The influence of pacing strategy on marathon world records

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

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

Pacing strategies in marathons: A systematic review

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

Professional long distance runners achieve high efficiency at the cost of weak orbital stability

Successful performance in long distance race requires both high efficiency and stability. Previous research has demonstrated the high running efficiency of trained runners, but no prior study quantitatively addressed their orbital stability. In this study, we evaluated the efficiency and orbital stability of 8 professional long-distance runners and compared them with those of 8 novices. We calculated the cost of transport and normalized mechanical energy to assess physiological and mechanical running efficiency, respectively. We quantified orbital stability using Floquet Multipliers, which assess how fast a system converges to a limit cycle under perturbations. Our results show that professional runners run with significantly higher physiological and mechanical efficiency but with weaker orbital stability compared to novices. This finding is consistent with the inevitable trade-off between efficiency and stability; increase in orbital stability necessitates increase in energy dissipation. We suggest that professional runners have developed the ability to exploit inertia beneficially, enabling them to achieve higher efficiency partly at the cost of sacrificing orbital stability.

Running Variability in Marathon-Evaluation of the Pacing Variables

Background and Objectives: Pacing analyses for increasingly popular long-distance running disciplines have been in researchers' spotlight for several years. In particular, assessing pacing variability in long-distance running was hardly achievable since runners must repeat long-running trials for several days. Potential solutions for these problems could be multi-stage long-distance running disciplines. Therefore, this study aimed to assess the long-distance running variability as well as the reliability, validity, and sensitivity of the variables often used for pacing analyses. Materials and Methods: This study collected the split times and finish times for 20 participants (17 men and three women; mean age 55.5 years ± 9.5 years) who completed the multiday marathon running race (five marathons in 5 days), held as part of the Bretzel Ultra Tri in Colmar, France, in 2021. Seven commonly used pacing variables were subsequently calculated: Coefficient of variation (CV), Change in mean speed (CS), Change in first lap speed (CSF), Absolute change in mean speed (ACS), Pace range (PR), Mid-race split (MRS), and First 32 km-10 km split (32-10). Results: Multi-stage marathon running showed low variability between days (Intraclass correlation coefficient (ICC) > 0.920), while only the CV, ACS, and PR variables proved to have moderate to good reliability (0.732 < ICC < 0.785). The same variables were also valid (r > 0.908), and sensitive enough to discern between runners of different performance levels (p < 0.05). Conclusions: Researchers and practitioners who aim to explore pacing in long-distance running should routinely utilize ACS, CV, and PR variables in their analyses. Other examined variables, CS, CSF, MRS, and 32-10, should be used cautiously. Future studies might try to confirm these results using different multi-stage event's data as well as by expanding sensitivity analysis to age and gender differences.

Influence of Running Shoe Longitudinal Bending Stiffness on Running Economy and Performance in Trained and National Level Runners

INTRODUCTION/PURPOSE

Previous results about shoe longitudinal bending stiffness (LBS) and running economy (RE) show high variability. This study aimed to assess the effects of shoes with increased LBS on RE and performance in trained and national runners.

METHODS

Twenty-eight male runners were divided into two groups according to their 10-km performance times (trained, 38-45 min and national runners, <34 min). Subjects ran 2 × 3 min (at 9 and 13 km·h -1 for trained, and 13 and 17 km·h -1 for national runners) with an experimental shoe with carbon fiber plate to increase the LBS (Increased LBS) and a control shoe (without carbon fiber plate). We measured energy cost of running (W·kg -1 ) and spatiotemporal parameters in visit one and participants performed a 3000 m time trial (TT) in two successive visits.

RESULTS

Increased LBS improved RE in the trained group at slow (11.41 ± 0.93 W·kg -1 vs 11.86 ± 0.93 W·kg -1 ) and fast velocity (15.89 ± 1.24 W·kg -1 vs 16.39 ± 1.24 W·kg -1 ) and only at the fast velocity in the national group (20.35 ± 1.45 W·kg -1 vs 20.78 ± 1.18 W·kg -1 ). The improvements in RE were accompanied by different changes in biomechanical variables between groups. There were a similar improvement in the 3000 m TT test in Increased LBS for trained (639 ± 59 vs 644 ± 61 s in control shoes) and national runners (569 ± 21 vs 574 ± 21 s in control shoes) with more constant pace in increased LBS compared with control shoes in both groups.

