International Journal of Performance Analysis in Sport 2012, 12, 208-221.
‘Knowledge Representation and Pattern Recognition Skills of Elite Adult and Youth Soccer Players’ David J. Evans1, Peter Whipp2 and Brendan S. Lay2 1
Central Institute of Technology, Western Australia
2
University of Western Australia, School of Sport Science, Exercise and Health, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009
Abstract This study investigated knowledge representation and pattern of play recognition skills of elite adult and youth soccer players, while participating in conditioned phases of play. Players (n = 16) participated in their own expertise group and verbal reports were transcribed and coded into concepts (Goals, Conditions, Actions) based on a modified model of protocol structure used for tennis by (McPherson & Kernodle 2007). A Mann Whitney test was used to analyse the mean scores of the participants for knowledge representation and a Chi Square test was performed using percentage scores to identify differences in the players’ ability to recognise patterns of play. The study showed that adult experts (n = 8) were able to generate more content and details, when verbalising their cognitive thought processes in game situations than youth (n = 8) elite players. The findings support previous research in that more experienced adult players are able to consistently call upon more developed long term memory whilst processing information with the existence of action plans and current event profiles. Differences were recorded in the percentage scores for players’ ability to recognise patterns of play, which provide evidence that elite youth players’ game-reading skills (pattern recognition) are as well developed as elite adults. Key Words: Cognitive skill, youth soccer, elite, patterns of play 1. Introduction
Elite players in every sport are able to make the correct decisions at crucial periods during games. Over the past few decades there has been an increase in the study of thought processes and decision making skills in expert performance for elite and nonelite athletes (Abernethy, Neal & Koning, 1994; French, Nevett, Spurgeon, Graham, Rink, & McPherson, 1996; Helsen & Starkes, 1999; Simon & Chase, 1973; Vaeyens, Lenoir, Williams, Mayzn, & Phillippaerts, 2007; Ward & Williams 2003). To perform at the highest level an athlete must develop both their physical and cognitive skills. This study concentrated on the cognitive processes of soccer players in relation to their knowledge representation and pattern recognition skills. Researchers who employ sport performance paradigms during game play to examine players’ response selection
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(cognitive skills) and response execution (motor skills) indicate that both variables contribute to the development of expertise (McPherson, 1993). One of the earliest works to determine expertise and performance was conducted by (Simon & Chase, 1973) who used international and club chess players to measure short term memory skills. They attributed the performance by experts to their superior ability to store knowledge and complex patterns, acquired over years of practice. The chunking together of perceptual information and the recognition of different scenarios during phases of play results in what Abernethy (1991) describes as the time paradox where skilled performers operating under extreme time constraints appear to have ‘all the time in the world’. (French et al., 1996) examined differences in knowledge representation and problem solution in youth baseball players. They found differences occur between expert and novice players (9 to 10 yr old) in problem solutions for complex game situations. (Abernethy et al., 1994) investigated cognitive differences between expert intermediate and novice snooker players. Within soccer (Helsen & Starkes, 1999) used a multidimensional approach to examine skilled perception and performance. McPherson (1993), as well as McPherson and Kernodle (2007) created verbal reports to compare the tactical skills of different level tennis players. These studies provided evidence that experts retain, recall and recognise significantly more information about structured game situations than sub-elite athletes, when information is presented in the athletes sport specific domain. The findings also provide evidence that expertise in ‘open’ skill sports arise from the cognitive processing strategies as opposed to physical capabilities. In soccer there have been a number of studies conducted between expert and non-expert players of varying ages. As previously mentioned, Helsen and Starkes (1999) used slides and film simulations to examine expertise in soccer with expert and intermediate players, they were in agreement with McPherson and Thomas (1989), Allard and Starkes (1991) that a distinguishing feature of experts is their adeptness at both ‘knowing’ what to do and ‘doing it’. Film sequences of 11 v 11 patterns of play in soccer were first used to examine visual search strategies in experienced and inexperienced soccer players (Williams, Davids, Burwitz, & Williams, 1994). It was found that experienced players exhibited superior anticipation skills than inexperienced, due to higher search rates (fixations) on more locations within the field of play. Later Ward and Williams (2003) also used 11 v 11 patterns of play to assess perceptual and cognitive skills of elite and sub-elite soccer players via the use of situational probabilities (players expectations of what will happen). They reported that memory recall of structured patterns of play was not predicted by age. As early as 9 years old, elite soccer players demonstrated superior perceptual and cognitive skills when compared to their sub-elite counterparts. They argue that the age for implementing perceptual skills training could be reduced, but the primary goal for training at an early age should be the development of key technical skills before concentrating on practice sessions that would improve their cognitive and game-reading skills. Whilst reviewing perceptual skills in soccer, Williams (2000) stated that skilled players can recall and recognise patterns of play more effectively than their less skilled counterparts. Experts’capacity to more accurately recall and recognise patterns of play has commonly been attributed to their increased ability to subjectively organise (chunk) information into larger more meaningful units of information (see Simon & Chase, 1973). However, more recently expert memory advantage has been accounted for by a 209
