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

Performance and Psychophysiological Effects of Light-Guided Pacing During a 5000-m Run

PURPOSE

In world-class middle- and long-distance running races, a Wavelight signal has recently been used as a pacing guide for setting records. The aim of the present study was to compare performance and psychophysiological effects between light-guided, drafting, and nonassisted pacing conditions in distance runners.

METHODS

Fifteen male middle- and long-distance runners of national and regional standard ran three 5000-m time trials in a counterbalanced order with the following pacing distribution: the first 4000 m and last 1000 m were covered at submaximal and maximal intensities, respectively. The 3 trials (conditions) were (1) self-paced, (2) guided by a light signal, and (3) guided by a cyclist in front (drafting condition). Pace, heart rate, rating of perceived exertion, and affective valence were recorded every 500 m.

RESULTS

No statistically significant differences were found between pacing-light and self-paced conditions. Running time was shorter in the drafting versus self-paced condition in the final 500-m section (P = .031; d = 0.76). No differences were found between drafting and light conditions. Similarly, whereas 9 out of 10 significant differences in terms of lower heart rate, or rating of perceived exertion, or higher affective valence responses were found in the drafting versus self-paced condition (P = .004-.041; d = 0.63-1.39), only 4 were found across the tests in the drafting versus light condition (P = .005-.016; d = 0.66-0.84).

CONCLUSION

Light-guided pacing did not influence performance or psychophysiological responses in distance runners during a 5000-m test, but drafting produced a large effect.

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

Background

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

Case study

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

Results

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

Conclusion

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

Pacing strategies in marathons: A systematic review

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

Differences in pacing behaviour between global championship medal performances and world records in men's and women's middle- and long-distance running track events

The differences in pacing demands between track distance-running championship and meet (e.g., World Record [WR]) races have not been specified yet in the current literature. Therefore, the aim of this study was to determine pacing behaviour differences between WRs and global championship (i.e., World Championships and Olympic Games) medal performances (GCMs) in middle- and long-distance running events. Percentages of mean race section speeds were compared through analysis of variance between men's and women's 169 WRs and 189 GCMs over 800 m, 1500 m, 3000 m steeplechase, 5000 m and 10,000 m. U-shaped and negative pacing approaches are observed during men's and women's 1500 m WRs and GCMs, respectively. The first and third 400 m of men's and women's 1500 m GCMs were relatively slower and faster, respectively (p ≤ 0.05, 1.31 ≤ d ≤ 1.69). Even profiles are followed during women's 3000 m steeplechase WRs and GCMs, whereas positive approaches were adopted in men's GCMs. Finally, whereas 5000 m and 10,000 m GCMs were finished with a fast endspurt, WRs had a U-shaped profile in men, with differences between the initial and last race stages (p ≤ 0.01, 1.20 ≤ d ≤ 3.66), and an even profile in women. Coaches should consider the different pacing demands existing among meet and global championship races to specifically implement training characteristics targeting either goal type.

Unraveling the Role of (Meta-) Cognitive Functions in Pacing Behavior Development during Adolescence: Planning, Monitoring, and Adaptation

PURPOSE

This study aimed to investigate whether (meta-) cognitive functions underpin the development of the self-regulated distribution of effort during exercise (i.e., pacing) throughout adolescence.

METHODS

Participants included 18 adolescents (9 girls, 15.6 ± 2.5 yr old) and 26 adults (13 women, 26.8 ± 3.1 yr old), all recreationally active but unfamiliar with time trial cycling. The (meta-) cognitive functions involved in preexercise planning were quantified by calculating the difference between estimated and actual finish time during a 4-km cycling time trial. The capability to monitor and adapt one's effort distribution during exercise was measured during a 7-min submaximal trial, in which the participants were tasked with adhering to a set submaximal goal velocity either with (0-5 min) or without (5-7 min) additional feedback provided by the researcher. Analyses included between-group comparisons (ANOVA) and within-group comparisons (correlation) ( P < 0.05).

RESULTS

Adolescents were less accurate in their estimation of the task duration. The adolescents' overestimation of task duration of the 4-km time trial was accompanied by pacing behavior characteristics resembling a longer trial (i.e., more even power output distribution, lower RPE, more pronounced end-spurt). Contrary to the adults, the adolescents deviated relatively more from the goal velocity during the 7-min submaximal trial, when no additional feedback was provided by the researcher. Within the adolescent group, estimation of task duration accuracy ( r = 0.48) and adherence to goal velocity ( r = 0.59) correlated with age.

CONCLUSIONS

The (meta-) cognitive functions involved in the preexercise planning and the monitoring and adaptation of the distribution of effort during exercise underpin the development of pacing behavior during adolescence. Feedback from the (social) environment can be used to aid the monitoring and adaptation of effort expenditure in adolescents.

The subject-environment interplay between runners from different Brazilian macro-regions

Purpose

Our purpose was to investigate the interplay between runners and their environment using a network approach.

