Injury risk factors and barriers to their mitigation for women playing rugby league: a Delphi study.

This study aimed to 1) develop a consensus (≥70% agreement between experts) on injury risk factors specific to women playing rugby league, 2) establish the importance of the identified injury risk factors and the feasibility of mitigating these risk factors and 3) establish context specific barriers to injury risk management. Aim 1: A Delphi panel, consisting of 12 experts in rugby league and injury (e.g., physiotherapists, research scientists) were asked to identify injury risk factors specific to women playing rugby league. Aim 2: seven coaches of women's rugby league teams were asked to rate each risk factor that achieved consensus by their importance and feasibility to manage. Aim 3: Coaches reported barriers which restrict injury risk factor mitigation. Of the 53 injury risk factors which achieved consensus, the five injury risk factors with the highest combination of importance and feasibility ratings were: "poor tackle technique", "a lack of pre-season intensity", "training session are too short", "the current medical standards", and "limited access to physiotherapists". Following the identification of injury risk factors, their feasibility to manage and context specific barriers, this study proposes three constraint driven, integrated solutions which may reduce the barriers which limit injury risk factor management.

Influence of Perceptions of Sleep on Well-Being in Youth Athletes.

ABSTRACT: Sawczuk, T, Jones, B, Scantlebury, S, and Till, K. Influence of perceptions of sleep on well-being in youth athletes. J Strength Cond Res 35(4): 1066-1073, 2021-To date, most research considering well-being questionnaires has only considered the training stress imposed on the athlete, without evaluating the questionnaire's relationship with a measure of recovery (e.g., sleep). This study aimed to assess the influence of sleep duration (Sduration), sleep quality (Squality), and sleep index (Sindex; Sduration × Squality) on well-being in youth athletes, while accounting for the known training stressors of training load and exposure to match play. Forty-eight youth athletes (age 17.3 ± 0.5 years) completed a daily questionnaire including well-being (DWBno-sleep; fatigue, muscle soreness, stress, and mood) measures, Perceived Recovery Status Scale (PRS), the previous day's training loads, Sduration, and Squality every day for 13 weeks. Linear mixed models assessed the impact of Sduration, Squality, and Sindex on DWBno-sleep, its individual subscales, and PRS. Sduration had a small effect on DWBno-sleep (d = 0.31; ±0.09), fatigue (d = 0.42; ±0.11), and PRS (d = 0.25; ±0.09). Squality had a small effect on DWBno-sleep (d = 0.47; ±0.08), fatigue (d = 0.53; ±0.11), stress (d = 0.35; ±0.07), mood (d = 0.41; ±0.09), and PRS (d = 0.37; ±0.08). Sindex had a small effect on DWBno-sleep (d = 0.44; ±0.08), fatigue (d = 0.55; ±0.11), stress (d = 0.29; ±0.07), mood (d = 0.37; ±0.09), and PRS (d = 0.36; ±0.09). The results indicate that an athlete's perceptions of sleep are associated with deviations in well-being measures and should be used as an input to the monitoring process rather than as part of the outcome well-being score. The sleep index is suggested as a potential input because it provides information on both the duration and quality of the sleep experienced.

The Frequency and Intensity of Representative and Nonrepresentative Late Adolescent Team-Sport Athletes' Training Schedules.

