussion

Better runners showed more even pacing than slower runners. The half-marathoners showed more even pacing than the marathoners across all performance groups but with a trivial practical significance in women.

Drafting in long-track speed skating team pursuit on the ice rink

Drafting is distinctive for team pursuit races in long-track speed skating. This study aims to compare the impact of drafting on physical intensity (heart rate [HR]) and perceived intensity (ratings of perceived exertion [RPE]) per drafting position. Eighteen skilled male (n = 9) and female (n = 9) skaters (20.0 ± 4.8 years) skated three trials, in first, second or third position, with consistent average velocity (F_2,10 = 2.30, p = 0.15, η_p² = 0.32). Differences in HR and RPE (Borg CR-10 scale) were compared within-subjects (three positions) using a repeated-measures ANOVA (p < 0.05). Compared to the first position, HR was lower in the second (benefit 3.2%) and third (benefit 4.7%) position and lower in third compared to second position (benefit 1.5%), observed in 10 skaters (F_2,28 = 28.9, p < 0.001, η_p²= 0.67). RPE was lower when comparing second (benefit 18.5%) and third (benefit 16.8%) position to first (F_1.3,22.1 = 7.02, p < 0.05, η_p²= 0.29) and similar for third and second positions., observed in 8 skaters. Even though the physical intensity was lower when drafting in third versus second position, the perceived intensity was equal. There were large interindividual differences between skaters. Coaches are advised to adopt a multidimensional, tailored approach when selecting and training skaters for a team pursuit.

Participation and performance characteristics in half-marathon run: a brief narrative review

Half-marathon (HM) is a running sport of increasing popularity in both sexes and in all age groups worldwide during the last years. Many studies have examined several aspects of HM, such as performance and participation trends, sex and age differences, physiological correlates, and training; however, no comprehensive review has ever been contacted to summarize the recently accumulated knowledge. Therefore, the aim of the present study was to review all previous research in this sport, focusing on participation and performance aspects. It was shown that HM runners had similar anthropometric and physiological characteristics as full-marathon runners which should be attributed to the affinity of these two races in terms of metabolic demands. Performance in HM was related with superior scores in aerobic capacity (maximal oxygen uptake, anaerobic threshold and running economy) and training characteristics (sport experience, weekly distance, training speed, frequency of sessions and long single endurance run distance), and lower scores in adiposity-related scores (e.g. body mass, body mass index, body fat percentage and skinfold thickness). Considering the popularity of HM race and the lack of many original studies (compared to FM race), this is an exciting field for scientific research with a large potential for practical applications, since the majority of HM runners are amateur runners in need of sex-, age- and performance-tailored exercise prescription.

Race development and performance-determining factors in a mass-start cross-country skiing competition

Introduction

Although five of six Olympic events in cross-country skiing involve mass-starts, those events are sparsely examined scientifically. Therefore, in this study, we investigated speed profiles, pacing strategies, group dynamics and their performance-determining impact in a cross-country skiing mass-start competition.

Methods

Continuous speed and position of 57 male skiers was measured in a six-lap, 21.8 km national mass-start competition in skating style and later followed up with an online questionnaire. Skiers ranked from 1 to 40 were split into four performance-groups: R1-10 for ranks 1 to 10, R11-20 for ranks 11 to 20, R21-30 for ranks 21 to 30, and R31-40 for ranks 31 to 40.

Results

All skiers moved together in one large pack for 2.3 km, after which lower-performing skiers gradually lost the leader pack and formed small, dynamic packs. A considerable accordion effect occurred during the first half of the competition that lead to additional decelerations and accelerations and a higher risk of incidents that disadvantaged skiers at the back of the pack. Overall, 31% of the skiers reported incidents, but none were in R1-10. The overall trend was that lap speed decreased after Lap 1 for all skiers and thereafter remained nearly unchanged for R1-10, while it gradually decreased for the lower-performing groups. Skiers in R31-40, R21-30, and R11-20 lost the leader pack during Lap 3, Lap 4, and Lap 5, respectively, and more than 60% of the time-loss relative to the leader pack occurred in the uphill terrain sections. Ultimately, skiers in R1-10 sprinted for the win during the last 1.2 km, in which 2.4 s separated the top five skiers, and a photo finish differentiated first from second place. Overall, a high correlation emerged between starting position and final rank.

Conclusions

Our results suggest that (a) an adequate starting position, (b) the ability to avoid incidents and disadvantages from the accordion effect, (c) tolerate fluctuations in intensity, and (d) maintain speed throughout the competition, particularly in uphill terrain, as well as (e) having well-developed final sprint abilities, are key factors determining performance during skating-style mass-start cross-country skiing competitions.

