Re-thinking athlete training loads: would you rather have one big rock or lots of little rocks dropped on your foot?

Determination of athlete training loads is of great interest to sport practitioners and is widely used in the prescription and monitoring of physical conditioning programmes. Although a number of methods of load quantification are used, a common feature is that total load calculations are the product of exercise intensity and duration. We argue that these methods may be limited, however, as they do not account for non-linearities in the biological response to stress, with the end result being that they fail to fully account for the load imposed by high-intensity or interval-based training sessions. We end with a call for sport scientists to develop novel method of training load quantification to better deal with this issue.

Physiological Responses to and Athlete and Coach Perceptions of Exertion During Small-Sided Basketball Games.

Vaquera, A, Suárez-Iglesias, D, Guiu, X, Barroso, R, Thomas, G, and Renfree, A. Physiological responses to and athlete and coach perceptions of exertion during small-sided basketball games. J Strength Cond Res 32(10): 2949-2953, 2018-This study describes heart rate (HR) responses during different small-sided games (SSGs) in junior basketball players and identifies the level of agreement between athlete and coach perceptions of internal training load calculated using the in-task rating of perceived exertion (RPE) method. Over a 6-week period, 12 male junior basketball players, who played in the Spanish national under-18 League, played 7 games of one-a-side (1v1), 6 games of 2-a-side (2v2), 8 games of 5-a-side (5v5), and 5 games of superiority (3v2) situations. During 1v1, 2v2, 5v5, and 3v2, peak HRs were 90.27 ± 3.37%, 92.68 ± 3.29%, 92.01 ± 3.48%, and 88.74 ± 5.77% of HRmax, respectively. These differences were statistically significant between 1v1 and 2v2 (p < 0.01), 1v1 and 5v5 (p ≤ 0.05), 2v2 and 3v2 (p < 0.001), and 5v5 and 3v2 (p < 0.001). Mean HR was 79.5 ± 4.4%, 83.1 ± 4.2%, 91.2 ± 4.7%, and 78.5 ± 7.5% of HRmax during 1v1, 2v2, 5v5, and 3v2, respectively, and differences were observed between 1v1 and 2v2 (p < 0.001), 2v2 and 3v2 (p < 0.001), and 5v5 and 3v2 (p ≤ 0.05). There were differences in athletes and coaches in-task RPE in all SSGs (all p < 0.0001 apart from 5 × 5 p = 0.0019). The 2v2 format elicited a higher mean in-task RPE in comparison with all other SSGs (p < 0.001), possibly because 2v2 imposes a greater cognitive load.

Validity and Test-Retest Reliability of the TIVRE-Basket Test for the Determination of Aerobic Power in Elite Male Basketball Players.

The aims of this study were to (a) determine the relationship between performance on the court-based TIVRE-Basket test and peak aerobic power determined from a criterion laboratory-based incremental treadmill test and (b) to examine the test-retest reliability of the TIVRE-Basket test in elite male basketball players. To address aim 1, 36 elite male basketball players (age: 25.2 ± 4.7 years, weight: 94.1 ± 11.4 kg, height: 195.83 ± 9.6 cm) completed a graded treadmill exercise test and the TIVRE-Basket within 72 hours. The mean distance recorded during the TIVRE-Basket test was 4001.8 ± 176.4 m, and mean VO2 peak was 54.7 ± 2.8 ml · kg(-1) · min(-1), and the correlation between the 2 parameters was r = 0.824 (p ≤ 0.001). Linear regression analysis identified TIVRE-Basket distance (in meters) as the only unique predictor of VO2 peak in a single variable plus constant model: VO2 peak = 2.595 + (0.13 × TIVRE-Basket distance [in meters]). Performance on the TIVRE-Basket test accounted for 67.8% of the variance in VO2 peak (t = 8.466, p ≤ 0.001, 95% confidence interval: 0.01-0.016, SEE: 1.61). To address aim 2, 20 male basketball players (age: 26.7 ± 4.2 years, height: 1.94 ± 0.92 cm, weight: 94.0 ± 9.1 kg) performed the TIVRE-Basket test on 2 occasions. There was no significant difference in total distance covered between trial 1 (4138.8 ± 677.3 m) and trial 2 (4188.0 ± 648.8 m; t = 0.5798, p = 0.5688). Mean difference between trials was 49.2 ± 399.5 m, with an intraclass correlation coefficient of 0.85 suggesting a moderate level of reliability. Standardized typical error of measurement was 0.88%, representing a moderate degree of trial-to-trial error, and the Coefficient of Variation (CV) was 6.3%. The TIVRE-Basket test therefore represents a valid and moderately reliable court-based sport-specific test of aerobic power for use with individuals and teams of elite-level male basketball players. Future research is required to ascertain its validity and reliability in other basketball populations, for example, across age groups, at different levels of competition, in females and in different forms of the game, for example, wheelchair basketball.

