Reliability of biomechanical variables of sprint running

Med Sci Sports Exerc. 2004 May;36(5):850-61. doi: 10.1249/01.mss.0000126467.58091.38.

Abstract

Purpose: The purpose of this paper was to report the reliability of variables used in the biomechanical assessment of sprint running and to document how these reliability measures are likely to improve when using the average score of multiple trials.

Methods: Twenty-eight male athletes performed maximal-effort sprints. Video and ground reaction force data were collected at the 16-m mark. The reliability (systematic bias, random error, and retest correlation) for a single score was calculated for 26 kinematic and 7 kinetic variables. In addition, the reliability (random error and retest correlation) for the average score of 2, 3, 4, and 5 trials was predicted from the reliability of a single score.

Results: For all variables, there was no evidence of systematic bias. The measures of random error and retest correlation differed widely among the variables. Variables describing horizontal velocity of the body's center of mass were the most reliable, whereas variables based on vertical displacement of the body's center of mass or braking ground reaction force were the least reliable. For all variables, reliability improved notably when the average score of multiple trials was the measurement of interest.

Conclusion: Although it is up to the researcher to judge whether a measurement is reliable enough for its intended use, some of the lower-reliability variables were possibly too unreliable to monitor small changes in an athlete's performance. Nonetheless, there was a consistent trend for reliability to improve notably when the average score of multiple trials was the measurement of interest. Subsequently, if resources permit, researchers and applied sports-scientists may like to consider using the average score of multiple trials to gain the advantages that improved reliability offers.

MeSH terms

  • Adult
  • Analysis of Variance
  • Biomechanical Phenomena
  • Data Collection / methods
  • Humans
  • Male
  • Reproducibility of Results
  • Running / physiology*
  • Signal Processing, Computer-Assisted