Module 11

Perceptual & Motor Skills: Exercise & Sport 2012, 115, 2, 567-580. © Perceptual & Motor Skills 2012

DOI 10.2466/30.10.25.PMS.115.5.567-580 ISSN 0031-5125

TACTICAL KNOWLEDgE IN TENNIS: A COMPARISON OF TWO gROUPS WITH DIFFERENT LEVELS OF EXPERTISE1

LUIS gARCÍA-gONzÁLEz

Faculty of Health and Sport Sciences University of Zaragoza

ALBERTO MORENO AND M. PERLA MORENO

Faculty of Sport Science University of Extremadura

DAMIÁN IgLESIAS

Faculty of Teacher Training University of Extremadura

FERNANDO DEL VILLAR

Faculty of Sport Science University of Extremadura

Summary.—Differences in the tactical knowledge of tennis players are described using the expert-novice approach to examine problem representation and strategy planning in 6 pre-professionals and 6 intermediate tennis players, by means of the McPherson and Thomas protocol for analysing verbal reports during game play. Statistical analyses indicated significant differences in conceptual content, struc- ture, and sophistication. These pre-professional tennis players had greater, more elaborated, and sophisticated tactical knowledge; with expertise, more complex structures are developed in long-term memory. Specific training programmes to improve tennis players’ tactical knowledge and cognitive skills may be desirable.

There is controversy about the role of long-term memory (LTM) struc- tures in controlling motor skills. Based on cognitive theory, the level of expertise in a certain sport should depend on internal mental representa- tions and on cognitive processes that intervene between stimulus inter- pretation and action selection (Hodges, Starkes, & MacMahon, 2006). Tra- ditionally, research has sought to describe these strongly related, cognitive characteristics of expert performance, with emphasis on the role of mem- ory (see Laurent & Ripoll, 2009, for a review). Knowledge structures in memory constrain decision-making. The greater and the more varied this knowledge, the better will be athletes’ anticipation and decision making (Williams & Davids, 1995; Williams, Davids, & Williams, 1999; Starkes, Helsen, & Jack, 2001). Knowledge influences other cognitive processes, directing attention, visual behaviour, and anticipation as well as response selection and execution. The knowledge accessed from memory as well as the use of strategies and tactics will depend upon the context defined by the environment, the athlete, and the task (MacMahon & McPherson, 2009).

The acquisition of specific knowledge used in athletic performance is explained through the Adaptive Control Thought model (ACT*) devel- oped by Anderson (1983, 1987, 1992). It has been applied in sport research 1Address correspondence to Luis garcía-gonzález, Facultad de Ciencias de la Salud y del Deporte, University of zaragoza, Plaza Universidad 3, CP 22002, Huesca, España.

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programmes (e.g., McPherson & Thomas, 1989), which posit that the con- struction of knowledge is developed through “if .  .  . then” productions, which combine environmental conditions with actions. More specifical- ly, as the level of expertise increases, two types of adaptations develop in long term memory, permitting high level decisions: (i) action plan profiles, which refer to the information used by the athlete to make decisions dur- ing game play including concepts related to game situations, game pat- terns, opponents, etc., and which can be assessed through problem repre- sentation (McPherson & Kernodle, 2007; MacMahon & McPherson, 2009); (ii) current event profiles, which refer to the information that is kept active by the athlete for subsequent decisions, and assessed through strategic planning (McPherson & Kernodle, 2007; MacMahon & McPherson, 2009). These profiles are constructed and modified dynamically during competi- tion (McPherson, 2008).

Both profiles are predicted to allow elite or expert players easy ac- cess to and retrieval of important information to make decisions during competition and to compensate or make adjustments during time-con- strained moments (McPherson & Kernodle, 2007). Different studies with- in the expert-novice paradigm in tennis, related to knowledge and cogni- tive processes involved in this sport, conclude that highly expert players: (i) have a stronger grasp of the relationships between concepts, and they focus on more sophisticated concepts (Schack & Mechsner, 2006); (ii) ex- hibit more advanced problem representation, have more specific goals, generate more tactics and solutions in response to their goals, access and update a variety of scripts regarding game tactics, condition profiles about their own and their opponents’ behaviours, game status , and so on, to achieve specific goals or to select actions (McPherson & Kernodle, 2007); (iii) are enabled to use their knowledge structure more effectively dur- ing game play because the sophistication of sport knowledge increases with expertise (McPherson & Thomas, 1989); and (iv) plan their actions on the basis of a tactical diagnostic of past events and anticipate specif- ic contextual conditions (like opponents’ positions and opponents’ action selection; McPherson, 2000). In contrast, novice players (i) process a min- imum amount of relevant information wherein weak problem representa- tion comprises goals for execution, failed actions (regulatory concepts) or reactions to game events (McPherson, 1999a) and (ii) generate few plans containing goals and poorly interpret the conditions of past and present events. These facts imply that novice tennis players approach problems in a more general manner (McPherson & Thomas, 1989).

