For the last two years, I´ve worked in talent identification for the Olympic sport of weightlifting and my main task was to find talented athletes and integrate them into a high-performance environment. I came across a lot of obstacles due to the fact that weightlifting is an Olympic sport, where (clean!) athletes reach their peak in their late 20s or even older, but the sports system I´m in forces me to search for talented athletes as early as possible because otherwise they will be recruited by other sports. Unfortunately, we do not really have a multisport participation approach in the German youth sports system.
I will try to give you an overview of the challenges that talent ID comes with and what approach I prefer.
Talent identification is designed to identify young athletes, who have extraordinary potential for success in senior elite sport. Many sports clubs and coaches want to spot talented athletes as early as possible, select and recruit them into talent development programs. The purpose of putting young athletes into talent development programs is mainly to increase their potential and ability for example through additional competition, game time and training opportunities, effective time management, high-profile coaching, scientific and medical supervision, and many more reasons. This actually sounds like a great idea and pretty effective, but the outcome of most talent development programs is rather disappointing. So, the effectiveness of talent ID is questioned a lot.
First of all, the definition of “talent” is important for the discussion of how to assess and identify talent. The definition of the term depends on the approach to the phenomenon of talent in talent research (Hohmann & Seidel, 2017). The prospective talent approach in talent research refers to athletes who are expected to achieve top performances in the future, whereas the retrospective expertise approach also includes adult athletes who have already achieved top performances and the talent assessment is carried out retrospectively (Heller, 2002; Höner et al., 2020). The retrospective approach attempts to identify performance factors and their degrees of expression in successful high-performance athletes and compare them with less successful athletes or junior athletes in order to determine talent criteria retrospectively. In a study, Gould, Dieffenbach & Moffett (2002) examined psychological characteristics and their development of Olympic champions from different sports and discussed them in the context of talent assessment and development. They came to the conclusion that each individual Olympic champion is characterized by individual psychological traits and that the emergence and development of these traits are based on a multitude of internal and external influencing factors such as the environment, the coach, or the family.
Due to the multitude of performance factors and influencing factors, as well as change processes in the course of an athlete's development, it is recommended that talent assessment is not carried out narrowly and statically with one-time data collection, but broadly and dynamically with several, comparable assessments (Abbott & Collins, 2004; Den Hartigh et al., 2018). In young athletes changes present in physical, social, as well as psychological domains, thus the sole use of motor skills as a talent predictor proves unreliable both before and during puberty (Hohmann & Seidel, 2017). Therefore, psychological and social resources should also be taken into consideration for talent ID. According to Hohmann (2009), both the development of the performance factors and the performance in sport-specific competition can be used as a separate talent criterion for the rate of development. In this context, the question arises as to the predictive relevance of talent criteria and their dependence on environmental conditions and change processes in the development of an athlete.
Höner et al. (2020) assume that talent predictors are fundamentally dependent on the developmental phase of the athlete and can also be weighted differently depending on the degree of demands placed on the athletes. For example, the psychological resource of stress management could be less relevant in children than in college athletes. In addition, talent predictors could be compensated for, since different performance factors are relevant for athletic performance in the overall view, and deficits in individual areas could be compensated (Seidel & Hohmann, 1999; Höner et al., 2020). Can a lack of speed be compensated with outstanding agility in hockey? Can a lack of physical abilities be compensated with extraordinary willpower and concentration? Clear empirical findings on the compensability of performance factors through a high degree of other performance factors, especially psychological resources, are still lacking. In sports practice, as well as in talent research, the main question is whether physical deficits can possibly be compensated by a high degree of psychosocial resources. Further research is needed in this area, including sport-specific research. This also leads to the last assumption of Höner et al. (2020), the group-specificity of talent predictors. According to this, talent criteria depend on the sport, the performance level of the athletes, and their age, and talent screening should take this into account.
