Risk Perception Influences Athletic Pacing Strategy

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.

Differential improvements between men and women in repeated CrossFit open workouts

INTRODUCTION

The CrossFit® Open (CFO) acts a preliminary round that qualifies men and women for later stages of its annual Games competition. The CFO typically consists of 4-6 workouts that variably challenge an athlete's weightlifting strength, gymnastic skill, and endurance capacity. Except for differences in prescribed intensity loads, workouts are designed the same for men and women to elicit a similar challenge. While all workouts within a single year are unique to each other, one has been repeated from a previous CFO each year between 2012 and 2021. Because previous CFO workouts are often integrated into training, improvements are expected when a workout is officially repeated. However, besides documented record performances, it is unclear whether most athletes are improving, if these improvements affect ranking, or if differences exist between men and women.

PURPOSE

To examine sex-division differences and performance changes across repeated CFO workouts, as well as their effect on CFO and workout ranking.

METHODS

Eleven separate samples of 500 men and 500 women, who were representative of the same overall percent rank within each year involving one of the nine repeated CFO workouts (2011-2021) were drawn for this study. Each athlete's age (18-54 years), rank (overall and within each workout), and reported workout scores were collected from the competition's publicly-available leaderboard. Each sample had excluded any athlete who had not met minimum performance criteria (e.g., at least one completed round) for all prescribed (Rx) workouts within a given year (including those not analyzed). Since some workouts could be scored as repetitions completed or time-to-completion (TTC), and because programming was often scaled between men and women, all scores were converted to a repetition completion rate (repetitions divided by TTC [in minutes]).

RESULTS

Separate sex-division x time analyses of variance with repeated measures revealed significant (p < 0.05) interactions in all but one repeated workout comparison. Initially, men were faster in four workouts (~18.5%, range = 3.9-35.0%, p < 0.001), women in two (~7.1%, range = 5.2-9.0%, p < 0.001), and they tied in the remaining three workouts. When workouts were repeated in subsequent years, men were faster in three workouts (~5.4%, range = 0.9-7.8%, p < 0.05), while women were faster in two (~3.8%, range = 3.5-4.1%, p < 0.01). Though performance improved in seven of the nine workouts (~14.3%, p < 0.001) and percentile rank was controlled, athletes earned a lower rank (overall and within workout) on each repeated workout (p < 0.001).

CONCLUSIONS

Performance (measured as repetition completion rate) has improved in most repeated CFO workouts, particularly for women. However, improvements seen among all athletes, along with increased participation, have made it more difficult for athletes to improve their overall rank. To rank higher, individual athletes must improve their pace to a greater degree than the average improvements seen across the competitive field.

Tactical positioning behaviours in short-track speed skating: A static and dynamic sequence analysis

Tactical positioning is essential for success in short-track speed skating as the race format (direct, head-to-head competition over multiple laps) prioritises finishing position over finishing time. Despite this, current research into tactical positioning treats the race's laps as discrete, independent events. Accordingly, the aggregate metrics used to summarise each lap's tactical positioning behaviour do not allow us to explore the sequential nature of the data, e.g., Lap 2 occurs after Lap 1 and before Lap 3. Here, we capture the sequential relationships between laps to investigate tactical positioning behaviours in short-track speed skating. Using intermediate and final rankings from 500 m, 1,000 m, and 1,500 m elite short-track races, we analyse whole-race and sub-race race sequences of group and winner tactical positioning behaviours. This approach, combined with a large dataset of races collected over eight seasons of competition (n  = 4,135), provides the most rigorous and comprehensive description of tactical positioning behaviours in short-track speed skating to date. Our results quantify the time-evolving complexity of tactical positioning, offer new thoughts on race strategy, and can help practitioners design more representative learning tasks to enhance skill transfer.

Pacing Behavior Development in Adolescent Swimmers: A Large-Scale Longitudinal Data Analysis

PURPOSE

This study aimed to use a large-scale longitudinal design to investigate the development of the distribution of effort (e.g., pacing) in adolescent swimmers, specifically disentangling the effects of age and experience and differentiating between performance levels in adulthood.

