This is the author version published as: This is the accepted version of this article. To be published as : This is the author version published as:

QUT Digital Repository: http://eprints.qut.edu.au/

Phillips, Elissa and Keith, David and Renshaw, Ian and Portus, Marc (2010) Expert performance in sport and the dynamics of talent development. Sports Medicine, 40(4). pp. 271-283.

© Copyright 2010 Adis Data Information BV

1

2

3

4

EXPERT PERFORMANCE IN SPORT AND THE DYNAMICS OF TALENT 5

DEVELOPMENT 6

7

8

9

10

Elissa Phillips1, 2, 3

, Keith Davids2, Ian Renshaw

2 and Marc Portus

3 11

12

1Biomechanics and Performance Analysis, Australian Institute of Sport, Canberra 13

2School of Human Movement Studies, Queensland University of Technology, Brisbane 14

3Sport Science Sport Medicine Unit, Cricket Australia Centre of Excellence, Brisbane 15

16

17

18

19

Correspondence to: Elissa Phillips, Biomechanics and Performance Analysis, Australian Institute 20

of Sport, PO Box 156, Bruce, ACT, Australia. Telephone + 61-02-6214-7329. Fax + 61-02-6214-21

1593. Email: elissa.phillips@ausport.gov.au 22

23

Word Count: 5,97124

2

Contents 1

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . 3 2

1. Traditional Expertise Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6 3

1.1 Methods for assessing expert performance in traditional research. . . . . . . . . . . . . . . . . . .7 4

1.2 Outcomes of research with quantitative methodologies. . . . . . . . . . . . . . . . . . . . . . . . . . . 8 5

1.3 Outcomes of research with qualitative methodologies. . . . . . . . . . . . . . . . . . . . . . . . . . . .11 6

2. Dynamical Systems Theory and Constraints on the Acquisition of Expertise in Sport. . . . . . .11 7

2.1 The Role of Neurobiological Degeneracy in Expertise Acquisition. . . . . . . . . . . . . . . . . .13 8

2.2 Constrains on Acquiring Expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15 9

3. A Complex Systems Approach to Talent Development. . . . . . . . . . . . . 18 10

4. The Role of Meta-stability in Acquiring Expertise . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . 20 11

5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 12

13

3

Abstract 1

Research on expertise, talent identification and development has tended to be mono-2

disciplinary, typically adopting adopting neurogenetic deterministic or environmentalist 3

positions, with an over-riding focus on operational issues. In this paper the validity of dualist 4

positions on sport expertise is evaluated. It is argued that, to advance understanding of expertise 5

and talent development, a shift towards a multi-disciplinary and integrative science focus is 6

necessary, along with the development of a comprehensive multi-disciplinary theoretical 7

rationale. Here we elucidate dynamical systems theory as a multi-disciplinary theoretical 8

rationale for capturing how multiple interacting constraints can shape the development of expert 9

performers. This approach suggests that talent development programmes should eschew the 10

notion of common optimal performance models, emphasise the individual nature of pathways to 11

expertise, and identify the range of interacting constraints that impinge on performance potential 12

of individual athletes, rather than evaluating current performance on physical tests referenced to 13

group norms. 14

15

16

17

18

19

20

21

Key words: Expertise, Talent Development, Talent Identification, Skill Acquisition, Dynamical 22

Systems Theory, Sport Performance 23

24

4

1

Research on expertise and talent identification and development has been dominated by opposing 2

geno-centric or environmentalist positions.[1]

Recently, Dunwoody[2]

has challenged 3

psychologists to look beyond the individual, suggesting researchers have neglected the role of the 4

environment and focused on organism structure and process in isolation. This position has been 5

criticised for emphasising neurogenetic determinism by Rose, due to its focus on identifying 6

genetic or neural codes deemed „responsible‟ for behaviours. Although there is a need to move 7

away from the cognitive psychology asymmetric–organismic focus[2]

, the tendency to over-8

emphasise the role of environmental constraints on expertise acquisition also needs to be 9

eschewed. For example, Ericsson and colleagues[3]

emphasised an environmental perspective, 10

advocating that expertise is acquired as performers specialise at an early age and engage in 11

deliberate practice.[3]

Other investigators have associated the hereditary nature of physiological, 12

anthropometric and psychological characteristics with elite performance in sports.[4]

For example, 13

early anthropometric research on Olympic athletes advocated a close relationship between 14

physical characteristics and specific Olympic events.[5]

This line of evidence has been somewhat 15

over-interpreted, leading to the questionable practice of anthropometric profiling of adolescents 16

to identify potential for early specialisation in a sport. Consequently, anthropometric profiling of 17

physical dispositions has tended to skew the rationale for talent identification models in sport, 18

despite a lack of supportive evidence and the unstable nature of anthropometric and physical 19

parameters during adolescence.[6, 7]

20

Recently, there have been proposals to integrate polar perspectives on sports performance 21

and expertise into a multi-disciplinary approach, to enhance understanding of the athlete–22

environment relationship as exemplifying a complex, dynamical system. In this position paper we 23

identify limitations of existing research on expert performance and talent development, and 24

5

provide evidence-based arguments for adopting a multi-disciplinary research perspective for the 1

comprehensive study of sport expertise. To support our argument we review and evaluate extant 2

literature on expertise in psychology and sport science. The search reference terms used included 3

„talent development‟, „talent identification‟ and „sport expertise‟ in PubMed, SportDiscus and 4

Ovid databases. 5

A major reason for adopting polarised, mono-disciplinary positions on the acquisition of 6

sport expertise has been the absence of a powerful multi-disciplinary theory to act as an 7

integrative conceptual framework. Although some models have advocated a multi-disciplinary 8

approach to talent identification and development, such as Simonton‟s[8]

model of talent as a 9

multiplicative, dynamic process and the Differentiated Model of Giftedness and Talent,[9]

these 10

approaches tend to be operational and propositional in nature. These models have not provided a 11

detailed, explanatory theoretical rationale underpinning a dynamic and multi-dimensional basis 12

for expertise and how it may support the process of identifying and developing talent. 13

One suitable theoretical approach to the study of performance, expertise and talent 14

development in sport conceptualises the athlete as a complex, dynamical system. In such systems 15

there is great potential for interactions between system components and the environment, often 16

leading to rich and unique patterns of behaviour. To date, studies of complex system behaviour in 17

sport include match play and behaviour during competitions,[10, 11]

decision-making,[12, 13]

motor 18

learning,[14, 15]

coordination,[16, 17]

human gait and injury[18, 19]

and medicine in sports.[20]

In this 19

article relevant theoretical concepts and insights from dynamical systems theory, complex 20

systems theory, ecological psychology and evolutionary sciences are identified and their 21

implications for the acquisition of sports expertise and talent development are discussed. 22

6

1

1. Traditional Expertise Approaches 2

As noted, much research has focused on the role of environmental constraints in expertise 3

acquisition, including participation in play and practice activities, and the role of family and 4

environmental contexts.[21, 22]

For example, Ericsson and Smith‟s[23]

expert performance approach 5

explored the contribution to expertise of specific practice environments. Ericsson and 6

colleagues‟[24]

deliberate practice approach has highlighted the importance of structured activities 7

involving goal directed skill learning which require effort and concentration. It was estimated that 8

experts spend typically about ten years or 10,000 hours in deliberate practice to attain exceptional 9

performance.[25]

The uni-dimensional nature of the deliberate practice approach led Starkes[26]

to 10

label it a „very environmentalist‟ theory of expertise acquisition, while others (e.g.,[27]

) have 11

proposed it has an organismic bias. Additionally, researchers studying deliberate practice in sport 12

have encountered some incongruities with the theory‟s main tenets. For example, in contrast to 13

previous findings, many athletes tend to find appropriate practice and training enjoyable and 14

motivating across all development stages.[28]

Moreover, early specialisation has not been found to 15

be essential for acquisition of expert sport skills in adulthood.[29-31]

Time spent in sport-specific 16

training does discriminate between experts and non-experts in some sports, although the 17

relationship between practice and performance is non-linear.[21]

Further, retrospective analysis of 18

historical data on time spent in practice has been criticised by Yarrow et al.., For example, this 19

method was unable to clarify differences between experts and novices based on micro-structure 20

of practice activities.[32]

For example, Weissensteiner, Abernethy, Farrow and Müller[33]

21

examined the practice histories of under-15, under-20 and adult cohorts of skilled and less skilled 22

cricket batsmen and found that hours spent in practice explained only a small proportion of 23

variance in the development of anticipation skills. A particular methodological concern in this 24

7

approach is the proliferation of „weaker‟ data from a plethora of cross-sectional studies, relative 1

to the lack of longitudinal research. More evidence on putative benefits of deliberate practice is 2

needed, following cohorts of young athletes through developmental pathways. To summarise, 3

although numerous hours of training are necessary for success in sport at the elite level, research 4

suggests that attainment of expert level is not always accomplished by engaging in deliberate 5

practice alone. 6

In another polarised approach to elite sports performance, some research has investigated 7

the genetic makeup of individual athletes. Molecular testing has attempted to identify single gene 8

variants deemed „responsible‟ for performance in specific sports (e.g., a gene responsible for 9

physical power or endurance capacity). This „single gene as magic bullet‟ philosophy has been 10

eloquently criticised for its determinist stance (Rose, 1995) although it has led to claims that elite 11

performers are born to succeed. For example, there have been attempts to identify sprinters and 12

endurance runners on the basis of differing alleles (i.e., forms) of a single gene known as alpha 13

actinin-3. [34, 35]

