Sports Medicine

, Volume 48, Issue 6, pp 1357–1368 | Cite as

Modelling Movement Energetics Using Global Positioning System Devices in Contact Team Sports: Limitations and Solutions

  • Adrian J. Gray
  • Kathleen Shorter
  • Cloe Cummins
  • Aron Murphy
  • Mark Waldron
Review Article


Quantifying the training and competition loads of players in contact team sports can be performed in a variety of ways, including kinematic, perceptual, heart rate or biochemical monitoring methods. Whilst these approaches provide data relevant for team sports practitioners and athletes, their application to a contact team sport setting can sometimes be challenging or illogical. Furthermore, these methods can generate large fragmented datasets, do not provide a single global measure of training load and cannot adequately quantify all key elements of performance in contact team sports. A previous attempt to address these limitations via the estimation of metabolic energy demand (global energy measurement) has been criticised for its inability to fully quantify the energetic costs of team sports, particularly during collisions. This is despite the seemingly unintentional misapplication of the model’s principles to settings outside of its intended use. There are other hindrances to the application of such models, which are discussed herein, such as the data-handling procedures of Global Position System manufacturers and the unrealistic expectations of end users. Nevertheless, we propose an alternative energetic approach, based on Global Positioning System-derived data, to improve the assessment of mechanical load in contact team sports. We present a framework for the estimation of mechanical work performed during locomotor and contact events with the capacity to globally quantify the work done during training and matches.


Compliance with Ethical Standards


No financial support was received for the conduct of this study or preparation of this article.

Conflict of interest

Adrian J. Gray, Kathleen Shorter, Aron Murphy and Mark Waldron have no conflicts of interest directly relevant to the content of this article. Cloe Cummins has previously held employment with a micro-technology manufacturer. Cloe Cummins is currently an external consultant to a micro-technology manufacturer in which she produces internal reports on micro-technology device validity and reliability.