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.

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.

Exercise Dose Equalization in High-Intensity Interval Training: A Scoping Review.

Based on comparisons to moderate continuous exercise (MICT), high-intensity interval training (HIIT) is becoming a worldwide trend in physical exercise. This raises methodological questions related to equalization of exercise dose when comparing protocols. The present scoping review aims to identify in the literature the evidence for protocol equalization and the soundness of methods used for it. PubMed and Scopus databases were searched for original investigations comparing the effects of HIIT to MICT. A total of 2041 articles were identified, and 169 were included. Of these, 98 articles equalized protocols by utilizing energy-based methods or exercise volume (58 and 31 articles, respectively). No clear consensus for protocol equalization appears to have evolved over recent years. Prominent equalization methods consider the exercise dose (i.e., energy expenditure/production or total volume) in absolute values without considering the nonlinear nature of its relationship with duration. Exercises resulting from these methods induced maximal exertion in HIIT but low exertion in MICT. A key question is, therefore, whether exercise doses are best considered in absolute terms or relative to individual exercise maximums. If protocol equalization is accepted as an essential methodological prerequisite, it is hypothesized that comparison of program effects would be more accurate if exercise was quantified relative to intensity-related maximums.

Effects of different goal orientations and virtual opponents performance level on pacing strategy and performance in cycling time trials.

We investigated the effects of different performance goals (best time vs. beat the opponent) on pacing behaviour during a 10-km cycling race and explored the influence of different performance level of opponents on ratings of perceived exertion (RPE), affective feelings and self-efficacy. Thirteen cyclists performed two time-trials (TT) and two races against a faster (FAST +6%) or a slower (SLOW -3%) virtual opponent. Power output (PO), RPE, affective feelings and self-efficacy were recorded at each kilometre point. Race average and race phases [starting (P1 = first kilometre); first half (P2 = 2nd-5th kilometre); second half (P3 = 6th-9th kilometre) and final sprint (FS = last kilometre)] were analysed. There was no difference in performance, assessed by race time between conditions (p = .84). PO during TT was lower in P3 compared to FS (p = .03; ES 0.6; 90%CI 0.4-0.7). In SLOW and FAST, PO was higher in P1 compared to other phases (p < .05). PO in FS was higher in TT compared to FAST (p = .01; ES -0.97; 90%IC -1.4 to -0.5). RPE increased and affective feelings decreased during all conditions. Self-efficacy was stable through TT and SLOW, but decreased during FAST with higher values in P1 compared to P2 (p = .01; ES -1.1; 90%IC -1.6 to -0.6), P3 (p < .001; ES -2.2; 90%IC -2.8 to -1.6) and FS (p < .001; ES -2.6; 90%IC -3.3 to -1.8). Pacing behaviour, specifically starting and final sprint, was affected by virtual opponents independent of performance level, demonstrating the importance of goal orientation.HighlightsAdjustments in exercise intensity result from a complex decision-making process involving physiological, psychological, environmental and tactical information.Goal pursuit is an important determinant of pacing behaviour since athletes must balance their efforts with expectations of success.A competitive environment may be included to motivate participants to maintain their effort and at the same time to improve their self-confidence.The presence of a final sprint seems to be related to the goal orientation and perceived outcomes of success or failure.

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.

Differentiating Endurance-and Speed-Adapted Types of Elite and World Class Milers According to Biomechanical, Pacing and Perceptual Responses during a Sprint Interval Session.

The aim was to compare pacing, biomechanical and perceptual responses between elite speed-and endurance-adapted milers during a sprint interval training session (SIT). Twenty elite and world-class middle-distance runners (male: n = 16, female: n = 4; 24.95 ± 5.18 years; 60.89 ± 7 kg) were classified as either speed- or endurance-adapted milers according to their recent performances at 800 m or longer races than 1500 m (10 subjects per group). Participants performed 10 repetitions of 100 m sprints with 2 min of active recovery between each, and performance, perceptual and biomechanical responses were collected. The difference between accumulated times of the last and the first five repetitions was higher in speed-adapted milers (ES = 1.07) displaying a more positive pacing strategy. A higher coefficient of variation (CV%) was displayed across the session by speed-adapted milers in average repetition time, contact time, and affective valence (ES ≥ 1.15). Speed-adapted milers experienced lower rates of valence after the 4th repetition excepting at the 8th repetition (ES ≥ 0.99). Speed-adapted milers may need to display a more positive pacing profile than endurance-adapted milers and, therefore, would experience lower levels of affective valence and a more rapid increase of ground contact time during a SIT.

