M4 A1Creativity in Sport
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High Ability Studies Vol. 21, No. 1, June 2010, 3–18
ISSN 1359-8139 print/ISSN 1469-834X online © 2010 European Council for High Ability DOI: 10.1080/13598139.2010.488083 http://www.informaworld.com
Play and practice in the development of sport-specific creativity in team ball sports
Daniel Memmerta*, Joseph Bakerb and Claudia Bertschc
aInstitute of Cognitive and Team Racket Sport Research, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Köln, Germany; bSchool of Kinesiology and Health Science, York University, Toronto, Ontario, Canada; cUniversity of Heidelberg, Germany Taylor and FrancisCHAS_A_488083.sgm10.1080/13598139.2010.488083High Ability Studies1359-8139 (print)/1469-834X (online)Original Article2010Taylor & Francis211000000June 2010Dr [email protected]
Current theoretical approaches regarding the development of creativity support the view that gathering diversified experience over years is an ideal medium for creative thinking. This study examined the role of practice conditions in the development of creative behavior in team ball sports. Twelve trainers selected the most creative and the least creative players from their teams. These athletes (n=72) provided information about the quantity and type of sport-specific and other related practice activities undertaken throughout their careers. Results indicated significant differences between the groups for time spent in unstructured play activities and a marginally significant difference for total time spent in training for their main sport. In both cases, more creative players accumulated more time than their less creative counterparts.
Keywords: expertise; divergent thinking; athletes; deliberate play; deliberate practice
Introduction
Earvin “Magic” Johnson became famous for his so-called “no-look-passes”, seeming to be able to take in all relevant stimuli of a situation, and use this information to fool his opponents by looking in the direction of the most obviously free team-mate while passing the ball to another player. Similarly, French soccer hero Zinedine Zidane was able to read the play and find an unmarked team-member who had been closely marked a moment before. In team ball sports, these players are often described as having tactical creativity. Creativity entails varying, rare and flexible decision- making in complex game situations (Memmert & Roth, 2007). The ability to think creatively in sports is often noted by coaches and trainers as being highly desirable (see Appendix 1); however, it is not clear how this type of thinking is developed.
Researchers from the field of expertise have spent considerable time and effort examining the acquisition of expert decision-making and performance. According to the theory of deliberate practice (Ericsson, Krampe, & Tesch-Römer, 1993), expertise in a given domain is the end result of extended engagement in high-quality training (i.e., deliberate practice). The Ericsson et al. theory is based on the assumption that the most beneficial form of training for acquiring sport skill involves activities that are highly relevant to performance improvement, effortful (either cognitively or
*Corresponding author. Email: [email protected]
4 D. Memmert et al.
physically) and performed for the purpose of improving current performance rather than for inherent enjoyment.
Although the role of involvement in other sports is seen as less valuable than sport- specific deliberate practice in Ericsson et al.’s theory, recent research suggests that in some sports participation in other nonspecific activities could play a functional role in the development of experts (Baker, 2003; Baker, Côté, & Abernethy, 2003; Côté, Baker, & Abernethy, 2003). For instance, Baker et al. (2003) found a negative corre- lation between early breadth of exposure to other sports and the amount of sport- specific training required to obtain expert-level proficiency in basketball, netball, and field hockey, suggesting that early involvement in other sports facilitates the acquisition of skills necessary for high-level performance. Other data from this study (Abernethy, Baker, & Côté, 2005) indicated that general cognitive skills, such as pattern recognition, were transferable across domains with similar offensive and defensive structures.
Although the ability to think creatively may be a significant component of expert decision-making, researchers do not consider them to be synonymous. In a general scientific context, Sternberg and Lubart (1999) define creativity as “the ability to produce work that is both novel (i.e., original, unexpected) and appropriate (i.e., useful)” (p. 3). The distinction between expert decision-making and creativity may lie in the theoretical distinction between “divergent thinking” and “convergent thinking” (Guilford, 1967). Convergent thinking refers to the ability to find the ideal solution to a given problem, whereas divergent thinking is defined at the behavioral level as the unusualness, innovativeness, statistical rareness, or even uniqueness of solutions to a related task. In sports, this latter form of thinking relates to tactical creativity (Memmert & Roth, 2007), that is, varying, rare, and flexible decisions in different kinds of situations (see Appendix 2). Conversely, expert decision-making describes the general ability to find the best tactical solution in any specific situation.
