Int J Sports Med 2013; 34(02): 152-157
DOI: 10.1055/s-0032-1316357
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Reproducibility of Pacing Profiles in Competitive Swimmers

S. Skorski
1   Institute of Sports and Preventive Medicine, Saarland University, Saarbrücken, Germany
,
O. Faude
1   Institute of Sports and Preventive Medicine, Saarland University, Saarbrücken, Germany
2   Institute of Exercise and Health Sciences, University of Basel, Basel, Switzerland
,
K. Rausch
1   Institute of Sports and Preventive Medicine, Saarland University, Saarbrücken, Germany
,
T. Meyer
1   Institute of Sports and Preventive Medicine, Saarland University, Saarbrücken, Germany
› Author Affiliations
Further Information

Publication History



accepted after revision 24 May 2012

Publication Date:
12 September 2012 (online)

Abstract

This study aimed at determining the reproducibility of pacing profiles (PP) during simulated swimming trials as well as the comparison between simulated and real competitions (RC). Sixteen competitive front crawl swimmers (7 females, 9 males) performed 2×200 m, 2×400 m and 2×800 m tests, each test 7 days apart. All 100 m split (ST) and total times (TT) were recorded (additionally 50 m ST for the 200 m bouts). The PP of one RC within a maximum of 8 weeks before or after data acquisition was used for comparison. No difference was observed between test and retest for TT (p<0.16). Coefficients of variation (CV) for all ST during 800 m were between 0.9 and 1.8% (standard error of measurement (SEM)=0.6–2.1 s), except for the last 2 sections (CV=2.5% and 2.9%). During 400 m and 200 m, CV was below 1.7% for each section (SEM=0.4–1.7 s). Mean differences between test and retest ranged from 1.8 s (Cl: 0.1–3.4 s) in the 400 m bouts to 4.1 s (Cl: 1.3–9.5 s) for the 800 m races. Although section times were faster during all sections of RC compared to SC, PP was similar during both trials (p>0.22). However, swimmers were faster in each section during RC. In conclusion, PP seem stable, at least during the first three quarters of the race. Furthermore, simulated trials seem to be an acceptable model to analyse PP in competitive swimming.