Players’ problem-solving processes as well as sport-specific and cogni- tive strategies emerged from the problem representation accessed during competition (French & McPherson, 1999; McPherson, 1999a, 1999b, 2000).

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Verbal reports during game play are a useful tool to evaluate knowledge representation in sport (Ericsson, 2006; McPherson & Kernodle, 2007); use of this tool shows that activation of critical input and concepts from long-term memory form an initial representation of the problem, includ- ing information and processes that players use to mediate performance and capture problem representations when performing tasks that require motor execution. In addition, this method allows examination of individ- uals’ thinking processes in a real game situation (Ericsson & Simon, 1993; McPherson, 1993, 1994; French & McPherson, 2004; McPherson & Kerno- dle, 2007).

The objective of this work was to evaluate the differences in tactical knowledge between pre-professional players and intermediate players us- ing verbal reports. Players with a higher expertise level in tennis were ex- pected to verbalize better quality tactical knowledge (broader, with more variety, more sophisticated and more structured) in both problem repre- sentation and strategy planning, during game play.

method Participants

Participants were 12 Under-18 Spanish tennis players (M age = 16.2 yr., SD = 2.2), divided into two groups: pre-professionals (n = 6) and inter- mediate (n = 6). The groups had the following characteristics: pre-profes- sionals were advanced tennis players with a high level of expertise and performance, and who were consistent over time, classified at Level 2 In- ternational Tennis Number (ITN) developed by the International Tennis Federation (ITF), for at least the last two years. Intermediate players were tennis players with medium expertise, classified as ITN Level 5. All the other features with respect to rank, age, years of training, and years of competition of both groups are presented in Table 1.

Before conducting the research, participants and their parents were informed about this study and they signed an informed consent as re- quired by the Helsinki Declaration (2008) and the local ethics committee.

TABLE 1 CharaCteristiCs of Pre-Professional and intermediate Players

Measure Pre-professional Intermediate

M SD M SD

National ranking 97.5 12.5 1,847.5 122.3 Age, yr. 16.1 2.3 16.3 2.3 Years of training 11.2 1.0 6.4 0.8 Years of competition 9.5 1.0 5.1 0.7

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Variables The dependent variable was tactical knowledge, comprising problem

representation and planning strategies, referring to the knowledge used by athletes (McPherson, 2008). Athletes have access to this knowledge when they are representing a game situation through knowledge struc- tures. The independent variable was expertise, with two levels: pre-pro- fessionals (ITN Level 2) and intermediate (ITN Level 5). Interview Procedure

Verbal reports have been used to access the knowledge representation of tennis players (McPherson & Thomas, 1989; McPherson, 1999a, 1999b, 2000). The tennis players answered two questions as accurately as they could between the points of each game during competition: (i) “What were you thinking about while playing that point?” (immediate recall). This ques- tion was taken from McPherson and Thomas (1989), and requires play- ers to remember their thoughts about the previous point. Responses were framed as problem representations. (ii) “What are you thinking about now?” (planning). This question was also taken from McPherson (2000). To an- swer, players have to give information about their current thoughts and possibilities for action choices in subsequent points. Such answers were considered planning strategies (McPherson & Kernodle, 2007). The answers were recorded on a digital audiotape (Sony TCM-200DV).

Players competed within their respective groups, were instructed to play as if they were competing in a sanctioned tournament, and answered the two questions throughout an entire set, after each point. Previous re- search has indicated that participants’ performance behaviours were not affected by interviews, and interview procedures were the same as those used in other research (c.f. McPherson & Kernodle, 2007): interview ques- tions were typed on sheet of paper and attached to a clipboard, placed off court close to the baseline fence with the audiotape recorder. Players were instructed to go directly to their tape recorder and respond accurately to the questions without time constraint. Participants operated the audio- tape manually and there were no technical problems during voice record- ing. Sixteen interview points were selected at random for each player. Coding Verbal Responses

Once interviews were recorded, they were transcribed by someone not involved in this study, and later those transcriptions were revised by a tennis expert (external to this study) to ensure that tennis-specific words were correctly transcribed, leaving them ready for analysis.