METHODS

Season best times and 50-m split times of 100- and 200-m freestyle swimmers from five continents were gathered between 2000 and 2021. Included swimmers competed in a minimum of three seasons between 12 and 24 yr old (5.3 ± 1.9 seasons) and were categorized by performance level in adulthood (elite, sub-elite, high-competitive; 100-m: n = 3498 (47% female); 200-m: n = 2230 (56% female)). Multilevel models in which repeated measures (level 1) were nested within individual swimmers (level 2) were estimated to test the effects of age, race experience, and adult performance level on the percentage of total race time spent in each 50-m section ( P < 0.05).

RESULTS

In the 100-m, male swimmers develop a relatively faster first 50-m when becoming older. This behavior also distinguishes elite from high-competitive swimmers. No such effects were found for female swimmers. Conversely, more experienced male and female swimmers exhibit a slower initial 50-m. With age and race experience, swimmers develop a more even velocity distribution in the 200-m. Adolescent swimmers reaching the elite level adopt a more even behavior compared with high-competitive. This differentiation occurs at a younger age in female (>13 yr) compared with male (>16 yr) swimmers.

CONCLUSIONS

Pacing behavior development throughout adolescence is driven by age-related factors besides race experience. Swimmers attaining a higher performance level during adulthood exhibit a pacing behavior that better fits the task demands during adolescence. Monitoring and individually optimizing the pacing behavior of young swimmers is an important step toward elite performance.

Experience, Training Preferences, and Fighting Style Are Differentially Related to Measures of Body Composition, Strength, and Power in Male Brazilian Jiu Jitsu Athletes-A Pilot Study

To examine relationships between Brazilian Jiu Jitsu (BJJ) descriptors (belt rank, experience, gi preference, and fighting style), resistance training (RT) experience, and measures of body composition, strength (maximal handgrip, 3-5-repetition maximum [RM] in barbell glute bridge [GB], prone bench row [PBR], and bench press [BP]), and velocity (GB, PBR, and BP at 7 kg and 30−60% 1-RM), 13 experienced (4.3 ± 3.4 years) BJJ athletes were recruited for this cross-sectional, pilot study. Significant (p < 0.05) Kendall’s tau and Bayesian relationships were seen between belt rank and body fat percentage (τ = −0.53, BF10 = 6.5), BJJ experience and body fat percentage (τ = −0.44 to −0.66, BF10 = 2.6−30.8) and GB velocity (τ = −0.45 to −0.46, BF10 = 2.8−3.1), RT experience and strength (τ = 0.44 to 0.73, BF10 = 2.6−75.1) and velocity (τ = −0.44 to 0.47, BF10 = 2.6−3.3), gi preference-training and relative PBR strength (τ = 0.70, BF10 = 51.9), gi preference-competition and height and lean mass (τ = −0.57 to 0.67, BF10 = 5.3−12.4) and BP velocity (τ = −0.52 to 0.67, BF10 = 3.5−14.0). The relevance of body composition and performance measures to sport-specific training and research interpretation are differentially affected by a BJJ athlete’s experience (BJJ, belt rank, RT), gi preferences, and fighting style.

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.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

Tactical positioning in short-track speed skating: The utility of race-specific athlete-opponent interactions

In short-track speed skating, tactical positioning is essential for success as the race format (head-to-head) prioritises finishing position over finishing time. At present, our understanding of this phenomenon is based on measuring the similarity between athletes' intermediate and final rankings. However, as this approach groups athlete performances across races, each lap's estimate of tactical importance ignores the athlete-opponent interactions specific to each race. Here, we examine the utility of race-specific athlete-opponent interactions for investigating tactical positioning. Using intermediate and final rankings of elite 1,000 m short-track speed skating competitors collected from 2010/11 to 2017/18 (n = 6,196, races = 1,549), we compared the current method to a novel approach that accounted for race-specific athlete-opponent interactions. This approach first applied the current method to each race independently before using these values to form (1) discrete, empirical distributions of each lap's tactical importance and (2) race-specific tactical positioning sequences. Our results showed that accounting for race-specific athlete-opponent interactions provided a higher measurement granularity (i.e., level of detail) for investigating tactical positioning in short-track speed skating, which better captured the complexity of the phenomenon. We observed 61 different tactical positioning behaviours and 1,269 unique tactical positioning sequences compared to the current approach's nine-point estimates of tactical positioning importance. For this reason, we recommend that researchers and practitioners account for race-specific athlete-opponent interactions in the future as it offers a deeper understanding of tactical positioning that will enhance both strategic and tactical decisions.

CrossFit® open performance is affected by the nature of past competition experiences

Purpose

To examine the relationships between past competition performances and 2020 CrossFit® Open (CFO) performance.

