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Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis

Karim Hader, Michael C. Rumpf, Maxime Hertzog, Liam Kilduff Orcid Logo, Olivier Girard, Joao R. Silva Orcid Logo

Sports Medicine - Open, Volume: 5, Issue: 1

Swansea University Author: Liam Kilduff Orcid Logo

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Abstract

Background: Monitoring athletes’ external load during a soccer match may be useful to predict post-match acute and residual fatigue. This estimation would allow individual adjustments to training programs to minimize injury risk, improve well-being, and restore players’ physical performance and info...

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Published in: Sports Medicine - Open
ISSN: 2199-1170 2198-9761
Published: Springer Science and Business Media LLC 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa52384
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spelling 2023-03-14T11:05:22.1131733 v2 52384 2019-10-09 Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis 972ed9a1dda7a0de20581a0f8350be98 0000-0001-9449-2293 Liam Kilduff Liam Kilduff true false 2019-10-09 STSC Background: Monitoring athletes’ external load during a soccer match may be useful to predict post-match acute and residual fatigue. This estimation would allow individual adjustments to training programs to minimize injury risk, improve well-being, and restore players’ physical performance and inform the recovery process.Methods: Using a systematic review and meta-analysis of the literature, the aim is to determine which monitoring variables would be the strongest predictors of acute (immediately) and residual (up to 72 h) fatigue states in soccer. PubMed, SPORTDiscus, and Web of Science databases were searched (until September 2018). Studies concurrently examining soccer match-related external load metrics and subjective and/or objective measures were selected to determine pooled correlations (r) with confidence intervals (CI). The quality and strength of the findings of eachstudy were evaluated to identify overall levels of evidence.Results: Eleven studies were included (n = 165 athletes). Acute (r = 0.67; 95% CI = [0.40, 0.94]) and residual (24 h post-match, r = 0.54; 95% CI = [0.35, 0.65]) changes in muscle damage markers and countermovement jump peak power output (CMJPPO) were, with moderate to strong evidence, largely correlated with running distance above 5.5 m s−1. No other external load metric was largely correlated with both biochemical and neuromuscular markers. For every 100-m run above 5.5 m·s−1, CK activity measured 24 h post-match increased by 30% and CMJPPO decreased by 0.5%. Conversely, the total distance covered did not present any evidence of a clear relationship with anyfatigue-related marker at any time-point.Conclusions: Running distance above 5.5 m·s−1 represents the most sensitive monitoring variable characterizing biochemical and neuromuscular responses, at least when assessed during the initial 24 h (not at 48 h/72 h) postmatch recovery period. In addition, total distance covered is not sensitive enough to inform decision-making during the fatigue monitoring process. Journal Article Sports Medicine - Open 5 1 Springer Science and Business Media LLC 2199-1170 2198-9761 External load, Time motion analysis, Monitoring, Fatigue, Recovery, Muscle damage, Perceptualresponses, Neuromuscular performance 1 12 2019 2019-12-01 10.1186/s40798-019-0219-7 http://dx.doi.org/10.1186/s40798-019-0219-7 COLLEGE NANME Sport and Exercise Sciences COLLEGE CODE STSC Swansea University 2023-03-14T11:05:22.1131733 2019-10-09T10:07:27.2701620 Faculty of Science and Engineering School of Engineering and Applied Sciences - Sport and Exercise Sciences Karim Hader 1 Michael C. Rumpf 2 Maxime Hertzog 3 Liam Kilduff 0000-0001-9449-2293 4 Olivier Girard 5 Joao R. Silva 0000-0001-5637-179x 6
title Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis
spellingShingle Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis
Liam Kilduff
title_short Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis
title_full Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis
title_fullStr Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis
title_full_unstemmed Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis
title_sort Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis
author_id_str_mv 972ed9a1dda7a0de20581a0f8350be98
author_id_fullname_str_mv 972ed9a1dda7a0de20581a0f8350be98_***_Liam Kilduff
author Liam Kilduff
author2 Karim Hader
Michael C. Rumpf
Maxime Hertzog
Liam Kilduff
Olivier Girard
Joao R. Silva
format Journal article
container_title Sports Medicine - Open
container_volume 5
container_issue 1
publishDate 2019
institution Swansea University
issn 2199-1170
2198-9761
doi_str_mv 10.1186/s40798-019-0219-7
publisher Springer Science and Business Media LLC
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Sport and Exercise Sciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Sport and Exercise Sciences
url http://dx.doi.org/10.1186/s40798-019-0219-7
document_store_str 0
active_str 0
description Background: Monitoring athletes’ external load during a soccer match may be useful to predict post-match acute and residual fatigue. This estimation would allow individual adjustments to training programs to minimize injury risk, improve well-being, and restore players’ physical performance and inform the recovery process.Methods: Using a systematic review and meta-analysis of the literature, the aim is to determine which monitoring variables would be the strongest predictors of acute (immediately) and residual (up to 72 h) fatigue states in soccer. PubMed, SPORTDiscus, and Web of Science databases were searched (until September 2018). Studies concurrently examining soccer match-related external load metrics and subjective and/or objective measures were selected to determine pooled correlations (r) with confidence intervals (CI). The quality and strength of the findings of eachstudy were evaluated to identify overall levels of evidence.Results: Eleven studies were included (n = 165 athletes). Acute (r = 0.67; 95% CI = [0.40, 0.94]) and residual (24 h post-match, r = 0.54; 95% CI = [0.35, 0.65]) changes in muscle damage markers and countermovement jump peak power output (CMJPPO) were, with moderate to strong evidence, largely correlated with running distance above 5.5 m s−1. No other external load metric was largely correlated with both biochemical and neuromuscular markers. For every 100-m run above 5.5 m·s−1, CK activity measured 24 h post-match increased by 30% and CMJPPO decreased by 0.5%. Conversely, the total distance covered did not present any evidence of a clear relationship with anyfatigue-related marker at any time-point.Conclusions: Running distance above 5.5 m·s−1 represents the most sensitive monitoring variable characterizing biochemical and neuromuscular responses, at least when assessed during the initial 24 h (not at 48 h/72 h) postmatch recovery period. In addition, total distance covered is not sensitive enough to inform decision-making during the fatigue monitoring process.
published_date 2019-12-01T04:04:43Z
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score 11.037581