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.

Evolution of 1500-m Olympic Running Performance.

PURPOSE: This study determined the evolution of performance and pacing for each winner of the men's Olympic 1500-m running track final from 1924 to 2020. METHODS: Data were obtained from publicly available sources. When official splits were unavailable, times from sources such as YouTube were included and interpolated from video records. Final times, lap splits, and position in the peloton were included. The data are presented relative to 0 to 400 m, 400 to 800 m, 800 to 1200 m, and 1200 to 1500 m. Critical speed and D' were calculated using athletes' season's best times. RESULTS: Performance improved ∼25 seconds from 1924 to 2020, with most improvement (∼19 s) occurring in the first 10 finals. However, only 2 performances were world records, and only one runner won the event twice. Pacing evolved from a fast start-slow middle-fast finish pattern (reverse J-shaped) to a slower start with steady acceleration in the second half (J-shaped). The coefficient of variation for lap speeds ranged from 1.4% to 15.3%, consistent with a highly tactical pacing pattern. With few exceptions, the eventual winners were near the front throughout, although rarely in the leading position. There is evidence of a general increase in both critical speed and D' that parallels performance. CONCLUSIONS: An evolution in the pacing pattern occurred across several "eras" in the history of Olympic 1500-m racing, consistent with better trained athletes and improved technology. There has been a consistent tactical approach of following opponents until the latter stages, and athletes should develop tactical flexibility, related to their critical speed and D', in planning prerace strategy.

The Fine-Tuning Approach for Training Monitoring.

PURPOSE: Monitoring is a fundamental part of the training process to guarantee that the programmed training loads are executed by athletes and result in the intended adaptations and enhanced performance. A number of monitoring tools have emerged during the last century in sport. These tools capture different facets (eg, psychophysiological, physical, biomechanical) of acute training bouts and chronic adaptations while presenting specific advantages and limitations. Therefore, there is a need to identify what tools are more efficient in each sport context for better monitoring of training process. METHODS AND RESULTS: We present and discuss the fine-tuning approach for training monitoring, which consists of identifying and combining the best monitoring tools with experts' knowledge in different sport settings, designed to improve (1) the control of actual training loads and (2) understanding of athletes' training adaptations. Instead of using single-tool approaches or merely subjective decision making, the identification of the best combination of monitoring tools to assist experts' decisions in each specific context (ie, triangulation) is necessary to better understand the link between acute and chronic adaptations and their impact on health and performance. Future studies should elaborate on the identification of the best combination of monitoring tools for each specific sport setting. CONCLUSION: The fine-tuning monitoring approach requires the simultaneous use of several valid and practical tools, instead of a single tool, to improve the effectiveness of monitoring practices when added to experts' knowledge.

Short-Term Speed Variability as an Index of Pacing Stochasticity in Athletic Running Events.

We aimed to compare differences in performance and pacing variability indices between 5000 m heats and finals during major championships in men and women. Data with 100 m time resolution were used to compare overall pacing variability (standard deviation of 100 m section times, SD; and coefficient of variation, CV%) and short-term pacing variability (root mean square of successive differences between 100 m section times, RMSSD). The changes in performance and pacing indices differed between races and competitions. For instance, the men's final in Beijing 2008 was quicker than the heat (p < 0.01) while the CV% was reduced (p = 0.03) and RMSSD increased (p < 0.01). For women, the heats and the final exhibited a similar mean time in London 2017 (p = 0.33) but with CV% (p < 0.001) and RMSSD (p < 0.001) showing opposite trends. Individual analyses of men's and women's champions revealed highly individual variability metrics. The use of RMSSD can complement overall variability indices for better characterization of pacing stochasticity.

The Evolution of World-Class Endurance Training: The Scientist's View on Current and Future Trends.

BACKGROUND: Elite sport is continuously evolving. World records keep falling and athletes from a longer list of countries are involved. PURPOSE: This commentary was designed to provide insights into present and future trends associated with world-class endurance training based on the perspectives, experience, and knowledge of an expert panel of 25 applied sport scientists. RESULTS: The key drivers of development observed in the past 10-15 years were related to (1) more accessible scientific knowledge for coaches and athletes combined with (2) better integration of practical and scientific exchange across multidisciplinary perspectives within professionalized elite athlete support structures, as well as (3) utilization of new technological advances. Based on these perspectives, we discerned and exemplified the main trends in the practice of endurance sports into the following categories: better understanding of sport-specific demands; improved competition execution; larger, more specific, and more precise training loads; improved training quality; and a more professional and healthier lifestyle. The main areas expected to drive future improvements were associated with more extensive use of advanced technology for monitoring and prescribing training and recovery, more precise use of environmental and nutritional interventions, better understanding of athlete-equipment interactions, and greater emphasis on preventing injuries and illnesses. CONCLUSIONS: These expert insights can serve as a platform and inspiration to develop new hypotheses and ideas, encourage future collaboration between researchers and sport practitioners, and, perhaps most important, stimulate curiosity and further collaborative studies about the training, physiology, and performance of endurance athletes.

