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Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, CanadaO'Brien Institute for Public Health, University of Calgary, Canada
To investigate the influence of previous season match exposure on injury incidence and burden in elite men's rugby union.
Design
A three-season (2016–17 to 2018–19) retrospective cohort design was used to collect and analyse injury and exposure data across English Premiership rugby union teams.
Methods
Generalised linear mixed-effects models were used to model the influence of match exposure (all match involvements, match involvements of ≥20 mins, and full-game equivalents) upon match and training injury incidence and burden in the following season.
Results
Involvement in ≥31 matches within a season was associated with substantially increased match and training injury burden in the following season. Match exposure was not clearly associated with injury incidence in the following season. The increased match injury burden associated with higher match involvements appeared to be driven by an increased risk for older (>26 y) Forwards, whilst the increased training injury burden associated with higher match involvements appeared to be driven by an increased risk for older (>26 y) Backs.
Conclusions
The present study demonstrates that all match involvements, regardless of duration, should be considered when exploring associations between match exposure and injury risk. High match involvements (≥ 31 matches) are associated with elevated injury burden, in both matches and training, in the following season. The physical and psychological load of players with high previous-season match exposure should be carefully managed.
All match involvements, regardless of duration, should be considered when exploring associations between match exposure and injury risk.
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High match involvements (≥31 matches) during a season elevates injury burden rates in both matches and training in the following season.
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The physical and psychological load of players with high previous-season match exposure should be carefully managed.
1. Introduction
The loads experienced by professional rugby players, and their impact on player welfare, have been highlighted as a cause for concern by players, coaches, sports media, and administrators. Previous qualitative research has credited heavy playing loads and an inadequate off-season for the higher injury incidence and prevalence of burnout syndrome in professional rugby player.
A mandatory post-season rest period of five weeks and guaranteed in-season breaks for players have been introduced to the English Premiership to help alleviate this.
Around the world, elite male rugby players participate in ~17 matches a year, with 20% of players involved in 25 or more, and 5% involved in 30 or more.
However, despite matches only accounting for ~5–11% of exposure to rugby-related activities, match injury rates are ~27 times higher than training injury rates.
Alongside the physical load of matches, professional rugby players also experience non-physical loads, such as travel, selection pressures, and media coverage.
A seven-season prospective cohort study reported that male players' chronic (12-month) and recent (1-month) match exposure contributes to their current injury risk.
This research concluded that players involved in: (1) a high (>35) number of matches in the previous 12 months, (2) a low (<15) matches in the previous 12 months, and (3) a low-moderate (12–28) number of matches in the previous 12 months but who have had high recent match exposure (>3 full-game equivalents in the previous month), should be monitored and their workload be carefully planned.
As a result, match load limits were introduced to the English Premiership for the 2019/20 season, stating that players must not be involved (play >20 min) in >35 matches per season, or play more than 30 full-match equivalents.
However, these recommendations were based on data collected between 2006 and 2013. Over recent years, rugby union has seen changes in match demands (e.g., a greater number of tackles per game)
in response to law changes and advancements in match analysis, equipment, technology, and player training; this suggests the recommendations made by Williams et al.
‘time-to-event’ analysis required the combination of match and training injuries to form a single compound group. However, it is preferable to consider match and training risk separately, as results depend on the ratio of training to match exposures and on the ratio of injury incidence during matches and training.
also focused solely on injury incidence but did not explore any variance in injury severity. Exploring injury incidence alone may provide an incomplete, and in some cases even erroneous, picture of injury risk.
the current study will utilise more recent injury data, improved modelling strategies, and will consider both injury incidence and burden. Further, the impact of match exposure on both match and training injury risk, and the moderating effects of positional groups and age, will be explored. Concussions are a prominent issue within elite rugby union,
Trends in match injury risk in professional male Rugby union: a 16-season review of 10 851 match injuries in the English premiership (2002–2019): the professional Rugby injury surveillance project.
and thus a subset analysis of concussion match injury risk will also be undertaken to elicit the impact of match exposure upon concussion risk. The overall aim of this study is to investigate the influence of previous season match exposure on injury risk in elite men's rugby union; this will allow the evaluation of any future changes to season structure and will inform future policy and player management discussions.
2. Methods
A three-season (2016–17 to 2018–19) retrospective cohort design was used to record all match and training injuries sustained by professional rugby union players in the English Premiership. Data were collected from a total of 13 teams (12 each season) in the top tier of English rugby, plus the England international team. Each team played 22 Premiership games each year with four teams involved in the semi-finals and two in the final, while European and National Cup exposure was based on the success of English teams in those competitions. Individual informed consent was obtained from first-team eligible players on a yearly basis. This project received a favourable ethical opinion from the University of Bath Research Ethics Approval Committee for Health (REACH reference number: EP 18/19096) and was carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans.
