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Perceptual and Motor Skills, 2011, 112, 3, 871-888. © Perceptual and Motor Skills 2011

DOI 10.2466/05.10.11.25.PMS.112.3.871-888 ISSN 0031-5125

DIFFERENCES IN DECISION-MAKING DEVELOPMENT BETWEEN EXPERT AND NOVICE INVASION GAME PLAYERS1

DAVID GUTIERREZ DIAZ del CAMPO, SIXTO GONZALEZ VILLORA, AND LUIS M. GARCIA LOPEZ

University of Castilla-La Mancha

STEPHEN MITCHELL

Kent State University

Summary.—This cross-sectional study investigated the differences between young expert soccer players’ (n = 55) and novice players’ (n = 74) decision-making ability during performance of invasion games (ages: 7–8, 9–10, 11–12, and 13–14 years). Decision-making ability was assessed in invasion games that were appro-priately modified for age and expertise. Games were modified to meet the devel-opmental needs and previous learning of the participants, so interference between motor execution and decision making was minimized. Game performance was videotaped, and measures of cognitive components were developed from observa-tional analysis. Decision making was measured at two levels: (a) decision making restricted to the selection of the technical-tactical skills (passing, moving with the ball, getting free, marking, tackling, double teaming, and interception) and (b) deci-sion making in the adaptation to the tactical context of the game. Expert players remained superior in decision-making ability when variation in skill execution was controlled. Decision-making differences between levels of expertise decreased with age with regard to the first level (skill selection) and increased with age in relation to the second level (tactical-context adaptation). Findings are discussed in terms of implications for instructional focus and task design.

This study examined the differences in the cognitive components of game performance among invasion game players with different levels of expertise. The study contributes to the expert–novice and decision-mak-ing literature in two ways: first by investigating the interaction of skill execution and decision making, and second by the assessment of the de-cision-making component of performance in skill selection and tactical adaptation to the game context.

Within expert–novice studies, expertise has typically been a depen-dent variable to compare players with different levels of sport perfor-mance. The main aims of these studies have been the understanding of the features that distinguish experts from novices, and the processes un-derlying the development of expertise. Expertise is defined as the result of the successful interaction between biological, psychological, and social 1Address correspondence to Dr. David Gutierrez Diaz del Campo, Facultad de Educacion, Universidad de Castilla-La Mancha, Ronda de Calatrava 3, 13071 Ciudad Real, Spain or e-mail ([email protected]).

D. GUTIERREZ DIAZ del CAMPO, et aL.872

factors (Baker, Horton, Robertson-Wilson, & Wall, 2003), and refers to the “characteristics, skills, and knowledge that distinguish experts from nov-ices and less experienced people” (Ericsson, 2006, p. 3). One of the pa-rameters used to determine expertise is experience. Experience influences game performance and is usually linear with age and analogous to prac-tice, performance, and competition time (Blomqvist, Luhtanen, & Laakso, 2000). Other parameters that discriminate between levels of expertise have been the trainer’s (French & Thomas, 1987) or teacher’s (Nevett, Rovegno, Babiarz, & McCaughtry, 2001) own judgment, the category players com-pete in (Auld, 2006), or previous skills tests (Campos, 1993). However, ac-cording to Abernethy, Thomas, and Thomas (1993), expertise is the result of a complex interaction between different variables such as physical char-acteristics, talent, knowledge, skill, intuition, and motivation. Thus, “ex-pertise” clearly involves more than experience.