CONCLUSIONS

Increasing shoe LBS improved RE at slow and fast velocities in trained runners and only at fast velocity in national runners. However, the 3000 m TT test improved similarly in both levels of runners with increased LBS. The improvements in RE are accompanied by small modifications in running kinematics that could explain the difference between the different levels of runners.

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.

Analysis of pacing and kinematics in 3000 m freestyle in elite level swimmers

This study aimed to determine elite swimmers' pacing strategy in the 3000 m event and to analyse the associated performance variability and pacing factors. Forty-seven races were performed by 17 male and 13 female elite swimmers in a 25 m pool (20.7 ± 2.9 years; 807 ± 54 FINA points). Lap performance, clean swim velocity (CSV), water break time (WBT), water break distance (WBD), stroke rate (SR), stroke length (SL) and stroke index (SI) were analysed including and excluding the first (0-50 m) and last lap (2950-3000 m). The most common pacing strategy adopted was parabolic. Lap performance and CSV were faster in the first half of the race compared to the second half (p < 0.001). WBT, WBD, SL and SI were reduced (p < 0.05) in the second half compared to the first half of the 3000 m when including and excluding the first and last laps for both sexes. SR increased in the second half of the men's race when the first and last laps were excluded. All studied variables showed significant variation between the two halves of the 3000 m, the highest variation being obtained in WBT and WBD, suggesting that fatigue negatively affected swimming kinematics.

Prescription of High-intensity Aerobic Interval Training Based on Oxygen Uptake Kinetics

Endurance training results in diverse adaptations that lead to increased performance and health benefits. A commonly measured training response is the analysis of oxygen uptake kinetics, representing the demand of a determined load (speed/work) on the cardiovascular, respiratory, and metabolic systems, providing useful information for the prescription of constant load or interval-type aerobic exercise. There is evidence that during high-intensity aerobic exercise some interventions prescribe brief interval times (<1-min), which may lead to a dissociation between the load prescribed and the oxygen uptake demanded, potentially affecting training outcomes. Therefore, this review explored the time to achieve a close association between the speed/work prescribed and the oxygen uptake demanded after the onset of high-intensity aerobic exercise. The evidence assessed revealed that at least 80% of the oxygen uptake amplitude is reached when phase II of oxygen uptake kinetics is completed (1 to 2 minutes after the onset of exercise, depending on the training status). We propose that the minimum work-time during high-intensity aerobic interval training sessions should be at least 1 minute for athletes and 2 minutes for non-athletes. This suggestion could be used by coaches, physical trainers, clinicians and sports or health scientists for the prescription of high-intensity aerobic interval training.

Effects of the Nike ZoomX Vaporfly Next% 2 shoe on long-interval training performance, kinematics, neuromuscular parameters, running power and fatigue

We analysed the effects of the Nike ZoomX Vaporfly (VPF) on long-interval training performance, kinematic parameters, running power and fatigue compared to a traditional running shoe. Twelve well-trained men (mean ± SD: 32.91 ± 7.50 years; 69.29 ± 7.55 kg and 172.73 ± 5.97 cm) performed two long-interval training sessions (5 × 1000 m with 90s recovery period) 7 days apart, with the VPF shoe or a traditional running shoe (CON) in random order. The countermovement jump (CMJ) height was measured before and after the training sessions and heart rate, spatiotemporal parameters, running power and leg stiffness was measured during training sessions. Running-related pain was assessed prior and post-24 h of each training session. Long-interval training performance improved 2.4% using the VPF shoe compared to CON (p = 0.009; ES = 0.482). Step length, contact time and leg stiffness were higher (p < 0.05; ES = 0.51, ES = 0.677, ES = 0.356) while flight time was lower (p < 0.001; ES = 0.756) when using VPF. Running power decreased in a similar way in both conditions throughout the training session. Vertical power was significantly higher in the VPF condition (p = 0.023, ES = 0.388). CMJ height decreased in both conditions after training (4.7 vs. 7.2%, for the VPF and control, respectively, p < 0.001; ES = 0.573). Finally, the perceived muscle pain was influenced by the shoe model condition (chi-square 5.042, P = 0.025). VPF shoes improved the long-interval training performance with similar running power, heart rate and neuromuscular fatigue, and reduced subjective perceived muscle pain compared to regular training shoes. HighlightsVPF shoe may improve long-interval training performance in trained runners with the same running power and heart rate.Lower subjective perceived muscle pain is found with VPF compared to the regular training shoes.This type of footwear may be used in high-intensity training sessions aiming to increase the training volume at higher intensities with lower associated fatigue.

