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See discussions, stats, and author profiles for this publication at: Fluctuations in running and skill-relatedperformance in elite rugby union match-playArticle · August 2016DOI: 10.1080/17461391.2016.1220986CITATIONSREADS0534 authors, including:Mathieu LacomeJulien PiscioneFFR.Fédération Française de Rugby11 PUBLICATIONS 25 CITATIONS30 PUBLICATIONS 140 CITATIONSSEE PROFILESEE PROFILEJ.-P. HagerCentre Orthopedique Santy26 PUBLICATIONS 230 CITATIONSSEE PROFILEAll content following this page was uploaded by Mathieu Lacome on 14 November 2016.The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original documentand are linked to publications on ResearchGate, letting you access and read them immediately.

European Journal of Sport ScienceISSN: 1746-1391 (Print) 1536-7290 (Online) Journal homepage: http://www.tandfonline.com/loi/tejs20Fluctuations in running and skill-relatedperformance in elite rugby union match-playMathieu Lacome, Julien Piscione, Jean-Philippe Hager & Chris CarlingTo cite this article: Mathieu Lacome, Julien Piscione, Jean-Philippe Hager & Chris Carling(2016): Fluctuations in running and skill-related performance in elite rugby union match-play,European Journal of Sport Science, DOI: 10.1080/17461391.2016.1220986To link to this article: lished online: 30 Aug 2016.Submit your article to this journalArticle views: 327View related articlesView Crossmark dataFull Terms & Conditions of access and use can be found tion?journalCode tejs20Download by: [UNIVERSITY OF BRIGHTON]Date: 14 November 2016, At: 11:59

European Journal of Sport Science, 6ORIGINAL ARTICLEFluctuations in running and skill-related performance in elite rugbyunion match-playMATHIEU LACOME1, JULIEN PISCIONE1, JEAN-PHILIPPE HAGER1, &CHRIS CARLING21Research Department, French Rugby Union, Marcoussis, France & 2Institute of Coaching and Performance, University ofCentral Lancashire, Preston, UKAbstractThis study investigated end-game and transient changes in running activities and whether these were concomitantlyassociated with reductions in skill-related performance in senior international rugby union match-play. Altogether, 18official matches were analysed (322 individual observations) using computerised video-based tracking and event coding(Amisco Pro , SUP, Nice, France). In forwards and backs, trivial to small reductions (% difference: 2.1, 1.3 to 10.0, 4.0%) in total distance and that covered at high speeds ( 18.0 km h 1) occurred in the second- versus the first-half whilethere were trivial differences in skill-related performance measures ( 2.3, 4.5 to 7.5, 14.0%). In both positions, smallto moderate declines ( 42, 10 to 21, 7%) occurred in high-speed running in the final 10-min and 5-min periodsversus mean values for all other 10-min and 5-min periods throughout the game while only small changes ( 18, 51 to13, 41%) in skill-related performance were observed. Trivial changes in running and skill-related performance ( 11, 74to 7, 39%) were observed in the 5-min period immediately following the most intense 5-minute periods of playcompared to mean performance over the other 5-min periods. These findings suggest that international rugby unionplayers were generally able to maintain skill-related performance over the course of match-play even when declines inrunning performance occurred.Keywords: Performance; fatigue; team sport; skillIntroductionIn elite rugby union match-play, a large body of literature has described the physical demands usingtime-motion analyses of running activities, such asthe total distance covered and that travelled at highspeeds. In comparison, patterns of fatigue represented by declines in distances covered havereceived less attention. Investigations have nevertheless reported that running activity (e.g. total distance,high-speed running) was frequently unaffected acrossmatch halves, quarters and 10-minute intervals(Cunniffe, Proctor, Baker, & Davies, 2009; Duthie,Pyne, & Hooper, 2005; Lacome, Piscione, Hager,& Bourdin, 2014; Roberts, Trewartha, Higgitt, ElAbd, & Stokes, 2008). Thus, it would seem thatelite players generally do not experience accumulated‘fatigue’ manifested by a progressive drop in runningactivity over the course of play although furtherresearch particularly at international standards andusing a larger number of match observations is warranted. Studies notably in elite rugby league(Kempton, Sirotic, & Coutts, 2014) and soccer(Bradley & Noakes, 2013; Carling & Dupont,2011) have also examined running performance inthe very latter stages of match-play (e.g. final 5minute period). Kempton et al. (2014) reportedthat overall distance covered in the final 5 minutesof rugby league matches declined significantly( 14% decrease) in comparison to the first 5minute period suggesting that players were possiblyfatigued in the closing stages of play. A similar temporal analysis of running performance is warrantedin elite rugby union as previous analyses of 10minute intervals did not demonstrate any reductionsin activity. This information has the potential toCorrespondence: Mathieu Lacome, Research Department, French rugby union, 3-5 rue Jean de Montaigu, 91460 Marcoussis, France.Email: mathieu.lacome@ffr.fr 2016 European College of Sport Science