Methods

A random selection from the top one thousand athletes (n = 220, 28.5 ± 4.4 years, 178 ± 7 cm, 87.5 ± 10.2 kg) were selected for this study. Overall and weekly performances (including ranks and scores) of the 2020 CFO, as well as overall ranks from all previous CFO, regional, and Games™ competitions in which they competed, were recorded from their publicly available online profile. The highest, lowest, average, and standard deviation (SD) of past rankings, as well as participation statistics (i.e., years since first appearance, total and consecutive appearances, and participation rate), were calculated for each competition stage. Relationships were then assessed between 2020 CFO performance and all past competition experience variables by calculating Kendall’s tau (τ) correlation coefficients and Bayes factors (BF₁₀).

Results

Overall and weekly ranking of the 2020 CFO was extremely favored (p < 0.001, BF₁₀ > 100) to be related to the athlete’s highest previous CFO rank (τ = 0.26–0.39) and individual regional appearances (τ = − 0.26 to − 0.34), as well as individual Games™ appearances (overall and for weeks 1, 3, and 4; τ = − 0.20 to − 0.22, p < 0.001, BF₁₀ > 100). Evidence for all other significant relationships ranged from moderate to very strong (p < 0.05, BF₁₀ = 3–100) and varied among specific 2020 CFO workouts. Few associations were noted for team competition experience, and these were generally limited to Games™ appearances (τ = − 0.12 to − 0.18, p < 0.05, BF₁₀ = 3.3–100).

Conclusions

Although specific relationships were found between 2020 CFO performance and individual appearances at regional and Games™ competitions, the most consistent relationships were seen with participation and ranking in past CFO competitions.

Evidence on the Relationship Between Emotional Intelligence and Risk Behavior: A Systematic and Meta-Analytic Review

The aim of the present study was to carry out a qualitative and quantitative synthesis of the existing literature studying the relationship between emotional intelligence and risk behavior. We conducted a systematic review and meta-analysis of the scientific evidence available relating both constructs. Particular attention was paid to identifying possible differences in this relationship as a function of the different conceptualizations of EI and the risk domain. The study was conducted following the Cochrane and PRISMA guidelines. Our results revealed a significant negative relationship between EI and health-related risk behaviors. However, this relationship was not observed in other risk domains such as finance and gambling. The relationship between EI and risk behavior differed according to the risk domain studied, which supports the notion that risk is a domain-specific construct. The results associated with the health-related risk behaviors are consistent with existing literature about the positive impact of emotional abilities on the health domain. A more complete understanding of the emotional mechanisms that underlie risk behavior could help to establish action guidelines and improve programmes to prevent and reduce the negative effects of risk behavior on our society.

Workout Pacing Predictors of Crossfit® Open Performance: A Pilot Study

To observe workout repetition and rest interval pacing strategies and determine which best predicted performance during the 2016 CrossFit® Open, five male (34.4 ± 3.8 years, 176 ± 5 cm, 80.3 ± 9.7 kg) and six female (35.2 ± 6.3 years, 158 ± 7 cm, 75.9 ± 19.3 kg) recreational competitors were recruited for this observational, pilot study. Exercise, round, and rest time were quantified via a stopwatch for all competitors on their first attempt of each of the five workouts. Subsequently, pacing was calculated as a repetition rate (repetitions·s^-1) to determine the fastest, slowest, and average rate for each exercise, round, and rest interval, as well as how these changed (i.e., slope, Δ rate / round) across each workout. Spearman’s rank correlation coefficients indicated that several pacing variables were significantly (p < 0.05) related to performance on each workout. However, stepwise regression analysis indicated that the average round rate best predicted (p < 0.001) performance on the first (R² = 0.89), second (R² = 0.99), and fifth (R² = 0.94) workouts, while the competitors’ rate on their slowest round best predicted workout three performance (R² = 0.94, p < 0.001). The wall ball completion rate (R² = 0.89, p = 0.002) was the best predictor of workout four performance, which was improved by 9.8% with the inclusion of the deadlift completion rate. These data suggest that when CrossFit^® Open workouts consist of multiple rounds, competitors should employ a fast and sustainable pace to improve performance. Otherwise, focusing on one or two key exercises may be the best approach.

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.

