The 2017 NHL GM Report Card – Part 3

It’s been a crazy couple of days writing up this general manager project. If you haven’t already, please read the methodology before checking out our final list of rankings.

When going through the final rankings there were several interesting things that only show up when the data is viewed holistically. Here are some of our big findings that didn’t make it into the rankings piece.

GM Ranking

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The 2017 NHL GM Report Card – Part 2

(This piece was written as a collaboration between Carolyn Wilke and Chris Watkins)

Alright, we’re only a little bit sorry we made you read our methodology post first, because we know what you really want is below. Still, we recommend you understand how we came to our ratings before you continue reading this post.

We’re sure you’ll disagree with us on some points, and that’s fine – despite our best efforts, these are still fairly subjective ranks. Still, try this exercise for yourself, and it’s possible your opinions will change.

Now, without further ado – all 31 GMs, ranked.

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The 2017 NHL GM Report Card – Part 1

(This piece was written as a collaboration between Carolyn Wilke and Chris Watkins)

What makes a good general manager in the NHL?

It’s a hard question, plagued by subjectivity, by bias, and by lack of transparency. It’s complicated by league mandates like the expansion draft and the hard salary cap. It mixes the weight of process, results, and vision into one big stew, where it can be difficult to distinguish the meat from the sauce.

It’s a question, that unlike many others, is difficult to quantify with even the most advanced of stats.

And it’s one that the league has no desire to answer definitively, as that would only hurt the men currently in those roles.

Fortunately for you, Hockey Graphs loves tackling the hard questions.

In the following articles, we will attempt to rank all 31 of the NHL’s GMs, as objectively as possible, according to seven important criteria. They each painstakingly researched trade histories, draft selections, and salary cap management, coming up with a final score for each.

While this process still was subjective, in that these scores are not quantitatively derived, it was an extremely holistic process, and both of us were forced to confront some of our own biases.

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Shea Weber, Norris Voting, and the Role of the Modern Defender

So on Thursday, I went on a bit of a rant about the role of defensemen in the NHL. Well, rant is probably the wrong word, as it wasn’t particularly emotional, so let’s call it instead a “tweetstorm”. This piece will expound upon those tweets in greater depth, as I think it’s a topic that deserves a little more than what 140 characters and snark can provide.

Though I can’t promise this won’t also include some snark.

The entire discussion was kick started by this tweet:

Now, you’re probably thinking “oh man, a Shea Weber analytics take. Let me go get my popcorn for the inevitable scathing fallout.”

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Exploring the Impact of New NHL Coaches and GMs

With Todd Richards being let go after a disastrous 0-7 start by the Blue Jackets, and Bruce Boudreau on the hot seat (heck, he might be out of a job by the time I finish writing this), coaching is once again in the spotlight. After Richards was fired, I went on a mini rant about how I believe having a good GM is more important than having a good coach, and while I still believe this is true, I wouldn’t be a data person unless I tried to prove it.

This project has many parts to it. The first, which I’ll be doing here, is just looking at the breakdown of Scoring Chances For% compared to Coaches and GMs in the early days of their tenure, i.e. right after being hired. Scoring Chances, to simplify things, are basically “more dangerous shots” (click here for a more rigorous definition).

To start, I needed data. I pulled all 30 teams from 2006/07 to 2015/16, and coded each season by what kind of organizational changes happened within. This gave me 331 data points, as there were often midseason coaching or GM hirings to account for.

The states broke down like this:

1) No Change – 64%
2) Hired a new Coach – 21.5%
3) Hired a new GM – 7.3%
4) Hired a new Coach & new GM – 7.3%

In looking at the data, some patterns quickly emerged. The first two years of tenure in either role were where the most change, for better or worse, happened.

Because I had so much data in the No Change category, I wanted to see if there was any sort of trend year over year for the control group.

No Changes - Coaches SCF Delta YoY

No Changes - GMs SCF Delta YoY

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