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Rugby league has a relatively high injury risk, with the tackle having the greatest injury propensity. The number of tackles players engage in, prior to injurious tackles may influence injury risk, which has yet to be investigated. Therefore, this study investigated if rugby league players are involved in more tackles (as either tackler or ball carrier) (i) in the 10 minutes, or (ii) 1-min periods prior to an injurious tackle-event, (iii) differences for ball carriers vs. tacklers, and (iv) forwards vs. backs. Video analysis was utilised to quantify the number and rate of tackles in the 10-min periods prior to 61 tackle-related injuries. One thousand two hundred and eighty 10-min periods where players were not injured, were used as matched-controls. Generalized mixed linear models were used to analyse mean total and rate for tackles. Injured players were involved in significantly fewer tackles during the 10-min period, yet significantly more tackles during the final minute prior to the injurious tackle-event, compared to non-injured players. There were no differences between ball carriers vs. tacklers during the 10-min period. Both injured position groups were involved in significantly more tackles in the final minute. Additional match data sources are needed to further inform injury preventive strategies of tackle events.

OBJECTIVES: Describe the highest frequency and variability for tackle events in rugby league. Investigate seasonal differences in total tackle events per match over a seven-year period. DESIGN: Retrospective observational. METHODS: Tackle events (i.e., ball carrier events [attacker] and tackler involvements [defender]) from 864 male professional rugby league players competing in 1176 Super League matches from 2014 to 2020 were included. A series of linear mixed effect models were used to determine the frequency and variability during peak 1-, 3-, 5-, 10-, 20-, 40-min and whole-match tackle events per player per match at a positional group level. Differences between seasons for the total number of tackle events per match were compared using a one-way analysis of variance and with Tukey's honestly significant difference test. RESULTS: Tackle events were greatest for Props (51.5 [47.7-55.4] per match). Within-players, between-matches, and between-seasons variability was <10 % for tackle events. There were significantly less tackle events and tackler involvements per match in 2014 and a significantly more tackle events per match in season 2020b when compared with all other seasons. CONCLUSIONS: Large between-position variability in peak tackle events, ball carrier events, and tackler involvements would suggest that coaches should separate players into positional groups and prescribe training accordingly. Total number of tackle events, ball carrier events, and tackler involvements were significantly greater in season 2020b when compared to season 2014 to 2019 (inclusive) which may be a consequence of rule changes introduced to the sport.

In collision sports, the tackle has the highest injury incidence, and is key to a successful performance. Although the contact load of players has been measured using microtechnology, this has not been related to tackle technique. The aim of this study was to explore how PlayerLoad™ changes between different levels of tackling technique during a simulated tackle. Nineteen rugby union players performed twelve tackles on a tackle contact simulator (n = 228 tackles). Each tackle was recorded with a video-camera and each player wore a Catapult OptimEyeS5. Tackles were analysed using tackler proficiency criteria and split into three categories: Low scoring(≤5 Arbitrary units (AU), medium scoring(6 and 7AU) and high scoring tackles(≥8AU). High scoring tackles recorded a higher PlayerLoad™ at tackle completion. The PlayerLoad™ trace was also less variable in the high scoring tackles. The variability in the PlayerLoad™ trace may be a consequence of players not shortening their steps before contact. This reduced their ability to control their movement during the contact and post-contact phase of the tackle and increased the variability. Using the PlayerLoad™ trace in conjunction with subjective technique assessments offers coaches and practitioners insight into the physical-technical relationship of each tackle to optimise tackle skill training and match preparation.

This study investigated sources of variability in the overall and phase-specific running match characteristics in elite rugby league. Microtechnology data were collected from 11 Super League (SL) teams, across 322 competitive matches within the 2018 and 2019 seasons. Total distance, high-speed running (HSR) distance (>5·5 m·s−1), average speed, and average acceleration were assessed. Variability was determined using linear mixed models, with random intercepts specified for player, position, match, and club. Large within-player coefficients of variation (CV) were found across whole match, ball-in-play, attack and defence for total distance (CV range = 24% to 35%) and HSR distance (37% to 96%), whereas small to moderate CVs (≤10%) were found for average speed and average acceleration. Similarly, there was higher between-player, -position, and -match variability in total distance and HSR distance when compared with average speed and average acceleration across all periods. All metrics were stable between-teams (≤5%), except HSR distance (16% to 18%). The transition period displayed the largest variability of all phases, especially for distance (up to 42%) and HSR distance (up to 165%). Absolute measures of displacement display large within-player and between-player, -position, and -match variability, yet average acceleration and average speed remain relatively stable across all match-periods.