Pre-planned Vs. Executed Real-Time Pacing Strategies during 3-km Race: Role of Rating Perceived Exertion

Purpose: The aim of the study was to verify the agreement between preplanned and executed pacing during a 3-km race and determine whether adjustments are mediated by the rating of perceived exertion (RPE). Method: Thirteen young runners (eight males and five females, 17.5 ± 2.1 and 17.0 ± 1.6 years old, respectively) with national and international experience participated in the study. Before the simulated competition, the athletes informed of their preplanned pacing for the distance through a dashboard with the most common pacing profiles and were also asked to complete a questionnaire communicating their preplanned RPE for each lap of race. During 3-km, heart rate (HR), executed RPE and lap time were recorded. Results: Our results showed no significant association between preplanned and executed pacing (p = .631). Moreover, no significant difference between preplanned and executed RPE was found, including the analysis by laps and phases. RPE and HR increased over time during the race (p < .001). Conclusions: The athletes changed from their preplanned pacing, however, their RPE were similar in the preplanned and executed during the 3-km race. These findings indicate that the RPE could be responsible for adjustments in the pacing strategy.

The Potential to Change Pacing and Performance During 4000-m Cycling Time Trials Using Hyperoxia and Inspired Gas-Content Deception

PURPOSE

Determine if a series of trials with fraction of inspired oxygen (FiO2) content deception could improve 4000-m cycling time-trial (TT) performance.

METHODS

Fifteen trained male cyclists (mean ± SD: body mass 74.2 ± 8.0 kg; peak oxygen uptake 62 ± 6 mL.kg-1.min-1) completed six, 4000-m cycling TTs in a semi-randomised order. After a familiarisation TT, cyclists were informed in two initial trials they were inspiring normoxic air (NORM, FiO2: 0.21), however in one trial (deception condition) they inspired hyperoxic air (NORM-DEC, FiO2: 0.36). During two subsequent TTs, cyclists were informed they were inspiring hyperoxic air (HYPER, FiO2: 0.36), but in one trial normoxic air was inspired (HYPER-DEC). In the final TT (NORM-INFORM) the deception was revealed, and cyclists were asked to reproduce their best TT performance while inspiring normoxic air.

RESULTS

Greater power output and faster performances occurred when cyclists inspired hyperoxic air in both truthful (HYPER) and deceptive (NORM-DEC) trials compared to NORM (P < 0.001). However, performance only improved in NORM-INFORM (377 W [95% CI 325, 429]) vs NORM (352 W [299, 404]), P < 0.001) when participants (n = 4) completed the trials in the following order: NORM-DEC, NORM, HYPER-DEC, HYPER.

CONCLUSIONS

Cycling performance improved with acute exposure to hyperoxia. Mechanisms for the improvement were likely physiological, however improvement in a deception trial suggests an additional placebo effect may be present. Finally, a particular sequence of oxygen deception trials may have built psycho-physiological belief in cyclists such that performance improved in a subsequent normoxic trial.

Are experienced and high-level race walking athletes able to match pre-programmed with executed pacing?

The objective of this study was to verify the agreement between pre-programmed and executed pacing during race walking and whether level of the athletes experience and performance influenced this relationship. Twenty-nine national and international race walkers participated in this study (14 males, 24.0±7.1 years old, and 15 females, 23.3±7.3 years old). Pre-programmed pacing for 10- and 20-km official walking races was self-selected via demonstrative pacing charts prior to races, while executed pacing was analyzed by a specialist investigator via an individual plot of current velocity versus distance. There was no agreement between pre-programmed and executed pacing (P=0.674). There was no association between the ability to match the pre-programmed pace with the executed pace and race walking experience or level of performance. Low- and high-performance athletes pre-programmed a similar pacing profile (P=0.635); however, high-performance athletes generally executed an even pacing strategy, while low-performance athletes generally adopted a positive pacing strategy (P=0.013). Race walkers did not faithfully match their pre-programmed with their executed pacing, and this seemed to be independent of previous experience and level of performance. High-performance athletes, however, tended to execute an even pacing strategy, even though this had not been pre-programmed.