Following this sport-specific interpretation of creativity, tactical creativity can only occur during offensive game situations and not in defensive situations.1 Because the offensive player initiates the action, the defensive player is constrained in their response and therefore limited creatively in a way the offensive player is not. Good defensive action is noted when the player shows adequate behavior (i.e., convergent thinking) towards the opponent’s actions.
Is creativity synonymous then with a high level of offensive performance? Not at all. There are a couple of notable players – although this arguably applies to most players – who show a high degree of convergent thinking, but do not typically demon- strate exceptional creativity in the game. Some examples from basketball are Dirk Nowitzki and Dennis Rodman and from soccer Michael Ballack.
Just as in more explicit cognitive processes (such as pattern recognition, Abernethy et al., 2005), involvement in a diverse range of sport and physical activities may be valuable for the development of creativity. Current theoretical approaches (e.g., Dietrich, 2004; Runco, 2007; Sternberg & Lubart, 1995) support the view that gathering diversified experience over a number of years is ideal for the development of creativity. This is supported by theoretical models (Simonton, 1999b; Sternberg & Lubart, 1995) and empirical evidence from research on general creativity-related context variables (Csikzentmihalyi, 1999; Kurtzberg & Amabile, 2000–2001; Martin- dale, 1990; Milgram, 1990; Simonton, 1996; Smith, Ward, & Finke, 1995). Taken together, a wide range of environmental variability is important and perhaps even necessary for creativity development. From this view, it is important for a team ball
High Ability Studies 5
player – particularly in invasion games such as soccer, hockey or basketball where the generation of tactical response patterns and original solutions are critical – that players have a wide breadth of experience, as this may increase their capability to deal with situations that occur unexpectedly.
What is the bridge between expertise and flexible or creative behavior? Research examining the connection between one aspect of creativity named cognitive flexibility and exceptional performance is not consistent (Anzai & Yokoyama, 1984; Charness & Bieman-Copland, 1992; Frensch & Sternberg, 1989). Some researchers (Anzai & Yokoyama, 1984) found evidence of a positive correlation between flexibility and expertise; others (Charness & Bieman-Copland, 1992), however, did not. Particularly, it is unclear whether the cognitive flexibility characteristic of creativity is domain independent (i.e., if it transfers across domains).
Empirically, several researchers have shown that exceptional creators do not have to be experts in their chosen domains (for a review, see Simonton, 1996). Evidence supports major differences between creators and experts in different character traits such as nonconformity, unconventionality, independence, openness to experience, and risk taking (e.g., Feist, 1998; Simonton, 1991a; 1999a, Sternberg & Lubart, 1995). Central to our investigation is the important individual-difference factor diversifica- tion. For example, diversification can occur on a within-sport basis, if an individual engages in various training and/or play activities, yet it can also occur more broadly, if an individual samples many sports in addition to their primary sport interest (e.g., Côté et al., 2003). Notable creators in an area typically have broader interests and greater versatility than less creative domain experts (e.g., Gough, 1979; Manis, 1951; Runco, 2007; Simon, 1974; Simonton, 1976; Sternberg, 1999). If highly influential creators had broad experiences in their past, this could be associated with “cross- training” (Simonton, 2000), which is incongruent with the specialization approach advocated by Ericsson et al. (1993). With respect to creativity, domain-specific expe- riences do not seem to have more predictive power than general experiences.
On the contrary, past research has also indicated that excessive domain specializa- tion can undermine creative development (Hudson & Jacot, 1986; Kuhn, 1970; Simonton, 1984b, 1991b). In contrast, frequently creators required less time to attain creative performance in different kinds of domains (e.g., Raskin, 1936; Roe, 1952; Zuckermann, 1977). Furthermore, exceptional creativity can occasionally have a curvilinear, inverted-U relationship to training (Simonton, 1983; 1984a), suggesting that domain-specific experience could differ between “experts” and “creators”.