In research studies that use expert–novice differentiation in their de-sign, sport performance can be a key concept. Sport performance, a con-cept similar to that of game performance, is defined by Thomas, French, and Humphries (1986) as “a complex product of cognitive knowledge about the current situation and past events, combined with a player’s ability to produce the sport skill(s) required” (p. 259). This definition emphasizes the existence of two components: the cognitive component (knowledge and decision making) and the motor component (response execution). Both components are plainly related during a game, each be-ing necessary to reach high performance. Players with excellent tech-niques may not understand when and where to use those techniques and, therefore, may not know what to do when confronted with a specific situ-ation in a game (Turner & Martinek, 1995). Decisions become reality only if efficiently transferred to action (Grehaigne, Godbout, & Bouthier, 2001). Co-dependence of skills and tactics was evident in a study by Gutierrez Diaz del Campo, Contreras Jordan, and Garcia Lopez (2008) where signif-icant correlations were found between decision making and skill execu-tion. This indicates, as Thomas and Thomas (1994) suggested, that multi-ple measures of skill, knowledge, and game performance should be used in sport performance research. Thus, further studies have indicated rela-tionships between knowledge and decision making, including those by Allard, Deakin, Parker, and Rodgers (1993), Dodds, Griffin, and Placek (2001), and Gonzalez Villora, Garcia Lopez, Gutierrez Diaz del Campo, and Contreras Jordan (2010).

Research on expertise indicates that experts are superior in all under-lying components of game performance. Oslin and Mitchell (2006) clas-sified the results of these studies, in which experts are better than nov-ices, into the following: organization and structure of declarative and

DECISION MAKING IN INVASION GAMES 873

procedural knowledge, decision making, pattern recognition, anticipa-tion during the game, visual search and selection of important stimuli, retrieval of information taking place in the game environment, retrieval of information from short-term memory to long-term memory, and infor-mation processing speed. Abernethy, Burgess-Limerick, and Parks (1994, in French & McPherson, 2004, p. 403) summarize the characteristics that distinguish sport experts in the response-selection processes: “. . . experts are faster and more accurate in organizing patterns, have superior knowl-edge of both factual and procedural matters, possess knowledge organ-ized in a deeper, more structural form, have superior knowledge of sit-uational probabilities, plan their own actions in advance, anticipate the actions of an opponent, and possess superior self-monitoring of tactical decision making processes.”

In most expert–novice studies, the knowledge-based, information-processing perspective has served as the principal theoretical framework. The same theoretical framework is the one used by the majority of the re-search on games teaching (Oslin & Mitchell, 2006). Both research fields, expert–novice and games teaching, are linked in studies that examine the development of youth sport performance through the comparison of par-ticipants with different levels of expertise (for an extensive review, see Mc-Morris, 1999). Most of these studies assess cognitive components of game performance through the use of written knowledge tests (e.g., French & Thomas, 1987), situated interviews (e.g., French, Nevett, Spurgeon, Gra-ham, Rink, & McPherson 1996), interviews during competition (e.g., Ne-vett & French, 1997), or video-based situations (e.g., Garcia Lopez, Gu-tierrez Diaz del Campo, Gonzalez Villora, Abellan Hernandez, & Webb, 2010).

Just a few studies assess decision making in actual game play, nota-bly in tennis (McPherson & Thomas, 1989), baseball (French, Spurgeon, & Nevett, 1995), basketball (French & Thomas, 1987), soccer (Fontana, Maz-zardo, Mokgothu, Furtado, & Gallagher, 2009), and modified invasion games (Auld, 2006; Nevett, et al., 2001). Of importance among these stud-ies, French and Thomas (1987) developed an observation method to as-sess separately decision-making components of performance and motor skill execution components of performance. Subsequently, several authors have attempted to devise methods for authentic assessment of real game play situations (Grehaigne, Godbout, & Bouthier, 1997; Oslin, Mitchell, & Griffin, 1998; Nevett, et al., 2001; Tallir, Musch, Lannoo, & van der Voorde, 2003; Blomqvist, Vänttinen, & Luhtanen, 2005; Gutierrez Diaz del Campo, 2008). Most of these methods were designed for application in both re-search and physical education settings. The two most commonly used in games teaching and research are the Game Performance Assessment In-


strument (Oslin, et al., 1998) and the Team Sport Assessment Procedure (Grehaigne, Godbout, & Bouthier, 1997).