Methods

This cross-sectional study sampled Brazilian runners of both sexes, from the five macro-regions of the country. An electronic questionnaire was used to obtain information regarding age, sex, training volume, socio-economic level, place of residence, and running pace. Environmental indicators (public illumination, pavement, sidewalk, and green areas) were collected from available public information. Descriptive statistics were presented in mean (SD), and frequency (%). A network analysis was performed to evaluate the association between individual and environmental characteristics. Statistical analyses were performed in the JASP, considering p < 0.05.

Results

At North and Mid-West regions, public illumination presents the highest values for the expected influence (1.74 and 1.56), while in Northeast and Southeast, sidewalks present the highest values (2.13; 0.91). For betweenness centrality, in North, Northeast, and Mid-West regions, residency in the capital of a state presented a hub. In contrast, pavement, and training volume present higher values in the South and Southeast. Network topologies are different.

Conclusion

Public illumination (North and Mid-West) and sidewalk (Northeast, Southeast) were the most important variables for runners. Continental size countries need specific approaches to improve physical activity levels and health outcomes that consider the cultural, historical, and environmental background.

Beyond the border of the athlete-centered approach: a model to understand runners' performance

Our purpose is to move beyond the borders of the athlete-centered approach by examining the runners' environment interplay as a key factor for performance. Based on the ecological systems theory, the micro-level (intrapersonal, interpersonal, and training characteristics), meso-level (a direct association with athletes is not observed, but the environment plays an influence on the relationships built at the micro-level), and macro-level (contextual features that influence athletic systems) were theorized and contextualized as important factors for the expression of different outcomes, including performance and participation. We also conceptualized the microtime, mesotime, and macrotime as a constraint. Through this model, we aimed to provide applications and conclusions about how this conceptual model provides advances in the scientific research field. By understanding how environmental factors influence their performance, runners can make informed decisions about where and how to train and compete. Furthermore, by recognizing the role of culture and social context in shaping runners' experiences and outcomes, we can work toward creating a more equitable and supportive running culture for all.

Pacing Variation in Multistage Ultramarathons: Internet-Based Cross-Sectional Study

BACKGROUND

Ultramarathon running is the most popular ultraendurance competition in terms of the number of races and runners competing annually worldwide; however, no study has compared pacing and performance over a long period.

OBJECTIVE

This study analyzes the pacing of successful finishers and nonfinishers in multistage ultramarathons worldwide.

METHODS

A total of 4079 athletes (men=3288; women=791) competing in 99 multistage ultramarathon events from 1983 to 2021 were analyzed, including the number of participants, age, gender, rank, and running speed of successful finishers.

RESULTS

The results showed a significant increase in the number of events (n=338) and a significant increase in the number of finishers and nonfinishers (n=5575) in the ultramarathons worldwide during this period. The general linear models (GLMs) of pacing variation showed nonsignificant effects for gender (F1,36.2=2.5; P=.127; ηp2=0.063) and age group (F10,10=0.6; P=.798; ηp2=0.367), but it showed a significant interaction (gender × age) effect (F10,2689=2.3; P=.008; ηp2=0.009). Post hoc analyses showed that men have a higher pacing variation than women in the under 30 years (U30), U35, U45, and U50 groups. Additionally, the fastest women's age group (U35) had the lowest pacing variation. The GLM of pacing variation by gender and event distance showed significant effects for both gender (F1,3=18.5; P<.001; ηp2=0.007) and distance (F2,3=20.1; P<.001; ηp2=0.015). Post hoc analyses showed a growing pacing variation with increasing race distance for both men and women. In addition, men had a higher variation in long events. Furthermore, there was a significant main effect for both genders (F1,3=33.7; P<.001; ηp2=0.012) and rank (F1,3=136.6; P<.001; ηp2=0.048) on performance, with men being faster than women. Pacing varied greatly due to gender (F1,3=4.0; P=.047; ηp2=0.001), with a lower (ie, more even) pacing variation for male athletes in the top 3 finishers. Male nonfinishers showed a higher performance than female nonfinishers (F1,1340=25.6; P<.001), and no difference was identified for pacing variation (F1,789=1.5; P=.228) based on gender. In addition, a weak but significant correlation (r=-0.130; P<.001) was identified between the average running speed and pacing variation for both female and male nonfinishers.

CONCLUSIONS

In summary, multistage ultramarathon competitions showed an increasing number of competitors and a higher performance challenge. Men have a higher pacing (ie, less even) variation than women, especially observed in longer events. A higher pacing variation was associated with lower performance for men, women, and nonfinishers.

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.

The Relative Importance of Training and Social Support for Runners' Performance: A Cross-Sectional Study

BACKGROUND

Running participation/performance is a complex system. Understanding the variables associated with these behaviors may help to increase population physical activity and improve performance. This study aimed to investigate social and training variables important for running performance using a network approach.

METHODS

This cross-sectional study sampled 1151 non-professional Brazilian runners of both sexes (women, 38.2%; men, 61.7%). A questionnaire was available for eligible participants using an online platform, and information regarding training (volume and running pace) and social variables (participation in a running event, participation in a running group, influence on running, runners in the family, and childhood sport) related to runners' performance was obtained. The Chi-square test and network model were estimated by sex.