 
  • References

  • 1 Abbiss CR, Laursen PB. Describing and understanding pacing strategies during athletic competition. Sports Med 2008; 38: 239-252
  • 2 Ansley L, Schabort St E, Clair Gibson A, Lambert MI, Noakes TD. Regulation of pacing strategies during successive 4-km time trials. Med Sci Sports Exerc 2004; 36: 1819-1825
  • 3 Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med 1998; 26: 217-238
  • 4 Baron B, Moullan F, Deruelle F, Noakes TD. The role of emotions on pacing strategies and performance in middle and long duration sport events. Br J Sports Med 2011; 45: 511-517
  • 5 Batterham AM, Atkinson G. How big does my sample need to be? A primer on the murky world of sample size estimation. Phys Ther Sport 2005; 6: 153-163
  • 6 Brown MR, Delau S, Desgorces FD. Effort regulation in rowing races depends on performance level and exercise mode. J Sci Med Sport 2010; 13: 613-617
  • 7 Chaffin M, Berg K, Zuniga J, Hanumanthu VS. Pacing pattern in a 30-minute maximal cycling test. J Strength Cond Res 2008; 22: 2011-2017
  • 8 Chatard JC, Wilson B. Drafting distance in swimming. Med Sci Sports Exerc 2003; 35: 1176-1181
  • 9 Corbett J, Barwood MJ, Ouzounoglou A, Thelwell R, Dicks M. Influence of competition on performance and pacing during cycling exercise. Med Sci Sports Exerc 2012; 44: 509-515
  • 10 Corbett J, Barwood MJ, Parkhouse K. Effect of task familiarisation on distribution of energy during a 2 000 m cycling time trial. Br J Sports Med 2009; 43: 770-774
  • 11 Foster C, Green MA, Snyder AC, Thompson NN. Physiological responses during simulated competition. Med Sci Sports Exerc 1993; 25: 877-882
  • 12 Foster C, Hendrickson KJ, Peyer K, Reiner B, deKoning JJ, Lucia A, Battista RA, Hettinga FJ, Porcari JP, Wright G. Pattern of developing the performance template. Br J Sports Med 2009; 43: 765-769
  • 13 Foster C, Schrager M, Snyder AC, Thompson NN. Pacing strategy and athletic performance. Sports Med 1994; 17: 77-85
  • 14 Harriss DJ, Atkinson G. Update – ethical standards in sport and exercise science research. Int J Sports Med 2011; 32: 819-821
  • 15 Hettinga FJ, De Koning JJ, Broersen FT, Van Geffen P, Foster C. Pacing strategy and the occurrence of fatigue in 4 000-m cycling time trials. Med Sci Sports Exerc 2006; 38: 1484-1491
  • 16 Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 2000; 30: 1-15
  • 17 Hopkins WG, Hawley JA, Burke LM. Design and analysis of research on sport performance enhancement. Med Sci Sports Exerc 1999; 31: 472-485
  • 18 Laursen PB, Shing CM, Jenkins DG. Reproducibility of a laboratory-based 40-km cycle time-trial on a stationary wind-trainer in highly trained cyclists. Int J Sports Med 2003; 24: 481-485
  • 19 Mauger AR, Jones AM, Williams CA. Influence of feedback and prior experience on pacing during a 4-km cycle time trial. Med Sci Sports Exerc 2009; 41: 451-458
  • 20 Mauger AR, Jones AM, Williams CA. Influence of exercise variation on the retention of a pacing strategy. Eur J Appl Physiol 2010; 108: 1015-1023
  • 21 Micklewright D, Papadopoulou E, Swart J, Noakes T. Previous experience influences pacing during 20 km time trial cycling. Br J Sports Med 2010; 44: 952-960
  • 22 Pyne D, Trewin C, Hopkins W. Progression and variability of competitive performance of Olympic swimmers. J Sports Sci 2004; 22: 613-620
  • 23 Schabort EJ, Hopkins WG, Hawley JA. Reproducibility of self-paced treadmill performance of trained endurance runners. Int J Sports Med 1998; 19: 48-51
  • 24 Sporer BC, McKenzie DC. Reproducibility of a laboratory based 20-km time trial evaluation in competitive cyclists using the Velotron Pro ergometer. Int J Sports Med 2007; 28: 940-944
  • 25 St Clair Gibson A, Lambert EV, Rauch LH, Tucker R, Baden DA, Foster C, Noakes TD. The role of information processing between the brain and peripheral physiological systems in pacing and perception of effort. Sports Med 2006; 36: 705-722
  • 26 Stewart AM, Hopkins WG. Consistency of swimming performance within and between competitions. Med Sci Sports Exerc 2000; 32: 997-1001
  • 27 Stone MR, Thomas K, Wilkinson M, St Clair Gibson A, Thompson KG. Consistency of perceptual and metabolic responses to a laboratory-based simulated 4 000-m cycling time trial. Eur J Appl Physiol 2011; 111: 1807-1813
  • 28 Thomas K, Stone MR, Thompson KG, St Clair Gibson A, Ansley L. Reproducibility of pacing strategy during simulated 20-km cycling time trials in well-trained cyclists. Eur J Appl Physiol 2012; 112: 223-229
  • 29 Tucker R. The anticipatory regulation of performance: the physiological basis for pacing strategies and the development of a perception-based model for exercise performance. Br J Sports Med 2009; 43: 392-400
  • 30 Tucker R, Noakes TD. The physiological regulation of pacing strategy during exercise: a critical review. Br J Sports Med 2009; 43: 1-9
  • 31 Ulmer HV. Concept of an extracellular regulation of muscular metabolic rate during heavy exercise in humans by psychophysiological feedback. Experientia 1996; 52: 416-420
  • 32 Vandenbogaerde TJ, Hopkins WG. Monitoring acute effects on athletic performance with mixed linear modeling. Med Sci Sports Exerc 2010; 42: 1339-1344
  • 33 Viru M, Hackney AC, Karelson K, Janson T, Kuus M, Viru A. Competition effects on physiological responses to exercise: performance, cardiorespiratory and hormonal factors. Acta Physiol Hung 2010; 97: 22-30