Bayer (1979) described novice players’ play as self-centred, while ex-pert players are more cooperative. Further, the designation “watcher-player” has been associated with the developmental characteristics of younger players due to their self-centred personalities and their limited at-tention spans (Contreras Jordan, De la Torre Navarro, & Velazquez Buen-dia, 2001). A player behaves as “watcher-player” when she or he does not show tactical intention or involvement in the game, mainly watching the other players’ performance. “Watcher-player” behaviour can be linked with the “competent bystander” behavior described in the instructional and managerial task systems literature (Tinning & Siedentop, 1985).

One problem in the studies referenced above is that the decision-mak-ing component of game performance has been assessed independently of motor execution. This fails to account for the possible interaction (or in-terference) between cognitive and motor execution components of game performance in the assessment of decision making during game play. In sports with a high level of spontaneity such as invasion games, the imple-mentation of the decision-making component is based on what players can do or think they can do (Nevett & French, 1997). For example, a player will not decide to pass to an unmarked, but distant, teammate if he or she does not have the strength, ability, or confidence to do it. Given such cir-cumstances, when players with different levels of expertise are compared using the same setting, it is difficult to distinguish the origin and real mag-nitude of the differences in the decision-making component.

A second limitation of previous research is that instruments used do not assess or separate all the factors present in the decision-making com-ponent during actual game play. In this way, although French and Thomas (1987, p. 18) asserted that decision-making components of performance “would involve selection of the skill . . . as well as which teammate to pass to, what direction to dribble, when to shoot, when to stop dribbling, and so on,” the authors did not include all of these considerations in coding procedures. Thus, previous research has typically assessed decision mak-ing on just one level, though two levels are possible. The first level, “re-sponse selection,” involves the technical-tactical skill and the teammate and opponent directly implicated in the action (e.g., passing the ball to an unmarked teammate). This might be best thought of as the decision-making question of “what is done.” But a second level of decision mak-ing would consider the tactical-context adaptation which might best be thought of as the question of “what should be done” in a particular game context or situation. The game context is composed of all teammates and opponents that could have any influence in a segment of play, as well as


the area where the action takes place. Tactical contexts in invasion games can be grouped together according to action principles described by Bay-er (1979). In attack, action principles include maintaining possession of the ball, penetrating the defense (moving toward the goal), and attacking the goal. In defence, action principles include regaining possession of the ball, avoiding and preventing the opponent from advancing the ball, and reaching the goal. For example, if the tactical-context adaptation perfor-mance in the attacker with the ball was analysed, when the game context is coded as maintaining possession of the ball, the player should make ac-tions directed to keep the ball, such as protecting the ball until a better op-tion comes up or passing the ball to a teammate who is unmarked but po-sitioned behind the ball carrier. In the same way, when the game context is coded as penetrating the defence, the player should perform actions to penetrate the defence (gtting closer to the goal), such as moving with the ball toward the goal or passng the ball to a teammate positioned closer to the goal.

Adapting to the tactical context of the game entails tactical awareness. This is the “ability to identify problems that arise while a game is in prog-ress and to select the skills necessary to solve these problems” (Mitchell, Griffin, & Oslin, 1994, p. 21). The second level of decision making, tactical-context adaptation, is very important with regard to game performance in invasion games due to the tactical complexity (Auld, 2006) and relational nature of skills in this category of games (MacPhail, Kirk, & Griffin, 2008; Gutierrez Diaz del Campo, Garcia Lopez, & Contreras Jordan, 2009). The purpose of the present study was twofold: first, to examine differences in decision making between expert and novice invasion game players dur-ing a real game, and second, to address methodological limitations of pre-vious research. The latter include modifying invasion games to match the participant’s previous learning and development to minimize the influ-ence of technical ability, and measuring decision making more broadly on two levels.