ABSTRACT: Scantlebury, S, Till, K, Sawczuk, T, Dalton-Barron, N, Phibbs, P, and Jones, B. The frequency and intensity of representative and nonrepresentative late adolescent team-sport athletes' training schedules. J Strength Cond Res 35(12): 3400-3406, 2021-This study aimed to identify and compare the training frequency and intensity (via session rating of perceived exertion load [sRPE load]) of representative and nonrepresentative late adolescent athletes. Thirty-six team sport athletes completed a web-based questionnaire daily over an 8-month period, reporting their training/match activities from the previous day. Athletes were categorized as representative (academy/county/international) or nonrepresentative (club/school) depending on the highest level of their sport they participated. Mean weekly frequencies and sRPE load of different training/match activities were quantified for each athlete across 5 school terms. Mann-Whitney U tests established the significance of differences and effect sizes between playing standards for mean weekly frequencies and mean sRPE load. Within-athlete weekly sRPE loads were highly variable for both playing standards; however, representative level athletes participated in significantly more activity outside of school compared with nonrepresentative athletes during November-December (effect size; 0.43-club technical training; 0.36-club matches), January-February (effect size; 0.78-club technical training; 0.75-club matches), and February-March (effect size; 0.63-club technical training; 0.44-club matches). Therefore, club and school coaches must ensure that all elements of representative athletes training schedules are coordinated and flexible to promote positive adaptions to training such as skill and physical development and prevent maladaptive responses such as overuse injury and nonfunctional overreaching. A cooperative and malleable training schedule between club/school coaches and the athlete will allow the athlete to perform on multiple fronts while also being able to meet the demands of additional stressors such as schoolwork.

Achieving a desired training intensity through the prescription of external training load variables in youth sport: More pieces to the puzzle required.

Identifying the external training load variables which influence subjective internal response will help reduce the mismatch between coach-intended and athlete-perceived training intensity. Therefore, this study aimed to reduce external training load measures into distinct principal components (PCs), plot internal training response (quantified via session Rating of Perceived Exertion [sRPE]) against the identified PCs and investigate how the prescription of PCs influences subjective internal training response. Twenty-nine school to international level youth athletes wore microtechnology units for field-based training sessions. SRPE was collected post-session and assigned to the microtechnology unit data for the corresponding training session. 198 rugby union, 145 field hockey and 142 soccer observations were analysed. The external training variables were reduced to two PCs for each sport cumulatively explaining 91%, 96% and 91% of sRPE variance in rugby union, field hockey and soccer, respectively. However, when internal response was plotted against the PCs, the lack of separation between low-, moderate- and high-intensity training sessions precluded further analysis as the prescription of the PCs do not appear to distinguish subjective session intensity. A coach may therefore wish to consider the multitude of physiological, psychological and environmental factors which influence sRPE alongside external training load prescription.

The relative contribution of training intensity and duration to daily measures of training load in professional rugby league and union.

This study examined the relative contribution of exercise duration and intensity to team-sport athlete's training load. Male, professional rugby league (n = 10) and union (n = 22) players were monitored over 6- and 52-week training periods, respectively. Whole-session (load) and per-minute (intensity) metrics were monitored (league: session rating of perceived exertion training load [sRPE-TL], individualised training impulse, total distance, BodyLoad™; union: sRPE-TL, total distance, high-speed running distance, PlayerLoad™). Separate principal component analyses were conducted on the load and intensity measures to consolidate raw data into principal components (PC, k = 4). The first load PC captured 70% and 74% of the total variance in the rugby league and rugby union datasets, respectively. Multiple linear regression subsequently revealed that session duration explained 73% and 57% of the variance in first load PC, respectively, while the four intensity PCs explained an additional 24% and 34%, respectively. Across two professional rugby training programmes, the majority of the variability in training load measures was explained by session duration (~60-70%), while a smaller proportion was explained by session intensity (~30%). When modelling the training load, training intensity and duration should be disaggregated to better account for their between-session variability.

Seasonal Changes in the Physical Performance of Elite Youth Female Soccer Players.

