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Objectives: Describe head acceleration events (HAEs) experienced by professional male rugby union players during tackle, ball‐carry, and ruck events using instrumented mouthguards (iMGs). Design: Prospective observational cohort. Methods: Players competing in the 2023 Currie Cup (141 players) and Super Rugby (66 players) seasons wore iMGs. The iMG‐recorded peak linear acceleration (PLA) and peak angular acceleration (PAA) were used as in vivo HAE approximations and linked to contact‐event data captured using video analysis. Using the maximum PLA and PAA per contact event (HAEmax), ordinal mixed‐effects regression models estimated the probabilities of HAEmax magnitude ranges occurring, while accounting for the multilevel data structure. Results: As HAEmax magnitude increased the probability of occurrence decreased. The probability of a HAEmax ≥15g was 0.461 (0.435–0.488) (approximately 1 in every 2) and ≥45g was 0.031 (0.025–0.037) (1 in every 32) during ball carries. The probability of a HAEmax >15g was 0.381 (0.360–0.404) (1 in every 3) and >45g 0.019 (0.015–0.023) (1 in every 53) during tackles. The probability of higher magnitude HAEmax occurring was greatest during ball carries, followed by tackles, defensive rucks and attacking rucks, with some ruck types having similar profiles to tackles and ball carries. No clear differences between positions were observed. Conclusion: Higher magnitude HAEmax were relatively infrequent in professional men's rugby union players. Contact events appear different, but no differences were found between positions. The occurrence of HAEmax was associated with roles players performed within contact events, not their actual playing position. Defending rucks may warrant greater consideration in injury prevention research. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to examine head acceleration event (HAE) propensity and incidence during elite-level men's and women's rugby union matches. Methods: Instrumented mouthguards (iMGs) were fitted in 92 male and 72 female players from nine elite-level clubs and three international teams. Data were collected during 406 player matches (239 male, 167 female) using iMGs and video analysis. Incidence was calculated as the number of HAEs per player hour and propensity as the proportion of contact events resulting in an HAE at a range of linear and angular thresholds. Results: HAE incidence above 10 g was 22.7 and 13.2 per hour in men's forwards and backs and 11.8 and 7.2 per hour in women's forwards and backs, respectively. Propensity varied by contact event, with 35.6% and 35.4% of men's tackles and carries and 23.1% and 19.6% of women's tackles and carries producing HAEs above 1.0 krad/s2. Tackles produced significantly more HAEs than carries, and incidence was greater in forwards compared with backs for both sexes and in men compared with women. Women's forwards were 1.6 times more likely to experience a medium-magnitude HAE from a carry than women's backs. Propensity was similar from tackles and carries, and between positional groups, while significantly higher in men than women. The initial collision stage of the tackle had a higher propensity than other stages. Conclusion: This study quantifies HAE exposures in elite rugby union players using iMGs. Most contact events in rugby union resulted in lower-magnitude HAEs, while higher-magnitude HAEs were comparatively rare. An HAE above 40 g occurred once every 60–100 min in men and 200–300 min in women. Future research on mechanisms for HAEs may inform strategies aimed at reducing HAEs. [ABSTRACT FROM AUTHOR]

The article presents the discussion on correction notice "Instrumented Mouthguards in Elite‑Level Men's and Women's Rugby Union: The Incidence and Propensity of Head Acceleration Events in Matches."

ObjectiveTo establish match injury rates and patterns in elite female rugby union players in England.Method: We conducted a six-season (2011/2012-2013/2014 and 2017/2018-2019/2020) prospective cohort study of time-loss match injuries in elite-level female players in the English Premiership competition. A 24-hour time-loss definition was used.Results: Five-hundred and thirty-four time-loss injuries were recorded during 13 680 hours of match exposure. Injury incidence was 39 injuries per 1000 hours (95% CIs 36 to 42) with a mean severity of 48 days (95% CIs 42 to 54) and median severity of 20 days (IQR: 7-57). Concussion was the most common specific injury diagnosis (five concussions per 1000 hours, 95% CIs 4 to 6). The tackle event was associated with the greatest burden of injury (615 days absence per 1000 hours 95% CIs 340 to 1112), with 'being tackled' specifically causing the most injuries (28% of all injuries) and concussions (22% of all concussions).Conclusions: This is the first multiple-season study of match injuries in elite women's rugby union players. Match injury incidence was similar to that previously reported within international women's rugby union. Injury prevention strategies centred on the tackle would focus on high-burden injuries, which are associated with substantial player time-loss and financial costs to teams as well as the high-priority area of concussions. [ABSTRACT FROM AUTHOR]

