Comparison of acceleration-speed profiles from training and competition to individual maximal sprint efforts
This study aimed to (1) compare "in-situ" monitored acceleration-speed (ASin-situ) profile metrics from training/competition data in elite female soccer players to similar metrics from profiles developed from isolated maximal sprint efforts (ASsprint) and; (2) compare the confidence interval (CI) and a Tukey boxplot (BP) outlier removal technique on the training/competition data to derive ASin-situ profiles. Fifteen national team soccer players participated in a 4-week camp while wearing 10 Hz GNSS units. Towards the middle of the camp, 2 × 40 m isolated maximal sprints were performed. ASin-situ profiles (theoretical maximum acceleration A0 in m·s-2 and speed S0 in m·s-1) were computed using the CI and BP techniques with training/competition data. The sprint data were modelled separately to construct horizontal force-velocity (FV) profiles, from which ASsprint profiles were derived. Bland-Altman analysis was used to assess agreement between the CI- and BP-derived ASin-situ profiles to the ASsprint profiles, as well as regression analysis for systematic and proportional bias. Additionally, 1-way ANOVAs with Tukey posthoc compared the metrics between each method of analysis. Using the BP method, good agreement of the ASin-situ with ASsprint profile metrics A0/S0 was displayed, whereas good to moderate agreement was shown for the CI. The CI technique showed a proportional bias for A0/S0. Good to excellent intertrial reliability was demonstrated for isolated sprint metrics. Both BP and CI techniques provided comparable ASin-situ profiles to ASsprint profiles. This current research demonstrated that ASin-situ profiling is applicable in elite women`s soccer and will have further application in many team sports.
© Copyright 2023 Journal of Biomechanics. Elsevier. All rights reserved.
| Subjects: | |
|---|---|
| Notations: | sport games |
| Tagging: | Monitoring |
| Published in: | Journal of Biomechanics |
| Language: | English |
| Published: |
2023
|
| Online Access: | https://doi.org/10.1016/j.jbiomech.2023.111724 |
| Volume: | 157 |
| Pages: | 111724 |
| Document types: | article |
| Level: | advanced |