Sports Medicine

, Volume 46, Issue 8, pp 1041–1058 | Cite as

The Great British Medalists Project: A Review of Current Knowledge on the Development of the World’s Best Sporting Talent

  • Tim Rees
  • Lew Hardy
  • Arne Güllich
  • Bruce Abernethy
  • Jean Côté
  • Tim Woodman
  • Hugh Montgomery
  • Stewart Laing
  • Chelsea Warr
Open Access
Review Article

Abstract

The literature base regarding the development of sporting talent is extensive, and includes empirical articles, reviews, position papers, academic books, governing body documents, popular books, unpublished theses and anecdotal evidence, and contains numerous models of talent development. With such a varied body of work, the task for researchers, practitioners and policy makers of generating a clear understanding of what is known and what is thought to be true regarding the development of sporting talent is particularly challenging. Drawing on a wide array of expertise, we address this challenge by avoiding adherence to any specific model or area and by providing a reasoned review across three key overarching topics: (a) the performer; (b) the environment; and (c) practice and training. Within each topic sub-section, we review and calibrate evidence by performance level of the samples. We then conclude each sub-section with a brief summary, a rating of the quality of evidence, a recommendation for practice and suggestions for future research. These serve to highlight both our current level of understanding and our level of confidence in providing practice recommendations, but also point to a need for future studies that could offer evidence regarding the complex interactions that almost certainly exist across domains.

Keywords

Elite Athlete Implicit Learning Deliberate Practice Great Britain Talent Development 

Key Points

We identify what is known and what is thought likely to be true in relation to understanding the development of the world’s best sporting talent, make recommendations for policy makers and practitioners to act on, and suggest fruitful avenues for future research.

Examining topics related to the performer, the environment, and practice and training, our analysis highlights variation in the quality of evidence relevant to the development of the world’s best sporting talent, such that the strength of evidence in some topics (e.g. anthropometric and physiological factors) is higher than in others (e.g. birthdate).

We provide an authoritative, balanced, comprehensive, fully referenced and critical review of the literature, which should serve as a key point of reference (a) for researchers in talent identification and development in sport, as well as a guide to future research; and (b) for practitioners and policy makers in sport seeking an overarching, evidence-based understanding of the current state of knowledge in the area, as well as a guide for translating that knowledge into action.

1 Introduction

With the competition for medals at Olympics and World Championships intensifying, there is greater investment than ever in sporting systems and structures to identify and develop exceptionally talented athletes. The Australian Institute of Sport has been credited with boosting Australia’s medal haul from five medals in the 1976 Montreal Olympics to 60 medals in the 2000 Sydney Olympics. Team Great Britain (GB)’s fourth position in the 2008 Beijing Olympics medals table was supported by a markedly increased investment (£235M), and this funding continued to support Team GB’s climb to third position in the 2012 London Olympics (£261M). When organizations such as UK Sport (the UK’s high performance sports agency) commit a further £355M of public funds to the Rio 2016 Olympic cycle, it becomes increasingly necessary to be able to draw on an evidence-based understanding of the identification and development of the world’s best sporting talent to maintain the success that is expected with this expenditure. This is the context for the present review, which seeks to identify what is known and what is thought likely to be true in relation to understanding the development of the world’s best sporting talent.

In September 2009, UK Sport invited all UK academic institutions to submit tenders to (a) “research and understand elements of identification and development, to ultimately inform the prediction of future elite sporting talent”; and (b) “conclude unique recommendations from the research that highlight key accelerants and retardants in the pathway development of elite performers”. As part of the subsequent work, the research team (led by the two first authors) drew together a panel of international research experts, elite athletes, coaches from the GB World Class Programme and expertise from UK Sport’s Research and Innovation, and Athlete Development disciplines, and UK Sport’s Senior Management Team. An initial series of meetings, presentations and workshops was held between April 2010 and January 2011. The topics highlighted and conclusions drawn from these sessions guided the development of a review/position statement with regard to current understanding of the performance and development of ‘super-elite athletes’. This review/position statement was used both in strategic planning for Rio 2016 (in March 2013) and to inform a separate research study which further explored the development of super-elite athletes. This process provided the initial guide for the present article, which was subsequently further revised and up-dated through 2015. Of particular note was the first meeting of the collaborative team at UK Sport’s headquarters in Loughborough, UK in June 2010. At this meeting, contributors were asked to present on their key topic(s) of expertise and calibrate evidence in relation to non-elite, junior elite, elite and super-elite levels of performance.

There is a voluminous literature devoted to understanding the development of sporting talent. In addition to numerous peer-reviewed journal articles, there are various academic books [1, 2, 3, 4], reviews/position papers [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16], governing body documents (e.g. from the UK, the USA and Australia [17, 18, 19, 20, 21, 22, 23, 24, 25]), popular books [26, 27, 28, 29, 30, 31, 32], specific models of talent development [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45] and other related works of note [46, 47, 48, 49, 50, 51, 52, 53, 54, 55]. With so much information and opinion across many sub-disciplines of the sports sciences, so many models and frameworks, so many levels of performer, such varied levels of empirical knowledge and much apparent truth, popular wisdom and controversy, the task of generating a clear understanding of the development of the world’s best sporting talent was challenging.

In order to provide recommendations for best practice in which readers could have confidence, we believed it was important to move beyond a purely narrative description of research evidence to rate the quality of evidence available. Thus, we provide additional information, by focusing on three key aspects:
  1. (a)

    Categorization of the performance level of the study samples as non-elite (juniors or seniors competing below national level), junior elite (junior national to junior international level), elite (senior international level) or super-elite (Gold medalists at Olympics or World Championships);1

     
  2. (b)

    Employing a modification to the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system [56] to rate the quality of evidence (based on study design, consistency of evidence and directness of evidence)—indicating the extent to which we can be confident that an estimate of effect is correct;2 , 3 and

     
  3. (c)

    Offering a recommendation (as noted in the GRADE [57] guidelines) to policy makers and/or practitioners on whether to draw on the evidence and use it in practice.

     

We should stress that a strong body of evidence does not necessarily in itself lead to a strong recommendation for practice. For example, one may make confident recommendations when the quality of evidence is high, but the potential benefits of applying knowledge may only lead to modest practical gains. Conversely, one may be less confident in making recommendations because the quality of evidence is low or moderate, yet the potential benefits may be compelling.

2 The Performer

2.1 Birthdate

Athletic success may be influenced by birthdate. The relative age effect (RAE) refers to a biased distribution of elite athletes’ birthdates, with an over-representation of those born at the beginning of any given competitive year (e.g. September in most Western societies) and an under-representation of those born at the end (e.g. August). A meta-analysis [58] of studies from 1984 to 2007, examining non-elite-, junior elite- and elite-level athletes showed robust support for the RAE across ice hockey, soccer, baseball, basketball and volleyball. More recent research with junior elite samples [59, 60, 61] has provided additional evidence for this RAE with ice hockey, handball and soccer.

Although the above results appear convincing, there is evidence that RAEs may be inconsistent. In some elite samples [62, 63, 64, 65], RAEs have been demonstrated in ice hockey and baseball, but not in American Football, basketball, soccer, golf, handball, taekwondo, volleyball and various other unspecified Olympic sports. Elite-level ice hockey players [66] have demonstrated moderate evidence for RAEs in ‘average’ players, but a reversal of the effect in the ‘most’ elite players (‘All Star’ and Olympians), with relatively younger players enjoying longer careers. There is also evidence [67] at junior elite level that RAEs may be more prominent in boys than in girls, as well as evidence that younger athletes figure more prominently in earlier rounds of drafting into US National Hockey teams, and some elite-level data [68] demonstrating a greater proportion of relatively younger players at later stages of careers.

Research [69, 70] with non-elite- and elite-level samples has cautioned against the normal comparison of observed birthdates with an expected distribution of birthdates, because the distribution of birthdates within sports may be uneven due to younger athletes not choosing a particular sport—a form of ‘self-restriction’—and younger athletes being more likely to drop out. For example, when the population of soccer players originally registered in the sport was taken as the comparison group, the RAE disappeared [70].

With moderate study design, low consistency and moderate direct evidence (up to elite level), the quality of the evidence that being relatively older is an advantage with regard to the development of super-elite performance in sport is moderate to low. The evidence suggests that any advantage associated with being born in the first two quarters of the year may disappear by the time athletes reach elite level. We therefore recommend that practitioners do not make use of RAEs for talent selection [71] or development purposes, but rather policy makers and practitioners focus on structuring the environment to limit the negative effect of relative age [72, 73]. More research is needed to better understand the extent to which RAE-related effects occur (a) at initial involvement in a sport (‘self-selection’), (b) after prolonged involvement in competitions (success-related selection), or (c) on selection to an athlete support programme (explicit selection). Researchers should also carefully consider the most appropriate comparator groups. Further, it would be helpful to examine the extent to which the competitive level and range of sports available throughout development is responsible for the RAE—that is, with more players and fewer available sports are RAEs more pronounced?

2.2 Genetics

It would appear no longer a case of whether there is a genetic component to sporting performance, but rather which genetic profiles make the greatest contribution [74]. There is evidence at non-elite level [75, 76, 77, 78, 79] that genetic factors explain 20–80 % of the variance in a host of measures: explosive strength, speed of limb movement, running speed, reaction time, flexibility, balance, bone mineral density, lean muscle mass, eccentric arm flexor strength, concentric arm flexor strength, arm cross-sectional area, change in maximum voluntary force, isometric strength and VO2max. Specific gene variants appear to influence participation in physical activity [80]—the GENEATHLETE project claims to have identified a phenotype for athletic status by comparing athletic samples with sedentary people [81, 82]. Indeed, 66 % of the variance in non-elite ‘athlete status’ may be explained by genetic factors [83].

A significant heritable component has been identified with non-elite samples in agility, sprinting, jumping, throwing, kinematics and reaction time [76, 84, 85, 86], and also in personality/character [87]. Specific gene variants may influence the determination of endurance/aerobic and muscle strength/anaerobic performance [88, 89, 90, 91]. In particular, substantial attention has been paid to the relationship of ACTN3 (actinin alpha 3) and VDR (vitamin D receptor) gene variants with strength/power. Within the ACE (angiotensin I-converting enzyme) gene, the absence (deletion, D allele) rather than presence (insertion, I allele) of 287 base pairs is associated with higher circulating ACE activity [92, 93]. The I allele is generally associated with fatigue resistance and endurance performance, and the D allele with power/strength/sprint phenotypes [94, 95]. The I allele is associated with training-related improvements in loaded repetitive biceps performance [96], its frequency is increased among elite-level high altitude mountain climbers [96] when compared with controls, and it is associated with success in summiting even among non-elite samples [97, 98]. I allele frequency rises with distance run in elite-level runners [99]. Conversely, the D allele is associated with sprint/power performance in elite short-distance swimming [100, 101, 102].

Genetics are also related to susceptibility to injury [103]. The E4 variant of the apolipoprotein E epsilon4 (ApoE4) may be associated with increased severity of chronic neurological deficits in high-exposure non-elite boxers [104], while genetic variation within the collagen type 5 alpha 1 (COL5A1) gene has been associated with Achilles tendon [105] and anterior cruciate ligament injury [106] in non-elite athletes when compared with non-injured controls. The field of epigenetics [107, 108, 109, 110] offers evidence of (heritable but reversible) changes in gene expression, which do not involve a change in the DNA sequence (i.e. gene expression may result from environmental influences). The fact, for example, that mothers’ activity levels might influence gene expression (across generations) could likely have important implications for the emergence of sporting talent. Work on (functional) genomics [111, 112, 113] has demonstrated compelling evidence of changes in gene expression relating to functional adaptation in response to muscle activity in endurance training.

With high study designs, moderate consistency and moderate direct evidence (up to elite level), the quality of the evidence that genetics could make an important contribution to talent selection and development in sport is at least moderate. Indeed, although rare combinations of gene variants are likely to act in concert to yield propensity to super-elite athlete status [114], and elite performance cannot necessarily be predicted well from genetic factors, genetic factors may influence the sport in which athletes are most likely to successfully compete [115]. Genetic selection methodologies may, however, come with negative reputational, personal, ethical and societal impacts. We therefore recommend that policy makers and practitioners consider the possibility of using genetic profiling to help athletes make more informed and appropriate decisions about sport type and discipline during their development years. We may only be able to evaluate the true benefits of genetic testing when geneticists and sports scientists collaborate in large prospective cohort studies that empirically determine the utility of genetic analyses in predicting future performance. The potential impact of genetics could be great, and thus further research in this area is warranted, in particular in relation to specific performance genes, training/learning genes and genes underpinning injury proneness.

2.3 Anthropometric and Physiological Factors

There is a long history of anthropometric studies of Olympic athletes, dating back to documenting the physique of track and field athletes at the 1960 Rome Olympics [116]. As a result, both anthropometric and physiological factors have now been identified across a number of sports at all levels of performance: non-elite [117, 118, 119, 120], junior elite [121, 122, 123, 124, 125, 126, 127, 128], elite [129, 130, 131] and super-elite [132]. Among the many variables examined are: height, weight and (lean) body mass; bone mineral content and density; limb length and circumference; amount of adipose tissue; jumping and sprinting ability; strength; and VO2max. This research has examined a wide range of sports, including: Australian Rules football, basketball, canoe polo, field hockey, football, handball, netball, rowing, rugby league and tennis. Clearly, aerobic capacity, anaerobic endurance and anaerobic power [133] are important for optimal sport performance, with a large proportion of training focused on these qualities, and with specific protocols for physiological assessments likely to be different across different sports [134, 135].

