Minimal Number of Events Required for Acceleration–Speed Profiling in Elite Women's Soccer.

Cormier, Patrick; Tsai, Ming-Chang; Meylan, Cesar; Soares, Victor H.T.; Clarke, David C.; Klimstra, Marc

Purpose: To determine the minimum number of events (training or matches) for producing valid acceleration–speed (AS) profiles from global navigation satellite system (GNSS) data. Methods: Nine elite female soccer players participated in a 4-week training camp consisting of 19 events. AS profile metrics calculated from different combinations of athlete events were compared to force–velocity (FV) profile metrics from 2 × 40-m stand-alone sprint effort trials, using the same GNSS 10-Hz technology. Force–velocity profiles were calculated, from which AS profiles were obtained. AS profiles from training and matches were generated by plotting acceleration and speed points and performing a regression through the maximal points to obtain the AS metrics (theoretical maximal speed, x-intercept [in meters per second], theoretical maximal acceleration, y-intercept [in meters per second squared], and the slope per second). A linear mixed model was performed with the AS metrics as the outcome variables, the number of events as a fixed effect, and the participant identifier as a mixed effect. Dunnett post hoc multiple comparisons were used to compare the means of each number of event grouping (1–19 events) to those estimated from the dedicated sprint test. Results: Theoretical maximal speed and theoretical maximal acceleration means were no longer significantly different from the isolated sprint reference with 9 to 19 (small to trivial differences = −0.31 to −0.04 m·s−1, P =.12–.99) and 6 to 19 (small differences = −0.4 to −0.28 m·s−2, P =.06–.79) events, and the slopes were no longer different with 1 to 19 events (trivial differences = 0.06–0.03 s−1, P =.35–.99). Conclusions: AS profiles can be estimated from a minimum of 9 days of tracking data. Future research should investigate methodology resulting in AS profiles estimated from fewer events.

CANADA; SOCCER; GEOGRAPHIC information systems; STATISTICS; CONFIDENCE intervals; PHYSICAL training & conditioning; REGRESSION analysis; PHYSIOLOGICAL effects of acceleration; EXERCISE intensity; INTRACLASS correlation; DESCRIPTIVE statistics; RESEARCH funding; ATHLETIC ability; STATISTICAL models; DATA analysis; DATA analysis software; SPRINTING

International Journal of Sports Physiology & Performance, 2023, Vol 18, Issue 12, p1457

1555-0265

Academic Journal

10.1123/ijspp.2023-0223