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Abstract: Peek, RJ, Carey, DL, Middleton, KJ, Gastin, PB, and Clarke, AC. Association between position-specific impact and movement characteristics of professional rugby union players during game play. J Strength Cond Res 37(1): 161-166, 2023-The aim of this study was to understand the association between impact and movement characteristics during whole game and peak 1- to 10-minute rolling windows in professional rugby union. Maximal impact (impacts·min-1) and corresponding running (m·min-1) characteristics as well as maximal running (m·min-1) and corresponding impact (impacts·min-1) characteristics were obtained for 160 athletes from 4 teams across the 2018 and 2019 Super Rugby seasons. A linear mixed-effects model reported a positive association between whole-game running and impacts, where greater impact characteristics corresponded with greater running characteristics. The average 1-minute peak running characteristics (150-160 m·min-1) typically occurred when no impacts occurred. The average 1-minute peak impact characteristics (4-6 impacts·min-1) corresponded with an average relative distance of 90-100 m·min-1. Worst case scenario observed impact characteristics as large as 15 impacts·min-1 with a corresponding relative distance of 140 m·min-1. When training for peak period characteristics, running may be completed in isolation; however, peak impacts often occur in conjunction with moderate to high running movements. Given running and impact characteristics can appear concurrently within game play, this highlights the need to train them accordingly. As such, when prescribing training drills to replicate the peak characteristics in rugby union, consideration should be taken for both running and impact characteristics., (Copyright © 2021 National Strength and Conditioning Association.)

The purpose of this study was to compare the peak periods (1- to 6-minute epochs) for three different training methods (game-based training - GBT; small-sided games - SSG; and conditioning training - CT) in elite male rugby union (RU) players. The peak movement (m·min -1 ) and impact (impact·min -1 ) characteristics of 42 players during in-season training were assessed. When comparing between training methods, SSG drills produced the greatest peak movement characteristics for all time epochs (1-minute average peak periods - SSG 195 m·min -1 , GBT 160 m·min -1 , and CT 144 m·min -1 ). The peak impact characteristics performed during training were 1-2 impact·min -1 for a 1-minute period and then decreased as the time period increased for all training methods. The greatest distribution of training time occurred at 30-39% (SSG and CT) and 40-49% (GBT) of peak movement intensity, with less than 5% of training performed at or above 80% peak intensity across all drill types. Findings from the current study show that the peak movement periods (m·min -1 ) in RU training from all three training methods match or exceed those which are previously reported in peak gameplay, yet their ability to replicate peak impact characteristics is questionable.

Objectives: This study identifies the distribution (as a percentage of the positional peak) and occurrence (within a half) of 1-min movement characteristics (m·min -1 ) and contact-based events (impact·min -1 ) during professional rugby union game play., Design: Within 95 rugby union games, players wore global positioning system (GPS) devices (n = 1422 player-game files, 160 athletes). One-minute rolling-window averages were calculated with the maximum and mean value being recorded for each dependent variable; relative distance (m·min -1 ) and impacts (impact·min -1 ), then standardised by the positional peak mean., Methods: The distribution of these variables accumulated in 10% increments of the peak were determined as was their occurrence throughout a playing half for each positional group., Results: The greatest distribution of game play (%) was observed at ~30-39% of the positional peak for movement and with no impacts. The greatest occurrence of maximum positional peak 1-min movement periods occurred at the beginning of each half and declined as the half went on. Peak impact characteristics, however, were found to be more sporadic across a half., Conclusions: These findings suggest that the distribution of positional peak 1-min movement (80-100%+) and peak impacts (4+) were <5% of overall game play, and observed <2% of total occurrences. This highlights that practitioners should alter training drills by time, volume, and intensity in order to replicate the peak intensities of game play., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

High-speed running (HSR) loads have been linked with non-contact injury risks in team-sports. This study investigated whether player-specific speed zones, reflecting individual fitness characteristics, impact the associations between non-contact injury and acute and chronic HSR loads. Semi-professional soccer players from two clubs (n = 47) were tracked over two seasons using 10 Hz GPS (5552 observations). HSR distances were calculated arbitrarily (≥5.5 m·s -1 ), and in an individualised fashion based on the final speed of the 30-15 intermittent fitness test. Cumulative running loads were represented by exponentially weighted moving averages with 7-(acute) and 28-day (chronic) decay parameters. Physiotherapists collected non-contact, lower-limb, time-loss injury data (n = 101). Injury models using session type (training vs matches), coach, as well as arbitrary or individualised running loads were constructed via mixed-effect logistic regression. Session type had the largest effect on injury (training vs match OR = 0.28; 95%CI:0.17-0.44). Variations in individualised or arbitrary acute and chronic HSR loads within the mid-range of the observed data had negligible effects on predicted injury risk. However, the uncertainty of estimated effects at extreme values of acute and chronic HSR loads prevented any conclusive findings. Therefore, the efficacy of using customised speed thresholds in quantifying load for injury risk mitigation purposes remains unclear.