Although morphology-related factors may be involved in directing some athletes to specific sports [136]—e.g. gymnasts and divers are typically the smallest and lightest of all athletes; weightlifters and powerlifters have a high ratio of sitting height to stature caused by shorter than average upper and lower limb lengths—some argue [11] that anthropometric research has been over-interpreted, leading to the questionable practice of anthropmetric profiling to identify athletes for early selection and specialization in a sport. Factors such as individual variability in growth, the unstable nature of anthropometric—as well as physiological—measures throughout adolescence and the limited predictability of performance potentially limit the utility of anthropometric and physiological measures for talent identification purposes. Biological maturation should thus be accounted for in talent identification [123, 137]. Hormonal changes during puberty result in physical and physiological changes, which are important for sporting performance. A review [138] across many sports with non-elite and junior elite data concluded that significant changes during puberty make the prediction of adult performance from adolescent data challenging.

With high study design, high consistency and high direct relevance (up to super-elite level), the quality of the evidence that anthropometric and physiological factors contribute to the development of super-elite performance in sport is high. However, changes during puberty make the prediction of adult performance from adolescent data unreliable. We therefore recommend that practitioners make use of physiological testing for purposes of informing the training process, and make use of anthropometric profiling and physiological tests for both talent selection and development purposes, but policy makers and practitioners should ensure that such action is accompanied by appropriate procedures (considering biological maturation) to ‘re-capture’ lost/missed late maturers. The most obvious issue for talent identification researchers in sport to solve is the problem of predicting adult performance from adolescent anthropometric and physiological data. Solving this conundrum could have an enormous impact on talent identification procedures.

2.4 Psychological Skills and Motivational Orientations

As long ago as 1977, Mahoney and Avener [139] attempted to identify some of the psychological characteristics of elite gymnasts. There is now evidence at non-elite [140, 141, 142, 143, 144, 145, 146], junior elite [147, 148, 149], elite [23, 139, 150, 151, 152, 153, 154, 155, 156] and super-elite [151, 157, 158, 159, 160, 161, 162, 163, 164] level that more successful athletes display higher levels of motivation, higher levels of confidence and perceived control, higher levels of mental toughness and resilience, better ability to cope with adversity, greater resistance to ‘choking’ (i.e. performing worse than expected [165, 166]) in high-pressure situations, and command a wide range of mental skills (e.g. goal-setting, anxiety control, imagery, self-talk and decision-making).

Evidence at elite [23, 153] and super-elite [157, 161, 163, 164] level suggests that athletes display a strong task orientation to base their perceptions of competence on personal improvements, but that at non-elite [167], junior elite [168], elite [169] and super-elite [163, 170] level athletes also display a strong ego orientation to formulate perceptions of competence by comparing their own ability with that of others. There is also evidence that non-elite- [171, 172] and elite- [173] level athletes can use anxiety to enhance their performance. In particular, athletes have been noted to produce both their best and their worst performances when anxious [172]. This may be because anxiety is associated with higher levels of effort [171, 174], which could lead to higher levels of performance, provided the performer does not lapse into attempting to consciously control each specific movement or action [166, 175, 176]. Higher performing athletes also interpret their anxiety symptoms as being more facilitative to their performance than lower performing athletes [177, 178].

There is evidence at non-elite and elite level [179, 180, 181] that successful athletes display self-determined forms of motivation, and that the greater the levels of this form of motivation, the lower the risk of burnout. However, there is also evidence that elite athletes have higher levels of extrinsic motivation and lower levels of intrinsic motivation than less accomplished athletes [182, 183]. More recent research [184] has found that obsessive (more controlling) passion in non-elite athletes is a stronger predictor of deliberate practice (see Sect. 4.1), and thus sports performance, than harmonious (more self-determined) passion.

With moderate study design, high consistency and high direct relevance (up to super-elite level), the quality of the evidence that psychological factors are an important contributor to the development of super-elite performance in sport is high to moderate, although the evidence is more widespread across some psychological characteristics than others. We therefore recommend that practitioners make use of psychological profiling for talent development purposes. Key questions for future research include examining the causes of exceptional levels of motivation, resilience and mental toughness, including assessing whether and how psychological skills at junior level influence long-term adult elite/super-elite performance. How do exceptional performers use their anxiety in a positive way? How do the world’s best performers maintain focus and concentration, while avoiding lapses into conscious control? How can these skills be trained?

2.5 Personality Traits

There is evidence at non-elite [185, 186, 187, 188], elite [23, 189] and super-elite [157, 161, 164] level that more successful athletes display greater conscientiousness, dispositional optimism and hope than less successful athletes. There is also evidence at non-elite [190, 191, 192], elite [23, 164] and super-elite level [161] that athletes display adaptive perfectionism—a tendency to maintain perspective on performances while striving to achieve exceptional standards. This contrasts with the many negative outcomes (e.g. burnout, preoccupation with mistakes and self-doubts) associated with (maladaptive) perfectionism [193]. There is evidence at non-elite level [194, 195, 196, 197, 198] for the influence of narcissism on performance. Narcissists have an inherent (albeit unrealistic) belief in their ability [199], but this self-belief may well facilitate very high levels of performance under pressure [198].

With moderate study design, moderate to low consistency (generally consistent, though relatively infrequent) and high direct relevance (including super-elite level), the quality of the evidence that personality is an important contributor to the development of super-elite performance in sport is moderate. Furthermore, the risks associated with practitioners acting on the available evidence for talent development purposes seem to be only modest, although the same cannot be said with regard to using it for talent selection purposes. We therefore recommend that practitioners might make use of personality profiling for talent development but not talent selection purposes. Future research could focus on whether there are other important (combinations of) personality characteristics that are necessary for the development of a strong competitive personality and how these characteristics might be best developed.

3 The Environment

3.1 Birthplace

There is evidence across junior elite [59, 200, 201] and elite levels [64, 65, 202, 203, 204] that the size of the city where an athlete spends his/her developmental years can affect the likelihood of attaining elite-level performance. Small- to medium-sized communities (circa 30,000–1,000,000) appear to offer the greatest opportunities for success, although there is wide variation (not least because a medium-sized city in one country may be considered small or large in another), and in UK-based data [63], areas with populations of 10,000 and 29,999 are more likely to produce Olympic athletes, with areas between 500,000 and 999,999 being disadvantaged. A birthplace effect analysis [205] with elite and super-elite athletes from the UK World Class Programme (WCP) revealed the following: Compared to the general UK population, WCP athletes were 2.1 times more likely to be born in a medium-sized town (50,000–99,999 residents), 10.5 times more likely to attend a primary school in a very small village (<1999 residents) and 3.0 times more likely to attend secondary school in a very small village (<1999 residents). Birthplace itself may not be as critical as place of early development. Indeed, birthplace effects may be buffered by broader psychological, social, structural and cultural mechanisms [63, 200, 204, 206]. Nevertheless, birthplace effects provide support for the notion that environments vary in their capacity to develop sporting talent and that ‘talent hotspots’ may be a reality.

With moderate study design, high consistency and high direct relevance (up to super-elite level), the quality of the evidence that birthplace offers an advantage with regard to the development of super-elite performance in sport is high to moderate. We therefore recommend that policy makers and practitioners at least take consideration of birthplace when designing talent search initiatives as well as profiling athletes during talent selection and development. Understanding more about the physical and social environment, organisation of resources and the number of participants competing for available places in sports are key areas for research—i.e. understanding more about the environments and neighbourhoods that potential sporting talents are exposed to, and less about birthplace population size.

3.2 Support from Parents, Family, Siblings and Coaches

The importance of family and siblings during athletes’ developmental years has been highlighted [39]. Evidence from non-elite [207, 208, 209, 210, 211, 212, 213, 214, 215, 216], junior elite [148, 217, 218, 219], elite [23, 220, 221, 222] and super-elite [158, 159, 160] athletes attests to the influence of social groups, social support and support networks [223] (including family, coaches, other athletes/peers and support staff). In addition to their key role in the provision of expert coaching and training, coaches can help to enhance the development of psychological skills and mental toughness in athletes during their developmental years [50, 158, 161, 224, 225]. Non-elite data [226, 227] suggest that the supportiveness and feedback effectiveness of coaches is dependent on a unique fit (and common identity) between the characteristics of the coach and the personality of the athlete.

With moderate study design, moderate consistency and high direct relevance (up to super-elite level), the quality of the evidence that support plays a role in the development of super-elite performance in sport is at least moderate. We therefore recommend that policy makers and practitioners heed the important influence of the support process during talent development. However, it is worthy of note that the nuances of providing appropriate support appear to be much more complex than most lay people realize. There is still a relative lack of knowledge with regard to the influence of early family experiences, and we need to know more about the role of the family (parents, siblings, inter-relations) more generally with respect to who reaches super-elite level in sport.

3.3 Athlete Support Programmes

Evidence from 19 European countries [228] suggests that most talent identification systems in sport use current junior performance and/or early competitive success as the main criterion for selection to a development programme. Although most elite and super-elite athletes have been involved in athlete support programmes at some stage [20, 229], there is evidence across all performance levels [13, 20, 228, 229, 230, 231, 232, 233, 234] that junior success does not significantly predict long-term senior success. A 7-year longitudinal study of 4686 German athletes (from athletics, cycling, field hockey, rowing, table tennis, weight lifting and wrestling) across all performance levels [229] and a 12-year longitudinal study involving 1420 members of 13 soccer academies [235] revealed: (a) considerable annual turnover of athletes within each squad; (b) the younger the first recruitment to a support programme, the younger the exit from the programme; and (c) the higher the attained level within an athlete support programme and the higher the level of senior success, the later the age of first recruitment. Various other studies have highlighted super-elite performers being recruited to support programmes at significantly later ages than their elite counterparts [228, 229, 236, 237]. Interestingly, UK data [13] suggest that athletes selected via ‘Talent Transfer’ programmes at ages 16–25 years can reach the performance of their elite peers within 1 year. Relatedly, data from German elite and super-elite athletes at the Summer 2004 and Winter 2006 Olympic Games [238] and from Dutch non-elite and elite athletes [239] reveal no differences in medal success between athletes who attended “elite sport schools” and those who did not, while the latter attained higher academic achievements.

With moderate study design, moderate to low consistency (i.e. consistent but infrequent), and high direct relevance (up to super-elite level), the quality of the evidence regarding early athlete support programmes’ contribution to the development of super-elite performance in sport is moderate. The trajectory to super-elite status appears distinctly non-linear [240], involving repeated selection and de-selection, rather than linear progression within athlete support programmes [235]. We therefore recommend that policy makers and practitioners appreciate that junior success does not contribute significantly to predicting long-term senior success, that early athlete support programmes are not the sole route to the development of talent, that support programmes be open for access at all age ranges, and thus that de-selected athletes be monitored for potential return. Empirical evaluations of the efficacy of athlete support programmes would appear a priority for future research, with the potential to encourage a major re-think of some of the components of the current support programme strategy. At a more theoretical level, why do some apparently ‘talented’, highly motivated athletes fail to progress at key transition points (especially from junior elite to elite level)? Do sport systems typically require the talented athlete to ‘fit in’ more than they adapt to allow the athlete to thrive toward excellence?

4 Practice and Training

4.1 Volume of Sport-Specific Practice and Training

Despite wide variation across sports, most junior elite, elite and super-elite athletes have accumulated enormous volumes of organized practice and training [149, 230, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260]. Extensive sport-specific deliberate practice (DP) is thus a pre-requisite to world-class performance in sports with a large participant base.

A widely held view, based on seminal work in chess [261] and music [262], is that 10 years and 10,000 h of DP are necessary and sufficient to reach expert level [27, 31]. Indeed, many elite and super-elite athletes have been practicing and training for ten years or longer [230, 241, 243, 244, 245, 248]. In discussing his DP framework, however, Ericsson [263] has recently emphasized he did not intend for his original (i.e. 1993 [262]) conclusions to constitute a 10,000 h ‘rule’. In fact, there is considerable variation within and across sports at elite and super-elite level [10, 23, 264], with some data suggesting an average time from novice to senior national representation of just 7.5 years, and even Olympic level in just 14 months [265]. Evidence at super-elite level suggests as few as 4400 h may lead to Olympic Gold in field hockey [236], and 4500 h to representing the German national soccer team [266], with just 4000 h sufficient to reach elite and super-elite levels in basketball, field hockey and netball [241]. Interestingly, organized practice/training has been shown at junior elite [267] and super-elite level [266] to comprise considerable non-DP activity (e.g. play).

DP theory also asserts [262] that the more DP accumulated, the higher the performance attained. There is evidence that more successful athletes have averaged larger amounts of organized sport-specific practice/training. These observations are based on comparisons of non-elite athletes with: junior elite athletes in cricket and soccer [246, 259, 260]; elite athletes in basketball, cricket, field hockey, handball, soccer, swimming, triathlon and wrestling [243, 248, 250, 255, 260]; and super-elite athletes in basketball, darts, field hockey and netball [241, 245], and also on comparisons of adolescent elite with super-elite rhythmic gymnasts [254]. Additionally, elite Australian Rules footballers with better perceptual/decision-making skills performed more domain-specific practice than less skilled players [244]. Differences in the amounts of organized domain-specific practice/training were, however, only significant in these studies for data referring to training in late adolescence and adulthood, not training at younger ages (except rhythmic gymnastics [254]).

Such differences have not been observed between super-elite and elite athletes in field hockey, soccer, tennis, swimming [203, 236, 253, 266] and across all Olympic sports (including athletics, badminton, basketball, fencing, figure skating, gymnastics, judo, rowing, soccer, swimming, table tennis and wrestling) [20, 230]. The opposite effect has also been noted, with super-elite field hockey players training significantly less than their elite peers [258]. No consistent differences have been reported with regard to the volume of competition experienced between different success levels [241, 244, 245, 246, 259].

