Edel, L. (Lars) (2019) Predicting well-being and heart rate variability in male professional soccer: the role of short-term and long-term preceding loads. thesis, Sport Sciences.
Full text available on request.Abstract
Background: Understanding the dose-response relationship in professional soccer is important to manage training load. Current research included well-being and heart rate variability (HRV) to assess outcome of training and match load. These studies mostly focused on short-term relations accumulated over the preceding 7 days. Longer timeframes of load and combinations of timeframes are not investigated yet, but could provide a better understanding of the dose-response relationship. Purpose: Therefore, the aims of this study were to investigate the relationships between load with well-being and HRV in professional soccer players. In addition, the role of single and combinations of short-term and long-term timeframes was assessed. Methods: 26 professional soccer players participated in this observational study. Training and match load were monitored over 9 months, using a Global Positioning System (GPS) and session Rating of Perceived Exertion (sRPE). Players completed a daily well-being questionnaire that consisted of the following 5 items; fatigue, stress, sleep quality, muscle soreness and stress (Modified Borg 0-10 scale, good to poor). In addition, weekly HRV measurements were taken over a period of 10 weeks using a forced breathing protocol. Machine learning was used to predict well-being and HRV using different single timeframes (1, 7 and 30 days) and combinations of timeframes (1+7, 1+30, 7+30, 1+7+30) of preceding load. Results: The mean scores for well-being were: fatigue (3.0), stress (1.3), sleep quality (3.2), muscle soreness (2.8) and mood (3.4). The mean score for HRV was 141.2 Root mean square of successive differences (RMSSD). Fatigue was best predicted using the previous day load. Muscle soreness was best predicted using the previous day load or any combination where the previous day load was included. Sleep quality was best predicted using the combination over 7 and 30 days. Stress was best predicted using load over 30 days or the combination of load over 1 and 30 days. These relations all had small effect sizes. Mood and HRV could not be predicted based on preceding loads. Conclusions: Preceding load over short timeframes are important to understand fatigue and muscle soreness in professional soccer players. Preceding load over longer timeframes are related to stress and sleep quality. Keywords: Individual predictive modelling; Wellness; Daily monitoring; Response to training; Training outcome
| Item Type: | Thesis (UNSPECIFIED) |
|---|---|
| Supervisor name: | Brink, dr. M.S. and Brauers, J. and Oosterveld, dr. F.G.J. |
| Faculty: | Medical Sciences |
| Date Deposited: | 16 May 2022 09:56 |
| Last Modified: | 16 May 2022 09:56 |
| URI: | https://umcg.studenttheses.ub.rug.nl/id/eprint/3344 |
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