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A Standardized Small Sided Game Can Be Used to Monitor Neuromuscular Fatigue in Professional A-League Football Players

Overview of attention for article published in Frontiers in Physiology, August 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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53 X users

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174 Mendeley
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Title
A Standardized Small Sided Game Can Be Used to Monitor Neuromuscular Fatigue in Professional A-League Football Players
Published in
Frontiers in Physiology, August 2018
DOI 10.3389/fphys.2018.01011
Pubmed ID
Authors

Amber E. Rowell, Robert J. Aughey, Jo Clubb, Stuart J. Cormack

Abstract

Introduction: Training and competition load can cause neuromuscular fatigue (NMF) and modified movement strategy such as an increase in the contribution of the medio-lateral [PlayerLoadTMML(%)] and decrease in the % vertical [PlayerLoadTMV(%)] vectors, to total PlayerLoadTM (accelerometer derived measurement in vertical, medio-lateral, and anterior-posterior planes) in matches. NMF assessment involves expensive equipment, however, given the modification of match movement strategy with NMF, this may be present in a standardized drill. The aim of this study was to determine the utility of a small sided game (SSG) for the measurement of NMF. Materials and Methods: Data was collected throughout a competitive football season. External load was quantified using global positioning system (GPS) and accelerometry, and internal load by session rating of perceived exertion (sRPE). A 5 vs. 5 SSG and countermovement jump (CMJ), for determination of flight time:contraction time (FT:CT), were performed the day prior to each match. Weekly volume from GPS, PlayerLoadTM and sRPE were calculated across the season. Weekly SSG activity profile and FT:CT was compared between "high" and "low" load weeks determined relative to season average. SSG activity profile was assessed between weeks where FT:CT was above or below pre-season baseline. Impact on match activity profile was examined between weeks where FT:CT and SSG activity profile were higher or lower than baseline. The difference (high vs. low load and < or > pre-season baseline) was calculated using the effect size (ES) ± 90% CI and practically important if there was a >75% likelihood of exceeding an ES of 0.2. Results: All weekly load metrics increased SSG PlayerLoadTM⋅m⋅min-1 when above season average, however, the impact on FT:CT was trivial. Reduced weekly FT:CT compared to baseline resulted in lower SSG PlayerLoadTM⋅min-1 and PlayerLoadTMSlow⋅min-1. FT:CT below baseline increased match PlayerLoadTMML(%) and decreased PlayerLoadTMV(%) during subsequent match play. Similarly, a reduction in SSG PlayerLoadTM⋅m⋅min-1 was followed by increased match PlayerLoadTMML(%). Conclusion: Changes in select match activity profile variables following a reduction in SSG PlayerLoadTM m.min-1, mirror those seen when FT:CT is reduced. Increased PlayerLoadTMML(%) during matches likely represents fatigue driven modification to movement strategy. Small-sided games may be a useful tool to detect NMF.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 174 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 17%
Student > Master 28 16%
Researcher 12 7%
Student > Bachelor 11 6%
Other 10 6%
Other 35 20%
Unknown 49 28%
Readers by discipline Count As %
Sports and Recreations 97 56%
Computer Science 5 3%
Medicine and Dentistry 5 3%
Nursing and Health Professions 3 2%
Agricultural and Biological Sciences 3 2%
Other 5 3%
Unknown 56 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 33. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 January 2022.
All research outputs
#1,274,001
of 26,205,030 outputs
Outputs from Frontiers in Physiology
#691
of 15,781 outputs
Outputs of similar age
#25,726
of 344,199 outputs
Outputs of similar age from Frontiers in Physiology
#39
of 489 outputs
Altmetric has tracked 26,205,030 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,781 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 344,199 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 489 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.