Testing and Profiling Athletes: Recommendations for Test Selection, Implementation, and Maximizing Information

Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.

To examine the physiological response and reproducibility of the Yo-Yo intermittent recovery test and its application to elite soccer. Heart rate was measured, and metabolites were determined in blood and muscle biopsies obtained before, during, and after the Yo-Yo test in 17 males. Physiological measurements were also performed during a Yo-Yo retest and an exhaustive incremental treadmill test (ITT). Additionally, 37 male elite soccer players performed two to four seasonal tests, and the results were related to physical performance in matches. The test-retest CV for the Yo-Yo test was 4.9%. Peak heart rate was similar in ITT and Yo-Yo test (189 +/- 2 vs 187 +/- 2 bpm), whereas peak blood lactate was higher (P < 0.05) in the Yo-Yo test. During the Yo-Yo test, muscle lactate increased eightfold (P < 0.05) and muscle creatine phosphate (CP) and glycogen decreased (P < 0.05) by 51% and 23%, respectively. No significant differences were observed in muscle CP, lactate, pH, or glycogen between 90 and 100% of exhaustion time. During the precompetition period, elite soccer players improved (P < 0.05) Yo-Yo test performance and maximum oxygen uptake ([OV0312]O(2max)) by 25 +/- 6 and 7 +/- 1%, respectively. High-intensity running covered by the players during games was correlated to Yo-Yo test performance (r = 0.71, P < 0.05) but not to [OV0312]O(2max) and ITT performance. The test had a high reproducibility and sensitivity, allowing for detailed analysis of the physical capacity of athletes in intermittent sports. Specifically, the Yo-Yo intermittent recovery test was a valid measure of fitness performance in soccer. During the test, the aerobic loading approached maximal values, and the anaerobic energy system was highly taxed. Additionally, the study suggests that fatigue during intense intermittent short-term exercise was unrelated to muscle CP, lactate, pH, and glycogen.