Although the DP framework has gained popularity in sport science and in popular literature, its applicability to high-performance sport may be limited. The suggestion of 10 years/10,000 h was originally based on: (a) musicians, not outstanding athletes; and (b) a strict interpretation of DP, excluding intrinsically enjoyable activities, team practice, play, competition, non-organized sporting activities, and also ruling out implicit (improved task performance in the absence of conscious awareness) and incidental learning (learning in the absence of an intention to learn). DP also implies full attention and concentration, while research indicates that full concentration does not always generate optimal learning/performance. Increasing conscious awareness may even result in poorer performance (e.g. paralysis by analysis [268]; the regression hypothesis [176]—(i.e., regressing to a performance level akin to earlier learning). Evidence at non-elite level [176, 269] also indicates that implicit learning leads to more robust performance under pressure. Finally, evidence at junior elite [246, 259, 260, 270], elite [242, 244] and super-elite level [241, 245, 266] demonstrates that organized and non-organized play is an important component of (early) experiences of developing sporting experts.

With moderate/high study design, moderate consistency and high direct relevance (up to super-elite level), the quality of evidence that extensive DP is an important contributor to the development of super-elite performance in sport is high to moderate, while high/moderate quality of evidence suggests that the applicability of the 10 years/10,000 h rule is limited and that DP alone does not guarantee sporting success. Additionally, the contribution of practice/training to the development of sporting expertise may only apply to domain-specific practice accrued during late adolescence or adulthood, with practice volume not discriminating elite from super-elite athletes. Finally, there is some low quality evidence to suggest that automaticity and implicit learning may contribute to the development of sporting expertise. We therefore recommend that policy makers and practitioners continue to promote deliberate practice, but consider the present evidence before routinely increasing practice volumes with junior athletes, and acknowledge the potential benefits of automaticity, implicit learning and also enjoyment in practice and play. The links between early sport-specific practice/training and short- and long-term outcomes are a research priority. How is intensified specific training related to long-term enjoyment, motivation, stress-recovery and prolonged involvement? Future research should also further explore the roles of explicit and implicit/incidental learning in the development of expert performance. This implies scrutiny of the intentions and specific activities performed during practice/training and play, their combinations, variability, potential interactions and relative influence through different developmental age ranges.

4.2 Early Specialization Versus Sampling and Play

Where peak performance in sport is achieved before biological maturity, early specialization may be necessary to reach elite level. For example, super-elite athletes in artistic composition sports (artistic gymnastics, figure skating, platform diving and rhythmic gymnastics [230]) performed three to seven times more sport-specific training until age 10 years compared to all other types of Olympic sports. Their volumes of practice/training did not, however, differ from their elite counterparts within their respective sports. A super-elite sample of rhythmic gymnasts also experienced reduced involvement in other sports compared to their elite counterparts [254]. However, evidence at non-elite, junior elite, elite and super-elite level suggests that many athletes have not progressed exclusively within one discipline, but have practiced multiple sports during childhood and adolescence [230, 236, 241, 242, 243, 244, 260, 270, 271, 272, 273, 274]. Further, evidence from non-elite and super-elite data [254, 275, 276, 277, 278] points to the potential costs and risks associated with early specific practice, training and competitions (e.g. less enjoyment, time demands, restricted activities outside sport, exhaustion, overuse injuries and increased risk of dropout). Comparisons between super-elite and elite athletes from field hockey, soccer, tennis and 47 Olympic sports [203, 230, 236, 266] have even demonstrated larger volumes of practice/training and/or play in other sports among the super-elite, mostly associated with a later start in their main sport and a later specialization.

There is also evidence at non-elite, junior elite, elite and super-elite level that many athletes have spent considerable time in non-organized play during childhood [39, 241, 244, 246, 255, 259, 260, 270]. A positive relationship between non-organized play and junior elite [246, 260] and super-elite success [266] has been noted, but equally other studies have noted no differences between performance levels, with some demonstrating more play among non-elite compared with elite/super-elite athletes [236, 241, 244, 245, 255, 259, 260]. Elite and non-elite soccer players [279] could be differentiated by a combination of above-average volume of organized soccer training/practice with either above-average involvement in other sports or above-average non-organized soccer play.

With moderate study design, moderate (early sampling of diverse sports, late specialization)/low (play) consistency, and high direct relevance (up to super-elite level), the quality of the evidence that early specialization or sampling represent the best route to the development of super-elite performance in sport is moderate. Both early specialization and sampling (and play) may be routes to expertise under optimal conditions. However, the probability of attaining elite or super-elite level may be enhanced by the coupling of a large volume of intensive, organized specific training/practice in the main sport with appreciable amounts of organized training/practice and competitions in other sports and/or non-organized play in the main or other sports. We thus recommend policy makers and practitioners to draw on this evidence, bearing in mind the need to minimize the potential hazards of early specialization when such specialization is necessary, and with regard to promoting opportunities for young athletes to experience non-organized play and sampling in a variety of sports. Future research is needed to understand how participation in various sports benefits super-elite performance in one main sport. Further, how does the process of late specialization following prior diversification or ‘talent transfer’ proceed? Are there certain sports or clusters that lay the best foundation for super-elite success in a final sport?

5 Other Potential Factors

There are a number of additional topics that have been raised in the literature, which do not meet the level of evidence of the other topics in this review (e.g. descriptive, anecdotal, non-elite sport or one study). Under-studied in sport, the quality of evidence for these topics is thus low, and we cannot make recommendations to act. Nonetheless, they may still be intriguing ‘candidates’ for future examination. They include: the role of the family’s socioeconomic status in different sports and countries [203, 280, 281, 282]; the different routes to super-elite level across cultures [237]; making errors in the learning process without penalties or consequences [283]; the significance of recovery, rest and sleep to optimize the benefits of practice [284, 285, 286, 287], potentially linked to the reminiscence effect (i.e. ‘improvement in the performance of a partially learned act that occurs while the subject is resting’ p. 3; [288]); the opportunity in sport for athletes to identify, express and (thereby) exercise control over their emotions, which in normal life they find difficult to express [289, 290]; and finally, a potential impact of childhood emotional trauma on qualities such as mental toughness, grit, resilience, growth mindset, achievement striving and ability to overcome difficulties [291, 292, 293]—and relatedly, positive or negative ‘critical’ events with high personal significance (e.g. success milestones, squad selection, non-selection, losses, injury, school disruption, parental divorce and bereavement [23, 156, 158, 159, 291, 294, 295, 296]).

6 Conclusion

We reviewed key topics (see Table 1) relevant to the development of the world’s best sporting talent, generating a current level of understanding, recommendations to act and suggestions for future research. In encouraging researchers, we would point to the relative dearth of prospective and multidisciplinary studies that could offer insight regarding the complex interactions that almost certainly exist across domains. Embracing this complexity remains the most obvious future direction.
Table 1

Overview of research into the development of the world’s best sporting talent: study design quality, consistency of evidence, directness of evidence and key points

Topic

Study design quality

Consistency of evidence

Directness of evidence

The performer

 Birthdate

Moderate

Low

Moderate

  Relative age effects exist but may not be robust across all sports

 Genetics

High

Moderate

Moderate

  Genetics may influence and thus limit the development of performance. Performance cannot, however, be well predicted from genetic factors. Caution should be urged for ethical and societal reasons when considering genetic selection methodologies

 Anthropometric and physiological factors

High

High

High

  Anthropometric and physiological factors are important for performance. However, caution should be urged when using anthropometric and physiological tests for talent selection purposes with adolescents because of variation in biological maturation

 Psychological skills and motivational orientations

Moderate

High

High

  Psychological factors (e.g. motivation, confidence, perceived control, mental toughness, resilience, coping with adversity, resistance to ‘choking’, mental skills) appear to be important contributors to the development of super-elite performance

Personality traits

Moderate

Moderate/low

High

  Super-elite athletes are conscientious, optimistic, hopeful and perfectionist

The environment

 Birthplace

Moderate

High

High

  Small-to-medium communities provide favourable environments for developing athletes. Talent hotspots may exist

 Support from parents, family, siblings and coaches

Moderate

Moderate

High

  Super-elite athletes have benefitted from supportive families, coaches and networks during their development. The subtleties of the provision of support are not well understood

 Athlete support programmes

Moderate

Moderate/low

High

  Early success is a poor predictor for later super-elite success, and thus for early talent identification purposes. Super-elite success is mostly preceded by relatively late entry into organized support programmes

Practice, training and play

 Volume of sport-specific practice and training

High/moderate

Moderate

High

  Super-elite performance develops from extensive deliberate practice, but the applicability of the 10 years/10,000 hours 'rule' to high-performance sport is limited. Play may also be relevant, as may implicit/automatic and incidental skill learning

 Early specialization vs. sampling and play

Moderate

Moderate/low

High

  The key to reaching super-elite level may be involvement in diverse sports during childhood and appreciable amounts of sport-specific practice/training in late adolescence and adulthood

Footnotes

  1. 1.

    Studies of genuinely world-class (i.e. super-elite) athletes are under-represented in sport. At the same time, definitions of ‘elite’ athletes in research vary widely, from regional juniors (non-elite athletes, according to our definitions) through to Olympic gold medal winners (super-elite athletes). As well as attempting to clarify these distinctions, our reasoning for differentiating super-elite from merely elite athletes was the appreciation that there may be subtle yet fundamental differences between athletes who reach international level and those who achieve Gold at Olympic or world level. Such differences would be of great importance and relevance to sporting organizations, tasked with the role of converting elite performers into world’s best.

  2. 2.

    The GRADE system may be used for rating quality of evidence in reviews and guidelines and grading strength of recommendations. The system classifies the quality of evidence into one of four levels: high, moderate, low and very low. Because randomized controlled trials (regarded as the highest rating within the GRADE system) over multiple years are rarely possible in elite sport, we re-calibrated the quality and strength of research evidence by effectively inflating GRADE quality ratings by one point.

  3. 3.

    Our reviews were based on non-exhaustive literature reviews (using Web of Science and Google Scholar in combination with UK Sport’s archives, and the authors’ personal archives). Indeed, many unpublished reports that we considered could not have been considered in a systematic review. Thus, the conclusions are our criterion-based judgments, which we believe aligns with Sports Medicine’s mission to provide an authoritative, balanced, comprehensive, fully referenced and critical review of the literature.

Notes

Compliance with Ethical Standards

Funding

The initial development of the manuscript was supported by a research grant from UK Sport.

Conflict of interest

Tim Rees, Lew Hardy, Arne Güllich, Bruce Abernethy, Jean Côté, Tim Woodman, Hugh Montgomery, Stewart Laing and Chelsea Warr declare that they have no potential conflicts of interest relevant to the content of this review.

