Should we predict development?
“Did you know the average age of medalist is 26 in running events, but in the throwing events it’s much older?”
That’s how the conversation started, before progressing towards how we needed to center our development and funding models on this data. The underlying message was a simple one, we can predict performance using past data. Everyone has a path.
It’s not the only time I’ve heard this conversation, and yes, it has meaning, but whenever I hear people going all in towards this towards of predictive nature, I step back and wonder. Does the data really help, or are we simply after that feeling of comfort and certainty that data provides. After all, it’s a lot easier to justify my choice (and perhaps job) if I state “the model predicts X” versus “I have a hunch based on experience.”
There’s growing trend within track, and sports in general, to defer to statistical/algorithmic decision-making. Whether it is in terms of countries funding athletes, companies choosing athletes, or coaches deciding “potential.” We all are falling into the allusion of certainty. Yet, few of us–myself included– even have the statistical expertise to realize what we are doing. Maybe in the sport of baseball, where former statistical experts are hired for nice sums, but in track, we are almost always amateurs doing an experts job. But the main problem doesn’t lie in knowing statistics or not, it lies in the assumptions we don’t know.
The performance path is often built on a simple statistical look at how athletes progress. Average out the data, see when athletes reach their “peak” or personal best, and that becomes the developmental model.
Yet, behind this simple statistical model are a host of confounding variables and assumptions.
Take for example the following:
Like it or not, the latest research shows a relatively large percentage of professional athletes are on performance enhancing drugs. For those who turn to the dark side, we have no idea when they started, or how it may impact their development. Anecdotally, we know that it can extend careers and provide breakthroughs. Maybe a normal athlete hits a point of plateau and stagnation, while another athlete chooses this moment to try the juice to break through.
Psychology and Motivation
Prodigies often reach their peaks early not because of physical maturity but because their motivation for sport has been hijacked at a young age. They aren’t allowed to experience the normal developmental route and learn to deal with success and failure. Instead, they are thrust onto the world stage with the physical tools to handle it, but not necessarily the psychological ones.
In the world of running, where support is hard to come by, we often lose athletes at a young age not due to inability to improve, but due to the financial risk of continuing. Should they delay real life and potential financial stability of an actual job, for the continual chasing of the dream? Alternatively, if you make millions of dollars, or are an East African who wins a couple marathons that allow you to set up your family for life, the incentive to continue can dwindle.
The Real Path…
Look no further than the research I conducted on world-class 800-meter women. Despite controlling for “drugs” as best as I could, the athletes reached their peak from anywhere from 18 to 36. Yes, on average, the development looks nice and progressive to their peak.
But on an individual level, it’s all over the map.
The Trickiness of Potential and Development:
Who would have predicted a late 20’s also-ran at the world stage would become dominant at the world stage? It’s happened in running and cycling. Is that normal progression or are we missing a variable that may help explain? When using past data, we don’t know the details and variable we are missing.
Or how about two high school phenoms of the who attended the same University, Nick Willis and Alan Webb? Both have had tremendous careers in very different ways, ending up with similar 1,500m/mile PR’s, set almost a decade apart, despite being about the same age.
Can all of that be attributed to coaching differences? That’s the tempting answer. But that would be an armchair quarterback type of call. The reality is it is just as likely that it could have been physical development and personality.
If a coaches knowledge of smart progression and long-term development was what separated out promising athletes peaked in their early years and who had a long successful career, then we could see it in the coaches records. Yet, some of the same coaches who we laud for masterfully progressing an athlete have a pile of highly touted athletes who reached their peak during their early years. Did the coach only apply his Long-Term Development Plan to only a select few athletes?
Reality is much more difficult than the narratives that give us comfort that this incredibly complex process of human development is controllable. Ambiguity, not certainty is the name of the game with humans.
Hindsight deceives us. It makes it Feel like we knew all along. After all, how could we not have seen Usain Bolt rising to the level he did? But what about Walter Dix, Xavier Carter, Trentavis Friday, Jeff Demps, or whoever else over the last decade or two has been branded–and paid as if– they were going to be the next “Bolt.”
At the time, we all felt so sure of that pick! Look beyond running to the NFL, MLB, or NBA draft, and even with the intrusion of “Moneyball” type picks, the sports world is littered with wrong calls on potential.
This doesn’t mean we should give up on predicting potential. It’s necessary to make decisions, but it does mean that we should recognize the complexity of performance.
As administrators, statistical models should guide, not dictate decisions. It’s frustrating to see support decisions made not based on what the athlete is currently doing, but based on where they fit on a statistical model. Are they in the so-called developmental model? If they are an outlier, god help him. The model becomes the dictator, without understanding the nuance of performance.
As a coach, I think we should be even more cautious. I think progression is a misunderstood concept. We tend to put people in boxes based on what they have run. You are a 2:00 runner or you are a 2:05 runner, and as coaches and athletes we start to believe these boxes we dictate. I think this is the beginning of the end of progression. Once you put yourself in a box or are assigned one, it limits the vision of improvement. You just simply don’t know who is going to be your next Maggie Vessey, who had a best of 2:02.01 at the age of 26, and went on to run 1:57.8 the very next year.
I’m not arguing for giving up on performance prediction, but instead for some caution. Don’t let it become the driving force. It should be part of the puzzle, not the entire one.