Comparison of anaerobic speed reserve and maximal aerobic speed methods to prescribe short format high-intensity interval training.

The purpose of the study was to compare the degree of intersubject variability in the cardiorespiratory, metabolic, and perceptual responses to high-intensity interval training (HIIT) prescribed based on the relative anaerobic speed reserve (ASR) or maximal aerobic speed (MAS) and to identify the optimal % ASR for execution of such HIIT. Seventeen male physical education students (age: 23.6 ± 1.1 years, height: 180.2 ± 5.9, body mass: 78.3 ± 8.1 kg; % body fat: 14.3 ± 2.7%) volunteered to execute three randomly scheduled 10-min HIIT exercises at 110% vVO2max , Δ15% ASR, or Δ25% ASR. Analysis of variance for repeated measures and the least significant difference post-hoc test were used to compare the physiological responses and the mean of individual residuals between the training sessions. The coefficients of variation (CV) of time spent ≥90% of maximal oxygen uptake (VO2max ) and maximal heart rate (HRmax ), peak VO2 , mean VO2 , peak HR, mean HR, blood lactate [La], and rating of perceived exertion (RPE) were 48.7%, 35.9%, 9.3%, 7%, 3.5%, 4.8%, 32%, and 16.9% during 110% vVO2max , 47.2%, 31%, 7.5%, 6.7%, 3.9%, 4.6%, 24.2%, and 14.6% during Δ15% ASR, and 48.1%, 31.5%, 7.6%, 8.4%, 3.6%, 4.1%, 20.2%, and 3.4% during Δ25% ASR session, respectively. Only the residuals in RPE were significantly (p < 0.001) higher in 110% vVO2max and Δ15% ASR in comparison to Δ25% ASR. Time spent ≥90% HRmax /VO2max was maximized during Δ15% ASR session, albeit this was not significantly different from other sessions. The ASR-based method leads to reduced CVs of physiological and perceptual responses during 10-min HIIT; however, only reductions in [La] and RPE may be considered practically meaningful. Practitioners can use vVO2max for prescription of 10-min HIIT session comprised of 15-s work and passive recovery intervals.

Does Lactate-Guided Threshold Interval Training within a High-Volume Low-Intensity Approach Represent the "Next Step" in the Evolution of Distance Running Training?

The aim of the present study was to describe a novel training model based on lactate-guided threshold interval training (LGTIT) within a high-volume, low-intensity approach, which characterizes the training pattern in some world-class middle- and long-distance runners and to review the potential physiological mechanisms explaining its effectiveness. This training model consists of performing three to four LGTIT sessions and one VO2max intensity session weekly. In addition, low intensity running is performed up to an overall volume of 150-180 km/week. During LGTIT sessions, the training pace is dictated by a blood lactate concentration target (i.e., internal rather than external training load), typically ranging from 2 to 4.5 mmol·L-1, measured every one to three repetitions. That intensity may allow for a more rapid recovery through a lower central and peripheral fatigue between high-intensity sessions compared with that of greater intensities and, therefore, a greater weekly volume of these specific workouts. The interval character of LGTIT allows for the achievement of high absolute training speeds and, thus, maximizing the number of motor units recruited, despite a relatively low metabolic intensity (i.e., threshold zone). This model may increase the mitochondrial proliferation through the optimization of both calcium and adenosine monophosphate activated protein kinase (AMPK) signaling pathways.

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

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

Expanding Knowledge About the Effect of Measurement Time on Session Rating of Perceived Exertion.