Emmonds, S, Sawczuk, T, Scantlebury, S, Till, K, and Jones, B. Seasonal changes in the physical performance of elite youth female soccer players. J Strength Cond Res 34(9): 2636-2643, 2020-This study investigated the seasonal change in physical performance of 113 (Under 10: U10 [n = 20], U12 [n = 30], U14 [n = 31], and U16 [n = 32]) elite youth female soccer players. Players completed testing pre-, mid-, and post-season, including speed (10- and 30-m sprint), change of direction (CoD; 505 test), power (countermovement jump [CMJ]), strength (isometric midthigh pull), and aerobic capacity (Yo-Yo intermittent recovery test level 1 [YYIRL1]). A general linear model was used to evaluate the change in physical characteristics and the influence of covariates (baseline performance; change in maturity status) on each characteristic across the season. U10's speed and CoD performance decreased from pre-post season, whereas relative strength likely improved. U12's relative strength very likely improved; however, 10-m sprint performance decreased. Relative strength likely decreased, whereas 30-m sprint and CoD time very likely improved in U14's. U16's likely improved relative strength, CMJ, and 10-m sprint, and very likely improved 30-m sprint and CoD from pre-post season. U12-U16's improved YYIRL1 performance pre-post season. Strength and conditioning coaches working with U10-U12 players should look to develop speed, lower-body power, and CoD ability as part of structured strength and conditioning sessions as well as within warm-ups before pitch-based sessions. With U14-U16 players' manipulation of small-sided games combined with short-duration high-intensity running drills may provide an efficient training stimulus to develop the aerobic system while concurrently developing technical/tactical skills. Findings of this study provide a basis for the implementation of strategies to enhance the long-term athletic development of youth female soccer players.

Physical Characteristics of Elite Youth Female Soccer Players Characterized by Maturity Status.

Emmonds, S, Scantlebury, S, Murray, E, Turner, L, Robsinon, C, and Jones, B. Physical characteristics of elite youth female soccer players characterized by maturity status. J Strength Cond Res 34(8): 2321-2328, 2020-The purpose of this study was to investigate the influence of maturity status on the physical characteristics of youth female soccer players. One hundred fifty-seven players from 3 elite soccer academies in England completed assessments of anthropometry, strength (isometric midthigh pull), lower-body power (countermovement jump [CMJ]), aerobic capacity (Yo-Yo intermittent recovery test level 1), change of direction (CoD: 505-left/right), and speed (10 and 30 m). Each player was classified into 1 of 6 maturity groups based on their estimated years from peak height velocity (YPHV). Magnitude-based inferences were used to assess for the practical significance between consecutive groups. Speed, CoD time, CMJ, and aerobic capacity were all possibly most likely better in more mature players. However, there was a likely difference in relative peak force between maturity groups -0.5 YPHV (27.13 ± 4.24 N·Kg) and 0.5 YPHV (24.62 ± 3.70 N·Kg), which was associated with a likely difference in 10-m sprint time (-0.5 YPHV: 2.00 ± 0.12 vs. 0.5 YPHV 2.08 ± 0.16 seconds) and unclear changes in CMJ and CoD time. Findings provide novel comparative data for this cohort relative to maturity status and can be used by strength and conditioning coaches to inform the design of training programs for youth female soccer players. Strength and conditioning coaches should be aware that youth female soccer players may experience a decrease in relative strength around peak height velocity, which may impact upon the speed, CoD time, and CMJ of players.

Relationships Between Training Load, Sleep Duration, and Daily Well-Being and Recovery Measures in Youth Athletes.

PURPOSE: To assess the relationships between training load, sleep duration, and 3 daily well-being, recovery, and fatigue measures in youth athletes. METHODS: Fifty-two youth athletes completed 3 maximal countermovement jumps (CMJs), a daily well-being questionnaire (DWB), the perceived recovery status scale (PRS), and provided details on their previous day's training loads (training) and self-reported sleep duration (sleep) on 4 weekdays over a 7-week period. Partial correlations, linear mixed models, and magnitude-based inferences were used to assess the relationships between the predictor variables (training and sleep) and the dependent variables (CMJ, DWB, and PRS). RESULTS: There was no relationship between CMJ and training (r = -.09; ±.06) or sleep (r = .01; ±.06). The DWB was correlated with sleep (r = .28; ±.05, small), but not training (r = -.05; ±.06). The PRS was correlated with training (r = -.23; ±.05, small), but not sleep (r = .12; ±.06). The DWB was sensitive to low sleep (d = -0.33; ±0.11) relative to moderate; PRS was sensitive to high (d = -0.36; ±0.11) and low (d = 0.29; ±0.17) training relative to moderate. CONCLUSIONS: The PRS is a simple tool to monitor the training response, but DWB may provide a greater understanding of the athlete's overall well-being. The CMJ was not associated with the training or sleep response in this population.

