Evidence map›Paper›PMID 27459866›Full record

SynthesisSports medicine (Auckland, N.Z.)2017

Relationships Between Training Load Indicators and Training Outcomes in Professional Soccer.

Arne Jaspers, Michel S Brink, Steven G M Probst, Wouter G P Frencken, Werner F Helsen

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Sports medicine (Auckland, N.Z.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 7 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

70 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Metabolomics analyses and physical interventions in soccer: a systematic review.Metabolomics : Official journal of the Metabolomic Society · 2024
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  5. Monitoring Accumulated Training and Match Load in Football: A Systematic Review.International journal of environmental research and public health · 2021
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10 more citing papers are in PubMed but not listed here.

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

5 authors.

Arne JaspersDepartment of Kinesiology, Laboratory of Perception and Performance, Movement Control and Neuroplasticity Research Group, University of Leuven (KU Leuven), Leuven, Belgium. arne.jaspers@kuleuven.be.ORCID http://orcid.org/0000-0001-6809-0792
Michel S BrinkCenter for Human Movement Sciences, University of Groningen, University Medical Center, Groningen, The Netherlands.
Steven G M ProbstDepartment of Kinesiology, Laboratory of Perception and Performance, Movement Control and Neuroplasticity Research Group, University of Leuven (KU Leuven), Leuven, Belgium.
Wouter G P FrenckenCenter for Human Movement Sciences, University of Groningen, University Medical Center, Groningen, The Netherlands.
Werner F HelsenDepartment of Kinesiology, Laboratory of Perception and Performance, Movement Control and Neuroplasticity Research Group, University of Leuven (KU Leuven), Leuven, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn professional senior soccer, training load monitoring is used to ensure an optimal workload to maximize physical fitness and prevent injury or illness. However, to date, different training load indicators are used without a clear link to training outcomes.

objectiveThe aim of this systematic review was to identify the state of knowledge with respect to the relationship between training load indicators and training outcomes in terms of physical fitness, injury, and illness.

methodsA systematic search was conducted in four electronic databases (CINAHL, PubMed, SPORTDiscus, and Web of Science). Training load was defined as the amount of stress over a minimum of two training sessions or matches, quantified in either external (e.g., duration, distance covered) or internal load (e.g., heart rate [HR]), to obtain a training outcome over time.

resultsA total of 6492 records were retrieved, of which 3304 were duplicates. After screening the titles, abstracts and full texts, we identified 12 full-text articles that matched our inclusion criteria. One of these articles was identified through additional sources. All of these articles used correlations to examine the relationship between load indicators and training outcomes. For pre-season, training time spent at high intensity (i.e., >90 % of maximal HR) was linked to positive changes in aerobic fitness. Exposure time in terms of accumulated training, match or combined training, and match time showed both positive and negative relationships with changes in fitness over a season. Muscular perceived exertion may indicate negative changes in physical fitness. Additionally, it appeared that training at high intensity may involve a higher injury risk. Detailed external load indicators, using electronic performance and tracking systems, are relatively unexamined. In addition, most research focused on the relationship between training load indicators and changes in physical fitness, but less on injury and illness.

conclusionHR indicators showed relationships with positive changes in physical fitness during pre-season. In addition, exposure time appeared to be related to positive and negative changes in physical fitness. Despite the availability of more detailed training load indicators nowadays, the evidence about the usefulness in relation to training outcomes is rare. Future research should implement continuous monitoring of training load, combined with the individual characteristics, to further examine their relationship with physical fitness, injury, and illness.

Indexed as

Physical Education and TrainingPhysical FitnessSoccerWorkloadHeart RateHumansSeasons

Identifiers

What OpenQuestion holds

Textmetadata
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.