Research Articles Scientific Aspects of Talent ...

Research Articles Scientific Aspects of Talent Development A. Hohmnann& I. Seidel (Potsdam, Germany) 1 2

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Talent Identification and Talent Promotion Initial, Juvenile, and FinalPerformance as Stages of the Talent Development Process Talent Detection 2.] Talent Skills (Make-Up) 2.2 Talent Selection 2.3 2.3.1 DiagnosticProblems 2.3.2 Diagnostic Criteria Talent Training 2.4 Talent Prediction 2.5 Talent Perfection 2.6 Summary and Conclusions

Abstract Talent Development with its various aspects (e.g. educational, psychological, institutional) represents (or should represent) very important and extensive aspects of the work of teachers as well as of coaches in the field of sports. Both groups of professionals are more or less consciously involved in the early stages of talent identification and talent promotion. Therefore scientific knowledge about the basic skills and abilities, as to the detection, training, and selection procedures of talented children is indispensable. The purpose of this paper is to give an overview on scientific tasks, especially on the problems of talent identification and talent promotion. These two key factors of the talent development process are very much intertwined, and therefore need to be discussed in close context. With this in mind, this paper will pay special attention to the issues in the field of training interventions and performance diagnostic measures, and not so much on institutional or social aspects of talent development. 1

Talent Identification and Talent Promotion

In the 1970's talent research was conceptualised as a domain specific variant of the more general psychological research on giftedness. With this method the talent approach is directed prospectively and aims at the goal to predict future success on the basis of prepubescent and adolescent performance data. In the 1990's an altemate research concept, called the expertise approach was introduced with the work of Ericsson, Krampe, & Tesch-Romer (1993). The most regarded sport specific studies based on this approach are summarized in the book "Developing talent in young people" by Bloom (1985). With this approach, the research perspective is reversed, meaning it is retrospective. After asking the question what is special about adult elite athletes, and what these adult elite performers had to say about their training history and athletic career, deliberatepractice tumed out to be a crucial factor. Deliberate practice is done to develop required abilities that are not intrinsically motivating, require effort and attention, and do not lead to immediate social or financial rewards. 9

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Figure 1: Initial,juvenile andfinal athleticperformances as segmental stages of talent development

All in all, expertise research has led to an enormous amount of knowledge of how to achieve excellence with its occasional ups and downs. Still unanswered, however, are the very important questions concerning talent development, which can only be solved on the basis of the prospective talent research approach: 1. Talent is an important part of the child's overall potential and deserves recognition and encouragement from the beginning. Therefore, early talent identification is a central need for the well being of our young athletes that strive to realise their full potential. 2. Early talent identification reduces the negative consequences of early specialisation, which on the one hand is definitely needed in regard to future success, but on the other hand may be imposed on children, that are not necessarily best suited for that specific kind of sport. Last, but not least, effective early talent identification lowers the cost of the talent promotion programs. 2

Initial, Juvenile, and Final Performance as Stages of the Talent Development Process

Initial performance means the performance of an individual before he/she gets involved in sport specific training. That kind of performance exhibited by children serves as a starting point of the talent development process (see Fig. l). It is followed by the subsequent juvenile performances of prepubescence and during puberty and adolescence. The last stage of final performance begins when the adult athlete strives for ultimate success. 2.1

Talent Detection

The first step in the stream of talent identification procedures (see Fig. 1) is the detection of talented children that are not yet involved in regular training procedures. Even though the early detection of talented youngsters appears to be advantageous, there are a couple of problems related to the initial screening of (in most cases) prepubescent children that have to be addressed. 10