2M. Lacome et al.identify whether fatigue represented by a decline indistance run occurs at the very end of play therebyinforming coach decision-making (e.g. substitutions,tactics) particularly if the match result is stillundecided.To our knowledge, there is no information onthe existence of transient fatigue represented bytemporary reductions in running activity in eliterugby union competition. Research in elite soccerand rugby league has shown that high-speed distancein the 5-minute period immediately following themost intense 5-minute period of activity wasreduced in comparison to the mean value for all theother 5-minute match periods (Bradley & Noakes,2013; Kempton, Sirotic, Cameron, & Coutts,2013). However, conflicting results exist in rugbyleague (Hulin & Gabbett, 2015; Hulin, Gabbett,Kearney, & Corvo, 2015) as sub-elite and eliteplayers maintained performance following thepeak 5-min activity period. Research into these aforementioned areas is warranted in an attempt todetermine whether transient changes also occur inelite rugby union match-play. Data could informprescription of physical conditioning regimens inorder to help prepare players cope with the mostintense running demands that arise during shortperiods of play (Jones, West, Crewther, Cook, &Kilduff, 2015).Up to now, no study has examined the potentialassociation between fatigue indirectly determinedby time-motion analyses and skill-related performance in elite rugby union match-play. In otherteam sports contrasting findings have been reported(Rampinini, Impellizzeri, Castagna, Coutts, &Wisloff, 2009; Sirotic, Coutts, Knowles, & Catterick,2009). In elite soccer, moderate declines occurred inhigh-speed running following short intense phasesand at the end of match-play (effect sizes: 0.7)whereas only small reductions (effect sizes: 0.4)in the frequency of and success rates in technicalactions such as passing (Carling & Dupont, 2011)were concomitantly observed. In contrast, total distance covered, the ‘quality’ of skill performance,and the number of ball involvements were allreduced both transiently and in the very finalstages of matches in rugby league players withthese drops possibly linked to glycogen depletion inindividual muscle fibres, dehydration arising fromhyperthermia and declines in cognitive function(Kempton et al., 2013). Similar information wouldbe pertinent for elite rugby union training settingsto determine, for example, whether there is a needfor players to practice game skills under ‘fatigued’conditions. Consequently, the aim of this study inelite rugby union match-play was to examine endgame and transient changes in running performanceusing time-motion analyses and determine whetherthese were accompanied by altered skill-relatedperformance.MethodIn this study, male player performance in official international rugby union competition was examined. Atotal of 18 matches of which 7 test (autumn tours)and 11 Six Nations tournament matches playedbetween 2005 and 2011 were analysed. All playerswere either members of the French national team ortheir direct opponents (nine different teams) and completed all matches in their entirety. Players either substituted or replaced were not included. Altogether,322 match performance observations for 188 differentplayers were collected. In order to conduct interpositional comparisons, players were subdivided intoforwards (match observations: n 154) and backs(match observations: n 168). Further breakdown ofplaying positions was not feasible due to insufficientnumbers of match observations. To ensure player confidentiality, all performance data were anonymisedbefore the analysis. Approval for the study wasobtained from the Fédération Française de Rugby.Study designAn optical computerised player tracking system(Amisco Pro , Sport Universal Process, Nice,France) was used to analyse performance in international rugby union match-play at the Stade deFrance stadium (St Denis, France). This systempassively tracked the movements of every playerover the entire course of play. Simultaneously,trained operators coded post-match each technicalaction involving the ball. The workings and qualitycontrol of AMISCO Pro have been described elsewhere (Carling, Bloomfield, Nelsen, & Reilly, 2008;Carling, Williams, & Reilly, 2005; Lacome et al.,2014; Randers, Mujika, & Hewitt, 2010).Two categories of performance measures wereemployed:(1)(2)Running performance: total distance run andthat covered in high-speed running. Thelatter was also categorised according toteam ball possession: running during ownteam and opponent possession. Movementsrecorded at speeds above 18.0 km h 1 wereconsidered high-speed running actions(Roberts et al., 2008).Measures of skill-related performance definedin the and coded internally by AMISCO Pro trained company match analysts included thetotal number of passes and tackles and