Interviews were divided into phrases or information units. There could be one or more concepts in each phrase. Pauses over two seconds and sentence endings were counted as the end of a phrase. Finally, every

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concept was codified by means of a system of categories with three anal- ysis levels (for a review, see McPherson, 2000; McPherson & Kernodle, 2007).

Concept content.—Analysis Level 1 categorized the phrases in terms of concept content, so each concept was assigned to a major concept catego- ry and a sub-concept category. Within concept content, the major concept categories were: goal, condition, action, regulatory, or do concepts. Defini- tions of major concept categories were developed in McPherson and Ker- nodle (2007). Every concept identified in a major concept category was also assigned to a sub-concept category; options differ with major concept category, and provide information about the variety of concepts of goal, condition, or action (Fig. 1).

Concept sophistication.—Analysis level 2, concept sophistication, was applied only to major concept categories of goal, condition, and action. Goal concepts were classified into 3 levels: (a) hierarchical level 0, con- cepts related to skill and themselves; (b) hierarchical level 1, concepts re- lated to themselves and opponents; (c) hierarchical level 2, concepts relat- ed to win (the point, the game, or the match). The concept sophistication of each condition and action concept was classified by quality of sophisti- cation: (a) quality level 0, inappropriate or weak concept; (b) quality lev- el 1, appropriate concept without any details or features; (c) quality level 2, appropriate concept with one detail or feature; (d) level 3, appropri- ate with two or more features (McPherson, 2000; McPherson & Kernodle, 2007).

Major Concept Category

1. goals 2. Conditions 3. Actions, Regulato- ries, Do

Sub-concept categories

1.1. Executing the skill 1.2. getting the ball in 1.3. Keeping the ball in

play 1.4. Keeping the ball away

from the opponent 1.5. Preventing opponent’s

aggressive shots 1.6. Making opponent

make mistakes 1.7. Specific goals about

moving opponent 1.8. To do the same thing

or plan 1.9. Win the point or game 1.10. End the match

2.1. Their strength 2.2. Their weakness 2.3. Their tendencies 2.4. Their position 2.5. Their prior shot 2.6. Opponent’s strength 2.7. Opponent’s weakness 2.8. Opponent’s position 2.9. Opponent’s prior shot 2.10. Opponent’s tenden-

cies 2.11. Shot type 2.12. Service type 2.13. Position type 2.14. game status 2.15. Environment

3.1. Serve 3.2. Return of serve 3.3. groundstroke 3.4. Lob 3.5. Drop shot 3.6. Approach shot 3.7. Volley 3.8. Smash 3.9. Passing shot 3.10. Position move 3.11. Visual act

Fig. 1. Major concept categories and sub-concept categories for verbal reports analysis.

L. GARCÍA-GONZÁLEZ, et al.572

Concept structure.—Analysis level 3 coded concept structure or links between concepts (McPherson, 2000; McPherson & Kernodle, 2007). Con- cept structure analyzeds the number of linkages of concepts observed in each phrase, classifying phrases into 3 levels: single concepts (only one concept), double-concept linkages (two linked concepts) and triple-con- cept linkages (with three or more linked concepts). Examples of coding, applying these three analysis levels are as follows, for an intermediate and a pre-professional player. Intermediate player 3: “I was only thinking about getting the ball into the court” (goal concept; sub-concept 1.2. get- ting the ball in; goal hierarchical level 1; Single concept); Pre-professional player 1: “I was thinking about how to move Peter from side to side .  .  .” (Goal concept; sub-concept 1.7. Specific goals about moving opponent; Goal hierarchical level 2) “.  .  . so that when he was placed out of the court near to the doubles zone .  .  .” (Condition concept; Condition sub-concept 2.9. Opponent’s position; Condition quality level 3); “I make a down-the- line winner” (Action concept; Action sub-concept 3.3. groundstroke; Ac- tion quality level 2; Structure, triple-concept linkage). Reliability of Coding System