Competition Between Desired Competitive Result, Tolerable Homeostatic Disturbance, and Psychophysiological Interpretation Determines Pacing Strategy

Scientific interest in pacing goes back >100 years. Contemporary interest, both as a feature of athletic competition and as a window into understanding fatigue, goes back >30 years. Pacing represents the pattern of energy use designed to produce a competitive result while managing fatigue of different origins. Pacing has been studied both against the clock and during head-to-head competition. Several models have been used to explain pacing, including the teleoanticipation model, the central governor model, the anticipatory-feedback-rating of perceived exertion model, the concept of a learned template, the affordance concept, the integrative governor theory, and as an explanation for "falling behind." Early studies, mostly using time-trial exercise, focused on the need to manage homeostatic disturbance. More recent studies, based on head-to-head competition, have focused on an improved understanding of how psychophysiology, beyond the gestalt concept of rating of perceived exertion, can be understood as a mediator of pacing and as an explanation for falling behind. More recent approaches to pacing have focused on the elements of decision making during sport and have expanded the role of psychophysiological responses including sensory-discriminatory, affective-motivational, and cognitive-evaluative dimensions. These approaches have expanded the understanding of variations in pacing, particularly during head-to-head competition.

Performance prediction, pacing profile and running pattern of elite 1-h track running events

Purpose

This study aimed at comparing the predictive accuracy of the power law (PL), 2-parameter hyperbolic (HYP) and linear (LIN) models on elite 1-h track running performance, and evaluating pacing profile and running pattern of the men’s best two 1-h track running performances of all times.

Methods

The individual running speed–distance profile was obtained for nine male elite runners using the three models. Different combinations of personal bests times (3000 m-marathon) were used to predict performance. The level of absolute agreement between predicted and actual performance was evaluated using intraclass correlation coefficient (ICC), paired t test and Bland–Altman analysis. A video analysis was performed to assess pacing profile and running pattern.

Results

Regardless of the predictors used, no significant differences (p > 0.05) between predicted and actual performances were observed for the PL model. A good agreement was found for the HYP and LIN models only when the half-marathon was the longest event predictor used (ICC = 0.718–0.737, p < 0.05). Critical speed (CS) was highly dependent on the predictors used. Unlike CS, PLV20 (i.e., the running speed corresponding to a 20-min performance estimated using the PL model) was associated with 1-h track running performances (r = 0.722–0.807, p < 0.05). An even pacing profile with minimal changes of step length and frequency was observed.

Conclusions

The PL model may offer the more realistic 1-h track running performance prediction among the models investigated. An even pacing might be the best strategy for succeeding in such running events.

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.

Comparison of Race Time-Differences Between and Within Para and Able-Bodied Cross-Country Skiers

Purpose

To compare differences in race time (i.e., the average percent difference in race time for each skier compared to the winner, RT_diffs) between female and male Para and able-bodied (AB) skiers, and to examine whether RT_diffs change across seasons.

Methods

Race data from World Cups (WCs), World Championships (WCHs), and Paralympic/Olympic Winter Games (PWG/OWGs) of the 2011–2020 seasons was extracted from the website of the International Paralympic Committee and the International Ski Federation. All individual distance races for female and male visually impaired standing (VI), physically impaired sitting (SIT) and standing (STAND), and AB skiers with ≥10 competitors were included in the analyses. We investigated the main effect of skiing groups (i.e., VI, STAND, SIT, and AB skiers) and sex on RT_diffs for top-3 and top-8 skiers. Furthermore, the main effect of season and skiing group on RT_diffs for top-3 and top-8 skiers were investigated. All models were adjusted for distance, skiing style (classical- and freestyle), and event type (WC, WCH, and PWG/OWG).

Results

RT_diffs were significantly larger in Para compared to AB skiers (top-3: 2.1 vs. 0.9%; top-8: 6.2 vs. 2.1%, all p < 0.01), and in female compared to male skiers (top-3: 1.8 vs. 1.3%; top-8: 4.9 vs. 3.5%, all p < 0.05). For top-3 skiers, RT_diffs did not significantly differ between the Para categories (all p > 0.2), while for top-8 skiers RT_diffs were significantly larger for VI compared to SIT and STAND (7.0 vs. 5.5 and 5.6%, respectively, all p < 0.05). RT_diffs were stable across the 2011–2020 seasons for top-3 skiers (VI: 1.7–3.6%, STAND: 1.1–2.2%, SIT: 1.0–3.9%, AB: 0.4–1.1%; all p > 0.1) and top-8 skiers (VI: 3.4–12.0%, STAND: 2.6–5.7%, SIT: 1.9–5.9%, AB: 0.1–1.7%; all p > 0.1).

Conclusion

The larger RT_diffs in Para compared to AB skiers indicate larger variability in performance, which are in part disability related. Female skiers displayed larger RT_diffs than their male counterparts, indicating larger variability in performance among the female skiers. Our results provide insights about performance demands in Para cross-country skiing, which is of relevance for coaches and skiers.