ABSTRACT: Rodríguez-Marroyo, JA, Blanco, P, Foster, C, Villa, JG, and Carballo-Leyenda, B. Expanding knowledge about the effect of measurement time on session rating of perceived exertion. J Strength Cond Res 37(1): 230-233, 2023-The purpose of this study was to analyze the effect of postexercise rating times (from 0 minutes to 4 weeks) on session rating of perceived exertion (sRPE). Twenty-five athletes (12 women and 13 men) from different sports (sprinting, endurance running, cycling, and volleyball) were involved in this study. At least 3 training sessions per subject were quantified based on sRPE using a visual analog scale. The scale was administered immediately after, at 5, 10, 20, and 30 minutes, 24, 48, and 72 hours, and 1, 2, 3, and 4 weeks postexercise. In addition, the effect of rating time on sRPE was studied according to the training intensity. For this, the training sessions were classified (based on the 30-minute rating) as easy (sRPE < 3), moderate (sRPE 3-5), and hard (sRPE > 5). A significant (p < 0.001) main effect of the postexercise rating time on sRPE was found. There were significant (p < 0.05) differences between sRPE obtained at 30 minutes and those obtained immediately after hard training sessions and at 1, 2, 3, and 4 weeks postexercise. There was no significant effect of rating time on sRPE in the easy and moderate training sessions. In conclusion, the present data suggest that athletes' sRPE may be obtained in a valid and reliable manner within a time frame of 5 minutes to 72 hours posttraining. The effect of postexercise rating time on sRPE seems to be conditioned by the training intensity, especially in those training sessions whose training intensity was high (sRPE > 5).

Can plyometric training change the pacing behaviour during 10-km running?

The effects of plyometric training (PT) on middle- and long-distance running performances are well established. However, its influence on pacing behaviour is still unclear. The aim of this study was to evaluate the effects of PT on pacing behaviour. In addition, verify whether the adaptations induced by PT would change ratings of perceived exertion (RPE) and/or affective feelings during the race. Twenty-eight male runners were assigned to two groups: control (C) and PT. PT held two weekly PT sessions for eight weeks. Drop jump (DJ) performance, 10-km running performance, pacing behaviour, RPE and affective feelings, VO2peak, ventilatory thresholds (VT1 and VT2), peak treadmill speed (PTS), and running economy (RE) were measured. For group comparisons, a mixed model analysis for repeated measures, effect size (ES) and 90% confidence interval (90% CI) were calculated for all dependent variables. Significant differences pre-to-post was observed for PT group in DP (7.2%; p ≤ 0.01; ES = 0.56 (0.28-0.85)) and RE (4.5%; p ≤ 0.05; ES = -0.52 ((-0.73 to -0.31)) without changes in pacing behaviour. While PT was effective for improving DJ and RE, there is no evidence that pacing behaviour, RPE or affective feelings are directly affected by these adaptations during a 10-km time trial run.

Effect of Face Masks on Physiological and Perceptual Responses during 30 Minutes of Self-Paced Exercise in Older Community Dwelling Adults.

This study examined the effects of different types of masks (no mask, surgical mask (SM), and N95-mask) on physiological and perceptual responses during 30-min of self-paced cycle ergometer exercise. This study was a prospective randomly assigned experimental design. Outcomes included workload (Watts), oxygen saturation (SpO2), end-tidal carbon dioxide (PetCO2), heart rate (HR), respiratory rate (RR), rating of perceived exertion (RPE), and rating of perceived dyspnea (RPD). Volunteers (54-83 years (n = 19)) completed two familiarization sessions and three testing sessions on an air braked cycle ergometer. No significant difference was found for condition x time for any of the dependent variables. RPE, RPD, and PetCO2 were significantly higher with an N95-mask vs. no mask (NM) ((p = 0.012), (p = 0.002), (p < 0.001)). HR was significantly higher with the SM compared to the NM condition (p = 0.027) (NM 107.18 ± 9.96) (SM 112.34 ± 10.28), but no significant difference was found when comparing the SM to the N95 condition or when comparing the N95condition to the NM condition. Watts increased across time in each condition (p = 0.003). Initially RR increased during the first 3 min of exercise (p < 0.001) with an overall gradual increase noted across time regardless of mask condition (p < 0.001). SpO2 significantly decreased across time but remained within normal limits (>95%). No significant difference was found in Watts, RR, or SpO2 regardless of mask condition. Overall, the N95mask was associated with increased RPE, RPD, and PetCO2 levels. This suggests trapping of CO2 inside the mask leading to increased RPE and RPD.

Validation of session ratings of perceived exertion for quantifying training load in karate kata sessions.