Besides obvious ethical issues, reports of gene-profiling and gene-transfer 14

technology raise more general theoretical and practical questions about the nature of genetic and 15

environmental constraints on skill acquisition and performance.[36]

Research on human behaviour 16

has yet to reveal that the function of a single gene variant can be inferred from identifying 17

performance phenotypic variance (e.g., power athletes and endurance athletes), supporting the 18

notion of non-specificity of genetic constraints.[37]

19

20

1.1 Methods for assessing expert performance in traditional research 21

Empirical expertise research has typically been conducted with two main methods 22

involving: (i) quantitative analyses, which include implementation of multiple test batteries on 23

developing athletes; and (ii) qualitative examination of developmental histories of past or present 24

8

elite athletes, with methods such as interviews, questionnaires or self-reported, retrospective 1

recall of practice histories. 2

3

1.2 Outcomes of research with quantitative methodologies 4

Attempts to distinguish athletic expertise based on skills testing have been unsuccessful or 5

have been confounded by the over-riding importance of maturational factors on observed 6

performance.[7]

The over-use of „closed-skill drill tasks‟ to elucidate athletic potential has been a 7

major weakness in extant research because they lack task representativeness, resulting in a failure 8

to identify skilled players from lesser skilled individuals. For example, Gabbett, Georgieff and 9

Domrow[38]

attempted to assess skills of passing (digging), setting, serving, and spiking as part of 10

a test battery to discriminate between junior volleyball players of different abilities. The only test 11

that revealed differences between selected and non-selected players was passing. This may have 12

been because skills in volleyball (digging, setting, spiking and blocking) are not performed in 13

stable environments but are dynamic and characterised by marked temporal and spatial variability 14

dependent on preceding play (e.g. quality of contact of the ball by teammates and opponents). In 15

other work, Hoare and Warr[39]

assessed talented athletes (non-football players) aged 15-19 years 16

to identify and develop female football players. Initial screening required coaches to grade 17

players by assessing skill performance such as ball juggling, dribbling (around cones) and 18

passing. Players were grouped by performance test scores for playing small-sided games before 19

progressing to full-size games for coach observation and selection. Hoare and Warr[39]

used an 20

innovative quasi-applied research model to identify and develop talent in women‟s soccer, and 21

highlighted the need to assess athletes over a longer time period than typical in sport talent 22

assessment, suggesting that two to three months is necessary for coaches to make a valid 23

assessment of athlete potential. They also proposed that components of performance require 24

9

different weightings since the importance of speed and acceleration was underestimated in their 1

tests. Finally, the need to develop an objective test of game sense was suggested as some athletes 2

performed well on physical tests, but weakly in terms of general tactical understanding. 3

Other quantitative approaches in empirical talent identification research have attempted to 4

examine sport-specific, relevant performance characteristics, through anthropometric, physical, 5

technical, tactical and psychological testing.[39-43]

In the main, these tests have been limited in 6

utility for identifying talented performers in sport. For example, test batteries focusing on discrete 7

performance measures have provided limited information of athletic potential and adaptability in 8

different performance environments.[6, 40]

Questions on the data of these studies, and the efficacy 9

of traditional talent identification practices, arise due to constraints on individuals like growth, 10

maturation, development and training.[41]

To exemplify, Elferink-Gemser, Visscher, Lemmink 11

and Mulder[42]

employed a test battery to examine 30 elite and 35 sub-elite youth hockey players 12

over three competitive seasons. Their research established differences in technical and tactical 13

variables between skill levels at 14 years as well as variations in endurance capacity in the 14

subsequent two years. However, the task demands of the technical test did not provide a valid 15

representation of the competitive performance setting (cf. the importance of representative 16

experimental design in studies of human behaviour).[43]

The use of closed skill proficiency tests, 17

without opposition and in a static environment, and physical performance measures considered in 18

isolation need to be carefully evaluated, because they have a low correlation with the specific 19

demands on an individual during a dynamic competitive situation. Several studies have 20

highlighted the importance of using more sports-specific assessments of tactical and technical 21

competence rather than generic physical measures such as strength or endurance tests.[39, 44]

22

Skill-based differences in perceptual-cognitive skills such as anticipation and decision-23

making have been successfully identified in a number of studies (see Williams & Ward).[45]

24

10

Although a number of generalised visual training programmes are predicated on the idea that a 1

superior visual hardware system provides perceptual advantages to skilled performers, research 2

evidence does not support this view. Rather it has been argued that expertise advantages emerge 3

as a result of sport-specific practice and experience.[45-47]

4

Despite the large volume of studies examining the role of perceptual-cognitive expertise 5

in sport, there has been some confusion over whether research has actually demonstrated the true 6

extent of expertise. Van der Kamp, Rivas, van Doorn, and Savelsbergh[48]

criticised the lack of 7

precision in perceptual-cognitive research, highlighted the magnitude of errors reported in many 8

occlusion-based studies of anticipation skill, and suggested a weakness in a popular experimental 9

methodology. In a popular approach, liquid crystal spectacles permit information sources 10

available to participants to be manipulated by limiting vision during key moments of 11

performance.[49]

It was argued that high levels of error observed in these studies may have been 12

due to the failure of the methodology to capture the complementary efforts of the ventral and 13

dorsal cortical visual systems in regulating perception and action. This is important since, as 14

Williams and Ericsson[50]

indicated, the first stage in determining expertise is that „performance 15

be observed in situ in an attempt to capture the essence of expertise in the domain of interest and 16

to design representative tasks that allow component skills to be faithfully reproduced in the 17

laboratory‟ (p.286). Van der Kamp et al.[48]

also argued that a weakness of previous work was 18

requiring participants to undertake non-representative actions such as pressing buttons, marking 19

crosses on images of court surfaces, and verbally reporting findings. Another common error is the 20

provision of video footage that does not replicate the view of performers in action, thereby 21

limiting understanding of the true extent of the expert advantage. Some researchers, such as 22

Müller and Abernethy,[49]

have developed and incorporated what they termed as an „ecologically 23

11

valid‟ batting test to measure a batsman's perceptual-action coupling and found skilled players 1

utilised prospective ball flight information to a greater extent than less skilled players. 2

3

1.3 Outcomes of research using qualitative methods 4

Qualitative studies on the development histories of elite athletes have been somewhat limited in 5

number, examining physical, psychological, environmental and social factors that shape 6

performance.[51, 52]

They have established the importance of environmental constraints including 7

support from family or friends and the opportunity to participate in residency development 8

programmes. A range of individual constraints including mental preparation, focus and 9

commitment, and clear goal setting have been found to contribute to the development of 10

expertise.[6]

Durand-Bush and Salmela[52]

examined qualitatively the development and 11

maintenance of expert performance in Olympic and world championship competitions. Their data 12

revealed that athletes did not all follow the same pathway to become world and Olympic 13

champions, highlighting how individuals can take different routes to expert status, use various 14

resources and strategies, and be innovative and creative as they develop and maintain their 15

expertise in sport. However, some common factors were observed including: (i) all athletes 16

underwent stages described as the sampling, specializing, investment and maintenance years;[53]

17

(ii) high levels of self confidence and motivation; and (iii) high levels of creativity and 18

innovation during the maintenance years, a continuous drive to learn and improve, and a strong 19

work ethic. 20

21

2. Dynamics Systems Theory and Constraints on the Acquisition of Expertise in 22

Sport 23

12

In contrast to more traditional approaches to studying expertise, a potentially valuable 1

conceptual framework for modelling the acquisition of expertise exists in understanding 2

performers as complex, dynamical systems. Complexity sciences have been used to study and 3

explain the rich patterns formed in complex systems such as animal collectives, weather systems, 4

the human brain and movements in team sports, where patterns emerge from seemly random 5

component trajectories.[54-56]

From this description an emerging expert can be viewed as a 6

complex system, composed of many degrees of freedom on many system levels. The potential for 7

interaction between system components provides the platform for rich patterns of behaviour to 8

emerge as individuals interact with dynamically changing environments. This new perspective 9

reveals that adaptation in performance occurs as the result of system trade-offs between 10

specificity and diversity of behaviours.[57]

Dynamical systems theory emphasises the influence of 11

interacting constraints on performance and provides a framework showing how expertise can be 12

achieved in diverse ways as individual performers attempt to satisfy the unique constraints on 13

them.[20]

14

Some current models of talent development are harmonious with these theoretical ideas, 15

although their tenets are not necessarily predicated conceptually on these insights. For example, 16