The Value of Meteorological Data in Optimizing the Pattern of Physical Load-A Forecast Model of Rowing Pacing Strategy

Mastering the information of arena environment is the premise for athletes to optimize their patterns of physical load. Therefore, improving the forecast accuracy of the arena conditions is an urgent task in competitive sports. This paper excavates the meteorological features that have great influence on outdoor events such as rowing and their influence on the pacing strategy. We selected the meteorological data of Tokyo from 1979 to 2020 to forecast the meteorology during the Tokyo 2021 Olympic Games, analyzed the athletes' pacing choice under different temperatures, humidity and sports levels, and then recommend the best pacing strategy for rowing teams of China. The model proposed in this paper complements the absence of meteorological features in the arena environment assessment and provides an algorithm basis for improving the forecast performance of pacing strategies in outdoor sports.

Pacing profiles and tactical behaviors of elite runners

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

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.

Comparisons of Macro-Kinematic Strategies During the Rounds of a Cross-Country Skiing Sprint Competition in Classic Technique

This study was designed to examine macro-kinematic parameters of six female cross-country skiers during the qualifying, semi-final and final rounds of a 1.1 km sprint competition in classical technique. During each round these skiers were monitored continuously with a single micro-sensor, and their cycle parameters and relative use of these two sub-techniques calculated. Within each round six sections of the course, during which all skiers employed either double pole (DP) or diagonal stride (DS) sub-technique, were chosen for additional analysis. The mean macro-kinematic cycle parameters and relative usage of sub-techniques over the full course did not differ significantly between rounds. On average 54% of the course was covered employing DP and 13% using DS, while 32% was covered utilizing a non-cyclical or irregular technique. With DP, the mean racing speed and cycle rate (CR) on the starting, middle and finishing sections of the course differed significantly, with no differences in mean cycle length (CL) between the last two sections. At the finish, higher DP speed was achieved by increasing CR. On the three hills, where all athletes utilized DS, mean racing speed and CL, but not mean CR, differed significantly. On these sections DS speed was increased by utilizing longer cycles. The individual skiers utilized a variety of macro-kinematic strategies during different rounds and on different sections of the course, depending on individual strengths, preferences and pacing strategies, as well as the course topography and tactical interactions with other skiers. Such collection of macro-kinematic data during competitions can help to identify an individual skier's strengths and weaknesses, guiding the testing of different cycle rates, and lengths on different terrains during training in order to optimize performance.

Pacing and Hazard Score of Elite Open Water Swimmers During a 5-km Indoor Pool Race

PURPOSE

The sensation of fatigue experienced at a certain point of the race is an important factor in the regulation of pacing. The rating of perceived exertion (RPE) is considered one of the main mediators utilized by athletes to modify pacing. The aim was to analyze the relationship between pacing and RPE of elite open water swimmers during national indoor pool championships.

METHODS

A total of 17 elite open water swimmers (males, n = 9; females, n = 8) agreed to provide RPE every 500 m during the finals of the national championships 5-km indoor pool race. Time splits, stroke rate, and RPE were collected every 500 m. The Hazard score was calculated by multiplying the momentary RPE by the remaining fraction of the race. Athletes were placed in one of two categories: medalists or nonmedalists. For all variables, separate mixed analysis of variances (P ≤ .05) with repeated measures were used considering the splits (ie, every 500 m) as within-subjects factor and the groups (ie, medalists and nonmedalists) as between-subjects factor.

RESULTS

Average swimming speed showed a significant main effect for split for both males and females (P < .001). A significant interaction was observed between average swimming speed and groups for females (P = .032). RPE increased in both groups (P < .001) with no difference observed between groups. However, the female nonmedalists showed a disproportionate nonlinear increase in RPE (5.20 [2.31]) halfway through the event that corresponded to the point where they started significantly decreasing speed.

CONCLUSIONS

The results of the present study show different pacing strategies adopted by medalists and nonmedalists despite a similar RPE.

Physiological responses during the long-distance race in the warm environment in runners: a pilot-study

BACKGROUND

This study investigated the effects of warm temperature in the external environment on physiological response in self- pace during the long-distance race in runners and the association between the physiological index of endurance performance (i.e., speeds at ventilatory anaerobic threshold [VVAT], respiratory compensation [VRCP], maximum oxygen uptake [<inf>V</inf>VO2max], and running economy) and average pace for each 3-km during the 21-km race.

METHODS

Five male recreational runners (mean±SE age 36.6±6.1 years; VO<inf>2</inf> max: 59.2±7.9) were submitted to a 21-kilometers race in the outdoor environment using a portable metabolic analyzer.

RESULTS

Our results showed a reduction in speed to kilometers 12, 15, 18 and 21 than kilometer 3 (P<0.05). The runners showed a decrease in both VO<inf>2</inf> (mL/kg/min) and RER from kilometer 15 (P=0.001 and P=0.003, respectively). Regarding cardiovascular response, our data demonstrated a steady HR response from kilometer 6 to 21 (P=0.99). Otherwise, the runners showed a decrease in oxygen pulse from kilometer 9 than both kilometers 3 and 6 (P=0.001). During the race, the runners demonstrated a significant increase in body temperature compared to rest (P=0.001). The results of the correlation analysis between physiological index of endurance performance and average pace for each 3-km during the 21-km race showed significant correlation between VVAT and average pace for: 12-km (r=0.95; P=0.01), 15-km (r=0.89; P=0.05) and 21-km (r=0.86; P=0.04); VRCP and average pace for 3-km (r=0.88; P=0.05).