The influence of training load, exposure to match play and sleep duration on daily wellbeing measures in youth athletes.

This study assessed the influence of training load, exposure to match play and sleep duration on two daily wellbeing measures in youth athletes. Forty-eight youth athletes (age 17.3 ± 0.5 years) completed a daily wellbeing questionnaire (DWB), the Perceived Recovery Status scale (PRS), and provided details on the previous day's training loads (TL) and self-reported sleep duration (sleep) every day for 13 weeks (n = 2727). Linear mixed models assessed the effect of TL, exposure to match play and sleep on DWB and PRS. An increase in TL had a most likely small effect on muscle soreness (d = -0.43;± 0.10) and PRS (d = -0.37;± 0.09). Match play had a likely small additive effect on muscle soreness (d = -0.26;± 0.09) and PRS (d = -0.25;± 0.08). An increase in sleep had a most likely moderate effect on sleep quality (d = 0.80;± 0.14); a most likely small effect on DWB (d = 0.45;± 0.09) and fatigue (d = 0.42;± 0.11); and a likely small effect on PRS (d = 0.25;± 0.09). All other effects were trivial or did not reach the pre-determined threshold for practical significance. The influence of sleep on multiple DWB subscales and the PRS suggests that practitioners should consider the recovery of an athlete alongside the training stress imposed when considering deviations in wellbeing measures.

Validity of Retrospective Session Rating of Perceived Exertion to Quantify Training Load in youth Athletes.

Scantlebury, S, Till, K, Sawczuk, T, Phibbs, P, and Jones, B. Validity of retrospective session rating of perceived exertion to quantify training load in youth athletes. J Strength Cond Res 32(7): 1975-1980, 2018-Youth athletes frequently participate in multiple sports or for multiple teams within the same sport. To optimize player development and minimize undesirable training outcomes (e.g., overuse injuries), practitioners must be cognizant of an athlete's training load within and outside their practice. This study aimed to establish the validity of a 24-hour (s-RPE24) and 72-hour (s-RPE72) recall of session rating of perceived exertion (s-RPE) against the criterion measure of s-RPE collected 30 minutes' post training (s-RPE30). Thirty-eight adolescent athletes provided a s-RPE30 following the first field based training session of the week. Approximately 24 hours later subjects were asked to recall the intensity and duration of the previous days training. The following week subjects once again provided an s-RPE30 measure after training before recalling the intensity and duration of the session approximately 72 hours later. A nearly perfect correlation (0.98 [0.97-0.99]) was found between s-RPE30 and s-RPE24, with a small typical error of estimate (TEE; 8.3% [6.9-10.5]) and trivial mean bias (-1.1% [-2.8 to 0.6]). Despite a large correlation between s-RPE30 and s-RPE72 (0.73 [0.59-0.82]) and a trivial mean bias (-0.2% [-6.8 to 6.8]), there was a large TEE (35.3% [29.6-43.9]). s-RPE24 provides a valid measure of retrospectively quantifying s-RPE; however, the large error associated with s-RPE72 suggests that it is not a suitable method for monitoring training load in youth athletes.

Understanding the Relationship Between Coach and Athlete Perceptions of Training Intensity in Youth Sport.

Scantlebury, S, Till, K, Sawczuk, T, Weakley, J, and Jones, B. Understanding the relationship between coach and athlete perceptions of training intensity in youth sport. J Strength Cond Res 32(11): 3239-3245, 2018-To alleviate issues arising from the over-/under-prescription of training load, coaches must ensure that desired athlete responses to training are being achieved. The present study aimed to assess the level of agreement between the coach-intended (presession) and observed (postsession) rating of perceived exertion (RPE), with athlete RPE during different training intensities (easy, moderate, hard). Coach-intended RPE was taken before all field-based training sessions over an 8-week in-season period. After training, all coaches and athletes, who were participants in hockey, netball, rugby, and soccer were asked to provide an RPE measure for the completed session. Sessions were then classified based on the coach's intended RPE, with a total of 28, 125, and 66 easy, moderate, and hard training sessions collected, respectively. A univariate analysis of variance was used to calculate within-participant correlations between coach-intended/-observed RPE and athlete RPE. Moderate correlations were found between coach-intended and athlete RPE for sessions intended to be moderate and hard whilst a small correlation was found for sessions intended to be easy. The level of agreement between coach and athlete RPE improved following training with coaches altering their RPE to align with those of the athlete. Despite this, moderate and small differences between coach-observed and athlete RPE persisted for sessions intended to be easy and moderate, respectively. Coaches should, therefore, incorporate strategies to monitor training load to increase the accuracy of training periodization and reduce potential over-/under-prescription of training.