Simonton[8]

proposed that talent emerges from multidisciplinary, multiplicative and dynamic 17

processes and is likely to operate as an intricate system beyond the scope of the polar nature–18

nurture debate. He pioneered mathematical equations to operationalise the potential components 19

that contribute to talent development. These components were weighted by relevance and 20

included reference to genetic dispositions (e.g. height or endurance capacity), environmental (e.g. 21

social and familial support) and developmental constraints. Subsequently the model was 22

described as emergenic and epigenetic, comprising components that interact and change with 23

time[8]

. The emergenic aspect proposed that potential talent consists of multiple components, 24

13

including all physical, physiological, cognitive and dispositional traits that facilitate the 1

manifestation of superior expertise in a specific domain. Beyond individual differences, 2

Simonton‟s [8]

model captured the dynamics of epigenetics. Epigenetics were seen in the diverse 3

components that make up talent which slowly appear and differentiate over time in an individual 4

and ultimately depend on underlying neurological, muscular, cultural, skeletal, social, 5

psychological, physiological and environmental variables.[58]

However, they emerge gradually 6

during the course of long-term interactions between the internally developing organism and 7

appropriate environmental constraints.[8]

This system is complicated, as it includes the 8

evolutionary interaction of components, and any examination of talent development that utilises 9

this model needs to be holistic, impartial and sophisticated.[8]

Although this mathematical model 10

is a useful starting point for sport scientists since it attempts to operationalise key concepts such 11

as multidisciplinary talent development practices and multiple developmental trajectories towards 12

potential expertise,[6]

it lacks theoretical power as it is not conceptualized within a theoretical 13

framework. This weakness could be mediated by including dynamical systems theory as a viable 14

rationale for talent development as an emergenic and epigenetic process. Furthermore, on a 15

practical level, adopting Simonton‟s[8]

model may be extremely difficult as its efficacy is 16

predicated on identifying all components that contribute to expertise in any one specific sporting 17

domain. Identification of every component is essential because the model is proposed to be 18

multiplicative, and any score of zero for any specific factor signifies that expertise cannot be 19

achieved. 20

Vaeyens et al.[7]

provided an insightful model of talent identification, capturing the 21

dynamic nature of talent and its development, and focusing on potential for development and 22

inclusion rather than early identification. Such a model can be strengthened with a dynamical 23

14

system theoretical approach also, and in the next section we elucidate key ideas in this 1

framework. 2

3

2.1 The Role of Neurobiological Degeneracy in Expertise Acquisition 4

Athletes considered as complex, neurobiological systems are comprised of many 5

interacting parts and levels, which self-organize under constraints.[59]

These systems have been 6

conceptualised recently as pleiotropic and degenerate with the ability to adapt to different task 7

and environmental demands.[60]

Pleitropy provides neurobiological systems with a variety of 8

alternate performance solutions.[61]

Neurobiological degeneracy refers to the ability of 9

structurally different components to be coordinated together to achieve the same behavioural 10

goal.[57]

At the level of gene networks, degeneracy promotes evolutionary fitness by ensuring that 11

genetic diversity supports functional adaptation to variable environments.[62]

The degenerate 12

relationship between system components and system output in developing experts implies that 13

there are many different pathways to achieving expert performance. Genetic diversity is 14

responsible for a portion of training or performance response differences between individuals, 15

and when there is a favourable interaction with important environmental constraints, performance 16

benefits may be observed. Given differences in genetic contributions, performance variations are 17

more likely to assert themselves under intensive practice regimes. 18

The characteristics of pleiotropy and degeneracy in athletes highlight the need for a 19

systems-oriented, multidimensional framework.[22]

Expertise attainment in a particular sport 20

depends on many additional constraints outside the cognitive domain, including but not limited to 21

genetics, social and physical environment, opportunity, encouragement and the effect of these 22

variables on physical and psychological traits.[63]

Mono-disciplinary approaches to the acquisition 23

of expertise (e.g., Yarrow et al., 2009) have failed to capture the complementary nature of the 24

15

relationship between individual, task and environmental constraints.[6, 22, 64]

For these reasons, 1

Davids and Baker[22]

highlighted the need for an interactionist explanatory framework to examine 2

performance attainment in sport. As we note in the following sections of this paper, this 3

theoretical approach provides a viable platform for explaining the dynamic relationship between 4

an individual‟s genetic disposition and the environment and the acquisition of expertise in sport 5

through variable pathways and processes. 6

7

2.2 Constraints on Acquiring Expertise 8

In sport, the expression of expertise is limited or shaped by interacting constraints at many 9

system levels. The concept of constraints (boundaries that constrain the interactions of system 10

components) in human movment science was readdressed by Newell.[65]

He classified them into 11

organismic, task and environmental constraints.[65]

Constraints in the expertise acquisition 12

context can be conceived of as the numerous variables that form each individual expert‟s 13

developmental trajectory, and itis important to identify the range of constraints on the acquisition 14

of expertise. Given that an individual is born with distinguishing physical characteristics (with a 15

degree of genetic influence), expertise research is concerned with how environmental constraints 16

interact to affect the development of skill and the expression of genotypes. 17

Performance emerges from the intrinsic dynamics of experts, the preferred behavioural 18

tendencies which arise from the interaction of environmental, task and organismic constraints 19

(including development, experience, genes and learning of each performer).[66]

Kelso[66]

proposed 20

that intrinsic dynamics reflect the organisational tendencies of an individual. Thelen[67]

referred 21

to intrinsic dynamics as “the preferred states of the system given its current architecture and 22

previous history of activity” (p.76). The intrinsic dynamics of each individual are unique and 23

16

shaped by many constraints including experience, learning, development, morphology and genes 1

which interact to shape performance and the acquisition of expertise in sport.[68]

In developing 2

experts, these contributions can lead to significant variations in performance solutions. The 3

manner in which each developing expert attempts to satisfy constraints during performance and 4

learning is determined by the matching of his/her intrinsic dynamics with the specific task 5

dynamics.[69]

By knowing an individual‟s intrinsic dynamics one can specify what in the 6

performance repertoire actually changes due to environmental, learned or intentional 7

influences.[70]

8

Due to variations in intrinsic dynamics, expert performers are able to generate different 9

types of functional performance solutions. This idea fits with data, in cricket fast bowling 10

reported by Pyne, Duthie, Saunders, Petersen & Portus[71]

who examined the relationship 11

between junior and senior high performance athletes‟ anthropometric and strength characteristics 12

and bowling speed. They observed differences in the variables and strength of correlation of 13

predictors of peak ball speed between age groups and suggested growth and biological maturation 14

largely accounted for greater peak ball speed in seniors. This line of thinking could be followed 15

in a comprehensive performance analysis including technical/coordination variants under a 16

variety of conditions, such as different delivery types, to gain an understanding of the relationship 17

between the intrinsic dynamics and performance solutions of individuals in developmental 18

groups. 19

Therefore, understanding the nature of each individual‟s intrinsic dynamics is central to 20

understanding how expert performance develops in sport. Due to different relationships between 21

an individual‟s intrinsic dynamics and a set of task dynamics, each athlete may harness system 22

variability in a different way implying that expertise may develop in quite unique ways. As 23

individuals progress towards a state of expertise and explore different performance solutions, 24

17

their intrinsic dynamics will alter and diversify. If the behavioural requirements of a task provide 1

a close match with the pre-existing intrinsic dynamics of an individual learner, the rate of 2

expertise acquisition is likely to be enhanced. The matching of intrinsic and task dynamics may 3

explain precocial behaviour in sport when some athletes can perform incredibly well from an 4

early age and forms the basis of talent transfer in sport. In contrast, acquiring task dynamics 5

which are dissimilar to those of a previously learned task (e.g., tennis and squash movement 6

pattern dynamics) may lead to a longer process of learning because the specific learner‟s intrinsic 7

dynamics may need to be significantly re-shaped.[72]

8

These ideas in dynamical systems theory have important implications for understanding 9

the development and maintenance of expert performance. How the intrinsic dynamics of 10

developing experts are continually shaped by genetic and environmental constraints needs to be 11

understood. The effects of environmental constraints on phenotypic gene expression suggests that 12

athletes with what may be perceived as less favourable genetic dispositions may still achieve 13

expert levels of performance given an appropriate skill acquisition environment.[73]

Alternatively, 14

genetically gifted athletes may fail to achieve expert status without an environment that allows 15

rich interactions for acquiring and practising skills (for a discussion of rich learning environments 16

see ideas of Hammond and Bateman).[74]

Rich learning environments provide many opportunities 17

to engage in continuous interactions with skilled peers, mentors, skilled coaches and supportive 18

parents as athletes acquire movement skills and knowledge in specific sports. In Australia, 19

Abernethy[75]

discussed the disproportionate success of athletes from rural locations as the 20

„Wagga-effect‟. Wagga Wagga is a rural town with a population of 46,735 people,[76]

where 21

children typically play many different sports, often engaging in senior or adult competition prior 22

to specialisation. It has produced an inordinately high number of international and professional 23