Data were collected for 1023 players (age = 25.6 ± 4.4), of whom 446 were Backs and 577 were Forwards. Across the three seasons, 404 players were involved in one season, 278 players were involved in two seasons, and 341 players were involved in all three seasons.
To calculate match exposure, individual match exposure data were collected from the Rugby Football Union player monitoring system (‘Elite Hub’) for seasons 2015–16 to 2018–19, and included matches from the Premiership, National Cup, European Cups, International appearances for any of the ‘Six Nations’ countries and British and Irish Lions, friendlies, and loan appearances in the Championship. ‘Match exposure’ was defined in three ways: the total number of appearances of any duration; the total number of appearances of at least 20 mins; and full-game equivalents (total match mins ÷ 80). Players' match exposures in the preceding season were used as predictor variables to explore the chronic influence of match exposures on injury risk. For injury risk estimations, match exposures in Premiership, National Cup, European Cups, England Internationals, and friendly fixtures in the current season were used, as these competitions could be aligned with corresponding injury data. Thus, the 2015–16 season was only used for the calculation of ‘season match exposure’ for the 2016–17 season and not included in the injury risk models.
Training exposure data were also collected from the ‘Elite Hub’ online platform. Training exposure data were reported as the number of players partaking in each session type during the week and the number of minutes spent performing each training type; this was then multiplied to calculate training volume in each category and summed across each season to get total training exposure. These values were then divided by the average number of players attending training throughout each season to infer the typical training exposure per player for each team.
Injury data were captured directly from the injury surveillance section of an online clinical electronic medical record-keeping system, ‘Rugby Squad’ (The Sports Office, UK). For each injury reported, information including injury type, site, the activity causing injury, and severity was collected. An injury was defined as ‘any injury that resulted in a player being unable to take a full part in future rugby training or match play for more than 24 h from midnight at the end of the day the injury was sustained’.
Injury severity was defined as the number of days lost from match play or training, with the injury return date set as the day the player was deemed fully fit to play by the team's medical staff, irrespective of whether a match or training was planned for that day.
Injury incidence was calculated as the count of injuries per 1000 player hours of exposure: (injury count / exposure hours) × 1000. Injury burden was calculated as the total number of days absence per 1000 player hours of exposure: (total days lost / exposure hours) × 1000. All estimations were performed using R (version 4.1.0, R Foundation for Statistical Computing, Vienna, Austria). Generalised linear mixed-effects models were fitted using the glmmTMB package
to model the association between match exposure variables and injury risk, using a Poisson distribution and log-link function. For injury incidence outcomes, the count of injuries incurred in the given season was used, whilst for injury burden outcomes, the total number of days missed due to injuries incurred in the given season was used. All models were offset for match/training exposure. Each match exposure predictor variable was modelled as both a linear and nonlinear effect by including polynomial terms in the model, with model performance metrics used to determine the most appropriate model for each outcome.
Players' age, positional group (Forwards/Backs) and recent injury history (total days missed due to injury in preceding season) were included as covariates in all models.
A nested random effect (player within team: ‘1 | team/player ID’) was used to account for clustering and repeated observations. A baseline model (no predictor variables included) was used to determine typical injury risk with 95% confidence limits; effects were considered substantial when the 95% confidence interval band for the effect estimate did not overlap with the baseline risk region. Interaction terms (age group × position group × match exposure variable) were used to examine the moderating effect of age and playing position. For these, age was split into two groups based on the median age of the cohort; ≤26 y, and >26 y.
3. Results
The distribution of season match exposure by position and age group for (A) match involvements (B) match involvements of at least 20 min and (C) full-game equivalents are displayed in Fig. 1. Across the whole cohort, the mean (median) season match loads were: Match involvements = 16.5 (13); Match involvements of at least 20 mins = 13.9 (10); Full-game equivalents = 11.4 (7.8). The match exposure limits (introduced as policy from 2019/20 onwards and therefore not specifically in place during the study period) for match involvements of at least 20 min and full-game equivalents were exceeded by 0.14% (n = 3) and 0.23% (n = 5) of the cohort, respectively. On average, each match involvement was associated with 60 min of exposure time (0.75 full-game equivalents).
Fig. 1Distribution and boxplot of season match loads by position and age group for (A) match involvements (B) match involvements of at least 20 min and (C) full-game equivalents. Dashed vertical lines represent the current match load limits.
No clear relationships were observed between previous season match exposure and match and training injury incidence rates in the current season (Fig. 2). Further, no substantial moderating effects of previous season match exposures, position, and age group upon match and training injury incidence rates in the current season were observed.