References

  1. 1.
    Baker J, Schorer J, Cobley S. Talent identification and development in sport: international perspectives. London: Routledge; 2012.Google Scholar
  2. 2.
    Ericsson KA. The road to excellence: the acquisition of expert performance in the arts and sciences, sports, and games. Mahwah: Erlbaum; 1996.Google Scholar
  3. 3.
    Hemery D. The pursuit of sporting excellence: a study of sport’s highest achievers. London: Willow Books; 1986.Google Scholar
  4. 4.
    Starkes JL, Ericsson KA. Expert performance in sports: advances in research on sport expertise. Champaign: Human Kinetics; 2003.Google Scholar
  5. 5.
    Gulbin JP, Croser MJ, Morley EJ, et al. An integrated framework for the optimisation of sport and athlete development: a practitioner approach. J Sports Sci. 2013;31(12):1319–31. doi: 10.1080/02640414.2013.781661.PubMedCrossRefGoogle Scholar
  6. 6.
    Bailey R, Collins D. The standard model of talent development and its discontents. Kinesiol Rev. 2013;2:248–59.Google Scholar
  7. 7.
    Breitbach S, Tug S, Simon P. Conventional and genetic talent identification in sports: Will recent developments trace talent? Sports Med. 2014:–15. doi: 10.1007/s40279-014-0221-7.
  8. 8.
    Abbott A, Collins D. Eliminating the dichotomy between theory and practice in talent identification and development: considering the role of psychology. J Sports Sci. 2004;22(5):395–408. doi: 10.1080/02640410410001675324.PubMedCrossRefGoogle Scholar
  9. 9.
    Elferink-Gemser MT, Jordet G, Coelho-E-Silva MJ, et al. The marvels of elite sports: how to get there? Br J Sports Med. 2011;45(9):683–4. doi: 10.1136/Bjsports-2011-090254.PubMedCrossRefGoogle Scholar
  10. 10.
    Gulbin J. Identifying and developing sporting experts. In: Farrow D, Baker J, MacMahon C, editors. Developing sport expertise. Abingdon: Routledge; 2008. p. 60–72.Google Scholar
  11. 11.
    Phillips E, Davids K, Renshaw I, et al. Expert performance in sport and the dynamics of talent development. Sports Med. 2010;40(4):271–83. doi: 10.2165/11319430-000000000-00000.PubMedCrossRefGoogle Scholar
  12. 12.
    Tucker R, Collins M. What makes champions? A review of the relative contribution of genes and training to sporting success. Br J Sports Med. 2012;46(8):555–61. doi: 10.1136/Bjsports-2011-090548.PubMedCrossRefGoogle Scholar
  13. 13.
    Vaeyens R, Gullich A, Warr CR, et al. Talent identification and promotion programmes of Olympic athletes. J Sports Sci. 2009;27(13):1367–80. doi: 10.1080/02640410903110974.PubMedCrossRefGoogle Scholar
  14. 14.
    Vaeyens R, Lenoir M, Williams AM, et al. Talent identification and development programmes in sport: current models and future directions. Sports Med. 2008;38(9):703–14. doi: 10.2165/00007256-200838090-00001.PubMedCrossRefGoogle Scholar
  15. 15.
    Collins D, Bailey R. ‘Scienciness’ and the allure of second-hand strategy in talent identification and development. Int J Sport Policy Politics. 2012;5(2):183–91. doi: 10.1080/19406940.2012.656682.CrossRefGoogle Scholar
  16. 16.
    Pankhurst A, Collins D. Talent identification and development: the need for coherence between research, system, and process. Quest. 2013;65(1):83–97. doi: 10.1080/00336297.2012.727374.CrossRefGoogle Scholar
  17. 17.
    Abbott A, Collins D, Martindale R, et al. Talent identification and development: an academic review. A report for SportScotland by the University of Edinburgh. Edinburgh: SportScotland; 2002.Google Scholar
  18. 18.
    Bailey R, Collins D, Ford P, et al. Participant development in sport: an academic review. Leeds; 2010.Google Scholar
  19. 19.
    Douglas K, Carless D. Performance environment research. UK Sport; 2006.Google Scholar
  20. 20.
    Gibbons T, Hill R, McConnell A, et al. The path to excellence: a comprehensive view of development of U.S. Olympians who competed from 1984–1998. Results of the Talent Identification and Development Questionnaire to U.S. Olympians. A United States Olympic Committee publication; 2002.Google Scholar
  21. 21.
    Gibbons T, McConnell A, Forster T, et al. Reflections on success: U.S. Olympians describe success factors and obstacles that most influenced their Olympic development. Results of the Talent Identification and Development Questionnaire to U.S. Olympians. A United States Olympic Committee publication; 2003.Google Scholar
  22. 22.
    Moore S. The development of sporting talent. English Sports Council; 1997.Google Scholar
  23. 23.
    Oldenziel K, P. GJ, Gagne F. How do elite athletes develop? A look through the rear-view mirror. Canberra: Australian Sports Commission; 2003.Google Scholar
  24. 24.
    Rowe N. The development of sporting talent. London: The English Sports Council; 1998.Google Scholar
  25. 25.
    UKSport. Athlete Insights Survey 2009–10. London: UKSport; 2010.Google Scholar
  26. 26.
    Epstein D. The sports gene: what makes the perfect athlete. London: Yellow Jersey Press; 2013.Google Scholar
  27. 27.
    Gladwell M. Outliers: the story of success. London: Penguin; 2009.Google Scholar
  28. 28.
    Johnson M. Gold rush: what makes an Olympic champion?. London: Harper Collins; 2008.Google Scholar
  29. 29.
    Schenk D. The genius in all of us: why everything you’ve been told about genes, talent and intelligence is wrong. London: Icon Books; 2010.Google Scholar
  30. 30.
    Syed M. Bounce: how champions are made. London: Harper Collins; 2010.Google Scholar
  31. 31.
    Coyle D. The talent code. New York: Random House; 2009.Google Scholar
  32. 32.
    Oakley B. Podium: sporting champions’ paths to the top. London: Bloomsbury Sport; 2014.Google Scholar
  33. 33.
    Abbott A, Collins D. A theoretical and empirical analysis of a ‘State of the Art’ talent identification model. High Abil Stud. 2002;13(2):157–78. doi: 10.1080/1359813022000048798.CrossRefGoogle Scholar
  34. 34.
    Abbott A, Button C, Pepping GJ, et al. Unnatural selection: talent identification and development in sport. Nonlinear Dynamics Psychol Life Sci. 2005;9(1):61–88.PubMedGoogle Scholar
  35. 35.
    Abbott A, Collins D, Sowerby K, et al. Developing the potential of young people in sport: a report for SportScotland by the University of Edinburgh. Edinburgh: SportScotland; 2007.Google Scholar
  36. 36.
    Balyi I. Sport system building and long-term athlete development in British Columbia. Coach Rep. 2001;8:22–8.Google Scholar
  37. 37.
    Balyi I. Long-term athlete development: the system and solutions. Faster Higher Stronger. 2002;14:6–9.Google Scholar
  38. 38.
    Balyi I, Hamilton A. Key to success: long-term athlete development. Sport Coach (Canberra, Australia). 2000(23):10–32.Google Scholar
  39. 39.
    Côté J. The influence of the family in the development of talent in sport. Sport Psychol. 1999;13(4):395–417.Google Scholar
  40. 40.
    Côté J, Fraser Thomas J. Youth involvement in sport. In: Crocker PRE, editor. Introduction to sport psychology: a Canadian perspective. Toronto: Pearson Prentice Hall; 2007. p. 266–94.Google Scholar
  41. 41.
    Côté J, Baker J, Abernethy B. Practice and play in the development of sport expertise. In: Eklund R, Tenenbaum G, editors. Handbook of sport psychology. Hoboken: Wiley; 2007. p. 184–202.Google Scholar
  42. 42.
    Gagne F. Giftedness and talent: reexamining a reexamination of the definitions. Gifted Child Quart. 1985;29(3):103–12. doi: 10.1177/001698628502900302.CrossRefGoogle Scholar
  43. 43.
    Gagné F. Constructs and models pertaining to exceptional human abilities. In: Heller KA, Mönks FJ, Passow AH, editors. International handbook of research and development of giftedness and talent. Oxford: Pergamon Press; 1993. p. 63–85.Google Scholar
  44. 44.
    Gagné F. Transforming gifts into talents: the DMGT as a developmental theory. In: Colangelo N, Davis GA, editors. Handbook of gifted education. 3rd ed. Boston: Allyn and Bacon; 2003. p. 60–74.Google Scholar
  45. 45.
    Stambulova N. Talent development in sport: The perspective of career transitions. In: Tsung-Min Hung E, Lidor R, Hackfort D, editors. Psychology of sport excellence. Morgantown: Fitness Information Technology; 2009. p. 63–74.Google Scholar
  46. 46.
    Davids K, Araújo D, Vilar L, et al. An ecological dynamics approach to skill acquisition: implications for development of talent in sport. Talent Dev Excel. 2013;5(1):21–34.Google Scholar
  47. 47.
    Duckworth AL, Peterson C, Matthews MD, et al. Grit: perseverance and passion for long-term goals. J Pers Soc Psychol. 2007;92(6):1087–101. doi: 10.1037/0022-3514.92.6.1087.PubMedCrossRefGoogle Scholar
  48. 48.
    Dweck CS. Self-theories: the mindset of a champion. In: Morris T, Terry P, Gordon S, editors. Sport and exercise psychology: international perspectives. Morgantown: Fitness Information Technology; 2007. p. 15–23.Google Scholar
  49. 49.
    Martindale RJJ, Collins D, Daubney J. Talent development: a guide for practice and research within sport. Quest. 2005;57(4):353–75.CrossRefGoogle Scholar
  50. 50.
    Martindale RJJ, Collins D, Abraham A. Effective talent development: the elite coach perspective in UK sport. J Appl Sport Psychol. 2007;19(2):187–206. doi: 10.1080/10413200701188944.CrossRefGoogle Scholar
  51. 51.
    Simonton DK. Talent and its development: an emergenic and epigenetic model. Psychol Rev. 1999;106(3):435–57. doi: 10.1037//0033-295x.106.3.435.CrossRefGoogle Scholar
  52. 52.
    Henriksen K, Stambulova N, Roessler KK. Holistic approach to athletic talent development environments: a successful sailing milieu. Psychol Sport Exerc. 2010;11(3):212–22. doi: 10.1016/J.Psychsport.2009.10.005.
  53. 53.
    Uehara L, Button C, Falcous M, et al. Contextualised skill acquisition research: A new framework to study the development of sport expertise. Phys Ed Sport Pedagogy. 2014:1–16. doi: 10.1080/17408989.2014.924495.
  54. 54.
    MacNamara A, Button A, Collins D. The role of psychological characteristics in facilitating the pathway to elite performance part 2: examining environmental and stage-related differences in skills and behaviors. Sport Psychol. 2010;24(1):74–96.Google Scholar
  55. 55.
    Araujo D, Davids K. Ecological approaches to cognition and action in sport and exercise: ask not only what you do, but where you do it. Int J Sport Psychol. 2009;40(1):5–37.Google Scholar
  56. 56.
    Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. Br Med J. 2008;336(7650):924–6. doi: 10.1136/Bmj.39489.470347.Ad.CrossRefGoogle Scholar
  57. 57.
    Guyatt GH, Oxman AD, Kunz R, et al. GRADE: going from evidence to recommendations. Br Med J. 2008;336(7652):1049–51. doi: 10.1136/Bmj.39493.646875.Ae.CrossRefGoogle Scholar
  58. 58.
    Cobley S, Baker J, Wattie N, et al. Annual age-grouping and athlete development: a meta-analytical review of relative age effects in sport. Sports Med. 2009;39(3):235–56.PubMedCrossRefGoogle Scholar
  59. 59.
    Baker J, Logan AJ. Developmental contexts and sporting success: birth date and birthplace effects in national hockey league draftees 2000–2005. Br J Sports Med. 2007;41(8):515–7. doi: 10.1136/Bjsm.2006.033977.PubMedPubMedCentralCrossRefGoogle Scholar
  60. 60.
    Figueiredo AJ, Goncalves CE, Silva MJCE, et al. Youth soccer players, 11–14 years: maturity, size, function, skill and goal orientation. Ann Hum Biol. 2009;36(1):60–73. doi: 10.1080/03014460802570584.PubMedCrossRefGoogle Scholar
  61. 61.
    Schorer J, Baker J, Büsch D, et al. Relative age, talent identification and youth skill development: do relatively younger athletes have superior technical skills? Talent Dev Excel. 2009;1(1):45–56.Google Scholar
  62. 62.
    Albuquerque MR, Lage GM, da Costa VT, et al. Relative age effect in Olympic taekwondo athletes. Percept Mot Skills. 2012;114(2):461–8. doi: 10.2466/05.25.Pms.114.2.461-468.PubMedCrossRefGoogle Scholar
  63. 63.
    Baker J, Schorer J, Cobley S, et al. Circumstantial development and athletic excellence: the role of date of birth and birthplace. Eur J Sport Sci. 2009;9(6):329–39. doi: 10.1080/17461390902933812.CrossRefGoogle Scholar
  64. 64.
    MacDonald DJ, Cheung M, Cote J, et al. Place but not date of birth influences the development and emergence of athletic talent in American football. J Appl Sport Psychol. 2009;21(1):80–90. doi: 10.1080/10413200802541868.CrossRefGoogle Scholar
  65. 65.
    Côté J, Macdonald DJ, Baker J, et al. When “where” is more important than “when”: birthplace and birthdate effects on the achievement of sporting expertise. J Sports Sci. 2006;24(10):1065–73. doi: 10.1080/02640410500432490.PubMedCrossRefGoogle Scholar
  66. 66.