Validity, reliability, and the contributing physical characteristics of a modified 15m prone Yo-Yo Intermittent Recovery Test Level-1 test in elite female rugby league players.

This study aims to establish the validity and reliability of the prone Yo-YoIRL1 in elite female rugby league players (part one) and determine the anthropometric and physical characteristics contributing to 15m prone Yo-YoIRL1 performance (part two). Part one, 21 subjects completed one Yo-YoIRL1, one 20m and two 15m prone Yo-YoIRL1 tests over four sessions, with 7-14 days in-between. Part two, ten subjects completed a testing battery, including body mass, height, dual-energy x-ray absorptiometry, isometric mid-thigh pull, isometric bench-press, 10m and 20m sprints and an incremental treadmill test ([Formula: see text]). The 15m prone YoYoIRL1 demonstrated poor reliability with a typical error of 68m (21%) and a smallest worthwhile change of 54m (9%). Validity analysis found the prone versions of the YoYoIRL1 were not sensitive measures of intermittent running performance. Both prone YoYoIRL1 test distances demonstrated large mean bias (76% and -37% respectively) and typical error of the estimate (19% and 21%, respectively) in comparison to the YoYoIRL1. Body mass (r = -0.89), lean mass (r = -0.64), body fat % (r = -0.68), [Formula: see text] (l∙min-1) (r = -0.64), IMTP (r = -0.69), IBP (r = -0.15), 10m (r = -0.77) and 20m (r = -0.72) momentum displayed large negative relationships with 15m prone Yo-YoIRL1 performance. Due to the poor validity of the 20m prone YoYoIRL1, the poor validity and reliability of the 15m prone YoYoIRL1, and the anthropometric and physical characteristics which negatively impact performance, practitioners should reconsider the use of the prone YoYoIRL1 test to monitor high intensity intermittent running performance.

Training injuries in elite men's senior and academy (Super League) rugby league; an analysis of 224,000 exposure-hours.

OBJECTIVES: Report two-years of training injury data in senior and academy professional rugby league. DESIGN: Prospective cohort study. METHODS: Match and training time-loss injuries and exposure data were recorded from two-seasons of the European Super League competition. Eleven/12 (2021) and 12/12 (2022) senior and 8/12 (2021) and 12/12 (2022) academy teams participated. Training injuries are described in detail and overall match injuries referred to for comparison only. RESULTS: 224,000 training exposure hours were recorded with 293 injuries at the senior (mean [95 % confidence interval]; 3 [2-3] per 1000 h) and 268 academy level (2 [2-3] per 1000 h), accounting for 31 % and 40 % of all injuries (i.e., matches and training). The severity of training injuries (senior: 35 [30-39], academy: 36 [30-42] days-lost) was similar to match injuries. Lower-limb injuries had the greatest injury incidence at both levels (senior: 1.85 [1.61-2.12], academy: 1.28 [1.08-1.51] per 1000 h). Head injuries at the academy level had greater severity (35 [25-45] vs. 18 [12-14] days-lost; p < 0.01) and burden (17 [16-18] vs. 4 [4-5] days-lost per 1000 h; p = 0.02) than senior level. At the senior level, the incidence of contact injuries was lower than non-contact injuries (risk ratio: 0.29 [0.09-0.88], p = 0.02). CONCLUSIONS: Training injuries accounted for about a third of injuries, with similar injury severity to match-play. Within training there is a higher rate of non-contact vs. contact injuries. Whilst current injury prevention interventions target matches, these data highlight the importance of collecting high quality training injury data to develop and evaluate injury prevention strategies in training.