Data coding was carried out by two coders. Before assessing the reli- ability of the coders, they received eight training sessions. In these sessions, coders trained with 20% of all verbal reports, chosen randomly (Tabachnick & Fidell, 2007). After coding training sessions, inter-coder and intra-coder reliabilities were assessed. For that purpose, coders coded 10 verbal reports. Another codification of the same verbal reports was carried out 10 days lat- er. Values in Cohen’s kappa index of .87 of intra-coder reliability and values of .85 of inter-coder reliability were achieved, considered high or near com- plete concordance (Landis & Koch, 1977; Altman, 1991). Data Extraction

To extract the data and perform the statistical processing, the follow- ing procedure was applied for each sub-variable. For concept content, to- tal concepts was the sum of all concepts generated for each major concept category; variety of concepts was the sum of all sub-concept categories generated for goals, conditions, and actions,2 irrespectively. Concept so- phistication had two scores, goal sophistication was the total number of concepts from each hierarchy; condition and action sophistication were the total of concepts generated in each category. Concept structure was scored as the sum of all individual concepts (single concepts) plus one- concept linkages (double concept) plus two or more concept linkages (tri- ple concepts). The values presented in Tables 2 and 3 are frequencies. 2In the original papers about this verbal protocol, variety of sub-concepts is measured only for goals, conditions, and actions (i.e., McPherson & Kernodle, 2007).

TACTICAL KNOWLEDGE IN TENNIS 573

Statistical Analysis Descriptive and inferential data analyses were performed in agree-

ment with previous research that used these same instruments (McPher- son, 1999a, 1999b, 2000; McPherson & Kernodle, 2007). Means, standard deviations, and mean ranks were calculated. For inferential data analy- sis, the Mann-Whitney U test was used. This was justified by the small sample and was based on the assessment of the normality test (Shapiro- Wilks test). In each Mann-Whitney U test conducted for each subvariable, frequency data were transformed to ranks. Effect size (r) was calculated separately for each subvariable, r = z/ N (Rosenthal & DiMatteo, 2001) to know the extent of the differences found, because this minimizes the influence of the sample size. Statistical power was also calculated in each analysis. The 95% confidence interval (CI) was included for each variable.

results Frequencies and U values for conceptual content, conceptual sophis-

tication, and conceptual structure are shown in Table 2 for problem repre- sentation and in Table 3 for planning strategies. Problem Representations

In concept content of problem representation, the concepts most often verbalized by pre-professional players were condition concepts, and in in- termediate players, goal concepts. Significant differences were also found between groups in the total of condition concepts, variety of condition concepts, total of action concepts, and total of regulatory concepts, with significantly higher frequencies in pre-professional players.

In concept sophistication, the two groups obtained similar results with respect to sophistication of goal concepts, with no significant differ- ences at any level. In condition concepts sophistication and action con- cepts sophistication, significant differences were found at Level 2 (appro- priate concepts with one feature) and Level 3 (appropriate concepts with two or more features), with significantly higher frequencies in pre-profes- sional players.

In concept structure of problem representation it shows that pre- professional tennis players generated a significantly higher number of double and triple concept phrases than intermediate players. At the three aforementioned analysis levels, the effect size was high in the mea- surements with significant differences, with values of over .60, so the level of expertise of the players had a considerable effect on these vari- ables (Field, 2005). Planning Strategies

In concept content, the most verbalized concepts were goal concepts, both in pre-professional players and intermediate players. There were sig-

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574TABLE 2 means, mean ranKs, standard deviations, and U values for measures of ConCePt

Content, soPhistiCation, and struCture for level of exPertise in ProBlem rePresentation

Variable Pre-professional Intermediate U Z p* ES SP 95%CI

M MR SD M MR SD

Concept content Total goals 15.33 5.33 6.77 19.17 7.67 5.03 11.00 −1.13 .26 .32 .20 13.4, 21.1 Variety goals 4.83 6.42 0.75 4.83 6.58 0.40 17.50 −0.10 .92 .03 .05 4.5, 5.2 Total conditions 31.50 8.83 10.21 15.17 4.17 9.23 4.00 −2.25 .02 .65 .83 15.3, 31.3 Variety conditions 9.83 9.50 1.72 5.17 3.50 1.83 0.00 −2.90 .01 .84 .99 5.6, 9.4 Total actions 13.67 8.92 4.08 8.00 4.08 3.16 3.50 −2.34 .02 .68 .77 7.9, 13.7 Variety actions 6.17 8.33 1.94 4.17 4.67 1.72 7.00 −1.79 .07 .52 .47 3.9, 6.5 Total regulatory 5.00 9.42 1.26 1.33 3.58 1.21 0.50 −2.84 .01 .82 1.00 1.7, 4.6

