This study assessed the influence of environmental factors, air travel, and epoch estimation method on locomotor demands of international men's rugby sevens match-play. Eighteen men's rugby sevens players wore 10 Hz Global Positioning Systems (STATsport) during 52 international matches over nine global tournaments (418 observations). Whole-match average speed was recorded, whilst average speed and relative high-speed distance (>5.0 m·s-1) were quantified using FIXED and ROLL methods over 60-420 s epochs (60 s increments) to establish worst-case scenario demands. Linear mixed models compared FIXED versus ROLL estimation methods and assessed whether temperature, humidity, travel duration, number of time-zones crossed, and travel direction were associated with locomotor responses. Temperature and humidity were positively associated with overall and worst-case scenario average speed (effect estimates; b: 0.18-0.54), whilst worst-case scenario high-speed distance at 300 s was also related to temperature (b: 0.19). Easterly air travel compromised overall and 180 and 300 s worst-case scenario average speed (b: -8.31 to-7.39), alongside high-speed distance over 300 s (b: -4.54). For worst-case scenario average speed and high-speed distance, FIXED underestimated ROLL at all epoch lengths (∼9.9-18.4%, p≤0.001). This study indicated that international rugby sevens match-play locomotor responses were greater as air temperature increased but reduced following eastward air travel. Underestimation of demands in FIXED vs ROLL over 60-420 s epochs was confirmed. Such climatic and travel influences warrant the adoption of strategies targeted at maximising performance and safety according to the tournament conditions. Knowing the most demanding periods of match-play facilitates training specificity.HighlightsSelected locomotor responses were reduced following eastward air travel, potentially suggesting interventions to mitigate these effects are warranted.Match-play running responses were greater as air temperature increased. Strategies targeted at optimising body temperature in both warm and cool conditions warrant consideration to promote performance and maintain player safety.Fixed epochs underestimated worst-case scenario average speed (9.9-11.7%) and high-speed distance (11.4-18.4%). Rolling averages may thus be more appropriate for detecting the most intense periods, while duration-specific data provide training targets.

This study investigated the effects of flywheel inertia training (FIT) vs traditional resistance training (TRT) over four weeks in academy male rugby union (RU) players. Sixteen elite male academy RU players (age = 18.0 ± 1.0 years, body mass = 93.0 ± 13.1 kg) were allocated into either FIT (n = 8) or TRT (n = 8) groups. Pre and post measures of countermovement jump (CMJ), squat jump (SJ) and drop jump (DJ) were completed. Relative peak force (PF), relative peak power (PP) and jump height (H) were measured for CMJ and SJ with reactive strength index measured for the DJ. Both groups showed improvements in all measures, except for SJ peak power, following TRT. Within-group analysis showed significant increases following TRT in CMJ-H (2.79 cm, 90% CI = -0.70, 4.89 cm; p = 0.002; ES = 0.51) and SJ-H (3.68 cm, 90% CI = 1.25, 6.11 cm; p = 0.002; ES = 0.88) with a significant improvement following FIT for CMJ-PP (1.96Wkg-1, 90% CI = -0.89, 4.80 Wkg-1; p = 0.022; ES = 0.55). No significant between-group differences (p > 0.05) were evident. These findings suggest both FIT and TRT are effective for developing lower-body strength and power qualities in male academy RU players.

CONTEXT:Individual and team injury burden and performance are 2 key considerations facing practitioners in the daily prescription of an athlete's training load. Whereas a considerable number of researchers have examined univariate relationships between training load and performance, training load and injury, or injury and performance, few investigators have examined all 3 concurrently. OBJECTIVE:To assess the association among training load, injury burden, and performance in professional rugby union. DESIGN:Descriptive epidemiology study. SETTING:The English Premiership competition. PATIENTS OR OTHER PARTICIPANTS:Individual injury and training load data, as well as team performance data, were captured during the 2015-2016 (n = 433 players) and 2016-2017 (n = 569 players) seasons. MAIN OUTCOME MEASURE(S):Data were aggregated into team average scores for each week, including weekly (acute) load, smoothed chronic load, changes in load, injury burden, and weekly performance. Linear mixed modelling techniques were used to assess the association among measures. RESULTS:Injury burden was negatively associated with performance, with a high weekly burden associated with a likely harmful (P = .01) decrease in performance. Training load measures displayed only trivial associations with performance. Only the acute:chronic workload ratio measure was clearly associated with injury burden, with a possibly harmful effect (P = .02). Both squad size and player availability were associated with only trivial changes in performance. CONCLUSIONS:Whereas no association between average training load and performance existed, associations between training load and injury burden and between injury burden and performance were clear. Further investigation using more sensitive and individualized measures of load, performance, and injury may elicit a clearer relationship and should be considered for future work.

