Critical speed and finite distance capacity: norms for athletic and non-athletic groups.

Purpose: Two parameters in particular span both health and performance; critical speed (CS) and finite distance capacity (D'). The purpose of the present study was to: (1) classify performance norms, (2) distinguish athletic from non-athletic individuals using the 3-min all-out test (3MT) for running, and (3) introduce a deterministic model highlighting the relationship between variables of the 3MT.

Methods: Athletic (n = 43) and non-athletic (n = 25) individuals participated in the study. All participants completed a treadmill graded exercise test (GXT) with verification bout and a 3MT on an outdoor sprinting track.

Results: Meaningful differences between non-athletic and athletic individuals (denoted by mean difference scores, p value and Cohen's d with 95% confidence intervals) were evident for CS (- 0.74 m s, p < 0.001, d = - 1.41 [1.97, - 0.87]), exponential growth time constant ([Formula: see text]; 2.75 s, p < 0.001, d = - 1.29 [- 1.45, - 0.42]), time to maximal speed ([Formula: see text]; - 2.80 s, p < 0.001, d = - 0.98 [- 1.51, - 0.47]), maximal speed ([Formula: see text]; - 1.36 m s, p < 0.001, d = - 1.56 [- 2.13, - 1.01]), gas exchange threshold (GET; - 5.62 ml kg min, p < 0.001, d = - 0.97 [- 1.50, - 0.45]), distance covered in the first minute (1st min; - 81.69 m, p < 0.001, d = - 1.91 [- 2.52, - 1.33]), distance covered in the second minute (2nd min; - 52.02 m, p < 0.001, d = - 1.71 [- 2.30, - 1.15]) and maximal distance (- 153.78 m, p < 0.001, d = - 1.27 [- 1.82, - 0.74]). The correlation coefficient between key physiological and performance variables are shown in the form of a deterministic model created from the data derived from the 3MT.

Conclusions: Coaches and clinicians may benefit from the use of normative data to potentially identify exceptional or irregular occurrences in 3MT performances.