18

athletes, more than any other urban conurbation in Australia. Côté, et al.[77]

suggested that smaller 1

cities (defined as having populations <100, 000 people) provide advantageous opportunities for 2

talent development, because the populace is large enough to support the need for facilities, 3

different sporting codes, club networks and competition infrastructure, and allows early exposure 4

to adult competition. Côté et al.[77]

referred to the „birthplace effect‟ where the quality and 5

quantity of play and practice interactions afforded by the physical environment of smaller cities is 6

favourable for talent development. These data highlight the need to undertake more research 7

examining appropriate environmental cultural constraints underpinning development of expertise. 8

The range of unique constraints on athlete performance and behaviour have made predictions of 9

expert performance difficult due to the dynamic nature of sport performance contexts.[22]

10

To summarise so far, it seems unlikely that a singular common optimal pathway to 11

performance expertise exists because of the degenerate neurobiological system characterising 12

each individual performer and the effect of interactions between environmental and personal 13

constraints on the intrinsic dynamics of each learner. Expert performers are able to generate 14

different types of functional performance solutions, depending on differences in their intrinsic 15

dynamics. Future research needs to provide a more comprehensive examination of influential 16

constraints including technical/coordination variants under a variety of tasks‟ demands. For 17

example in cricket fast bowling, investigating different delivery types, would allow greater 18

insight into the individual dynamics and movement solutions of such a group (e.g., varying ball 19

speed or type and line and/or length in cricket fast bowling). 20

21

3. A Complex Systems Approach to Talent Development 22

Conceptualising expertise acquisition as a complex system has several implications for 23

talent development programmes. First, the aim of talent development is to aid individuals in 24

19

gaining the expertise needed to satisfy the unique constraints impinging on them in specific 1

performance domains. This can be achieved by measuring intrinsic dynamics of each individual 2

athlete, identifying key constraints on him/her and facilitating development by manipulating 3

these constraints to encourage exploration of movement solutions. [68, 78-80], Second, talent 4

development programmes can harness existing system nonlinearities by developing strategies to 5

induce phase transitions in individual performers. This aim might be met by understanding how 6

to force individuals into the meta-stable region of the perceptual-motor landscape of practice 7

where a strategy of co-adaptation can underpin the emergence of creative behaviours (typical of 8

the profile of expert performers in line with the findings of Durand-Bush and Salmela).[52]

Meta-9

stable regions of a performance landscape are areas where the system is poised in a state of 10

dynamic stability which allows it to rapidly undergo phase transitions to new, more functional 11

states of organisation as constraints change. If this strategy were aligned with observations of 12

critical developmental periods in young athletes, abrupt phase transitions in expertise and 13

performance may be induced. An implication of this approach for coaches is to incorporate tasks 14

that promote adaptability and creativity in performers. In cricket, this aim could be tested through 15

the implementation of carefully designing games that require batters to probe the boundaries of 16

their skill set and force co-adaptive behaviours in learners as long as the design of game tasks are 17

based on grounded principles of the game .[72]

18

Third, these ideas signify the nonlinear nature of expertise acquisition. Traditional models 19

of talent development need to be adjusted to consider the different rates of development of 20

potentially talented athletes.[6]

Sub-system behaviours continually shape an individual athlete‟s 21

intrinsic dynamics. Because of variations in each athlete‟s intrinsic dynamics, individual rates of 22

skill acquisition are likely to progress at different time scales.[14]

Talent development models 23

20

need to take into account the different rates of learning and growth and maturation processes 1

experienced by individuals on their pathway to expertise (not least it must take into account the 2

relative age effect to maximise the available talent).[81]

These different rates of learning can be 3

influenced by key constraints which act as „rate limiters‟ causing systems to find new functional 4

performance solutions.[78]

Rate limiters can be defined as system controllers, i.e. components or 5

sub-systems which limit the development of an individual in sport.[79]

For example, children‟s 6

strength in key muscle groups may act as a rate limiter which inhibits them from demonstrating 7

the skills that they have acquired already through practice and experience in sport. An important 8

task is to identify the rate-limiting constraints which are acting on an expert system in order to 9

manipulate them and facilitate transitions to a new performance level. 10

11

4. The Role of Meta-stability in Acquiring Expertise 12

Two important characteristics of complex systems mentioned already include meta-13

stability and co-adaptation. These features are important for talent identification and development 14

but need to be conceptualised in the sport performance domain. Emerging expert athletes exhibit 15

complexity and meta-stability due to the potential for interaction between their sub-systems. In 16

this way, the whole dynamical landscape of expertise can suddenly change with small variations 17

in responses to constraints impinging on the developing athlete. Critical periods have been 18

identified as brief windows of time and space during which a complex system‟s organisation is 19

most open to modification from external and internal constraints. It has been argued that motor 20

learning can be enhanced when developing athletes are located within these critical periods[82]

. 21

The challenge for coaches and sport scientists is to identify when individual athletes enter 22

meta-stable regions and/or critical periods while developing their expertise levels so that 23

performance paradigm shifts in expertise and skill acquisition might be triggered, as we 24

21

exemplify in this section. For the individual to utilise technical and cognitive variability and find 1

new performance solutions and cope with instabilities (meta-stability) requires complementary 2

cognitive attributes (e.g. confidence, sacrifice, dedication, and perseverance). By ensuring 3

exposure to meta-stable regions of the performance landscape during development, experts can 4

discover new modes of behaviour to satisfy interacting perceptual, affective and task constraints. 5

These new modes of performance are likely to emerge as novel solutions to performance 6

problems as developing athletes co-adapt their responses to challenging constraints imposed by 7

opponents, coaches or performance environments. 8

Co-adaptation is an evolutionary strategy that has implications for the way that constraints 9

can influence the process of talent development by forcing the developing expert to find new 10

functional performance solutions. It may represent a useful expertise development strategy for 11

practitioners, as different performers and/or technologies attempt to pressurise individuals to seek 12

unique performance solutions. Furthermore, the process occurs naturally as a sport develops (i.e., 13

through technique changes, rule changes or equipment change or as athletes pose each other new 14

performance problems). New solutions to performance problems emerge as talented individuals 15

learn how to assemble creative movement solutions during practice. 16

In cricket, fast bowlers can make the ball “swing”, which is the curved trajectory of the 17

ball‟s flight path, thereby making the task of hitting the ball more difficult for the batter. A 18

cricket ball will swing when asymmetrical aerodynamic forces are acting on the ball, 19

conventionally achieved by angling the ball‟s seam obliquely to its direction of travel and caring 20

for the ball so that one side is shiny and smooth and the other dull or rough. A more modern 21

variant of this flight characteristic is “Reverse swing”, which originally gained prominence in 22

Pakistan in the 1970s, with the success of players such as Sarfraz Nawaz, Imran Khan, Wasim 23

Akram and Waqar Younis. These players experimented with ball care and grips and found they 24

22

could achieve reverse swing, by focussing less on keeping the ball smooth and shiny on one side, 1

and bowling the ball with the rough side forward (rotating the ball 180o from the traditional 2

position for swing bowling).[83]

The prominence of this technique in Pakistan has been attributed 3

to the specific environmental conditions such as hard dry grounds resulting in balls enduring 4

greater wear and tear at a faster rate.[83]

Reverse swing fast bowling is now considered one of the 5

most potent forms of attacking bowling in cricket, seldom mastered but often aspired to in elite 6

level fast bowling. 7

In other sports, performance paradigm shifts have been created by: 8

(i) equipment changes (e.g., the change from bamboo to fibre glass pole vaults 9

leading to the World record increasing from around 4.5m to 6.14m in a vault by 10

Sergey Bubka in 1993); 11

(ii) changes to playing surfaces (such as international hockey matches on artificial turf 12

instead of grass), which may explain the ebb and flow of current performance 13

standings and international rankings between countries; and 14

(iii) rule changes, such as the turn-over law in rugby union or the distance of the three-15

point line in the Olympics versus the NBA. 16

In elite sport, the drive for success means that performers are being challenged constantly 17

to co-adapt to succeed. Through co-adaptation, players need to add new skills or strategies in the 18

off-season in order to continue to challenge opponents with new problems.[84]

Essentially, players 19

have to constantly re-invent themselves or demonstrate an ability to adapt to the strategies 20

developed by opponents. A good example of this adaptation was observed in 2008 in cricket 21

when the use of „switch hitting‟ by Kevin Pieterson (a current English test batsman) was first 22

formalised. He developed a strategy of changing his stance (from his typically right-handed 23

23

position) as a bowler was in the process of delivering a ball, by „jumping‟ into a left-handed 1

stance in order to overcome the restrictive field placings of opponents in one-day cricket. 2

The idea of sub-systems co-adapting to constraints imposed by other sub-systems of the 3

body is influential in a dynamic systems analysis of motor development across the lifespan.[80]