Concept sophistication goal hierarchies

0-Skill & selves 9.67 5.33 3.93 12.17 7.67 4.07 11.00 −1.12 .26 .32 .19 8.3, 13.5 1-Selves & opponent 2.67 6.00 2.16 3.33 7.00 2.16 15.00 −0.50 .62 .14 .08 1.7, 4.3 2-Win attributes 3.00 6.25 2.75 3.67 6.75 3.55 16.50 −0.24 .81 .07 .06 1.4, 5.3

Condition qualities 1-Appropriate-no features 9.00 6.92 2.44 9.33 6.08 7.25 15.50 −0.40 .69 .12 .05 5.9, 12.5 2-Appropriate-one feature 13.33 8.83 5.35 5.50 4.17 3.83 4.00 −2.26 .02 .65 .83 5.6, 13.3 3-Appropriate-two features 9.17 9.50 3.71 0.50 3.50 0.83 0.00 −2.94 .01 .85 1.00 1.5, 8.1

Action qualities 1-Appropriate-no features 4.67 6.25 3.07 5.50 6.75 2.81 16.50 −0.24 .81 .07 .08 3.3, 6.9 2-Appropriate-one feature 4.67 9.25 1.36 2.17 3.75 0.98 1.50 −2.70 .01 .78 .95 2.3, 4.5 3-Appropriate-two features 4.33 9.33 2.33 0.33 3.67 0.51 1.00 −2.80 .01 .81 .98 0.7, 4.0

Concept structure Single concepts 13.00 7.42 2.09 11.83 5.58 1.17 12.50 −0.91 .36 .26 .23 11.3, 13.5 Double-concept linkages 9.83 9.50 1.94 5.83 3.50 1.60 0.00 −2.91 .01 .84 .97 6.1, 9.5 Triple-concept linkages 4.67 9.42 2.16 0.67 3.58 0.82 0.50 −2.83 .01 .82 .99 1.0, 4.3

Note.—*Bilateral asymptotic significance. MR = Mean Rank; ES = Effect Size; SP = Statistical Power.

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575 TABLE 3

means, mean ranKs, standard deviations, and U values for measures of ConCePt Content, soPhistiCation, and struCture for level of exPertise in Planning strategies

Variable Pre-professional Intermediate U Z p* ES SP 95%CI

M MR SD M MR SD

Concept content Total goals 21.33 7.50 3.88 18.67 5.50 3.67 12.00 −0.97 .33 .28 .23 17.5, 22.4 Variety goals 6.33 9.17 1.03 4.33 3.83 0.51 2.00 −2.71 .01 .78 .99 4.5, 6.2 Total conditions 19.83 8.42 11.33 9.67 4.58 7.52 6.50 −1.85 .06 .53 .45 8.0, 21.5 Variety conditions 7.50 8.83 1.76 4.17 4.17 2.13 4.00 −2.27 .02 .65 .84 4.2, 7.5 Total actions 5.83 7.50 3.48 4.00 5.50 2.68 12.00 −0.97 .33 .28 .17 2.9, 6.9 Variety actions 3.83 8.42 1.72 2.17 4.58 0.75 6.50 −1.95 .05 .56 .58 2.0, 4.0 Total regulatory 1.33 8.17 1.03 0.33 4.83 0.51 8.00 −1.75 .08 .50 .57 0.2, 1.4

Concept sophistication goal hierarchies

0-Skill & selves 12.50 7.25 1.87 11.50 5.75 3.56 13.50 −0.73 .47 .21 .09 10.2, 13.8 1-Selves & opponent 2.50 7.50 1.76 1.50 5.50 1.37 12.00 −0.99 .32 .28 .20 1.0, 3.0 2-Win attributes 6.33 6.92 3.26 5.67 6.08 3.55 15.50 −0.40 .68 .12 .06 3.9, 8.1