The cumulative domain-specific or nonspecific experiences behind creative achievement in sport are also unclear (for a recent review, see Chen, Himsel, Kasof, Greenberger, & Dmitrieva, 2006). Two studies have examined the role of tactical creativity in the development of exceptional performance in sport. First, a quasi- experimental study by Raab, Hamsen, Roth and Greco (2001) indicated that Brazilian children – with broad and unguided stimuli as well as game experiences – showed considerably greater growth in creativity than German children who had received game-specific training and high-grade instruction in sport clubs. Second, Memmert and Roth (2007) investigated the efficacy of various training approaches in team ball sports for the development of tactical creativity. Children aged seven years took part in a 15-month field-based study where they participated in nonspecific treatment groups, a specific handball, soccer, or field hockey group, or a control group. The analysis of treatment-related effects showed that the areas in which the groups were trained were precisely the areas in which they showed significant improvements. This
6 D. Memmert et al.
could be interpreted as evidence for specific training effects (deliberate practice); however, this interpretation has to be considered relative to evidence of clear transfer effects regarding tactical creativity in team ball sports. For example, the results showed that the soccer-specific group improved in handball- and hockey-oriented creativity and the hockey-specific group also achieved higher performances in handball-oriented creativity. Unlike motor competencies, it seems possible to train tactical creativity independently from movement techniques. This result also supports previous research in net and team ball sports (e.g., French & Thomas, 1987; Jones & Farrow; 1999; Mitchell & Oslin, 1999), which shows that transfer of learning is possible from one net game form to another within the same tactical category.
With this study we aim to further our understanding of the developmental precursors of creativity by examining the role of different forms of sport involvement in explaining differences between highly creative and less creative team sport athletes. In an attempt to maximize the variance of the independent variable (highly creative vs. less creative player), we compare highly creative offensive players with less creative defensive players. We hypothesize that the developmental profiles of highly creative athletes will be different from less-creative athletes with regard to time spent in structured training (e.g., deliberate practice) and unstructured training (e.g., play). Specifically, we hypothesize that more creative athletes will have spent more time in unstructured forms of training/involvement. Furthermore, Baker and Horton (2004) hypothesized that unique contextual factors associated with different sports would affect the amount and type of training required for expertise development. Therefore, we have also considered the relationships between varying forms of training across sports and within a sport (i.e., at different levels of attainment).
Method
Participants
Seventy-two athletes with an average age of 23.2 years (SD=4.4) voluntarily took part in the study. All of them were professional players from the sports of basketball (n=18; female=12), soccer (n=18; female=0), handball (n=18; female=6), and field hockey (n=18; female=12). Basketball and field hockey players were drawn from the male and female German national teams and the highest national league. Handball players were drawn from the national team or in teams playing in the second highest national league. Finally, soccer players were drawn from the first, second, and third highest national leagues. It is important to note that soccer players in the third league had experience playing in the first and second leagues (M=2.8 years, SD=1.8).
All of the participants in this study were selected by their trainers. Twelve trainers from eight clubs and four national teams nominated the three most creative offensive players and least creative defensive players from their teams. Expert creative behavior was operationally defined to the coaches in terms of: (a) unusualness, innovativeness, statistical rareness or even uniqueness of tactical solutions to a game related task; and (b) varying and flexible tactical solutions over different complex game situations (cf. Guilford, 1967; Hocevar & Bachelor, 1989). Informed consent was obtained before commencing the study.
A crucial requirement in this study was establishing the validity of the classifica- tion of highly creative and less-creative players. To this end, the sample of nominated players were assessed by a group of expert trainers from basketball (n=6), field hockey (n=9), handball (n=9), and soccer (n=5). These expert trainers had high training
High Ability Studies 7
licences and trained different teams for more than 10 years. Trainers independently rated each of the players in their team sport (e.g., the soccer trainer rated only the soccer player) according to tactical creativity (using the same definition/criteria as outlined previously) on a 6-point scale with endpoints ranging from 1 (not at all creative) to 6 (very creative). In this way, the word “creative” was affixed to the Likert-scale anchors. The trainers knew about 81% of the presented players and noted when they did not know a player (i.e., they only assessed players they knew). The intra-rater reliability values for all team sports were above the crucial of .80.