MethodParticipants and Procedures

The sample was made up of four age groups (7–8, 9–10, 11–12, and 13–14 years) and two performance levels (expert soccer players and novice players, cf. Table 1). The criterion to establish expertise was the amount of weekly and accumulated deliberate practice, experience in official compe-titions, and the judgment of the club coach. The expert players belonged to the youth program of the Albacete Football Club (Spain) and were se-lected by their coaches as being the best performers on their teams. They had all accumulated at least 1 yr. with more than 3 hr. per week of deliber-


ate practice and they all had experience in official competitions. The nov-ice players were selected from among physical education students with no formal training in invasion games and without any experience in of-ficial competitions. Expert soccer players were evaluated in different ver-sions of soccer, depending on age group. Novice players were evaluated through a modified invasion game, where the rules and technical require-ments were minimized. The games were selected based on the develop-mental abilities and previous training for each of the groups in such a way that they would be able to reach their maximum achievement on the deci-sion-making component of performance. The number of players per team and the size of the playing field were also adjusted since they are impor-tant structural elements that have great influence on the number of stimu-li present in the decision-making processes. Table 1 summarizes the ages, size of the playing field, and numbers of players per team in each group.

The design of the modified invasion game for novices was based on those used in similar research in educational contexts (Nevett, et al., 2001; Blomqvist, et al., 2005; Contreras Jordan, Garcia Lopez, & Cervel-lo Gimeno, 2005). The game played was team handball, with important structural and rule modifications designed to ensure developmental ap-propriateness and facilitate novice players’ success: the objective was to score goals by throwing the ball into the goal; there were no goalkeepers; moving with the ball was possible just by bouncing the ball; there was no double-dribble rule; stealing the ball from an opponent and physical contact were not permitted; after a foul, the game was restarted from the place where the infraction took place; throwing the ball to score from one’s own half of the court was not permitted; and only “one-on-one” defence

TABLE 1Sample Sizes In Each Category For the Four Groups, and Game Form in Which Players Were Evaluated

Age group, yr.

Physical Education Students (Grade)

n Game Form Soccer Players(Category,

Year of Birth)

n Game form

7–8 Grade 2 16(8 boys; 8 girls)

2 vs 214 × 7 m

U9Born in 1998

14 2 vs 220 × 10 m


3 vs 320 × 10 m

U116 born in 19977 born in 1996

14 3 vs 330 × 15 m


4 vs 430 × 15 m

U13Born in 1994

13 5 vs 552 × 40 m


5 vs 540 × 20 m

U152 born in 199312 born in 1992

14 7 vs 770 × 52 m

Note.—Game form includes number of players per team and size of the playing field.


was permitted, between pairs of attackers and defenders as established previously by teachers. This last rule, one-on-one defence, was important in that the matching of opposing players enabled differences in technical ability to be more easily controlled.

The expert players played soccer with the same “one-on-one” de-fence rule and fixed attacking-defending pairs. In addition, only the old-est group of expert soccer players played their games with goalkeepers. In the rest of the games (soccer for expert players and team handball for novice players), a banned area was established in front of the goal in such a way that no attackers or defenders could step into this area. All games lasted 8 min., divided into two halves. This length of time was similar to those established in similar studies (French & Thomas, 1987; Nevett, et al., 2001; Blomqvist, et al., 2005). Physical education teachers refereed inva-sion games, while soccer games were refereed by researchers. Coding Instrument

All matches were recorded with a video camera located behind and above the court and analyzed using the Game Performance Evaluation Tool (G-PET). The design for the G-PET (Gonzalez Villora, 2008; Gutierrez Diaz del Campo, 2008) was based on the instruments designed by French and Thomas (1987) and Nevett, et al. (2001). Most relevant variations from these instruments were the analysis of defensive actions and the context-adaptation decision making. Decision making was categorized into two levels. The first level evaluated decision making relative to technical-tac-tical skills. The second level analyzed the tactical context adaptation. The second level evaluated players’ tactical intentions with regard to the tacti-cal game context in which the action is located and was established only for offensive actions. In both levels, decision making was coded as 1: Cor-rect and 0: Incorrect.

