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Working paper, Conference Public Matters
Utrecht School of Governance, 19-20 November 2010
Maarten van Bottenburg, Utrecht University
Veerle de Bosscher, Vrije Universiteit Brussel
Simon Shibli, Sheffield Hallam University
Without his individual talent, Pieter van den Hoogenband would never have developed his
impressive swimming career. But neither could he have become a twofold Olympic
champion without the network of sports clubs where he developed as a swimmer; without
the training and competition opportunities he got; without the guidance from coaches,
physiotherapists, doctors, dieticians and sports scientists; nor without the support services
from national governing bodies, governments, Olympic Committees and private partners,
who enabled him to train on a full time basis during many years.
What is at stake here, is a basic feature of social life: people are mutually dependent. Talent,
whether it is in sport, arts, economy or science, is an individual quality that can only be fully
expressed, come out and do well in a specific social environment and with the support of
others. And thus, it depends on the social context and support systems whether talents can
develop themselves and whether an organization, country or other collectivity witnesses a
period of prosperity or decline (cf. Bosscher, Bingham, Shibli, Bottenburg, & Knop, 2008 with
respect to sport; and Willink, 1991 with respect to science). Having the talent, spirit and
dedication are still essential, but the performance capacity and effectiveness of the
environment and support systems they represent are having an increasing impact on the
individual’s chances of success (Bosscher, Knop, Bottenburg, & Shibli, 2006; Heinilä, 1982).
Over the years, policy makers in more and more countries have become aware of the fact
that they can influence this system and produce elite sporting success by investing in elite
sport. Moreover, because elite sporting success – especially at the Olympic Games – is
increasingly regarded as a means to help achieve non-sporting objectives like promoting
national pride and enhancing international prestige, governments have become more willing
to spend increasing sums of money and intervene directly in elite sport (Green & Houlihan,
2005). Several nations have indeed shown that accelerated funding in elite sport can lead to
an increase of medals won at the Olympics. Although a range of macro-level factors who are
out of the control of sports policies (population size, wealth of a country) still account for
approximately fifty per cent of Olympic success (Bosscher et al., 2006), Hogan and Norton
(2000) found a linear relationship between money spent and total medals won by Australia
in the 1980s and 1990s (Hogan & Norton, 2000).
However, in a climate of increased demand for success in a competition for a fixed number
of medals and championships, the ‘price of success’ is raising and the return of investment is
diminishing (Shibli, 2003). This has led Oakley and Green (Oakley & Green, 2001) to describe
the international competition for international sporting success as a ‘global sporting arms
race’. Today, the Australian saying that ‘more money in equals more medals out’ does not
hold anymore. Over the last decade, governments and national sports agencies in many
countries have invested substantially and increasingly in high performance sport – in some
countries even doubling budgets over the four year cycle on the road to Beijing – without
obtaining a proportional return on their investment in terms of international sporting
success (Bosscher et al., 2008; Bottenburg, 2009).
The global sporting arms race has made policy makers even more aware of the need for a
thorough search for effectiveness and efficiency in their elite sport management processes
and policies. They have broadened their scope and policy, from providing support to elite
athletes and creating state of the art training facilities, to other key drivers of international
sporting success, like coach development, post-career support, talent identification and
talent development. With respect to the last two key drivers – talent identification and
talent development – this increased attention has led to a more systematic approach. The
most advanced elite sport policies do no longer rely on chance and the believe that talent
will emerge naturally from the pool of sports participants. Instead, this ‘strategy of chance’ is
replaced by a ‘strategy of planning’. In this new strategy, many antecedents of the – once
detested – elite sport system of the former Eastern Bloc are apparent. This system was
based on a centrally planned system of selection, testing, grading and sifting over a long
period (Green & Oakley, 2001).
This change in strategy has led to a trend toward early identification and specialization of
talented athletes. It has also resulted in sport programs requiring higher levels of investment
from earlier ages and commitment to training in a single sport at the exclusion of other sport
and non-sport activities. To achieve the level of excellence in sport, talents are urged to train
on a full time basis at an increasingly younger age during their adolescence. Moreover, they
are taught that a total commitment of time, energy and emotions is needed to succeed,
often at the sacrifice of social contacts outside of school and sport club (Côté, Lidor, &
Hackfort, 2009; Wiersma, 2000).