One of these problems is the ethical question, whether society is allowed to impose such a screening procedure on their breed, especially when the motivation is not used to enhance its development (see above), but merely to "tum flesh into gold" (Lloyd, 1995). Another question is, whether such a screening routine should rely on general or specific testing, i.e. general or specific abilities that compose the initial performance of children. Abernethy (1991) and also Williams and Burwitz (1993) showed strong evidence that the performance in sports games (the same may be true in contact sports) is primarily determined by information processing skills. Therefore, unspecific testing which focuses on general motor abilities or body measures may not provide enough useful information about future success in these types of sports. A third, and maybe the most difficult question is concemed with the statistical assumptions that are based on the Gaussian bell curve, which underlie most of the talent detection projects. The main idea of this model is that abilities are normally distributed within the (young) population, and therefore only the bearers of extreme ability levels have to be identified. This selection process can be problematic, as one can tell from the various cut off limits that are proposed by sport scientists, and which were consequently adopted by different federations and/or institutions. A limit of 2 standard deviations above the average performance of an age population leads to the integration of 2.3 percent of the children of each age population into the talent promotion system. This value served as the gold standard in the GDR and for the Russian talent selection procedure at the entrance of the elite sport schools (Ljach, 1997). If one follows the standards of 3 standard deviations proposed by the Czech Kovar (1981), then only 0.13 percent of the group of interest performs in an acceptable manner. The suggestion of a 4 standard deviation threshold by Matsudo (1996), who regards only 0.003 percent of the population to be capable of an elite athletic career can be viewed as very extreme. 2.2

Talent Skills (Make - Up)

The talent promotion issue (see Fig. 1) still leaves a lot of unanswered questions conceming the make-up of the initial performance of young boys and girls. When speaking of peak performances in adult athletes, one very often does not know much about the structure of the basic motor or cognitive abilities. Even less is known about the typical structures of children's initial performances in most of the various sports disciplines. Therefore, it is quite unclear which skills should be tested. The problem is demonstrated by an anecdote which was reported by Blanksby (1980): "The first talent identification test I saw was at school. When classes marched into the pool the teacher stood by the door, looking down at the ground and pulling various people out of the line - the ones who walked with the feet splayed out. He made them concentrate on breaststroke. That school did always well in breaststroke events." (13). When testing a newcomer for the first time, not much is known about the amount of earlier training and support. In general, this is not a severe problem, since in talented children motor experience appears to be closely linked to a) a supportive movement environment, and b) to a motivated family that promotes the motor development of the youngsters. Poppleton and Salmoni (1991) support these findings in their study on differences between 817 years old talented swimmers (n=77) as compared to non-competitors (n=34) or other (less successful) athletes (n=71). The differences between these three groups were greatest in regard to parental encouragement, parental expectations, and fathers who had been successful in sport.

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2.3

Talent Selection

The most important stage of talent development in young athletes is addressed with juvenile performance (see Fig. 1). At these (pre-) pubescent and adolescent ages athletes have already started with long-term training. 2.3.1

Diagnostic Problems

In the beginning of talent research in the 1960/1970's heredity of certain abilities (see Fig. 2) was in the centre of interest. In some cases this research strategy led to such extreme positions like the one of Hopkins (2001): "If you want your kids to be great athletes, marry a great athlete". Ability 10

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Nature (heredity) vs. Nurture [%] 30 40 50 60 70 80 90

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aerobic endurance 1- Maes, Beunen, Vlietinck, Neale, Thomis, van den Eynde, Lyssens, Simons, Derom & Derom (1996); 2: Kovar (1981) 3: Weiss (1979); 4: Harsanyi & Martin (1986) 98)

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Figure2: Estimates of the heredity of some motor abilities in J0-year-old boys andgirls The early estimates claimed up to 90 percent of the aerobic endurance (VO2 max) to be innate (Klissouras, 1971). Today, only 50 percent of the aerobic endurance is thought to be determined by genetics (Hopkins, 2001). In almost all other abilities the uncertainty conceming the genetically fixed portion of performance abilities is much greater, as the grey area in figure 2 shows. The reasons for this are methodological restrictions that affect the results of the commonly used twin studies: (1) Results from twin studies refer primarily to untrained resp. low trained participants or average athletes. Therefore, the results have to be extrapolated into peak performance level, which is a highly questionable procedure. (2) Genetic limits of an individual athlete also vary over the life span, because of the existence of trainability genes. (3) A unique environment, i.e. the influence of deliberate practice and various support systems has a much higher influence on athletic performance as assumed earlier (Regnier, Salmela & Russell, 1993; Thomis & Beunen, i.p.).

