Ecological Dynamics and Sport Performance


          This e-lab focuses on the role of Ecological Dynamics as a theoretical framework for analysing performance of athletes and sports teams as complex adaptive systems (Davids, Hristovski, Araújo, Balagué-Serre, Button & Passos, 2014). It combines key concepts from ecological psychology and nonlinear dynamical system theory, seeking to enhance understanding of performance and learning contexts in sport, to aid the acquisition and transfer of adaptive human behaviours (for other important texts, see Araújo, Davids, & Hristovski, 2006; Davids, Araújo, Hristovski, Passos, & Chow, 2012; Davids, Button, & Bennett, 2008).

In ecological psychology the continuous regulation of human behaviour is predicated on the role of information that emerges from the individual–environment system to guide activity (Gibson, 1979). The most significant information sources that constrain performance behaviours are affordances, which provide invitations for action offered by each individual’s perception of functional relations with a performance environment (Gibson, 1979; Withagen, de Poel, Araújo, & Pepping, 2012). This information-based approach has been enhanced with the integration of tools and concepts from nonlinear dynamics to explain how information is cyclically related to the dynamics of a performance environment (Kelso, 1995). Dynamical systems theory addresses the emergence of coordination tendencies that exist between, and within, components and levels of complex neurobiological systems (e.g. human beings and sports teams). System organisation is both facilitated and bounded by the interacting constraints which shape the dynamics of emergent behaviours (Newell, 1986). Constraints on behaviours include task, performer and environmental factors.

Ecological Dynamics is a viable theoretical framework for studying sport performance because it addresses the weaknesses of traditional approaches to expert performance in sport, which uniquely focus on the performer and the environment separately. Ecological Dynamics identifies key properties of expertise in sport predicated on the performer-environment relationship as the appropriate scale of analysis. Key properties of expert movement systems include multi- and meta-stability (Kelso, 2012), adaptive variability (Davids, Bennett, & Newell, 2006; Newell & Corcos, 1993), redundancy, degeneracy (Edelman & Gally, 2001; Mason, 2010; Price & Friston, 2002; Whitacre, 2010) and the attunement to affordances (Fajen, Riley, & Turvey, 2009; Gibson, 1979; Withagen & Chemero, 2012). Empirical research on these expert system properties indicates that skill acquisition does not emerge from the internal representation of declarative and procedural knowledge, or the imitation of expert behaviours to linearly reduce a perceived ‘gap’ separating movements of beginners and a putative expert model. Rather expert performance corresponds with the ongoing co-adaptation of an individual’s behaviours to dynamically changing, interacting constraints, individually perceived and encountered (Seifert, Button, & Davids, 2013; Seifert & Davids, 2012).

Developing knowledge of the functional role of adaptive movement variability is essential to understanding expert performance in many different sports (involving individuals and teams; ball games and outdoor activities; land and aquatic environments) (Davids et al., 2006; Davids, Glazier, Araújo, & Bartlett, 2003; Glazier & Davids, 2009). These key properties signify that, in sport performance, although basic movement patterns need to be acquired by developing athletes, there exists no ideal movement template towards which all learners should aspire, since relatively unique functional movement solutions emerge from the interaction of key constraints.


          Additionally, in an ecological dynamics framework, the concept of representative design underpins the organisation of experimental and learning environments so that observations and acquired skills can be linked to emergent functional behaviours in a specific performance context (Brunswik, 1955, 1956). The representative design framework provides guidance for the development of ecological constraints that best reflect continuous performance interactions of athletes and performance environments, and the role of variability during these interactions. This is an important feature of skill transfer in complex adaptive systems, since it ensures that cognitions, perceptions and actions used to regulate behaviour in one performance context (e.g., a practice environment) can be expected to generalise and underpin performance in another context (competitive performance environments) (Araújo, Davids, & Passos, 2007; Pinder, Davids, Renshaw, & Araújo, 2011).

  These key theoretical concepts in ecological dynamics provide a powerful underlying principled basis for the implementation of a nonlinear pedagogy (Chow, 2013): a pedagogical structure for enhancing learning in athletes and sports teams as complex adaptive systems. Chow (2013) proposed five principles for a nonlinear pedagogy in sport and physical education: the representativeness of the situation, focus of attention, functional variability through exploratory behaviours, manipulation of constraints, and ensuring relevant information-movement couplings (e.g., favouring perception of affordances). Through these principles, nonlinear pedagogy emphasizes the non linearity and non proportionality between the amount of practice and the skill acquisition (i.e., the level of expertise) (Chow, Davids, Hristovski, Araújo, & Passos, 2011).

