Profiling Professional Rugby Union Activity After Peak Match Periods

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Samuel T. Howe Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia

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Robert J. Aughey Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia

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William G. Hopkins Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia

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Andrew M. Stewart Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia

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The aim of this investigation was to quantify professional rugby union player activity profiles after the most intense (peak) passages of matches. Movement data were collected from 30 elite and 30 subelite professional rugby union athletes across respective competitive seasons. Accelerometer-derived PlayerLoad and global navigation satellite system–derived measures of mean speed and metabolic power were analyzed using a rolling-average method to identify the most intense 5- to 600-second passages (ie, worst-case scenarios) within matches. Player activity profiles immediately post their peak 5- to 600-second match intensity were identified using 5 epoch duration-matched intervals. Mean speed, metabolic power, and PlayerLoad declined sharply (∼29%–86%) after the most intense 5 to 600 seconds of matches. Following the most intense periods of rugby matches, exercise intensity declined below the average match-half intensity 81% of the time and seldom returned to or exceeded it, likely due to a host of individual physical and physiological characteristics, transient and/or accumulative fatigue, contextual factors, and pacing strategies. Typically, player exercise intensities after the most intense passages of matches were similar between match halves, positional groups, and levels of rugby competition. Accurate identification of the peak exercise intensities of matches and movement thereafter using novel methodologies has improved the limited understanding of professional rugby union player activity profiles following the worst-case scenarios of matches. Findings of the present study may inform match-representative training prescription, monitoring, and tactical match decisions (eg, substitutions and positional changes).

Aughey https://orcid.org/0000-0002-0285-8516

Hopkins https://orcid.org/0000-0002-7066-4000

Stewart is now with Central Queensland University, Rockhampton, QLD, Australia, https://orcid.org/0000-0001-5490-7976

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  • Expand
  • 1.

    Duthie G, Pyne D, Hooper S. Applied physiology and game analysis of rugby union. Sports Med. 2003;33(13):973991. doi:10.2165/00007256-200333130-00003

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Delaney JA, Thornton HR, Pryor JF, Stewart AM, Dascombe BJ, Duthie GM. Peak running intensity of international rugby: implications for training prescription. Int J Sports Physiol Perform. 2016;12(8):10391045. doi:10.1123/ijspp.2016-0469

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Faude O, Koch T, Meyer T. Straight sprinting is the most frequent action in goal situations in professional football. J Sports Sci. 2012;30(7):625631. doi:10.1080/02640414.2012.665940

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Gabbett T, Gahan C. Repeated high-intensity effort activity in relation to tries scored and conceded during rugby league match-play. Int J Sports Physiol Perform. 2016;11(4):530534. doi:10.1123/ijspp.2015-0266

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Edgecomb SJ, Norton KI. Comparison of global positioning and computer-based tracking systems for measuring player movement distance during Australian Football. J Sci Med Sport. 2006;9(1–2):2532. doi:10.1016/j.jsams.2006.01.003

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Aughey RJ. Australian football player work rate: evidence of fatigue and pacing. Int J Sports Physiol Perform. 2010;5(3):394405. doi:10.1123/ijspp.5.3.394

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Duthie G, Pyne D, Hooper S. Time motion analysis of 2001 and 2002 super 12 rugby. J Sports Sci. 2005;23(5):523530. doi:10.1080/02640410410001730188

  • 8.

    Coutts AJ, Quinn J, Hocking J, Castagna C, Rampinini E. Match running performance in elite Australian rules football. J Sci Med Sport. 2010;13(5):543548. doi:10.1016/j.jsams.2009.09.004

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Varley MC, Gabbett T, Aughey RJ. Activity profiles of professional soccer, rugby league and Australian football match play. J Sports Sci. 2014;32(20):18581866. doi:10.1080/02640414.2013.823227

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Jones MR, West DJ, Crewther BT, Cook CJ, Kilduff LP. Quantifying positional and temporal movement patterns in professional rugby union using global positioning system. Eur J Sport Sci. 2015;15(6):488496. doi:10.1080/17461391.2015.1010106

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Cunningham DJ, Shearer DA, Carter N, et al. Assessing worst case scenarios in movement demands derived from global positioning systems during international rugby union matches: rolling averages versus fixed length epochs. PLoS One. 2018;13(4):e0195197. doi:10.1371/journal.pone.0195197

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Ferraday K, Hills SP, Russell M, et al. A comparison of rolling averages versus discrete time epochs for assessing the worst-case scenario locomotor demands of professional soccer match-play. J Sci Med Sport. 2020;23(8):764769. doi:10.1016/j.jsams.2020.01.002

    • Search Google Scholar
    • Export Citation
  • 13.