more comprehensive theory, namely that of long term working memory (LTWM) (Ericsson & Kintsch, 1995; Tenenbaum, 2003). From an information processing perspective, motor behaviours in competitive situations consist of encoding the relevant environmental cues through the utilisation of attention strategies, processing them through an ongoing interaction between working memory and long-term memory and making an action related decision. Verbalisations of skilled performers offer insights into the knowledge structures that are accessed and used to make decisions prior to executing a task (Hodges, Huys, & Starkes, 2007). Structured questionnaires and verbal reports are two ways to determine knowledge of sports participants. (McRobert, Williams, Ward & Eccles, 2009) used retrospective verbal reports to assess the cognitive representations of skilled and unskilled cricket players. They found that skilled batters were able to engage in deeper planning of potential outcomes, which resulted in a higher percentage of correct anticipations. Abernethy (1994) identified three different types of knowledge that are used to explore expert and novice differences. ‘Declarative knowledge’ knowledge based on factual information. ‘Procedural knowledge’ which is knowledge pertaining how to do something within a particular domain, produce patterns or actions. ‘Strategic knowledge’ which is knowledge of rules concepts and strategies. In sport, players’ utterances collected during actual or simulated tasks reveal information about their problem representations accessed during sport performance. In tennis competition it is proposed that sport experts’ superior decision making skills are due to two adaptations to long term memory termed current event and action plan profiles (McPherson, 1993; McPherson & Kernodle, 2003). They state that novice players have poor problem representation and little experience in memory from which they can draw on to apply action plans. Advanced players, however, with accumulated hours of practice (7,000 to 10,000 hrs), develop current event profiles (memory structures used to keep relevant information active with potential past, current and possible future events) and also action plan profiles (memory structures used to create action plans that match the current conditions in the game, such as player positions). Elite players process information utilising their long term memory which allows them to consider, anticipate and respond, due to specific exposure in their chosen sport domain. The purpose of this investigation was to examine soccer performance skills in relation to pattern recognition and knowledge representation during phase of play scenarios, for adult and youth high performance players. Although a large amount of research to date has concentrated on the comparison of elite versus sub-elite or novice players of similar age, very few studies have compared the decision skills of high performance players of different ages that include adult participants. Soccer is a good domain for studying developmental differences, as players across ages are governed by the same rules, play on the same configured playing area and have the opportunity to execute the same skills or techniques whilst playing in the same positions. The research into expert performance in soccer has been predominantly conducted in a laboratory setting using slides or film simulations to assess the perceptual skills and visual search patterns that are adopted by players. However, research into expertise in tennis (McPherson, 1999; McPherson & Kernodle, 2007) has adopted a more ecologically valid approach to assess the different ability levels of 210
players. This was achieved by recording verbal responses to questions after the completion of points within matches. From the data collected, knowledge representation and pattern recognition skills were interpreted. Verbal reports collected during or immediately following task performance allow investigators to monitor the content of information from long term memory. In addition, information from verbal reports (immediate recall) are most appropriate for assessing problem representations during motor performance tasks (McPherson & Kernodle, 2003). We acknowledge that within the literature, pattern recognition has been traditionally assessed using film simulations in a lab environment. This study uses a field based tactical identification task to maintain the ecological validity similar to McPherson and colleagues. For the remainder of this paper our field based tactical identification task will be referred to as pattern recognition. This study aims to determine if there are any differences in the cognitive processing of adult and youth high performance soccer players in relation to (a) knowledge representation (b) recognising patterns of play. This will be achieved by recording the verbal responses of participants after they have participated in a number of phase of play scenarios for soccer. It is hypothesised that (1) the elite adult soccer players will display greater knowledge representation skills than the youth players, (2) the elite adult players will demonstrate greater pattern recognition capabilities during the phase of play scenarios.
