Behavior Research Methods

, Volume 38, Issue 4, pp 683–691 | Cite as

Interpersonal dynamics in sport: The role of artificial neural networks and 3-D analysis

  • Pedro Passos
  • Duarte Araújo
  • Keith Davids
  • Luís Gouveia
  • Sidónio Serpa


In previous attempts to identify dynamical systems properties in patterns of play in team sports, only 2-D analysis methods have been used, implying that the plane of motion must be preselected and that movements out of the chosen plane are ignored. In the present study, we examined the usefulness of 3-D methods of analysis for establishing the presence of dynamical systems properties, such as phase transitions and symmetry-breaking processes in the team sport of rugby. Artificial neural networks (ANN s) were employed to reconstruct the 3-D performance space in a typical one-versus-one subphase of rugby. Results confirm that ANs are reliable tools for reconstructing a 3-D performance space and may be instrumental in identifying pattern formation in team sports generally.


  1. Araújo, D., Davids, K., Bennett, S., Button, C., &Chapman, G. (2004). Emergence of sport skills under constraints. In A. M. Williams & N. J. Hodges (Eds.),Skill acquisition in sport: Research, theory and practice (pp. 409–433). London: Routledge.Google Scholar
  2. Araújo, D., Davids, K., Saínhas, J., &Fernandes, O. (2002). Emergent decision-making in sport: A constraints-led approach. In L. Toussaint & P. Boulinguez (Eds.),International Congress of Movement, Attention & Perception (p. 77). Poitiers, France: Université de Poitiers Press.Google Scholar
  3. Bartlett, R. (1997).Introduction to sports biomechanics. London: Spon Press.CrossRefGoogle Scholar
  4. Basheer, M. H. (2000). Artificial neural networks: Fundamentals, computing, design, and application.Journal of Microbiological Methods,43, 3–31.CrossRefPubMedGoogle Scholar
  5. Bates, B. T., Dufek, J. S., &Davis, H. P. (1992). The effect of trial size on statistical power.Medicine & Science in Sports & Exercise,24, 1059–1068.CrossRefGoogle Scholar
  6. Biscombe, T., &Drewett, P. (1998).Rugby: Steps to success. Champaign, IL: Human Kinetics.Google Scholar
  7. D’Appuzo, N. (2002), Surface measurement and tracking of human body parts from multi-image video sequences.ISPRS Journal of Photogrammetry & Remote Sensing,56, 360–375.CrossRefGoogle Scholar
  8. Fernandes, O., & Caixinha, P. (2003, April).A new method in time— motion analysis in soccer training and competition. Paper presented at the Fifth World Congress of Science & Football, Lisbon.Google Scholar
  9. Greenwood, J. (2003).Total rugby: Fifteen-man rugby for coach and player. London: A&C Black.Google Scholar
  10. Gruen, A. (1997). Fundamentals of videogrammetry: A review.Human Movement Science,16, 155–187.CrossRefGoogle Scholar
  11. Haykin, S. (1994).Neural networks: A comprehensive foundation. New York: Macmillan.Google Scholar
  12. Hughes, M., &Franks, I. M. (Eds.) (2004).Notational analysis of sport: Systems for better coaching and performance in sport (2nd ed.). London: Routledge.Google Scholar
  13. Kelso, J. A. S. (1995).Dynamic patterns: The self-organization of brain and behaviour. Cambridge, MA: MIT Press.Google Scholar
  14. Kelso, J. A. S., Buchanan, J. J., DeGuzman, G. C., &Ding, M. (1993). Spontaneous recruitment and annihilation of degrees of freedom in biological coordination.Physics Letters A,179, 364–371.CrossRefGoogle Scholar
  15. Klein, G. (2001). The fiction of optimization. In G. Gigerenzer & R. Stelten (Eds.),Bounded rationality: The adaptive toolbox (pp. 103–121). Cambridge, MA: MIT Press.Google Scholar
  16. McGarry, T., &Perl, J. (2004). Models of sports contests: Markov processes, dynamical systems and neural networks. In M. Hughes & I. Franks (Eds.),Notational analysis of sport: Systems for better coaching and performance in sport (2nd. ed., pp. 227–242). London: Routledge.Google Scholar
  17. Memon, Q., &Khan, S. (2001). Camera calibration and three-dimensional world reconstruction of stereo-vision using neural networks.International Journal of Systems Science,32, 1155–1159.CrossRefGoogle Scholar
  18. Perl, J. (2002). Game analysis and control by means of continuously learning networks.International Journal of Performance Analysis in Sport,2, 21–35.Google Scholar
  19. Smith, L. (2001),An introduction to neural networks. Retrieved March 31, 2004, from University of Sterling, Department of Computing Science and Mathematics Web site: Scholar
  20. Stergiou, C., & Siganos, D. (1996),Introduction to neural networks. Retrieved March 31, 2004, from Scholar
  21. Zanone, P. G., &Kelso, J. A. S. (1994). The coordination dynamics of learning. In S. [P.] Swinnen, H. Hever, J. Massion, & P. Cassaer (Eds.)Interlimb coordination: Neural, dynamical, and cognitive constraints (pp. 462–490). San Diego: Academic Press.Google Scholar

Copyright information

© Psychonomic Society, Inc. 2006

Authors and Affiliations

  • Pedro Passos
    • 1
    • 2
  • Duarte Araújo
    • 1
  • Keith Davids
    • 3
  • Luís Gouveia
    • 4
  • Sidónio Serpa
    • 1
  1. 1.Technical University of LisbonLisbonPortugal
  2. 2.Lusófona University of Humanities and TechnologiesLisbonPortugal
  3. 3.University of OtagoDunedinNew Zealand
  4. 4.University of LisbonLisbonPortugal

Personalised recommendations