  1. 1.
    Viru A, Viru M. Biochemical monitoring of sports training. Champaign: Human Kinetics; 2001.Google Scholar
  2. 2.
    Impellizzeri FM, Rampinini E, Marcora SM. Physiological assessment of aerobic training in soccer. J Sport Sci. 2005;23:583–92.CrossRefGoogle Scholar
  3. 3.
    Blomqvist CG, Saltin B. Cardiovascular adaptations to physical training. Annu Rev Physiol. 1983;45:169–89.CrossRefPubMedGoogle Scholar
  4. 4.
    Holloszy JO, Coyle EF. Adaptations of skeletal muscle to endurance exercise and their metabolic consequences. J Appl Physiol Respir Environ Exerc Physiol. 1984;56:831–8.PubMedGoogle Scholar
  5. 5.
    Jones AM, Carter H. The effect of endurance training on parameters of aerobic fitness. Sports Med. 2000;29:373–86.CrossRefPubMedGoogle Scholar
  6. 6.
    Iaia FM, Rampinini E, Bangsbo J. High-intensity training in football. Int J Sports Physiol Perform. 2009;4:291–306.CrossRefPubMedGoogle Scholar
  7. 7.
    Helgerud J, Engen LC, Wisloff U. Aerobic endurance training improves soccer performance. Med Sci Sports Exerc. 2001;33:1925–31.CrossRefPubMedGoogle Scholar
  8. 8.
    Gaudino P, Iaia FM, Alberti G, et al. Monitoring training in elite soccer players: systematic bias between running speed and metabolic power data. Int J Sports Med. 2013;34:963–8.CrossRefPubMedGoogle Scholar
  9. 9.
    Osgnach C, Poser S, Bernardini R, et al. Energy cost and metabolic power in elite soccer: a new match analysis approach. Med Sci Sports Exerc. 2010;42:170–8.CrossRefPubMedGoogle Scholar
  10. 10.
    Coutts AJ, Kempton T, Sullivan C, et al. Metabolic power and energetic costs of professional Australian football match-play. J Sci Med Sport. 2015;18:219–24.CrossRefPubMedGoogle Scholar
  11. 11.
    Furlan N, Waldron M, Shorter K, et al. Running-intensity fluctuations in elite Rugby Sevens performance. Int J Sports Physiol Perform. 2015;10:802–7.CrossRefPubMedGoogle Scholar
  12. 12.
    Fox R, Patterson SD, Waldron M. The relationship between heart rate recovery and temporary fatigue of kinematic and energetic indices among soccer players. Sci Med Football. 2017;1:132–8.CrossRefGoogle Scholar
  13. 13.
    Boyd LJ, Ball K, Aughey RJ. The reliability of MinimaxX accelerometer for measuring physical activity in Australian football. Int J Sports Physiol Perform. 2011;6:311–21.CrossRefPubMedGoogle Scholar
  14. 14.
    Kempton T, Sirotic AC, Rampinini E, et al. Metabolic power demands of rugby league match play. Int J Sports Physiol Perform. 2015;10:23–8.CrossRefPubMedGoogle Scholar
  15. 15.
    Delaney JA, Thornton HR, Burgess DJ, et al. Duration-specific running intensities of Australian Football match-play. J Sci Med Sport. 2017;20:689–94.CrossRefPubMedGoogle Scholar
  16. 16.
    Sirotic AC, Coutts AJ, Knowles H, et al. A comparison of match demands between elite and semi-elite rugby league competition. J Sport Sci. 2009;27:203–11.CrossRefGoogle Scholar
  17. 17.
    Cunniffe B, Proctor W, Baker JS, et al. An evaluation of the physiological demands of elite rugby union using GPS tracking software. J Strength Cond Res. 2009;23:1195–203.CrossRefPubMedGoogle Scholar
  18. 18.
    Austin D, Gabbett T, Jenkins T. Tackling in professional rugby league. J Strength Cond Res. 2011;25:1659–63.CrossRefPubMedGoogle Scholar
  19. 19.
    Gabbett TJ, Jenkins DG, Abernethy B. Relationships between physiological, anthropometric, and skill qualities and playing performance in professional rugby league players. J Sport Sci. 2011;29:1655–64.CrossRefGoogle Scholar
  20. 20.
    Twist C, Waldron M, Highton J, et al. Neuromuscular, biochemical and perceptual post-match fatigue in professional rugby league forwards and backs. J Sports Sci. 2012;30:359–67.CrossRefPubMedGoogle Scholar
  21. 21.
    Waldron M, Worsfold PR, Twist C, et al. The relationship between physical abilities, ball-carrying and tackling among elite youth rugby league players. J Sports Sci. 2014;32:542–9.CrossRefPubMedGoogle Scholar
  22. 22.