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Since heredity of certain perfornances tumed out not to be as important as previously thought, science examined the stability of performances over the course of the motor development and the training history of young athletes. Figure 3 shows that highly valid tests such as a 20-or 30m sprint will have satisfactory stability over a few years only at the prepubescent stage. With the beginning of puberty these correlation's vanish. Today's scientific findings are leaning toward the direction, that not only the different abilities and traits, but more important, the trainabilityof the athlete itself is the most important innate factor (Bouchard, Malina & Perusse, 1997). The working group around Claude and Thomas Bouchard distinguishes between high and low responders according to their inherited responsiveness to training. In conclusion, it seems to be clear that heredity may play the same important role as nurturing one's talent in mono-structured sports, i.e. sports that depend on very few, sometimes on only one prime physiological component. In all other sports, especially in those where informationprocessing abilities come into play, the role of deliberate practice remains dominant (Baker, 2001).

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Figure3: Stability of some motor abilities over thejuvenile ages

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Two major problems that the responsible institutions are faced with are the voluntary drop out during the many years of prepubescent and adolescent training, and even more critical the segregation of young athletes. Again, there are severe ethical concems against selecting people out from talent promotion, as it has been and is still done frequently in the sport schools or national teams. Future performance t Unexpected High Achievers

Expected High Achievers

r Desired Future Performance

Expected Non-Achievers

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I Selection cut off

Juvenile Performance

Figure 4: Positive and negative selection effects as the consequences of the level of the cut off-limit (adaptedfrom Zaciorski, Bulgakowa, Ragimow & Segijonko, 1974, p. 249) Nontrivial middle cut off values (see Fig. 4) pose the problem that because they are late in maturity, and therefore become high performers at a later point in time, that they may be excluded from specialised coaching and a supportive training environment. Very high cut offs may indicate extraordinary gifted children, but also exclude a much bigger portion of unexpected high achievers. By using this method, institutions will run short of talents or, at least, training partners or team mates. On the other hand, low thresholds as performance limits do not contribute to the effective identification of future excellent performers. In our opinion this dilemma can be overcome by introducing new mathematical methods that avoid strict cut offs and deal with the trade-off between different facets of talent in a better way. One such method is the Fuzzy Logic (Zinner, 1994). According to that concept, there is no fixed limit discriminating optimally good from bad performances. Therefore, a smooth transition between the two poles is preferred. According to this model, each athlete is described by a certain probability to belong, for example, to the group of "strong athletes". The main advantage is that in an athlete lower talent probabilities in one ability or domain can be compensated by higher probabilities in others, as one can see in the endurance example. In the end, every youngster shows different estimates of his abilities, and also of his talent for different sports and therefore, the selection decision will be more profound. Another problem is the age discriminationbias produced by the different birth dates of tested age group children. Over 50 percent of the members of the English Football Association's National School at Lilleshall are born in the first three months after the selection date (see Fig. 5; also Simmons & Paull, 2001). This selection bias results from greater biological age and therefore more physical maturity than their less proficient counterparts and leads to access better coaching and training. The main problem is that the age bias causes differences that last throughout the career of the soccer players, so that the same 50 percent of early borns can be found in the English National Teams during the 1986, 1990, 1994 and 1998 World Cup qualifications (Richardson & Stratton, 1999). Coming back to the fuzzyfication method, age can be fuzzyfied as well. 14

