Evidence map›Paper›PMID 39305464›Full record

ArticleEuropean journal of sport science2024

The application of match-event and instrumented mouthguard data to inform match limits: An example using rugby union Premiership and rugby league Super League data from England.

Thomas Sawczuk, Matt Cross, Cameron Owen, Gregory Roe, Keith Stokes, Simon Kemp, James Tooby, David Allan, Éanna Falvey, Lindsay Starling and 3 more

Abstract read
In one paragraph

Article in European journal of sport science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

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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

13 authors.

Thomas SawczukCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
Matt CrossCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
Cameron OwenCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
Gregory RoeCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.ORCID https://orcid.org/0000-0003-1428-9282
Keith StokesRugby Football Union, Twickenham, UK.
Simon KempRugby Football Union, Twickenham, UK.
James ToobyCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
David AllanSport and Exercise Sciences Research Institute, Ulster University, Belfast, UK.
Éanna FalveyWorld Rugby, Dublin, Ireland.
Lindsay StarlingCentre for Health and Injury and Illness Prevention in Sport, University of Bath, Bath, UK.
Gregory TierneyCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
Ross TuckerWorld Rugby, Dublin, Ireland.
Ben JonesCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.

Funding

Premiership Rugby
6 · The paper itself

Abstract

The study aimed to illustrate how contact (from match-event data) and head acceleration event (HAE) (from instrumented mouthguard [iMG]) data can be combined to inform match limits within rugby. Match-event data from one rugby union and rugby league season, including all competitive matches involving players from the English Premiership and Super League, were used. Playing exposure was summarised as full game equivalents (FGE; total minutes played/80). Expected contact and HAE exposures at arbitrary thresholds were estimated using match-event and iMG data. Generalised linear models were used to identify differences in contact and HAE exposure per FGE. For 30 FGEs, forwards had greater contact than backs in rugby union (n = 1272 vs. 618) and league (n = 1569 vs. 706). As HAE magnitude increased, the differences between positional groups decreased (e.g., rugby union; n = 34 and 22 HAE >40 g for forwards and backs playing 30 FGEs). Currently, only a relatively small proportion of rugby union (2.5%) and league (7.3%) players exceeded 25 FGEs. Estimating contact and HAEs per FGE allows policymakers to prospectively plan and model estimated overall and position-specific loads over a season and longer term. Reducing FGE limits by a small amount would currently only affect contact and HAE exposure for a small proportion of players who complete the most minutes. This may be beneficial for this cohort but is not an effective HAE and contact exposure reduction strategy at a population level, which requires individual player management. Given the positional differences, FGE limits should exist to manage appropriate HAE and contact exposure.

Indexed as

AccelerationFootballMouth ProtectorsAthletic InjuriesCompetitive BehaviorEnglandHeadHumansathlete welfarecollision sportplayer monitoringpolicy

Identifiers

PMID39305464
PMCPMC11534626

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.