Performance fluctuations in rugby union match-play 3success rates in these events. Passes weredeemed unsuccessful when a player attempteda pass to a team mate but the ball did not go tohand. Tackles were coded as unsuccessful ifthe tackling player attempted to tackle butwas unable to stop an opponent moving withthe ball in hand.The effective playing time (total time the ball was inplay) was also determined as this affects time-relatedchanges in running and skill-related performance(Carling & Dupont, 2011).Data collection proceduresTo investigate accumulated and transient changes inmatch performance in forwards and backs, runningand skill-related performance measures were compared between match halves and across 5- and 10min intervals. Performance data collected duringstoppage time were not included in the analysis tofacilitate comparisons.Accumulated changes in match performance wereinvestigated by comparing the above running andskill-related performance measures across first- andsecond-half halves. Performance was also examinedfor the first 10- and 5-min intervals versus both thefinal 10- and 5-min intervals and the mean for allother 10- and 5-min intervals (minus first and final10- and 5-min periods).To analyse transient changes in running and skillrelated performance, data were compared betweenthe peak 5-min period of high-speed running activity,the following 5-min period, and the mean of all other5-min periods (minus the peak and the following 5min periods) (Carling & Dupont, 2011). Data forplayers performing their peak 5-min period at theend of a half were removed. The peak 5-min periodof running activity was considered to represent themost intense match-play interval in terms of highspeed running output (Bradley et al., 2009).Statistical analysisStatistical analyses were performed using R statisticalsoftware (R. 3.1.0, R Foundation for Statistical Computing) using the lme4 and psychometric package.Means and standard deviations for each group orplaying time were derived from a generalised linearmodel, with the distribution and link function contingent upon the nature of the dependent variable. Theoverdispersed Poisson distribution was chosen formodelling the data from the notational analysis, andthe normal distribution was chosen for distancesfrom the time-motion analysis. For each analysis,the playing time (halves, 10-min and 5-min periods)was included as a fixed effect while players andteams were included as random effects. The % differences between mean values with 90% confidenceintervals (CI) are reported.A magnitude-based inferential approach to statistics was adopted based on recent recommendations(Batterham & Hopkins, 2006; Winter, Abt, & Nevill,2014). Effect sizes (ES) were quantified to indicatethe practical meaningfulness of the differences inmean values. Standardisation was performed withthe estimated marginal means and associated variance provided by the generalised linear model. TheES was classified as trivial ( 0.2), small ( 0.2–0.6),moderate ( 0.6–1.2), large ( 1.2–2.0) and verylarge ( 2.0–4.0) based on the guidelines of Batterham and Hopkins (Batterham & Hopkins, 2006). Ifthe 90% CI over-lapped positive and negativevalues, the magnitude was deemed unclear. Thechances that the changes in running or technical performance were greater for a group (i.e. greater thanthe smallest worthwhile change, SWC (0.2 multipliedby the between-subject standard deviation, based onCohen’s d principle)), similar or smaller than theother group, were calculated. Quantitative chancesof greater or smaller changes in performance variables were assessed qualitatively as follows: 1%,almost certainly not; 1–5%, very unlikely; 5–25%,probably not; 25–75%, possibly; 75–97.5%, likely;97.5–99%, very likely; 99%, almost certain(Hopkins, Marshall, Batterham, & Hanin, 2009).In order to ease reading of the results, inferencesand effect magnitudes were collated in the textsection by calculating the likelihood of having theappropriate effect.ResultsFirst- versus second-half performanceTable I reports a possible small decline in total distance covered by forwards in the second- comparedto the first-half (% difference: 2.1, 1.3%; %chance of having greater/trivial/lower performance:0/36/64). Backs experienced very likely smallreductions in total distance covered during thesecond- versus the first-half ( 3.8, 1.1%; 0/1/99)as well as a likely small reduction in distancecovered at high speeds ( 10.0, 4.0%; 0/15/85).Regarding high-speed distance covered while in possession of the ball or not and skill-related performance in forwards and backs, only trivial differenceswere observed between match halves (ES: 0.19, 0.10 to 0.09, 0.17).Trivial effect size differences were observed for thefrequency and success rates in skill-related performance measures across halves in backs and forwards.