Developing a Broadly Applicable Measure of Risk Perception

Decades of research identify risk perception as a largely intuitive and affective construct, in contrast to the more deliberative assessments of probability and consequences that form the foundation of risk assessment. However, a review of the literature reveals that many of the risk perception measures employed in survey research with human subjects are either generic in nature, not capturing any particular affective, probabilistic, or consequential dimension of risk; or focused solely on judgments of probability. The goal of this research was to assess a multidimensional measure of risk perception across multiple hazards to identify a measure that will be broadly useful for assessing perceived risk moving forward. Our results support the idea of risk perception being multidimensional, but largely a function of individual affective reactions to the hazard. We also find that our measure of risk perception holds across multiple types of hazards, ranging from those that are behavioral in nature (e.g., health and safety behaviors), to those that are technological (e.g., pollution), or natural (e.g., extreme weather). We suggest that a general, unidimensional measure of risk may accurately capture one's perception of the severity of the consequences, and the discrete emotions that are felt in response to those potential consequences. However, such a measure is not likely to capture the perceived probability of experiencing the outcomes, nor will it be as useful at understanding one's motivation to take mitigation action.

Risk Taking Runners Slow More in the Marathon

Much research has explored the physiological, energetic, environmental, and psychological factors that influence pacing in endurance events. Although this research has generally neglected the role of psychological variation across individuals, recent studies have hinted at its importance. Here we conducted an online survey of over 1,300 marathon runners, testing whether any of five psychological constructs - competitiveness, goal achievement, risk taking in pace (RTP), domain-specific risk taking, and willingness to suffer in the marathon - predicted slowing in runners' most recent marathons. Analyses revealed that RTP - the extent to which runners agreed that they began the marathon at a pace that was so fast that it would jeopardize their capacity to maintain this pace throughout the event - was a robust predictor of marathon slowing. RTP proved a substantial predictor even in regression models controlling for the other psychological constructs, training, experience, and other known pacing correlates. This result suggests that marathoners consider trade-offs when making pacing decisions, and that individuals vary in their pacing decision making.

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

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

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

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

The Effect of Head-to-Head Competition on Behavioural Thermoregulation, Thermophysiological Strain and Performance During Exercise in the Heat

Background

It has been suggested that pacing is a thermoregulatory behaviour. We investigated the effect of competition on pacing, performance and thermophysiological strain during exercise in the heat and the psychological factors mediating competition effects.

Method

Eighteen males (maximum oxygen uptake [VO_2max] 3.69 [0.44] L min⁻¹) undertook a preliminary 20-km cool (wet-bulb globe temperature [WBGT] 12 °C) cycling time trial (TT) and three experimental 20-km trials (balanced order): (i) cool TT (CoolSolo); (ii) hot (WBGT 26 °C) TT (HotSolo); (iii) hot head-to-head competition (HotH2H). During TTs, an avatar of the participant’s performance was visible. During HotH2H, participants believed they were competing against another participant, but the competitor’s avatar replicated their own preliminary (cool) TT.

Results

TTs (min:sec [SD]) slowed with increased ambient temperature [CoolSolo 35:31 (2:11) versus HotSolo 36:10 (2:26); p = 0.011]. This effect was negated by competition; performances were not different between HotH2H [35:17 (1:52)] and CoolSolo (p = 0.160) and were quicker in HotH2H versus HotSolo (p = 0.001). End-exercise rectal temperature, mean body temperature and physiological strain index were (p < 0.05) higher in HotH2H than either solo condition. Despite faster performance and greater thermophysiological strain, rating of perceived exertion (RPE), thermal comfort and sensation, and perceptual strain index were not different between HotH2H and HotSolo. The difference in end-exercise rectal temperature between HotH2H and HotSolo was related to pre-exercise anticipatory heart rate response (r = 0.608, p = 0.010) and participants’ propensity for deliberate risk-taking (B = 0.12, p < 0.001), whereas self-reported resilience predicted change in performance times between HotH2H versus HotSolo (B = − 9.40, p = 0.010).

Conclusion

Competition changes the relationship between perceived and actual thermophysiological state, altering behavioural thermoregulation and increasing thermophysiological strain; this could increase heat-illness risk. Psychophysiological and psychological measures may identify susceptible individuals.

Anticipated Task Difficulty Provokes Pace Conservation and Slower Running Performance

PURPOSE

Models of self-paced endurance performance suggest that accurate knowledge of the exercise end-point influences pace-related decision making. No studies have examined the effects of anticipated task difficulty during equidistant endurance activities. Accordingly, the purpose of this study was to investigate the effects of anticipated task difficulty on pacing, psychological, and physiological responses during running time trials.

