Evidence map›Paper›PMID 31344056›Full record

ArticlePloS one2019

Effects of a six-week period of congested match play on plasma volume variations, hematological parameters, training workload and physical fitness in elite soccer players.

Karim Saidi, Hassane Zouhal, Fatma Rhibi, Jed M Tijani, Daniel Boullosa, Amel Chebbi, Anthony C Hackney, Urs Granacher, Benoit Bideau, Abderraouf Ben Abderrahman

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  5. Load Measures in Training/Match Monitoring in Soccer: A Systematic Review.International journal of environmental research and public health · 2021
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  18. Innate immunity changes in soccer players after whole-body cryotherapy.BMC sports science, medicine & rehabilitation · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Karim SaidiMovement, Sport, Health and Sciences Laboratory (M2S), University of Rennes 2, Rennes, France.
Hassane ZouhalMovement, Sport, Health and Sciences Laboratory (M2S), University of Rennes 2, Rennes, France.ORCID 0000-0001-6743-6464
Fatma RhibiMovement, Sport, Health and Sciences Laboratory (M2S), University of Rennes 2, Rennes, France.
Jed M TijaniHigher Institute of Sport and Physical Education of Ksar-Said, University of Manouba, Tunis, Tunisia.
Daniel BoullosaCatholic University of Brasilia, Taguatinga, Brazil.
Amel ChebbiFaculty of Medicine of Tunis, University of Tunis, Tunis, Tunisia.
Anthony C HackneyDepartment of Exercise & Sport Science, University of North Carolina, Chapel Hill, NC, United States of America.
Urs GranacherDivision of Training and Movement Sciences, University of Potsdam, Potsdam, Germany.
Benoit BideauMovement, Sport, Health and Sciences Laboratory (M2S), University of Rennes 2, Rennes, France.
Abderraouf Ben AbderrahmanHigher Institute of Sport and Physical Education of Ksar-Said, University of Manouba, Tunis, Tunisia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aims of this study were to investigate the effects of a six-week in-season period of soccer training and games (congested period) on plasma volume variations (PV), hematological parameters, and physical fitness in elite players. In addition, we analyzed relationships between training load, hematological parameters and players' physical fitness.

methodsEighteen elite players were evaluated before (T1) and after (T2) a six-week in-season period interspersed with 10 soccer matches. At T1 and T2, players performed the Yo-Yo intermittent recovery test level 1 (YYIR1), the repeated shuttle sprint ability test (RSSA), the countermovement jump test (CMJ), and the squat jump test (SJ). In addition, PV and hematological parameters (erythrocytes [M/mm3], hematocrit [%], hemoglobin [g/dl], mean corpuscular volume [fl], mean corpuscular hemoglobin content [pg], and mean hemoglobin concentration [%]) were assessed. Daily ratings of perceived exertion (RPE) were monitored in order to quantify the internal training load.

resultsFrom T1 to T2, significant performance declines were found for the YYIR1 (p<0.001, effect size [ES] = 0.5), RSSA (p<0.01, ES = 0.6) and SJ tests (p< 0.046, ES = 0.7). However, no significant changes were found for the CMJ (p = 0.86, ES = 0.1). Post-exercise, RSSA blood lactate (p<0.012, ES = 0.2) and PV (p<0.01, ES = 0.7) increased significantly from T1 to T2. A significant decrease was found from T1 to T2 for the erythrocyte value (p<0.002, ES = 0.5) and the hemoglobin concentration (p<0.018, ES = 0.8). The hematocrit percentage rate was also significantly lower (p<0.001, ES = 0.6) at T2. The mean corpuscular volume, mean corpuscular hemoglobin content and the mean hemoglobin content values were not statistically different from T1 to T2. No significant relationships were detected between training load parameters and percentage changes of hematological parameters. However, a significant relationship was observed between training load and changes in RSSA performance (r = -0.60; p<0.003).

conclusionsAn intensive period of "congested match play" over 6 weeks significantly compromised players' physical fitness. These changes were not related to hematological parameters, even though significant alterations were detected for selected measures.

Indexed as

Hematologic TestsPhysical FitnessSoccerWorkloadAdipose TissueBody Mass IndexHumansMalePlasma VolumeYoung Adult

Identifiers

PMID31344056
PMCPMC6657839

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.