    Petersen C, Pyne D, Portus M, et al. Validity and reliability of GPS units to monitor cricket-specific movement patterns. Int J Sports Physiol Perform. 2009;4:381–93.CrossRefPubMedGoogle Scholar
  23. 23.
    Gray AJ, Jenkins D, Andrews MH, et al. Validity and reliability of GPS for measuring distance travelled in field-based team sports. J Sport Sci. 2010;28:1319–25.CrossRefGoogle Scholar
  24. 24.
    Waldron M, Worsfold P, Twist C, et al. Concurrent validity and test-retest reliability of a global positioning system (GPS) and timing gates to assess sprint performance variables. J Sports Sci. 2011;29:1613–9.CrossRefPubMedGoogle Scholar
  25. 25.
    Varley MC, Fairweather I, Aughey RJ. Validity and reliability of GPS for measuring instantaneous velocity during acceleration, deceleration, and constant motion. J Sport Sci. 2012;30:121–7.CrossRefGoogle Scholar
  26. 26.
    Johnston RJ, Watsford ML, Kelly SJ, et al. Validity and interunit reliability of 10 Hz and 15 Hz GPS units for assessing athlete movement demands. J Strength Cond Res. 2014;28:1649–55.CrossRefPubMedGoogle Scholar
  27. 27.
    Gabbett TJ, Jenkins DG, Abernethy B. Physical demands of professional rugby league training and competition using microtechnology. J Sci Med Sport. 2012;15:80–6.CrossRefPubMedGoogle Scholar
  28. 28.
    Higham DG, Pyne DB, Anson JM, et al. Movement patterns in rugby sevens: effects of tournament level, fatigue and substitute players. J Sci Med Sport. 2012;15:277–82.CrossRefPubMedGoogle Scholar
  29. 29.
    Waldron M, Twist C, Highton J, et al. Movement and physiological match demands of elite rugby league using portable global positioning systems. J Sport Sci. 2011;29:1223–30.CrossRefGoogle Scholar
  30. 30.
    Wisbey B, Montgomery PG, Pyne DB, et al. Quantifying movement demands of AFL football using GPS tracking. J Sci Med Sport. 2010;13:531–6.CrossRefPubMedGoogle Scholar
  31. 31.
    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;43:1025–42.CrossRefPubMedGoogle Scholar
  32. 32.
    Aughey RJ. Australian football player work rate: evidence of fatigue and pacing? Int J Sports Physiol Perform. 2010;5:394–405.CrossRefPubMedGoogle Scholar
  33. 33.
    McLellan CP, Lovell DI. Neuromuscular responses to impact and collision during elite rugby league match play. J Strength Cond Res. 2012;26:1431–40.CrossRefPubMedGoogle Scholar
  34. 34.
    Lovell T, Sirotic A, Impellizzeri F, et al. Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. Int J Sports Physiol Perform. 2013;8:62–8.CrossRefPubMedGoogle Scholar
  35. 35.
    Impellizzeri FM, Rampinini E, Coutts AJ, et al. Use of RPE-based training load in soccer. Med Sci Sport Exerc. 2004;36:1042–7.CrossRefGoogle Scholar
  36. 36.
    Borresen J, Lambert MI. Quantifying training load: a comparison of subjective and objective methods. Int J Sports Physiol Perform. 2008;3:16–30.CrossRefPubMedGoogle Scholar
  37. 37.
    Eston RG, Davies BL, Williams JG. Use of perceived effort ratings to control exercise intensity in young healthy adults. Eur J Appl Physiol. 1987;56:222–4.CrossRefGoogle Scholar
  38. 38.
    Borg G. A simple rating scale for use in physical work tests. Kungliga Fysiografi ska Sallskapets I Lund Forhandlinger. 1962;32:7–15.Google Scholar
  39. 39.
    Krustrup P, Mohr M, Steensberg A, et al. Muscle and blood metabolites during a soccer game: implications for sprint performance. Med Sci Sport Exerc. 2006;38:1165–74.CrossRefGoogle Scholar
  40. 40.
    Ekblom B. Applied physiology of soccer. Sports Med. 1986;3:50–60.CrossRefPubMedGoogle Scholar
  41. 41.
    Drust B, Reilly T, Cable NT. Physiological responses to laboratory-based soccer-specific intermittent and continuous exercise. J Sports Sci. 2000;18:885–92.CrossRefPubMedGoogle Scholar
  42. 42.
    Coutts A, Reaburn P, Abt G. Heart rate, blood lactate concentration and estimated energy expenditure in a semi-professional rugby league team during a match: a case study. J Sport Sci. 2003;21:97–103.CrossRefGoogle Scholar
  43. 43.