At the same time, however, this talent identification and development system is critically
considered and followed from several perspectives, at least in western countries; by sport
organizations, sport scientists, sport journalists, the athletes themselves, their parents, and
many other people involved. On the one hand, a constant critical reflection on the
effectiveness of the talent identification and development is part of the system because
their potential benefits are not a ‘quick fix’, but require a long-term and resource-intensive
strategy; with no guarantee of success (Bosscher et al., 2008). On the other hand, there is a
growing concern about the potential health, psychological and sociological risks for sporting
talents associated with the trend to specialize and fully commit themselves to elite sport at a
young (and increasingly younger) age. After all, by definition, only a small percentage of all
talented athletes reaches the top of the Olympus, in spite of all their sacrifices (Côté, Lidor et
al., 2009; Hecimovich, 2004; Wiersma, 2000).
From both perspectives, pressure is exerted to develop a modified sporting system based on
empirical evidence on the future sport performance of talented athletes and their personal
development. This has resulted in a relatively strong tradition of research in the field of
talent management; not the least because the output of talent management – sport
performances – are so easy to measure and follow. In no other field of study, individual and
team performances and the differences with their competitors can be determined in such an
objective and accurate manner and with so many data available. This has not only given a
deeper insight in ways to influence future performances effectively, but also shed light on
the complexities of talent identification and development and their unintended
consequences for people identified as talents or non-talents.
In this paper, I will discuss these complexities of talent identification and development with
respect to three issues in the field of sport management. The first issue concerns the
contrast between the ‘strategy of chance’ and ‘strategy of planning’. I will elaborate on this
in a discussion of the relationship between sport participation and elite sport policies. The
second issue concerns the effects of early sampling and early specialization pathways in
talent development. And the third issue concerns the predictability of future success and the
changing and multidimensional character of talent.
The strategy of chance is based on the so-called pyramid theory (Bottenburg, 2002).
According to this theory, thousands of people practising sport at the base lead almost
automatically to a few Olympic champions, while the existence of champion role models
spontaneously encourage thousands of people to take up some form of sport. One route to
elite performance could thus be just to increase sports participation among the wider
population. In so doing, the pool of talents will be widened, leading to an increased number
of well performing athletes. Such a sport-for-all policy would serve two goals: more people
being active in sport, and more international sporting success.
In an earlier study, Van Bottenburg found a significant correlation between the percentage
of the population participating in organised sports and the number of medals won per
million inhabitants in 20 European nations (r=.535; p=.007). Furthermore, it appeared from
this study that this correlation primarily depended on the intensity, competitiveness and
degree of organisation in sport participation. This correlation was higher (r=.789; .035) and
not significant for the percentage of the population participating in sport (Bottenburg, 2002).
These findings were supported by De Bosscher and De Knop (Bosscher & Knop, 2002) who
found that success in tennis was highly correlated among 43 European nations with the
number of registered tennis players (r=.724; p=.000). and the number of tennis courts
(r=.858; p=.000). However, Steward et al. (Stewart, Nicholson, Smith, & Westerbeek, 2004)
looked at the correlation between the number of registered sports club members and
international success on a sport-by-sport basis in Australia, and did not find any correlation
in six sports over a fourteen-year period. For example, while Australia is one of the best
swimming nations over the world, the participation rate is only 2 per cent of all sports. A
similar analysis in Flanders partly confirmed these findings. Braeckmans et al. (Braeckmans,
Bosscher, & Hoecke, 2005) analysed six sports over a period of 11 years and found a
significant correlation in two sports: tennis (r=.969; p<0.01) and cycling (r=.0687; p=.014).
Some sports even correlated negatively.
Clearly, these kind of studies are fragmentary. Questions can be raised concerning the
strength on this relationship between national sport participation levels and international
sporting successes, on its causality and on how this relationship occurs. Unfortunately, a lack
of comparable data hinders further in-depth analysis. Further research is needed to get a
deeper understanding of the pyramid theory. The correlations do, however, indicate that
this relationship is at least ambiguous and may vary by sport (Bosscher & Bottenburg, 2010).
Due to processes of specialisation, commercialisation and professionalisation, new
additional structures have been created. On the one hand, many people practice sport
without any desire to move up to a higher level. And increasingly they do so in an informal or
commercial context. On the other, elite sport has developed into a relatively autonomous
world that functions in accordance with different principles from those of sport-for-all.
