There’s a fascinating look at skill development here that reminds me of an interesting anecdote I read in Sports Illustrated a while back. When people think of sports inefficiencies these days they think of analytics, numbers, Moneyball, etc. But those are just the most the most prominent modern manifestations. Back in the late 19th century, Baltimore Orioles manager Ned Hanlon began bringing his team down south prior to the season to work on their skills and ability to execute plays like the squeeze bunt and the hit and run. He had players field grounders and fly balls for hours every day, and his teams, more ready for the season than ever before, won three straight National League pennants, leading other managers to copy his practice and develop what has become known as Spring Training. Hanlon actually developed baseball’s first true inefficiency: fundamentals.
As many of you know, I love reading about baseball and soccer analytics. I think that in baseball’s case, having the “first mover” element means that later-adapting sports like hockey can look to copy many of their concepts and ideas, even if the sports are quite different. Soccer, meanwhile, is quite a similar game to hockey – just a slower version – and therefore many of the more specific practices translate quite well.
Soccer is at an interesting point though because they, unlike baseball, are uncovering new statistics (courtesy of companies like Opta) while also just now figuring out which of those statistics are meaningful. You can get an idea of how far behind analytics in soccer is by the fact that its main predictive statistic: Total Shots Ratio – which is essentially the soccer version of corsi – is actually based on corsi.
There’s a scene in Moneyball where Red Sox owner John Henry offers his vacant GM position to Billy Beane. “Anybody who’s not tearing their team down right now and rebuilding it using your model,” he says. “They’re dinosaurs.” The Oakland A’s were the first movers of modern sports analytics. They took a risk, and while there were stumbles along the way, they benefitted as a result. In hockey, it took a decade longer for any kind of true analytic implementation, and we’re still not quite in “tear down and rebuild using your model” territory. So why has it taken so long? I think the answer lies in the hockey world’s view of baseball. NHL executives are drawn to the differences between the two sports rather than their similarities. Yes, baseball is a stop-start game whereas hockey is fluid. And yes, baseball involves more one-on-one matchups and less team play. But beyond that, the games – and the strategies that result in building the best possible teams – are actually quite similar.