Understanding differences in locomotor and collision characteristics between phases of play can help rugby league coaches develop training prescription. There are no data currently available describing these differences at the elite international level. The aim of our study was to determine the differences in average speed (m∙min−1), high-speed running (>5.5 m∙s−1) per minute and collision frequencies per minute (n∙min−1) between attack and defence during the 2017 Rugby League World Cup (RLWC). Methods: Microtechnology data were collected from 24 male professional rugby league players from the same international squad across six matches of the RLWC. Data were then subject to exclusion criteria and stratified into forwards (n = 9) and backs (n = 7) before being analysed with linear mixed-effects models. Results: When comparing attack with defence, forwards and backs had substantially slower average speeds (effect size [ES]; ±90% confidence limits: −2.31; ±0.31 and −1.17; ±0.25) and substantially greater high-speed distance per minute (1.61; ±0.59 and 4.41; ±1.19). Forwards completed substantially more collisions per minute when defending (2.75; ±0.32) whilst backs completed substantially more when attacking (0.63; ±0.70). There was greater within- and between-player variability for collision frequency (coefficient of variation [CV] range; 25–28%) and high-speed distance (18–33%) per minute when compared to average speed (6–12%). Conclusions: There are distinct differences in locomotor and collision characteristics when attacking and defending during international rugby league match-play, yet the variability of high-speed running and collisions per minute is large. These data may be useful to plan or evaluate training practices.

Purpose Optic nerve head (ONH) assessment and its interpretation in healthy patients and those with glaucoma remains a pivotal topic specifically considering rapid advancements in imaging technologies. We undertook a large-scale, mixed cohort, comparative study to assess the correlation of optic disc measurements between different imaging modalities and investigated the impact of patient and disc associated parameters. Methods ONH sizes were obtained from one randomly selected eye of each of 209 patients using stereophotography, confocal scanning laser ophthalmoscopy and two different optical coherence tomographers (OCT). Patient related data, glaucoma status and optic disc variables, specifically oblique insertion, torsion, presence of beta PPA and spherical equivalent were recorded. Measurements between imaging modalities were analysed using Pearson correlation, linear regression analysis and Blend-Altman plots. Individual variables were compared applying multivariate regression analysis, ANOVA and chi square statistics was used to determine correlations between patient and clinical characteristics. Results Absolute measurements significantly differed between imaging modalities generally producing smaller measurements for OCT derived measurements of Bruch’s membrane opening (BMO). Pairwise correlations between imaging modalities were between 0.83 and 0.93 for discs without myopia, oblique insertion, or beta PPA. These features impacted on measurements for individual modalities and consequently contributed to inconsistencies and variability. Conclusion In comparison to planimetry, OCT derived BMO measurements are more variable in the presence of oblique insertion, beta PPA or magnification errors due to myopia. Impact of these factors, however, differs between instruments and needs to be considered to accurately interpret optic disc features in particular within the context of glaucoma diagnosis.

PURPOSE: Optic nerve head (ONH) assessment and its interpretation in healthy patients and those with glaucoma remains a pivotal topic specifically considering rapid advancements in imaging technologies. We undertook a large-scale, mixed cohort, comparative study to assess the correlation of optic disc measurements between different imaging modalities and investigated the impact of patient and disc associated parameters. METHODS: ONH sizes were obtained from one randomly selected eye of each of 209 patients using stereophotography, confocal scanning laser ophthalmoscopy and two different optical coherence tomographers (OCT). Patient related data, glaucoma status and optic disc variables, specifically oblique insertion, torsion, presence of beta PPA and spherical equivalent were recorded. Measurements between imaging modalities were analysed using Pearson correlation, linear regression analysis and Blend-Altman plots. Individual variables were compared applying multivariate regression analysis, ANOVA and chi square statistics was used to determine correlations between patient and clinical characteristics. RESULTS: Absolute measurements significantly differed between imaging modalities generally producing smaller measurements for OCT derived measurements of Bruch's membrane opening (BMO). Pairwise correlations between imaging modalities were between 0.83 and 0.93 for discs without myopia, oblique insertion, or beta PPA. These features impacted on measurements for individual modalities and consequently contributed to inconsistencies and variability. CONCLUSION: In comparison to planimetry, OCT derived BMO measurements are more variable in the presence of oblique insertion, beta PPA or magnification errors due to myopia. Impact of these factors, however, differs between instruments and needs to be considered to accurately interpret optic disc features in particular within the context of glaucoma diagnosis.

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