Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net. My ramblings will look at the theory and philosophy behind analytics and their applications given what is already publicly known, keeping my job safe while still getting to interact with the public hockey-sphere.

Hello. Hope everyone is enjoying my return after a long hiatus. I am back from my busy schedule of helping run a tracking company that sells private tracking data to argue here against overvaluing private tracking data (and in addition black-box models)… or really I’m suggesting to not underrate what’s in the public.

You heard that right. The guy that has vested interests in demonizing public models and data is going to defend public models and data!

We’re bringing it back! Every once in a while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net. My ramblings will look at the theory and philosophy behind analytics and their applications given what is already publicly known, keeping my job safe while still getting to interact with the public hockeysphere.

I’m back and here to ramble on things like models, sheltering, and environmental impacts on the results we measure.

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By MithrandirMage [CC BY-SA 3.0], via Wikimedia Commons

Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

Hey! Remember me?

I work full-time for (slash help run) HockeyData, a data tracking and analysis company. Because of this conflict of interest, it limits what I can and cannot talk about. The good news is I can still talk generalities, the basics behind analytical thinking in hockey, and other peoples’ good work, which fits my Behind the Numbers series.

Why have there been so few updates then? Been busy (…lazy).

One generality I’d like to rant about is how we look at and evaluate statistics and models: how meaningful different numbers are and why we view them that way.
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Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

As the hockey analytics community pushes for validation of current metrics and their value, I think it is sometimes lost that we do understand these statistics have their weaknesses. We do wish and try to improve upon these weaknesses.

I also think an often underlooked fact is that each incremental improvement diminishes the potential value from every subsequent improvement.

Let’s take a look at what I mean…

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Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

Almost weekly, you will see a “quant” or “math” type complain about some of the binning going on (usually with Quality of Competition or scoring chances).

But the reason may not seem intuitive, so I’ll use scoring chances as an example and explain the issues with binning continuous data.

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Interesting. This season teams who score first are 151-50-28. Teams who give up first goal are 78-128-23. You sure it doesn’t matter? https://t.co/BCGaTotHD3

— Jason Gregor (@JasonGregor) November 15, 2016

Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

Not long ago Jason Gregor tweeted about the value of scoring first.

It may be a bit controversial and difficult to get right away, but the value of scoring first is not special. Long ago, Mr. Eric Tulsky, now of the Carolina Hurricanes, showed that the value of scoring first equals the value of any other goal.

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Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

Hockey’s plus/minus may be the worst statistic in hockey, although there is some debate with goalie statistics not based off of save percentage (like GAA or Win% that just adds a team component to a goalie’s save percentage). It could even be in contention for just the worst statistic in sport.

Now, some people may read that and think I’m simply saying this because I value shot metrics over goal metrics in player evaluations. While I do feel that way, it is only one of a few reasons that that plus/minus fails in being useful.

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Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

Here we go. Here is part two, to what really should have been part one in hindsight prior to this piece, which would have saved me some of the backlash on Twitter, as the point was frequently misunderstood. (And while we’re dealing with hindsight, the title was part of the misunderstanding as well.)

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