Let's stop trying to identify sport talent and start developing it
In 1985 Benjamin Bloom studied young experts in art, sport, and science to find out what made these individuals exceptional and what they did to enhance their talents. Bloom's purpose was to find out what set talented youth apart from their peers, but his findings changed the way we think about talent, what it is, and where it comes from. Before the Bloom study talent was generally believed to be an innate ability, something one was born with and something that was easy to spot even from an early age. But Bloom's results indicated just the opposite: Talent can be learned.
Bloom assumed that talented teenagers must have been seen as gifted in some way when they were younger, thus he wanted to find out how they exhibited their early talents. But the teens Bloom studied didn't exhibit any skills at younger ages that anyone regarded as exceptional. Instead what set these teens apart from others is that they seemed to practice a lot more than their peers. But it wasn't just the practice that mattered. It was the way they practiced and the conditions under which it took place that combined to produce real talent. Later, in an interview, Bloom noted that "We were looking for exceptional kids, and what we found were exceptional conditions."
The notion that talent might depend on environmental components, rather than natural gifts, has shaped almost all subsequent studies of talent and expertise. Bloom introduced the term deliberate practice which became the basis of Ericsson's 10-year-rule, and a focus on creating environments where talent grows can be found in many popular books such as The Talent Code and Outliers. Creating talent nurturing environments though is not as easy as it sounds. Sport organizations struggle with this idea because, regardless of the evidence, sport talent is still seen by many as being somewhat innate; and because national governing bodies (NGBs) simply haven't figured out how to institutionalize the idea of exceptional environments yet.
Schemes that try to identify early sport talent backfire since their main effect, albeit not the intended one, is to eliminate youngsters from sport. But talent identification programs persist probably because identifying talent seems easier and more straightforward than the concept of developing it. Here's the bottom line though: We don't know how to identify talent (or if that's even possible) but we do know how to develop it. So why not do that?
Istvan Balyi, one of the architects of the long-term athlete development framework, compares identifying talent to looking for a black cat in a dark, windowless room. We think the cat is there but we can't see it, and if we find it we do so only by accident. We think talent exists but so far we have not come up with a way to find it. And numerous programs notwithstanding we don't even know how to look for it. Developing talent is a much more sensible tactic and one which we know at least a little bit about.
Attempting to identify young talent early demonstrates a mismatch between what we know and what we do. Instead of looking for exceptional young athletes we should heed Bloom and work at creating exceptional conditions where talent can be developed. Sport organizations and NGBs have a higher responsibility not only to the athletes involved but also to the public who usually fund the organization's programs either through direct subsidy or by the provision of public facilities.
Creating programs that treat all young athletes the same by providing instruction, practice opportunities, good coaching advice, and taking a long-term developmental approach to youth sport is the best way for NGBs to create Bloom's exceptional conditions.
But perhaps the most important aspect of youth sport development is one Bloom does not mention: Patience. Talent identification conveys a sense of immediacy that gives coaches and administrators a feeling of doing something right now, while developmental programs occur over the long-term. It's easy to see how short-term identification schemes seem more productive but over time long-term development programs will produce better results.
Bill Price (email@example.com) is the owner and Chief Data Scientist at Sportkid Metrics.