A Novel Method to Characterize the Pacing Profile of Elite Male 1500-m Freestyle Swimmers

in International Journal of Sports Physiology and Performance
Restricted access

Purchase article

USD  $24.95

Student 1 year online subscription

USD  $112.00

1 year online subscription

USD  $149.00

Student 2 year online subscription

USD  $213.00

2 year online subscription

USD  $284.00

Purpose: Pacing, or the distribution of energy expenditure, is particularly important in swimming; however, there is limited research examining pacing profiles in long-distance freestyle events. This study aimed to characterize the pacing profiles of elite male 1500-m freestyle swimmers using a novel method to provide a detailed analysis of different race segments. Methods: The race data for 327 male 1500-m freestyle long-course races between 2010 and 2019 were analyzed retrospectively. The raw 50-m split times for each lap were converted to a percentage of overall race time. The races were classified as a fast-, average-, or slow-start strategy (laps 1–2); as an even, negative, or positive pacing strategy (laps 3–28); and as a fast-, average-, or slow-finish strategy (laps 29–30) to give an overall pacing profile. Results: Slow- and average-start strategies were associated with faster overall 1500-m times than a fast-start strategy (mean = −21.2 s; 90% confidence interval, −11.4 to −32.3 s, P = .00). An even pacing strategy in laps 3 to 28 yielded faster overall 1500-m times than a positive pacing strategy (−8.4 s, −3.9 to −13.0 s, P = .00). The overall 1500-m times did not differ substantially across the finish strategies (P = .99). The start strategy differed across age groups and nationalities, where younger swimmers and swimmers from Australia and Great Britain typically spent a lower percentage of race time in laps 1 to 2 (faster start strategy; −0.10%, −0.01% to −0.23%, P ≤ .02). Conclusion: Adopting a relatively slower start strategy helps conserve energy for the latter stages of a 1500-m freestyle race.

McGibbon and Pyne are with the University of Canberra Research Inst for Sport and Exercise, University of Canberra, Bruce, ACT, Australia. McGibbon is also with the Queensland Academy of Sport, Nathan, QLD, Australia. Heidenreich is with the University of the Sunshine Coast, Sippy Downs, QLD, Australia. Pla is with the Fédération Française de Natation, Clichy, France; Laboratory Sport, Expertise and Performance (EA 7370),  Research Dept, French Inst of Sport (INSEP), Paris, France; and the Inst de Recherche Biomédicale et d’Epidémiologie du Sport (EA7329), Paris, France.

McGibbon (katie.mcgibbon@canberra.edu.au) is corresponding author.
  • 1.

    Abbiss CR, Laursen PB. Describing and understanding pacing strategies during athletic competition. Sports Med. 2008;38(3):239252. PubMed ID: 18278984 doi:.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    McGibbon KE, Pyne DB, Shephard ME, Thompson KG. Pacing in swimming: a systematic review. Sports Med. 2018;48(7):16211633. PubMed ID: 29560605 doi:.

  • 3.

    Skorski S, Faude O, Caviezel S, Meyer T. Reproducibility of pacing profiles in elite swimmers. Int J Sport Physiol Perform. 2014;9(2):217225. PubMed ID: 23689199 doi:.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Skorski S, Faude O, Rausch K, Meyer T. Reproducibility of pacing profiles in competitive swimmers. Int J Sports Med. 2013;34(2):152157. PubMed ID: 22972249 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Nikolaidis PT, Kach I, Rosemann T, Knechtle B. The role of nationality on the pacing of ironman triathletes. Asian J Sports Med. 2017;8(4):e57130.

    • Search Google Scholar
    • Export Citation
  • 6.

    Lipin´ska P. Kinematic tactics in the women’s 800 m freestyle swimming final at the Beijing 2008 Olympic games. Balt J Health Phys Act. 2009;1(1):8692.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Lipin´ska P, Allen SV, Hopkins WG. Modeling parameters that characterise pacing of elite female 800-m freestyle swimmers. Eur J Sport Sci. 2016;16(3):287292. PubMed ID: 25703479 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Lipin´ska P, Allen SV, Hopkins WG. Relationships between pacing parameters and performance of elite male 1500-m swimmers. Int J Sport Physiol Perform. 2016;11(2):159163. PubMed ID: 26114929 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    de Oliveira GT, Werneck FZ, Coelho EF, Simim MAdM, Penna EM, Ferreira RM. What pacing strategy 800 m and 1500 m swimmers use? [published online ahead of print August 8, 2019]. Rev Bras Cineantropom Desempenho Hum. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Thompson KG. Pacing—Individual Strategies for Optimal Performance. Champaign, IL: Human Kinetics; 2015.