Fig. 2Influence of match loads undertaken in the previous season upon match (A-C) and training (D-F) injury incidence rates in the current season. The blue and grey shaded regions show the 95% confidence limits for the baseline injury risk and effect estimate, respectively. The dashed vertical lines represent the lower, median, and upper quartiles for each match load measure. * indicates a meaningful difference in injury risk.
Substantially elevated match and training injury burden was observed at or beyond ≈31 match involvements in the previous season (Fig. 3). Approximately 6% (n = 59) of the cohort exceeded this threshold in the current study. For match involvements in the range of 4 to 31 in the previous season, every additional match involvement was associated with an increase of 170 injury days per 1000 h of match exposure in the following season, with risk tending to return towards baseline for match exposures beyond this point. Every additional match involvement was associated with an increase of 11 injury days per 1000 h of training exposure in the following season. Substantially greater training injury burden was also observed beyond ≈26 full-game equivalents; approximately 4% (n = 44) of the cohort exceeded this threshold in the current study. The increased training injury burden associated with higher match exposure appeared to be driven by an increased risk for older (>26 y) Backs, but the increased match injury burden associated with higher match exposure appeared to be driven by an increased risk for older (>26 y) Forwards (see online supplementary material).
Fig. 3Influence of match loads undertaken in the previous season upon match (A–C) and training (D–F) injury burden rates in the current season. The blue and grey shaded regions show the 95% confidence limits for the baseline injury risk and effect estimate, respectively. The dashed vertical lines represent the lower, median, and upper quartiles for each match load measure. * indicates a meaningful difference in injury risk.
Players who had minimal match exposure in the previous season were found to display substantially elevated match concussion incidence rates in the current season (see Online supplementary material). This relationship was not evident with training concussion incidence rates. A substantial increase in match concussion burden was observed above ≈38 match involvements in the previous season, but this was driven by a small number of observations (n = 2). No clear associations were seen for training concussion burden rates.
4. Discussion
The present study aimed to describe the influence that previous season match exposures have upon current injury risk in elite rugby union players, building upon previous research by Williams et al.
Using improved modelling strategies and more recent injury data, the present study was able to explore the influence of previous-season match exposure on injury incidence and injury burden separately, whilst also considering both match and training injury risk independently. The results suggest that involvement in ≥31 matches (for any duration) within a season substantially increases a player's match and training injury burden in the following season. Notably, only three players in the present analysis exceeded the current match load limit (introduced as policy from 2019/20 onwards and therefore not specifically in place during the study period) of 35 match involvements of over 20 mins, and only five players exceeded the 30 full game equivalents limit.
Match and training injury burden were substantially increased for players involved in ≥31 matches (for any duration) in the previous season. Approximately 6% (n = 59) of the cohort exceeded this threshold in the current study. For match involvements in the range of 4 to 31 in the previous season, every additional match involvement was associated with an increase of 170 injury days per 1000 h of match exposure in the following season. For match injury burden, injury risk appeared to return towards baseline for those with the highest match exposures; this may be the result of survivorship bias.
Every additional match involvement was associated with an increase of 11 injury days per 1000 h of training exposure in the following season. Similarly, the training injury burden was substantially elevated beyond ≈26 full-game equivalents, but there was no substantial association between full-game equivalents and match injury burden. No clear association was found between previous season match exposure and injury incidence rates, highlighting the benefit of exploring injury burden to gain a more complete picture of injury risk. That is, season match exposures appeared to influence the severity, but not frequency, of injuries incurred the following season. High chronic match exposures are likely to elicit cumulative fatigue, which can reduce the stress-bearing capacity of tissue, alter neuromuscular control responses, and thus contribute to the observed increase in match injury burden.
These non-physical demands could explain why match involvements of any duration presented a clearer and more consistent association with injury burden when compared to appearances of at least 20 min and full-game equivalents. Practitioners are advised to adopt global approaches to monitor the internal response to the psychological load experienced by professional rugby union players, from both in and outside of sports, and acknowledge the central role of appraisal and the personal and social resources available to the athlete to successfully cope with these demands.
When splitting the cohort by position and age, the higher match injury burden with higher chronic match loads was likely driven by an increased risk for older (>26 y) Forwards, whilst the higher training injury burden was primarily driven by older (>26 y) Backs. The apparent trend between higher injury burden and age may be related to older players experiencing greater accumulated fatigue and delayed recovery time, as playing or training under fatigue blunts neuromuscular control, which may in turn increase injury risk.
In addition, older players are likely to have accumulated a greater injury history over their careers, which is a known risk factor for subsequent injury risk.