Objectives: Rugby union is a high intensity intermittent sport, typically analysed via set time periods or rolling average methods. This study reports the demands of international rugby union via global positioning system (GPS) metrics expressed as mean ball in play (BiP), maximum BiP (max BiP), and whole match outputs. Design: Single cohort cross sectional study involving 22 international players, categorised as forwards and backs. Methods: A total of 88 GPS files from eight international test matches were collected during 2016. An Opta sportscode timeline was integrated into the GPS software to split the data into BiP periods. Metres per min (m min(-1)), high metabolic load per min (HML), accelerations per min (Acc), high speed running per min (HSR), and collisions per min (Coll) were expressed relative to BiP periods and over the whole match (>60 min). Results: Whole match metrics were significantly lower than all BiP metrics (p < 0.001). Mean and max BiP HML, (p < 0.01) and HSR (p < 0.05) were significantly higher for backs versus forwards, whereas Coll were significantly higher for forwards (p < 0.001). In plays lasting 61 s or greater, max BiP m min(-1) were higher for backs. Max BiP m min HML, HSR and Coll were all time dependant (p < 0.05) showing that both movement metrics and collision demands differ as length of play continues. Conclusions: This study uses a novel method of accurately assessing the BiP demands of rugby union. It also reports typical and maximal demands of international rugby union that can be used by practitioners and scientists to target training of worst-case scenario's equivalent to international intensity. Backs covered greater distances at higher speeds and demonstrated higher HML, in general play as well as 'worst case scenarios'; conversely forwards perform a higher number of collisions, (C) 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

The assessment of competitive movement demands in team sports has traditionally relied upon global positioning system (GPS) analyses presented as fixed-time epochs (e.g., 5-40 min). More recently, presenting game data as a rolling average has become prevalent due to concerns over a loss of sampling resolution associated with the windowing of data over fixed periods. Accordingly, this study compared rolling average (ROLL) and fixed-time (FIXED) epochs for quantifying the peak movement demands of international rugby union match-play as a function of playing position. Elite players from three different squads (n = 119) were monitored using 10 Hz GPS during 36 matches played in the 2014-2017 seasons. Players categorised broadly as forwards and backs, and then by positional sub-group (FR: front row, SR: second row, BR: back row, HB: half back, MF: midfield, B3: back three) were monitored during match-play for peak values of high-speed running (>5 m·s-1; HSR) and relative distance covered (m·min-1) over 60-300 s using two types of sample-epoch (ROLL, FIXED). Irrespective of the method used, as the epoch length increased, values for the intensity of running actions decreased (e.g., For the backs using the ROLL method, distance covered decreased from 177.4 ± 20.6 m·min-1 in the 60 s epoch to 107.5 ± 13.3 m·min-1 for the 300 s epoch). For the team as a whole, and irrespective of position, estimates of fixed effects indicated significant between-method differences across all time-points for both relative distance covered and HSR. Movement demands were underestimated consistently by FIXED versus ROLL with differences being most pronounced using 60 s epochs (95% CI HSR: -6.05 to -4.70 m·min-1, 95% CI distance: -18.45 to -16.43 m·min-1). For all HSR time epochs except one, all backs groups increased more (p < 0.01) from FIXED to ROLL than the forward groups. Linear mixed modelling of ROLL data highlighted that for HSR (except 60 s epoch), SR was the only group not significantly different to FR. For relative distance covered all other position groups were greater than the FR (p < 0.05). The FIXED method underestimated both relative distance (~11%) and HSR values (up to ~20%) compared to the ROLL method. These differences were exaggerated for the HSR variable in the backs position who covered the greatest HSR distance; highlighting important consideration for those implementing the FIXED method of analysis. The data provides coaches with a worst-case scenario reference on the running demands required for periods of 60-300 s in length. This information offers novel insight into game demands and can be used to inform the design of training games to increase specificity of preparation for the most demanding phases of matches.

The purpose of this study was to quantify movement demands of elite international age grade (U20) rugby union players during competitive tournament match play. Forty elite professional players from an U20 international performance squad were monitored using 10 Hz global positioning systems (GPS) during 15 international tournament matches during the 2014/15 and 2015/16 seasons. Data on distances, velocities, accelerations, decelerations, high metabolic load (HML) distance and efforts, and number of sprints were derived. Data files from players who played over 60 min (n = 161) were separated firstly into Forwards and Backs, and more specifically into six positional groups; FR--Front Row (prop & hooker), SR--Second Row, BR--Back Row (Flankers & No.8), HB--Half Backs (scrum half & outside half), MF--Midfield (centres), B3--Back Three (wings & full back) for match analysis. Analysis revealed significant differences between forwards and backs positions. Backs scored higher on all variables measured with the exception of number of moderate accelerations, decelerations (no difference). The centres covered the greatest total distance with the front row covering the least (6.51 ± 0.71 vs 4.97 ± 0.75 km, p < 0.001). The front row also covered the least high speed running (HSR) distance compared to the back three (211.6 ± 112.7 vs 728.4 ± 150.2 m, p < 0.001) who covered the most HSR distance, affirming that backs cover greater distances but forwards have greater contact loads. These findings highlight for the first time differences in the movement characteristics of elite age grade rugby union players specific to positional roles.