METHODS

Twenty-eight trained runners completed three self-paced 3000-m time trials. The first was a baseline time trial completed on a 0% treadmill gradient. Time trials 2 and 3 were counterbalanced. Before a known incline time trial, anticipated to be more difficult, subjects were accurately informed that the gradient would increase to 7% for the final 800 m. Before an equivalent, unknown incline (UI) time trial subjects were deceptively informed that the gradient would remain at 0% throughout.

RESULTS

Expressed relative to baseline, running speed was 2.44% slower (d = -0.47) over the first 2200 m during known incline (KI) time trial than UI time trial. Effort perception, affective valence, heart rate, and blood lactate did not differ between time trials. Initial running speed during KI was related to pretrial motivation, pretrial vigor, perceived effort, and affective valence (all r ≥ 0.382). No such relationships existed during UI. More subjects also reported a conscious focus on pacing during KI.

CONCLUSIONS

An anticipated increase in task difficulty provoked pace conservation during 3000 m running time trials. The reduced pace may have resulted from greater task uncertainty and consciously aware, effort- and affect-based decisions to conserve energy and maintain hedonic state during KI. The findings add to theoretical understandings of factors that influence pacing during endurance activity. Consequently, recommendations to minimize the potentially deleterious effects of anticipated increases in task difficulty are provided.

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

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

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

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

Will the Conscious-Subconscious Pacing Quagmire Help Elucidate the Mechanisms of Self-Paced Exercise? New Opportunities in Dual Process Theory and Process Tracing Methods

The extent to which athletic pacing decisions are made consciously or subconsciously is a prevailing issue. In this article we discuss why the one-dimensional conscious-subconscious debate that has reigned in the pacing literature has suppressed our understanding of the multidimensional processes that occur in pacing decisions. How do we make our decisions in real-life competitive situations? What information do we use and how do we respond to opponents? These are questions that need to be explored and better understood, using smartly designed experiments. The paper provides clarity about key conscious, preconscious, subconscious and unconscious concepts, terms that have previously been used in conflicting and confusing ways. The potential of dual process theory in articulating multidimensional aspects of intuitive and deliberative decision-making processes is discussed in the context of athletic pacing along with associated process-tracing research methods. In attempting to refine pacing models and improve training strategies and psychological skills for athletes, the dual-process framework could be used to gain a clearer understanding of (1) the situational conditions for which either intuitive or deliberative decisions are optimal; (2) how intuitive and deliberative decisions are biased by things such as perception, emotion and experience; and (3) the underlying cognitive mechanisms such as memory, attention allocation, problem solving and hypothetical thought.

Physiology and Pathophysiology in Ultra-Marathon Running

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

The Influence of Mid-Event Deception on Psychophysiological Status and Pacing Can Persist across Consecutive Disciplines and Enhance Self-paced Multi-modal Endurance Performance

Purpose: To examine the effects of deceptively aggressive bike pacing on performance, pacing, and associated physiological and perceptual responses during simulated sprint-distance triathlon.

Methods: Ten non-elite, competitive male triathletes completed three simulated sprint-distance triathlons (0.75 km swim, 500 kJ bike, 5 km run), the first of which established personal best “baseline” performance (BL). During the remaining two trials athletes maintained a cycling power output 5% greater than BL, before completing the run as quickly as possible. However, participants were informed of this aggressive cycling strategy before and during only one of the two trials (HON). Prior to the alternate trial (DEC), participants were misinformed that cycling power output would equal that of BL, with on-screen feedback manipulated to reinforce this deception.

Results: Compared to BL, a significantly faster run performance was observed following DEC cycling (p < 0.05) but not following HON cycling (1348 ± 140 vs. 1333 ± 129 s and 1350 ± 135 s, for BL, DEC, and HON, respectively). As such, magnitude-based inferences suggest HON running was more likely to be slower, than faster, compared to BL, and that DEC running was probably faster than both BL and HON. Despite a trend for overall triathlon performance to be quicker during DEC (4339 ± 395 s) compared to HON (4356 ± 384 s), the only significant and almost certainly meaningful differences were between each of these trials and BL (4465 ± 420 s; p < 0.05). Generally, physiological and perceptual strain increased with higher cycling intensities, with little, if any, substantial difference in physiological and perceptual response during each triathlon run.