4

For example, during children‟s motor development, dynamic systems analysts emphasise the idea 5

that specific behaviours may not have yet appeared in developing children, because specific sub-6

systems act as system „rate limiters‟ and are „lying in wait‟ for another critical sub-system to 7

reach a critical level (e.g., changes in the muscle to fat ratio in infants to enable upright postural 8

control). In the performance of specific sports, various sub-systems could be critical to the 9

performance development in athletes, such as strength, speed, mobility, or game understanding as 10

a result of numerous experiences. 11

12

5. Conclusion 13

Historically, expertise research has typically focused either on the role of nature (genes) 14

or nurture (environment) as mechanisms for understanding how experts emerge in performance 15

domains such as sport. This dualist approach has failed to emulate the complementary nature of 16

the relationship between individual and environmental constraints. Although numerous hours of 17

training are needed at the elite level, attainment of an expert level of skill is not accomplished by 18

hours of deliberate practice alone. Similarly, the importance of an individual‟s genetic make up 19

has been accentuated with biased interpretation of genomic studies. In recent years sport 20

performance research has encompassed a move toward multi-dimensional models of performance 21

and learning in sport, with significant implications for understanding processes of expertise and 22

talent development. In this article we have shown how dynamical systems theory and the 23

24

complexity sciences might provide the basis of an interactionist perspective on expertise 1

acquisition in sports. 2

Dynamical systems theory is an appropriate functional framework for expert performance 3

research because it can be used to consider developing athletes as nonlinear, complex 4

neurobiological systems. It avoids the organismic asymmetry which can be observed in 5

traditional models of expertise acquisition and talent development, addressing questions that 6

other frameworks do not have the language and tools to pose. This paper has highlighted several 7

concepts with important implications for expertise and talent development researchers, including 8

the concepts of self-organisation under constraints; emergence; meta-stability, creativity; 9

degeneracy; system stabilities and instabilities over different timescales. Within this overarching 10

theoretical framework it has been argued that the same performance outcomes can be achieved in 11

diverse ways as individual performers attempt to satisfy the unique constraints on them.[20]

12

Genetic diversity may be responsible for a small part of training or performance response 13

differences between individuals, and only when there is a favourable interaction with important 14

environmental constraints are performance benefits observed. Phenotypic expression of 15

behaviour might be best understood at the level of individual interactions with key environmental 16

and task constraints. Given differences in genetic contributions, performance variations are more 17

likely to assert themselves under intensive practice regimes. Common optimal pathways to 18

performance expertise are not expected because of neurobiological degeneracy characterising 19

each individual performer and the effect of interactions between environmental and personal 20

constraints on the intrinsic dynamics of each learner. 21

The acquisition of expertise is domain specific and involves adaptation to performance 22

environments through satisfying unique constraints which impinge on each developing expert. 23

25

Expertise acquisition emphasizes the changing nature of the performer-environment relationship 1

through development, and gaining experience through training, practice, coaching and 2

competing. A comprehensive examination of expertise involves identifying the intrinsic 3

dynamics of each individual and the specific rate limiters and constraints which shape their 4

behaviour. Each individual athlete comes to a performance context with a particular set of 5

intrinsic dynamics which has already been shaped by genes, development and early experiences. 6

Individualised pathways to expert performance are expected because of the uniqueness of these 7

dynamics constraints. 8

9

10

11

Acknowledgments. 12

No sources of funding were used to assist in the preparation of this review. The authors have no 13

conflicts of interest that are directly relevant to the content of this review. 14

15

26

[1] Howe MJA, Davidson JW, Sloboda JA. Innate talents: Reality or myth? Behavioral and 1

Brain Sciences. 1998;21(3):399-407. 2

[2] Dunwoody PT. The Neglect of the Environment by Cognitive Psychology. Journal of 3

Theoretical and Philosophical Psychology. 2006;26:139-53. 4

[3] Ericsson KA, Krampe RT, Tesch-Romer C. The role of deliberate practice in the 5

acquisition of expert performance. Psychological Review. 1993;100(3):363-406. 6

[4] Starkes JL, Deakin JM, Allard F, Hodges NJ, Hayes A. The road to excellence: The 7

acquisition of expert performance in the arts and sciences, sports and games. In: Ericsson KA, ed. 8

Deliberate practice in sports: What is it anyway? Mahwah, NJ: Lawrence Erlbaum Associates 9

1996:81–106. 10

[5] Rankinen T, Bray MS, Hagberg JM, Perusse L, Roth SM, Wolfarth B, et al. The human 11

gene map for performance and health-related fitness phenotypes: the 2005 update. Medicine and 12

Science in Sports and Exercise. 2006;38(11):1863-88. 13

[6] Carter JEL, Heath B. Somatotyping: Development and Applications. Cambridge: 14

Cambridge University Press 1990. 15

[7] Abbott A, Button C, Pepping G-J, Collins D. Unnatural selection: talent identification and 16

development in sport. Nonlinear Dynamics, Psychology, & Life Sciences. 2005 Jan;9(1):61-88. 17

[8] Vaeyens R, Lenoir M, Williams AM, Philippaerts RM. Talent Identification and 18

Development Programmes in Sport: Current Models and Future Directions. Sports Medicine. 19

2008;38(9):703-14. 20

[9] Simonton DK. Talent and Its Development: An Emergenic and Epigenetic Model. 21

Psychological Review. 1999;106(3):435-57. 22

[10] Gagné F. Transforming gifts into talents: the DMGT as a developmental theory. High 23

Ability Studies. 2004. 24

[11] McGarry T, Anderson DI, Wallace SA, Hughes MD, Franks IM. Sport competition as a 25

dynamical self-organizing system. Journal of Sports Sciences. 2002;20:771-81. 26

[12] Chow JY, Davids K, Button C, Shuttleworth R, Renshaw I, Araujo D. Nonlinear 27

Pedagogy: A Constraints-Led Framework for Understanding Emergence of Game Play and 28

Movement Skills. Nonlinear Dynamics, Psychology, & Life Sciences. 2006;10(1):71-103. 29

[13] Araújo D, Davids K, Serpa S. An ecological approach to expertise effects in decision-30

making in a simulated sailing regatta. Psychology of Sport and Exercise. 2005;6(6):671-92. 31

[14] Araújo D, Davids K, Hristovski R. The ecological dynamics of decision making in sport. 32

Psychology of Sport and Exercise. 2006;7(6):653-76. 33

[15] Liu Y-T, Mayer-Kress G, Newell KM. Qualitative and Quantitative Change in the 34

Dynamics of Motor Learning. Journal of Experimental Psychology: Human Perception and 35

Performance. 2006;32(2):380-93. 36

[16] Newell KM, Liu Y-T, Mayer-Kress G. Time scales in motor learning and development. 37

Psychological Review. 2001;108(1):57-82. 38

[17] Davids K, Renshaw I, Glazier P. Movement Models from Sports Reveal Fundamental 39

Insights into Coordination Processes. Exercise and Sport Sciences Review. 2005;33(1):36-42. 40

[18] Jaitner T, Mendoza L, Schollhorn WI. Analysis of the Long Jump Technique in the 41

Transition From Approach to Takeoff Based on Time-Continuous Kinematic Data. European 42

Journal of Sport Science. 2001;1(5):1-12. 43

[19] Van Emmerik REA, Hamill J, McDermott WJ. Variability and Coordinative Function in 44

Human Gait. Quest. 2005;57:102-23. 45

[20] Hamill J, van Emmerik REA, Heiderscheit BC, Li L. A dynamical systems approach to 46

lower extremity running injuries. Clinical Biomechanics. 1999;14(5):297-308. 47

27

[21] Davids K, Glazier P, Araujo D, Bartlett R. Movement systems as dynamical systems: the 1

functional role of variability and its implications for sports medicine. Sports Medicine. 2

2003;33(4):245-60. 3

[22] Baker J, Côté J, Deakin J. Expertise in Ultra-Endurance Triathletes Early Sport 4

Involvement, Training Structure, and the Theory of Deliberate Practice. Journal of Applied Sport 5

Psychology. 2005;17(1):64 - 78. 6

[23] Davids K, Baker J. Genes, environment and sport performance: Why the Nature-Nurture 7

dualism is no longer relevant. Sports Medicine. 2007;37(11):961-80. 8

[24] Ericsson KA, Smith J. Toward a general theory of expertise: Prospects and limits. New 9

York: Cambridge University Press 1991. 10

[25] Hodges NJ, Starkes JL. Wrestling with the nature of expertise: A sport specific test of 11

Ericsson, Krampe, and Tesch-Römers (1993) theory of deliberate practice. International Journal 12

of Sport Psychology. 1996;27:400-24. 13

[26] Starkes J. The road to expertise: is practice the only determinant? International Journal of 14

Sport Psychology. 2000 10;31(4):431-51. 15

[27] Araújo D. Promoting ecologies where performers exhibit expert interactions. International 16

Journal of Sport Psychology. 2007;38:73-7. 17

[28] Helsen WF, Starkes JL, Hodges NJ. Team sports and the theory of deliberate practice. 18

Journal of Sport & Exercise Psychology. 1998;20:12-34. 19

[29] Baker J, Côté J, Abernethy B. Sport-Specific Practice and the Development of Expert 20

Decision-Making in Team Ball Sports. Journal of Applied Sport Psychology. 2003;15(1):12 - 25. 21

[30] Côté J. The influence of the family in the development of talent in sports. The Sport 22

Psychologist. 1999;13:395-417. 23

[31] Soberlak P, Côté J. The developmental activities of elite ice hockey players. Journal of 24