Table 2 describes the coding categories for the two levels of decision making. In Level 1, variables linked to technical-tactical skills are grouped by the game roles of attacking and defending both on and off the ball. In Level 2, context adaptation decision making is grouped in a single variable (Global context adaptation performance) but also analysed by the three of-fensive tactical contexts described by Bayer (1979): keeping the ball, pene-trating the defence, and attacking the goal contexts. The “watcher-player” behaviour is also analyzed in this category. For coding purposes, the play-ing time was divided into decision-making units of action (Nevett, et al., 2001). The ending of a decision-making unit occurred after 4 sec. of action, when the player performed a different technical-tactical skill, or when the offensive tactical context changed. Content validity was established by a panel of experts. Instrument reliability was established through test-retest


procedures, with intra- and inter-observer correlations among the observ-ers in all categories ranging from .77 to 1.00.Statistical analysis

The means and standard deviations were calculated for each variable and for each of the participating groups. Performance was compared be-tween same-age groups. The Kolgomorov-Smirnov test for assumption of normality and the Levene test for homogeneity of variance showed that the sample did not meet these assumptions for all the variables in the study. Therefore, and also due to a small sample size, a Mann-Whitney U test was conducted to analyse for differences between the two samples (Vincent, 2005).

ResultsFour age groups were studied. Within physical education students

(the novice performers), these four groups were Grades 2, 4, 6, and 8. Cor-responding groups of soccer players were under 9 (U9), Under 11 (U11), Under 13 (U13), and Under 15 (U15). Results are summarized by age group, comparing expert and novice performers within each age group.

In the first age group (Grade 2 and U9 soccer players), the soccer play-ers attained significantly better results than the physical education stu-dents in global context-adaptation performance, and specifically on tac-

TABLE 2Description of the Dependent Variables to Measure Decision Making

Level 1 Decision Making:Technical-tactical Skill Selection

Level 2 Decision Making:Tactical Context Adaptation

Attacker on the ball Pass decision making Shoot decision making Moving-with-the-ball decision making

Global context adaptation performance: Glo-bal efficiency during the whole game in adapting the actions to the tactical context

Attacker off the ball Get-free decision making

Tactical context-adaptation performance to keep the ball contexts: Efficiency in select-ing actions to keep the ball when the tacti-cal context is coded as “keeping-the-ball context”

Defender on the ball Mark (on-the-ball) decision making Blocked shot decision making Tackle decision makingDouble team (on-the-ball) decision making

Tactical context-adaptation performance to penetrating-the-defense contexts: Efficien-cy in selecting actions to penetrate the de-fense when the tactical context is coded as “penetrating-the-defense context”

Defender off the ball Mark (off-the-ball) decision making Interception decision making Double team (off-the-ball) decision making

Tactical context-adaptation performance to attacking-the-goal contexts: Efficiency in selecting actions to try to score when the tactical context is coded as “attacking-the-goal context”

Watcher-player: A player is coded as “watch-er-player” when he does not show tactical intention or involvement in the game


tical context-adaptation performance to keep the ball. Soccer players showed better results also in decision making about passing and efficient off-the-ball movement. Defensively, U9 soccer players scored significantly better in terms of tackling, interceptions, and double-teaming decisions. The only category in which the physical education students scored higher than the soccer players was that of “watcher-player,” indicating less actual involvement in game play by these students (Table 3).