Impact of advanced footwear technology on elite men's in the evolution of road race performance

Advanced footwear technology (AFT) changed footwear design concepts by using a curved carbon fibre plate in combination with new, more compliant and resilient foams. The aim of this study was (1) to examine the individual effects of AFT on the evolution of the main road events and (2) to re-assess the impact of AFT on the world's top-100 performance in men's 10k, half-marathon and marathon events. Data from the top-100 men's 10k, half-marathon and marathon performances were collected between 2015 and 2019. The shoes used by the athletes were identified in 93.1% of the cases by publicly available photographs. Runners wearing AFT had an average performance of 1671 ± 22.28 s compared to 1685 ± 18.97 s of runners not using AFT in 10k (0.83%) (p < 0.001), 3589 ± 29.79 s compared to 3607 ± 30.49 s in half-marathon (0.50%) (p < 0.001) and 7563 ± 86.10 s compared to 7637 ± 72.51 s in the marathon (0.97%) (p < 0.001). Runners wearing AFTs were faster by ~1% in the main road events compared to non-users. Individual analysis showed that ~25% of the runners did not benefit from the use of this type of footwear. The results of this study suggest that AFT has a clear positive impact on running performance in main road events.

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

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

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

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

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

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

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

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

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

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

Characteristics of Pacing Strategies among Elite Cross-Country Skiers According to Final Rank

The purpose of this study is to explore differences in pacing strategies between successful and less successful male elite cross-country skiers during a 15 km interval-start race involving different techniques. The final rank, split times and final times were extracted individually for the top 100 finishers in the 15 km individual time trial races from the Norwegian national season opener races over two years. The same course was used in all the competitions. The athletes were divided into four groups according to final rank: Q1: 1st–25th; Q2: 26th–50th; Q3: 51st–75th; Q4: 76th–100th. The relative change in speed was used for the time spent on lap 1, to an average for laps 2 and 3. Significant correlation between placement and speed reduction after the first lap was found in three out of four races. In Race 2 (skating), both Q1 and Q2 had lower speed decreases between laps than Q4 did. In year 2, both races (classical and skating) had lower speed reduction between laps for the first quartile compared to that of the last. Overall, this study shows that lower-level cross-country skiers started out relatively faster in the first lap and achieved a greater reduction in speed in the subsequent laps when compared to their faster opponents.

World and European Rowing Medallists Pace With Smaller Variation Than Their Competitors

Purpose: To establish the relation between pacing pattern and performance, within sex, and number of crew members, at the very highest performance level in World class rowing.

Methods: Pacing profiles based on official 500 m split times in 106 A-finals with six contesting boat crews (n = 636 crews), in recent World (2017–2019) and European (2017–2021) championships, were analyzed. The coefficient of variation (CV) and sum of relative differences (SRD) of the split times, and normalized velocities in the four segments of the race, were compared between performance levels, that is, placement (1st–6th), and subgroups based on sex (female or male) and number of crew members (one, two, or four). Statistical tests and resulting p-values and effect sizes (Cohen's d) were used to assess differences between groups.