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Figure 5: Proportionof different age groups at the Lilleshall Sport School (Helsen, Hodges, van Winkel & Starkes, 2000, p. 370) 2.3.2

Diagnostic Criteria

Up to now only methodological problems of the talent identification process have been discussed. But of course there are also diagnostic advances. In the study conducted by Hohmann and co-workers (2001) four diagnostic criteria stood out. (1) Juvenileperformance In some sports disciplines the juvenile competition performance provides good information about future outcomes of an athlete. The predictions vary between about 20 and 65 percent, like in high jump (Harsanyi & Martin, 1986), whereas in other sports such as the crawl sprint this information can be obtained only after puberty (Letzelter & Freitag, 1984). The reason for good predictions in some sports is, that these disciplines are solely determined by only a very few performance components that remain fairly stable during puberty, e.g. body height, throwing technique etc. (2) Speed ofperformance development The second criterion is the speed ofperformance development (see Fig. 6). The importance of this criterion has been neglected very often. The reason for this lies in the methodological problems: The better an athlete performs, the smaller are the remaining possible rates of progress in the future. To avoid the resulting bias against the better performing athletes, the performance at the beginning of the time period of interest has to be partitioned out of the gain of performance during that period. Through this process the relative speed of development is revealed. This partitioning out can be done by regression analysis.

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Figure 6: Different speeds offormerijuvenile performance development in better adult male crawl sprinters (Letzelter & Freitag, 1984, p. 29) (3) Utilisation ofperformance conditions The third talent criterion describes to what extend an athlete uses his/her general or specific abilities to produce a competitive performance. It is hypothesised that at least in the juvenile stages talents do not require oversized capacities in one or more basic abilities, such as strength or endurance. On the contrary, talents should excel more by using their resources appropriately. Figure 7 shows that there is indeed no difference between high (HT), normal (NT), and low talented (LT) sprint runners in regard to the share of statistical variance that the predictors flexibility, strength or elementary speed have in common with the criterion sprint performance. These findings confirm the utilisation hypothesis for the more general abilities at least. Differences occur, however, when looking at more specific qualities, such as technique, coordination, complex sprint speed and certain anthropometrical measures. Dim.: LEN-Points [XI+ 100 P.]

1= Flexibility (ns) 2= Strength & Power (ns) 3= Elementary Speed (ns) 4= Technique &Coordination I(1-2**,1-3**,2-3ns)

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(4) Load tolerance The fourth criterion is the capability of an athlete to tolerate high and maximum training loads without getting overtrained or injured. It is evident that it is difficult for the "injury-prone" athlete to be integrated into a profound concept of talent in sport. The talent criterion load tolerance would not be that critical today, if coaches and trainers would change their training strategies from starting rehabilitation after an athlete is injured, to one that prevents injuries by increasing the amount of preventiveforms of trainingat the very beginning of training. 2.4

Talent Training

The key factor in reaching the top level in a sport is a very effective and tolerable training process. But even in this area a lot of questions remain unanswered. The literature on training methodology seems to agree that the long-term training process during sport seen under the age-group perspective has to be divided into at least three training stages (Bompa, 1999): (a) basic education, (b) build-up training, and (c) peak performance training. Even though practitioners unanimously accept these training stages, very little empirical proof exists whether 3, or 4, or even 5 stages are better. In addition to that, there are no scientific data that can illustrate a significant difference between the characteristics of these training concepts. When planning long-term training processes of young athletes, it seems to be advantageous to put stress on the individual strengths and weaknesses. In a series of studies conducted by Platonov and Bulatova (1993), the findings indicate that there are systematic differences in the trainability of children in regard to speed and endurance. The same results can be hypothesised for strength, flexibility and probably for co-ordination, too. The special demands that are typical for the training of children and adolescents lead to the question, whether age group training necessitates certain profiles of coach qualification. A great portion of the success of certain clubs or federations is based on a superior coach tableau in the age groups sport section. 2.5