Conclusions: The present study is the first to show that mid-event pace deception can have a practically meaningful effect on multi-modal endurance performance, though the relative importance of different psychophysiological and emotional responses remains unclear. Whilst our findings support the view that some form of anticipatory “template” may be used by athletes to interpret levels of psychophysiological and emotional strain, and regulate exercise intensity accordingly, they would also suggest that individual constructs such as RPE and affect may be more loosely tied with pacing than previously suggested.

Exogenous Cortisol Administration; Effects on Risk Taking Behavior, Exercise Performance, and Physiological and Neurophysiological Responses

Rationale: Exogenous cortisol is a modulator of behavior related to increased motivated decision making (Putman et al., 2010), where risky choices yield potentially big reward. Making risk based judgments has been shown to be important to athletes in optimizing pacing during endurance events (Renfree et al., 2014; Micklewright et al., 2015).

Objectives: Therefore, the aims of this study were to examine the effect of 50 mg exogenous cortisol on neurophysiological responses and risk taking behavior in nine healthy men. Further to this, to examine the effect of exogenous cortisol on exercise performance.

Methods: Using a double blind counterbalanced design, cyclists completed a placebo (PLA), and a cortisol (COR) trial (50 mg cortisol), with drug ingestion at 0 min. Each trial consisted of a rest period from 0 to 60 min, followed by a risk taking behavior task, a 30 min time trial (TT) with 5 × 30 s sprints at the following time intervals; 5, 11, 17, 23, and 29 min. Salivary cortisol (SaCOR), Electroencephalography (EEG) and Near Infrared Spectroscopy (NIRs) were measured at 15, 30, 45, and 60 min post-ingestion. Glucose and lactate samples were taken at 0 and 60 min post-ingestion. During exercise, power output (PO), heart rate (HR), EEG, and NIRS were measured. SaCOR was measured 10 min post-exercise.

Results: Cortisol increased risk taking behavior from baseline testing. This was in line with significant neurophysiological changes at rest and during exercise. At rest, SaCOR levels were higher (P < 0.01) in COR compared to PLA (29.7 ± 22.7 and 3.27 ± 0.7 nmol/l, respectively). At 60 min alpha slow EEG response was higher in COR than PLA in the PFC (5.5 ± 6.4 vs. −0.02 ± 8.7% change; P < 0.01). During the TT there was no difference in total km, average power or average sprint power, although Peak power (PP) achieved was lower in COR than PLA (465.3 ± 83.4 and 499.8 ± 104.3; P < 0.05) and cerebral oxygenation was lower in COR (P < 0.05).

Conclusion: This is the first study to examine the effect of exogenous cortisol on exercise performance. These results are in line with previous research showing altered risk taking behavior following exogenous cortisol, however the altered behavior did not translate into changes in exercise performance.

Effect of Environmental and Feedback Interventions on Pacing Profiles in Cycling: A Meta-Analysis

In search of their optimal performance athletes will alter their pacing strategy according to intrinsic and extrinsic physiological, psychological and environmental factors. However, the effect of some of these variables on pacing and exercise performance remains somewhat unclear. Therefore, the aim of this meta-analysis was to provide an overview as to how manipulation of different extrinsic factors affects pacing strategy and exercise performance. Only self-paced exercise studies that provided control and intervention group(s), reported trial variance for power output, disclosed the type of feedback received or withheld, and where time-trial power output data could be segmented into start, middle and end sections; were included in the meta-analysis. Studies with similar themes were grouped together to determine the mean difference (MD) with 95% confidence intervals (CIs) between control and intervention trials for: hypoxia, hyperoxia, heat-stress, pre-cooling, and various forms of feedback. A total of 26 studies with cycling as the exercise modality were included in the meta-analysis. Of these, four studies manipulated oxygen availability, eleven manipulated heat-stress, four implemented pre-cooling interventions and seven studies manipulated various forms of feedback. Mean power output (MPO) was significantly reduced in the middle and end sections (p < 0.05), but not the start section of hypoxia and heat-stress trials compared to the control trials. In contrast, there was no significant change in trial or section MPO for hyperoxic or pre-cooling conditions compared to the control condition (p > 0.05). Negative feedback improved overall trial MPO and MPO in the middle section of trials (p < 0.05), while informed feedback improved overall trial MPO (p < 0.05). However, positive, neutral and no feedback had no significant effect on overall trial or section MPO (p > 0.05). The available data suggests exercise regulation in hypoxia and heat-stress is delayed in the start section of trials, before significant reductions in MPO occur in the middle and end of the trial. Additionally, negative feedback involving performance deception may afford an upward shift in MPO in the middle section of the trial improving overall performance. Finally, performance improvements can be retained when participants are informed of the deception.