Accordingly, sport-for-all and elite sport are developing in different directions, so that the
mutual connection between the two is placed under increasing strain (Bosscher &
Bottenburg, 2010). Several countries have separated their elite sport policy from the sport-
for-all objectives and resources.
Among other things, this separation is expressed in a change from diversity to priority in elite
sport policy. Some nations invest in a broad portfolio of sports; others focus more narrowly
on specific sports. The prioritization strategy is based on the idea that it may be more
efficient in elite sport to target the resources on a relatively small number of sports through
identifying those that have a real chance of success at world level (Clumpner, 1994; Oakley &
Green, 2001). This strategy was followed by a number of former communist countries and
has been copied in the last decade increasingly by other nations. However, its foundation
and implication are far more complex than might be expected at first glance.
The talent management system in the Netherlands is a case in point in this respect. The
Netherlands can be seen as typically a nation which has explicitly taken a diversity rather
than a priority approach to performance. A broad spectrum of national sports associations –
63 in total, representing both Olympic and non-Olympic sports such as billiards, bridge, and
chess – is supported for elite performance. Federations and athletes were funded if they had
reached the top eight of the world, regardless of whether their sport was football,
swimming, athletics, draughts, petanque or aero-modelling. Although NOC*NSF has
tightened up this policy since 2003 by reducing the number of targeted sport disciplines
which are eligible for subsidies and stipends, even today elite sport funding is spread over
150 elite sport disciplines of 57 sports. Moreover, talent identification and development
have long been a neglected domain in Dutch elite sport policy. Sports screening programs
are lacking. Most children in the Netherlands are introduced to sports in a spontaneous,
playful way. They are stimulated by their parents, siblings, friends, or teachers. In terms of
sport participation this is quite successful: 75 per cent of the 6- to 11-year old children
participates in sport at least 40 weeks a year. Of these young sport participants, 90 per cent
is affiliated to a sports club and 68 per cent is involved in training and/or competition
(Breedveld, Kamphuis and Tiessen-Raaphorst, 2008). However, as voluntary sport clubs in
the Netherlands generally represent one branch of sport and multiple club memberships or
club membership changes do not occur often or easily (Breedveld en Tiessen-Raaphorst
2006), we do not know whether these children have a talent for other sports than the ones
they practice. They are classified according to their playing level at a relatively young age.
Participation in sport competitions by age groups, regions and levels, leading to promotion,
relegation and championships, completes this system.
From a sport performance perspective, this strategy of chance has thus far been surprisingly
efficient and effective. In spite of the lack of a talent identification and development system
and without a prioritization strategy in elite sport, the Netherlands outperformed other
sample nations (UK, Canada, Italy and Belgium) with respect to the flow of talented athletes
to the expert level in an international comparative research; the so-called SPLISS-study
(Bosscher et al., 2008). Compared to these countries, the Netherlands appeared to have the
most athletes per million inhabitants ranked in the top World eight and top World three (see
Table 1: Number of world top eight and top three athletes in sample nations
Number of athletes in the world top 8 (2003)
227 (Olympic Summer and Winter sports)
17 (Olympic Summer sports)
461 (343 Olympic (of which 111 in team sports) and 118 non-
Olympic disciplines; 40 are in winter sports)
28.3 (21.4 if only Olympic disciplines;
14,6 if team sports are left out)
240 (Mainly Olympic Summer sports)
462 athletes are in WCPP and World Class Podium
programme, of which 20 in Winter sports
8 (Olympic Summer sports)
Number of athletes in the world top 3 (2003)
82 (Olympic Summer and Winter sports)
97 (mainly Olympic Summer sports)
47 (Olympic Summer and Winter sports)
4 (Olympic Summer sports)
2 (Olympic Summer sports)
Source: (Bosscher et al., 2008)
Nevertheless, the international sport policy trends are from chance to strategy and from
diversity to priority. These trends are related to the ever increasing level of sport
performances in the global sporting arms race. If a certain sport in a particular country is
given a competitive advantage thanks to prioritization, other countries are or feel forced to
do the same or accept a slighter chance of winning. In the same way, if the training programs
of young athletes are intensified in one country, sport organizations in other countries are or
feel forced to follow the example. The SPLISS-study revealed that talent identification and
talent development were relatively under developed in all sample nations. Especially the
larger nations achieved relatively poor ratings in terms of their talent identification and
development systems. Apparently, nations with a larger population and a good track record
of success, had taken a relatively relaxed approach to talent development, believing that
talent would emerge quite naturally (Bosscher et al., 2008).