CONCLUSIONS

Our findings demonstrated that the increase in body temperature in a warm environment during the 21-km race is associated with both cardiovascular and metabolic strain in runners. Concerning physiological markers of endurance performance, VVAT appears to be the best predictor of the average pace throughout the 21-km race in a warm environment in recreational runners.

More Pace Variation and Pack Formation in Successful World-Class 10,000-m Runners Than in Less Successful Competitors

PURPOSE

To determine different relationships between, and predictive ability of, performance variables at intermediate distances with finishing time in elite male 10,000-m runners.

METHODS

Official electronic finishing and 100-m split times of the men's 10,000-m finals at the 2008 and 2016 Olympic Games and IAAF World Championships in 2013 and 2017 were obtained (125 athlete performances in total). Correlations were calculated between finishing times and positions and performance variables related to speed, position, time to the leader, and time to the runner in front at 2000, 4000, 6000, 8000, and 9900 m. Stepwise linear-regression analysis was conducted between finishing times and positions and these variables across the race. One-way analysis of variance was performed to identify differences between intermediate distances.

RESULTS

The SD and kurtosis of mean time, skewness of mean time, and position and time difference to the leader were either correlated with or significantly contributed to predictions of finishing time and position at at least one of the analyzed distances (.81 ≥ r ≥ .30 and .001 ≤ P ≤ .03, respectively). These variables also displayed variation across the race (.001 ≤ P ≤ .05).

CONCLUSIONS

The ability to undertake a high degree of pace variability, mostly characterized by acceleration in the final stages, is strongly associated with achievement of high finishing positions in championship 10,000-m racing. Furthermore, the adoption and maintenance of positions close to the front of the race from the early stages are important to achieve a high finishing position.

Pacing Profiles and Competitive Performance of Elite Female 400-m Freestyle Swimmers

Lipinska, P, and Hopkins, WG. Pacing profiles and competitive performance of elite female 400-m freestyle swimmers. J Strength Cond Res 34(1): 218-224, 2020-Pacing can impact competitive endurance performance. The objective of this study was to determine relationships between pacing parameters and competitive performance of elite female 400-m freestyle swimmers. Publicly available websites provided 50-m split and final times for 381 swims of 20 elite female swimmers in over 150 national and international competitions between 2004 and 2016. Most pacing profiles displayed negative quadratic curvature, with the fifth of the 8 laps being the median slowest. The mean times for the first and last laps were faster than predicted by the quadratic by 5.6 and 1.9%, respectively, and lap-to-lap variability was 0.65%. Scatter plots of each swimmer's final time often showed no obvious relationships with their pacing parameters, suggesting that swimmers compensated for changes in one parameter with changes in another. However, some plots showed a U shape or linear trend that allowed tentative identification of optimum values of the pacing parameters. In these plots, it was apparent that about half the swimmers might make small to moderate improvements (up to ∼1%) by changing the slope or curvature of their pacing profile or by changing time in the first or last laps. This approach for characterizing pacing profiles to identify possible improvements might be appropriate to assess pacing in other sports with multiple laps, frequent competitions, and relatively constant environmental conditions.

The Relationship Between Tactical Positioning and the Race Outcome in 800-M Running at the 2016 Olympic Games and 2017 IAAF World Championship

The purpose of this analysis was to quantify the probability of achieving a top-3 finishing position during 800-m races at a global championship, based on dispersion of the runners during the first and second laps and the difference in split times between laps. Overall race times, intermediate and finishing positions and 400 m split times were obtained for 43 races over 800 m (21 men’s and 22 women’s) comprising 334 individual performances, 128 of which resulted in higher positions (top-3) and 206 the remaining positions. Intermediate and final positions along with times, the dispersion of the runners during the intermediate and final splits (SS1 and SS2), as well as differences between the two split times (Dsplits) were calculated. A logistic regression model was created to determine the influence of these factors in achieving a top-3 position. The final position was most strongly associated with SS2, but also with SS1 and Dsplits. The Global Significance Test showed that the model was significant (p < 0.001) with a predictive ability of 91.08% and an area under the curve coefficient of 0.9598. The values of sensitivity and specificity were 96.8% and 82.5%, respectively. The model demonstrated that SS1, SS2 and Dplits explained the finishing position in the 800-m event in global championships.

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.