    Mohr M, Krustrup P, Bangsbo J. Match performance of high-standard soccer players with special reference to development of fatigue. J Sports Sci. 2003;21(7):519528. doi:10.1080/0264041031000071182

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Waldron M, Highton J. Fatigue and pacing in high-intensity intermittent team sport: an update. Sports Med. 2014;44(12):16451658. doi:10.1007/s40279-014-0230-6

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Kempton T, Coutts AJ. Factors affecting exercise intensity in professional rugby league match-play. J Sci Med Sport. 2016;19(6):504508. doi:10.1016/j.jsams.2015.06.008

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Kempton T, Sirotic AC, Cameron M, Coutts AJ. Match-related fatigue reduces physical and technical performance during elite rugby league match-play: a case study. J Sports Sci. 2013;31(16):17701780. doi:10.1080/02640414.2013.803583

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Varley MC, Elias GP, Aughey RJ. Current match-analysis techniques’ underestimation of intense periods of high-velocity running. Int J Sports Physiol Perform. 2012;7(2):183185. doi:10.1123/ijspp.7.2.183

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Howe ST, Aughey RJ, Hopkins WG, Cavanagh BP, Stewart AM. Sensitivity, reliability and construct validity of GPS and accelerometers for quantifying peak periods of rugby competition. PLoS One. 2020;15(7):e0236024. doi:10.1371/journal.pone.0236024

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Howe ST, Aughey RJ, Hopkins WG, Stewart AM. Modeling professional rugby union peak intensity–duration relationships using a power law. Int J Sports Physiol Perform. 2022;1:337. doi:10.1123/ijspp.2021-0337

    • Search Google Scholar
    • Export Citation
  • 20.

    TrackVU. FIFA Electronic Performance & Tracking Systems (EPTS) Performance Test Report, Catapult S5. 2019. https://football-technology.fifa.com/media/172169/catapultgps-s5-epts-report-nov2018.pdf

    • Search Google Scholar
    • Export Citation
  • 21.

    Delaney JA, Scott TJ, Thornton HR, et al. Establishing duration-specific running intensities from match-play analysis in rugby league. Int J Sports Physiol Perform. 2015;10(6):725731. doi:10.1123/ijspp.2015-0092

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Akenhead R, Nassis GP. Training load and player monitoring in high-level football: current practice and perceptions. Int J Sports Physiol Perform. 2016;11(5):587593. doi:10.1123/ijspp.2015-0331

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Barrett S, Midgley A, Lovell R. Playerload™: reliability, convergent validity, and influence of unit position during treadmill running. Int J Sports Physiol Perform. 2014;9(6):945952. doi:10.1123/ijspp.2013-0418

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Delaney J, Duthie G, Thornton H, Scott TJ, Gay D, Dascombe BJ. Acceleration-based running intensities of professional rugby league match-play. Int J Sports Physiol Perform. 2016;11(6):802806. doi:10.1123/ijspp.2015-0424

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Rampinini E, Alberti G, Fiorenza M, et al. Accuracy of GPS devices for measuring high-intensity running in field-based team sports. Int J Sports Med. 2015;36(1):4953. doi:10.1055/s-0034-1385866

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Buchheit M, Manouvrier C, Cassirame J, Morin JB. Monitoring locomotor load in soccer: is metabolic power, powerful? Int J Sports Med. 2015;36(14):11491155. doi:10.1055/s-0035-1555927

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exercise. 2009;41(1):312. doi:10.1249/MSS.0b013e31818cb278

    • Search Google Scholar
    • Export Citation
  • 28.

    Hopkins WG. A spreadsheet to compare means of two groups. Sportsci. 2007;11:2224.

  • 29.

    Smith TB, Hopkins WG. Variability and predictability of finals times of elite rowers. Med Sci Sports Exercise. 2011;43(11):21552160. doi:10.1249/MSS.0b013e31821d3f8e

    • Search Google Scholar
    • Export Citation
  • 30.