Condition qualities 1-Appropriate-no features 4.17 5.67 3.65 6.00 7.33 4.60 13.00 −0.81 .42 .23 .12 2.5, 7.7 2-Appropriate-one feature 9.17 8.67 6.01 3.17 4.33 3.18 5.00 −2.09 .04 .60 .51 2.6, 9.7 3-Appropriate-two features 6.50 9.50 3.27 0.50 3.50 0.54 0.00 −2.93 .01 .84 .99 1.0, 5.9

Action qualities 1-Appropriate-no features 2.17 6.08 0.98 3.00 6.92 2.60 15.50 −0.42 .68 .12 .11 1.4, 3.8 2-Appropriate-one feature 1.50 6.08 2.07 1.33 6.92 0.81 15.50 −0.41 .68 .12 .05 0.5, 2.4 3-Appropriate-two features 2.17 9.50 0.75 0.00 3.50 0.00 0.00 −3.11 .01 .90 .99 0.3, 1.9

Concept structure Single concepts 11.83 7.67 2.23 10.50 5.33 1.22 11.00 −1.18 .24 .34 .25 10.0, 12.3 Double-concept linkages 10.17 9.33 1.83 6.17 3.67 1.72 1.00 −2.76 .01 .80 .97 6.4, 9.9 Triple-concept linkages 4.33 9.50 1.63 0.67 3.50 0.52 0.00 −2.94 .01 .85 .99 1.1, 3.9

Note.—*Bilateral asymptotic significance. MR = Mean Rank; ES = Effect Size; SP = Statistical Power.

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nificant differences between groups in the variety of goal concepts, of con- dition concepts and of action concepts, with higher frequencies in pre-pro- fessional players.

In concept sophistication of planning strategies, the data obtained are similar to those of problem representation. The significant differences found were in levels 2 and 3 of the condition concepts and in level 3 of the action concepts, with significantly higher frequencies in pre-professional players.

In concept structure of planning strategies, pre-professional players generated a significantly higher number of double and triple concepts than intermediate players. The effect size of the level of expertise was high, over .60, in the measurements with significant differences (Field, 2005).

disCussion Dealing with the initial hypothesis, where it was said that players

with a higher level of expertise in tennis would develop a better quality of tactical knowledge (broader, with more variety, more sophisticated and more structured) in both problem representation and strategy planning during game play, the data show that the group of pre-professional ten- nis players developed a larger number of concepts on average than did intermediate tennis players. Consequently, knowledge employed during game play is expected to be greater. Despite the fact that the number of goal concepts was similar in both problem representation and in strategy planning, the total numbers of condition, action, and regulatory concepts developed by the pre-professional group were significantly higher than those of intermediate players, confirming one of the hypotheses.

Several researchers have pointed to the development of procedural or tactical knowledge according to expertise; knowledge is greater in players at higher competitive levels (Doods, Griffin & Placek, 2001; Moran, 2004). In this regard, the presence of a larger number of condition concepts in players with higher expertise represents a development of superior plan- ning processes (McPherson & Kernodle, 2003). A significantly larger num- ber of regulatory concepts are verbalized by pre-professional players, rep- resenting a greater capacity for self-assessment (McPherson, 1999a; Ruiz, Sanchez, Duran, & Jimenez, 2006). This indicates a construction of the necessary procedures to execute tasks (McPherson, 1993), and favours the possibility of athletes increasing their understanding of the factors that in- fluence their performance (MacMahon & McPherson, 2009). In this sense, the real distinguishing element between players with different levels of expertise can be found in the quality and distribution of the condition and action concepts and not in the goals (McPherson, 1993).

With regard to the variety of knowledge, the greater variety verbal- ized by the group of pre-professional players in goal concepts, condition concepts, and action concepts implies that intermediate players have a

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more global approach to the sport situation, only processing a few rel- evant elements of the task (McPherson, 1999a). When players develop more expertise, their approach can be more tactical because they have ac- quired more relevant information (McPherson, 1994; McPherson & Ker- nodle, 2003, 2007).

In addition, within the analysis of the conceptual content, appar- ently the pre-professionals, through their problem representation, make decisions based mostly on the environmental conditions that appear in the game context (i.e., scoreboard, opponent’s tendencies, weaknesses or strengths of the opponent or of the player him- or herself, etc.) and on the actions that occur (shots executed during the game) as a consequence of the action plan profiles (more complex profiles developed in their long term memory) that let them develop more advanced problem representa- tions (McPherson & Kernodle, 2007; McPherson, 2008). Strategy planning seemed to be based on a more varied selection of goals, conditions and actions in pre-professional players. They may keep relevant information active, updating it as the game is played, as current event profiles, due to more complex constructions in long term memory (McPherson, 2008; McPherson & MacMahon, 2008).