To assess the creativity effect for the sports, each were considered in isolation. Analyses of the expert trainer scores confirmed significant differences between the creative and noncreative groups [basketball: F(1,12)=13.208, p<.01, partial η2=.52; field hockey: F(1,16)=23.696, p<.001, partial η2=.60; handball: F(1,16)=5.640, p<.05, partial η2=.26; soccer: F(1,15)=12.457, p<.01, partial η2=.45]. Overall, these examinations indicated that the division of creative and noncreative players was reasonably valid.
Materials
All participants completed a questionnaire based on the interview guide by Côté, Ericsson, and Law (2005) and the deliberate practice questionnaire developed by Ericsson et al. (1993) and modified for sport by Helsen et al. (Helsen, Starkes, & Hodges, 1998). This instrument consisted of three sections with different subscales designed to measure sport experiences across the sport careers of the participants. The first part included questions about general sport involvement. The participants went through a list of sporting activities and marked all activities they participated in between the ages of five and 14 (i.e., prior to the “investment stage” outlined by Côté et al., 2003). They then provided further information about the quantity (hours per week and months per year) and quality (regular participation, level of performance) of each activity. The second section assessed the amount of time participants spent in their main sport (i.e., basketball, soccer, handball, or field hockey) throughout their development. Initially, participants recorded the total amount of time in hours per week and months per year, which was aggregated into hours per year. In the third section, involvement in their main sport was subdivided into unstructured, “play-like activity” (e.g., deliberate play, Côté, Baker, & Abernethy, 2007, which we have called “play”) and other forms of training like organized practice, technique training and weight training (which we have called “practice”). After completing the questionnaire, participants answered follow-up questions designed to determine in which sport they participated and which position they usually played, as well as to gather demographic information.
Procedure
The participants were given one week to complete and return the questionnaire. For the analyses, participants were allocated to two subgroups: highly creative players and less-creative players. Tests of difference were computed using t-tests and univariate analysis of variance (ANOVA). Post hoc tests were conducted using Tukey–HSD. For all analyses, gender of the athletes did not show up as a significant covariate. Because of significant age differences among the sports (F(1,71)=6.86, p<.001), type of sport was included as a covariate. An alpha level of .05 was used for all statistical
8 D. Memmert et al.
comparisons, and effect sizes were calculated using Cohen’s d (for t-tests) and η2 (for ANOVAs).
Results
Reliability of retrospective recall information
Reliability of the players’ estimates was examined through a re-test questioning. Two months later, 10 participants from basketball (n=5) and soccer (n=5) completed the same questionnaire a second time. To validate the players’ self-reported information regarding when they began training and the number of others sports they participated in, the percent agreement was calculated (Bahrick, Hall, & Berger, 1996). There was strong agreement for data on when they began training (100%) and for total number of activities (88%). Pearson correlation analyses were performed between all evalua- tions by the player at the first and second time points. Strong correlations were found regarding years of involvement in main sport (r=.99; p<.001), total hours of involve- ment in main sport (r=.74; p<.01), hours in play (r=.70; p<.05), hours in practice (r=.79; p<.01), and time spent in play activities prior to age 14 (r=.79; p<.05), and time spent in practice activities prior to age 14 (r=.71; p<.05). Collectively, results indicated the data were reasonably reliable.
What experiences are most important for developing creative athletes?
Table 1 provides a comparison of time spent in various types of training in the highly creative and less creative groups. No significant differences were found between the groups for the age at which they began training, number of years of involvement in their main sport, the number of other sports they participated in and the number of hours they spent in practice. However, a significant difference between the groups was found for total time spent in play in their main sport (F(1,71)=2.07, p<.05) indicating that the highly creative athletes spent more time in play, with a medium effect size (d=.49). In addition, the difference between the groups for total hours of time spent in training approached significance (p=.08) again indicating that the highly creative athletes accumulated more total time in training.