    Mclaren SJ, Macpherson TW, Coutts AJ, et al. The relationship between internal and external measures of training load and intensity in team sports: a meta-analysis. Sports Med. 2018;48:641–58.CrossRefPubMedGoogle Scholar
  44. 44.
    Waldron M, Highton J, Daniels M, et al. Preliminary evidence of transient fatigue and pacing during interchanges in rugby league. Int J Sport Physiol Perform. 2013;8:157–64.CrossRefGoogle Scholar
  45. 45.
    Veale JP, Pearce AJ. Physiological responses of elite junior Australian rules footballers during match-play. J Sports Sci Med. 2009;8:314–9.PubMedPubMedCentralGoogle Scholar
  46. 46.
    Bangsbo J. Energy demands in competitive soccer. J Sports Sci. 1994;12:S5–12.PubMedGoogle Scholar
  47. 47.
    Garby L, Astrup A. The relationship between the respiratory quotient and the energy equivalent of oxygen during simultaneous glucose and lipid oxidation and lipogenesis. Acta Physiol Scand. 1987;129:443–4.CrossRefPubMedGoogle Scholar
  48. 48.
    Achten J, Jeukendrup AE. Heart rate monitoring: applications and limitations. Sports Med. 2003;33:517–38.CrossRefPubMedGoogle Scholar
  49. 49.
    Takarada Y. Evaluation of muscle damage after a rugby match with special reference to tackle plays. Br J Sports Med. 2003;37:416–9.CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Smart DJ, Gill ND, Beaven CM, et al. The relationship between changes in interstitial creatine kinase and game-related impacts in rugby union. Br J Sports Med. 2008;42:198–201.CrossRefPubMedGoogle Scholar
  51. 51.
    Oxendale CL, Twist C, Daniels M, et al. The relationship between match-play characteristics of elite rugby league and indirect markers of muscle damage. Int J Sports Physiol Perform. 2016;11:515–21.CrossRefPubMedGoogle Scholar
  52. 52.
    Deutsch MU, Kearney GA, Rehrer NJ. Time–motion analysis of professional rugby union players during match-play. J Sports Sci. 2007;25:461–72.CrossRefPubMedGoogle Scholar
  53. 53.
    Waldron M, Worsfold P, Twist C, et al. A three-season comparison of match performances among selected and unselected elite youth rugby league players. J Sport Sci. 2014;32:1110–9.CrossRefGoogle Scholar
  54. 54.
    Gabbett T, Jenkins D, Abernethy BJ. Physical collisions and injury during professional rugby league skills training. Sci Med Sport. 2010;13:578–83.CrossRefGoogle Scholar
  55. 55.
    Hulin BT, Gabbett TJ, Johnston RD, et al. Wearable microtechnology can accurately identify collision events during professional rugby league match-play. J Sci Med Sport. 2017;20:638–42.CrossRefPubMedGoogle Scholar
  56. 56.
    Gastin PB, McLean OC, Breed RV, et al. Tackle and impact detection in elite Australian football using wearable microsensor technology. J Sports Sci. 2014;32:947–53.CrossRefPubMedGoogle Scholar
  57. 57.
    Hendricks S, Karpul D, Nicolls F, et al. Velocity and acceleration before contact in the tackle during rugby union matches. J Sport Sci. 2012;30:1215–24.CrossRefGoogle Scholar
  58. 58.
    Mommaerts WF. Energetics of muscular contraction. Physiol Rev. 1969;49:427–508.CrossRefPubMedGoogle Scholar
  59. 59.
    Preatoni E, Stokes KA, England ME, et al. The influence of playing level on the biomechanical demands experienced by rugby union forwards during machine scrummaging. Scand J Med Sci Sports. 2013;23:178–84.CrossRefGoogle Scholar
  60. 60.
    Cazzola D, Stone B, Holsgrove TP, et al. Spinal muscle activity in simulated rugby union scrummaging is affected by different engagement conditions. Scand J Med Sci Sports. 2016;26:432–40.CrossRefPubMedGoogle Scholar
  61. 61.
    Danoff PL, Danoff JV. Energy cost and heart rate response to static and dynamic leg exercise. Arch Phys Med Rehabil. 1982;63:130–4.PubMedGoogle Scholar
  62. 62.
    Robergs RA, Gordon T, Reynolds J, et al. Energy expenditure during bench press and squat exercises. J Strength Cond Res. 2007;21:123–30.CrossRefPubMedGoogle Scholar
  63. 63.