The Science Behind Competition and Winning in Athletics: Using World-Level Competition Data to Explore Pacing and Tactics

The purpose of this study was to examine whether World Championship and Olympic medallist endurance athletes pace similarly to their race opponents, where and when critical differences in intra-race pacing occur, and the tactical strategies employed to optimally manage energy resources. We analyzed pacing and tactics across the 800, 1,500, 5,000, 10,000 m, marathon and racewalk events, providing a broad overview for optimal preparation for racing and pacing. Official electronic splits from men's (n = 275 performances) and women's (n = 232 performances) distance races between 2013 and 2017 were analyzed. Athletes were grouped for the purposes of analysis and comparison. For the 800 m, these groups were the medalists and those finishing 4th to 8th ("Top 8"). For the 1,500 m, the medalists and Top 8 were joined by those finishing 9th to 12th ("Top 12"), whereas for all other races, the Top 15 were analyzed (those finishing 9th to 15th). One-way repeated measures analysis of variance was conducted on the segment speeds (p < 0.05), with effect sizes for differences calculated using Cohen's d. Positive pacing profiles were common to most 800 m athletes, whereas negative pacing was more common over longer distances. In the 1,500 m, male medalists separated from their rivals in the last 100 m, whereas for women it was after 1,200 m. Similarly, over 5,000 m, male medalists separated from the slowest pack members later (4,200 m; 84% of duration) than women (2,500 m; 50% of duration). In the 10,000 m race, the effect was very pronounced with men packing until 8,000 m, with the Top 8 athletes only dropped at 9,600 m (96% of duration). For women, the slowest pack begin to run slower at only 1,700 m, with the Top 8 finishers dropped at 5,300 m (53% of duration). Such profiles and patterns were seen across all events. It is possible the earlier separation in pacing for women between the medalists and the other runners was because of tactical racing factors such as an early realization of being unable to sustain the required speed, or perhaps because of greater variation in performance abilities.

Successful Pacing Profiles of Olympic and IAAF World Championship Middle-Distance Runners Across Qualifying Rounds and Finals

Purpose: This was the first study to analyze high-resolution pacing data from multiple global championships, allowing for deeper and rigorous analysis of pacing and tactical profiles in elite-standard middle-distance racing. The aim of this study was to analyze successful and unsuccessful middle-distance pacing profiles and variability across qualifying rounds and finals. Methods: Finishing and 100-m-split speeds and season’s best times were collected for 265 men and 218 women competing in 800- and 1500-m races, with pace variability expressed using coefficient of variation. Results: In both events, successful athletes generally separated themselves from slower athletes in the final 200 m, not by speeding up but by avoiding slowing compared with competitors. This was despite different pacing profiles between events in the earlier part of the race preceding the end spurt. Approximately 10% of athletes ran season’s best times, showing a tactical approach to elite-standard middle-distance racing and possible fatigue across rounds. Men’s and women’s pacing profiles were remarkably similar within each event, but the previously undescribed seahorse-shaped profile in the 800-m (predominantly positive pacing) differed from the J-shaped negative pacing of the 1500-m. Pacing variability was high compared with world records, especially in the finals (coefficient of variation: 5.2–9.1%), showing that athletes need to be able to vary pace and cope with surges. Conclusions: The best athletes had the physiological capacity to vary pace and respond to surges through successive competition rounds. In competition-specific training, coaches should incorporate several sessions in which pace changes frequently and sometimes unexpectedly.

Athlete-Opponent Interdependency Alters Pacing and Information-Seeking Behavior

PURPOSE

The influence of interdependency between competitors on pacing decision-making and information-seeking behavior has been explored. This has been done by only altering instructions, and thereby action possibilities, while controlling environment (i.e., competitor behavior) and exercise task.

METHODS

Twelve participants performed a 4-km time trial on a Velotron cycle ergometer in a randomized, counterbalanced order alone with no virtual opponent (NO), against a virtual opponent with no restrictions (low athlete-opponent interdependency [OP-IND]), or against a virtual opponent who the participant was permitted to overtake only once during the trial (high athlete-opponent interdependency [OP-DEP]). Information-seeking behavior was evaluated using an SMI eye tracker. Differences in pacing, performance, and information-seeking behavior were examined using repeated-measures ANOVA (P < 0.05).

RESULTS

Neither mean power output (NO, 298 ± 35 W; OP-IND, 297 ± 38 W; OP-DEP, 296 ± 37 W) nor finishing time (NO, 377.7 ± 17.4 s; OP-IND, 379.3 ± 19.5 s; OP-DEP, 378.5 ± 17.7 s) differed between experimental conditions. However, power output was lower in the first kilometer of OP-DEP compared with the other experimental conditions (NO, 332 ± 59 W; OP-IND, 325 ± 62 W; OP-DEP, 316 ± 58 W; both P < 0.05), and participants decided to wait longer before they overtook their opponent (OP-IND, 137 ± 130 s; OP-DEP, 255 ± 107 s; P = 0.040). Moreover, total fixation time spent on the avatar of the virtual opponent increased when participants were only allowed to overtake once (OP-IND, 23.3 ± 16.6 s; OP-DEP, 55.8 ± 32.7 s; P = 0.002).

