Automatic detection of one-on-one tackles and ruck events using microtechnology in rugby union

Published:January 06, 2019DOI:



      To automate the detection of ruck and tackle events in rugby union using a specifically-designed algorithm based on microsensor data.


      Cross-sectional study.


      Elite rugby union players wore microtechnology devices (Catapult, S5) during match-play. Ruck (n = 125) and tackle (n = 125) event data was synchronised with video footage compiled from international rugby union match-play ruck and tackle events. A specifically-designed algorithm to detect ruck and tackle events was developed using a random forest classification model. This algorithm was then validated using 8 additional international match-play datasets and video footage, with each ruck and tackle manually coded and verified if the event was correctly identified by the algorithm.


      The classification algorithm’s results indicated that all rucks and tackles were correctly identified during match-play when 79.4 ± 9.2% and 81.0 ± 9.3% of the random forest decision trees agreed with the video-based determination of these events. Sub-group analyses of backs and forwards yielded similar optimal confidence percentages of 79.7% and 79.1% respectively for rucks. Sub-analysis revealed backs (85.3 ± 7.2%) produced a higher algorithm cut-off for tackles than forwards (77.7 ± 12.2%).


      The specifically-designed algorithm was able to detect rucks and tackles for all positions involved. For optimal results, it is recommended that practitioners use the recommended cut-off (80%) to limit false positives for match-play and training. Although this algorithm provides an improved insight into the number and type of collisions in which rugby players engage, this algorithm does not provide impact forces of these events.


      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Journal of Science and Medicine in Sport
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Chambers R.
        • Gabbett T.J.
        • Cole M.H.
        • et al.
        The use of wearable microsensors to quantify sport-specific movements.
        Sports Med. 2015; 45: 1065-1081
        • Cummins C.
        • Orr R.
        • O’Connor H.
        • et al.
        Global positioning systems (GPS) and microtechnology sensors in team sports: a systematic review.
        Sports Med. 2013; 43: 1025-1042
        • Lacome M.
        • Piscione J.
        • Hager J.P.
        • et al.
        A new approach to quantifying physical demand in rugby union.
        J. Sports Sci. 2014; 32: 290-300
        • Hendricks S.
        • van Niekerk T.
        • Sin D.W.
        • et al.
        Technical determinants of tackle and ruck performance in International rugby union.
        J. Sports Sci. 2018; 36: 522-528
        • Reardon C.
        • Tobin D.P.
        • Delahunt E.
        Application of individualized speed thresholds to interpret position specific running demands in elite professional rugby union: a GPS study.
        PLoS One. 2015; 10e0133410
        • Austin D.
        • Gabbett T.
        • Jenkins D.
        Repeated high-intensity exercise in professional rugby union.
        J. Sports Sci. 2011; 29: 1105-1112
        • Reardon C.
        • Tobin D.P.
        • Tierney P.
        • et al.
        Collision count in rugby union: a comparison of micro-technology and video analysis methods.
        J. Sports Sci. 2017; 35: 2028-2034
        • Roberts S.P.
        • Trewartha G.
        • Higgitt R.J.
        • et al.
        The physical demands of elite English rugby union.
        J. Sports Sci. 2008; 26: 825-833
        • Gabbett T.J.
        Quantifying the physical demands of collision sports: does microsensor technology measure what it claims to measure?.
        J. Strength Cond. Res. 2013; 27: 2319-2322
        • McNamara D.J.
        • Gabbett T.J.
        • Blanch P.
        • et al.
        The relationship between variables in wearable microtechnology devices and cricket fast-bowling intensity.
        Int. J. Sports Physiol. Perform. 2018; 13: 135-139
        • McNamara D.J.
        • Gabbett T.J.
        • Chapman P.
        • et al.
        The validity of microsensors to automatically detect bowling events and counts in cricket fast bowlers.
        Int. J. Sports Physiol. Perform. 2015; 10: 71-75
        • Murray N.B.
        • Black G.M.
        • Whiteley R.J.
        • et al.
        Automatic detection of pitching and throwing events in baseball with inertial measurement sensors.
        Int. J. Sports Physiol. Perform. 2017; 12: 533-537
        • Kelly D.
        • Coughlan G.F.
        • Green B.S.
        • et al.
        Automatic detection of collisions in elite level rugby union using a wearable sensing device.
        Sports Eng. 2012; 15: 81-92
        • Gabbett T.
        • Jenkins D.
        • Abernethy B.
        Physical collisions and injury during professional rugby league skills training.
        J. Sci. Med. Sport. 2010; 13: 578-583
        • Hulin B.T.
        • Gabbett T.J.
        • Johnston R.D.
        • et al.
        Wearable microtechnology can accurately identify collision events during professional rugby league match-play.
        J. Sci. Med. Sport. 2017; 20: 638-642
        • Gastin P.B.
        • McLean O.
        • Spittle M.
        • et al.
        Quantification of tackling demands in professional Australian football using integrated wearable athlete tracking technology.
        J. Sci. Med. Sport. 2013; 16: 589-593
        • Gastin P.B.
        • McLean O.C.
        • Breed R.V.
        • et al.
        Tackle and impact detection in elite Australian football using wearable microsensor technology.
        J. Sports Sci. 2014; 32: 947-953
        • Wheeler K.W.
        • Askew C.D.
        • Sayers M.G.
        Effective attacking strategies in rugby union.
        Eur. J. Sport Sci. 2010; 10: 237-242
        • Fuller C.W.
        • Ashton T.
        • Brooks J.H.
        • et al.
        Injury risks associated with tackling in rugby union.
        Br. J. Sports Med. 2010; 44: 159-167
        • Hendricks S.
        • Matthews B.
        • Roode B.
        • et al.
        Tackler characteristics associated with tackle performance in rugby union.
        Eur. J. Sport Sci. 2014; 14: 753-762
        • Cunniffe B.
        • Proctor W.
        • Baker J.S.
        • et al.
        An evaluation of the physiological demands of elite rugby union using Global Positioning System tracking software.
        J. Strength Cond. Res. 2009; 23: 1195-1203
      1. – accessed on 30th January 2018.

        • Quarrie K.L.
        • Hopkins W.G.
        Tackle injuries in professional Rugby Union.
        Am. J. Sports Med. 2008; 36: 1705-1716
        • Deutsch M.U.
        • Kearney G.A.
        • Rehrer N.J.
        Time — motion analysis of professional rugby union players during match-play.
        J. Sports Sci. 2007; 25: 461-472
        • Song Y.
        • Demirdjian D.
        • Davis R.
        Continuous body and hand gesture recognition for natural human-computer interaction.
        ACM Trans. Interact. Intell. Syst (TiiS). 2012; 2: 5
        • Cippitelli E.
        • Gambi E.
        • Spinsante S.
        • et al.
        Human Action Recognition Based on Temporal Pyramid of Key Poses Using RGB-D Sensors.
        in: International Conference on Advanced Concepts for Intelligent Vision Systems, Springer2016: 510-521
        • Chaaraoui A.A.
        • Flórez-Revuelta F.
        Continuous human action recognition in ambient assisted living scenarios.
        in: International Conference on Mobile Networks and Management, Springer2014: 344-357
        • Chambers R.M.
        • Gabbett T.J.
        • Cole M.H.
        Validity of a microsensor-based algorithm for detecting scrum events in Rugby Union.
        Int. J. Sports Physiol. Perform. 2018; : 1-22
        • Wundersitz D.W.
        • Gastin P.B.
        • Robertson S.
        • et al.
        Validation of a trunk-mounted accelerometer to measure peak impacts during team sport movements.
        Int. J. Sports Med. 2015; 36: 742-746