2. Methods 2.1. Participants Consistent with the previous work of McPherson and Kernodle (2007), a similar number of participants were recruited for this study, all were male soccer players. Adult participants (n = 8: mean age 19.2 years SD = 1.75) were elite players playing in the national Under 21s competition for an A-League team in Australia (i.e. the highest level). They had a mean of 12.3 years playing experience and each player on average had taken part in 304 (SD = 27) competitive games. The youth participants (n = 8: mean age 15 years SD = 0.65) were selected from the National Training Centre (NTC) of Western Australia, these participants have been identified as elite players for their age and compete in both state and national competitions. On average they had 6.8 years of playing experience and a mean of 112 (SD = 27) competitive games per player. Participants or parents (for minors) signed an informed consent form and the study was approved by the University’s Human Research Ethics Committee. 2.2. Apparatus In order to collect verbal reports and record immediate responses to interview questions, all the participants had an Olympus WS-110 digital voice recorder fitted in a comfortable position on the participant’s upper arm utilizing Nike iPod holders. In addition a Sony HDR-XR100 digital camcorder was used to record the sequence of plays, in order to verify the patterns of play (described in Procedures) being performed by the attacking players.
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2.3. Procedures The study was conducted on two different occasions, firstly with the adult participants and secondly with the youth. On each occasion the participants were randomly allocated into two sub groups of four players, as the participants in the study would be performing the role of defenders i.e. a back four unit. This meant for each sequence of play they would be inferior numerically (6 attackers v 4 defenders) to the opposing players. Prior to the evaluation a separate group of non-participants were selected to perform the role of the attacking players. These players practiced the patterns of play prior to this study to ensure they were both familiar with and able to consistently perform the different patterns of play for each sequence (that are presented in Table 1). Two experienced soccer coaches (certified by Football Federation Australia) reviewed the attacking sequences and confirmed that they were realistic representations of match situations. Before testing began participants were familiarised with audio recording devices and given an overview of the processes of the experiment. Participants performed warm up tasks giving verbal responses to sport specific questions to ensure that the criteria for giving level I or II verbal reports were met (see Ericsson & Simon, 1993). They also performed in three practice trials giving verbal responses after each phase of play. Where necessary, feedback was given to participants in relation to the clarity of the voice recording along with their start position for the phases of play. Prior to the start of each attacking play, defenders were asked to take up realistic defensive positions on the edge of the penalty area and to hold their position until the second attacking player in the sequence had taken a touch or control of the ball. Once an attacking play had been completed (when there was either a shot on goal or defenders had won the ball) the investigator would hold up a coloured card that indicated the question that was to be answered by the participant. Interview questions were either one of two recall questions 1. ‘What were you thinking during the play?’ or 2. ‘What did you try to do, to prevent the attack being successful?’ or a planning question ‘What are you thinking about now?’ After the final attacking play in each sequence, a pattern of play question was asked ‘Can you identify any attacking patterns of play and what are they?’ Again, participants provided verbal responses to this question on two out of the four sequences and on the other two sequences of play, they used a tick sheet (see Abernethy et al., 1994; Abernethy et al., 2005; Ward & Williams, 2003) which was attached to a clip board (one per player) positioned behind the goal line to record their responses. The tick sheet was utilised for recording information in order to try and tap into different knowledge bases. Research into learning styles for athletes suggests, that one prominent learning style does not manifest; instead there is wide use of different learning styles. Educators should use different learning styles and methodologies to maximise the assimilation of knowledge of learners (González-Haro, Calleja-González & Escanero, 2010). In addition, consistent with recommendations made by González-Haro et al. (2010) in order to access knowledge bases in different learners the tick sheet provided a means to maximise attendance of knowledge of the participants and offered a less discriminative method for collecting data. The colour coded questions were placed under a piece of elastic bandage on the participants forearm. For each sequence the attackers performed the designated pattern of play on four occasions (see Table 1), on three occasions the participants responded to the recall or planning questions and after the final play in the sequence they answered 212