Talent Prediction

During the final stage of the talent development process (see Fig. 1), the talented junior hopefully reaches his/her peak performance i.e. his/her greatest personal success. Starting again with the talent identification aspect, one has to realise that problems surrounding talent prediction are no less severe than those discussed earlier. If only the best performers are left at this stage, then the problems will shift primarily to statistical and methodological questions. (1) Homogeneous competition performances of adult elite athletes often appear in sharp contrast to the occasional big differences in their individual set of physiological or psychological abilities. This fact reduces the chance to isolate specific factors that discriminate between high and low achievers. statistical constraint results from the retirement of athletes not only from their Another (2) athletic career, but also from dropping out of longitudinal study samples (sample mortality). Since the population of elite performance is very small in size from the beginning, this loss of data affects statistical solutions in a dramatic way. (3) Other scientific problems that result from the study duration and come up with longitudinal research design are the following: Many diagnostic instruments change their validity, some aerobic endurance tests may become more and more anaerobic, and speed tests may no longer control movement coordination but strength abilities. The validity shift appears most difficult with "paper and pencil"-testing, and also with questionnaire in17

struments. Longitudinal studies are not very attractive, especially for young investigators. Beside the methodological difficulties, the study duration and the very often uncertain outcome seem to pose the biggest problems. All in all, there seems to be only one coping strategy possible: rigorous quality management of scientific research. Feasible measures could be to plan investigations in sport schools or as a required assessment by the federation's training system. Furthermore, the design of singlecase-studies, the use of personal gratification's to athletes taking part in tests, and the fillingin of missing data by advanced statistical techniques like multiple imputation. Beside the problems mentioned above, results indicated that multiple interactions ofperformance components might lead to mutual suppressive or enhancing effects. For example, the interaction of strength and speed abilities may be completely positive in one athlete, and only up to a certain limit in another one. It is quite possible that these inter-individual differences in the personal make up of elite athletes affect scientific analyses, especially when it is done on the basis of linear models of group statistics. Another consequence of mutual negative and positive feedback mechanisms within the individual set of abilities and traits is that it may cause a non-linearperformance development. Very seldom do performance improvements develop steadily; on the contrary, in most cases they occur in sudden spurts in a non-linear fashion. From a synergetic point of view, the different states of performance can be regarded as attractors or order parameters. The dynamics of the complex system "athlete" are only stable for a certain stage of the training process (see Davids, 2001; Hohmann, Bulgner, EdelmannNusser, Kellmann & Dobler, 2001). If the performance development of an athlete is interpreted from the dynamic system's perspective, then the athletic behaviour needs to be analysed by means of non-linear mathematical models that are capable to respect explicitly "chaotic" system behaviour. One such tool is the neural netvork model. It allows distinguishing the different levels of talent by means of the self-organisation Kohonen feature map method (Fig. 8) and therefore should be able to lead to a greater success rate. This method allows to group even very different sets of individual performance components in a coherent way. In addition, multilayer back propagation networks could be used for future talent or performance predictions.

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Talent Perfection

The final step of the talentpromotion process (see Fig. ]) is the perfection of adolescent high performers into elite athletes. The transition from junior to senior elite performance is proba18

