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A new paper just came out in Science, one of the most prestigious scientific journals in the world, and it raises a counterintuitive possibility that getting ahead may actually reduce your chances of becoming truly great.
The paper analyzed tens of thousands of people across sports, music, science, and chess, all asking a deceptively simple question. Who actually becomes world class? And the headline is one that some people might find deeply uncomfortable, maybe even hard to believe. The people who are the very best performers as kids are almost never the same as those who end up being the best as adults.
Now, what's important here is not that any single study in this paper is new. If you've read Range, most of this evidence will feel familiar. What is new is the scale and the synthesis and the fact that it's published in one of the two most prestigious scientific journals in the world. This paper pulls together results across domains, across decades, and across nearly 35,000 elite performers. And when you see those results side by side, a very consistent pattern emerges. That pattern challenges one of our most common assumptions about talent and success.
I'm David Epstein, author of Range, The Sports Gene, and Inside the Box. I've spent over a decade investigating how elite performers develop. And what I've learned challenges one of our most common assumptions about success. So, let me get more specific about what the research actually shows.
Among already high-erforming adults, the ones who reach the very top tend to have developed more slowly, more broadly, and less narrowly early on than their peers. This is not a comparison between experts and beginners. Let's be clear. It's a comparison within high achieving populations. Very good adults versus truly world-class adults. And when you make that comparison, early dominance turns out to be a surprisingly poor predictor of ultimate greatness. Not only that, but some of the predictors of elite youth performance turn out to be the opposite of those that predict elite adult performance.
Now, when you dig into the data, the pattern gets even more interesting. The paper identifies three consistent reversals. So that's three things that flip when you compare what predicts early success versus what predicts reaching the very highest level as an adult.
First, early performance. Early success predicts more early success. That part makes sense. But among high performing adults, early dominance is actually a negative predictor of reaching the highest level later on. In other words, among already excellent adults, the very best were often not the strongest early performers.
Second, rate of early progress. Fast early improvement predicts junior stardom. Kids who accelerate quickly early on become the prodigies that everyone notices. But adult worldclass performers tend to show more gradual early progress. Rapid early acceleration is common among prodigies. It's also rare among those who ultimately reach the very top as adults. And that pattern holds across sports and science and music.
The new paper also cites research that shows that people who won the Nobel Prize actually progress more slowly than their peers early on in their careers. They get tenure later. They publish less frequently in their early years. And it seems to be because they're more interdisiplinary early on, building what I would call range. They're broader early on, both in what they study and in their work. And they seem to get a little bit docked for that early on, but obviously not when they win the Nobel Prize. That's actually one of the themes of my book Range, that what's best for short-term development is often at odds for what's best in the long term.
Third, specialization. Early specialization predicts early excellence. If you want to make the best 12-year-old, hyper specialized practice is the way to go, but broader, more multidisciplinary early experience predicts adult world-class performance, even though it often hurts early rankings. And this pattern shows up again across sports, music, and science.
This research is often misinterpreted. So, it's worth being really clear about what it does not mean. It does not mean that practice doesn't matter. It does not mean that early effort is wasted. And it does not mean that world-class performers were bad early on. Most of the eventual world-class adults in these studies practiced a lot and often performed above average early. The difference isn't effort. It's the shape of development.
One way to think about this is that early success often reflects optimization for the current environment. You're being groomed to win right now. But long-term greatness that depends on adaptability, on building what the authors of this paper describe as learning capital, a foundation that expands the range of problems you can solve later and reduces the risk of locking into the wrong path too early.
So, if it's not about effort, and world-class performers aren't bad early on, then why do we see this pattern again and again? There are three buckets I've been using for years now to explain this, all of which the authors of the new study highlight, and they translate pretty well from sports to the rest of the world.
Bucket one, match quality. Match quality is a term economists use to describe the degree of fit between the work someone does and who they are, their abilities and their interests. Your insight into yourself is constrained by your roster of previous experiences. When you get to try different things, you get information signals about your interests and your abilities, and that helps you pick a better match. Match quality turns out to be enormously important. If we treated careers like dating, we'd never pressure people to settle down so quickly. The earlier you're forced to pick a narrow path, the more likely you put the wrong person in the wrong spot.
