Data May Not Drive Play, But It Should Drive Decisions

It’s not easy creating a data-driven decision-making culture in any organization, let alone one as bound in tradition and lore as the NHL, where hockey men are imbued with mythical powers of observation and judgement just by virtue of having played the game. And yet, the NHL is clearly moving in that direction. It may be at a glacier-like pace, but I suppose that makes sense, what with the ice and all. Despite some early stumbles, it’s probably safe to say that it is only a matter of time before data-driven decisions are the norm rather than the exception. Whether that happens while we still have glaciers is another matter.

But even when there is a managerial will and top-down direction to move toward a data-driven culture, it is often difficult to introduce data analysis into the existing decision-making process of an organization. It’s not just deep structural changes that are necessary, but also staff will need a robust change management process. It’s hard enough to get people to accept change, but a new culture requires that they go beyond acceptance and embrace it as a new way of doing things. This is a difficult process in any organization. However, it is made more difficult in the hockey world where many in positions of authority are in those roles precisely because they “played the game” and understand the traditional way of doing things.

But what if you could start from scratch and build something from the ground up? 

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So You Got Accepted To Present at a Sports Analytics Conference

First of all, congratulations if you got accepted. Kudos to you if you got accepted to a conference like RITSAC, a very well run and well curated conference. This is a wonderful accomplishment, and you should be proud. Tell your friends and family. Celebrate. Bask in the adoration.

Well, maybe not that last part. But you get my point. Your work clearly has some perceived value and is based on solid reasoning and data analysis.

So now what?

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When Can You Trust Your Intuition: The problem with having played the game

A common retort that many in the hockey analytics community have gotten is: “have you ever played the game?”

The insinuation, of course, is that if you haven’t played hockey at a high level, let alone in the NHL, then you can’t possibly understand the game. Certainly not as well as those who have. And that when it comes to evaluating players or making decisions on how best to improve a hockey team, the former players and lifelong hockey men that populate the league’s front offices can always fall back on their instinct for the game in ways that no one else can.

But let’s talk about relying on your gut instincts to make decisions.

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It’s Time To Stop Talking About Analytics

Look, nobody knows what analytics actually is anyway, so why are we still talking about it? At its most basic, analytics is simply a tool. Much like a hammer is a tool.

Maybe too much like a hammer. As the old saying goes, when all you have is a hammer, everything looks like a nail. The same may be true for analytics. At least in some contexts. Yes, analytics is simply a way to draw meaning out of data, but just because you finally figured out how to apply gradient boosting to your ridge regression model doesn’t mean you should.

Once you think of analytics as a tool, a means to an end, then it’s much easier to see that it’s not just a tool, but an entire toolbox. And when you reach into that toolbox, the tool you take out should depend on what you want to accomplish.

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Friday Quick Graphs: The Dangers of Binning Data

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If you’ve ever read a little math, you likely know the dangers of binning continuous data when testing relationships between two variables. It is one of the easiest and most common mistakes that an amateur statistician might make, largely because, intuitively, it seems like it should make sense.

But it doesn’t, and here’s why.

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Applying CUSUM to hockey prediction models

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The NHL season is a long and grueling affair and most teams will experience some ups and downs over the course of 82 games. Even a team that had a 67% chance of winning every game it played, would still have a 20% probability of putting up a five-game losing streak. And this is just straight probability theory with fixed probabilities. What happens when you consider all of the factors that go into determining the probability of winning an individual game, let alone predicting performance over an entire season?

Well, I’m not here to answer that question.

What I am here to do is to try to apply an analytical technique that was developed in the 1950s for the purposes of quality control in industrial and manufacturing processes to the game of hockey. Continue reading

How does performance as of Dec. 1 relate to making the playoffs?

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Every year right around December 1, NHL analysts and fans alike start thinking a little more seriously about playoff chances. Although in many ways this is an arbitrary point in time, particularly when linking it to US Thanksgiving, there’s also some logic to it as well.

By the end of November, we are two months in and most teams have played 20-25 games, or a quarter of the season. And from an analytics perspective, that’s about the point when you can start making use of most of the early season data.

So while most of the traditional playoff discussion at this time of the year tends to focus on points or even where teams are in the standings, let’s take a look at how early-season shot-based metrics relate to whether a team ultimately makes the playoffs.

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Have you even used a calculator, jock?

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There has been quite a lot of talk over the last couple of days about how unhappy NHL players are with the escrow hit they take on every paycheque.

Unfortunately, when you have a collective bargaining agreement that specifies how hockey related revenues are to be split between owners and players, an escrow account is a necessary evil. Because the players’ share is paid out under the provisions of 700 or so individual player contracts throughout the season, there needs to be a mechanism to reconcile those payments with the total share following completion of the season, when all hockey related revenues have been accounted for.

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Can defensemen control rebound opportunities? Putting the eye test to the test.

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One of the attributes that is often attached to defensemen is the ability to clear rebounds. You hear this quite often on NHL broadcasts, usually after a flurry of rebound shots that ultimately wind up in a goal. The colour commentator will jump in and imagine the goalie is saying to his defensemen, “I’ll stop the first three, you get the fourth one.”

But just how much is there to defensemen’s ability to prevent rebound shots?
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Hockey Talk: Shot Quality

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Hockey Talk is a (not quite) weekly series where you will get to view the dialogue among a few Hockey-Graphs contributors on a particular subject, with some fun tangents.

This week we started from a Twitter conversation suggesting that expected goals calculations (xG) might underweight “shot quality”. A topic that HG contributors are hardly short of opinions on. Continue reading