The goal-directed regulation of exercise intensity over an exercise bout has been defined as pacing and is widely recognized as an essential determinant for performance. 1 Based on existing theories about pacing, it can be concluded that sensations of fatigue and a willingness to tolerate
Marco J. Konings, Jordan Parkinson, Inge Zijdewind and Florentina J. Hettinga
Stacy N. Scott, Cary M. Springer, Jennifer F. Oody, Michael S. McClanahan, Brittany D. Wiseman, Tyler J. Kybartas and Dawn P. Coe
-based shuttle run was developed to simulate a graded exercise test to assess aerobic fitness through the estimation of VO 2 peak ( 6 ). The FitnessGram™ (Cooper Institute for Aerobics Research, Dallas, TX) progressive aerobic cardiovascular endurance run (PACER) assessment was created based on the Leger shuttle
Philip Hurst, Lieke Schipof-Godart, Florentina Hettinga, Bart Roelands and Chris Beedie
reasonable to suggest that after ingesting caffeine, for example, athletes may anticipate an offset in fatigue and alter their exercise behavior. Thus, athletes’ pacing strategy may depend on their belief regarding the effect of a substance and their subsequent decisions during performance. Pacing strategies
Kleverton Krinski, Daniel G. S. Machado, Luciana S. Lirani, Sergio G. DaSilva, Eduardo C. Costa, Sarah J. Hardcastle and Hassan M. Elsangedy
responses during exercise should be explored ( Dalle Grave et al., 2011 ; DaSilva et al., 2009 ; Ekkekakis & Lind, 2006 ; Mattsson, Larsson, & Rössner, 1997 ). In this regard, several studies have highlighted the potential benefits of self-paced walking for individuals with obesity due to lower physical
Sabrina Skorski, Oliver Faude, Seraina Caviezel and Tim Meyer
To analyze the reproducibility of pacing in elite swimmers during competitions and to compare heats and finals within 1 event.
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.
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%).
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
Jelle de Jong, Linda van der Meijden, Simone Hamby, Samantha Suckow, Christopher Dodge, Jos J. de Koning and Carl Foster
To reach top performance in cycling, optimizing distribution of energy resources is crucial. The purpose of this study was to investigate power output during 250-m, 500-m, and 1000-m cycling time trials and the characteristics of the adopted pacing strategy.
Nine trained cyclists completed an incremental test and 3 time trials that they were instructed to finish as quickly as possible. Preceding the trials, peak power during short sprints (PPsprint) and gross efficiency (GE) were measured. During the trials, power output and oxygen consumption were measured to calculate the contribution of the aerobic and anaerobic energy sources. After the trial GE was measured again.
Peak power during all trials (PPTT) was lower than PPsprint. In the 250-m trial the PPTT was higher in the 1000-m trial (P = .008). The subjects performed a significantly longer time at high intensity in the 250-m than in the 1000-m (P = .029). GE declined significantly during all trials (P < .01). Total anaerobically attributable work was less in the 250-m than in the 500-m (P = .015) and 1000-m (P < .01) trials.
The overall pacing pattern in the 250-m trial appears to follow an all-out strategy, although peak power is still lower than the potential maximal power output. This suggests that a true all-out pattern of power output may not be used in fixed-distance events. The 500-m and 1000-m had a more conservative pacing pattern and anaerobic power output reached a constant magnitude.
Silvia Varela, José M. Cancela, Manuel Seijo-Martinez and Carlos Ayán
cycling at a self-selected pace is an easy-going exercise routine with a positive impact on the health status of older adults. Therefore, permitting individuals to self-select the cycling pace, instead of monitoring the intensity of the activity to control the same movements within a pre-established range
Graham J. Mytton, David T. Archer, Louise Turner, Sabrina Skorski, Andrew Renfree, Kevin G. Thompson and Alan St Clair Gibson
Previous literature has presented pacing data of groups of competition finalists. The aim of this study was to analyze the pacing patterns displayed by medalists and nonmedalists in international competitive 400-m swimming and 1500-m running finals.
Split times were collected from 48 swimming finalists (four 100-m laps) and 60 running finalists (4 laps) in international competitions from 2004 to 2012. Using a cross-sectional design, lap speeds were normalized to whole-race speed and compared to identify variations of pace between groups of medalists and nonmedalists. Lap-speed variations relative to the gold medalist were compared for the whole field.
In 400-m swimming the medalist group demonstrated greater variation in speed than the nonmedalist group, being relatively faster in the final lap (P < .001; moderate effect) and slower in laps 1 (P = .03; moderate effect) and 2 (P > .001; moderate effect). There were also greater variations of pace in the 1500-m running medalist group than in the nonmedalist group, with a relatively faster final lap (P = .03; moderate effect) and slower second lap (P = .01; small effect). Swimming gold medalists were relatively faster than all other finalists in lap 4 (P = .04), and running gold medalists were relatively faster than the 5th- to 12th-placed athletes in the final lap (P = .02).
Athletes who win medals in 1500-m running and 400-m swimming competitions show different pacing patterns than nonmedalists. End-spurtspeed increases are greater with medalists, who demonstrate a slower relative speed in the early part of races but a faster speed during the final part of races than nonmedalists.
Carl Foster, Jos J. de Koning and Christian Thiel
The official world records (WR) for the 1-mile run for men (3:43.13) and for women (4:12.58) have improved 12.2% and 32.3%, respectively, since the first WR recognized by the International Association of Athletics Federations. Previous observations have suggested that the pacing pattern for successive laps is characteristically faster-slower-slowest-faster. However, modeling studies have suggested that uneven energy-output distribution, particularly a high velocity at the end of the race, is essentially wasted kinetic energy that could have been used to finish sooner. Here the authors report that further analysis of the pacing pattern in 32 men’s WR races is characterized by a progressive reduction in the within-lap variation of pace, suggesting that improving the WR in the 1-mile run is as much about how energetic resources are managed as about the capacity of the athletes performing the race. In the women’s WR races, the pattern of lap times has changed little, probably secondary to a lack of depth in the women’s fields. Contemporary WR performances have been achieved a coefficient of variation of lap times on the order of 1.5–3.0%. Reasonable projection suggests that the WR is overdue for improving and may require lap times with a coefficient of variation of ~1%.
The aim of this study was to describe the pacing profiles used by racewalkers competing in IAAF World Championships.
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.
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.
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.