In the second age group (Grade 4 and U11 soccer players), the soccer players again demonstrated superior performance in most aspects of de-cision making. Offensively, significant differences were evident in global tactical context-adaptation performance, and specifically on the adapta-tion to penetrating the defence context. Expert soccer players scored bet-

TABLE 3Comparison of Percentages of Good Decisions Between

Grade 2 Students and U9 Soccer Players

Variable Soccer Players

Physical Educa-tion Students

Mann-Whitney

U

p

M SD M SD

Tactical Context AdaptationTactical-context-adaptation

performance to keep-the-ball context 86.9 11.9 65.7 18.1 40.0 .003Tactical-context-adaptation

performance to penetrating-the- defense context 73.5 18.6 68.1 15.1 79.5 .18

Tactical-context-adaptation perfor-mance to attacking-the-goal context 72.4 39.6 78.5 28.8 71.0 .98

Global context adaptation performance 78.2 10.5 67.4 13.2 55.0 .02

Watcher-player (% of decision- making units) .0 .0 5.2 5.1 42.0 .001

Attacker on the ballPass decision making 93.4 13.1 73.3 20.3 46.0 .006Shoot decision making 53.1 36.7 65.3 38.7 66.5 .36Moving-with-the-ball decision making 68.3 29.5 63.2 26.6 86.0 .43

Attacker off the ballGet-free decision making 80.6 19.3 66.7 18.3 64.0 .05

Defender on the ballMark (on-the-ball) decision making 51.4 26.1 66.3 19.7 73.5 .11Blocked-shot decision making 96.2 13.9 95.1 11.5 72.0 .56Tackle decision making 72.5 32.4 93.5 17.1 47.5 .03Double team (on-the-ball) decision

making 89.2 29.0 90.0 19.5 82.0 .55Defender off the ball

Mark (off-the-ball) decision making 47.2 32.2 41.4 20.2 101.0 .65Interception decision making 100.0 .0 87.8 20.6 54.0 .02Double team (off-the-ball) decision

making 93.3 9.5 54.9 31.5 16.5 .001


ter also on passing decisions and off-the-ball movement. Defensively, the U11 soccer players scored significantly higher than the physical education students on marking (on- and off-the-ball) decisions and interception de-cisions. Though the physical education students did score higher in the “watcher-player” category, this was not statistically significant (Table 4).

Results in the third age group (Grade 6 and U13 soccer players) fol-lowed a similar pattern, with the youth soccer players demonstrating su-perior performance to the physical education students on most variables. U13 soccer players scored significantly higher than the physical education students on global tactical context adaptation, and specifically both on the adaptation to contexts of keeping the ball and penetrating the defence. Ex-pert soccer players scored better also on passing decisions and decisions





Mann-Whitney

U

p

M SD M SD


performance to keep-the-ball-context 90.4 13.1 80.6 17.5 87.5 .11Tactical-context-adaptation




Watcher-player (% of decision- making units) 3.6 6.9 4.6 5.5 98.0 .22

Attacker on the ballPass decision making 96.9 4.9 84.6 13 50.0 .003Shoot decision making 79.9 33.9 77.4 38.3 88.5 .93Moving-with-the-ball decision making 76.6 28.8 64.3 28.5 72.5 .11


Defender on the ballMark (on-the-ball) decision making 83.2 18.9 58.5 21.5 47.5 .002Blocked-shot decision making 100.0 .0 86.4 21.5 31.5 .11Tackle decision making 88.1 17.6 70.1 38.4 53.5 .25Double team (on-the-ball) decision

making 86.7 21.2 66.7 51.6 34.0 .60Defender off the ball


making 90.3 9.9 62.4 37.0 77.0 .07


to move with the ball. Defensively, significant differences were found in marking (off-the-ball) and double-teaming (off-the-ball) decisions, with the U13 soccer players again scoring higher (Table 5). No significant dif-ferences were found on “watcher-player” behaviour.

The older age group (Grade 8 and U15 soccer players) yielded simi-lar findings, with U15 soccer players scoring significantly higher on global tactical-context adaptation, in both contexts of keeping the ball and pene-trating the defence. Expert soccer players scored better also on off-the-ball movement, and (defensively) double-teaming decisions. The physical ed-ucation students scored significantly higher on the “watcher-player” cat-egory, again indicating significantly less game involvement by these stu-dents (Table 6).