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

Background. Previous studies have demonstrated that men are more likely than women to slow in the marathon (footrace). This study investigated whether the sex difference in pacing occurs for a shorter race distance. Materials & Methods. Data were acquired from the Bolder Boulder 10 km road race for the years 2008-2013, which encompassed 191,693 performances. There were two pacing measures, percentage change in pace of the first 3 miles relative to the final 3.2 miles and percentage change in pace of the first mile relative to the final 5.2 miles. Pacing was analyzed as a continuous variable and as two categorical variables, as follows: "maintain the pace," defined as slowing <5% and "marked slowing," defined as slowing ≥10%. Results. Among the fastest (men < 48:40; women < 55:27) and second fastest (men < 53:54; women < 60:28) sex-specific finishing time sextiles, men slowed significantly more than women with both pacing measures, but there were no consistently significant sex differences in pacing among the slower four sextiles. For the fastest sextile, the odds for women were 1.96 (first pacing measure) and 1.36 (second measure) times greater than men to maintain the pace. For the fastest sextile, the odds for women were 0.46 (first measure) and 0.65 (second measure) times that of men to exhibit marked slowing. Multiple regression indicated that being older was associated with lesser slowing, but the sex difference among faster runners persisted when age was controlled. Conclusions. There was a sex difference in pacing during a 10 km race where glycogen depletion is not typically relevant. These results support the hypothesis that the sex difference in pacing partly reflects a sex difference in decision making.

Thinking and Action: A Cognitive Perspective on Self-Regulation during Endurance Performance

Self-regulation reflects an individual's efforts to bring behavior and thinking into line with often consciously desired goals. During endurance activity, self-regulation requires an athlete to balance their speed or power output appropriately to achieve an optimal level of performance. Considering that both behavior and thinking are core elements of self-regulation, this article provides a cognitive perspective on the processes required for effective pace-regulation during endurance performance. We also integrate this viewpoint with physiological and performance outcomes during activity. As such, evidence is presented to suggest that what an athlete thinks about has an important influence on effort perceptions, physiological outcomes, and, consequently, endurance performance. This article also provides an account of how an athlete might control their cognition and focus attention during an endurance event. We propose that effective cognitive control during performance requires both proactive, goal-driven processes and reactive, stimulus-driven processes. In addition, the role of metacognition—or thinking about thinking—in pace-regulation will also be considered. Metacognition is an essential component of self-regulation and its primary functions are to monitor and control the thoughts and actions required for task completion. To illustrate these processes in action, a metacognitive framework of attentional focus and cognitive control is applied to an endurance performance setting: specifically, Bradley Wiggins' successful 2015 Hour record attempt in cycling. Finally, future perspectives will consider the potentially deleterious effects of the sustained cognitive effort required during prolonged and strenuous endurance tasks.

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

The aim of this study is to analyse the influence of performance level, age and gender on pacing during a 100-km ultramarathon. Results of a 100-km race incorporating the World Masters Championships were used to identify differences in relative speeds in each 10-km segment between participants finishing in the first, second, third and fourth quartiles of overall positions (Groups 1, 2, 3 and 4, respectively). Similar analyses were performed between the top and bottom 50% of finishers in each age category, as well as within male and female categories. Pacing varied between athletes achieving different absolute performance levels. Group 1 ran at significantly lower relative speeds than all other groups in the first three 10-km segments (all P < 0.01), and significantly higher relative speeds than Group 4 in the 6th and 10th (both P < 0.01), and Group 2 in the 8th (P = 0.04). Group 4 displayed significantly higher relative speeds than Group 2 and 3 in the first three segments (all P < 0.01). Overall strategies remained consistent across age categories, although a similar phenomenon was observed within each category whereby 'top' competitors displayed lower relative speeds than 'bottom' competitors in the early stages, but higher relative speeds in the later stages. Females showed lower relative starting speeds and higher finishing speeds than males. 'Top' and 'bottom' finishing males displayed differing strategies, but this was not the case within females. Although pacing remained consistent across age categories, it differed with level of performance within each, possibly suggesting strategies are anchored on direct competitors. Strategy differs between genders and differs depending on performance level achieved in males but not females.