Table 1. Mean (SD) time spent in various types of training in highly creative and less-creative groups.
Highly creative Less creative t d
Career sport involvement Begin training 6.54 (2.69) 7.45 (3.15) – – Main sport involvement (years) 16.97 (4.91) 16.27 (4.90) – – Main sport involvement (hours) 6842.86 (3559.68) 5454.70 (2849.95) 1.79a .43 # of other sport 3.49 (2.35) 3.71 (2.40) – – Sport training activities (play) 2857.00 (2071.33) 1954.97 (1291.09) 2.07b .49 Training activities (practice) 3146.39 (2150.44) 3544.03 (2817.72) – –
Early sport involvement (<14) Sport training activities (play) 1340.51 (1166.53) 842.14 (643.75) 2.05b .49 Training activities (practice) 977.40 (677.24) 888.45 (517.91) – –
Note: ap<.10; bp<.05.
High Ability Studies 9
Based on research by Baker, Côté and their colleagues (Baker & Côté, 2006; Baker et al., 2003), we were interested in whether time spent in play and practice prior to age 14 (the transition from “sampling” to “investing”, Côté et al., 2007) would differentiate the two groups. This comparison is also presented in Table 1. As with the total time analyses above, differences between the groups were found for time spent in play (F(1,71)=2.05, p<.05, d=.49) but not for time spent in practice.
Differences across sports and levels of competition
In addition to the overall analyses, exploratory analyses of differences between sports and across competition levels were conducted (Tables 2 and 3). Comparison across the levels of competition revealed significant differences among the levels for age of beginning participation in their main sport (F(2, 69)=3.23, p<.05, η2=.09) and post hoc tests indicated that the national league players started significantly later than play- ers in the next highest level of competition. Differences were also found among the levels for total time spent in play (F(2, 69)=7.31, p<.05, η2=.19), with higher levels of competition being involved in less play than lower levels. There was also a signif- icant main effect for time spent in practice (F(2, 69)=3.44, p<.05, η2=.10) with the lowest level of competition accumulating significantly more time in this type of train- ing than the second highest level. Finally, a significant difference between the levels of competition was found for time spent in play prior to age 14 (F(2, 69)=4.93, p<.05, η2=.14). Similar to the result for total time in play, post hoc analyses revealed that the national-level players reported significantly less time in play than players at the levels below.
Investigation of differences across the sports revealed several significant main effects. These analyses almost exclusively identified basketball as being significantly different from the other sports. More specifically, basketball was significantly differ- ent from all other sports for age at beginning training (F(3, 69)=15.73, p<.05, η2=.42) and total years of involvement (F(3, 69)=19.72, p<.05, η2=.47). Basketball was signif- icantly different from all sports but handball for total time spent in play-like activities (F(3, 69)=7.49, p<.05, η2=.27) and time spent in play-like activities prior to age 14 (F(3, 69)=4.56, p<.05, η2=.19). Basketball was significantly different from all sports but hockey for total time spent in all forms of training (F(3, 69)=12.70, p<.05, η2=.37). Moreover, basketball was significantly different from handball for the number of other sports involved in (F(3, 69)=3.75, p<.05, η2=.14). Finally, soccer was different from basketball and hockey for time spent in practice (F(3, 69)=4.41, p<.05, η2=.18).
Discussion
Our study analyzed whether time spent in play and/or practice was beneficial for becoming a creative player in team ball sports. More specifically, the practice condi- tions of highly creative and less creative team sport athletes were contrasted. Our data show that deliberate practice (Ericsson et al., 1993) and unstructured play-like involvement both have crucial roles for the development of creative behavior in basketball, handball, field hockey, and soccer. In some sense, this is good news for both the expertise and creativity approaches. The results indicate that more creative players accumulated more time in training for their main sport than their less creative counterparts. In addition, significant differences between these groups for time spent
10 D. Memmert et al.
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12 D. Memmert et al.
in unstructured play activities were reported. Both results suggest that practice experiences and early play are important influences on the development of sport creativity. In this case, specific experiences over a long time (10-year rule) are neces- sary for the attainment of expertise (e.g., Helsen et al., 1998; Kalinowski, 1985; Monsaas, 1985). At the same time, gathering diversified experience (such as unstruc- tured play) appears to be necessary for the development of creative thinking (as suggested by Csikzentmihalyi, 1999; Kurtzberg & Amabile, 2000–2001; Sternberg & Lubart, 1995; Sternberg, 1999).