Referring to conceptual sophistication, problem representation and strategy planning had very similar characteristics, because pre-profession- als developed a significantly higher number of condition and action con- cepts in a more detailed and sophisticated way. Once again, with higher ex- pertise, more sophisticated output is observed, consistent with the findings of McPherson (1993). Referring to condition concepts, the players update, modify and test the environmental aspects to interpret what is happen- ing. All this supports their response selection in a continuous way, based on assessments of the strengths, tendencies or weaknesses of their oppo- nents (McPherson & Kernodle, 2003). In this regard, the predominance of concepts without nuances in intermediate players and of concepts with one, two, or more nuances in pre-professional players, indicates a change from superficial processing of the environment in initial stages towards in- depth information processing, with more tactical levels when expert level is achieved (McPherson & Kernodle, 2003). Thus, it is possible to state that the major difference between the groups was the tactical content of the concepts generated during the game (McPherson, 1993).

On a third level of analysis, there were significantly larger numbers of double and triple concepts in verbal responses to both questions in the pre-professional players. Tactical knowledge was more structured, with a greater interrelationship of concepts, developing more cohesive and so- phisticated action plans. In experts, a larger number of productions and “condition-action-goal” links were developed (McPherson, 2000; McPher-

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son & Kernodle, 2003). Finally, as a synthesis, it can be said that the tactical knowledge rep-

resented in pre-professional players’ responses was more varied and so- phisticated, with more in-depth interpretation and with more tactical as- pects (Chi, glaser, & Farr, 1988; McPherson, 1993; McPherson & Kernodle, 2007). On the other hand, intermediate players still try to solve game sit- uations in a global way, with less environmental interpretation, process- ing less of the relevant information during their performance and gener- ating a smaller number of action plans. Their plans tend to contain only goals, or weak interpretations of present and past events (McPherson, 1993; McPherson, 1999a). Pre-professional players planned their actions on the basis of the tactical diagnosis of representative situations and an- ticipated specific environmental conditions (McPherson, 2000). Adapta- tion in action plan profiles and current event profiles are developed along- side physical sport expertise, allowing more expert players to develop and plan their response selection and enhance tactical decisions during com- petition (McPherson & Kernodle, 2007). Conclusions

Differences found in tactical knowledge between the two groups rep- resenting two levels of tennis expertise suggest a continuum in the rele- vant knowledge base that increases with experience and expertise. Cogni- tive differences suggest the need to stimulate use of tactical knowledge in an explicit manner in the stages of tennis expertise.

REFERENCES

altman, d. g. (1991) Practical statistics for medical research. New York: Chapman & Hall. anderson, J. r. (1983) The architecture of cognition. Cambridge, MA: Harvard Univer.

Press. anderson, J. r. (1987) Skill acquisition: compilation of weak-method problem solu-

tions. Psychological Review, 94, 192-210. anderson, J. r. (1992) Automaticity and the ACT* theory. American Journal of Psychol-

ogy, 105, 165-180. Chi, m. t. h., glaser, r., & farr, m. J. (1988) The nature of expertise. Hillsdale, NJ:

Erlbaum. dodds, P., griffin, l. l., & PlaCeK, J. h. (2001) A selected review of the literature on

development of learners’ domain-specific knowledge. Journal of Teaching in Physi- cal Education, 20, 301-313.

eriCsson, K. a. (2006) Protocol analysis and expert thought: concurrent verbalization of thinking during experts’ performance on representative tasks. In K. A. Erics- son, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance. Cambridge, UK: Cambridge Univer. Press. Pp. 223-241.

eriCsson, K. a., & simon, h. a. (1993) Protocol analysis: verbal reports as data. Cam- bridge, MA: The MIT Press.