bly the most difficult step of all. This holds true, even if the junior athlete has already successfully competed on a high international level in his age group. Even though easy solutions are not readily available, it seems to be necessary to build farm teams or plan new, attractive international competitions for junior top athletes, so that their high motivation can be stabilized for a longer time period. But even if motivation problems do not lead to the drop out of a hopeful junior from his athletic career, there are many scenarios in which a young athlete is denied the opportunity to access high-quality training facilities and if he/she is allowed to, then only on a limited basis. In this case, the preferred solution of many promising athletes seems to be to move to a high-quality training centre in another club, town, state or continent. References Abemethy, B. (1991). Visual search strategies and decision-making in sport. International Journalof Sport Psychology, 22, 189-210. Baker, J. (2001). Genes and Training for Athletic Performance Revisited. Sportscience, 5 (2), sportsci.org/jour/0102/jb.htm (2032 words). Blanksby, B.B. (1980). Measures of Talent in Competitive Swimming. Sports Coach, 4 (4), 13-19. Bloom, B.S. (1985). Developing Talent in Young People. New York: Ballantine. Bompa, T.O. (1999). Periodization. Theory and Methodology of Training (4th ed.). Champaign, IL: Human Kinetics. Bouchard, C.; Malina, R.M., & Perusse, L. (1997). Genetics ofFitness andPhysicalPerformance. Champaign, IL: Human Kinetics. Davids, K. (2001). Genes, Training, and other Constraints on Individual Performance: A Role for Dynamical Systems Theory. Sportscience, 5 (2), sportsci.org/jour/0102/kd.htm (1460 words). Ericsson, K.A., Krampe, R.T., & Tesch-R6mer, C. (1993). The role of deliberate practice in the acquisition of' expert performance. PsychologicalReview, 100, 363-406. Harsanyi, L.; Martin, M. (1986). Vererbung - Stabilitat - Auswahl [Heredity - Stability Selection]. Leistungssport, 16 (3), 9-11. Helsen, W.F., Hodges, N.J., van Winkel, J., & Starkes, J.L. (2000). The roles of talent, physical precocity and practice in the development of soccer expertise. Journal of Sports Sciences, 18, 727-736. Hohmann, A., Btigner, J., Edelmann-Nusser, J., Kellmann, M. & Dobler, S. (2001). Nonlinear Identification of Different States of Performance as Orderparameters in an Athletic Training Process . In J. Mester, G. King, H. Struider, E. Tsolakidis & A. Osterburg (eds.), Profiles and Perspectives. Proceedings of the eh Annual Congress of the European College of Sport Science, (p. 332). Cologne: Sport & Buch Strauss. Hohmann, A., Seidel, I., Luihnenschloss, D., Dierks, B., Daum, M. & Wichmann, E. (2001). Schnelligkeit in Nachwuchsleistungssport. [Speed in Elite Age Group Sport]. (9. unv. Zwischenbericht an das BISp, Oktober 2001). Potsdam University: Institute of Sport Science. Hopkins, W.G. (2001). Genes and Training for Athletic Performance. Sportscience, 5 (1), sportsci.org/jour/0101/wghgene.htm (1899 words); 23.09.2002. Joch, W. (1990). Gesetzmatiigkeit und Indetermination der sportmotorischen Leistungsentwicklung im Kindes- und Jugendalter. Zum Problem von Leistungsprognosen im Sport [Law and indetermination of the motor development of sport performance in childhood and adolescence. To the problem of performance prognosis in sport] (pp. 131-160). In H.-J. Menzel & R. Preiss (eds.), ForschungsgegenstandSport. Frankfurt/Main. Klissouras, V. (1971). Heritability of adaptive variation. Journal of Applied Physiology, 31, 338-344. 19