    Gibbs BG, Jarvis JA, Dufur MJ. The rise of the underdog? The relative age effect reversal among Canadian-born NHL hockey players: a reply to Nolan and Howell. Int Rev Sociol Sport. 2012;47(5):644–9. doi: 10.1177/1012690211414343.CrossRefGoogle Scholar
  67. 67.
    Vincent J, Glamser FD. Gender differences in the relative age effect among US Olympic Development Program youth soccer players. J Sports Sci. 2006;24(4):405–13. doi: 10.1080/02640410500244655.PubMedCrossRefGoogle Scholar
  68. 68.
    Schorer J, Cobley S, Busch D, et al. Influences of competition level, gender, player nationality, career stage and playing position on relative age effects. Scand J Med Sci Sports. 2009;19(5):720–30. doi: 10.1111/J.1600-0838.2008.00838.X.PubMedCrossRefGoogle Scholar
  69. 69.
    Delorme N, Boiche J, Raspaud M. Relative age and dropout in French male soccer. J Sports Sci. 2010;28(7):717–22. doi: 10.1080/02640411003663276.PubMedCrossRefGoogle Scholar
  70. 70.
    Delorme N, Boiche J, Raspaud M. Relative age effect in elite sports: methodological bias or real discrimination? Eur J Sport Sci. 2010;10(2):91–6. doi: 10.1080/17461390903271584.CrossRefGoogle Scholar
  71. 71.
    Deaner RO, Lowen A, Cobley S. Born at the wrong time: selection bias in the NHL draft. PLoS One. 2013;8(2):1–7. doi: 10.1371/journal.pone.0057753.CrossRefGoogle Scholar
  72. 72.
    Hancock DJ, Adler AL, Côté J. A proposed theoretical model to explain relative age effects in sport. Eur J Sport Sci. 2013;13(6):630–7. doi: 10.1080/17461391.2013.775352.PubMedCrossRefGoogle Scholar
  73. 73.
    Romann M, Cobley S. Relative age effects in athletic sprinting and corrective adjustments as a solution for their removal. PLoS One. 2015;10(4):1–12. doi: 10.1371/journal.pone.0122988.CrossRefGoogle Scholar
  74. 74.
    Eynon N, Ruiz JR, Oliveira J, et al. Genes and elite athletes: a roadmap for future research. J Physiol Lond. 2011;589(13):3063–70. doi: 10.1113/Jphysiol.2011.207035.PubMedPubMedCentralCrossRefGoogle Scholar
  75. 75.
    Bouchard C, Daw EW, Rice T, et al. Familial resemblance for VO2max in the sedentary state: the HERITAGE Family Study. Med Sci Sports Exerc. 1998;30(2):252–8. doi: 10.1097/00005768-199802000-00013.PubMedCrossRefGoogle Scholar
  76. 76.
    Maes HHM, Beunen GP, Vlietinck RF, et al. Inheritance of physical fitness in 10-yr-old twins and their parents. Med Sci Sports Exerc. 1996;28(12):1479–91. doi: 10.1097/00005768-199612000-00007.PubMedCrossRefGoogle Scholar
  77. 77.
    Seeman E, Hopper JL, Young NR, et al. Do genetic factors explain associations between muscle strength, lean mass, and bone density? A twin study. Am J Physiol Endocrinol Metab. 1996;270(2):E320–7.Google Scholar
  78. 78.
    Thomis MAI, Beunen GP, Maes HH, et al. Strength training: importance of genetic factors. Med Sci Sports Exerc. 1998;30(5):724–31. doi: 10.1097/00005768-199805000-00013.PubMedCrossRefGoogle Scholar
  79. 79.
    Thomis MAI, Beunen GP, Van Leemputte M, et al. Inheritance of static and dynamic arm strength and some of its determinants. Acta Physiol Scand. 1998;163(1):59–71. doi: 10.1046/J.1365-201x.1998.00344.X.PubMedCrossRefGoogle Scholar
  80. 80.
    De Moor MHM, Liu YJ, Boomsma DI, et al. Genome-wide association study of exercise behavior in Dutch and American adults. Med Sci Sports Exerc. 2009;41(10):1887–95. doi: 10.1249/Mss.0b013e3181a2f646.PubMedPubMedCentralCrossRefGoogle Scholar
  81. 81.
    Doring F, Onur S, Fischer A, et al. A common haplotype and the Pro582Ser polymorphism of the hypoxia-inducible factor-1 alpha (HIF1A) gene in elite endurance athletes. J Appl Physiol. 2010;108(6):1497–500. doi: 10.1152/Japplphysiol.01165.2009.PubMedCrossRefGoogle Scholar
  82. 82.
    Wolfarth B, Rankinen T, Muhlbauer S, et al. Association between a beta(2)-adrenergic receptor polymorphism and elite endurance performance. Metab Clin Exp. 2007;56(12):1649–51. doi: 10.1016/J.Metabol.2007.07.006.
  83. 83.
    De Moor MHM, Spector TD, Cherkas LF, et al. Genome-wide linkage scan for athlete status in 700 British female DZ twin pairs. Twin Res Hum Genet. 2007;10(6):812–20. doi: 10.1375/Twin.10.6.812.PubMedCrossRefGoogle Scholar
  84. 84.
    Bouchard C, Malina RM, Perusse L. Genetics of fitness and physical performance. Champaign: Human Kinetics; 1997.Google Scholar
  85. 85.
    Malina RM, Bouchard C. Genetic considerations in physical fitness. In: Drury TF, editor. Assessing physical fitness and physical activity in population-based surveys. DHHS Pub. No. (PHS) 89-1253. Washington, DC: US Government Printing Office; 1989. p. 453–73.Google Scholar
  86. 86.
    Okuda E, Horii D, Kano T. Genetic and environmental effects on physical fitness and motor performance. Int J Sport Health Sci. 2005;3:1–9.CrossRefGoogle Scholar
  87. 87.
    Althoff RR, Hudziak JJ. The role of behavioral genetics in child and adolescent psychiatry. J Can Acad Child Adolesc Psychiatry. 2011;20(1):4–5.PubMedPubMedCentralGoogle Scholar
  88. 88.
    Bray MS, Hagberg JM, Perusse L, et al. The human gene map for performance and health-related fitness phenotypes: the 2006–2007 update. Med Sci Sports Exerc. 2009;41(1):34–72. doi: 10.1249/Mss.0b013e3181844179.CrossRefGoogle Scholar
  89. 89.
    Beunen G, Thomis M. Gene powered? Where to go from heritability (H-2) in muscle strength and power? Exerc Sport Sci Rev. 2004;32(4):148–54.PubMedCrossRefGoogle Scholar
  90. 90.
    Peeters MW, Thomis MAI, Beunen GP, et al. Genetics and sports: an overview of the pre-molecular biology era. In: Collins M, editor. Genetics and sports. Basel: Kargel; 2009. p. 28–42.CrossRefGoogle Scholar
  91. 91.
    Rankinen T, Roth SM, Bray MS, et al. Advances in exercise, fitness, and performance genomics. Med Sci Sports Exerc. 2010;42(5):835–46. doi: 10.1249/Mss.0b013e3181d86cec.PubMedCrossRefGoogle Scholar
  92. 92.
    Danser AHJ, Schalekamp MADH, Bax WA, et al. Angiotensin-converting enzyme in the human heart: effect of the deletion/insertion polymorphism. Circulation. 1995;92(6):1387–8.PubMedCrossRefGoogle Scholar
  93. 93.
    Costerousse O, Allegrini J, Lopez M, et al. Angiotensin I-converting enzyme in human circulating mononuclear cells: genetic polymorphism of expression in T-lymphocytes. Biochem J. 1993;290:33–40.PubMedPubMedCentralCrossRefGoogle Scholar
  94. 94.
    Beunen GP, Thomis MAI, Peeters MW. Genetic variation in physical performance. Open Sports Sci J. 2010;3:77–80.CrossRefGoogle Scholar
  95. 95.
    Puthucheary Z, Skipworth JRA, Rawal J, et al. The ACE gene and human performance 12 years on. Sports Med. 2011;41(6):433–48. doi: 10.2165/11588720-000000000-00000.PubMedCrossRefGoogle Scholar
  96. 96.
    Montgomery HE, Marshall R, Hemingway H, et al. Human gene for physical performance. Nature. 1998;393(6682):221–2. doi: 10.1038/30374.PubMedCrossRefGoogle Scholar
  97. 97.
    Thompson J, Raitt J, Hutchings L, et al. Angiotensin-converting enzyme genotype and successful ascent to extreme high altitude. High Alt Med Biol. 2007;8(4):278–85. doi: 10.1089/Ham.2007.1044.PubMedCrossRefGoogle Scholar
  98. 98.
    Tsianos G, Eleftheriou KI, Hawe E, et al. Performance at altitude and angiotensin 1-converting enzyme genotype. Eur J Appl Physiol. 2005;93(5–6):630–3. doi: 10.1007/S00421-004-1284-1.PubMedCrossRefGoogle Scholar
  99. 99.
    Myerson S, Hemingway H, Budget R, et al. Human angiotensin I-converting enzyme gene and endurance performance. J Appl Physiol. 1999;87(4):1313–6.PubMedGoogle Scholar
  100. 100.
    Costa AM, Silva AJ, Garrido ND, et al. Association between ACE D allele and elite short distance swimming. Eur J Appl Physiol. 2009;106(6):785–90. doi: 10.1007/S00421-009-1080-Z.PubMedCrossRefGoogle Scholar
  101. 101.
    Nazarov IB, Woods DR, Montgomery HE, et al. The angiotensin converting enzyme I/D polymorphism in Russian athletes. Eur J Hum Genet. 2001;9(10):797–801. doi: 10.1038/Sj.Ejhg.5200711.PubMedCrossRefGoogle Scholar
  102. 102.
    Woods D, Hickman M, Jamshidi Y, et al. Elite swimmers and the D allele of the ACE I/D polymorphism. Hum Genet. 2001;108(3):230–2. doi: 10.1007/S004390100466.PubMedCrossRefGoogle Scholar
  103. 103.
    Collins M, Raleigh SM. Genetic risk factors for musculoskeletal soft tissue injuries. In: Collins M, editor. Genetics and sports. Basel: Karger; 2009. p. 136–49.CrossRefGoogle Scholar
  104. 104.
    Jordan BD, Relkin NR, Ravdin LD, et al. Apolipoprotein E epsilon 4 associated with chronic traumatic brain injury in boxing. JAMA (J Am Med Assoc). 1997;278(2):136–40. doi: 10.1001/Jama.278.2.136.CrossRefGoogle Scholar
  105. 105.
    Mokone GG, Schwellnus MP, Noakes TD, et al. The COL5A1 gene and Achilles tendon pathology. Scand J Med Sci Sports. 2006;16(1):19–26. doi: 10.1111/J.1600-0838.2005.00439.X.PubMedCrossRefGoogle Scholar
  106. 106.
    Posthumus M, September AV, Keegan M, et al. Genetic risk factors for anterior cruciate ligament ruptures: COL1A1 gene variant. Br J Sports Med. 2009;43(5):352–6. doi: 10.1136/Bjsm.2008.056150.PubMedCrossRefGoogle Scholar
  107. 107.
    Waddington CH. Canalization of development and the inheritance of acquired characters. Nature. 1942;150:563–5. doi: 10.1038/150563a0.CrossRefGoogle Scholar
  108. 108.
    Riggs AD, Martienssen RA, Russo VEA. Introduction. In: Russo VEA, Martienssen RA, Riggs AD, editors. Epigenetic mechanisms of gene regulation. New York: Cold Spring Harbor Laboratory Press; 1996.Google Scholar
  109. 109.
    Sharp NCC. The human genome and sport, including epigenetics and athleticogenomics: a brief look at a rapidly changing field. J Sports Sci. 2008;26(11):1127–33. doi: 10.1080/02640410801912117.PubMedCrossRefGoogle Scholar
  110. 110.
    Ehlert T, Simon P, Moser DA. Epigenetics in sports. Sports Med. 2013;43(2):93–110. doi: 10.1007/S40279-012-0012-Y.PubMedCrossRefGoogle Scholar
  111. 111.
    Keller P, Vollaard N, Babraj J, et al. Using systems biology to define the essential biological networks responsible for adaptation to endurance exercise training. Biochem Soc Trans. 2007;35:1306–9.PubMedCrossRefGoogle Scholar
  112. 112.
    Timmons JA, Jansson E, Fischer H, et al. Modulation of extracellular matrix genes reflects the magnitude of physiological adaptation to aerobic exercise training in humans. BMC Biol. 2005;3. doi: 10.1186/1741-7007-3-19.
  113. 113.
    Timmons JA, Larsson O, Jansson E, et al. Human muscle gene expression responses to endurance training provide a novel perspective on Duchenne muscular dystrophy. FASEB J. 2005;19(7):750–60. doi: 10.1096/Fj.04-1980com.PubMedCrossRefGoogle Scholar
  114. 114.
    Ahmetov II, Williams AG, Popov DV, et al. The combined impact of metabolic gene polymorphisms on elite endurance athlete status and related phenotypes. Hum Genet. 2009;126(6):751–61. doi: 10.1007/S00439-009-0728-4.PubMedCrossRefGoogle Scholar
  115. 115.
    MacArthur D, North K. Genes and human elite athletic performance. Hum Genet. 2005;116(5):331–9. doi: 10.1007/S00439-005-1261-8.PubMedCrossRefGoogle Scholar
  116. 116.
    Tanner JM. The physique of the Olympic athlete: A study of 137 track and field athletes at the XVIIth Olympic Games, Rome 1960, and a comparison with weight-lifters and wrestlers. London: Allen and Unwin; 1964.Google Scholar
  117. 117.
    Bunc V, Psotta R. Physiological profile of very young soccer players. J Sports Med Phys Fitness. 2001;41(3):337–41.PubMedGoogle Scholar
  118. 118.
    Elferink-Gemser MT, Visscher C, Lemmink KAPM, et al. Multidimensional performance characteristics and standard of performance in talented youth field hockey players: a longitudinal study. J Sports Sci. 2007;25(4):481–9. doi: 10.1080/02640410600719945.PubMedCrossRefGoogle Scholar
  119. 119.
    Visscher C, Elferink-Gemser MT, Lemmink KAPM. Interval endurance capacity of talented youth soccer players. Percept Mot Skills. 2006;102(1):81–6.PubMedCrossRefGoogle Scholar
  120. 120.
    Till K, Cobley S, O’Hara J, et al. Retrospective analysis of anthropometric and fitness characteristics associated with long-term career progression in Rugby League. J Sci Med Sport. 2015;18(3):310–4. doi: 10.1016/j.jsams.2014.05.003.PubMedCrossRefGoogle Scholar
  121. 121.
    Aouadi R, Jlid MC, Khalifa R, et al. Association of anthropometric qualities with vertical jump performance in elite male volleyball players. J Sports Med Phys Fitness. 2012;52(1):11–7.PubMedGoogle Scholar
  122. 122.
    Gabbett T, Kelly J, Ralph S, et al. Physiological and anthropometric characteristics of junior elite and sub-elite rugby league players, with special reference to starters and non-starters. J Sci Med Sport. 2009;12(1):215–22. doi: 10.1016/J.Jsams.2007.06.008.
  123. 123.
    Hirose N. Relationships among birth-month distribution, skeletal age and anthropometric characteristics in adolescent elite soccer players. J Sports Sci. 2009;27(11):1159–66. doi: 10.1080/02640410903225145.PubMedCrossRefGoogle Scholar