In contrast to a linear pedagogy that prescribes the movement to be learned, giving numerous verbal instructions, nonlinear pedagogy respects and even enables the use of the degenerative nature of neurobiological systems, encouraging behavioural exploration, interaction with task and environmental constraints (Chow et al., 2006). This approach to design requires a respect for processes like task simplification rather than part-task decomposition, in the sense that learning and training designs have to preserve the complexity of the activity (Davids et al., 2008). In nonlinear pedagogy, error-reduction towards a specific model is thus not relevant. The challenge for coaches, instructors and PE teachers is instead to create conditions that facilitate the exploratory process for the performer, rather than merely providing a precise description and prescription of the movement pattern.


         In summary, application of an Ecological Dynamics framework can address current challenges in understanding sport performance and skill acquisition in athletes and sports teams as complex adaptive systems. Addressing these challenges can enhance the effectiveness of current understanding and practice in sport science, pedagogical practice and performance analysis. Our specific aims include:


-       To identify key properties of expertise and skill acquisition in athletes,

-   To enhance understanding of how to design affordances into practice environments in sport which simulate competitive performance environments,

-       To understand the functional and adaptive role of movement variability (within and between individuals),

-       To help to design representative and interactive task constraints in sports development programmes, facilitating an individualised approach,

-      Engineering technology and equipment to enhance skill acquisition during practice and training, predicated on complexity and neurobiological principles,

-       To apply principles of a non-linear pedagogy to re-shape current Physical Education and Coaching practices.





Araújo, D., Davids, K., & Hristovski, R. (2006). The ecological dynamics of decision making in sport. Psychology of Sport and Exercise, 7(6), 653–676.

Araújo, D., Davids, K., & Passos, P. (2007). Ecological validity, representative design, and correspondence between experimental task constraints and

     behavioral setting: Comment on Rogers, Kadar, and Costall (2005). Ecological Psychology, 19(1), 69–78.

Brunswik, E. (1955). Representative design and probabilistic theory in a functional psychology. Psychological Review, 62(3), 193–217.

Brunswik, E. (1956). Perception and the representative design of psychological experiments. Berkeley, CA, USA: University of California Press.

Chow, J. Y. (2013). Nonlinear learning underpinning pedagogy: Evidence, challenges, and implications. Quest, 65, 469–484

Chow, J. Y., Davids, K., Button, C., Shuttleworth, R., Renshaw, I., & Araújo, D. (2006). Nonlinear pedagogy: a constraints-led framework for understanding

     emergence of game play and movement skills. Nonlinear Dynamics, Psychology, and Life Sciences, 10(1), 71–103.

Chow, J. Y., Davids, K., Hristovski, R., Araújo, D., & Passos, P. (2011). Nonlinear pedagogy: Learning design for self-organizing neurobiological systems. New

     Ideas in Psychology, 29(2), 189–200.

Davids, K., Araújo, D., Hristovski, R., Passos, P., & Chow, J. Y. (2012). Ecological dynamics and motor learning design in sport. In N. J. Hodges & A. M. Williams

     (Eds.), Skill acquisition in Sport: research, theory and practice (2nd Edition, pp. 112–130). New York, NY, USA: Routledge.

Davids, K., Bennett, S. J., & Newell, K. M. (2006). Movement System Variability. (K. Davids, S. J. Bennett, & K. M. Newell, Eds.). Champaign, Illinois.: Human


Davids, K., Button, C., & Bennett, S. J. (2008). Dynamics of skill acquisition: A Constraints-led approach. (K. Davids, C. Button, & S. J. Bennett, Eds.).

     Champaign, IL: Human Kinetics.

Davids, K., Glazier, P. S., Araújo, D., & Bartlett, R. M. (2003). Movement systems as dynamical systems: the functional role of variability and its implications for

     sports medicine. Sports Medicine, 33(4), 245–60.

Davids, K., Hristovski, R., Araújo, D., Balagué-Serre, N., Button, C., Passos, P. (2014) Complex systems in sports. Routledge, Taylor & Francis, London: UK.

Edelman, G. M., & Gally, J. a. (2001). Degeneracy and complexity in biological systems. Proceedings of the National Academy of Sciences of the United States

     of America, 98(24), 13763–8.

Fajen, B. R., Riley, M. R., & Turvey, M. T. (2009). Information, affordances, and the control of action in sport. International Journal of Sports Psychology, 40(1),


Gibson, J. (1979). The ecological approach to visual perception. Boston: Houghton Mifflin.