Time to level the playing field between men and women - Given similar injury incidence: A two-season analysis of match injuries in elite men and women's (Super League) rugby league.

OBJECTIVES: To compare match injury incidence, severity and burden in men's and women's elite rugby league. DESIGN: A prospective cohort epidemiological study. METHODS: Time loss match injury data were collected from all men's (11,301 exposure hours) and women's (5,244 exposure hours) Super League clubs. RESULTS: Injury incidence and burden were not different between men and women (mean [95 % CI]; 54 [45 to 65] vs. 60 [49 to 74] per 1000 match-hours; p = 0.39, and 2332 [1844 to 2951] vs. 1951 [1560 to 2440] days lost per 1000 match-hours; p = 0.26). However, injury severity was greater for men than women (42 [35-50] vs. 35 [29 to 42]; p = 0.01). Lower limbs accounted for 54 % and 52 % of injuries for men and women, with the head/face the most frequently injured location due to concussion (12 [10 to 15] and 10 [8 to 14] per 1000 match-hours for men and women). Injuries to the knee had the greatest burden for men and women (708 [268-1868] and 863 [320-2328] days lost per 1000 match-hours). Being tackled was the most common injury mechanism for men and women (28 % and 38 %) with greater burden (p < 0.01) than other injury mechanisms. CONCLUSIONS: Male and female rugby league players have similar injury incidence and burden; however, injury severity was higher in men. Head/face injuries have the highest injury incidence and knee injuries have the highest burden. These injuries should be the focus for prevention initiatives at a league (via laws), player, and coach level, with equal and specific focus for both men's and women's rugby league players.

Embracing the impact from instrumented mouthguards (iMGs): A survey of iMG managers' perceptions of staff and player interest into the technology, data and barriers to use.

Instrumented mouthguards (iMGs) are a novel technology being used within rugby to quantify head acceleration events. Understanding practitioners' perceptions of the barriers and facilitators to their use is important to support implementation and adoption. This study assessed men's and women's rugby union and league iMG managers' perceptions of staff and player interest in the technology, data and barriers to use. Forty-six iMG managers (men's rugby union and league n = 20 and n = 9 and women's rugby union and league n = 7 and n = 10) completed an 18-question survey. Perceived interest in data varied across staff roles with medical staff being reported as having the most interest. The iMG devices were perceived as easy to use but uncomfortable. Several uses of data were identified, including medical applications, player monitoring and player welfare. The comfort, size and fit of the iMG were reported as the major barriers to player use. Time constraints and a lack of understanding of data were barriers to engagement with the data. Continued education on how iMG data can be used is required to increase player and staff buy-in, alongside improving comfort of the devices. Studies undertaken with iMGs investigating player performance and welfare outcomes will make data more useful and increase engagement.

Longitudinal changes in anthropometric, physiological, and physical qualities of international women's rugby league players.