Applied Sport Psychology. 2003 03;15(1):41-9. 25

[32] Young BW, Salmella JH. Diary analyses of practice and recovery activities for elite and 26

intermediate middle distance runners. International Society of Sport Psychology. Skiathos 27

Island: Greece 2001. 28

[33] Weissensteiner J, Abernethy B, Farrow D, Müller S. The Development of Anticipation: A 29

Cross-Sectional Examination of the Practice Experiences Contributing to Skill in Cricket Batting. 30

Journal of Sport & Exercise Psychology. 2008;30:1-23. 31

[34] Yang N, MacArthur DG, Gulbin JP, Hahn AG, Beggs AH, Easteal S, et al. ACTN3 32

Genotype Is Associated with Human Elite Athletic Performance. The American Journal of 33

Human Genetics. 2003;73(3):627-31. 34

[35] Coghlan A. Elite athletes born to run. New Scientist. 2003;30:4-5. 35

[36] Stubbe JH, Boomsma DL, De Geus EJC. Sport participation during adolescence: A shift 36

from environmental to genetic factors. Medicine and Science in Sports and Exercise. 37

2005;37:563-70. 38

[37] Greenspan RJ. The flexible genome. Nature Genetics. 2001;2:383-7. 39

[38] Gabbett T, Georgieff B, Domrow N. The use of physiological, anthropometric, and skill 40

data to predict selection in a talent-identified junior volleyball squad. Journal of Sports Sciences. 41

2007;25(12):1337-44. 42

[39] Hoare DG, Warr CR. Talent identification and women's soccer: An Australian experience. 43

Journal of Sports Sciences. 2000;18:751-8. 44

[40] Morris T. Psychological characteristics and talent identification in soccer. Journal of 45

Sports Sciences. 2000;18(9):715-26. 46

28

[41] Reilly T, Williams AM, Nevill A, Franks A. A multidisciplinary approach to talent 1

identification in soccer. Journal of Sports Sciences. 2000;18:695-702. 2

[42] Falk B, Lidor R, Lander Y, Lang B. Talent identification and early development of elite 3

water-polo players: a 2-year follow-up study. Journal of Sports Sciences. 2004;22(4):347 - 55. 4

[43] Elferink-Gemser MT, Visscher C, Lemmink KAPM, Mulder T. Multidimensional 5

performance characteristics and standard of performance in talented youth field hockey players: 6

A longitudinal study. Journal of Sports Sciences. 2007;25(4):481 - 9. 7

[44] Araujo D, Davids K, Passos P. Ecological Validity, Representative Design, and 8

Correspondence Between Experimental Task Constraints and Behavioral Setting: Comment on 9

Rogers, Kadar, and Costall (2005). Ecological Psychology. 2007;19(1):69-78. 10

[45] Williams AM, Ward P. Perceptual-cognitive expertise in sport: exploring new horizons. 11

In: Tenenabum G, Eklund R, eds. Handbook of sport psychology. 3 ed. New York: John Wiley & 12

Sons 2007:203-23. 13

[46] Williams AM, Ericsson KA. Perceptual-cognitive expertise in sport: Some considerations 14

when applying the expert performance approach. Human Movement Science. 2005;24:283-307. 15

[47] Abernethy B, Wood J. Do generalized visual training programmes for sport really work? 16

An experimental investigation. Journal of Sports Sciences. 2001;19:203-22. 17

[48] van der Kamp J, Rivas F, van Doorn H, Savelsbergh GJP. Ventral and dorsal system 18

contribution to visual anticipation in fast ball sports. International Journal of Sport Psychology, 19

39, 100-130 2008;39:100-30. 20

[49] Müller S, Abernethy B. Batting with occluded vision: An in situ examination of the 21

information pick-up and interceptive skills of high- and low-skilled cricket batsmen. . Journal of 22

Science and Medicine in Sport. 2006;9:446-58. 23

[50] Williams AM, Ericsson KA. Perceptual-cognitive expertise in sport: Some considerations 24

when applying the expert performance approach. Human Movement Science. 2005;24:283–307. 25

[51] Gould D, Dieffenbach K, Moffett A. Psychological characteristics and their development 26

in Olympics Champions. Journal of Applied Sport Psychology. 2002;14(3):172-204. 27

[52] Durand-Bush N, Salmela J. The Development and Maintenance of Expert Athletic 28

Performance: Perceptions of World and Olympic Champions. Journal of Applied Sport 29

Psychology. 2002;14(3):154-71. 30

[53] Côté J, Hay J. Children‟s involvement in sport: A developmental perspective. In: Silva 31

JM, Stevens D, eds. Psychological foundations of sport. Boston: Merrill 2002:2nd ed, 484–502. 32

[54] Kauffman SA. The Origins of Order: Self-organization and Selection in Evolution. New 33

York: Oxford University Press 1993. 34

[55] Bak P, Chialvo DR. Adaptive learning by extremal dynamics and negative feedback. 35

Physical Review. 2001;63(3):031912. 36

[56] Sumpter DJT. The principles of collective animal behaviour. Philosophical Transactions 37

of the Royal Society B: Biological Sciences. 2006;361:5-22. 38

[57] Edelman GM, Gally JA. Degeneracy and complexity in biological systems. National 39

Academy of Sciences; 2001; USA; 2001. p. 13763-8. 40

[58] Obler LK, Fein D. The exceptional brain: Neuropsychology of talent and special abilities. 41

New York: Guilford Press 1988. 42

[59] Schöellhorn WI. Coordination Dynamics and its Consequences on Sport. International 43

Journal of Computer Science in Sport. 2003;2:40-6. 44

[60] Chow JY, Davids K, Button C, Koh M. Coordination changes in a discrete multi-articular 45

action as a function of practice. Acta Psychologica. 2008;127(1):163-76. 46

29

[61] Davids K, Araújo D, Button C, Renshaw I. Degenerate brains, indeterminate behavior and 1

representative tasks: Implications for experimental design in sport psychology research. In: 2

Tenenbaum G, Eklund R, eds. Handbook of sport psychology (3rd ed). New York: Wiley 2007. 3

[62] Kærns M, Elston TC, Blake W, Collins JJ. Stochasticity in gene expression: From 4

theories to phenotypes. Nature Reviews Genetics. 2005;6:451-64. 5

[63] Wolstencroft E. Talent Identification and Development: An Academic Review. 6

Edinburgh: sportscotland; 2002. 7

[64] Beek PJ, Jacobs DM, Daffertshofer A, Huys R. Expert Performance in Sport: Views From 8

the Joint Perspectives of Ecological Psychology and Dynamical Systems Theory. In: Starkes JL, 9

Ericsson KA, eds. Expert Performance in Sport 2003:321-44. 10

[65] Newell KM. Constraints on the development of coordination. In: Wade MG, Whiting 11

HTA, eds. Motor skill acquisition in children: Aspects of coordination and control. Amdsterdam: 12

Martinies NIJHOS 1986:341-60. 13

[66] Kelso JAS. Anticipatory dynamical systems, intrinsic pattern dynamics and skill learning. 14

Human Movement Science. 1991;10:93-111. 15

[67] Thelen E. Motor development: A new synthesis. American Psychologist. 1995;50:79-95. 16

[68] Davids K, Button C, Bennett S. Dynamics of Skill Acquisition: A Constraints-Led 17

Approach. Champaign, Il: Human Kinetics 2008. 18

[69] Corbetta D, Veriejken B. Understanding development and learning of motor coordination 19

in sport: The contribution of dynamical systems theory. International Journal of Sport 20

Psychology. 1999;30(44):507-30. 21

[70] Zanone PG, Kelso JAS. Learning and transfer as dynamical paradigms for behavioral 22

change. Advances in psychology. 1992;87(3):563-82. 23

[71] Pyne DB, Duthie G, Saunders PU, Petersen CA, Portus MR. Anthropometric and strength 24

correlates of fast bowling speed in junior and senior cricketers. Journal of Strength & 25

Conditioning Research. 2006;20(3):620-6. 26

[72] Renshaw I, Davids K, Chow J, Shuttleworth R. Insights from Ecological Psychology and 27

Dynamical Systems Theory Can Underpin a Philosophy of Coaching. International Journal of 28

Sport Psychology. In Press. 29

[73] Baker J, Horton S. A review of primary and secondary influences on sport expertise. High 30

Ability Studies. 2004;15(2):211 - 28. 31

[74] Hammond KR, Bateman RA. Sport Psychology as an instance of Ecological Psychology. 32

International Journal of Sport Psychology. 2009 01;40(1):38-49. 33

[75] Abernethy B. Sport expertise: From theory to practice. Applied Sport Expertise and 34

Learning Workshop. Canberra, Australia 2005. 35

[76] Australian Bureau of Statistics. Wagga Wagga (Urban Centre/Locality). 2006 Census 36

QuickStats. [cited 2009 May 10]; Available from: 37

http://www.censusdata.abs.gov.au/ABSNavigation/prenav/LocationSearch 38

[77] Côté J, Macdonald DJ, Baker J, Abernethy B. When „„where‟‟ is more important than 39

„„when‟‟: Birthplace and birthdate effects on the achievement of sporting expertise. Journal of 40