CONCLUSION

A higher interdependency between athlete and opponent altered pacing behavior in terms of in-race adaptations based on opponent's behavior, and it induced an increased attentional focus on the virtual opponent. Thus, in the context of exercise regulation, attentional cues are likely to be used in an adaptive way according to their availability and situational relevance, consistent with a decision-making framework based on the interdependence of perception and action.

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.

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.

Race Strategies of Open Water Swimmers in the 5-km, 10-km, and 25-km Races of the 2017 FINA World Swimming Championships

Despite literature on the pacing strategies of endurance sports, there is an existing lack of knowledge about the swimmers’ tactical decisions in the open water races. The aims of the present research were (1) to compare the pacing profiles and tactical strategies of successful elite open water swimmers (men and women) in the 5-km, 10-km, and 25-km races and (2) to relate these pacing strategies to the end race results. Intermediate split times, positions and gaps with leaders of the first ten swimmers classified in the 2017 FINA World Swimming Championships races were collected from the public domain and were related to the finishing positions. Overall swimming velocities of the 5-km races were faster than the 10-km (δ 0.03 ± 0.03 m/s) and the 25-km (δ 0.14 ± 0.01 m/s) events with male swimmers achieving relatively faster mean velocities than females in the 5-km (δ 0.12 ± 0.01 m/s) compared to the 25-km (δ 0.08 ± 0.01 m/s) events. Medallist swimmers achieved moderate faster overall velocities than finalists in the 25-km races (0.01 ± 0.01 m/s) only. Inter-level differences were detected in selected splits for each race distance. Pacing profiles presented lap to lap velocity improvements in the 5-km and men’s 10-km races (from +0.02 ± 0.00 to +0.11 ± 0.01 m/s) but also mid-race decreases in the women’s 10-km and on the 25-km races. Successful swimmers were located in the leading positions of the 5-km races but at mid-group in the first part of the 10-km and 25-km races, with time gaps with leaders of 15–20 s. Faster lap swimming velocities, mid-race leading positions and shorter time-gaps were only related to the finishing positions in the last lap of the 10-km and in the three last laps of the 25-km events, but also in the first lap of the women’s 5-km race. Despite different mid-race positioning, successful open water swimmers typically presented negative pacing profiles, a consistent control of mid-race gaps with leaders (15–20 s maximum) and great spurts (4–6% faster than mean race velocities) at the end of races. Coaches and swimmers should be aware of the different race dynamics depending to the event distance in order to select optimal race strategies.

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.

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.

Effects of Strength Training on the Physiological Determinants of Middle- and Long-Distance Running Performance: A Systematic Review

Background

Middle- and long-distance running performance is constrained by several important aerobic and anaerobic parameters. The efficacy of strength training (ST) for distance runners has received considerable attention in the literature. However, to date, the results of these studies have not been fully synthesized in a review on the topic.

Objectives

This systematic review aimed to provide a comprehensive critical commentary on the current literature that has examined the effects of ST modalities on the physiological determinants and performance of middle- and long-distance runners, and offer recommendations for best practice.

Methods

Electronic databases were searched using a variety of key words relating to ST exercise and distance running. This search was supplemented with citation tracking. To be eligible for inclusion, a study was required to meet the following criteria: participants were middle- or long-distance runners with ≥ 6 months experience, a ST intervention (heavy resistance training, explosive resistance training, or plyometric training) lasting ≥ 4 weeks was applied, a running only control group was used, data on one or more physiological variables was reported. Two independent assessors deemed that 24 studies fully met the criteria for inclusion. Methodological rigor was assessed for each study using the PEDro scale.

Results

PEDro scores revealed internal validity of 4, 5, or 6 for the studies reviewed. Running economy (RE) was measured in 20 of the studies and generally showed improvements (2–8%) compared to a control group, although this was not always the case. Time trial (TT) performance (1.5–10 km) and anaerobic speed qualities also tended to improve following ST. Other parameters [maximal oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{ \hbox{max} }}}$$\end{document}V˙O2max), velocity at \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{ \hbox{max} }}}$$\end{document}V˙O2max, blood lactate, body composition] were typically unaffected by ST.

Conclusion

Whilst there was good evidence that ST improves RE, TT, and sprint performance, this was not a consistent finding across all works that were reviewed. Several important methodological differences and limitations are highlighted, which may explain the discrepancies in findings and should be considered in future investigations in this area. Importantly for the distance runner, measures relating to body composition are not negatively impacted by a ST intervention. The addition of two to three ST sessions per week, which include a variety of ST modalities are likely to provide benefits to the performance of middle- and long-distance runners.

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.

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.