Glazier, P. S., & Davids, K. (2009). On analysing and interpreting variability in motor output. Journal of Science and Medicine in Sport, 12(4).

Kelso, J. A. S. (1995). Dynamic Patterns: the self-organization of brain and behavior. Cambridge, MA: MIT.

Kelso, J. A. S. (2012). Multistability and metastability: understanding dynamic coordination in the brain. Philosophical Transactions of the Royal Society of

     London. Series B, Biological Sciences, 367(1591), 906–18.

Mason, P. H. (2010). Degeneracy at Multiple Levels of Complexity. Biological Theory, 5(3), 277–288.

Newell, K. M. (1986). Constraints on the development of coordination. In M. G. Wade & H. T. A. Whiting (Eds.), Motor development in children. Aspects of

     coordination and control (pp. 341–360). Dordrecht, Netherlands: Martinus Nijhoff.

Newell, K. M., & Corcos, D. M. (1993). Variability and motor control. Champain, IL: Human kinetics.

Pinder, R. A., Davids, K., Renshaw, I., & Araújo, D. (2011). Representative learning design and functionality of research and practice in sport. Journal of Sport

     & Exercise Psychology, 33(1), 146–55.

Price, C. J., & Friston, K. J. (2002). Degeneracy and cognitive anatomy. Trends in Cognitive Sciences, 6(10), 416–421.

Seifert, L., Button, C., & Davids, K. (2013). Key properties of expert movement systems in sport : an ecological dynamics perspective. Sports Medicine, 43(3),


Seifert, L., & Davids, K. (2012). Intentions , Perceptions and Actions Constrain Functional Intra- and Inter- Individual Variability in the Acquisition of Expertise

     in Individual Sports. The Open Sports Sciences Journal, 5(8), 68–75.

Whitacre, J. M. (2010). Degeneracy: a link between evolvability, robustness and complexity in biological systems. Theoretical Biology & Medical Modelling,

     7(1), 6.

Withagen, R., & Chemero, A. (2012). Affordances and classification: On the significance of a sidebar in James Gibson’s last book. Philosophical Psychology,

     25(4), 521–537.

Withagen, R., de Poel, H. J., Araújo, D., & Pepping, G.-J. (2012). Affordances can invite behavior: Reconsidering the relationship between affordances and

     agency. New Ideas in Psychology, 30(2), 250–258.


Representative Members


Representative: Ludovic Seifert (University of Rouen, France)

Co-Representative: Keith Davids (Sheffield Hallam University, UK)


Scientific Committee


Duarte Araujo (University of Lisbon, Portugal)

Chris Button (University of Otago, New-Zealand)

Jia-Yi Chow (Nanyang Technological University, Singapore)

Régis Thouvarecq (University of Rouen, France)

Jon Wheat (Sheffield Hallam University, UK)

Ian Renshaw (Queensland University of Technology, Australia)


Members (chronological order of subscription)

John Komar (University of Rouen, France)

Dominic Orth (University of Rouen, France)

Mark Upton (English Institute of Sports, UK)

Jarmo Liukkonen (University of Jyvaskyla, Finland)

Timo Jaakkola (University of Jyvaskyla, Finland)

Linnamo Vesa Tapio (University of Jyvaskyla, Finland)

Janne Avela (University of Jyvaskyla, Finland)

Matt Dicks (University of Portsmouth, UK)

Joseph O'Halloran (University of Portsmouth, UK)

Paul Glazier (Victoria University, Australia)

Ana Conceição (Escola Superior de Desporto de Rio Maior, Portugal)

Robert Hristovski (Ss. Cyril and Methodius University, Macedonia)

Natàlia Balagué Serre (INEFC-Barcelona, Spain)

Nicolas Benguigui (University of Caen, France)

Bruno Mantel (University of Caen, France)

Elise Faugloire (University of Caen, France)

Laure Lejeune (University of Caen, France)

Ricardo Duarte (University of Lisbon, Portugal)

Jonathon Headrick (Queensland University of Technology, Australia)

John Barden (University of Regina, Canada)

Ricardo Fernandes (University of Porto, Portugal)

Miriam Chang Yi Lee (Nanyang Technological University, Singapore)

Michael Maloney (Australian Institute of Sport, Australia)

Denis Hauw (University of Lausanne, Switzerland)

Bruno Travassos (University of Beira Interior, Portugal)

Francisco Javier, Hernandez Moreno (University of Miguel Hernandez, Spain)