Bucket two, generalized learning advantage. This holds for both physical and cognitive skills. When you have to solve problems across a bunch of different types of domains instead of just learning how to execute procedures to solve a certain type of problem, you actually build general learning models that are more flexible. Sometimes I make an analogy, and it's not perfect, but it helps to kids who grow up bilingual. They'll actually show a bit of a deficit early on in certain language skills, like their reading and vocabulary skills. They might lag a little behind their monolingual peers. But not only do they catch up, so there's no deficit later on as adults, they then have an advantage for learning any subsequent language. And this has been shown even in studies where scientists made up a fake language that participants had to try to learn. So it's like they have a slower start, but they have a broader beginning. They're learning across these contexts and then it seems to give them a generalized learning advantage for anything going forward. It's building a more flexible brain. And there's similar research in sports showing that if someone played three different so-called attacking sports, that means sports where you're having to judge bodies or fastoving objects, then it takes them fewer hours to reach a high level in a new skill.
Bucket three, resistance to injury. And in this case, I mean both psychological and physical injury. Let me give you a physical example from sports. I spent some time with one of Cirus Sole's physiologists when I was reporting Range and The Sports Gene. They have exolympic athletes and they've studied them with all sorts of technology like biometric vests they can wear in training. They've got insane data. And they decided while they were looking at some of the research on the advantages of movement variability to have some of the performers that they were grooming learn the basics of three other performers skills. Not because they were going to perform them in a show they weren't, but because they wanted to see if it would make them more durable. Cirtole is a Canadian company and they measure their injury rates next to Canadian gymnastics. And the physiologist told me that they found it reduced their injury rates by a third. That is insane. It's an enormous reduction. There are all kinds of reasons I could speculate on why that works. Strengthening support muscles is one possibility. Other research has shown that increasing movement variability is protective. And there's also a protective effect of just general body awareness that comes from diversifying. This might be one reason, for example, that dancers have unusually low rates of ACL injuries compared to people in other vigorous physical activities. We don't know exactly what's going on for sure, but it works. And that's the important part. And I think we can make an analogy from that to psychological burnout, psychological injury. When people pick a better fit for themselves, have tried more things, have broader skills, broader interests, they're just more resistant to burnout.
Now, here's where this gets really practical because this creates a major problem for how we identify and develop talent. Many talent systems are designed to identify early stars and accelerate them. But this paper suggests that the traits that produce early wins are often not the traits that predict sustained excellence. That creates a tension between selection and development, between optimizing for early performance and optimizing for long-term potential. And when institutions confuse the two, they risk selecting for the wrong qualities.
Let me give you a concrete example of what this looks like in practice. There's a famous study from the 1980s that looked at top junior tennis players in Sweden. Some of them went on to become truly world-class professionals, top 15 in the world. Others were top juniors, but never made it at the elite level. And what they found was in many ways similar to this new science paper. The kids who looked the best early on, they didn't reliably end up being the best later on. At age 12 to 14, the future elites and a control group of non- elites were basically indistinguishable. Then their path diverged after puberty. Some kids who looked like world beaters early stalled out. Some kids who were good but not obviously special were the ones who rose to the top. And one of the things the researchers talked about was what they called a permissive versus restrictive environment. The future elite players grew up in smaller clubs, played lots of different sports, trained less intensely early on and only specialized later. Their environment was flexible, social, lower pressure at least early on. The others trained more, specialized earlier, and felt more pressure in large competitive clubs. The researchers described those settings as more restrictive and less stimulated. In fact, the kids who trained more and specialized earlier were less likely to become world class. In other words, the future champions had range first and then specialized. The early specialists, they mostly plateaued or burned out. Lots of those early stars would just quit. Others stalled out as peers passed them by. It was especially true for the girls. Girls who were early standouts were brought into those more restrictive environments and were more likely to drop out as soon as their early success faded.
That same distinction between early stars and eventual champions, it shows up in how smart organizations actually structure their development systems. When the UK was awarded the Olympics for 2012, they hired a woman named Chelsea Wir who had helped Australia when they hosted the Olympics set up their performance pathways, basically the developmental pipelines for athletes. And I spent some time talking with her and I remember she told me about how they split their system and it helped lead to an exceptional performance in 2012. They created pathways for what she called fast risers and also for slow bakers. Fast risers meaning the kids who everyone thought were going to be stars right away, the prodigies, although often really someone who just physically developed early in many cases. And the slow bakers, they obviously came along more slowly. And I remember having a group of UK coaches in the room and them saying that most of what they called the serial champions. So that was athletes who won not just a gold medal or world championship, but multiple golds or world titles were coming from the slow baker category. There were some of both for sure, but usually people put all their attention on the fast risers, right? The people you identify really early that just look like prodigies. And yet what they were seeing again and again was even though the systems weren't designed for them, it was the slow bakers who were ending up being the repetitive champions. And so one of their approaches leading up to 2012 was to actually build a system to help with slow bakers, which mostly just meant, hey, let's not deselect people so early on that they can't even pull themselves up by their own bootstraps and come back later. And it paid huge dividends.
