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Brian Hanley, Trent Stellingwerff and Florentina J. Hettinga

comprehensive analysis of pacing profiles, using high-resolution 100-m split times, adopted throughout major championships will better inform coaches about successful approaches to middle-distance racing, and including an analysis of variability will indicate the importance of responding to (or instigating

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Sabrina Skorski, Oliver Faude, Seraina Caviezel and Tim Meyer

Purpose:

To analyze the reproducibility of pacing in elite swimmers during competitions and to compare heats and finals within 1 event.

Methods:

Finals and heats of 158 male swimmers (age 22.8 ± 2.9 y) from 29 nations were analyzed in 2 competitions (downloaded from swimrankings.net). Of these, 134 were listed in the world’s top 50 in 2010; the remaining 24 were finalists of the Pan Pacific Games or European Championships. The level of both competitions for the analysis had to be at least national championships (7.7 ± 5.4 wk apart). Standard error of measurement expressed as percentage of the subject’s mean score (CV) with 90% confidence limits (CL) for each 50-m split time and for total times were calculated. In addition, mixed general modeling was used to determine standard deviations between and within swimmers.

Results:

CV for total time in finals ranged between 0.8% and 1.3% (CL 0.6–2.2%). Regarding split times, 200-m freestyle showed a consistent pacing over all split times (CV 0.9–1.6%). During butterfly, backstroke, and 400-m freestyle, CVs were low in the first 3 and 7 sections, respectively (CV 0.9–1.7%), with greater variability in the last section (1.9–2.2%). In breaststroke, values were higher in all sections (CV 1.2–2.3%). Within-subject SDs for changes between laps were between 0.9% and 2.6% in all finals. Split-time variability for finals and heats ranged between 0.9% and 2.5% (CL 0.3–4.9%).

Conclusion:

Pacing profiles are consistent between different competitions. Variability of pacing seems to be a result of the within-subject variation rather than a result of different competitions

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Brian Hanley

Purpose:

The aim of this study was to describe the pacing profiles used by racewalkers competing in IAAF World Championships.

Methods:

The times for each 5-km segment were obtained for 225 men competing over 20 km, 214 women competing over 20 km, and 232 men competing over 50 km, of whom 49 did not finish. Athletes were grouped based on finishing position (for medalists) or finishing time.

Results:

Different pacing profiles were used by athletes grouped by finishing time, with 20-km medalists using negative pacing and those finishing within 5% of the winning time matching the medalists’ early pace but failing to maintain it. Lower-placed 20-km athletes tended to start more quickly relative to personal-best pace and experienced significant decreases in pace later. Across all competitions, the fastest finishers started the slowest relative to previous best performance. All 50-km athletes slowed toward the finish, but lower-placed finishers tended to decrease pace earlier (with up to 60% of the race remaining). After halfway in the 50-km, 8 of the 15 athletes who had a 5-km split more than 15% slower than the previous split dropped out.

Conclusions:

The negative pacing profile used by 20-km medalists required the ability to start fast and maintain this pace, and similarly paced training may be beneficial in race preparation. Over 50 km, the tactic of starting slower than personal-best pace was generally less risky; nonetheless, any chosen pacing strategy should be based on individual strengths.

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Graham J. Mytton, David T. Archer, Alan St Clair Gibson and Kevin G. Thompson

Purpose:

To assess the reliability and stability of 400-m swimming and 1500-m running competitions to establish the number of samples needed to obtain a stable pacing profile. Coaches, athletes, and researchers can use these methods to ensure that sufficient data are collected before training and race strategies are constructed or research conclusions are drawn.

Method:

Lap times were collected from 5 world and European championship finals between 2005 and 2011, resulting in the capture of data from 40 swimmers and 55 runners. A cumulative mean for each lap was calculated, starting with the most recent data, and the number of races needed for this to stabilize to within 1% was reported. Typical error for each lap was calculated for athletes who had competed in more than 1 final.

Results:

International swimmers demonstrated more reproducible performances than runners in 3 of the 4 laps of the race (P < .01). Variance in runners’ lap times significantly decreased by 1.7–2.7% after lap 1, whereas variance in swimmers’ lap times tended to increase by 0.1–0.5% after lap 1. To establish a stable profile, at least ten 400-m swimmers and forty-four 1500-m runners must be included.

Conclusions:

A stable race profile was observed from the analysis of 5 events for 1500-m running and 3 events for 400-m swimming. Researchers and athletes can be more certain about the pacing information collected from 400-m swimming than 1500-m running races, as the swimming data are less variable, despite both events being of similar duration.