The global sporting arms race puts pressure on countries to revise this approach. A typical
example of this, is the way in which nations try to maximize their pool of potential talent and
develop innovative ways of talent transfer that can deliver a higher return of investment.
One way to do so is the system-related scientific selection process which was typical of
former communist countries. The aim of this selection process was to identify potential elite
athletes outside a sport’s participation base. A similar system currently exists in Australia.
Here, approximately 10,000 young people around the age of 14 are introduced to the most
physiologically appropriate sport of their choice and a selection of these young people is
offered intensive training under professional guidance (Oakley & Green, 2001).
Accordingly, the United Kingdom has set up four projects as a hunt for new talents in the run
op to London 2012. ‘Sporting Giants’ is a project directed towards the selection of tall people
between 16 and 25 and with some sort of athletic background, who may have the potential
to become part of the performance programme in the Olympic Sport of handball, rowing
and volleyball; 58 athletes were selected from a pool of 4,800 applicants. ‘Girls4Gold’ is a
search for highly competitive sportswomen between the age of 17 and 25 with the potential
to become Olympic champions in some targeted sports like cycling, bob skeleton and sailing.
In the project ‘Talent transfer’ UK Sport has analysed the records of over 1,200 retired or
nearly retired athletes previously involved in UK Sports World Class Programmes, to
investigate their suitability to switch sports, and extend their athletic career. And in
‘Pitch2Podium’ young football and rugby players who have been unsuccessful in securing a
professional contract are selected and provided with a second chance opportunity to
succeed in a new Olympic sport (cf. Bosscher & Bottenburg, 2010).
Projects like these are strong examples of talent identification and development outside the
traditional sport organizational structure. The key sports development feature in these
nations is a ‘system-related’ scientific selection system whereby potential elite athletes are
identified not only from within but also from outside the pool of sport participants.
Nonetheless, even here, most if not all newly selected athletes will have some of their roots
in former sport for all programs at schools or in clubs.
3. Early sampling or early specialization?
In most sports millions of young participants develop aspirations to reach the highest levels
of performance, while only a very small number can succeed. Given the low probability of
success, parents and coaches are eager to give them as early as possible encouragement,
support and the best opportunities. And understandably so, the levels of performance in
sport have increased so dramatically, that it takes many years of hard work to reach the top
(Ericsson & Charness, 1994).
In a study on expertise in chess, Simon and Chase (Simon & Chase, 1973) observed that no
chess player had attained the title of ‘grandmaster’ with less than ten years of intense
preparation. Ericsson et al. extended this so-called ’10-year rule’, by stating that it is not just
ten years of playing that makes the champion, but engagement in what they call ‘deliberate
practice’. This is a highly structured activity, which requires a high level of effort and
attention, motivated by the explicit goal of improving performance. The backhand volley, for
example, can only be practiced a few times in a tennis match, but can be repeated many
hundreds of times during a training session. Commitment therefore distinguishes the expert
performer most from players at a lower level. Only individuals who are really committed to
their goals are able and willing to put themselves through years of deliberate practice
(Ericsson & Charness, 1994; Ericsson, Krampe, & Tesch-Römer, 1993).
The ‘ten years-rule’ and theory of deliberate practice has been supported in many studies of
specific sports, such as figure skating, karate, wrestling, soccer, swimming, distance running,
field hockey and tennis, as well as in other domains, like music and mathematics (for review
articles see Baker, Horton, Robertson-Wilson, & Wall, 2003; Côté, Horton, MacDonald, &
Wilkes, 2009). Top violinists appeared to have practiced more than 10,000 hours in all those
years, many more than the next most accomplished groups of expert violinists (Ericsson et
al., 1993). On the basis of this theory, Ericsson et al. (Ericsson & Charness, 1994; Ericsson et
al., 1993) concluded that early specialization and maximization of deliberate practice are
essential for reaching the top. The higher the level of attained elite performance, the earlier
the age of first exposure as well as the age of starting deliberate practice. Elite performers
started practicing two to five years before the age when most children first gained access to
training and spent more time on deliberate practice than did less accomplished individuals.