So, how do most talent ID programs define and assess talent? In a systematic review of talent ID in sport, Johnston et al. (2018) looked at talent ID programs across many different sports and discovered quite a few issues. The study showed that most talent ID programs focus mainly on creating physical profiles of young athletes and therefore are pretty unidimensional. Talent ID programs lack criteria like anthropometrics, biological age, psychological factors like resilience, coping, self-efficacy, or confidence even though evidence highlights the importance of these factors in the development of elite athletes. Team sports have a tendency to deconstruct performance tasks e.g. agility and break them down into smaller subphases, which are then used as a talent test. For example, agility is very important in football, rugby or basketball. A number of talent ID programs tried to isolate agility and tested an unspecific, simple agility drill. Question is, does a good time at some simple agility test really tell us if that boy or girl is going to be a good football player? Probably not. Football, rugby, and basketball are dynamic and interactive and require decision making, so this deconstruction of a parameter like agility does not really represent the demands of competition and therefore, is also not very useful for talent ID.
In fact, talent assessments should be done as close as possible to the demands of the sport to be at least a little useful. But this leads to the next problem: If a talent ID program is pretty close to the competition demands, then coaches in clubs and wherever tend to specialize young athletes as early as possible to get them into a development program. Am I a supporter of early specialization? Definitely not. Read why in my blog about early specialization.
What are actually the perspectives of talent ID? As you might have noticed. I´ve come across a few problems that I´m still not sure how to address. On the one hand the sports system kind of requires talent ID, but our approaches are not compatible with the research on long-term athlete development. The only option that I can support is creating a more multidimensional and dynamic talent ID program where the focus is on progression with a variety of different tests close to the performance demands of the sport to track progression. It is important to consider many more factors like training age, biological age, multisport experience, training environment and include them in the assessment of a youth athlete. The long-term potential of athletes should be given a higher priority than their current state. Working in talent ID and doing these assessments and maybe also decide if the young athlete makes it into an academy or elite sports school requires a lot of responsibility because we’re given the power to make a decision about an athlete’s dreams, deciding whether they’re going to enter elite level sports. Rejection and not making it into a team or not making it into an academy or a youth national team can decide if an athlete will go on with the sport or not and we have experienced in the Olympic sports, that we have a huge dropout rate at the age of 16,17, 18 when they are on a plateau due to physical changes and don´t meet the competition standards we set or have other struggles in life. But this is another topic and I want to finish here.
If you´ve made other experiences with talent ID, I´m very happy to hear about them.
Resources
Abbott, A., & Collins, D. (2004). Eliminating the dichotomy between theory and practice in talent identification and development: Considering the role of psychology. Journal of Sports Sciences, 22, 395–408.
Den Hartigh, R. J., Niessen, A. S. M., Frencken, W. G., & Meijer, R. R. (2018). Selection procedures in sports: Improving predictions of athletes’ future performance. European journal of sport science, 18(9), 1191-1198.
Gould, D., Dieffenbach, K., & Moffett, A. (2002). Psychological characteristics and their development in Olympic champions. Journal of Applied Sport Psychology, 14(3), 172-204.
Heller, K. A. (2002). Theoretische Ansätze und empirische Befunde zur Hochbegabungs- und Expertiseforschung unter besonderer Berücksichtigung sportlicher Talente. In A. Hohmann, D. Wick, & K. Carl (Hrsg.), Talent im Sport (S. 52–66). Schorndorf: Hofmann.
Höner, O., Larkin, P., Leber, T. & Feichtinger, P. (2020). Talentauswahl und -entwicklung im Sport. In J. Schüler, M. Wegner, & H. Plessner (Hrsg.), Sportpsychologie: Grundlagen und Anwendung (S. 500-526). Springer.
Hohmann, A. (2009). Entwicklung sportlicher Talente an sportbetonten Schulen: Schwimmen, Leichtathletik, Handball. Petersberg: Imhof.
Hohmann, A., & Seidel, I. (2017). Talententwicklung: Talentdiagnose und Talentförderung. Handbuch Trainingswissenschaft - Trainingslehre, S. 305-317; Lit.-Verz.: S. 459-515.