Significant differences were found across levels and sports. These results indicate that the “path” to expertise is not as clearly defined as previously believed and that there can be some flexibility in the type of training an athlete does. The differences across the levels in time spent in play show that play is important but only to a point. Too much emphasis on play may reduce likelihood of developing into an expert. On the other hand, players who are now in the national team started their career signifi- cantly later than the other players did. This would seem to provide evidence against early specialization (Baker, 2003); however, we do not know about their training conditions before involvement in specific training and further study would be helpful. Collectively, these results indicate the need for a balance between the play necessary for motivation, the development of creative thinking, and the practice necessary for highly specific adaptations to task-relevant demands.
What do these results tell us about creativity development in sport?
Our results add to the growing body of evidence supporting the need for developmen- tally appropriate training (see Côté et al., 2007 for a detailed review). Although more research is needed, there is some support for the notion that creativity is learned and stored early in life (see, for a review, Milgram, 1990). Research from neuroscience confirms this view, indicating a distinct time window for the development of cognitive functions. Young children are particularly suitable for training creativity (Chugani, Phelps, & Mazziotta, 1987; Huttenlocher, 1990), since this age group (from birth to eight years) exhibits the greatest absolute number and density of synapses in the primary visual cortex as well as resting glucose uptake in the occipital cortex as measured by PET, indicators associated with creativity (Ashby, Valentin, & Turken, 2002; Bekhtereva, Dan’ko, Starchenko, Pakhomov, & Medvedev, 2001).
An additional issue regarding the development of sport creativity is the quality of training methods. Empirical findings support the hypothesis that a wide breadth of attention facilitates creative performance (Carson, Peterson, & Higgins, 2003; Friedman, Fishbach, Förster, & Werth, 2003; Healey & Rucklidge, 2005). Kasof (1997) argued that as a result of a narrow breadth of attention, not all stimuli and infor- mation that could lead to original and possibly creative solutions in certain situations can be taken in and assimilated. A wide breadth of attention makes it possible to assimilate a variety of stimuli that may initially appear to be irrelevant. Few studies have investigated the deliberate training of breadth of attention in sport. Memmert and Furley (2007) revealed the influence of specific instructions on tactical decision- making of team sport players and found that participants with a wide attentional focus made better tactical decisions than participants with a narrow breadth of attention. A six-month longitudinal study by Memmert (2007) supports the conclusion that an attention-broadening training program can influence the development of creative performance in some sports. These findings highlight the need for optimal design in
High Ability Studies 13
training programs since they can be useful in promoting the development of creativity in children. By using suitable training scenarios, wide breadths of attention can be trained in a targeted manner.
Another relevant factor in teaching team ball sports is motivation (e.g., Darling- Hammond & Snyder, 1992; Holt, Strean, & Bengoechea, 2002). By constantly changing materials (e.g., hockey stick, tennis racquet), balls (e.g., softballs, handballs, balloons) and parts of the body mainly used (hand, foot, head or racquet) in every lesson, trainers could ensure short-term varied experiences, which help to maintain children’s motivation – all with a minimal amount of organizational work. Self- determination theory and Vallerand’s hierarchical model of motivation in sport support the notion that early unstructured play activities will have positive effects on intrinsic motivation over time (cf. Ryan & Deci, 2000; Vallerand, 2001).