This theory has been contested for several reasons. First, while the relationship between the
quantity of training and the level of expertise obtained is not disputed, the focus on early
specialization and maximization of deliberate practice have been linked with social problems
(social isolation, identity foreclosure), physical problems (overtraining, injuries) and
psychological problems (motivational burnout, dropout from sport) (Hecimovich, 2004;
Martindale, Collins, & Daubney, 2005; Rossum, 2005; Strachan, Côté, & Deakin, 2009;
Wiersma, 2000). The theory of deliberate practice fully concentrates on the acquisition of
expertise, and in so doing neglects the reciprocal and interactive nature of this development
into an elite athlete and the stages and transitions in his or her psychological, social,
academic and vocational development (Wylleman & Lavallee, 2003).
Second, the application of the framework of deliberate practice to the development of
expertise in sport has been criticized because it only focuses on cognitive learning
mechanisms, while sport offers much room for what Côté et al. have called ‘deliberate play’
(Côté, Baker, & Abernethy, 2003, 2007; Soberlak & Côté, 2003). They define deliberate play
as activities in which children participate because they are inherently enjoyable but could
nonetheless contribute to the development of expertise. According to these authors, few
studies have shown that 10,000 hours of deliberate practice is indeed a prerequisite for
expert performance in sport. They found that peak performance had been achieved with
3,000 to 4,000 hours of sport specific deliberate practice, at least in sports where peak
performance was reached after maturation.
As an alternative approach, Coté et al. (Côté et al., 2007; Côté, Lidor et al., 2009) have
described another path toward elite participation. Next to elite performance through early
specialization they distinguish a trajectory of elite performance through sampling. These two
trajectories are linked to a stage model of talent development. Elaborating on a classic study
by Bloom (Bloom, 1985), Wylleman and Lavallee (2003) identified four stages: (1) the
initiation stage, in which young athletes are introduced to organized sport and identified as
talents; (2) the development stage, during which athletes become more dedicated to their
sport and increase their amount and level of training, ; (3) the mastery or perfection stage in
which athletes reach their highest level; and (4) the discontinuation stage. All stages are
delineated by specific transitions. The initiation stage includes a transition into organized
competitive sports, generally speaking around the age of 6 or 7. The development stage
includes a transition to an intensive level of training and competitions at age 12 or 13. The
mastery stage includes a transition to full-time commitment and engagement in the sport, at
about the age of 18 or 19. And the discontinuation stage involves a transition out of
competitive sports between 28 and 30 years. Of course, these age ranges are averaged over
many athletes and sports, and should be sport specific (Wylleman & Lavallee, 2003). What
distinguishes Wylleman and Lavallee’s approach from that of others is that they relate these
athletic stages and transitions to psychological, social, academic and vocational transitions in
the lives of athletes; and thus adopt a holistic perspective taking the reciprocal and
interactive nature of these different developmental contexts into account.
In the trajectory of elite performance through sampling, then, the initiation stage begins
with sampling years. The young athlete is involved in a variety of different activities which
emphasize motor development and fun. These sampling years are followed by specializing
years, in which a child increasingly focuses on one sport and deliberate play as well as
deliberate practice. After these years, the athlete entries into the investment years, in which
deliberate practice becomes more prominent. In the other trajectory, elite performance
through early specialization, the young athlete does not participate in the sampling years
and advances immediately after initiation into the specializing years. The athlete thus limits
his or her sport participation to a single sport at an early age, with a focus on training and
development in that sport (Côté et al., 2007; Côté, Horton et al., 2009; Côté, Lidor et al.,
According to Côté et al. (2009), the sampling trajectory does not hinder elite sport
participation in sports where peak performance is reached after maturation. Studies of elite
athletes in ice hockey, field hockey, basketball, netball, baseball, tennis, triathlon and rowing
have found that elite performance in these sports was usually preceded by a period of
sampling various sports. Typically, athletes in these sports specialized in their main sport
around age 13-15 and fully invested in their training around age 16. In sports where peak
performance usually occurs before full maturation, like gymnastics and figure skating,
athletes did not benefit from a period of sampling or diversification. For these sports, early
specialization was indeed a strong predictor of elite performance.
Côté et al. (2009) argue that both trajectories can lead to expertise development, but that
there is evidence regarding the developmental benefits of sampling over specialization. Early
sampling is associated with prolonged engagement in sport and physical activity and a lower
frequency of injuries, burnout and dropout than early specialization. Moreover, they argue
that sampling, compared to specialization, is linked to more positive psychosocial outcomes.