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

PURPOSE: To determine different relationships between, and predictive ability of, performance variables at intermediate distances with finishing time in elite male 10,000-m runners. METHODS: Official electronic finishing and 100-m split times of the men's 10,000-m finals at the 2008 and 2016 Olympic Games and IAAF World Championships in 2013 and 2017 were obtained (125 athlete performances in total). Correlations were calculated between finishing times and positions and performance variables related to speed, position, time to the leader, and time to the runner in front at 2000, 4000, 6000, 8000, and 9900 m. Stepwise linear-regression analysis was conducted between finishing times and positions and these variables across the race. One-way analysis of variance was performed to identify differences between intermediate distances. RESULTS: The SD and kurtosis of mean time, skewness of mean time, and position and time difference to the leader were either correlated with or significantly contributed to predictions of finishing time and position at at least one of the analyzed distances (.81 ≥ r ≥ .30 and .001 ≤ P ≤ .03, respectively). These variables also displayed variation across the race (.001 ≤ P ≤ .05). CONCLUSIONS: The ability to undertake a high degree of pace variability, mostly characterized by acceleration in the final stages, is strongly associated with achievement of high finishing positions in championship 10,000-m racing. Furthermore, the adoption and maintenance of positions close to the front of the race from the early stages are important to achieve a high finishing position.

A Plyometric Warm-Up Protocol Improves Running Economy in Recreational Endurance Athletes.

This study explored the impact of two differing warm-up protocols (involving either resistance exercises or plyometric exercises) on running economy (RE) in healthy recreationally active participants. Twelve healthy university students [three males, nine females, age 20 ± 2 years, maximal oxygen uptake (38.4 ± 6.4 ml min-1 kg-1)] who performed less than 5 h per week of endurance exercise volunteered to participant in this study. All participants completed three different warm-up protocols (control, plyometric, and resistance warm-up) in a counterbalanced crossover design with trials separated by 48 h, using a Latin-square arrangement. Dependent variables measured in this study were RE at four running velocities (7, 8, 9, and 10 km h-1), maximal oxygen uptake; heart rate; respiratory exchange rate; expired ventilation; perceived race readiness; rating of perceived exertion, time to exhaustion and leg stiffness. The primary finding of this study was that the plyometric warm-up improved RE compared to the control warm-up (6.2% at 7 km h-1, ES = 0.355, 9.1% at 8 km h-1, ES = 0.513, 4.5% at 9 km h-1, ES = 0.346, and 4.4% at 10 km h-1, ES = 0.463). There was no statistically significant difference in VO2 between control and resistance warm-up conditions at any velocity. There were also no statistically significant differences between conditions in other metabolic and pulmonary gas exchange variables; time to exhaustion; perceived race readiness and maximal oxygen uptake. However, leg stiffness increased by 20% (P = 0.039, ES = 0.90) following the plyometric warm-up and was correlated with the improved RE at a velocity of 8 km h-1 (r = 0.475, P = 0.041). No significant differences in RE were found between the control and resistance warm-up protocols. In comparison with the control warm-up protocol, an acute plyometric warm-up protocol can improve RE in healthy adults.

Affective Feelings and Perceived Exertion During a 10-km Time Trial and Head-to-Head Running Race.

PURPOSE: To verify the affective feelings (AFs) and rating of perceived exertion (RPE) responses during a 10-km competitive head-to-head (HTH) running race and compare them with a time-trial (TT) running race. METHODS: Fourteen male runners completed 2 × 10-km runs (TT and HTH) on different days. Speed, RPE, and AF were measured every 400 m. For pacing analysis, races were divided into the following 4 stages: first 400 m (F400), 401-5000 m (M1), 5001-9600 m (M2), and the last 400 m (final sprint). RESULTS: Improvement of performance was observed (39:32 [02:41] min:s vs 40:28 [02:55] min:s; P = .03; effect size = -0.32) in HTH compared with TT. There were no differences in either pacing strategy or RPE between conditions. AFs were higher during the HTH, being different in M2 compared with TT (2.09 [1.81] vs 0.22 [2.25]; P = .02; effect size = 0.84). CONCLUSIONS: AFs are directly influenced by the presence of opponents during an HTH race, and a more positive AF could be involved in the dissociation between RPE and running speed and, consequently, the overall race performance.