the pattern recognition question either verbally or using the tick sheet. In addition the attackers performed an unrelated drill not particularly linked to any common pattern of play. It is acknowledged that the pattern recognition task is not particularly complex. Previous studies using young participants that have employed complex recall tasks to differentiate between groups, have led to a lack of significance in the results produced (see Ward & Williams, 2003). Patterns were executed to a consistent level throughout the investigation. On the few occasions the phase of play broke down, the investigator would halt the play and instruct the players to re-set their positions and start the sequence again. Participants were not asked to give verbal responses on these occasions. Figure 1(Panel A) shows a frame from an attacking sequence and (Panel B) defending players giving verbal responses. Participants were asked to verbalise their thoughts as accurately as possible to the questions and there was no time constraint for giving their response. Table 1. Sequences of conditioned phases of play performed by the attacking players Sequence Condition Pattern of Play One 5v4 Early crosses into the box Two 6v4 Quick short passes on edge of the box Three 6v4 Third man running in behind defenders Four 6v4 Switching play with long passes
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Panel A
Panel B
Figure 1. Panel A: Attacking players executing an early cross into the penalty box. Panel B: Defending players giving verbal responses into voice recorders. 2.4. Coding verbal reports The verbal reports were coded based on (McPherson, 1993) model of protocol structure for sport and further developed by (McPherson & Kernodle, 2007). Concepts were separated according to the determined unit of information generated by each participant; phrases could contain one or more concepts (McPherson & Kernodle, 2007). Each of the players’ utterances was classified according to three major concept categories: (a) Goal concepts reflects the purpose of an action selected (‘try and close ball carrier down’); (b) Condition concepts specify under what circumstance to apply the action to achieve the goal (‘when the striker gets possession’); (c) Action concepts specify an action selected or patterns of actions which may produce goal related changes in the context of the sporting situation (‘I intercepted the pass’). These three concepts were 214
further examined for composition and sophistication and placed in sub-concept categories. Goals were classified as being about themselves and skill (I tried to head the ball clear) or goals about the opponent and themselves (Just thinking about marking my man and getting pressure on his touch). Conditions and action concepts were examined to see if two or more details were provided. Finally, linkages of concepts were coded from reports containing more than one concept (‘Goal, Condition, Action’) within a response. An individual with previous experience in transcribing verbal reports but blind to the purpose of the investigation was used to transcribe the verbal responses. In addition, the first author encoded a random sample on two occasions and another independent investigator encoded a third sample. Inter/intra observer agreement formulas were used to determine the percentage of agreement for verbal report data (see Thomas & Nelson, 2005). The agreement values for inter and intratester were 85% and 88% respectively. There was no data collected for one participant from the adult group and one participant from the youth group, due to audio failure. 2.5. Data Analysis Knowledge Representation A modified version of protocol structure from (McPherson & Kernodle, 2007) was used to analyse the coded verbal reports to allow quantitative analysis of the data. Each participant was scored separately for content and structure for each response given during the interviews. Concept content was scored for total of major concepts generated i.e. Goal, Condition and Action, totals for sub concepts; goals about self and skill and goals about opponent and self and sophistication of condition and action containing one or more details. Concept structure was scored according to total linkages (responses with two or more concepts). Since the data did not meet assumptions of normality and the sample size was small, a non-parametric Mann-Whitney U test was used to analyse the data (alpha level 0.05). Pattern Recognition To analyse the participant’s ability to recognise patterns of play, a Chi-square test was used, as the responses were either correct or incorrect. Taken into account the sample size, a Fisher’s exact test for count data was implemented instead of a standard Chisquare test (alpha level 0.05). The test is useful for categorical data that result from classifying objects in two different ways; it is used to examine the significance of the association (contingency) between the two kinds of classification (Field, 2009).