RESULTS

Training characteristics tend to be clustered. For both sexes, the training volume node presented the highest expected influence in the network (1.69 for women and 2.16 for men). Centrality indicators of social variables show that sports childhood participation and the presence of runners in the family were the most important nodes of network connection for women and men, respectively.

CONCLUSION

Based on these findings, it was concluded that sports participation during childhood and the practice of running by other family members were important factors to connect variables in the network. These findings have practical applications for health policymakers, highlighting the need to develop educational programs to increase sports participation during childhood and within families.

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.

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.

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

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

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

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

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

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

Uneven but Conservative Pacing Is Associated With Performance During Uphill and Downhill Running

PURPOSE

To investigate the relationship between pacing strategy and performance during uphill and downhill running-specifically, what distribution of energy corresponds to faster race finish times between and among participants.

METHODS

Eighteen years of race data from a 10.2-mile running race with an uphill first half and a downhill second half were analyzed to identify relationships between pacing and performance. A pacing coefficient (PC), equal to a participant's ascent time divided by finishing time (FT), was used to define each participant's pacing strategy. The American College of Sports Medicine metabolic running equation was used to estimate energy expenditure during the ascent, descent, and total race. Statistical analyses compared participants' PC to their FT and finishing place within their age and gender category. Additionally, FT and finishing place were compared between groups of participants who exhibited similar pacing strategies.

RESULTS

PCs were positively associated with faster FTs (r2 = .120, P < .001) and better finishing positions (r2 = .104, P < .001). PCs above .600 were associated with the fastest average FTs and best average finishing position within age and gender categories (all P ≤ .047).

CONCLUSIONS

Participants performed the best when energy expenditure increased no more than 10.4% during the uphill portion compared to their overall average. It is not possible to state that overly aggressive uphill efforts resulted in premature fatigue and thus slower decent times and worse race performance. However, participants should still avoid overly aggressive uphill pacing, as performance was associated with larger PCs.

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.

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

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

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.

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

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

Pacing Strategy Affects the Sub-Elite Marathoner's Cardiac Drift and Performance

The question of cardiac strain arises when considering the emerging class of recreational runners whose running strategy could be a non-optimal running pace. Heart rate (HR) monitoring, which reflects exercise intensity and environmental factors, is often used for running strategies in marathons. However, it is difficult to obtain appropriate feedback for only the HR value since the cardiovascular drift (CV drift) occurs during prolonged exercise. The cardiac cost (CC: HR divided by running velocity) has been shown to be a potential index for evaluation of CV drift during the marathon race. We sought to establish the relationship between recreational marathoners' racing strategy, cardiac drift, and performance. We started with looking for a trend in the speed time series (by Kendall's non-parametric rank correlation coefficient) in 280 (2 h30-3 h40) marathoners. We distinguished two groups, with the one gathering the large majority of runners (n = 215, 77%), who had a significant decrease in their speed during the race that appeared at the 26th km. We therefore named this group of runners the "fallers." Furthermore, the fallers had significantly lower performance (p = 0.006) and higher cardiac drift (p < 0.0001) than the non-fallers. The asymmetry indicator of the faller group runners' speed is negative, meaning that the average speed of this category of riders is below the median, indicating that they ran more than the half marathon distance (56%) above their average speed before they "hit the wall" at the 26th km. Furthermore, we showed that marathon performance was correlated with the amplitude of the cardiac drift (r = 0.18, p = 0.0018) but not with those of the increase in HR (r = 0.01, p = 0.80). In conclusion, for addressing the question of the cardiac drift in marathon, which is very sensitive to the running strategy, we recommend to utilize the cardiac cost, which takes into account the running speed and that could be implemented in the future, on mobile phone applications.

Different psychophysiological responses to a high-intensity repetition session performed alone or in a group by elite middle-distance runners

Internal training load refers to the degree of disturbance in psychophysiological homeostasis provoked by a training session and has been traditionally measured through session-RPE, which is the product of the session Rate of Perceived Exertion (RPE) and the duration. External training load refers to the actual physical work completed, and depends on session volume, intensity, frequency and density. Drafting, which is achieved by running closely behind another runner has been demonstrated to reduce the energy cost of running at a fixed speed and to improve performance. Therefore, it is hypothesised that psychophysiological responses might reflect different levels of internal load if training is performed individually or collectively. 16 elite middle-distance runners performed two high-intensity training sessions consisting of 4 repetitions of 500 m separated by 3 min of passive recovery. Sessions were performed individually and collectively. Times for each repetition, RPE, core affect (valence and felt arousal) and blood lactate concentrations [BLa] were measured after each repetition. Main time effect was significant and increased across repetitions for [BLa] and RPE (p < 0.001), and decreased for valence (p = 0.001). Main group effect was significant and values were higher when training individually for [BLa] (p = 0.003) and RPE (p = 0.001), and lower for valence (p = 0.001). No differential responses were found between conditions in terms of repeat time or felt arousal. Findings demonstrate that elite middle-distance athletes running collectively display lower levels of internal training load compared to running alone, despite external training load being similar.

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.