This study was intended to investigate the associations between session Ratings of Perceived Exertion (sRPE) and Edwards' training load (TL) and Banister training impulse (TRIMP) in order to determine the validity of the sRPE method for TL assessment in karate kata discipline. Eight elite karate kata athletes, members of the national karate team, took part in this study. A multistage 20 m shuttle run test was performed to determine maximal heart rate (HRmax). Subsequently, the subjects performed 3 different kata training sessions separated by minimally 48 hours. To calculate Edwards TL, Banister TRIMP and sRPE, heart rate (HR) was continuously monitored during the sessions and RPE of the entire session was collected 30 minutes after each training session. The Pearson correlation coefficient (r) was used for determining associations between TL variables. Edwards TL (p = 0.064) and Banister TRIMP (p = 0.102) were not, but sRPE was significantly different between each training session (p < 0.001). There were no significant correlations between sRPE and Edwards TL (r = 0.53, p = 0.18) or Banister TRIMP (r = 0.13, p = 0.77) when data from all training sessions were pooled. A significant correlation was obtained between sRPE and Edwards TL (r = 0.71, p = 0.04) in situational training session, whereas in technical training session sRPE was significantly correlated with Banister TRIMP (r = 0.82, p = 0.01). HR-based methods for TL assessment are not able to discriminate between kata training sessions and, therefore, sRPE may be more useful for coaches to monitor TL in karate kata athletes.

COVID-19 Lockdown: A Global Study Investigating the Effect of Athletes' Sport Classification and Sex on Training Practices.

PURPOSE: To investigate differences in athletes' knowledge, beliefs, and training practices during COVID-19 lockdowns with reference to sport classification and sex. This work extends an initial descriptive evaluation focusing on athlete classification. METHODS: Athletes (12,526; 66% male; 142 countries) completed an online survey (May-July 2020) assessing knowledge, beliefs, and practices toward training. Sports were classified as team sports (45%), endurance (20%), power/technical (10%), combat (9%), aquatic (6%), recreational (4%), racquet (3%), precision (2%), parasports (1%), and others (1%). Further analysis by sex was performed. RESULTS: During lockdown, athletes practiced body-weight-based exercises routinely (67% females and 64% males), ranging from 50% (precision) to 78% (parasports). More sport-specific technical skills were performed in combat, parasports, and precision (∼50%) than other sports (∼35%). Most athletes (range: 50% [parasports] to 75% [endurance]) performed cardiorespiratory training (trivial sex differences). Compared to prelockdown, perceived training intensity was reduced by 29% to 41%, depending on sport (largest decline: ∼38% in team sports, unaffected by sex). Some athletes (range: 7%-49%) maintained their training intensity for strength, endurance, speed, plyometric, change-of-direction, and technical training. Athletes who previously trained ≥5 sessions per week reduced their volume (range: 18%-28%) during lockdown. The proportion of athletes (81%) training ≥60 min/session reduced by 31% to 43% during lockdown. Males and females had comparable moderate levels of training knowledge (56% vs 58%) and beliefs/attitudes (54% vs 56%). CONCLUSIONS: Changes in athletes' training practices were sport-specific, with few or no sex differences. Team-based sports were generally more susceptible to changes than individual sports. Policy makers should provide athletes with specific training arrangements and educational resources to facilitate remote and/or home-based training during lockdown-type events.

Simple Approach to Defining Training Intensity in Endurance Runners.

Training intensity distribution is important to training program design. The zones 1 to 2 boundary can be defined by the Talk Test and the rating of perceived exertion. The zones 2 to 3 boundary can be defined by respiratory gas exchange, maximal lactate steady state, or, more simply, by critical speed (CS). The upper boundary of zone 3 is potential defined by the velocity at maximum oxygen uptake (vVO2max), although no clear strategy has emerged to categorize this intensity. This is not normally definable outside the laboratory. PURPOSE: This study predicts vVO2max from CS, determined from 1 (1.61 km) and 2 (3.22 km) citizen races in well-trained runners. METHODS: A heterogeneous group of well-trained runners (N = 22) performed 1- and 2-mile races and were studied during submaximal and maximal treadmill running to measure oxygen uptake, allowing computation of vVO2max. This vVO2max was compared with CS. RESULTS: vVO2max (4.82 [0.53] m·s-1) was strongly correlated with CS (4.37 [0.49] m·s-1; r = .84, standard error of estimate [SEE] = 0.132 m·s-1), 1-mile speed (5.09 [0.51] m·s-1; r = .84, SEE = 0.130 m·s-1), and 2-mile speed (4.68 [0.49] m·s-1; r = .86, SEE = 0.120 m·s-1). CONCLUSIONS: CS, calculated from 2 citizen races (or even training time trials), can be used to make reasonable estimates of vVO2max, which can be used in the design of running training programs.