  • 11.

    Barbosa TM, Bragada JA, Reis VM, Marinho DA, Carvalho C, Silva AJ. Energetics and biomechanics as determining factors of swimming performance: updating the state of the art. J Sci Med Sport. 2010;13(2):262269. PubMed ID: 19409842 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Thompson KG, MacLaren DP, Lees A, Atkinson G. The effect of even, positive and negative pacing on metabolic, kinematic and temporal variables during breaststroke swimming. Eur J Appl Physiol. 2003;88(4–5):438443. PubMed ID: 12527975 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    McGibbon KE, Shephard ME, Osborne MA, Thompson K, Pyne DB. Pacing and performance in swimming: differences between individual and relay events. Int J Sport Physiol Perform. 2020;15(8):10591066. PubMed ID: 32283539 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Foster C, Schrager M, Snyder AC, Thompson NN. Pacing strategy and athletic performance. Sports Med. 1994;17(2):7785. PubMed ID: 8171225 doi:

  • 15.

    Mitchell LJG, Rattray B, Saunders PU, Pyne DB. The relationship between talent identification testing parameters and performance in elite junior swimmers. J Sci Med Sport. 2018;21(12):12811285. PubMed ID: 29804652 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Bates D, Maechler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Softw. 2015;67(1):148. doi:

  • 17.

    R Core Group. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2013.

  • 18.

    Bretz F, Hothorn T., Westfall P. Multiple Comparisons Using R. New York: Chapman and Hall; 2011.

  • 19.

    Pyne DB, Trewin CB, Hopkins WG. Progression and variability of competitive performance of Olympic swimmers. J Sports Sci. 2004;22(7):613620. PubMed ID: 15370491 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Bishop D, Bonetti D, Dawson B. The influence of pacing strategy on VO2 and supramaximal kayak performance. Med Sci Sports Exerc. 2002;34(6):10411047. PubMed ID: 12048335 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Mattern CO, Kenefick RW, Kertzer R, Quinn TJ. Impact of starting strategy on cycling performance. Int J Sports Med. 2001;22(5):350355. PubMed ID: 11510871 doi:

  • 22.

    Bailey SJ, Vanhatalo A, DiMenna FJ, Wilkerson DP, Jones AM. Fast-start strategy improves VO2 kinetics and high-intensity exercise performance. Med Sci Sports Exerc. 2011;43(3):457467. doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Murray J, McCrudden M, Murias JM, Nolte V, Belfry GR. Differing six minute pacing strategies affect anaerobic contribution, oxygen uptake, muscle deoxygenation and cycle performance. J Sports Med Phys Fit. 2018;58(1–2):1726. PubMed ID: 27991483 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24.

    Hausswirth C, Le Meur Y, Bieuzen F, Brisswalter J, Bernard T. Pacing strategy during the initial phase of the run in triathlon: influence on overall performance. Eur J Appl Physiol. 2010;108(6):11151123. PubMed ID: 20024576 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Garland SW. An analysis of the pacing strategy adopted by elite competitors in 2000 m rowing. Br J Sports Med. 2005;39(1):3942. PubMed ID: 15618339 doi:

  • 26.

    Skorski S, Faude O, Abbiss CR, Caviezel S, Wengert N, Meyer T. Influence of pacing manipulation on performance of juniors in simulated 400-m swim competition. Int J Sport Physiol Perform. 2014;9(5):817824. PubMed ID: 24434079 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27.

    Mytton GJ, Archer DT, Turner L, et al. Increased variability of lap speeds: differentiating medalists and nonmedalists in middle-distance running and swimming events. Int J Sport Physiol Perform. 2015;10(3):369373. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28.

    Skorski S, Abbiss C. The manipulation of pace within endurance sport. Front Physiol. 2017;8:102. PubMed ID: 28289392 doi:

  • 29.

    Menting SGP, Konings MJ, Elferink-Gemser MT, Hettinga FJ. Pacing behavior of elite youth athletes: Analyzing 1500-m short-track speed skating. Int J Sport Physiol Perform. 2019;14(2):222231. PubMed ID: 30039992 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 768 768 145
Full Text Views 24 24 1
PDF Downloads 19 19 0