Results: The pacing profiles of the medallists had smaller variation than those of the non-podium finishers (CV = 1.72% vs. CV = 2.00%; p = 4 × 10−7, d = 0.41). Compared to the non-podium finishers, the medallists had lower normalized velocities in the first and second segments of the race, slightly higher in the third segment and higher in the fourth segment. Female crews paced somewhat more evenly than male crews. No significant differences were found in the evenness of pacing profiles between singles, doubles/pairs and quads/fours. Analyses of SRD were overall consistent with analyses of CV.

Conclusion: Medal winners in major rowing championships use a more even pacing strategy than their final competitors, which could imply that such a strategy is advantageous in rowing.

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.

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

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

Pacing 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.

Marathon race performance increases the amount of particulate matter deposited in the respiratory system of runners: an incentive for "clean air marathon runs"

Background

In the last decades, marathon running has become a popular form of physical activity among people around the world. It should be noticed that the main marathon races are performed in large cities, where air quality varies considerably. It is well established that breathing polluted air results in a number of harmful effects to the human body. However, there have been no studies to show the impact of marathon run performance on the amount of the deposition of varied fractions of airborne particulate matter (PM) in the respiratory tract of runners. This is why the present study sought to determine the impact of marathon run performance in the air of varying quality on the deposition of the PM₁, PM_2.5, PM₁₀ in the respiratory tract in humans.

Methods

The PM₁, PM_2.5 and PM₁₀ deposition was determined in an “average runner” (with marathon performance time 4 h: 30 min) and in an “elite marathon runner” (with marathon performance time 2 h: 00 min) at rest, and during a marathon race, based on own measurements of the PM content in the air and the size-resolved DF(d) profile concept.

Results

We have shown that breathing air containing 50 µg m⁻³ PM₁₀ (a borderline value according to the 2006 WHO standard - still valid) at minute ventilation (V_E) equal to 8 L min⁻¹ when at rest, resulted in PM₁₀deposition rate of approximately 9 µg h⁻¹, but a marathon run of an average marathon runner with the V_E = 62 L min⁻¹ increased the deposition rate up to 45 µg h⁻¹. In the elite runner, marathon run with the V_E= 115 L min⁻¹ increased PM₁₀ deposition rate to 83 µg h⁻¹. Interestingly, breathing the air containing 50 µg m⁻³of PM₁₀ at the V_E = 115 L min⁻¹by the elite marathon runner during the race resulted in the same PM₁₀deposition rate as the breathing highly polluted air containing as much as 466 µg m⁻³ of PM₁₀ when at rest. Furthermore, the total PM₁₀ deposition in the respiratory tract during a marathon race in average runners is about 22% greater (203 / 166 = 1.22) than in elite runners. According to our calculations, the concentration of PM₁₀in the air during a marathon race that would allow one not to exceed the PM₁₀ deposition rate of 9 µg h⁻¹should be lower than 10 µg m⁻³ in the case of an average runner, and it should be lower than 5.5 µg m⁻³ in the case of an elite runner.

Conclusions

We conclude that a marathon run drastically increases the rate of deposition of the airborne PM in the respiratory tract of the runners, as a consequence of the huge V_E generated during the race. A decrease of the PM content in the air attenuates this rate. Based on our calculations, we postulate that the PM₁₀ content in the air during a “clean air marathon run”, involving elite marathon runners, should be below 5.5 µg m⁻³.

Current Insights in the Age-related Decline in Sports Performance of the Older Athlete

The higher performance level of master athletes compared to non-athletes is often associated with better health throughout life. However, even the physical performance of master athletes declines with age, and this decline accelerates from about the age of 70 years onwards. A progressive loss of muscle mass, declines in force- and power-generating capacity, decreased flexibility, and the concomitant decline in specific tension characterize the muscular changes underlying performance declines. In the cardiovascular system, declines in stroke volume and cardiac output, and cardiac and vascular stiffness contribute to decreasing performance. Recent studies have shown that long-term endurance exercise in master athletes does not only have positive effects, but is associated with an increased incidence of atrial fibrillation, atherosclerotic plaques, and aortic dilation, and even more so in men than in women. Recently, larger longitudinal datasets were analysed and showed that the age-related decline in performance was similar in longitudinal and cross-sectional data. In conclusion, regular physical activity enhances the exercise capacity, and hence quality of life in old age, but it is not without risks.