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

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

Lane and Heat Draw Have Little Effect on Placings and Progression in Olympic and IAAF World Championship 800 m Running.

The aim of this study was to establish whether the lane and heat draw influenced placings and progression in world-class 800-m track running. Finishing positions and times of 1,086 performances at the Olympic Games and IAAF World Championships between 1999 and 2017 were obtained. Mean finishing and season's best times (SB), as well as placings and progression rates, were found for each heat number and for the inner (Lanes 1 and 2), middle (Lanes 3-6), and outer lanes (Lanes 7 and 8). In the qualifying heats and semi-finals, the theoretically expected number of fastest losers (non-automatic qualifiers) per heat was compared with the actual number. One-way ANOVA with Bonferroni post-hoc tests were conducted to compare finishing times between lane and heat numbers across rounds. With regard to the order of heats, there were no differences between finishing times in either the qualifying heats or semi-final rounds for men; in the women's event, only Semi-final 3 was the quickest, but still did not have higher progression rates. SB times did not differ between heats within each round, highlighting the fair distribution of athletes. Progression rates for each lane during the qualifying heats ranged between 36 and 52% (men) and between 49 and 61% (women), close to the expected ranges of 45 and 55%, respectively. The middle lanes were quicker in the seeded semi-finals and finals only. Men in the outer lanes fared slightly worse and should focus on achieving the optimal tactical position after breaking from lanes. The IAAF could reconsider how they allocate seeded lanes in the later rounds by switching the fifth and sixth fastest athletes from the outer to the inner lanes. Regarding the heat draw, athletes mostly did not take advantage of knowing previous performances from earlier races, and probably focused on achieving an automatic qualifying position instead. However, the fastest losers in the women's last semi-final were faster and showed that benefitting from the heat draw is possible with tactical coaching.

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 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.

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

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

Fortune Favors the Brave: Tactical Behaviors in the Middle-Distance Running Events at the 2017 IAAF World Championships.

PURPOSE: To assess tactical and performance factors associated with progression from qualification rounds in the 800-m and 1500-m running events at the 2017 International Association of Athletics Federations World Championships. METHODS: Official results were used to access final and intermediate positions and times, as well as performance characteristics of competitors. Shared variance between intermediate positions and rank order lap times with finishing positions were calculated, along with probability of automatic qualification, for athletes in each available race position at the end of every 400-m lap. Differences in race positions and lap times relative to season's best performances were assessed between automatic qualifiers, fastest losers, and nonqualifiers. RESULTS: Race positions at the end of each 400-m lap remained more stable through 800-m races than 1500-m races. Probability of automatic qualification decreased with both race position and rank order lap times on each lap, although rank order lap times accounted for a higher degree of shared variance than did intermediate position. In the 1500-m event, fastest losers ran at a higher percentage of season's best speed and adopted positions closer to the race lead in the early stages. This was not the case in the 800-m. CONCLUSIONS: Intermediate positioning and the ability to produce a fast final race segment are strongly related to advancement from qualification rounds in middle-distance running events. The adoption of a more "risky" strategy characterized by higher speeds relative to season's best may be associated with an increased likelihood of qualification as fastest losers in the 1500-m event.

A Computer Model of Drafting Effects on Collective Behavior in Elite 10,000-m Runners.

PURPOSE: Drafting in cycling influences collective behavior of pelotons. Although evidence for collective behavior in competitive running events exists, it is not clear if this results from energetic savings conferred by drafting. This study modeled the effects of drafting on behavior in elite 10,000-m runners. METHODS: Using performance data from a men's elite 10,000-m track running event, computer simulations were constructed using Netlogo 5.1 to test the effects of 3 different drafting quantities on collective behavior: no drafting, drafting to 3 m behind with up to ~8% energy savings (a realistic running draft), and drafting up to 3 m behind with up to 38% energy savings (a realistic cycling draft). Three measures of collective behavior were analyzed in each condition: mean speed, mean group stretch (distance between first- and last-placed runner), and runner-convergence ratio (RCR), which represents the degree of drafting benefit obtained by the follower in a pair of coupled runners. RESULTS: Mean speeds were 6.32 ± 0.28, 5.57 ± 0.18, and 5.51 ± 0.13 m/s in the cycling-draft, runner-draft, and no-draft conditions, respectively (all P < .001). RCR was lower in the cycling-draft condition but did not differ between the other 2. Mean stretch did not differ between conditions. CONCLUSIONS: Collective behaviors observed in running events cannot be fully explained through energetic savings conferred by realistic drafting benefits. They may therefore result from other, possibly psychological, processes. The benefits or otherwise of engaging in such behavior are as yet unclear.

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

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