Several limitations of this study should be noted. First, all problems concerning retrospective evaluations (e.g., limitations of long-term recall) apply to the data collected from the participants in this study. Although steps were taken to establish the reliability of these data, and similar methods have been used successfully in previ- ous research (Côté et al., 2005; Ericsson et al., 1993; Helsen et al., 1998), the present results should be confirmed in further research, particularly of a longitudinal nature. Second, some biases (e.g., personality, or cognitive traits) could compromise the validity of experts’ creativity nominations and ratings. Third, the sample size and the cross-sectional nature of this study preclude more complex analyses of the research questions (e.g., through models of mediation or moderation) because of the limited number of creative experts in team ball sports. Thus, some potentially confounding variables (e.g., trait of playfulness, intrinsic motivational orientation, domain-specific skills, general performance indicators, and convergent thinking abilities) could not be measured. Therefore, the design of the study precludes a definitive answer to the issue of direction of causality between unstructured playing activities and creativity. Forth, it would be worthwhile to examine in more depth the tool of factors or talents, which lead to extraordinary performance in sport. One possible research line could be to give questionnaires to the coaches, which not only focus on tactical creativity but also ask for information on domain-specific skills and general performance indicators. This could be helpful with regard to disentangling creativity and general motor and cogni- tive performance values in sport. These indicators could link to the past experiences of the athletes.
All the same, these results suggest several avenues for future research. For example, there were generally no differences were found between the handball, field hockey or soccer players. However, basketball players seemed to be quite distinct from the other athletes (e.g., starting their career later, have lower total years of involvement, total time spent in play-like activities, and time spent in play-like activ- ities prior to age 14). These results support Baker and Horton’s (2004) suggestion that sport-specific contextual or cultural factors influence the training and developmental profiles of expert athletes from different sports. The athletes in the present study were drawn from Germany, a country that typically places greater importance on the sports of soccer, field hockey, and handball than basketball. An altogether different pattern of results may be found in athletes from the United States where basketball is more prominent. It is also not clear whether all forms of practice (or play for that matter) are of equal value. Future work should explore the effects of different forms of train- ing (e.g., group practice/play versus individual practice/play) on creativity. The current results, at the very least, indicate that the processes underpinning the
14 D. Memmert et al.
development of creativity in sport are complex and multi-faceted requiring significant additional research using a variety of methods.
Acknowledgement We thank Miriam Knapp, Virginija Margyte, Funny Rinne, Christina Schwitalla, Sarah Seidl, Marija Sklizovic, and Julia Staebe for collecting data. Special thanks go to the editor and two anonymous reviewers for many inspirations and comments on earlier versions of this manu- script.
Note 1. In order to support this statement, we distributed a questionnaire on creativity in sport at a
sports congress for different sports (soccer, handball, field hockey, basketball, volleyball). This contained questions on definition, weighting, trainability, etc. We also included the following statement: “Tactical creativity can only occur during offensive game situations and not in defensive situations.” The participants had a choice of answering with “Agree” or “Disagree”. Of the questionnaires received from n=6 researchers and n=17 coaches, not one of them answered “Disagree”.
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Appendix 1. Statements of soccer coaches from the National Team and the 1. Bundesliga
● “Imagination and creativity should be left to the Brasilians.” (Franz Beckenbauer) ● “The midfield is not creative enough. We no longer have a Häßler or a Littbarski.
Certain things have been neglected that need to be put right.” (Jürgen Klinsmann, former German National Team Coach)
● “Technically and tactically, other countries are far ahead of us. That is why in many clubs the creative player is a foreigner.” (Christoph Daum, 1. FC Köln)
● “Whenever the Germans want to be creative they can’t manage it. They are unable to control the game.” (Jürgen Klopp, Borussia Dortmund)
Appendix 2. Description of sport-specific divergent thinking tests which evaluate tactical creativity in sport
Label Task Authors
Game test situation
This instrument contains a context-dependent real world setting which can directly provoke tactical tasks in ecologically valid situations. Participants’ tactical behavior is recorded on videotape and their tactical decisions are analyzed by expert coders using a subsequent concept-oriented expert rating system (criteria: originality, flexibil- ity).
Memmert (2006, 2007, in press); Memmert & Roth (2007)
Video creativity task
In this decision task, participants watch sport- specific videos. The image is frozen after one minute. The participants have to imag- ine themselves as the acting player and name all opportunities that might possibly lead to a goal. The answers were evaluated accord- ing the criteria of originality, flexibility, and fluency.
Johnson & Raab (2003)
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