3. Results Knowledge Representation The main effects from the Mann-Whitney U test used to analyse scores in both the participant groups for total goals U = 16, z = −1.095, p = 0.274, r = − 0.41, conditions U = 13, Z = −1.479, p = 0.139, r = − 0.56, and actions U = 9.5, Z = −1.938, p = 0.053, r = − 0.73, indicated no significant differences, even though the mean scores for all three were higher for the adult participants. The Mann-Whitney performed on the mean 215
scores for Goals about themselves and skill and opponent and themselves were not significant (p = 0.897, p = 0.220), again the adults recorded higher mean scores for opponent / self. There was a significant difference indicated for Conditions with more than one detail (p < 0.009) but not for Actions with more than one detail (p = 0.511) or linkages with two or more concepts (p = 0.262), although adults had slightly higher mean scores than youth for both of these categories. The mean scores for content, structure and sophistication are presented in Figure 2. The adult players generated more content in their verbal responses than the youth players for total Goals, Conditions and Actions. Both groups generated lots of goalorientated responses, these goals were concerned about the opponent and themselves rather than skill, verbalising what actions had been carried out by the opponent before determining the appropriate response. A significant amount of information was generated by adults under the concept for conditions with more than one detail. Information provided was more varied and contained more detail, the adult players would look at the strategies being implemented by the attackers before deciding on the appropriate action to perform to achieve their goal. Both adult and youth players linked two or more concepts when giving responses with no significant differences between the two groups but adults scoring slightly higher than youth in this category also. Pattern Recall A Fishers exact chi square test was performed to identify any differences in the two groups’ ability to recognise patterns of play. There was no significant difference found between the two groups for the number of correct responses recorded during the four sequences of play adults M = 2.25 (SD=1.03) and youth M = 2.5 (SD=1.07), (p = 0.076, p = 0.060, p = 0.099, p = 0.118). Figure 3 gives the percentage scores for correct and incorrect responses using verbal reports and the tick sheet questionnaire. Although there was no significant difference found in the analysis for the adults and youth players ability to recognise different patterns of play, a difference in the percentage of correct responses between the two groups was present (tick: adult 50%, youth 63%; verbal: adult 71%, youth 71%). Youth players exhibited a higher correct percentage score in three out of four sequences, when using a tick sheet. When giving a verbal response to the pattern recognition question, the adults had a higher score in two of the sequences and the youth scored higher in the remaining two sequences.
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16.00 14.00
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Figure 2. Mean (+ SE) scores of verbal report measures of concept content, structure and sophistication for adult (unfilled) and youth (filled) high performance players during conditioned small games for soccer.
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Figure 3. Percentage of patterns correctly recognised for high performance adult and youth players while participating in the four different sequences of play during conditioned small games of soccer.