TACTICAL KNOWLEDGE IN TENNIS 579

field, a. (2005) Discovering statistics using SPSS. (2nd ed.) London: Sage. frenCh, K. e., & mCPherson, s. l. (1999) Adaptions in response selection processes

used during sport competition with increasing age and expertise. International Journal of Sport Psychology, 30, 173-193.

frenCh, K. e., & mCPherson, s. l. (2004) Development of expertise in sport. In M. R. Wiss (Ed.), Developmental sport and exercise psychology: a lifespan perspective. Mor- gantown, WV: Fitness Information. Pp. 403-423.

hodges, n. J., starKes, J. l., & maCmahon, C. (2006) Expert performance in sport: a cognitive process. In K. A. Ericsson, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance. Cambridge, UK: Cambridge Univer. Press. Pp. 471-488.

landis, J. r., & KoCh, g. g. (1977) The measurement of observer agreement for cat- egorical data. Biometrics, 33, 159-174.

laurent, e., & riPoll, h. (2009) Extending the rather unnoticed gibsonian view that “Perception is cognitive”: development of the enactive approach to perceptual- cognitive expertise. In D. Araújo, H. Ripoll, & M. Raab (Eds.), Perspectives on cogni- tion and action in sport. New York: Nova Science. Pp. 133-146.

maCmahon, C., & mCPherson, s. l. (2009) Knowledge base as a mechanism for per- ceptual-cognitive tasks: skill is in the details! International Journal of Sport Psychol- ogy, 40, 565-579.

mCPherson, s. l. (1993) The influence of player experience on problem solving during batting preparation in baseball. Journal of Sport and Exercise Psychology, 15, 304-325.

mCPherson, s. l. (1994) The development of sport expertise: mapping the tactical do- main. Quest, 46, 223-240.

mCPherson, s. l. (1999a) 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. (1999b) Tactical differences in problem representations and solu- tions in collegiate varsity and beginner women tennis players. Research Quarterly for Exercise and Sport, 70, 369-384.

mCPherson, s. l. (2000) Expert-novice differences in planning strategies during col- legiate singles tennis competition. Journal of Sport & Exercise Psychology, 22, 39-62.

mCPherson, s. l. (2008) Tactics: using knowledge to enhance sport performance. In D. Farrow, J. Baker, & C. MacMahon (Eds.), Developing sport expertise: researchers and coaches put theory into practice. London: Routledge, Taylor, & Francis. Pp. 155-167.

mCPherson, s. l., & Kernodle, m. w. (2003) Tactics, the neglected attribute of exper- tise: problem representations and performance skills in tennis. In J. L. Starkes & K. A. Ericsson (Eds.), Expert performance in sports: advances in research on sport expertise. Champaign, IL: Human Kinetics. Pp. 137-168.

mCPherson, s. l., & Kernodle, m. w. (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 Sciences, 25, 945-959.

mCPherson, s. l., & maCmahon, C. (2008) How baseball players prepare to bat: tacti- cal knowledge as a mediator of expert performance in baseball. Journal of Sport and Exercise Psychology, 30, 755-778.

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.

L. GARCÍA-GONZÁLEZ, et al.580

moran, a. P. (2004) Sport and exercise psychology: a critical introduction. Washington, DC: Taylor & Francis.

rosenthal, r., & dimatteo, m. r. (2001) Meta-analysis: recent developments in quan- titative methods for literature reviews. Annual Review of Psychology, 52, 59-82.

ruiz, l. m., sánChez, m., durán, J., & Jiménez, C. (2006) The study and analysis of sport experts: a psychological approach. Anales de Psicología, 22, 134-142.

sChaCK, t., & meChsner, f. (2006) Representation of motor skills in human long-term memory. Neuroscience Letters, 391, 77-81.

starKes, J. l., helsen, w., & JaCK, r. (2001) Expert performance in sports and dance. In R. N. Singer, H. A. Hausenblas, & C. M. Janelle (Eds.), Handbook of sport psychology. (3rd ed.) New York: Wiley. Pp. 174-201.

taBaChniCK, B. g., & fidell, l. s. (2007) Experimental designs using ANOVA. Belmont, CA: Duxbury.

thomas, K. t., & thomas, J. r. (1994) Developing expertise in sport: the relation of knowledge and performance. International Journal of Sport Psychology, 25, 295-315.

williams, a. m., & davids, K. (1995) Declarative knowledge in sport: a by-product of experience or a characteristic of expertise? Journal of Sport and Exercise Psychology, 17, 259-275.

williams, a. m., davids, K., & williams, J. g. (1999) Visual perception and action in sport. London: E & FN Spon.

Accepted August 28, 2012.

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