This is the first study to assess longitudinal changes in anthropometric, physiological, and physical qualities of international women's rugby league players. Thirteen forwards and 11 backs were tested three times over a 10-month period. Assessments included: standing height and body mass, body composition measured by dual x-ray absorptiometry (DXA), a blood panel, resting metabolic rate (RMR) assessed by indirect calorimetry, aerobic capacity (i.e.,[Formula: see text]) evaluated by an incremental treadmill test, and isometric force production measured by a force plate. During the pre-season phase, lean mass increased significantly by ~2% for backs (testing point 1: 47 kg; testing point 2: 48 kg) and forwards (testing point 1: 50 kg; testing point 2: 51 kg) (p = ≤ 0.05). Backs significantly increased their [Formula: see text] by 22% from testing point 1 (40 ml kg-1 min-1) to testing point 3 (49 ml kg-1 min-1) (p = ≤ 0.04). The [Formula: see text] of forwards increased by 10% from testing point 1 (41 ml kg-1 min-1) to testing point 3 (45 ml kg-1 min-1), however this change was not significant (p = ≥ 0.05). Body mass (values represent the range of means across the three testing points) (backs: 68 kg; forwards: 77-78 kg), fat mass percentage (backs: 25-26%; forwards: 30-31%), resting metabolic rate (backs: 7 MJ day-1; forwards: 7 MJ day-1), isometric mid-thigh pull (backs: 2106-2180 N; forwards: 2155-2241 N), isometric bench press (backs: 799-822 N; forwards: 999-1024 N), isometric prone row (backs: 625-628 N; forwards: 667-678 N) and bloods (backs: ferritin 21-29 ug/L, haemoglobin 137-140 g/L, iron 17-21 umol/L, transferrin 3 g/L, transferring saturation 23-28%; forwards: ferritin 31-33 ug/L, haemoglobin 141-145 g/L, iron 20-23 umol/L, transferrin 3 g/L, transferrin saturation 26-31%) did not change (p = ≥ 0.05). This study provides novel longitudinal data which can be used to better prepare women rugby league players for the unique demands of their sport, underpinning female athlete health.

The propensity of non-concussive and concussive head contacts during elite-level women's rugby league matches: A prospective analysis of over 14,000 tackle events.

OBJECTIVES: Identify the frequency, propensity, and factors related to tackle events which result in contact with the head in elite-level women's rugby league. DESIGN: Prospective video analysis study. METHODS: Video footage from 59 Women's Super League matches were analysed (n = 14,378 tackle events). All tackle events were coded as no head contact or head contact. Other independent variables included: area contacting head, impacted player, concussion outcome, penalty outcome, round of competition, time in match and team standard. RESULTS: There were 83.0 ±â€¯20.0 (propensity 304.0/1000 tackle events) head contacts per match. The propensity of head contact was significantly greater for the tackler than ball-carrier (178.5 vs. 125.7/1000 tackle events; incident rate ratio 1.42, 95 % confidence interval 1.34 to 1.50). Head contacts occurring from an arm, shoulder, and head occurred significantly more than any other contact type. The propensity of concussions was 2.7/1000 head contacts. There was no significant influence of team standard or time in match on the propensity of head contacts. CONCLUSIONS: The observed head contacts can inform interventions, primarily focusing on the tackler not contacting the ball-carrier's head. The tackler's head should also be appropriately positioned to avoid contact with the ball-carrier's knee (highest propensity for concussion). The findings are consistent with other research in men's rugby. Law modifications and/or enforcement (reducing the number of un-penalised head contacts), concurrent with coaching interventions (optimising head placement or reducing the head being contacted) may help minimise head contact risk factors for women's rugby league.

A global perspective on collision and non-collision match characteristics in male rugby union: Comparisons by age and playing standard.

This study quantified and compared the collision and non-collision match characteristics across age categories (i.e. U12, U14, U16, U18, Senior) for both amateur and elite playing standards from Tier 1 rugby union nations (i.e. England, South Africa, New Zealand). Two-hundred and one male matches (5911 min ball-in-play) were coded using computerised notational analysis, including 193,708 match characteristics (e.g. 83,688 collisions, 33,052 tackles, 13,299 rucks, 1006 mauls, 2681 scrums, 2923 lineouts, 44,879 passes, 5568 kicks). Generalised linear mixed models with post-hoc comparisons and cluster analysis compared the match characteristics by age category and playing standard. Overall significant differences (p < 0.001) between age category and playing standard were found for the frequency of match characteristics, and tackle and ruck activity. The frequency of characteristics increased with age category and playing standard except for scrums and tries that were the lowest at the senior level. For the tackle, the percentage of successful tackles, frequency of active shoulder, sequential and simultaneous tackles increased with age and playing standard. For ruck activity, the number of attackers and defenders were lower in U18 and senior than younger age categories. Cluster analysis demonstrated clear differences in all and collision match characteristics and activity by age category and playing standard. These findings provide the most comprehensive quantification and comparison of collision and non-collision activity in rugby union demonstrating increased frequency and type of collision activity with increasing age and playing standard. These findings have implications for policy to ensure the safe development of rugby union players throughout the world.