  124. 124.
    McMillan K, Helgerud J, Macdonald R, et al. Physiological adaptations to soccer specific endurance training in professional youth soccer players. Br J Sports Med. 2005;39(5):273–7. doi: 10.1136/Bjsm.2004.012526.PubMedPubMedCentralCrossRefGoogle Scholar
  125. 125.
    Mohamed H, Vaeyens R, Matthys S, et al. Anthropometric and performance measures for the development of a talent detection and identification model in youth handball. J Sports Sci. 2009;27(3):257–66. doi: 10.1080/02640410802482417.PubMedCrossRefGoogle Scholar
  126. 126.
    Mohr M, Krustrup P, Bangsbo J. Fatigue in soccer: a brief review. J Sports Sci. 2005;23(6):593–9. doi: 10.1080/02640410400021286.PubMedCrossRefGoogle Scholar
  127. 127.
    Till K, Cobley S, O’Hara J, et al. Using anthropometric and performance characteristics to predict selection in junior UK Rugby League players. J Sci Med Sport. 2011;14(3):264–9. doi: 10.1016/J.Jsams.2011.01.006.
  128. 128.
    Vaeyens R, Malina RM, Janssens M, et al. A multidisciplinary selection model for youth soccer: the Ghent youth soccer project. Br J Sports Med. 2006;40(11):928–34. doi: 10.1136/Bjsm.2006.029652.PubMedPubMedCentralCrossRefGoogle Scholar
  129. 129.
    Kerr DA, Ross WD, Norton K, et al. Olympic lightweight and open-class rowers possess distinctive physical and proportionality characteristics. J Sports Sci. 2007;25(1):43–53. doi: 10.1080/02640410600812179.PubMedCrossRefGoogle Scholar
  130. 130.
    Roescher CR, Elferink-Gemser MT, Huijgen BCH, et al. Soccer endurance development in professionals. Int J Sports Med. 2010;31(3):174–9. doi: 10.1055/S-0029-1243254.PubMedCrossRefGoogle Scholar
  131. 131.
    Veale JP, Pearce AJ, Carlson JS. The Yo-Yo intermittent recovery test (level 1) to discriminate elite junior Australian football players. J Sci Med Sport. 2010;13(3):329–31. doi: 10.1016/J.Jsams.2009.03.006.
  132. 132.
    Lawton TW, Cronin JB, McGuigan MR. Anthropometry, strength and benchmarks for development: a basis for junior rowers’ selection? J Sports Sci. 2012;30(10):995–1001. doi: 10.1080/02640414.2012.682081.PubMedCrossRefGoogle Scholar
  133. 133.
    Williams AM, Reilly T. Talent identification and development in soccer. J Sports Sci. 2000;18(9):657–67. doi: 10.1080/02640410050120041.PubMedCrossRefGoogle Scholar
  134. 134.
    Winter EM. Sport and exercise physiology testing guidelines: the British Association of Sport and Exercise Sciences guide. 1st ed. New York: Routledge; 2006.Google Scholar
  135. 135.
    Gore CJ, Australian Sports Commission. Physiological tests for elite athletes. Champaign: Human Kinetics; 2000.Google Scholar
  136. 136.
    Hume PA, Stewart AD. Body composition change. In: Stewart AD, Sutton L, editors. Body composition in sport, exercise and health. Oxford: Routledge; 2012. p. 147–65.Google Scholar
  137. 137.
    Vandendriessche JB, Vaeyens R, Vandorpe B, et al. Biological maturation, morphology, fitness, and motor coordination as part of a selection strategy in the search for international youth soccer players (age 15–16 years). J Sports Sci. 2012;30(15):1695–703. doi: 10.1080/02640414.2011.652654.PubMedCrossRefGoogle Scholar
  138. 138.
    Pearson DT, Naughton GA, Torode M. Predictability of physiological testing and the role of maturation in talent identification for adolescent team sports. J Sci Med Sport. 2006;9(4):277–87. doi: 10.1016/J.Jsams.2006.05.020.
  139. 139.
    Mahoney M, Avener M. Psychology of the elite athlete: an exploratory study. Cogn Therapy Res. 1977;1(2):135–41. doi: 10.1007/bf01173634.CrossRefGoogle Scholar
  140. 140.
    Burton D. Do anxious swimmers swim slower? Reexamining the elusive anxiety-performance relationship. J Sport Exerc Psychol. 1988;10(1):45–61.Google Scholar
  141. 141.
    Gould D, Weiss M, Weinberg R. Psychological characteristics of successful and nonsuccessful big ten wrestlers. J Sport Psychol. 1981;3:69–81.Google Scholar
  142. 142.
    Coffee P, Rees T. When the chips are down: effects of attributional feedback on self-efficacy and task performance following initial and repeated failure. J Sports Sci. 2011;29(3):235–45. doi: 10.1080/02640414.2010.531752.PubMedCrossRefGoogle Scholar
  143. 143.
    Coffee P, Rees T, Haslam SA. Bouncing back from failure: the interactive impact of perceived controllability and stability on self-efficacy beliefs and future task performance. J Sports Sci. 2009;27(11):1117–24. doi: 10.1080/02640410903030297.PubMedCrossRefGoogle Scholar
  144. 144.
    Thomas PR, Murphy SM, Hardy L. Test of performance strategies: development and preliminary validation of a comprehensive measure of athletes’ psychological skills. J Sports Sci. 1999;17(9):697–711. doi: 10.1080/026404199365560.PubMedCrossRefGoogle Scholar
  145. 145.
    Gucciardi DF, Peeling P, Ducker KJ, et al. When the going gets tough: Mental toughness and its relationship with behavioural perseverance. J Sci Med Sport. 2015. doi: 10.1016/j.jsams.2014.12.005.
  146. 146.
    Crust L, Azadi K. Mental toughness and athletes’ use of psychological strategies. Eur J Sport Sci. 2010;10(1):43–51. doi: 10.1080/17461390903049972.CrossRefGoogle Scholar
  147. 147.
    Hardy L, Bell J, Beattie S. A neuropsychological model of mentally tough behavior. J Pers. 2014;82(1):69–81. doi: 10.1111/Jopy.12034.CrossRefGoogle Scholar
  148. 148.
    Holt NL, Dunn JGH. Toward a grounded theory of the psychosocial competencies and environmental conditions associated with soccer success. J Appl Sport Psychol. 2004;16(3):199–219. doi: 10.1080/10413200490437949.CrossRefGoogle Scholar
  149. 149.
    Ward P, Hodges NJ, Starkes JL, et al. The road to excellence: deliberate practice and the development of expertise. High Abil Stud. 2007;18(2):119–53. doi: 10.1080/13598130701709715.CrossRefGoogle Scholar
  150. 150.
    Boes R, Harung HS, Travis F, et al. Mental and physical attributes defining world-class Norwegian athletes: content analysis of interviews. Scand J Med Sci Sports. 2014;24(2):422–7. doi: 10.1111/j.1600-0838.2012.01498.x.PubMedCrossRefGoogle Scholar
  151. 151.
    Gould D, Eklund RC, Jackson SA. Coping strategies used by United States Olympic wrestlers. Res Q Exerc Sport. 1993;64(1):83–93.PubMedCrossRefGoogle Scholar
  152. 152.
    Gould D, Finch LM, Jackson SA. Coping strategies used by national champion figure skaters. Res Q Exerc Sport. 1993;64(4):453–68.PubMedCrossRefGoogle Scholar
  153. 153.
    Jones G, Hanton S, Connaughton D. What is this thing called mental toughness? An investigation of elite sport performers. J Appl Sport Psychol. 2002;14(3):205–18. doi: 10.1080/10413200290103509.CrossRefGoogle Scholar
  154. 154.
    Mahoney MJ, Gabriel TJ, Perkins TS. Psychological skills and exceptional athletic performance. Sport Psychol. 1987;1:181–99.Google Scholar
  155. 155.
    MacNamara A, Button A, Collins D. The role of psychological characteristics in facilitating the pathway to elite performance part 1: identifying mental skills and behaviors. Sport Psychol. 2010;24(1):52–73.Google Scholar
  156. 156.
    Gulbin JP, Oldenziel KE, Weissensteiner JR, et al. A look through the rear view mirror: developmental experiences and insights of high performance athletes. Talent Dev Excel. 2010;2(2):149–64.Google Scholar
  157. 157.
    Bush N, Salmela JH. The development and maintenance of expert athletic performance: perceptions of World and Olympic Champions. J Appl Sport Psychol. 2002;14:154–71.CrossRefGoogle Scholar
  158. 158.
    Connaughton D, Hanton S, Jones G. The development and maintenance of mental toughness in the world’s best performers. Sport Psychol. 2010;24(2):168–93.Google Scholar
  159. 159.
    Connaughton D, Wadey R, Hanton S, et al. The development and maintenance of mental toughness: perceptions of elite performers. J Sports Sci. 2008;26(1):83–95. doi: 10.1080/02640410701310958.PubMedCrossRefGoogle Scholar
  160. 160.
    Fletcher D, Sarkar M. A grounded theory of psychological resilience in Olympic champions. Psychol Sport Exerc. 2012;13(5):669–78. doi: 10.1016/J.Psychsport.2012.04.007.
  161. 161.
    Gould D, Dieffenbach K, Moffett A. Psychological characteristics and their development in Olympic champions. J Appl Sport Psychol. 2002;14(3):172–204. doi: 10.1080/10413200290103482.CrossRefGoogle Scholar
  162. 162.
    Hays K, Thomas O, Maynard I, et al. The role of confidence in world-class sport performance. J Sports Sci. 2009;27(11):1185–99. doi: 10.1080/02640410903089798.PubMedCrossRefGoogle Scholar
  163. 163.
    Hemery D. Sporting excellence: what makes a champion?. London: Collins Willow; 1991.Google Scholar
  164. 164.
    Orlick T, Partington J. Mental links to excellence. Sport Psychol. 1988;2:105–30.Google Scholar
  165. 165.
    Baumeister RF. Choking under pressure: self-consciousness and paradoxical effects of incentives on skillful performance. J Pers Soc Psychol. 1984;46:610–20. doi: 10.1037/0022-3514.46.3.610.PubMedCrossRefGoogle Scholar
  166. 166.
    Beilock SL, Carr TH. On the fragility of skilled performance: what governs choking under pressure? J Exp Psychol Gen. 2001;130(4):701–25. doi: 10.1037/0096-3445.130.4.701.PubMedCrossRefGoogle Scholar
  167. 167.
    Abrahamsen FE, Roberts GC, Pensgaard AM. Achievement goals and gender effects on multidimensional anxiety in national elite sport. Psychol Sport Exerc. 2008;9(4):449–64. doi: 10.1016/J.Psychsport.2007.06.005.
  168. 168.
    Cervello E, Rosa FJS, Calvo TG, et al. Young tennis players’ competitive task involvement and performance: the role of goal orientations, contextual motivational climate, and coach-initiated motivational climate. J Appl Sport Psychol. 2007;19(3):304–21. doi: 10.1080/10413200701329134.CrossRefGoogle Scholar
  169. 169.
    Pensgaard AM, Roberts GC. Achievement goal orientations and the use of coping strategies among Winter Olympians. Psychol Sport Exerc. 2003;4(2):101–16. doi: 10.1016/S1469-0292(01)00031-0.CrossRefGoogle Scholar
  170. 170.
    Ripol W. The psychology of the swimming taper. Contemp Psychol Perform Enhance. 1993;2:22–64.Google Scholar
  171. 171.
    Hardy L, Hutchinson A. Effects of performance anxiety on effort and performance in rock climbing: a test of processing efficiency theory. Anxiety Stress Coping. 2007;20(2):147–61. doi: 10.1080/10615800701217035.PubMedCrossRefGoogle Scholar
  172. 172.
    Hardy L, Parfitt G. A catastrophe model of anxiety and performance. Br J Psychol. 1991;82:163–78.PubMedCrossRefGoogle Scholar
  173. 173.
    Hanton S, Jones G. The acquisition and development of cognitive skills and strategies: I. Making the butterflies fly in formation. Sport Psychol. 1999;13(1):1–21.Google Scholar
  174. 174.
    Smith NC, Bellamy M, Collins DJ, et al. A test of processing efficiency theory in a team sport context. J Sports Sci. 2001;19(5):321–32. doi: 10.1080/02640410152006090.PubMedCrossRefGoogle Scholar
  175. 175.
    Hardy L, Mullen R. Performance under pressure: a little knowledge is a dangerous thing? In: Thomas PR, editor. Optimising performance in Golf. Brisbane: Australian Academic Press; 2001. p. 245–63.Google Scholar
  176. 176.
    Masters RSW. Knowledge, knerves and know-how: the role of explicit versus implicit knowledge in the breakdown of a complex motor skill under pressure. Br J Psychol. 1992;83:343–58.CrossRefGoogle Scholar
  177. 177.
    Hanton S, Neil R, Mellalieu SD. Recent developments in competitive anxiety direction and competition stress research. Int Rev Sport Exerc Psychol. 2008;1(1):45–57. doi: 10.1080/17509840701827445.CrossRefGoogle Scholar
  178. 178.
    Jones G, Hanton S, Swain A. Intensity and interpretation of anxiety symptoms in elite and non-elite sports performers. Pers Indiv Differ. 1994;17(5):657–63. doi: 10.1016/0191-8869(94)90138-4.CrossRefGoogle Scholar
  179. 179.
    Cresswell SL, Eklund RC. Motivation and burnout among top amateur rugby players. Med Sci Sports Exerc. 2005;37(3):469–77. doi: 10.1249/01.Mss.0000155398.71387.C2.PubMedCrossRefGoogle Scholar
  180. 180.
    Cresswell SL, Eklund RC. Motivation and burnout in professional rugby players. Res Q Exerc Sport. 2005;76(3):370–6.PubMedCrossRefGoogle Scholar
  181. 181.
    Mallett CJ, Hanrahan SJ. Elite athletes: why does the ‘fire’ burn so brightly? Psychol Sport Exerc. 2004;5(2):183–200. doi: 10.1016/S1469-0292(02)00043-2.CrossRefGoogle Scholar
  182. 182.
    Fortier MS, Vallerand RJ, Briere NM, et al. Competitive and recreational sport structures and gender: a test of their relationship with sport motivation. Int J Sport Psychol. 1995;26(1):24–39.Google Scholar
  183. 183.