And if you want to see the slow Baker path taken to an extreme, let me tell you about Helen Glover. When this science paper came out, BBC Radio 4 in England called me and put me on a program with Helen Glover. Helen didn't start rowing until she was in her 20s. Had literally not picked up an ore. She was one of the people in this British talent transfer program where they recruited people to try new stuff and see if they could find a fit. In her case, they were looking for people with certain body types. She went on to win two gold medals and in one event was undefeated for five straight years. Five years without a loss. She was the most dominant athlete in the world for a while in her sport, maybe in any sport. That's the slowb Baker path taken to an extreme. And that's obviously not typical, but it's an example that suggests how much undiscovered talent there might really be if we just encouraged people to try more stuff in search of better fit.
So, if early success isn't the right thing to optimize for, what should we optimize for instead? Building the toolbox, going where you can learn the most early on in development, identifying strengths, weaknesses, and interests is really important. You're optimizing for building a foundation that's going to propel you forever rather than going through development as quickly as you possibly can.
There's also this pervasive finding in research called the fade out effect where early advantages tend to disappear. And it's partly because the easiest way to get an early advantage is to focus early on what scientists call closed skills. Basically, things that everybody's going to learn eventually. It's like teaching a kid to walk early. Fine, great. But everyone's going to learn it and it doesn't lead to a lasting advantage. So, the fade out is actually just a catch-up of other people. You'd be better off spending that time sampling and looking for fit and broadening the toolbox that will serve you later rather than rushing to get a short-term advantage.
So, here's the billion-dollar question. What's the difference between developing broadly and just being unfocused? In many cases, it comes down to this. Are you using each of those experiences in what's called a self-regulated learning cycle? This behavior shows up in people who consistently get off of performance plateaus. They are whether implicitly or explicitly in this constant cycle of what am I trying to do? Here's an experiment. I'm going to try to work on that. Here's the way that I'm going to evaluate that experiment. and then they use that to move to the next experiment. Rinse and repeat. You don't necessarily have to be on the right track in development, but if you have no system for learning from what you're doing, then you're just pinballing around aimlessly and hoping for luck.
So, I think it's more like Harvard's Darkhorse project, which looked at how people find fulfilling work. Those who did were systematic. They didn't sit around saying, "Here's who's younger than me and has more than me." They said, "Here are my skills and interests right now and here are my opportunities and I'm going to try this one and maybe a year from now I'll change because I will have learned something about myself." And then they do it and ask, "What have I learned from this experience or this trial? And how does that inform the next pivot?" And they just kept doing that until they found a place where they uniquely could succeed. When you do that, you'll necessarily be zigzagging around and building a toolbox. But that's different than just being unfocused and hoping for luck and waiting for things to come.
Since this new science study looked at the difference between good and absolutely outstanding performers, we shouldn't conclude that early exposure is bad or early interest or early enthusiasm. We should be cautious about extrapolating too broadly because again, this is comparing within people who were good at some point. It's not a total comparison of the general population. Some people might argue that making someone good as a kid was a good experience for them and that was a really great outcome, maybe. But at the same time, I think it's abundantly clear that the way you make the best 12-year-old is not the way you make the best 25 or 35year-old.
This is another brick in this now huge wall of research showing that there's a trade-off between long-term and short-term performance. Because the way to get the best head start is to focus narrowly and intensely. And that's just not the way to build the best base for long-term development. If you design selection systems just around early performance, you'll build systems that manufacture early performance, often at the expense of truly exceptional performance later. You don't want to confuse early speed with the ultimate ceiling.
This doesn't mean you should suck early on or that you should totally ignore a domain you might be interested in. Early exposure is great, and most of the world-class adults in these studies practiced a lot. They just did it differently. The people who become truly exceptional often take longer to get there. And that's not despite their broader path. It's because of it.
If you like this video and you want to hear more from me, check out my free newsletter, Range Widly, where I write about cutting edge science and interview best-selling authors. There's a link in the description to subscribe. Thanks so much for watching. I'll see you in the next video.