For policy reasons, this is of importance of course, because only a small percentage of
children who participate in sports ever become elite athletes. However, a recent
comparative study (Strachan et al., 2009) showed that this distinction between psychosocial
effects of sampling and specialization should not be exaggerated. Samplers and specializers
appeared more similar than different. Samplers had more connections with family and
community through their sports participation than specializers, but the latter reported more
experiences relating to peer groups, as a result of their intimate involvement in sport with a
small but diverse group of peers. Specializers scored significantly higher on exhaustion,
which is linked to burnout and may lead to dropout, but no significant differences were
found between the sampling and specializing groups with respect to sport outcomes and
Like in other fields of expertise, there is strong evidence that adult expert performance is
difficult to predict from sport performances in childhood. As Ericsson et al. (1994)
emphasize, contrary to common belief even most child prodigies never attain exceptional
levels of performance as adults. Conversely, the vast majority of exceptional adult
performers never were child prodigies.
Various reviews of talent detection and talent development in sport literature support this
observation, with the possible exception of early performance sports, like gymnastics and
figure skating. They conclude that the long-term prediction of talented athletes is unreliable,
especially when detection of talent is attempted during the prepubescent or pubertal
periods of growth (Côté, Lidor et al., 2009; Kearney, 1998; Régnier, Salmela, & Russell, 1993).
For example, Bloom (1985) found that less than 10 per cent of top performers were
perceived as future champions when they were 11 or 12 years old. In one of the few
longitudinal studies on talent development in the Netherlands, Van Rossum (2005)
concluded that 12 per cent of a group of 178 talented athletes and volleyball players
reached top levels in their sports. Similar results were found in Flanders (Brouwers,
Bosscher, Truyens, Schaillée, & van Hoecke, 2009).
These findings are highly important. If not much more than 10 per cent of early identified
talents actually reach the top in their sport, that means that the potential of almost 90 per
cent of later elite athletes was not recognized immediately by talent identification programs
when they were young. The policy implication of this is that selection processes need to
have an open and provisional character. After all, selection implies de-selection. If selected
young talents are more and more given preferential treatment with respect to coaching,
facility access, and competitive experiences, late bloomers – with Michael Jordan as prime
example – may not get opportunities to develop in the future (Gould & Carson, 2004). Early
de-selection could then mean permanent de-selection, as Martindale et al. (2005) observed,
with a subsequent reduction in talent base and quality at the top.
This problem of de-selection is relatively strong in sport management because there are
many disparities in physical development amongst same-aged children. This comes to the
fore in the so-called ‘relative age effect’. It has been shown in various sports, including
baseball, hockey, football, tennis, swimming and soccer, that players born earlier in a
selection year are more likely to participate at the top levels of their age groups than players
born during later months of that selection year. As an unintended consequence of the
selection mechanism used in sport organizations, physical maturity differences benefit older
players who get better facilities to high-level training and resources, while the potential of
younger athletes can be overlooked (cf. Baker et al., 2003; Martindale et al., 2005). This
initial selection may result in a subsequent self-fulfilling process of selection, training,
improvement, and selection of those initially involved (Martindale et al., 2005). Many
individual life stories of young talents and elite athletes offer examples of the risks that
potential sport careers can come to an untimely end. Leroy Fer, for example, was almost
sent away when he was a 14 years old junior football player at Feyenoord Rotterdam.
According to his own account, he had growing pain, was all legs, had bad control over the
ball, and was slower in all his actions than his peers.
However, when he became full-grown,
he started to play better and better and is now accepted as the captain of the first team and
one of the most promising players of Dutch football.
Such observations bring into question what we really mean by talent. The key message from
sport management literature on the predictability of future success is that performance by
young athletes needs to be clearly separated from their potential (Martindale et al., 2005).
As performance level and age increase, the criteria for evaluating performance also change
(Ericsson & Charness, 1994). Moreover, talent is multidimensional and dynamic: children can
be identified as talents on the basis of a mix of components, but in the course of time the
relevance of these components and their scores on these components will change
The implication of this message for sport management is of course that talent identification
and development programs should be flexible to allow for such a dynamic and complex
interpretation of the concept of talent. As Martindale et al. conclude, sport organizations
should move away from early selection policies based on winning at young ages. However,
they also observe that in spite of this message, the majority of talent identification and
development programs throughout the world still uses performance measures as main
indicator of talent identification and development at all age groups (Martindale et al., 2005).
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