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4. Discussion The superior knowledge representation and pattern recognition skills of elite relative to novice performers are well established in the literature. (Abernethy et al., 1994; Simon & Chase, 1973; Ward & Williams, 2003) To date, however, there have been few studies conducted to compare cognitive skills of high performance individuals in different age groups within a field environment. In this study, verbal reports were collected from elite adult and youth soccer players, to determine differences in their level of knowledge representation and pattern recognition skills during conditioned phase of play scenarios. It was predicted that the adult players would demonstrate superior knowledge representation skills (i.e. content of information, more details) than the youth players. It was also anticipated that the adult players would display greater pattern recognition capabilities than their less experienced counterparts. The results showed support for the hypothesised difference between adult and youth players in knowledge representation. As predicted, the adult players generated considerably more total concepts than the youth players (210 vs 142). The responses of both groups contained a high amount of goals that were predominantly about their opponent and themselves as opposed to skill. Thought processes were targeted towards actions that were required to prevent the opposition being successful, with the youth players focusing upon the immediate threat from the attacking player closest to them or the location of the ball. Adult players would consider in more depth the tactics employed by the opposition (70% of responses related to opponent) and what decisions needed to be made as the sequence of play progressed and, as such, provided more detailed information. The youth players were utilising action plan profiles to verbalise the actions and tactics of their opponent and on several occasions, two players displayed use of current event profiles. They would do this by anticipating the movements of their opponent from the previous plays and state the best tactic(s) to nullify their opponents’ attacking options during the next play. While not significant, this suggests that there is evidence that these youth players possessed the capabilities to process information and employ relevant tactics, but were not able to verbalise their thought processes to the same degree as the adult players, therefore, needing to develop their current event profiles further. The adult players were able to make assumptions and predictions during the sequences of play, consistently making reference to team mates, their opponents and anticipating upcoming events. The adult players were, therefore, making tactical decisions and utilising both their action plan and current event profiles. There was a greater deal of information generated by adults under the concept of conditions (players specify under what circumstance to apply the action to achieve the goal), particularly conditions providing more than one detail, which resulted in a significant (p < 0.009) difference between the two groups. The information provided by the adult players had more variety and contained more detail, the adult players would observe the strategies and tactics being implemented by the attackers before deciding on the appropriate action to perform to achieve their goal. The process of observing before making a decision suggests that both current event and action plan profiles were being used to implement tactics and select the appropriate actions to be carried out. The majority of the youth players had difficulty in planning future events with their thoughts being of the current situation. Their access to inferior long term memory skills, that 218
allow the athlete to speculate about the upcoming events before these events occur i.e. anticipate (Tenenbaum, 2003), was most deficient during the coding of this concept. Although not significant, there was a notable difference in the total number of action concepts 45 vs 27 (players specify an action selected or patterns of actions which may produce goal related changes in the context of the sporting situation) generated between the groups. The adults implemented actions from information that had been processed using their current event profiles to coordinate an appropriate action related response to the opponents’ tactics during the sequences of play. Youth players were also able to identify appropriate action related responses, but essentially utilised action plans with occasionally some evidence of basic current event profiles being used. Both groups linked two or more concepts (Goal, Condition, Action) while giving responses. There were no significant differences between the adults and youth players although the adults recorded slightly higher number of linkages than the youth. The findings relating to knowledge representation are consistent with those reported for tennis players by McPherson and Kernodle (2007). Elite adult soccer players verbalised more concepts and sophistication of those concepts relative to less experienced youth players, across the majority of the concepts analysed for composition and sophistication. As with the responses given by tennis players the soccer participants’ verbal reports contained a higher number of goal orientated responses and similarly to tennis professionals these responses for elite adults were more tactical and strategical than the youth who concentrated on the immediate threat to themselves or the position of the ball. Again consistent with tennis, the more senior elite group for soccer showed the same ability to adapt tactics in relation to the conditions in the game scenario. The youth players were able to access action plan profiles to employ defensive strategies during sequences of play, while the adult players employed both action plan and current event profiles to select the appropriate action during recall and planning interviews. Our second hypothesis predicted that the adult players would display superior pattern recognition skills than the youth players. Although there was no significant difference found between the adult and youth players’ ability to recognise different patterns of play, contrary to what was expected, the youth players exhibited slightly greater pattern recognition skills than the adults when using a tick sheet and had the same mean percentage scores as adults when giving verbal responses. This suggests that youth elite players are able to develop cognitive skills in domain-specific tasks at a relatively early age. Ward and Williams (2003) suggested that soccer players as young as 9 years old are able to develop their cognitive skills and, similarly, French et al. (1996) found differences between expert and novice baseball players aged 10 years old, when players were confronted with complex game situations. It may take many hours of practice (10 year rule) to fully develop cognitive and memory skills to perform at the expert level (Simon & Chase, 1973). However, predictions that memory adaption’s are rarely demonstrated before the age of 15 – 16 yrs old (Ericsson & Kintisch, 1995; French & McPherson, 1999) could be open to discussion, given the data gathered in this study. The youth players’ ability to recognise domain-specific patterns of play might be attributed to high quality coaching, which can have a significant impact on the acquisition of cognitive skills at an early age (Ward & Williams, 2003).
