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June 1, 2016

The Formula for Elite Hockey Players

When Google started using their algorithm to predict your tastes, it was freaky. You’d be writing an email in your gmail account about a trip to Mexico, then not long after there would be an advertisement for trips to Mexico in your searches. Weird – Google is reading my email…

We might not like the idea of having our tastes reduced to an algorithm – a formula. But you also sort of enjoy it when you buy something that you “knew you wanted anyway” from Amazon. Or find another season to watch on Netflix.

The reality is that there are mathematical formulas which predict our tastes. They also predict our behaviours.

But it didn’t start that way.

Let’s look at the path that knowledge takes:

  • It starts as a mystery
  • Then it becomes a heuristic
  • Then it becomes an algorithm

The mystery is a bunch of information that has no connection. No seeming interlinkages. When someone starts to form conclusions about how the information is linked, it becomes a heuristic. A heuristic, or mental rule of thumb, organizes the information in a more meaningful way. This is where innovation happens. But the heuristic still has bias. So the next step is to systematically study the heuristic and make it more simple – reduce it to a mathematical formula.

Along the way, knowledge goes from exploratory to becoming exploited. What was learned in the heuristic stage gets exploited at the algorithm stage.

Not long ago, most of hockey was in the mystery stage. People attributed talent to inborn natural ability. They didn’t even try to do strength and conditioning. They would explain the success of certain players as literal mysteries.

Now we see some connections. Coaches are getting smarter. So are players. So are managers and parents. They’re starting to make connections in the patterns. There is still some bias. Bias is okay. It’s just part of the stage. And this is the stage is the heuristic stage.

I’d say that 90% of hockey is still in the heuristic stage. There’s nothing wrong with this. It’s just the way it is. Certain businesses like McDonald’s, Amazon, and Google are way past that. They’re exploiting the benefits of their algorithm. A sport like baseball is further along the continuum towards algorithm than hockey.

At the management level in the NHL, we see a shift towards algorithms. Managers figure out how to put together teams with advanced stats. They use algorithms to measure player value.

For a long time, I’ve been dissatisfied with my own role as a hockey development specialist. I have my own heuristics around what makes a good hockey player. I believe they’re more valid than other heuristics used by other coaches. For example, many coaches and scouts believe that big, smooth skating defensemen are the answer to any potential situation. When I stood on the bench and coached a team, I had a bias towards putting out my bigger defensemen. I’m not sure if that was because they were the best players, or that their size inclined me to think that way. Either way, I don’t know for sure. Neither does a scout. Neither does a manager. Neither does another coach. I used to think that the “bigger is better” heuristic was junk. But now I’m not sure.

As a hockey development specialist, my business survives on the perception that I’m making hockey players better. Once again, I truly believe that I’m doing the right things. I believe I’m giving my guys a bigger advantage than what other guys get with other coaches. But how do I know for sure? I can’t. You can’t. They can’t.

The earliest to the algorithm game in hockey was Anatoly Tarasov: the father of Russian hockey. He was using advanced stats before they were in vogue. The next to the algorithm game came Darryl Belfry. Whether he says this or not, he’s creating a formula for player success: an algorithm. He seems to measure many details, then sift through to find the ones that make the biggest difference. I’m not sure how his statistical process works, but it seems to work in the NHL. Good enough for me.

Many coaches, development specialists, and business people try to “measure things”. But the things they measure have close to no validity for predicting hockey success. “Oh ya? You measure shot speed to .00001km/h? Wow!!!”

For example: I was tagging a player the other day and on a shift he was -3 for Corsi. Except all three shots originated from the other side of the ice. The player I tagged was in position and had nothing to do with the shots against. He then retrieved a loose puck, and exited the zone. We tracked the shots against, the retrieval and the exit. So, which piece of data was most meaningful?

Obviously the loose puck recovery and exit showed what the player contributed on that shift. He wasn’t penalized for the shots against.

As a former pro and college player player, myself and my cofounder know which pieces of data to pay attention to. Then we use a couple simple, yet rigorous statistical methods to find the most important data points. To mathematically prove our heuristics. With that we’re building an algorithm. We’re building a formula for elite player development. And we’re getting data from all levels.

This is our drive to move from heuristic to algorithm. It greatly improves the rate of development of the average player. Very few in the space have the combined technical and mathematical expertise to do this. We count ourselves lucky to be working together on this.

Will this stymy innovation in hockey? Yes. An algorithm naturally does that. It trades the search for validity for reliable outcomes. With an algorithm, you can get reliable development. Killing innovation in hockey is not a good thing if you’re killing Darryl Belfry’s ability to innovate. We aren’t trying to do that. But killing “innovation” in hockey is a good thing if you’re killing an inexperienced coach in your association’s experiments in “chip & drive methodology” vs the “get it out methodology”. In that case, you want a formula. You want to drive out heuristics and amateurish experimentation. You want reliable development.

This may not be exciting to you. But it is to us. When you are paying for results from coaches, and coaches have nothing to be accountable to, you’re essentially paying for a mixture between hypnosis and snake oil. And that includes me and what I do. I just happen to be really good at hypnosis. And I have the best snake oil.

But now that all changes. If we have data to meaningfully show the improvements that a player makes, we have something to be accountable to. You can have that too.


P.S. If you liked this article because it was different than most Drone Coach advice, and you’d like to get to work on becoming a Hockey Wizard, then click here to check out the benefits of becoming a Train 2.0 Member.