Effect of marathon characteristics and runners' time category on pacing profile

This study aimed to analyse differences in pacing profiles in four marathon competitions and to explore that pacing per time category. A database of 91,493 runners gathered from 4 different races was analysed (Valencia, Chicago, London and Tokyo Marathon). Participants were categorized in accordance with their completion time. The relative speed of each section for each runner was calculated as a percentage of the average speed for the entire race. In the four marathons studied, the first 5 km differed widely, presenting London the highest relative speeds (5 km: CI95% London vs. Valencia [12.1, 13.6%], p < 0.001 and ES = 2.1; London vs. Chicago [5.5, 7.1%], p < 0.001 and ES = 1.1; London vs. Tokyo [15.2, 16.8%], p < 0.001 and ES = 2.3). Races did not differ at each section for high-performance runners (sub-2:30), but differences between races increased as the time category increases (e.g. 35 km and sub-3:00: CI95% London vs. Tokyo [-3.1, -1.8%], p < 0.001 and ES = 0.7; 35 km and sub-5:00: London vs. Tokyo [-9.8, -9.2%], p < 0.001 and ES = 1.3). The difference in relative speed between the first and second half of the marathon was higher in London than in the other marathons (e.g. CI95% London vs. Valencia [10.3, 10.8%], p < 0.001 and ES = 1.3). In conclusion, although race characteristics affect pacing, this effect was higher as the category time increases. Race pacing characteristics should be taken into consideration for runners and coaches choosing the race and working on pacing strategies, for researches to extrapolate or interpret results, or for race organizations to improve its pacing characteristics.Highlights The first 5 km differed widely on pacing profiles between the four marathons assessed.London had the highest relative speeds in the first 5 km.Race characteristics affect pacing, but this effect was higher as the category time increases.The difference in relative speed between the first and second half of the marathon was higher in London than in the other marathons.

Tactical behavior of high-level male marathon runners

This study analyzes the strategy used by the best male runners who participated in one of the major city marathons (Frankfurt Marathon, 2008-2018), the all-time performances <2:04:00, the male world records achieved during the 21st century and the Nike Breaking2 Project and INEOS 1:59 Challenge (total = 235 races). The races of the best runners in the Frankfurt Marathon (top 10) were analyzed (n = 110 runners, range: 2:03:42-2:14:05 hours); the runners were divided into two groups according to the tactical used. The pace of Group A (stable pace) remained steady throughout the race, while in Group B (decrease in running speed toward the end of the race) a moderate, but significant drop in speed was detected (P ≤ .001), starting from halfway through the race and getting sharper from the 30th kilometer (30-35 km = 1.6%, P ≤ .001 - 35-40 km = 4.3%, P ≤ .001 - 40-42.195 km: 3.9%, P ≤ .001, total = ≈10%). In the races in which the world record is achieved, the running speed tends to be steady and relatively conservative during the first stretch of the race, increasing smoothly in the second half and achieving a significant increase in the last 2195 m of the race (P = .016, ES = 1.14). Among all the possible strategies, running at a steady pace throughout the race seems the most effective option, especially when priority is given to time rather than position (ie, world records and best all-time races).