The safety of rugby union, especially the tackle, has previously been questioned but limited data are available to understand the collision and non-collision match characteristics between different age categories and playing standards.The frequency of collision and non-collision match characteristics increase with age and playing standard except for the frequency of scrums and tries which are lowest at the Senior Elite level. The activity of the tackle and ruck are also different between age categories and playing standards.Hierarchical cluster analysis demonstrated clear differences in all and collision match characteristics between junior (i.e. U12, U14, U16), and amateur (i.e. U18 and senior) and elite (i.e. U18 and senior) playing levels.Governing bodies and practitioners should be aware of the differences in collision and non-collision match characteristics by age and playing standard, when reviewing future versions of rugby union.

A video analysis framework for the rugby league tackle.

Rugby league tackle video analysis research typically uses technical criteria from coaching cues or tackle variables from rugby union. As such, content validity and relevance could be questioned. A video analysis framework that establishes appropriate variables for rugby league is therefore required. The study aimed to adopt a 5-stage process to establish a video analysis framework for the rugby league tackle, which was content valid, relevant and reliable.The 5-stage process included 1) creation of draft video analysis framework, using available rugby tackle research, 2) expert group recruitment and critique, 3) refinement of framework to establish content validity, 4) response process validity task and agreement within expert group, 5) intra- and inter-reliability testing using Kappa statistics.The agreed framework comprised six phases including; tackle event, defensive start point, pre-contact, initial contact, post-contact and play-the-ball. Within the identified phases, 63 variables were established. The intra- and inter-reliability testing resulted in strong agreement within all phases.The video analysis framework can be used in rugby league tackle research, categorising complex tackle events, such as injurious or optimal tackles, improving both player welfare and performance. The application of the framework to future rugby league research will increase coherence and usefulness of research findings.

Applied sports science and sports medicine in women's rugby: systematic scoping review and Delphi study to establish future research priorities.

Objectives: In part 1, the objective was to undertake a systematic scoping review of applied sports science and sports medicine in women's rugby, and in part 2 to develop a consensus statement on future research priorities. Design: In part 1, a systematic search of PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost) was undertaken from the earliest records to January 2021. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, the PRISMA extension for Scoping Reviews, and the PRISMA extension protocols were followed. In part 2, 31 international experts in women's rugby (ie, elite players, sports scientists, medical clinicians, sports administrators) participated in a three-round Delphi consensus method. These experts reviewed the findings from part 1 and subsequently provided a list of priority research topics in women's rugby. Research topics were grouped into expert-based themes and expert-based subthemes via content analysis. Expert-based themes and expert-based subthemes were ranked from very low to very high research priority on a 1-5 Likert scale. Consensus was defined by ≥70% agreement. The median research priority agreement and IQR were calculated for each expert-based theme and subtheme. Data sources: PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost). Eligibility criteria for selecting studies: Studies were eligible for inclusion if they investigated applied sports science or sports medicine in women's rugby. Results: In part 1, the systematic scoping review identified 123 studies, which were categorised into six sports science and sports medicine evidence-based themes: injury (n=48), physical performance (n=32), match characteristics (n=26), fatigue and recovery (n=6), nutrition (n=6), and psychology (n=5). In part 2, the Delphi method resulted in three expert-based themes achieving consensus on future research priority in women's rugby: injury (5.0 (1.0)), female health (4.0 (1.0)) and physical performance (4.0 (1.0)). Summary/Conclusion: This two-part systematic scoping review and Delphi consensus is the first study to summarise the applied sports science and sports medicine evidence base in women's rugby and establish future research priorities. The summary tables from part 1 provide valuable reference information for researchers and practitioners. The three expert-based themes that achieved consensus in part 2 (injury, female health and physical performance) provide clear direction and guidance on future research priorities in women's rugby. The findings of this two-part study facilitate efficient and coordinated use of scientific resources towards high-priority research themes relevant to a wide range of stakeholders in women's rugby.