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Arthur H. Bossi, Ciaran O’Grady, Richard Ebreo, Louis Passfield and James G. Hopker

unique pacing profile would be unsurprising, especially if the amount of running performed per lap varies as the race progresses. In this regard, establishing how elite athletes pace themselves during cyclo-cross races will provide coaches and scientists with an in-depth understanding of this discipline

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Luis Rodriguez and Santiago Veiga

a rapid start, with a progressive decrease in velocity until the finish, also known as positive pacing profile. 7 However, for middle-duration events (2–4 min), athletes may start quickly, but they slow through the middle stages, and finally, they produce an end spurt. This has been described as a

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Luca Filipas, Emiliano Nerli Ballati, Matteo Bonato, Antonio La Torre and Maria Francesca Piacentini

lap. However, studies analyzing 800-m performances, 3 tactical behaviors, 5 or energy system contribution during real or simulated competition 8 – 10 mainly studied male participants. Only 1 study has analyzed the pacing profiles and physiological requirements of high-level male athletes during 800

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Jo Corbett

Purpose:

To investigate pacing strategy during the 1-km time trial (TT) and 3- and 4-km individual pursuit (IP), in elite cyclists.

Methods:

Total times and intermediate times were obtained from the 2007 and 2008 cycling World Championships in the 1-km TT and 2006, 2007, and 2008 World Championships in the 3- and 4-km IP. Data were analyzed to examine the pacing-profiles employed and pacing strategies of “slow” and “fast” performances.

Results:

Similar pacing-profiles were evident in each event, which were characterized by an initial acceleration followed by a progressive decay in split times. In the 1-km TT, the first 250-m split time was a primary determinant of total time, whereas the rate of fatigue over the remainder of the race did not discriminate between performances. The first 250-m split time was also related to total time in the 3- and 4-km IP, although to a lesser extent than in the 1-km TT, whereas the ability to maintain a consistent pacing-profile was of increased importance. There were differences in the pacing strategies of slow and fast performances in the 3- and 4-km IP, with slow performances characterized by an overly quick start with a concomitant slowing at the finish.

Conclusion:

The pacing profiles adopted were similar to the optimal pacing strategies proposed in simulation models of cycling performance. However, in the 3-km and 4-km IP small alterations in pacing strategy appear to be important, at the elite level.

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Cyril Schmit, Rob Duffield, Christophe Hausswirth, Aaron J. Coutts and Yann Le Meur

Purpose:

To describe the effect of the initial perceptual experience from heat familiarization on the pacing profile during a freepaced endurance time trial (TT) compared with temperate conditions.

Methods:

Two groups of well-trained triathletes performed two 20-km TTs in either hot (35°C and 50% relative humidity [RH], n = 12) or temperate (21°C and 50% RH, n = 22) conditions, after standardization of training for each group before both trials. To ensure no physiological acclimation differences between conditions, the TTs for both groups were separated by 11 ± 4 d.

Results:

Performance improvement in the heat (11 ± 24 W) from the 1st to 2nd trial appeared comparable to that in temperate conditions (8 ± 14 W, P = .67). However, the specific alteration in pacing profile in the heat was markedly different than temperate conditions, with a change from “positive” to an “even” pacing strategy.

Conclusions:

Altered perceptions of heat during heat familiarization, rather than physiological acclimatization per se, may mediate initial changes in pacing and TT performance in the heat. These results highlight the need for athletes without time for sufficient heat acclimatization to familiarize themselves with hot conditions to reduce the uncertainty from behavior-based outcomes that may impede performance.

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Louise Martin, Anneliese Lambeth-Mansell, Liane Beretta-Azevedo, Lucy A. Holmes, Rachel Wright and Alan St Clair Gibson

Purpose:

Given the paucity of research on pacing strategies during competitive events, this study examined changes in dynamic high-resolution performance parameters to analyze pacing profiles during a multiple-lap mountain-bike race over variable terrain.

Methods:

A global-positioning-system (GPS) unit (Garmin, Edge 305, USA) recorded velocity (m/s), distance (m), elevation (m), and heart rate at 1 Hz from 6 mountain-bike riders (mean ± SD age = 27.2 ± 5.0 y, stature = 176.8 ± 8.1 cm, mass = 76.3 ± 11.7 kg, VO2max = 55.1 ± 6.0 mL · kg−1 . min−1) competing in a multilap race. Lap-by-lap (interlap) pacing was analyzed using a 1-way ANOVA for mean time and mean velocity. Velocity data were averaged every 100 m and plotted against race distance and elevation to observe the presence of intralap variation.

Results:

There was no significant difference in lap times (P = .99) or lap velocity (P = .65) across the 5 laps. Within each lap, a high degree of oscillation in velocity was observed, which broadly reflected changes in terrain, but high-resolution data demonstrated additional nonmonotonic variation not related to terrain.

Conclusion:

Participants adopted an even pace strategy across the 5 laps despite rapid adjustments in velocity during each lap. While topographical and technical variations of the course accounted for some of the variability in velocity, the additional rapid adjustments in velocity may be associated with dynamic regulation of self-paced exercise.