Physiological demands of running at 2-hour marathon race pace

The requirements of running a 2-h marathon have been extensively debated but the actual physiological demands of running at ∼21.1 km/h have never been reported. We therefore conducted laboratory-based physiological evaluations and measured running economy (O₂ cost) while running outdoors at ∼21.1 km/h, in world-class distance runners as part of Nike's "Breaking 2" marathon project. On separate days, 16 world-class male distance runners (age, 29 ± 4 yr; height, 1.72 ± 0.04 m; mass, 58.9 ± 3.3 kg) completed an incremental treadmill test for the assessment of V̇O_2peak, O₂ cost of submaximal running, lactate threshold and lactate turn-point, and a track test during which they ran continuously at 21.1 km/h. The laboratory-determined V̇O_2peak was 71.0 ± 5.7 mL/kg/min with lactate threshold and lactate turn-point occurring at 18.9 ± 0.4 and 20.2 ± 0.6 km/h, corresponding to 83 ± 5% and 92 ± 3% V̇O_2peak, respectively. Seven athletes were able to attain a steady-state V̇O₂ when running outdoors at 21.1 km/h. The mean O₂ cost for these athletes was 191 ± 19 mL/kg/km such that running at 21.1 km/h required an absolute V̇O₂ of ∼4.0 L/min and represented 94 ± 3% V̇O_2peak. We report novel data on the O₂ cost of running outdoors at 21.1 km/h, which enables better modeling of possible marathon performances by elite athletes. Using the value for O₂ cost measured in this study, a sub 2-h marathon would require a 59 kg runner to sustain a V̇O₂ of approximately 4.0 L/min or 67 mL/kg/min.NEW & NOTEWORTHY We report the physiological characteristics and O₂ cost of running overground at ∼21.1 km/h in a cohort of the world's best male distance runners. We provide new information on the absolute and relative O₂ uptake required to run at 2-h marathon pace.

Analysis of the world record time for combined father and son marathon

The aim of this study was to examine the physiological profiles and the pacing strategies of the father (59 yr old) and son (34 yr old) who broke the World Record time (4:59:22; father: 2:27:52, son: 2:31:30) for combined father and son marathon in 2019. Oxygen uptake (V̇o₂), heart rate (HR), ventilation (V̇e), blood lactate concentration (La), and running economy (RE) were measured during treadmill-running tests. The total distance of the marathon was divided into eight sections of 5 km and one last section of 2.195 km, and the relative average running velocity on each section was calculated individually. V̇o_2max, HR_max, V̇e_max, and La_max were 65.4 mL·kg^-1·min^-1, 165 beats/min, 115 L/min, 5.7 mmol/L for the father and 66.9 mL·kg^-1·min^-1, 181 beats/min, 153 L/min, 11.5 mmol/L for the son, respectively. At 17 km/h, RE was 210 mL·kg^-1·km^-1 for the father and 200 mL·kg^-1·km^-1 for the son, and % V̇o_2max sustained was 90.9% for the father and 84.5% for the son, respectively. The father maintained an even running velocity during the marathon (running velocity CV <1%), while the son ran the second half-marathon 7% slower than the first one, and his running velocity markedly dropped from the 35th kilometer. Father and son who broke the World record time for combined father and son marathon had a similar level of performance, but their physiological profiles and pacing strategies during the marathon were different. A more even speed for the son could help them to improve their own record in the near future.NEW & NOTEWORTHY We provide novel data demonstrating that different physiological profiles can lead to the same level of performance in a marathon, even at different ages. The novelty of our study is that we report on the physiological characteristics, training routine, and in-race pacing strategy that allowed a father (59 yr old) and son (34 yr old) to break the World Record time for combined father and son marathon. The father also established a new World record marathon time for the age of 59.

Pacing and Performance in the 6 World Marathon Majors

The main goal of this study was to analyse the pacing strategies displayed by the winners of the six World Marathon Majors in order to determine which race offers the greatest potential for future world record attempts. For data analysis, the total distance of the marathon was divided into eight sections of 5 km and a final section of 2.195 km, and time needed to complete each section was calculated in seconds. When we analyzed the mean winning time in the last 13 editions of each of the World Marathon Majors, we observed differences between New York and London (ES = 1.46, moderate effect, p = 0.0030), New York and Berlin (ES = 0.95, small effect, p = 0.0001), London and Boston (ES = 0.08, small effect, p = 0.0001), Boston and Berlin (ES = 0.10, small effect, p = 0.0001), Boston and Chicago (ES = 0.16, small effect, p = 0.0361), Berlin and Tokyo (ES = 0.20, small effect, p = 0.0034), Berlin and Chicago (ES = 0.27, small effect, p = 0.0162). This study shows that Berlin and London are likely candidates for future world record attempts, whilst such a performance is unlikely in New York or Boston.