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

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

Do I focus on the process of cycling or try to put my mind elsewhere? A comparison of concentration strategies for use in pacing by novice riders

The ability to hold a pace is a key skill for endurance athletes. The present study compared the influence of different strategies on how athletes learn to pace at 80% of their maximum performance for a 3-min cycle time trial. Participants first completed three maximal 3-min tests to establish maximal performance. During subsequent visits we asked participants to ride at 80% of their average maximal 3-min power output for four 3-min efforts under different conditions. Participants were blinded to feedback for three of the four conditions with participants (a) riding on feel (all feedback blinded), (b) associating on the task by focusing attention on the skills needed for efficient cycling, and (c) dissociating from the task by intentionally focusing concentration elsewhere (d) and finally, participants rode with full feedback where pace could be regulated via observation. All participants completed the blind condition first, the full feedback condition last, with association focus and dissociation focus rides being alternated. As expected, results showed participants rode close to the 80% goal when observing full feedback. Participants rode at 82% of maximum in the blind "ride on feel" condition, 79% in the associative condition, and 70% in the dissociative condition. We suggest results show that simple strategies related to concentration can influence the accuracy of pacing efforts. The difference in the ability to pace while using an associative or dissociative attentional focus was consistent with theory. The differences we observed occurred with minimal input from participants in terms of actively learning psychological skills. Future research is needed to investigate how athletes learn to use pacing strategies to help performance.

Pacing profile in the main international open-water swimming competitions

PURPOSE

Different aspects of pacing in endurance events have been investigated, however, there are very limited information on pacing strategies during open-water swimming. The aim was to describe and compare the pacing profile used by male and female open-water swimmers (OW-swimmers) during the 5-, 10- and 25 km races in the main international competitions.

METHODS

A total of 438 performances were analysed for 5 km, 579 for 10 km and 189 for 25 km, from 2012 to 2017. Swimmers were divided into four groups based on finishing time. G1 whose finishing times were within 0.5% of the winner's time, G2 between 0.51% and 1% slower than winner's time; G3 between 1.1% and 2% slower than winner's time; G4 over 2% of winner's time. Kolmogorov-Smirnov test was used to verify the normal distribution of data and repeated measures ANOVA was performed.

RESULTS

G1 adopted a negative pacing and significantly increased the speed in the last split compared with the other groups during the 5-, 10- and 25-km races in both males and females (p < .001). During the 5- and 10-km race, the last split speed of G1 was significantly faster compared to the other groups in both males and females (p < .05).

CONCLUSIONS

OW-swimmers that used a conservative approach remaining in G1 until the finish of the race, increase the possibility to win a medal in the main international competitions.

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.

Differences in pacing of cross-country skiers by nationality - The example of Vasaloppet 2004-2017

It has been previously observed that athletes of certain origin nationality dominate particular sports; however, this phenomenon has been less studied in cross-country (XC) skiing, especially with regards to performance-related aspects, such as pacing. The aim of the present study was to examine the effect of nationality on pacing strategies of XC skiers who finished the "Vasaloppet" from 2004 to 2017. We studied 183,919 finishers (19,465 women and 164,454 men), classified into 15 nationalities, i.e. nationalities with number of finishers larger than 0.25% of the total number of finishers. In women, athletes from Russia (7:47:46 h:min:s) were the fastest and athletes from Denmark (10:01:03 h:min:s) the slowest (p < 0.001, η² = 0.057). In men, athletes from Russia (6:33:03 h:min:s) were the fastest and athletes from Denmark (9:03:27 h:min:s) the slowest (p < 0.001, η² = 0.069). In women and men, a small nationality× split interaction on speed was observed (p < 0.001, η² = 0.016-0.019) with Russians presenting a more even pacing compared to their slower counterparts. It was concluded that fast nationalities present a more even pacing, which should be attributed to the general trend of fast athletes for a more even pacing.

Exercise Intensity During Cross-Country Skiing Described by Oxygen Demands in Flat and Uphill Terrain

Purpose: In this study wearable global navigation satellite system units were used on athletes to investigate pacing patterns by describing exercise intensities in flat and uphill terrain during a simulated cross-country ski race.

Methods: Eight well-trained male skiers (age: 23.0 ± 4.8 years, height: 183.8 ± 6.8 cm, weight: 77.1 ± 6.1 kg, VO_2peak: 73 ± 5 mL⋅kg^-1⋅min^-1) completed a 13.5-km individual time trial outdoors and a standardized indoor treadmill protocol on roller skis. Positional data were recorded during the time trial using a differential global navigation satellite system to calculate external workloads in flat and uphill terrain. From treadmill tests, the individual relationships between oxygen consumption and external workload in flat (1°) and uphill (8°) terrain were determined, in addition to VO_2peak and the maximal accumulated O₂-deficit. To estimate the exercise intensity in the time trial, the O₂-demand in two different flat and five different uphill sections was calculated by extrapolation of individual O₂-consumption/workload ratios.