4M. Lacome et al.Table I. Comparisons of running and skill-related performance for back and forwards across the first- and second-halves of match-play.Performance for forwards (n 154)TD (m)HS (m)HS (%)HS in posses (m)HS out of posses (m)Passes (n)Tackles (n)Successful passes (%)Successful tackles (%)Effective playing time (s)TD (m min of effective time)HS (m min of effective time)Performance for backs (n 168)TD (m)HS (m)HS (%)HS in posses (m)HS out of posses (m)Passes (n)Tackles (n)Successful passes (%)Successful tackles (%)Effective playing time (s)TD (m min of effective time)HS (m min of effective time)First halfSecond halfDiff% (90% CI)ES (90% CI)% chances3122 248249 1317.8 3.8130 68107 731.64 1.873.81 2.3492 1987 20900 77209.8 28.116.9 10.13056 260228 1237.3 3.7119 70101 721.76 1.964.05 2.7292 2485 18957 103193.7 32.014.4 8.7 2.1, 1.3 8.4, 5.6 6.8, 5.2 8.1, 6.6 5.6, 9.47.5, 14.06.3, 12.0 0.77, 4.7 2.3, 4.56.2, 1.8 7.7, 1.7 15.0, 5.7 0.23, 0.14 0.13, 0.09 0.11, 0.085 0.12, 0.10 0.07, 0.120.05, 0.090.09, 0.17 0.04, 0.22 0.10, 0.200.62, 0.18 0.64, 0.14 0.23, /85/111/79/21100/0/00/32/680/30/703515 289432 13212.2 3.3228 86165 705.19 9.262.81 2.3892 1682 27897 75237 2929 103381 322389 12611.4 3.3211 90151 745.50 8.592.81 2.1794 1083 27952 108215 3825 8 3.8, 1.1 10.0, 4.0 6.6, 3.5 7.8, 5.9 8.6, 7.06, 110, 132.6, 4.11.0, 6.46.2, 1.8 8.9, 1.6 16.0, 3.7 0.35, 0.10 0.26, 0.10 0.19, 0.10 0.17, 0.13 0.18, 0.140.03, 0.045 0.00, 0.140.12, 0.190.04, 0.240.60, 0.17 0.72, 0.13 0.43, 124/75/013/82/5100/0/00/7/930/0/100Notes: ES, effect size; % chances, % chances that the true difference is ive/trivial/ ive; TD, total distance; HS, high-speed distance; HS (%),high-speed distance relative to total distance.When normalised to effective playing time, therewas a possibly moderate decline in total distancecovered by forwards in the second- versus the firsthalf ( 7.7, 1.7%; 0/32/68) as well as a possiblysmall decline in high-speed distance ( 15.0, 5.7%; 0/30/70). In backs, there was a likely moderate decline in total distance covered ( 8.9, 1.6%; 0/7/93) and a most likely small decline in high-speeddistance ( 16.0, 3.7%; 0/0/100) in the secondhalf. Unclear or trivial effect size differences wereobserved for the frequency of passes and tackleswhen normalised to effective playing time in forwardsand backs.End-game performanceFinal 10-min interval. In backs and forwards, possiblymoderate to likely large declines (% difference range: 17, 4% to 47, 20%) in measures of runningperformance were observed for the first 10-minversus the 70–80-min period (Table II). Regardingthe 70–80-min period versus the mean for other 10min periods, there were most likely to possiblesmall declines ( 28, 18 to 7.1, 2.1%) inmeasures of running performance for both positionalroles. When normalised to effective playing time,there were possibly small declines in distancecovered at high speeds in forwards ( 18, 13%;0/48/52) and likely small declines in backs ( 16, 8%; 0/10/90).Regarding skill-related performance in backs andforwards, trivial or unclear effect size differences inthe frequency and success rates of skill-related performance measures were observed between the first10-min versus the 70–80-min period. Similarly,there were trivial or unclear effect size differences inthe frequency and success rates of skill-related performance measures between the 70–80-min periodversus the mean for all 10-min periods.Final 5-min interval. In Table III, likely moderate tolikely large declines ( 24, 6.6% to 68, 33) inrunning performance are reported for backs and forwards for the first 5-min versus the 75–80-minperiod. In comparison to the mean for 5-minperiods, backs experienced very likely small to likelymoderate declines in running performance in the75–80-min period ( 10.2, 2.9 to 42, 10%)while forwards showed possibly to very likely smallreductions ( 8.9, 3.5 to 42, 23%).When results were expressed relative to effectiveplaying time, very likely small to possibly largedeclines ( 11, 5% to 65, 24%) in running performance were observed for forwards and backs

Table II. Running and skill-related performance in back and forwards during the first 10-min period, the last 10-min period and the mean 10-min period of match-play.End-game fluctuationsObserved valuesFirst10 minLast 10 minLast 10 min vs First 10 minMean10 minDiff % (90%CI)712 102766 57 18.0, 5.2HS (m)84 5244 3658 31 47, 20HS (%)9.4 5.35.9

ORIGINAL ARTICLE Fluctuations in running and skill-related performance in elite rugby union match-play MATHIEU LACOME1, JULIEN PISCIONE1, JEAN-PHILIPPE HAGER1,& CHRIS CARLING2 1Research Department, French Rugby Union, Marcoussis, France & 2Institute of Coaching and Performance, University of Central Lancashire, Preston, UK

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