Purpose: The advantages of monitoring players in a team are well documented. However, barriers associated with lack of resources and time prevent teams from implementing systematic monitoring programs. This study aimed to identify (1) the methods rugby teams use to monitor the training load and associated response to the training load and (2) prerequisites of a monitoring protocol that are scientifically suitable and practically applicable for monitoring fitness and fatigue of rugby players. Methods: Coaches and support staff working with varying levels of rugby union were invited to complete an online questionnaire. Results: Of the 55 respondents, 96% indicated that although they regarded monitoring the training load and training-load response as important, there is no monitoring protocol that is cost-effective, time efficient, and nonaversive to the players. Respondents measured several variables when monitoring and incorporated more subjective than objective measures. Respondents (41%) indicated that they would like a protocol that is time efficient (5–10 min) and provides immediate feedback on players who identify as fatigued (50%). For coaches to have confidence in the information provided by the protocol, it needs to meet basic clinimetric principles of reliability and validity. The technical and biological error in the measurement needs to be known so that meaningful changes in fatigue and fitness can be distinguished from natural variations in the measurements. Conclusions: Prerequisites of an ideal monitoring protocol for rugby players were identified. It follows that a monitoring protocol that fulfills these prerequisites should satisfy both scientific principles and the coach’s demands. [ABSTRACT FROM AUTHOR]

Objectives: The Professional Rugby Injury Surveillance Project is the largest and longest running rugby union injury surveillance project globally and focuses on the highest level of rugby in England.Methods: We examined match injuries in professional men's rugby over the period 2002/2003 to 2018/2019 and described trends in injuries over this time.Results: Over the period 2002/2003-2018/2019, 10 851 injuries occurred in 1 24 952 hours of match play, equating to a mean of 57 injuries per club per season and one injury per team per match. The mean incidence, severity (days absence) and burden (days absence/1000 hours) of injury were 87/1000 hours (95% CI 82 to 92), 25 days (95% CI 22 to 28) and 2178 days/1000 hours (95% CI 1872 to 2484), respectively. The tackle accounted for 43% injuries with running the second most common activity during injury (12%). The most common injury location was the head/face with an incidence of 11.3/1000 hours, while the location with the highest overall burden was the knee (11.1 days/1000 hours). Long-term trends demonstrated stable injury incidence and proportion of injured players, but an increase in the mean and median severity of injuries. Concussion incidence, severity and burden increased from the 2009/2010 season onwards and from 2011 to 2019 concussion was the most common injury.Conclusion: The rise in overall injury severity and concussion incidence are the most significant findings from this work and demonstrate the need for continued efforts to reduce concussion risk as well as a greater understanding of changes in injury severity over time. [ABSTRACT FROM AUTHOR]

Regular monitoring of players in a team can be a challenge because it is time consuming, expensive and impractical. The Fatigue and Fitness Test for Teams (FFITT) was developed to satisfy the demands of a practical monitoring protocol for frequent use in team sports. This study aimed to quantify the sensitivity of the FFITT and assess the practicality of implementing the FFITT in a rugby team. The FFITT was completed before and after three university 1st XV rugby union matches. The FFITT was sensitive to the demands of a rugby match in some individuals. Grouped results (n = 22 players) revealed a significant reduction in HRR60s of 7 beats post-match 3 (P = 0.002; ES = 0.52), which is greater than the 5 beats which constitute a meaningful change in fatigue and fitness. A significant reduction in SLJ of 11 cm was also observed post-match 3 (P = 0.04; ES = 0.69), which is less than the meaningful change (13 cm). On an individual level, meaningful changes occurred in SLJ distance in nine players, in HRR60s in 14 players and in both HRR60s and SLJ in three players. Descriptive analysis of the RTT-Q revealed that players experienced increased muscle soreness and reduced readiness-to-train post-match 1 and post-match 2. The FFITT could be successfully completed by the squad in 8 min during their warm-up. The FFITT satisfies both scientific principles and the coach's demands of a practical monitoring protocol for frequent use in the team sports setting. [ABSTRACT FROM AUTHOR]