    Chantal Y, Guay F, Dobreva-Martinova T, et al. Motivation and elite performance: an exploratory investigation with Bulgarian athletes. Int J Sport Psychol. 1996;27(2):173–82.Google Scholar
  184. 184.
    Vallerand RJ, Mageau GA, Elliot AJ, et al. Passion and performance attainment in sport. Psychol Sport Exerc. 2008;9(3):373–92. doi: 10.1016/J.Psychsport.2007.05.003.
  185. 185.
    Piedmont RL, Hill DC, Blanco S. Predicting athletic performance using the five-factor model of personality. Pers Indiv Differ. 1999;27(4):769–77. doi: 10.1016/S0191-8869(98)00280-3.CrossRefGoogle Scholar
  186. 186.
    Woodman T, Zourbanos N, Hardy L, et al. Do performance strategies moderate the relationship between personality and training behaviors? An exploratory study. J Appl Sport Psychol. 2010;22(2):183–97. doi: 10.1080/10413201003664673.CrossRefGoogle Scholar
  187. 187.
    Grove JR, Heard NP. Optimism and sport confidence as correlates of slump-related coping among athletes. Sport Psychol. 1997;11(4):400–10.Google Scholar
  188. 188.
    Martin-Krumm CP, Sarrazin PG, Peterson C, et al. Explanatory style and resilience after sports failure. Pers Indiv Differ. 2003;35(7):1685–95. doi: 10.1016/S0191-8869(02)00390-2.CrossRefGoogle Scholar
  189. 189.
    Nicholls AR, Polman RCJ, Levy AR, et al. Mental toughness, optimism, pessimism, and coping among athletes. Pers Indiv Differ. 2008;44(5):1182–92. doi: 10.1016/J.Paid.2007.11.011.
  190. 190.
    Jowett GE, Hill AP, Hall HK, et al. Perfectionism and junior athlete burnout: the mediating role of autonomous and controlled motivation. Sport Exerc Perform Psychol. 2013;2(1):48–61. doi: 10.1037/a0029770.CrossRefGoogle Scholar
  191. 191.
    Stoeber J, Uphill MA, Hotham S. Predicting race performance in triathlon: the role of perfectionism, achievement goals, and personal goal setting. J Sport Exerc Psychol. 2009;31(2):211–45.PubMedGoogle Scholar
  192. 192.
    Stoll O, Lau A, Stoeber J. Perfectionism and performance in a new basketball training task: does striving for perfection enhance or undermine performance? Psychol Sport Exerc. 2008;9(5):620–9. doi: 10.1016/J.Psychsport.2007.10.001.
  193. 193.
    Roberts R, Rotheram M, Maynard I, et al. Perfectionism and the ‘Yips’: an initial investigation. Sport Psychol. 2013;27(1):53–61.Google Scholar
  194. 194.
    Roberts R, Callow N, Hardy L, et al. Interactive effects of different visual imagery perspectives and narcissism on motor performance. J Sport Exerc Psychol. 2010;32(4):499–517.PubMedGoogle Scholar
  195. 195.
    Roberts R, Woodman T, Hardy L, et al. Psychological skills do not always help performance: the moderating role of narcissism. J Appl Sport Psychol. 2013;25(3):316–25. doi: 10.1080/10413200.2012.731472.CrossRefGoogle Scholar
  196. 196.
    Wallace HM, Baumeister RF. The performance of narcissists rises and falls with perceived opportunity for glory. J Pers Soc Psychol. 2002;82(5):819–34. doi: 10.1037/0022-3514.82.5.819.PubMedCrossRefGoogle Scholar
  197. 197.
    Wallace HM, Ready CB, Weitenhagen E. Narcissism and task persistence. Self Identity. 2009;8(1):78–93. doi: 10.1080/15298860802194346.CrossRefGoogle Scholar
  198. 198.
    Woodman T, Roberts R, Hardy L, et al. There is an “I” in TEAM: narcissism and social loafing. Res Q Exerc Sport. 2011;82(2):285–90.PubMedGoogle Scholar
  199. 199.
    John OP, Robins RW. Accuracy and bias in self-perception: individual differences in self-enhancement and the role of narcissism. J Pers Soc Psychol. 1994;66(1):206–19. doi: 10.1037//0022-3514.66.1.206.PubMedCrossRefGoogle Scholar
  200. 200.
    Schorer J, Baker J, Lotz S, et al. Influence of early environmental constraints on achievement motivation in talented young handball players. Int J Sport Psychol. 2010;41(1):42–57.Google Scholar
  201. 201.
    Bruner MW, Macdonald DJ, Pickett W, et al. Examination of birthplace and birthdate in world junior ice hockey players. J Sports Sci. 2011;29(12):1337–44. doi: 10.1080/02640414.2011.597419.PubMedCrossRefGoogle Scholar
  202. 202.
    Curtis JE, Birch JS. Size of community of origin and recruitment to professional and Olympic hockey in North America. Sociol Sport J. 1987;4:229–44.Google Scholar
  203. 203.
    Carlson R. The socialization of elite tennis players in Sweden: an analysis of the players’ backgrounds and development. Sociol Sport J. 1988;5:241–56.Google Scholar
  204. 204.
    MacDonald DJ, King J, Cote J, et al. Birthplace effects on the development of female athletic talent. J Sci Med Sport. 2009;12(1):234–7. doi: 10.1016/J.Jsams.2007.05.015.
  205. 205.
    Allen S, Dunman N. Birthplace effect analysis: World Class Programme (WCP) Athletes. London: UK Sport; 2010.Google Scholar
  206. 206.
    Balish S, Côté J. The influence of community on athletic development: an integrated case study. Qual Res Sport Exerc Health. 2013;6(1):98–120. doi: 10.1080/2159676x.2013.766815.CrossRefGoogle Scholar
  207. 207.
    Freeman P, Rees T. How does perceived support lead to better performance? An examination of potential mechanisms. J Appl Sport Psychol. 2009;21(4):429–41. doi: 10.1080/10413200903222913.CrossRefGoogle Scholar
  208. 208.
    Rees T, Freeman P. Social support moderates the relationship between stressors and task performance through self-efficacy. J Soc Clin Psychol. 2009;28(2):244–63. doi: 10.1521/jscp.2009.28.2.244.CrossRefGoogle Scholar
  209. 209.
    Freeman P, Rees T. Perceived social support from team-mates: direct and stress-buffering effects on self-confidence. Eur J Sport Sci. 2010;10(1):59–67. doi: 10.1080/17461390903049998.CrossRefGoogle Scholar
  210. 210.
    Rees T, Hardy L. Matching social support with stressors: effects on factors underlying performance in tennis. Psychol Sport Exerc. 2004;5(3):319–37. doi: 10.1016/S1469-0292(03)00018-9.CrossRefGoogle Scholar
  211. 211.
    Tamminen KA, Holt NL. Adolescent athletes’ learning about coping and the roles of parents and coaches. Psychol Sport Exerc. 2012;13(1):69–79. doi: 10.1016/J.Psychsport.2011.07.006.
  212. 212.
    Jones JM, Jetten J. Recovering from strain and enduring pain: multiple group memberships promote resilience in the face of physical challenges. Soc Psychol Personal Sci. 2011;2(3):239–44. doi: 10.1177/1948550610386806.CrossRefGoogle Scholar
  213. 213.
    Keegan RJ, Harwood CG, Spray CM, et al. A qualitative investigation exploring the motivational climate in early career sports participants: coach, parent and peer influences on sport motivation. Psychol Sport Exerc. 2009;10(3):361–72. doi: 10.1016/j.psychsport.2008.12.003.CrossRefGoogle Scholar
  214. 214.
    Keegan R, Spray C, Harwood C, et al. The motivational atmosphere in youth sport: coach, parent, and peer influences on motivation in specializing sport participants. J Appl Sport Psychol. 2010;22(1):87–105. doi: 10.1080/10413200903421267.CrossRefGoogle Scholar
  215. 215.
    Davis L, Jowett S. Coach–athlete attachment and the quality of the coach–athlete relationship: implications for athletes’ well-being. J Sports Sci. 2014;32(15):1454–64. doi: 10.1080/02640414.2014.898183.PubMedGoogle Scholar
  216. 216.
    Ullrich-French S, Smith AL. Perceptions of relationships with parents and peers in youth sport: independent and combined prediction of motivational outcomes. Psychol Sport Exerc. 2006;7:193–214. doi: 10.1016/j.psychsport.2005.08.006.CrossRefGoogle Scholar
  217. 217.
    Wolfenden LE, Holt NL. Talent development in elite junior tennis: perceptions of players, parents, and coaches. J Appl Sport Psychol. 2005;17(2):108–26. doi: 10.1080/10413200590932416.CrossRefGoogle Scholar
  218. 218.
    Sagar SS, Lavallee D. The developmental origins of fear of failure in adolescent athletes: examining parental practices. Psychol Sport Exerc. 2010;11(3):177–87. doi: 10.1016/J.Psychsport.2010.01.004.
  219. 219.
    Harwood C, Swain ABJ. The development and activation of achievement goals in tennis: I. Understanding the underlying factors. Sport Psychol. 2001;15:319–41.Google Scholar
  220. 220.
    Rees T, Hardy L. An investigation of the social support experiences of high-level sports performers. Sport Psychol. 2000;14(4):327–47.Google Scholar
  221. 221.
    Van Yperen NW. Why some people make it and others do not: identifying psychological factors that predict career success in professional adult soccer. Sport Psychol. 2009;23:317–29.Google Scholar
  222. 222.
    Woodman T, Hardy L. A case study of organizational stress in elite sport. J Appl Sport Psychol. 2001;13(2):207–38. doi: 10.1080/104132001753149892.CrossRefGoogle Scholar
  223. 223.
    Phillips E, Davids K, Renshaw I, et al. The development of fast bowling experts in Australian cricket. Talent Dev Excel. 2010;2(2):137–48.Google Scholar
  224. 224.
    Gould D, Collins K, Lauer L, et al. Coaching life skills through football: a study of award winning high school coaches. J Appl Sport Psychol. 2007;19(1):16–37. doi: 10.1080/10413200601113786.CrossRefGoogle Scholar
  225. 225.
    Gucciardi DF, Gordon S, Dimmock JA, et al. Understanding the coach’s role in the development of mental toughness: perspectives of elite Australian football coaches. J Sports Sci. 2009;27(13):1483–96. doi: 10.1080/02640410903150475.PubMedCrossRefGoogle Scholar
  226. 226.
    Rees T, Freeman P, Bell S, et al. Three generalizability studies of the components of perceived coach support. J Sport Exerc Psychol. 2012;34(2):238–51.PubMedGoogle Scholar
  227. 227.
    Rees T, Salvatore J, Coffee P, et al. Reversing downward performance spirals. J Exp Soc Psychol. 2013;49(3):400–3. doi: 10.1016/J.Jesp.2012.12.013.
  228. 228.
    Güllich A, Emrich E. Evaluation of the support of young athletes in the elite sports system. Eur J Sport Soc. 2006;2:85–108.Google Scholar
  229. 229.
    Güllich A, Emrich E. Individualistic and collectivistic approach in athlete support programmes in the German high-performance sport system. Eur J Sport Soc. 2012;9(4):243–68.Google Scholar
  230. 230.
    Güllich A, Emrich E. Considering long-term sustainability in the development of world class success. Eur J Sport Sci. 2014;14(Suppl 1):S383–97. doi: 10.1080/17461391.2012.706320.PubMedCrossRefGoogle Scholar
  231. 231.
    Schumacher YO, Mroz R, Mueller P, et al. Success in elite cycling: a prospective and retrospective analysis of race results. J Sports Sci. 2006;24(11):1149–56. doi: 10.1080/02640410500457299.PubMedCrossRefGoogle Scholar
  232. 232.
    Barreiros A, Côté J, Fonseca AM. From early to adult sport success: analysing athletes’ progression in national squads. Eur J Sport Sci. 2012;14(sup1):S178–82. doi: 10.1080/17461391.2012.671368.PubMedCrossRefGoogle Scholar
  233. 233.
    Moesch K, Elbe AM, Hauge MLT, et al. Late specialization: the key to success in centimeters, grams, or seconds (cgs) sports. Scand J Med Sci Sports. 2011;21(6):E282–90. doi: 10.1111/J.1600-0838.2010.01280.X.PubMedCrossRefGoogle Scholar
  234. 234.
    Moesch K, Hauge MLT, Wikman JM, et al. Making it to the top in team sports: start later, intensify, and be determined. Talent Dev Excel. 2013;5(2):85–100.Google Scholar
  235. 235.
    Güllich A. Selection, de-selection and progression in German football talent promotion. Eur J Sport Sci. 2014;14(6):530–7. doi: 10.1080/17461391.2013.858371.PubMedCrossRefGoogle Scholar
  236. 236.
    Güllich A. Many roads lead to Rome—developmental paths to Olympic gold in men’s field hockey. Eur J Sport Sci. 2014;14(8):763–71. doi: 10.1080/17461391.2014.905983.PubMedCrossRefGoogle Scholar
  237. 237.
    Güllich A, Emrich E. Investment patterns in the careers of elite athletes in East and West Germany. Eur J Sport Soc. 2013;10(3):191–214.Google Scholar
  238. 238.
    Emrich E, Frohlich M, Klein M, et al. Evaluation of the elite schools of sport empirical findings from an individual and collective point of view. Int Rev Sociol Sport. 2009;44(2–3):151–71. doi: 10.1177/1012690209104797.CrossRefGoogle Scholar
  239. 239.
    van Rens FECA, Elling A, Reijgersberg N. Topsport talent schools in the Netherlands: a retrospective analysis of the effect on performance in sport and education. Int Rev Sociol Sport. 2015;50(1):64–82. doi: 10.1177/1012690212468585.CrossRefGoogle Scholar
  240. 240.
    Gulbin J, Weissensteiner J, Oldenziel K, et al. Patterns of performance development in elite athletes. Eur J Sport Sci. 2013;13(6):605–14. doi: 10.1080/17461391.2012.756542.PubMedCrossRefGoogle Scholar
  241. 241.
    Baker J, Cote J, Abernethy B. Sport-specific practice and the development of expert decision-making in team ball sports. J Appl Sport Psychol. 2003;15(1):12–25. doi: 10.1080/10413200390180035.CrossRefGoogle Scholar
  242. 242.