Kovar, R. (1981). Human Variation in Motor Abilities and its Genetic Analysis. Prague: Charles University (Faculty of Physical education and Sport). Letzelter, M. & Freitag, W. (1984). Leistungen und Leistungsentwicklung im Kraulsprint als Gradmesser des Schwimmtalents von Jungen und Madchen [Perfonnance and Performance Development in the Crawl Sprint as Indicator of Swimming Talent in Boys and Girls]. Leistungssport, 24 (2), 28-32. Ljach, W. (1997). Kinderhochleistungssport in Russland [Children Elite Sport in Russia]. Leistungssport, 27 (5),37-40. Lloyd, B. (1995). Blinded by Science. Inside Sport, March 1995. Maes, H.H.M., Beunen, G.P., Vlietinck, R.F., Neale, M.C., Thomis, M., vanden Eynde, B., Lyssens, R., Simons, J., Derom, C. & Derom, R. (1996). Inheritance of physical fitness in 10yr-old twins and their parents. Medicine andScience in Sports andExercise, 1479-1491. Matsudo, V.K.R. (1996). Prediction of Future Athletic Excellence. In Bar-Or, 0. (ed.), The ChildandAdolescent Athlete (pp. 92-109). Oxford: Blackwell Science. Platonov, W.N. & Bulatova, M.M (1993). Die Orientierung des mehrjiihrigen Trainings junger Schwimmer nach ihren Veranlagungen fur Sprint- oder Dauerarbeit [The Orientation of the long-tenn Training of Young Swimmers on the basis of their abilities for sprint or endurance work]. Leistungssport, 23 (1), 40-47. Poppleton, W.L. & Salmoni, A.W. (1991). Talent identification in swimming. Journal of Himan Movement Studies, 20, 85-100. Regnier, G., Salmela, J. & Russell, S.J. (1993). Talent detection and development in sport. In R.N. Singer, M. Murphy & L.K. Tennant (eds.), Handbook of Research in Sport Psychology (pp. 290-313). New York: Wiley. Richardson, D.J. & Stratton, G. (1999). Preliminary investigation into the seasonal birth distribution of England World Cup campaign players. Journalof Sports Sciences, 17, 821-822. Simmons, C. & Paull, G.C. (2001). Season-of-birth bias in association football. Journal of Sport Sciences, 19, 677-686. Siris, P.S. (1974). Das Wachstumstempo der motorischen Eigenschaften - Ein Faktor der potentiellen M6glichkeiten von Sportlem [The speed of development of motor abilities - a factor of the potential of athletes]. Leistungssport, 4 (5), 339-342. Starischka, S. & Stork, H.-M. (1988). Ausgewahlte Materialien zu den Modellversuchen "Talentsuche und Talentforderung Leichtathletik - Bochum/Wattenscheid und Dortmund" [Selected material to the model of "Talent-Search and Talent-Promotion Track and fieldBochum/Wattenscheid and Dortmund"]. In H. de Marees (Red.), Die Talentproblematik im Sport (pp. 140-160). Clausthal-Zellerfeld: Deutsche Vereinigung fur Sportwissenschaft. Thomis, M. & Beunen, G. (in print). Inheritance of Physical Fitness in Children. In A. Hohmann, D. Wick & K. Carl (eds.), Talent im Sport [Talent in Sport] (pp. 44-61). Schomdorf: Hofimann. Weiss, V. (1979). Die Heritabilitaten sportlicher Tests, berechnet aus den Leistungen zehnjahriger Zwillingspaare [Heritabilities of Sport Tests Calculated from the Performances of ten Year Old Twins]. Leistungssport. 9 (1), 58-61. Williams, A.M. & Burwitz, L. (2000). Advance cue utilization in soccer. In T. Reilly, J. Clarys & A. Stibbe (eds.), Science andFootballII (pp. 23 9-244). London: E & FN Spon. Zaciorskij, V.M., Bulgakowa, N.S., Ragimow, R.M. & Segijonko, L.P. (1974). Das Problem des Talents und der Talentsuche im Sport: Richtungen und Methodologien der Untersuchungen [The Problem of Talent and Talent Detection in Sport: Directions and Methodologies of Research]. Leistungssport, 4, 239-251. Zinner, M. (1994). Zur Nutzung unscharfer (fuzzy-) Optimierungsmethoden bei der Auswertung leistungsdiagnostischer Untersuchungen [Utilization of Fuzzy-Optimization Methods for the Analysis of Studies on Performance Diagnosis]. In R. Brack, A. Hohmann & H. Wieland (eds.), Trainingssteuerung- Konzeptionelle und trainingsmethodischeAspekte (pp. 133-137). Stuttgart: Naglschmid. 20

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