Mann-Whitney

U

p

M SD M SD






Watcher-player (% of decision- making units) 2.3 3.9 5.4 7.4 95.5 .15

Attacker on the ballPass decision making 98.2 6.7 83.5 22.0 77.5 .02Shoot decision making 100.0 .0 93.1 13.7 28.0 .17Moving-with-the-ball decision making 75.8 30.9 49.4 25.9 53.5 .01


Defender on the ballMark (on-the-ball) decision making 68.6 29 62.3 24.5 114.5 .50Blocked-shot decision making 100.0 .0 94.2 15.1 55.0 .17Tackle decision making 82.1 31.5 55.0 49.7 46.5 .19Double team (on-the-ball) decision

making 100.0 .0 85.7 37.8 9.0 .51Defender off the ball

Mark (off-the-ball) decision making 68.9 24.6 44.4 23.8 64.0 .01Interception decision making 94.4 16.7 92.4 17.3 46.5 .71Double team (off-the-ball) decision

making 85.6 20 64.9 20.2 48.5 .02


DiscussionPrevious research has shown that players with higher expertise are su-

perior in cognitive components of game performance. This superiority has been confirmed both in authentic game play through observational instru-ments that assess decision-making and skill-execution components sepa-rately (e.g., French & Thomas, 1987; Thomas, 1989; McPherson & Nevett, et al., 2001; Auld, 2006), as well as in isolated conditions through the use of written knowledge tests, interviews, or video-based situations (e.g., French & Thomas, 1987; French, et al., 1996; Nevett & French, 1997; Garcia Lopez, et al., 2010). The present study suggests that this remains true when the interference of execution ability is minimized. In these conditions, ex-pert players also have higher performance on tactical context adaptation.





Mann-Whitney

U

p

M SD M SD






Watcher-player (% of decision- making units) .0 .0 4.5 5.5 56.0 .001

Attacker on the ballPass decision making 97.8 6.5 89.2 20.2 109.0 .17Shoot decision making 97.2 8.3 93.8 12.1 46.0 .41Moving-with-the-ball decision making 83.8 19.9 88.5 16.6 72.0 .56


Defender on the ballMark (on-the-ball)decision making 83.1 17.0 80.6 19.0 131.5 .66Blocked-shot decision making 100.0 .0 93.6 11.2 22.5 .18Tackle decision making 87.9 19.1 75.4 36.6 49.5 .50Double team (on-the-ball) decision

making 100.0 .0 92.9 18.9 18.0 .36Defender off the ball


making 97.8 8.6 62.2 37.3 37.5 .001


The results indicated that the cognitive components of decision mak-ing differed between expert and novice players. The expert players at-tained better results in the cognitive aspects of game performance, with tactical awareness measured through the adaptation to tactical game con-texts being where more differences were found. In general, but not on all the variables measured, all soccer groups got better results than the physical education students of the same age. Statistically significant dif-ferences were found on the “watcher-player” variable, which indicated that the soccer players of every age group showed greater involvement in the game than the physical education students.

Findings showed significant differences in all groups in the global ad-aptation to the tactical contexts of the game (p < .01 level in the three older groups). In the two younger groups, the differences were found only in one of the three tactical contexts. In the two older groups, the differences were found on aspects of two of the three tactical contexts. This is consis-tent with an increase in expertise associated with age, thus resulting in an increasing gap between expert soccer players and novice game players.