    Baker J, Cote J, Deakin J. Expertise in ultra-endurance triathletes early sport involvement, training structure, and the theory of deliberate practice. J Appl Sport Psychol. 2005;17(1):64–78. doi: 10.1080/10413200590907577.CrossRefGoogle Scholar
  243. 243.
    Baker J, Cote J, Deakin J. Patterns of early involvement in expert and nonexpert masters triathletes. Res Q Exerc Sport. 2006;77(3):401–7.PubMedCrossRefGoogle Scholar
  244. 244.
    Berry J, Abernethy B, Cote J. The contribution of structured activity and deliberate play to the development of expert perceptual and decision-making skill. J Sport Exerc Psychol. 2008;30(6):685–708.PubMedGoogle Scholar
  245. 245.
    Duffy LJ, Baluch B, Ericsson KA. Dart performance as a function of facets of practice amongst professional and amateur men and women players. Int J Sport Psychol. 2004;35(3):232–45.Google Scholar
  246. 246.
    Ford PR, Ward P, Hodges NJ, et al. The role of deliberate practice and play in career progression in sport: the early engagement hypothesis. High Abil Stud. 2009;20(1):65–75. doi: 10.1080/13598130902860721.CrossRefGoogle Scholar
  247. 247.
    Helsen WF, Hodges NJ, Van Winckel J, et al. The roles of talent, physical precocity and practice in the development of soccer expertise. J Sports Sci. 2000;18(9):727–36.PubMedCrossRefGoogle Scholar
  248. 248.
    Helsen WF, Starkes JL, Hodges NJ. Team sports and the theory of deliberate practice. J Sport Exerc Psychol. 1998;20(1):12–34.Google Scholar
  249. 249.
    Hodge T, Deakin JM. Deliberate practice and expertise in the martial arts: the role of context in motor recall. J Sport Exerc Psychol. 1998;20(3):260–79.Google Scholar
  250. 250.
    Hodges NJ, Kerr T, Starkes JL, et al. Predicting performance times from deliberate practice hours for triathletes and swimmers: what, when, and where is practice important? J Exp Psychol Appl. 2004;10(4):219–37. doi: 10.1037/1076-898x.10.4.219.PubMedCrossRefGoogle Scholar
  251. 251.
    Hodges NJ, Starkes JL. Wrestling with the nature of expertise: a sport specific test of Ericsson, Krampe and Tesch-Romer’s (1993) theory of “deliberate practice”. Int J Sport Psychol. 1996;27(4):400–24.Google Scholar
  252. 252.
    Johnson MB, Castillo Y, Sacks DN, et al. “Hard work beats talent until talent decides to work hard”: coaches’ perspectives regarding differentiating elite and non-elite swimmers. Int J Sports Sci Coach. 2008;3(3):417–30. doi: 10.1260/174795408786238579.CrossRefGoogle Scholar
  253. 253.
    Johnson MB, Tenenbaum G, Edmonds WA. Adaptation to physically and emotionally demanding conditions: the role of deliberate practice. High Abil Stud. 2006;17(1):117–36. doi: 10.1080/13598130600947184.CrossRefGoogle Scholar
  254. 254.
    Law MP, Côté J, Ericsson KA. Characteristics of expert development in rhythmic gymnastics: a retrospective study. Int J Sport Exerc Psychol. 2008;5(1):82–103. doi: 10.1080/1612197x.2008.9671814.CrossRefGoogle Scholar
  255. 255.
    Memmert D, Baker J, Bertsch C. Play and practice in the development of sport-specific creativity in team ball sports. High Abil Stud. 2010;21(1):3–18. doi: 10.1080/13598139.2010.488083.CrossRefGoogle Scholar
  256. 256.
    Starkes JL, Deakin JM, Allard F, et al. Deliberate practice in sports: what is it anyway? In: Ericsson KA, editor. The road to excellence: the acquisition of expert performance in the arts and sciences, sports, and games. Mahwah: Erlbaum; 1996. p. 81–106.Google Scholar
  257. 257.
    Starkes J. The road to expertise: Is practice the only determinant? Int J Sport Psychol. 2000;31(4):431–51.Google Scholar
  258. 258.
    Van Rossum JHA. Deliberate practice and Dutch field hockey: an addendum to Starkes. Int J Sport Psychol. 2000;31:452–60.Google Scholar
  259. 259.
    Ward P, Hodges NJ, Williams AM, et al. Deliberate practice and expert performance: defining the path to excellence. In: Williams AM, Hodges NJ, editors. Skill acquisition in sport: research, theory and practice. London: Routledge; 2004. p. 231–58.Google Scholar
  260. 260.
    Weissensteiner J, Abernethy B, Farrow D, et al. The development of anticipation: a cross-sectional examination of the practice experiences contributing to skill in cricket batting. J Sport Exerc Psychol. 2008;30(6):663–84.PubMedGoogle Scholar
  261. 261.
    Simon HA, Chase WG. Skill in chess. Am Sci. 1973;61(4):394–403.Google Scholar
  262. 262.
    Ericsson KA, Krampe RT, Tesch-Romer C. The role of deliberate practice in the acquisition of expert performance. Psychol Rev. 1993;100(3):363–406. doi: 10.1037/0033-295x.100.3.363.CrossRefGoogle Scholar
  263. 263.
    Ericsson KA. Training history, deliberate practice and elite sports performance: an analysis in response to Tucker and Collins review—what makes champions? Br J Sports Med. 2013;47:533–5. doi: 10.1136/bjsports-2012-091767.PubMedCrossRefGoogle Scholar
  264. 264.
    Güllich A. Training–Support–Success: control-related assumptions and empirical findings. Saarbrücken: University of the Saarland; 2007 [in German].Google Scholar
  265. 265.
    Bullock N, Gulbin JP, Martin DT, et al. Talent identification and deliberate programming in skeleton: ice novice to Winter Olympian in 14 months. J Sports Sci. 2009;27(4):397–404. doi: 10.1080/02640410802549751.PubMedCrossRefGoogle Scholar
  266. 266.
    Hornig M, Aust F, Güllich A. Practice and play in the development of German top-level professional football players. Eur J Sport Sci. 2014:1–10. doi: 10.1080/17461391.2014.982204.
  267. 267.
    Ford PR, Yates I, Williams AM. An analysis of practice activities and instructional behaviours used by youth soccer coaches during practice: exploring the link between science and application. J Sports Sci. 2010;28(5):483–95. doi: 10.1080/02640410903582750.PubMedCrossRefGoogle Scholar
  268. 268.
    Eccles JC. Possible synaptic mechanism subserving learning. In: Karczmar AG, Eccles JC, editors. Brain and human behavior. New York: Springer-Verlag; 1972. p. 39–61.CrossRefGoogle Scholar
  269. 269.
    Maxwell JP, Masters RSW, Eves FF. From novice to no know-how: a longitudinal study of implicit motor learning. J Sports Sci. 2000;18(2):111–20. doi: 10.1080/026404100365180.PubMedCrossRefGoogle Scholar
  270. 270.
    Soberlak P, Cote J. The developmental activities of elite ice hockey players. J Appl Sport Psychol. 2003;15(1):41–9. doi: 10.1080/10413200390180053.CrossRefGoogle Scholar
  271. 271.
    Bridge MW, Toms MR. The specialising or sampling debate: a retrospective analysis of adolescent sports participation in the UK. J Sports Sci. 2013;31(1):87–96. doi: 10.1080/02640414.2012.721560.PubMedCrossRefGoogle Scholar
  272. 272.
    Cote J, Baker J, Abernethy B. From play to practice: a developmental framework for the acquisition of expertise in team sport. In: Starkes JL, Ericsson KA, editors. Expert performance in sports: advances in research on sport expertise. Champaign: Human Kinetics; 2003. p. 89–113.Google Scholar
  273. 273.
    Deakin JM, Cobley S. An examination of the practice environments in figure skating and volleyball: a search for deliberate practice. In: Starkes JL, Ericsson KA, editors. Expert performance in sports: advances in research on sport expertise. Champaign: Human Kinetics; 2003. p. 90–113.Google Scholar
  274. 274.
    Hill GM. Youth sport participation of professional baseball players. Sociol Sport J. 1993;10(1):107–14.Google Scholar
  275. 275.
    Fraser-Thomas J, Cote J, Deakin J. Examining adolescent sport dropout and prolonged engagement from a developmental perspective. J Appl Sport Psychol. 2008;20(3):318–33. doi: 10.1080/10413200802163549.CrossRefGoogle Scholar
  276. 276.
    Gould D, Tuffey S, Udry E, et al. Burnout in competitive junior tennis players: 1. A quantitative psychological assessment. Sport Psychol. 1996;10(4):322–40.Google Scholar
  277. 277.
    Strachan L, Cote J, Deakin J. “Specializers” versus “samplers” in youth sport: comparing experiences and outcomes. Sport Psychol. 2009;23(1):77–92.Google Scholar
  278. 278.
    Wall M, Côté J. Developmental activities that lead to dropout and investment in sport. Phys Ed Sport Pedagogy. 2007;12(1):77–87. doi: 10.1080/17408980601060358.CrossRefGoogle Scholar
  279. 279.
    Zibung M, Conzelmann A. The role of specialisation in the promotion of young football talents: a person-oriented study. Eur J Sport Sci. 2013;13(5):452–60. doi: 10.1080/17461391.2012.749947.PubMedCrossRefGoogle Scholar
  280. 280.
    Kay T. Sporting excellence: a family affair? Eur Phys Educ Rev. 2000;6(2):151–69. doi: 10.1177/1356336x000062004.CrossRefGoogle Scholar
  281. 281.
    Kirk D. Physical education, youth sport and lifelong participation: the importance of early learning experiences. Eur Phy Educ Rev. 2005;11(3):239–55. doi: 10.1177/1356336x05056649.CrossRefGoogle Scholar
  282. 282.
    Xiao Lin Yang, Telama R, Laakso L. Parents’ physical activity, socioeconomic status and education as predictors of physical activity and sport among children and youths: a 12-year follow-up study. Int Rev Sociol Sport. 1996;31(3):273–91. doi: 10.1177/101269029603100304.
  283. 283.
    Williams AM, Hodges NJ. Practice, instruction and skill acquisition in soccer: challenging tradition. J Sports Sci. 2005;23(6):637–50. doi: 10.1080/02640410400021328.PubMedCrossRefGoogle Scholar
  284. 284.
    Fischer S, Hallschmid M, Elsner AL, et al. Sleep forms memory for finger skills. Proc Natl Acad Sci. 2002;99(18):11987–91. doi: 10.1073/Pnas.182178199.PubMedPubMedCentralCrossRefGoogle Scholar
  285. 285.
    Kuriyama K, Stickgold R, Walker MP. Sleep-dependent learning and motor-skill complexity. Learn Mem. 2004;11(6):705–13. doi: 10.1101/Lm.76304.PubMedPubMedCentralCrossRefGoogle Scholar
  286. 286.
    Walker MP, Brakefield T, Morgan A, et al. Practice with sleep makes perfect: sleep-dependent motor skill learning. Neuron. 2002;35(1):205–11. doi: 10.1016/S0896-6273(02)00746-8.PubMedCrossRefGoogle Scholar
  287. 287.
    Walker MP, Brakefield T, Seidman J, et al. Sleep and the time course of motor skill learning. Learn Mem. 2003;10(4):275–84. doi: 10.1101/Lm.58503.PubMedPubMedCentralCrossRefGoogle Scholar
  288. 288.
    Eysenck HJ, Frith CD. Reminiscence, motivation and personality: a case study in experimental psychology. New York: Plenum Press; 1977.CrossRefGoogle Scholar
  289. 289.
    Woodman T, Hardy L, Barlow M, et al. Motives for participation in prolonged engagement high-risk sports: An agentic emotion regulation perspective. Psychol Sport Exerc. 2010;11(5):345–52. doi: 10.1016/J.Psychsport.2010.04.002.
  290. 290.
    Barlow M, Woodman T, Hardy L. Great expectations: different high-risk activities satisfy different motives. J Pers Soc Psychol. 2013;105(3):458–75. doi: 10.1037/A0033542.PubMedCrossRefGoogle Scholar
  291. 291.
    Gogarty P, Williamson I. Winning at all costs: Sporting gods and their demons. JR Books Limited; 2009.Google Scholar
  292. 292.
    Collins D, MacNamara A. The rocky road to the top: why talent needs trauma. Sports Med. 2012;42(11):907–14. doi: 10.2165/11635140-000000000-00000.PubMedCrossRefGoogle Scholar
  293. 293.
    Howells K, Fletcher D. Sink or swim: adversity- and growth-related experiences in Olympic swimming champions. Psychol Sport Exerc. 2015;16(Part 3):37–48. doi: 10.1016/j.psychsport.2014.08.004.
  294. 294.
    McCarthy N, Collins D. Initial identification & selection bias versus the eventual confirmation of talent: evidence for the benefits of a rocky road? J Sports Sci. 2014;32(17):1604–10. doi: 10.1080/02640414.2014.908322.PubMedCrossRefGoogle Scholar
  295. 295.
    Tamminen KA, Holt NL, Neely KC. Exploring adversity and the potential for growth among elite female athletes. Psychol Sport Exerc. 2013;14(1):28–36. doi: 10.1016/j.psychsport.2012.07.002.CrossRefGoogle Scholar
  296. 296.
    Sarkar M, Fletcher D, Brown DJ. What doesn’t kill me…: adversity-related experiences are vital in the development of superior Olympic performance. J Sci Med Sport. 2015;18(4):475–9. doi: 10.1016/j.jsams.2014.06.010.PubMedCrossRefGoogle Scholar

Copyright information

© The Author(s) 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of Sport and Physical Activity, Faculty of ManagementBournemouth UniversityPooleUK
  2. 2.Sport, Health and Exercise Sciences, Bangor UniversityGwyneddUK
  3. 3.Department of Sport ScienceUniversity of KaiserslauternKaiserslauternGermany
  4. 4.School of Human Movement and Nutrition Sciences, Faculty of Health and Behavioral SciencesThe University of QueenslandSt LuciaAustralia
  5. 5.School of Kinesiology and Health Studies, SKHS Building 28 Division StreetQueen’s UniversityKingstonCanada
  6. 6.School of Life and Medical Sciences, University College LondonLondonUK
  7. 7.UK SportLondonUK

Personalised recommendations