    Rafi Z, Greenland S. Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise. BMC Med Res Methodol. 2020;20:244. doi:10.17605/OSF.IO/6W8G9

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Hopkins WG. Replacing statistical significance and non-significance with better approaches to sampling uncertainty. Front Physiol. 2022;13:962132. doi:10.3389/fphys.2022.962132

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Hopkins WG, Batterham AM. Error rates, decisive outcomes and publication bias with several inferential methods. Sports Med. 2016;46(10):15631173. doi:10.1007/s40279-016-0517-x

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Kempton T, Sirotic AC, Coutts AJ. An integrated analysis of match-related fatigue in professional rugby league. J Sports Sci. 2015;33(1):3947. doi:10.1080/02640414.2014.921832

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Ament W, Verkerke GJ. Exercise and fatigue. Sports Med. 2009;39(5):389422.

  • 35.

    Gabbett TJ. Influence of the opposing team on the physical demands of elite rugby league match play. J Strength Cond Res. 2013;27(6):16291635. doi:10.1519/JSC.0b013e318274f30e

    • Search Google Scholar
    • Export Citation
  • 36.

    Murray NB, Gabbett TJ, Chamari K. Effect of different between-match recovery times on the activity profiles and injury rates of national rugby league players. J Strength Cond Res. 2014;28(12):34763483. doi:10.1519/JSC.0000000000000603

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Johnston RD, Weaving D, Hulin BT, Till K, Jones B, Duthie G. Peak movement and collision demands of professional rugby league competition. J Sports Sci. 2019;37(18):21442151. doi:10.1080/02640414.2019.1622882

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Gronow D, Dawson B, Heasman J, Rogalski B, Peeling P. Team movement patterns with and without ball possession in Australian Football League players. Int J Perform Anal Sport. 2014;14(3):635651. doi:10.1080/24748668.2014.11868749

    • Search Google Scholar
    • Export Citation
  • 39.

    Sullivan C, Bilsborough JC, Cianciosi M, Hocking J, Cordy J, Coutts AJ. Match score affects activity profile and skill performance in professional Australian Football players. J Sci Med Sport. 2014;17(3):326331. doi:10.1016/j.jsams.2013.05.001

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Bradley PS, Carling C, Archer D, et al. The effect of playing formation on high-intensity running and technical profiles in English FA Premier League soccer matches. J Sports Sci. 2011;29(8):821830. doi:10.1080/02640414.2011.561868

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41.

    Gabbett TJ, Polley C, Dwyer DB, Kearney S, Corvo A. Influence of field position and phase of play on the physical demands of match-play in professional rugby league forwards. J Sci Med Sport. 2014;17(5):556561. doi:10.1016/j.jsams.2013.08.002

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Hulin BT, Gabbett TJ, Kearney S, Corvo A. Physical demands of match play in successful and less-successful elite rugby league teams. Int J Sports Physiol Perform. 2015;10(6):703710. doi:10.1123/ijspp.2014-0080

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43.

    Duthie GM, Thornton HR, Delaney JA, McMahon JT, Benton DT. Relationship between physical performance testing results and peak running intensity during professional rugby league match play. J Strength Cond Res. 2017;34(12):35063513. doi:10.1519/JSC.0000000000002273

    • Search Google Scholar
    • Export Citation
  • 44.

    Furlan N, Waldron M, Shorter K, et al. Running intensity fluctuations in elite rugby sevens performance. Int J Sports Physiol Perform. 2015;10(6):802807. doi:10.1123/ijspp.2014-0315

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45.

    Black GM, Gabbett TJ, Naughton GA, McLean BD. The effect of intense exercise periods on physical and technical performance during elite Australian Football match-play: a comparison of experienced and less experienced players. J Sci Med Sport. 2016;19(7):596602. doi:10.1016/j.jsams.2015.07.007

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46.

    Howe ST, Aughey RJ, Hopkins WG, Cavanagh BP, Stewart AM. Quantifying important differences in athlete movement during collision-based team sports: accelerometers outperform global positioning systems. In 2017 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL). IEEE; 2017. doi:10.1109/ISISS.2017.7935655

    • Search Google Scholar
    • Export Citation
  • 47.

    Osgnach C, Poser S, Bernardini R, Rinaldo R, di Prampero PE. Energy cost and metabolic power in elite soccer: a new match analysis approach. Med Sci Sports Exercise. 2010;42(1):170178. doi:10.1249/MSS.0b013e3181ae5cfd

    • Search Google Scholar
    • Export Citation
  • 48.

    Boyd LJ, Ball K, Aughey RJ. Quantifying external load in Australian football matches and training using accelerometers. Int J Sports Physiol Perform. 2013;8(1):4451. doi:10.1123/ijspp.8.1.44

    • PubMed
    • Search Google Scholar
    • Export Citation
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