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In summary, this study used an ecological approach to determine levels of cognitive functioning skills between elite soccer players of different ages. It followed a model of protocol used previously in tennis to determine knowledge representation skills of players during problem solving tasks. It supports previous research in that more experienced elite players are able to call upon consistently more developed long term memory skills when problems are presented in their sport specific domain (Ericsson & Kintisch, 1995; McPherson, 1999; McPherson & Kernodle, 2007). Knowledge acquired over years of practice is pivotal in determining the level of expertise that can be achieved by an individual. No significant results were recorded during assessment for pattern recognition skills. However, some trends were observed for the youth players recording slightly greater percentage scores than their more experienced counterparts. Irrespective, youth game reading skills (pattern recognition) are developed to a similar level to those of adult players. Further research in knowledge representation and pattern recognition for soccer, with the replication of this study incorporating higher numbers of participants and a control group, could possibility offer evidence for coaches to incorporate additional skill and technique development into training methods for youth players.
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McPherson, S.L. & Thomas, J.R. (1989). Relation of knowledge and performance in boys tennis: Age and expertise. Journal of Experimental Child Psychology, 48, 190-211. McPherson, S.L. (1993). Knowledge representation and decision making. In Starkes, J.L & Allards, F (Eds). Advances in psychology: Cognitive issues in motor experience (159-188). Amsterdam: North Holland. McPherson, S.L. (1999). Expert-Novice differences in performance skills and problem representations of youth and adults during tennis competition. Research Quarterly for Exercise and Sport, 70, 233-251. McPherson, S.L., & Kernodle, M. (2003). Tactics the neglected attribute of expertise. In Starkes, J.L & Ericsson, K.A (Eds.). Expert Performance in Sports: Advances in Research on Sport Expertise (pp.137-167). Champaign, USA: Human Kinetics. McPherson, S.L & Kernodle, M. (2007). Mapping two new points on the tennis expertise continuum: Tactical skills of adult advanced beginners and entry level professionals during competition. Journal of Sports Science. 1-15. McRobert, A.P., Williams, A.M, Ward, P & Eccles, D.W. (2009) Tracing the process of expertise in a simulated anticipation task, Ergonomics. 52(4), 474 -483. Simon, H.A., & Chase, W.G. (1973). Skill in Chess. American Scientist, 61, 394-403. Tenenbaum, G. (2003). An integrated approach to decision making. In Starkes, J.L & Ericsson, K.A (Eds.). Expert Performance in Sports: Advances in Research on Sport Expertise (pp.191-218). Champaign, USA: Human Kinetics. Thomas, J.R., & Nelson, J.K. (2005). Research methods in physical activity. Champaign, IL: Human Kinetics. Vaeyens, R., Lenoir, M., Williams, A.M., Mayzn, L., & M. Phillippaerts. (2007). The effects of task constraints on visual search behaviour and decision –making skill in youth soccer players. Journal of Sport & Exercise Psychology, 29, 147-169. Ward, P., & Williams, A.M. (2003). Perceptual and cognitive skills development in soccer the multidimensional nature of expert performance. Journal of Sport and Exercise Psychology, 25, 93-111. Williams, M.A., Davids, K., Burwitz, L., & Williams, J.G. (1994). Visual search strategies in experienced and inexperienced soccer players. Research Quarterly for Exercise and Sport, 65, 127-135. Williams, M.A. (2000). Perceptual skill in soccer: Implications for talent identification and development. Journal of Sport Sciences, 18, 737-750.
Correspondence Mr David J. Evans – Central Institute of Technology, Western Australia E-mail:
[email protected]
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