    di Prampero P, Fusi S, Sepulcri L, et al. Sprint running: a new energetic approach. J Exp Bio. 2005;208:2809–16.CrossRefGoogle Scholar
  64. 64.
    Minetti A, Moia C, Roi G, et al. Energy cost of walking and running at extreme uphill and downhill slopes. J Appl Physiol. 2002;93:1039–46.CrossRefPubMedGoogle Scholar
  65. 65.
    Bourdon PC, Cardinale M, Murray A. Monitoring athlete training loads: consensus statement. Int J Sport Physiol Perform. 2017;12:161–70.CrossRefGoogle Scholar
  66. 66.
    Osgnach C, Paolini E, Roberti V, et al. Metabolic power and oxygen consumption in team sports: a brief response to Buchheit et al. Int J Sports Med. 2016;37:77–81.CrossRefPubMedGoogle Scholar
  67. 67.
    Buchheit M, Manouvrier C, Cassirame J, et al. Monitoring locomotor load in soccer: is metabolic power powerful? Int J Sports Med. 2015;36:1149–55.CrossRefPubMedGoogle Scholar
  68. 68.
    Highton J, Mullen T, Norris J, et al. The unsuitability of energy expenditure derived from microtechnology for assessing internal load in collision-based activities. Int J Sports Physiol Perform. 2017;12:264–7.CrossRefPubMedGoogle Scholar
  69. 69.
    Oxendale CL, Highton J, Twist C. Energy expenditure, metabolic power and high speed activity during linear and multi-directional running. J Sci Med Sport. 2017;20:957–61.CrossRefPubMedGoogle Scholar
  70. 70.
    Stevens TG, De Ruiter CJ, Van Maurik D, et al. Measured and estimated energy cost of constant and shuttle running in soccer players. Med Sci Sports Exerc. 2015;47:1219–24.CrossRefPubMedGoogle Scholar
  71. 71.
    Arsac LM, Locatelli E. Modeling the energetics of 100-m running by using speed curves of world champions. J Appl Physiol. 2002;92:1781–8.CrossRefPubMedGoogle Scholar
  72. 72.
    Docherty D, Wenger HA, Neary P. Time-motion analysis related to the physiological demands of rugby. J Hum Mov Stud. 1988;14:269–77.Google Scholar
  73. 73.
    Meir R, Arthur D, Forrest M. Time and motion analysis of professional rugby league: a case study. Strength Cond Coach. 1993;1:24–9.Google Scholar
  74. 74.
    King T, Jenkins DG, Gabbett TJ. A time-motion analysis of professional rugby league match-play. J Sports Sci. 2009;27:213–9.CrossRefPubMedGoogle Scholar
  75. 75.
    Brewer J, Davis J. Applied physiology of rugby league. Sports Med. 1995;20:129–35.CrossRefPubMedGoogle Scholar
  76. 76.
    Malone JJ, Lovell R, Varley MC, Coutts AJ. Unpacking the black box: applications and considerations for using GPS devices in sport. Int J Sports Physiol Perform. 2017;12(Suppl. 2):S218–26.CrossRefPubMedGoogle Scholar
  77. 77.
    Kelly SJ, Murphy AJ, Watsford ML, et al. Reliability and validity of sports accelerometers during static and dynamic testing. Int J Sports Physiol Perform. 2015;10:106–11.CrossRefPubMedGoogle Scholar
  78. 78.
    di Prampero PE. The energy cost of human locomotion on land and in water. Int J Sports Med. 1986;7:55–72.CrossRefPubMedGoogle Scholar
  79. 79.
    van Ingen Schenau GJ, Hollander AP. Comment on “A mathematical theory of running” and the applications of this theory. J Biomech. 1987;20:91–5.CrossRefPubMedGoogle Scholar
  80. 80.
    Ward Smith AJ. A mathematical theory of running, based on the first law of thermodynamics, and its application to the performance of world-class athletes. J Biomech. 1985;18:337–49.CrossRefPubMedGoogle Scholar
  81. 81.
    Cavagna GA, Thys H, Zamboni A. The sources of external work in level walking and running. J Physiol. 1976;262:639–57.CrossRefPubMedPubMedCentralGoogle Scholar
  82. 82.
    Hendricks S, Karpul D, Lambert M. Momentum and kinetic energy before the tackle in rugby union. J Sports Sci Med. 2014;13:557–63.PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Adrian J. Gray
    • 1
  • Kathleen Shorter
    • 1
  • Cloe Cummins
    • 1
  • Aron Murphy
    • 1
  • Mark Waldron
    • 1
    • 2
  1. 1.School of Science and TechnologyUniversity of New EnglandArmidaleAustralia
  2. 2.School of Sport, Health and Applied ScienceSt Mary’s UniversityLondonUK

Personalised recommendations