Validity, reliability and sensitivity of measures of sporting performance

Sports Med. 2008;38(4):297-316. doi: 10.2165/00007256-200838040-00003.


Performance testing is one of the most common and important measures used in sports science and physiology. Performance tests allow for a controlled simulation of sports and exercise performance for research or applied science purposes. There are three factors that contribute to a good performance test: (i) validity; (ii) reliability; and (iii) sensitivity. A valid protocol is one that resembles the performance that is being simulated as closely as possible. When investigating race-type events, the two most common protocols are time to exhaustion and time trials. Time trials have greater validity than time to exhaustion because they provide a good physiological simulation of actual performance and correlate with actual performance. Sports such as soccer are more difficult to simulate. While shuttle-running protocols such as the Loughborough Intermittent Shuttle Test may simulate physiology of soccer using time to exhaustion or distance covered, it is not a valid measure of soccer performance. There is a need to include measures of skill in such protocols. Reliability is the variation of a protocol. Research has shown that time-to-exhaustion protocols have a coefficient of variation (CV) of >10%, whereas time trials are more reliable as they have been shown to have a CV of <5%. A sensitive protocol is one that is able to detect small, but important, changes in performance. The difference between finishing first and second in a sporting event is <1%. Therefore, it is important to be able to detect small changes with performance protocols. A quantitative value of sensitivity may be accomplished through the signal : noise ratio, where the signal is the percentage improvement in performance and the noise is the CV.

Publication types

  • Review

MeSH terms

  • Athletic Performance / physiology*
  • Athletic Performance / standards*
  • Athletic Performance / statistics & numerical data
  • Ergometry / methods*
  • Humans
  • Muscle Fatigue / physiology
  • Physical Exertion / physiology
  • Reproducibility of Results
  • Sensitivity and Specificity