Sports Sciences. 2006;24(10). 41

[78] Handford C, Davids K, Bennett S, Button C. Skill acquisition in sport: Some applications 42

of an evolving practice ecology. Journal of Sports Sciences. 1997;15(6):621-40. 43

[79] Thelen E, Smith LB. A dynamics systems approach to the development of perception and 44

action: MIT Press 1994. 45

[80] Thelen E. Motor development: A new synthesis. American Psychologist. 1995;50(2):79-46

95. 47

30

[81] Cobley S, Baker J, Wattie N, McKenna J. Annual Age-Grouping and Athlete 1

Development: A Meta-Analytical Review of Relative Age Effects in Sport. Sports Medicine. 2

2009;39(3):235-56. 3

[82] Anderson DI. Do critical periods determine when to initiate sport skill learning? . In: 4

Smoll FL, Smith RE, eds. Children and Youth in Sports: A Biopsychosocial Perspective. 2 ed. 5

Indianapolis: Brown & Benchmark 2002:pp105-48. 6

[83] Mehta RD. Cricket ball aerodynamics: myth versus science. In: Subic AJ, Hakke SJ, eds. 7

The Engineering of Sport Research, Development and Innovation. Oxford: Blackwell Science 8

2000:153-67. 9

[84] Cowdrey MC. Tackle Cricket. London: Stanley Paul 1974. 10

11

Brain Sciences. 1998;21(3):399-407. 12

[2] Dunwoody PT. The Neglect of the Environment by Cognitive Psychology. Journal of 13

Theoretical and Philosophical Psychology. 2006;26:139-53. 14

[3] Starkes JL, Deakin JM, Allard F, Hodges NJ, Hayes A. The road to excellence: The 15

acquisition of expert performance in the arts and sciences, sports and games. In: Ericsson KA, ed. 16

Deliberate practice in sports: What is it anyway? Mahwah, NJ: Lawrence Erlbaum Associates 17

1996:81–106. 18

[4] Rankinen T, Bray MS, Hagberg JM, Perusse L, Roth SM, Wolfarth B, et al. The human 19

gene map for performance and health-related fitness phenotypes: the 2005 update. Medicine and 20

Science in Sports and Exercise. 2006;38(11):1863-88. 21

[5] Carter JEL, Heath B. Somatotyping: Development and Applications. Cambridge: 22

Cambridge University Press 1990. 23

[6] Abbott A, Button C, Pepping G-J, Collins D. Unnatural selection: talent identification and 24

development in sport. Nonlinear Dynamics, Psychology, & Life Sciences. 2005 Jan;9(1):61-88. 25

[7] Vaeyens R, Lenoir M, Williams AM, Philippaerts RM. Talent Identification and 26

Development Programmes in Sport: Current Models and Future Directions. Sports Medicine. 27

2008;38(9):703-14. 28

[8] Simonton DK. Talent and Its Development: An Emergenic and Epigenetic Model. 29

Psychological Review. 1999;106(3):435-57. 30

[9] Gagné F. Transforming gifts into talents: the DMGT as a developmental theory. High 31

Ability Studies. 2004. 32

[10] McGarry T, Anderson DI, Wallace SA, Hughes MD, Franks IM. Sport competition as a 33

dynamical self-organizing system. Journal of Sports Sciences. 2002;20:771-81. 34

[11] Chow JY, Davids K, Button C, Shuttleworth R, Renshaw I, Araujo D. Nonlinear 35

Pedagogy: A Constraints-Led Framework for Understanding Emergence of Game Play and 36

Movement Skills. Nonlinear Dynamics, Psychology, & Life Sciences. 2006;10(1):71-103. 37

[12] Araújo D, Davids K, Serpa S. An ecological approach to expertise effects in decision-38

making in a simulated sailing regatta. Psychology of Sport and Exercise. 2005;6(6):671-92. 39

[13] Araújo D, Davids K, Hristovski R. The ecological dynamics of decision making in sport. 40

Psychology of Sport and Exercise. 2006;7(6):653-76. 41

[14] Liu Y-T, Mayer-Kress G, Newell KM. Qualitative and Quantitative Change in the 42

Dynamics of Motor Learning. Journal of Experimental Psychology: Human Perception and 43

Performance. 2006;32(2):380-93. 44

[15] Newell KM, Liu Y-T, Mayer-Kress G. Time scales in motor learning and development. 45

Psychological Review. 2001;108(1):57-82. 46

31

[16] Davids K, Renshaw I, Glazier P. Movement Models from Sports Reveal Fundamental 1

Insights into Coordination Processes. Exercise and Sport Sciences Review. 2005;33(1):36-42. 2

[17] Jaitner T, Mendoza L, Schollhorn WI. Analysis of the Long Jump Technique in the 3

Transition From Approach to Takeoff Based on Time-Continuous Kinematic Data. European 4

Journal of Sport Science. 2001;1(5):1-12. 5

[18] Van Emmerik REA, Hamill J, McDermott WJ. Variability and Coordinative Function in 6

Human Gait. Quest. 2005;57:102-23. 7

[19] Hamill J, van Emmerik REA, Heiderscheit BC, Li L. A dynamical systems approach to 8

lower extremity running injuries. Clinical Biomechanics. 1999;14(5):297-308. 9

[20] Davids K, Glazier P, Araujo D, Bartlett R. Movement systems as dynamical systems: the 10

functional role of variability and its implications for sports medicine. Sports Medicine. 11

2003;33(4):245-60. 12

[21] Baker J, Côté J, Deakin J. Expertise in Ultra-Endurance Triathletes Early Sport 13

Involvement, Training Structure, and the Theory of Deliberate Practice. Journal of Applied Sport 14

Psychology. 2005;17(1):64 - 78. 15

[22] Davids K, Baker J. Genes, environment and sport performance: Why the Nature-Nurture 16

dualism is no longer relevant. Sports Medicine. 2007;37(11):961-80. 17

[23] Ericsson KA, Smith J. Toward a general theory of expertise: Prospects and limits. New 18

York: Cambridge University Press 1991. 19

[24] Ericsson KA, Krampe RT, Tesch-Romer C. The role of deliberate practice in the 20

acquisition of expert performance. Psychological Review. 1993;100(3):363-406. 21

[25] Hodges NJ, Starkes JL. Wrestling with the nature of expertise: A sport specific test of 22

Ericsson, Krampe, and Tesch-Römers (1993) theory of deliberate practice. International Journal 23

of Sport Psychology. 1996;27:400-24. 24

[26] Starkes J. The road to expertise: is practice the only determinant? International Journal of 25

Sport Psychology. 2000 10;31(4):431-51. 26

[27] Araújo D. Promoting ecologies where performers exhibit expert interactions. International 27

Journal of Sport Psychology. 2007;38:73-7. 28

[28] Helsen WF, Starkes JL, Hodges NJ. Team sports and the theory of deliberate practice. 29

Journal of Sport & Exercise Psychology. 1998;20:12-34. 30

[29] Baker J, Côté J, Abernethy B. Sport-Specific Practice and the Development of Expert 31

Decision-Making in Team Ball Sports. Journal of Applied Sport Psychology. 2003;15(1):12 - 25. 32

[30] Côté J. The influence of the family in the development of talent in sports. The Sport 33

Psychologist. 1999;13:395-417. 34

[31] Soberlak P, Côté J. The developmental activities of elite ice hockey players. Journal of 35

Applied Sport Psychology. 2003 03;15(1):41-9. 36

[32] Young BW, Salmella JH. Diary analyses of practice and recovery activities for elite and 37

intermediate middle distance runners. International Society of Sport Psychology. Skiathos 38

Island: Greece 2001. 39

[33] Weissensteiner J, Abernethy B, Farrow D, Müller S. The Development of Anticipation: A 40

Cross-Sectional Examination of the Practice Experiences Contributing to Skill in Cricket Batting. 41

Journal of Sport & Exercise Psychology. 2008;30:1-23. 42

[34] Yang N, MacArthur DG, Gulbin JP, Hahn AG, Beggs AH, Easteal S, et al. ACTN3 43

Genotype Is Associated with Human Elite Athletic Performance. The American Journal of 44

Human Genetics. 2003;73(3):627-31. 45

[35] Coghlan A. Elite athletes born to run. New Scientist. 2003;30:4-5. 46

32

[36] Stubbe JH, Boomsma DL, De Geus EJC. Sport participation during adolescence: A shift 1

from environmental to genetic factors. Medicine and Science in Sports and Exercise. 2

2005;37:563-70. 3

[37] Greenspan RJ. The flexible genome. Nature Genetics. 2001;2:383-7. 4

[38] Gabbett T, Georgieff B, Domrow N. The use of physiological, anthropometric, and skill 5

data to predict selection in a talent-identified junior volleyball squad. Journal of Sports Sciences. 6

2007;25(12):1337-44. 7

[39] Hoare DG, Warr CR. Talent identification and women's soccer: An Australian experience. 8

Journal of Sports Sciences. 2000;18:751-8. 9

[40] Morris T. Psychological characteristics and talent identification in soccer. Journal of 10

