Pacing Profiles and Competitive Performance of Elite Female 400-m Freestyle Swimmers

J Strength Cond Res. 2020 Jan;34(1):218-224. doi: 10.1519/JSC.0000000000002187.

Abstract

Lipinska, P, and Hopkins, WG. Pacing profiles and competitive performance of elite female 400-m freestyle swimmers. J Strength Cond Res 34(1): 218-224, 2020-Pacing can impact competitive endurance performance. The objective of this study was to determine relationships between pacing parameters and competitive performance of elite female 400-m freestyle swimmers. Publicly available websites provided 50-m split and final times for 381 swims of 20 elite female swimmers in over 150 national and international competitions between 2004 and 2016. Most pacing profiles displayed negative quadratic curvature, with the fifth of the 8 laps being the median slowest. The mean times for the first and last laps were faster than predicted by the quadratic by 5.6 and 1.9%, respectively, and lap-to-lap variability was 0.65%. Scatter plots of each swimmer's final time often showed no obvious relationships with their pacing parameters, suggesting that swimmers compensated for changes in one parameter with changes in another. However, some plots showed a U shape or linear trend that allowed tentative identification of optimum values of the pacing parameters. In these plots, it was apparent that about half the swimmers might make small to moderate improvements (up to ∼1%) by changing the slope or curvature of their pacing profile or by changing time in the first or last laps. This approach for characterizing pacing profiles to identify possible improvements might be appropriate to assess pacing in other sports with multiple laps, frequent competitions, and relatively constant environmental conditions.

MeSH terms

  • Adolescent
  • Adult
  • Athletic Performance / physiology
  • Athletic Performance / statistics & numerical data*
  • Competitive Behavior
  • Female
  • Humans
  • Physical Endurance
  • Swimming / physiology
  • Swimming / statistics & numerical data*
  • Time Factors
  • Young Adult