There were no significant differences between the soccer players and the physical education students in any of the comparisons carried out re-garding context adaptation in attacking the goal. This result suggests that the tactical problem of attacking the goal is the one that requires the least amount of expertise and can be resolved by the players in the most natu-ral way. This concurs with those authors who think that novice players play a self-centred game oriented toward goal scoring, only later becom-ing more cooperative (Bayer, 1979). In invasion games, maintaining pos-session as opposed to trying to penetrate the defence means playing a more cooperative game and being more aware of the game’s objective, which is reaching the goal, but also keeping the ball away from your op-ponent so he will not be able to score. There were no technical-tactical skills which seemed to be more relevant in the differences between lev-els of expertise. The number of technical-tactical skills on which signifi-cant expertise differences were found decreased with age. In addition, in the oldest age group, these differences are found only in off-the-ball roles. These results seem to indicate that along with age, differences between ex-perts and novices involve the defensive, off-the-ball aspects of the game. These require greater explicit attention in the training process, though of-ten training processes and informal learning focus on the on-the-ball and offensive components (Blomqvist, et al., 2005; Auld, 2006; Gutierrez Diaz del Campo, 2008). These findings also lend weight to the suggestion by French, et al. (1995) that since the context of the game performance and the underlying factors are changing, the criterion used to evaluate and define expertise can change with age.


An important variable in the study was the “watcher-player” variable on which the experts scored consistently lower, thus showing greater in-volvement in the game. These results show that motivation and maintain-ing concentration, both elements necessary to following the game action, are characteristics of expertise. Greater involvement on the part of the ex-pert soccer players was found in every age group. “Watcher-player” be-haviour has traditionally been associated with the developmental charac-teristics of younger players due to their self-centred personality and their lack of attention span (Contreras Jordan, et al., 2001). It is likely that the type of game for each different age, in which the younger played with fewer players per team and on a small field, would be of great importance in the results of this variable. These results suggest that excessive watch-ing behaviour might be alleviated to a large extent by designing age-ap-propriate game situations, and that expertise seems to be more important than age in the player’s involvement in the game.

Novice groups included both girls and boys, while soccer players were all boys. Sex differences have previously been found to exist in various as-pects of performance such as perception of enjoyment and competence in physical education (Cervello, Jimenez, del Villar, Ramos, & Santos-Ro-sa, 2004), amount of physical activity (Riddoch, Anderson, Wedderkopp, Harro, Klasson-Heggebo, Sardinha, et al., 2004), motor performance (Ma-lina, Bouchard, & Bar-Or, 2004), and social interactions (Brock, Rovegno, & Oliver, 2009). As these abilities and attitudes can have a direct influence on game performance, sex differences might be considered a limitation or bias in the data. Nevertheless, the research was designed to minimize this bias. Possible motor differences were minimized by assessing only cog-nitive components of game performance and also by the “one-on-one” defence rule and fixed attacking-defending couples; amount of physical activity was controlled by the questionnaire (asking about previous expe-rience) which was used to exclude students with formal training in inva-sion games; finally, participants were children and pre-adolescents, and in the aforementioned studies it is during adolescence where the biggest differences between girls and boys are found. Lastly, to provide a more detailed view of the differences between experts and novices in the cog-nitive components of game performance, declarative knowledge should have been assessed, as recommended by McPherson and Thomas (1989) and French and Thomas (1987). Conclusion

The purpose of this study was to investigate differences in the deci-sion-making capacity of young performers, while controlling for technical ability by ensuring that players participated in game play of appropriate difficulty. Findings indicated that young expert players are more effec-


tive decision-makers than young novice players in invasion games, when compared with similar age groups. These findings have implications re-garding practice. The fact that there were significant differences between experts and novices in the cognitive aspects of the game supports the po-tential value of a tactics-centred approach to teaching. Results seem to in-dicate that adaptation to tactical contexts of the game is a very important game performance component in the development of expertise in inva-sion games, making it appropriate to focus on the development of tacti-cal awareness, especially for novice performers of limited technical abil-ity. Likewise, involvement in the game seems to be a decisive factor in the processes that lead to expertise, making it important to increase game in-volvement for physical education students by designing games that facili-tate greater involvement.

The approach presented in this study for assessing and comparing the cognitive components of game performance, in a setting where the in-terference between the decision-making and the motor-execution compo-nents is minimized, provides a new framework to study the nature and development of expertise. More research is needed to understand how results such as those presented in this study can facilitate learning of re-sponse-selection processes and the development of expertise. In addition, further research must address the way to apply this approach to other sport and games categories.

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