Sports Sciences. 2000;18(9):715-26. 11

[41] Reilly T, Williams AM, Nevill A, Franks A. A multidisciplinary approach to talent 12

identification in soccer. Journal of Sports Sciences. 2000;18:695-702. 13

[42] Elferink-Gemser MT, Visscher C, Lemmink KAPM, Mulder T. Multidimensional 14

performance characteristics and standard of performance in talented youth field hockey players: 15

A longitudinal study. Journal of Sports Sciences. 2007;25(4):481 - 9. 16

[43] Araujo D, Davids K, Passos P. Ecological Validity, Representative Design, and 17

Correspondence Between Experimental Task Constraints and Behavioral Setting: Comment on 18

Rogers, Kadar, and Costall (2005). Ecological Psychology. 2007;19(1):69-78. 19

[44] Falk B, Lidor R, Lander Y, Lang B. Talent identification and early development of elite 20

water-polo players: a 2-year follow-up study. Journal of Sports Sciences. 2004;22(4):347 - 55. 21

[45] Williams AM, Ward P. Perceptual-cognitive expertise in sport: exploring new horizons. 22

In: Tenenabum G, Eklund R, eds. Handbook of sport psychology. 3 ed. New York: John Wiley & 23

Sons 2007:203-23. 24

[46] Williams AM, Ericsson KA. Perceptual-cognitive expertise in sport: Some considerations 25

when applying the expert performance approach. Human Movement Science. 2005;24:283-307. 26

[47] Abernethy B, Wood J. Do generalized visual training programmes for sport really work? 27

An experimental investigation. Journal of Sports Sciences. 2001;19:203-22. 28

[48] van der Kamp J, Rivas F, van Doorn H, Savelsbergh GJP. Ventral and dorsal system 29

contribution to visual anticipation in fast ball sports. International Journal of Sport Psychology, 30

39, 100-130 2008;39:100-30. 31

[49] Müller S, Abernethy B. Batting with occluded vision: An in situ examination of the 32

information pick-up and interceptive skills of high- and low-skilled cricket batsmen. . Journal of 33

Science and Medicine in Sport. 2006;9:446-58. 34

[50] Williams AM, Ericsson KA. Perceptual-cognitive expertise in sport: Some considerations 35

when applying the expert performance approach. Human Movement Science. 2005;24:283–307. 36

[51] Gould D, Dieffenbach K, Moffett A. Psychological characteristics and their development 37

in Olympics Champions. Journal of Applied Sport Psychology. 2002;14(3):172-204. 38

[52] Durand-Bush N, Salmela J. The Development and Maintenance of Expert Athletic 39

Performance: Perceptions of World and Olympic Champions. Journal of Applied Sport 40

Psychology. 2002;14(3):154-71. 41

[53] Côté J, Hay J. Children‟s involvement in sport: A developmental perspective. In: Silva 42

JM, Stevens D, eds. Psychological foundations of sport. Boston: Merrill 2002:2nd ed, 484–502. 43

[54] Kauffman SA. The Origins of Order: Self-organization and Selection in Evolution. New 44

York: Oxford University Press 1993. 45

[55] Bak P, Chialvo DR. Adaptive learning by extremal dynamics and negative feedback. 46

Physical Review. 2001;63(3):031912. 47

33

[56] Sumpter DJT. The principles of collective animal behaviour. Philosophical Transactions 1

of the Royal Society B: Biological Sciences. 2006;361:5-22. 2

[57] Edelman GM, Gally JA. Degeneracy and complexity in biological systems. National 3

Academy of Sciences; 2001; USA; 2001. p. 13763-8. 4

[58] Obler LK, Fein D. The exceptional brain: Neuropsychology of talent and special abilities. 5

New York: Guilford Press 1988. 6

[59] Schöellhorn WI. Coordination Dynamics and its Consequences on Sport. International 7

Journal of Computer Science in Sport. 2003;2:40-6. 8

[60] Chow JY, Davids K, Button C, Koh M. Coordination changes in a discrete multi-articular 9

action as a function of practice. Acta Psychologica. 2008;127(1):163-76. 10

[61] Davids K, Araújo D, Button C, Renshaw I. Degenerate brains, indeterminate behavior and 11

representative tasks: Implications for experimental design in sport psychology research. In: 12

Tenenbaum G, Eklund R, eds. Handbook of sport psychology (3rd ed). New York: Wiley 2007. 13

[62] Kærns M, Elston TC, Blake W, Collins JJ. Stochasticity in gene expression: From 14

theories to phenotypes. Nature Reviews Genetics. 2005;6:451-64. 15

[63] Wolstencroft E. Talent Identification and Development: An Academic Review. 16

Edinburgh: sportscotland; 2002. 17

[64] Beek PJ, Jacobs DM, Daffertshofer A, Huys R. Expert Performance in Sport: Views From 18

the Joint Perspectives of Ecological Psychology and Dynamical Systems Theory. In: Starkes JL, 19

Ericsson KA, eds. Expert Performance in Sport 2003:321-44. 20

[65] Newell KM. Constraints on the development of coordination. In: Wade MG, Whiting 21

HTA, eds. Motor skill acquisition in children: Aspects of coordination and control. Boston, MA: 22

Martinies NIJHOS 1986:341-60. 23

[66] Kelso JAS. Anticipatory dynamical systems, intrinsic pattern dynamics and skill learning. 24

Human Movement Science. 1991;10:93-111. 25

[67] Thelen E. Motor development: A new synthesis. American Psychologist. 1995;50:79-95. 26

[68] Davids K, Button C, Bennett S. Dynamics of Skill Acquisition: A Constraints-Led 27

Approach. Champaign, Il: Human Kinetics 2008. 28

[69] Corbetta D, Veriejken B. Understanding development and learning of motor coordination 29

in sport: The contribution of dynamical systems theory. International Journal of Sport 30

Psychology. 1999;30(44):507-30. 31

[70] Zanone PG, Kelso JAS. Learning and transfer as dynamical paradigms for behavioral 32

change. Advances in psychology. 1992;87(3):563-82. 33

[71] Pyne DB, Duthie G, Saunders PU, Petersen CA, Portus MR. Anthropometric and strength 34

correlates of fast bowling speed in junior and senior cricketers. Journal of Strength & 35

Conditioning Research. 2006;20(3):620-6. 36

[72] Renshaw I, Davids K, Chow J, Shuttleworth R. Insights from Ecological Psychology and 37

Dynamical Systems Theory Can Underpin a Philosophy of Coaching. International Journal of 38

Sport Psychology. In Press. 39

[73] Baker J, Horton S. A review of primary and secondary influences on sport expertise. High 40

Ability Studies. 2004;15(2):211 - 28. 41

[74] Hammond KR, Bateman RA. Sport Psychology as an instance of Ecological Psychology. 42

International Journal of Sport Psychology. 2009 01;40(1):38-49. 43

[75] Abernethy B. Sport expertise: From theory to practice. Applied Sport Expertise and 44

Learning Workshop. Canberra, Australia 2005. 45

34

[76] Australian Bureau of Statistics. Wagga Wagga (Urban Centre/Locality). 2006 Census 1

QuickStats. [cited 2009 May 10]; Available from: 2

http://www.censusdata.abs.gov.au/ABSNavigation/prenav/LocationSearch 3

[77] Côté J, Macdonald DJ, Baker J, Abernethy B. When „„where‟‟ is more important than 4

„„when‟‟: Birthplace and birthdate effects on the achievement of sporting expertise. Journal of 5

Sports Sciences. 2006;24(10). 6

[78] Handford C, Davids K, Bennett S, Button C. Skill acquisition in sport: Some applications 7

of an evolving practice ecology. Journal of Sports Sciences. 1997;15(6):621-40. 8

[79] Thelen E, Smith LB. A dynamics systems approach to the development of perception and 9

action: MIT Press 1994. 10

[80] Thelen E. Motor development: A new synthesis. American Psychologist. 1995;50(2):79-11

95. 12

[81] Cobley S, Baker J, Wattie N, McKenna J. Annual Age-Grouping and Athlete 13

Development: A Meta-Analytical Review of Relative Age Effects in Sport. Sports Medicine. 14

2009;39(3):235-56. 15

[82] Anderson DI. Do critical periods determine when to initiate sport skill learning? . In: 16

Smoll FL, Smith RE, eds. Children and Youth in Sports: A Biopsychosocial Perspective. 2 ed. 17

Indianapolis: Brown & Benchmark 2002:pp105-48. 18

[83] Mehta RD. Cricket ball aerodynamics: myth versus science. In: Subic AJ, Hakke SJ, eds. 19

The Engineering of Sport Research, Development and Innovation. Oxford: Blackwell Science 20

2000:153-67. 21

[84] Cowdrey MC. Tackle Cricket. London: Stanley Paul 1974. 22

23

References to add to the list: 24

25

Rose, S.P.R. (2005). Human agency in the neurocentric age. European Molecular Biology 26

Organization 6, 1001-1005. 27

Yarrow, K., Brown, P. & Krakauer, J.W. ( 2009). Inside the brain of an elite athlete: the 28

neural processes that support high achievement in sports. Nature Reviews Neuroscience 29

10, 585-596. 30

31

32

33