Purpose: To assess the short-term reliability of measurement instruments to quantify the acute psychophysiological response to load in adolescent soccer players in relation to biological maturity. Methods: Data were collected from 108 U12 to U17 soccer players on 2 consecutive weeks (pre, n = 32; at, n = 34; and post, n = 42 estimated peak height velocity). Measurements consisted of the Short Recovery and Stress Scale, a countermovement jump, assessment of leg stiffness, and a submaximal run to assess exercise heart rate and heart rate recovery. Test–retest reliability was assessed with the coefficient of variation (CV) and intraclass correlation coefficient (ICC). Results: Items of the Short Recovery and Stress Scale showed poor reliability across maturity groups (CV = 7.0%–53.5%; ICC = .28 to .79). Only few countermovement jump variables (jump height, concentric impulse, and concentric velocity) possessed good reliability. For most variables of the countermovement jump, reliability was better for the post peak height velocity group followed by at-peak height velocity and prepeak height velocity. Very high levels of reliability across maturity groups were observed for exercise heart rate (CV < 1.8%; ICC > .94), while heart rate recovery was more variable (CV < 16.5%; ICC > .48). Conclusion: Results suggest that the majority of investigated variables have poor reliability, questioning their ability to detect small, yet meaningful changes in acute responses to load in adolescent soccer players.

While sample sizes in elite sports are necessarily small, so are the effects that may be relevant. This conundrum is complicated by an understandable reluctance of athletes to comply with extensive study requirements. In Bayesian analyses, pre-existing knowledge (e.g., from sub-elite trials) can be formally included to supplement scarce data. Moreover, some design specifics for small sample research extend to the extreme case of a single subject. This provides the basis for actionable feedback (e.g., about individual responses) thereby incentivising participation. As a proof-of-concept, we conducted a replicated cross-over trial on the effect of cold-water immersion (CWI) on sprint performance recovery in soccer players. Times for 30 m linear sprint and the initial 5 m section, respectively, were measured by light gates before and 24 h after induction of fatigue. Data were analysed by Bayesian and by standard frequentist methods. Informative priors are based on a published metaanalysis. Seven players completed the trial. Sprint performance was 4.156 ± 0.193 s for 30 m linear sprint and 0.978 ± 0.064 s for the initial 5 m section. CWI improved recovery of sprint time for the initial 5 m section (difference to control: −0.060 ± 0.060 s, p = 0.004) but not for the full 30 m sprint (0.002 ± 0.115 s, p = 0.959), with general agreement between Bayesian and frequentist interval estimates. On the individual level, relevant differences between analytical approaches were present for most players. Changes in the two performance measures are correlated (p = 0.009) with a fairly good reproducibility of individual response patterns. Bayesian analyses with informative priors may be a practicable and meaningful option particularly for very small samples and when the analytical aim is decision making (use / don't use in the specific setting) rather than generalizable inference.

To analyse the association of seasonal best time, distance and different performance levels with end-spurt behaviour in one swimming season. Race results in 800 and 1500 m pool freestyle swimming in the season 2018/2019 including 14,930 races and 2650 swimmers were obtained. The end-spurt for each race was determined by means of an End-Spurt Indicator (ESI). Subsequently, ESI was used as a dependent variable and influences were analysed using a linear mixed model with fixed effects for seasonal best time, distance, and performance level amongst others. In the 800 and 1500 m races swimmers showed a mean ESI of 2.08 (95% CI: 2.02-2.13) and 3.68 (95% CI: 3.59-3.76), respectively. There was a significant association between seasonal best time and ESI, with a better seasonal best time showing a greater ESI (F = 70.5, P < .001, f 2 = 0.04). A significant effect on greater ESI was also observed for longer distance (F = 1067.5, P < .001, f 2 = 0.06) and higher performance level (F = 91.1, P < .001, f 2 = 0.02). Elite swimmers had a mean ESI of 5.47 (95% CI: 4.91-6.03), sub-elite swimmers of 3.74 (95% CI: 3.53-3.95) and competitive swimmers of 2.41 (95% CI: 2.37-2.46). A more pronounced end-spurt is associated with seasonal best time in long-distance pool swimming, higher performance level of the swimmer and longer race distance.