Results: There was a significant interaction between section and average O₂-demands, with higher O₂-demands in the uphill sections (110–160% of VO_2peak) than in the flat sections (≤100% of VO_2peak) (p < 0.01). The maximal accumulated O₂-deficit associated with uphill treadmill roller skiing was significantly higher compared to flat (6.2 ± 0.5 vs. 4.6 ± 0.5 L, p < 0.01), while no significant difference was found in VO_2peak.

Conclusion: Cross-country (XC) skiers repeatedly applied exercise intensities exceeding their maximal aerobic power. ΣO₂-deficits were higher during uphill skiing compared to flat which has implications for the duration and magnitude of supramaximal work rates that can be applied in different types of terrain.

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.

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

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

Effect of age and performance on pacing of marathon runners

Pacing strategies in marathon runners have previously been examined, especially with regard to age and performance level separately. However, less information about the age × performance interaction on pacing in age-group runners exists. The aim of the present study was to examine whether runners with similar race time and at different age differ for pacing. Data (women, n=117,595; men, n=180,487) from the “New York City Marathon” between 2006 and 2016 were analyzed. A between–within subjects analysis of variance showed a large main effect of split on race speed (p<0.001, η²=0.538) with the fastest speed in the 5–10 km split and the slowest in the 35–40 km. A small sex × split interaction on race speed was found (p<0.001, η²=0.035) with men showing larger increase in speed at 5 km and women at 25 km and 40 km (end spurt). An age-group × performance group interaction on Δspeed was shown for both sexes at 5 km, 10 km, 15 km, 20 km, 25 km, 30 km, 35 km, and 40 km (p<0.001, 0.001≤η²≤0.004), where athletes in older age-groups presented a relatively more even pace compared with athletes in younger age-groups, a trend that was more remarkable in the relatively slow performance groups. So far, the present study is the first one to observe an age × performance interaction on pacing; ie, older runners pace differently (smaller changes) than younger runners with similar race time. These findings are of great practical interest for coaches working with marathon runners of different age, but similar race time.

The Science of Racing against Opponents: Affordance Competition and the Regulation of Exercise Intensity in Head-to-Head Competition

Athlete–environment interactions are crucial factors in understanding the regulation of exercise intensity in head-to-head competitions. Previously, we have proposed a framework based on the interdependence of perception and action, which allows us to explore athletic behavior in the more complex pacing situations occurring when athletes need to respond to actions of their opponents. In the present perspective we will further explore whether opponents, crucial external factors in competitive sports, could indeed be perceived as social invitations for action. Decisions regarding how to expend energy over the race are based on internal factors such as the physiological/biomechanical capacity of the athlete in relation to external factors such as those presented by opponents. For example: Is the athlete able to overtake competitors, or not? We present several experimental studies that demonstrate that athletes regulate their exercise intensity differently in head-to-head competition compared to time-trial exercises: Relational athlete-environment aspects seem to outweigh benefits of the individual optimal energy distribution. Also, the behavior of the opponents has been shown to influence pacing strategies of competing athletes, again demonstrating the importance of relational athlete–environment aspects in addition to strictly internal factors. An ecological perspective is presented in which opponents are proposed to present social affordances, and decision-making is conceptualized as a resultant of affordance-competition. This approach will provide novel insights in tactical decision-making and pacing behavior in head-to-head competitions. Future research should not only focus on the athlete's internal state, but also try to understand opponents in the context of the social affordances they provide.

Altering Pace Control and Pace Regulation: Attentional Focus Effects during Running

PURPOSE

To date, there are no published studies directly comparing self-controlled (SC) and externally controlled (EC) pace endurance tasks. However, previous research suggests pace control may impact on cognitive strategy use and effort perceptions. The primary aim of this study was to investigate the effects of manipulating perception of pace control on attentional focus, physiological, and psychological outcomes during running. The secondary aim was to determine the reproducibility of self-paced running performance when regulated by effort perceptions.

METHODS

Twenty experienced endurance runners completed four 3-km time trials on a treadmill. Subjects completed two SC pace trials, one perceived exertion clamped (PE) trial, and one EC pace time trial. PE and EC were completed in a counterbalanced order. Pacing strategy for EC and perceived exertion instructions for PE replicated the subjects' fastest SC time trial.

RESULTS

Subjects reported a greater focus on cognitive strategies such as relaxing and optimizing running action during EC than during SC. The mean HR was 2% lower during EC than that during SC despite an identical pacing strategy. Perceived exertion did not differ between the three conditions. However, increased internal sensory monitoring coincided with elevated effort perceptions in some subjects during EC and a 10% slower completion time for PE (13.0 ± 1.6 min) than that for SC (11.8 ± 1.2 min).

CONCLUSIONS

Altering pace control and pace regulation impacted on attentional focus. External control over pacing may facilitate performance, particularly when runners engage attentional strategies conducive to improved running efficiency. However, regulating pace based on effort perceptions alone may result in excessive monitoring of bodily sensations and a slower running speed. Accordingly, attentional focus interventions may prove beneficial for some athletes to adopt task-appropriate attentional strategies to optimize performance.