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

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

Effects of complex training versus heavy resistance training on neuromuscular adaptation, running economy and 5-km performance in well-trained distance runners

Background

Recently, much attention has been paid to the role of neuromuscular function in long-distance running performance. Complex Training (CT) is a combination training method that alternates between performing heavy resistance exercises and plyometric exercises within one single session, resulting in great improvement in neuromuscular adaptation. The purpose of this study was to compare the effect of CT vs. heavy resistance training (HRT) on strength and power indicators, running economy (RE), and 5-km performance in well-trained male distance runners.

Methods

Twenty-eight well-trained male distance runners (19–23 years old, VO_2max:65.78 ± 4.99 ml.kg⁻¹.min⁻¹) performed one pre-test consisting of: maximum strength (1RM), counter movement jump (CMJ) height, peak power, a drop jump (DJ), and RE assessments, and blood lactate concentration (BLa) measurement at the speeds from 12–16 km.h⁻¹, a 50-m sprint, and a 5-km running performance test. They were then divided into 3 groups: complex training group (CT, n = 10), that performed complex training and endurance training; heavy resistance training group (HRT, n = 9) that performed heavy strength training and endurance training; and control group (CON, n = 9) that performed strength-endurance training and endurance training. After the 8 weeks training intervention, all participants completed a post-test to investigate the training effects on the parameters measured.

Results

After training intervention, both the CT and HRT groups had improvements in: 1RM strength (16.88%, p < 0.001; 18.80%, p < 0.001, respectively), CMJ height (11.28%, p < 0.001; 8.96%, p < 0.001, respectively), 14 km.h⁻¹RE (−7.68%, p < 0.001; −4.89%, p = 0.009, respectively), 50-m sprints (−2.26%, p = 0.003; −2.14%, p = 0.007, respectively) and 5-km running performance (−2.80%, p < 0.001; −2.09%, p < 0.001, respectively). The CON group did not show these improvements. All three training groups showed improvement in the 12 km.h⁻¹RE (p ≤ 0.01). Only the CT group exhibited increases in DJ height (12.94%, p < 0.001), reactive strength index (19.99%, p < 0.001), 16 km.h⁻¹ RE (−7.38%, p < 0.001), and a reduction of BLa concentrations at the speed of 16 km.h⁻¹ (−40.80%, p < 0.001) between pre- and post-tests.

Conclusion

This study demonstrated that CT can enhance 1RM strength, CMJ height, 12 and 14 km.h⁻¹REs, 50-m sprints and 5-km running performances in well-trained male distance runners and may be superior to HRT for the development of reactive strength and 16 km.h⁻¹RE, and reduction of BLa concentrations at speed of 16 km.h⁻¹. Young male distance runners could integrate CT into their programs to improve the running performance.

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

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

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

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

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

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

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

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

Effects of Pacing Properties on Performance in Long-Distance Running

This article focuses on the performance of runners in official races. Based on extensive public data from participants of races organized by the Boston Athletic Association, we demonstrate how different pacing profiles can affect the performance in a race. An athlete's pacing profile refers to the running speed at various stages of the race. We aim to provide practical, data-driven advice for professional as well as recreational runners. Our data collection covers 3 years of data made public by the race organizers, and primarily concerns the times at various intermediate points, giving an indication of the speed profile of the individual runner. We consider the 10 km, half marathon, and full marathon, leading to a data set of 120,472 race results. Although these data were not primarily recorded for scientific analysis, we demonstrate that valuable information can be gleaned from these substantial data about the right way to approach a running challenge. In this article, we focus on the role of race distance, gender, age, and the pacing profile. Since age is a crucial but complex determinant of performance, we first model the age effect in a gender- and distance-specific manner. We consider polynomials of high degree and use cross-validation to select models that are both accurate and of sufficient generalizability. After that, we perform clustering of the race profiles to identify the dominant pacing profiles that runners select. Finally, after having compensated for age influences, we apply a descriptive pattern mining approach to select reliable and informative aspects of pacing that most determine an optimal performance. The mining paradigm produces relatively simple and readable patterns, such that both professionals and amateurs can use the results to their benefit.

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

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