The study investigated whether countermovement jump (CMJ) metrics and subjective responses to a readiness-to-train questionnaire (RTT-Q) tracked simulated match-induced acute fatigue. This was a randomized cross-over repeated measures study. Participants were assigned into one of two groups; CONTROL or LIST. The LIST group performed the Loughborough Intermittent Shuttle Run (LIST), which was designed to simulate the demands of a soccer match. The CONTROL performed light physical activity at an intensity of <65% of maximal heart rate. Each group performed three CMJ's and completed an RTT-Q before (PRE), and again at 24 and 48 h after the LIST and/or CONTROL interventions. At 24 h there were significant differences in RTT-Q answers between the Pre and 24 h for the LIST group for questions; "Do you feel physically strong today?" and "Do you have muscle soreness today?" (p = 0.02 and 0.0008, respectively). The questions "Do you feel mentally strong today?" and "Do you have muscle soreness today?" (p = 0.02 and p = 0.0001 respectively) were the only questions that had a significant difference between Pre and 48 h for the LIST group. None of the CMJ metrics (LIST or CONTROL) changed significantly at any stage of the experiment. Although fatigue was detected by changes in the RTT-Q at 24 and 48 h after the LIST, none of the CMJ metrics changed. These findings suggest that subjective measures are more sensitive to low-level fatigue than objective measures, thus effective monitoring should include both. [ABSTRACT FROM AUTHOR]

We developed the Fatigue and Fitness Test for Teams (FFITT) to address the challenges of monitoring players in a team simultaneously. The test, which takes 8 min for the entire team, incorporates subjective measures of well-being (RTT-Q), and objective measures of the autonomic system (HRR60s) and neuromuscular function (SLJ). The aim of this study was to present the rationale for the FFITT as a novel athlete monitoring protocol and to measure the reliability of each component of the test. The internal consistency of the RTT-Q questions ranged from α = 0.69–0.92. All questions had an α > 0.83, with one exception of question 'Rate the well-being/stress your school/university/work is causing you to feel' which had an α = 0.69. The reliability of the HRR60s and SLJ was high (R = 0.92, and 0.91 respectively). The absolute typical error of measurement (TEM) of the SLJ was 8 cm and HRR60s was 3 beats. When expressed relatively the CVTEM of HRR60s was 8.4% and SLJ was 3.0%. Based on the TEM the HRR60s and SLJ could detect medium and large changes in fatigue and fitness. In absolute terms this equates to more than 5 bpm (HRR60s) and more than 13 cm (SLJ). The FFITT has the potential to satisfy both scientific principles and the coach's demands of a practical monitoring protocol for frequent use in a team. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: To examine the likelihood of head acceleration events (HAEs) as a function of previously identified risk factors: match time, player status (starter or substitute) and pitch location in elite-level men's and women's rugby union matches., Methods: Instrumented mouthguard data were collected from 179 and 107 players in the men's and women's games and synchronised to video-coded match footage. Head peak resultant linear acceleration (PLA) and peak resultant angular acceleration were extracted from each HAE. Field location was determined for HAEs linked to a tackle, carry or ruck. HAE incidence was calculated per player hour across PLA recording thresholds with 95% CIs estimated. Propensity was calculated as the percentage of contact events that caused HAEs across PLA recording thresholds, with a 95% CI estimated. Significance was assessed by non-overlapping 95% CIs., Results: 29 099 and 6277 HAEs were collected from 1214 and 577 player-matches in the men's and women's games. No significant differences in match quarter HAE incidence or propensity were found. Substitutes had higher HAE incidence than starters at lower PLA recording thresholds for men but similar HAE propensity. HAEs were more likely to occur in field locations with high contact event occurrence., Conclusion: Strategies to reduce HAE incidence need not consider match time or status as a substitute or starter as HAE rates are similar throughout matches, without differences in propensity between starters and substitutes. HAE incidence is proportional to contact frequency, and strategies that reduce either frequency or propensity for contact to cause head contact may be explored., Competing Interests: GT and BJ have received research funding from Prevent Biometrics and World Rugby. KAS and MB have received research funding from World Rugby. LS, RT, ECF, DMS and JB are employed by or contracted as consultants to World Rugby. GT previously conducted consultancy work for World Rugby. KAS and SPTK are employed by the Rugby Football Union. SH receives funding for his PhD studies from the Rugby Football Union and Premiership Rugby. BJ is a consultant with Premiership Rugby and the Rugby Football League. MC is employed by Premiership Rugby and was previously employed by the Rugby Football Union. PO'H has previously been contracted by the Rugby Football Union and is employed by Marker Diagnostics UK, a company developing salivary biomarker testing for sport-related concussion., (Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)