The variation between positional groups, with the Forwards driving match injury burden and Backs driving training injury burden, may be a result of their differing physical demands. For instance, Forwards typically undertake a greater volume of contact and collisions than Backs during match play, which may contribute to their higher match injury burden.
Trends in match injury risk in professional male Rugby union: a 16-season review of 10 851 match injuries in the English premiership (2002–2019): the professional Rugby injury surveillance project.
In the current study, it was found that players with minimal match involvements in the previous season had a significantly elevated match concussion incidence rate in the following season. This cohort is likely to consist of players transitioning into professional rugby (i.e., from the academy setting), or players who were injured for a large proportion of the previous season, and so both groups should be carefully managed to ensure they are appropriately prepared for the match demands of professional rugby union. Given the majority of head injuries in rugby union occur during tackles,
Does reducing the height of the tackle through law change in elite men’s rugby union (The Championship, England) reduce the incidence of concussion? A controlled study in 126 games.
It is acknowledged that this study is not without limitations. Due to the type of analysis chosen, a direct comparison of the results of this study to Williams et al.
was not possible. However, there are several additional benefits to using generalised linear mixed-effects models over the ‘time-to-event’ analysis in the previous study. Firstly, it was possible to explore match and training injury risk separately, which is preferable to combining match and training injuries to form a single compound group.
Another limitation to the current study is that it was not possible to gain access to injury data for players playing in international teams other than England, e.g., if players were injured whilst playing for Wales in a Six Nations fixture, the injury data would not be captured as part of the Professional Rugby Injury Surveillance Project. However, such instances would represent a small proportion of the dataset. In addition, individual-level training exposure data were not available, and so an implicit assumption of the training injury risk analyses was that players within the same team undertook the same volume of training, which may not have been the case. Finally, as with any injury surveillance system involving human data entry, there is a risk of error not just in the data entered but in the maintenance and updating of records. To address this, several quality control processes were used to maximise the validity of the data (e.g., cross-referencing match report cards against injuries entered into the database to ensure all match injuries sustained were captured).
Trends in match injury risk in professional male Rugby union: a 16-season review of 10 851 match injuries in the English premiership (2002–2019): the professional Rugby injury surveillance project.
The current study demonstrates that all match involvements, regardless of duration, should be considered when exploring associations between match exposure and injury risk. High match involvements (≥31 matches) in the previous season elevates injury burden rates in both matches and training in the following season. The physical and psychological load of players falling into any of these categories should be carefully managed to ensure they are either adequately conditioned for matches, or adequately recovered. Finally, few players are reaching the current season match load limits of ≥35 matches (>20 mins) or 30 full-game equivalents, which suggests these limits will have minimal impact on reducing match load demands in this cohort in their present form.
Funding Information
This study was funded by The Rugby Players Association.
Confirmation of Ethical Compliance
Ethical approval for this work was granted by the University of Bath Research Ethics Approval Committee for Health (REACH reference number: EP 18/19096) and was carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans.
Declaration of Interest Statement
Richard Bryan and Mark Lambert are employed by the Rugby Players Association.
Matthew Cross is employed by Premier Rugby Limited.
Simon Kemp and Keith A. Stokes are employed by the Rugby Football Union, the governing body for rugby union in England.
Sean Williams has received research funding from the Rugby Football Union and Rugby Players Association.
Acknowledgements
This study was funded by The Rugby Players Association. The authors would like to thank all players and staff who assisted in the data collection for this study as part of the Professional Rugby Injury Surveillance Project.
Appendix A. Supplementary data
The following are the supplementary data related to this article.
Fig. S1Influence of match loads undertaken in the previous season upon match (A–C) and training (D-F) injury burden rates in the current season, as a function of positional and age groups. The dashed vertical lines represent the lower, median, and upper quartiles for each match load measure.
Fig. S2Influence of match loads undertaken in the previous season upon match (A–C) and training (D-F) concussion burden rates in the current season. The dashed vertical lines represent the lower, median, and upper quartiles for each match load measure. * indicates a meaningful difference in injury risk.
Fig. S3Influence of match loads undertaken in the previous season upon match (A–C) and training (D-F) concussion incidence rates in the current season. The dashed vertical lines represent the lower, median, and upper quartiles for each match load measure. * indicates a meaningful difference in injury risk.
Trends in match injury risk in professional male Rugby union: a 16-season review of 10 851 match injuries in the English premiership (2002–2019): the professional Rugby injury surveillance project.
Does reducing the height of the tackle through law change in elite men’s rugby union (The Championship, England) reduce the incidence of concussion? A controlled study in 126 games.
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