Evidence map›Paper›PMID 31803067›Full record

ArticleFrontiers in physiology2019

Match and Training Load Exposure and Time-Loss Incidence in Elite Rugby Union Players.

Ben E W Cousins, John G Morris, Caroline Sunderland, Anthony M Bennett, Golnaz Shahtahmassebi, Simon B Cooper

Abstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 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

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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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  9. Session-RPE for quantifying workload in olympic curling athletes.Frontiers in sports and active living · 2025
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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

6 authors.

Ben E W CousinsSport Performance Research Group, Sport Science Department, Nottingham Trent University, Nottingham, United Kingdom.
John G MorrisSport Performance Research Group, Sport Science Department, Nottingham Trent University, Nottingham, United Kingdom.
Caroline SunderlandSport Performance Research Group, Sport Science Department, Nottingham Trent University, Nottingham, United Kingdom.
Anthony M BennettApplied Sports, Technology, Exercise and Medicine Research Centre (A-STEM), College of Engineering, Swansea University, Swansea, United Kingdom.
Golnaz ShahtahmassebiDepartment of Physics and Mathematics, Nottingham Trent University, Nottingham, United Kingdom.
Simon B CooperSport Performance Research Group, Sport Science Department, Nottingham Trent University, Nottingham, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the impact of match and training load on time-loss incidence in elite, professional Rugby Union players. MATERIALS AND

methodsEighty-nine Rugby Union players were monitored over two seasons of training and competition. Load was measured for all training sessions and matches using subjective [session ratings of perceived exertion (sRPE) load; RPE × session duration] and objective [global positioning systems (GPS); distance and high-speed running distance] methods and quantified using multiple approaches; absolute match and training load, acute:chronic workload ratio (ACWR), exponentially weighted moving average (EWMA) and cumulative 7, 14, 21, and 28 d sums. Mixed effect models were used to assess the effect of each variable on time-loss incidence.

resultsOf the 474 time-loss incidences that occurred across the two seasons, 50.0% were contact injuries (86.5% occurred during matches and 13.5% during training), 34.8% were non-contact injuries (31.5% occurred during matches and 68.5% during training) and 15.2% were cases of illness. The absolute match and training load variables provided the best explanation of the variance in time-loss incidence occurrence [sRPE load:

conclusionOverall, the absolute sRPE load variable best explained the variance in time-loss incidence, followed by absolute distance and absolute high-speed running distance. Whilst the model fit using the EWMA approach was not as good as the absolute load variables, it was better than when the same variables were calculated using the ACWR method. Overall, these findings suggest that the absolute match and training load variables provide the best predictors of time-loss incidence rates, with sRPE load likely to be the optimal variant of those examined here.

Indexed as

acute:chronic workload ratioexponentially weighted moving averageGPSmixed effect modelsmonitoringRPE

Identifiers

PMID31803067
PMCPMC6877544

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.