This past weekend, I (along with our very own Steph Driver) had the pleasure of attending the inaugural Columbus Blue Jackets Hockey Analytics Conference, hosted by the Blue Jackets out in Ohio. The hockey analytics world has hosted a number of these kinds of events over the past half-decade or so, but this was the first one put on by a team, and it featured more than 20 different presentations, talks, and panels throughout the day, all from incredibly smart and knowledgeable people in various parts of the hockey world, from team management to journalists to consultant-types to hobbyists. It was an awesome experience, particularly as someone who had never attended one of these before, and I’m really glad I made the trip.

If that all piques your interest, and if you ever find yourself with approximately eight hours to kill, here’s the full stream of the conference in its entirety. And, if you want a very quick recap of every single presentation that we saw, in case anything in particular sounds of interest to you, our friends over at The Cannon put that together for you here.

To get right to the point, though, I figured I would zoom in on a few things that were said that I not only enjoyed hearing about, but also found particularly relevant to this year’s Flyers team. (For your convenience, I’ll link to those specific parts of the video above, if you find yourself interested in anything said here.)

The Power Kill

By: Meghan Hall of Hockey-Graphs and Alison Lukan of The Athletic

Where you can watch it: Here, at about the 1:23:30 mark of the video.

The gist of it:

NHL teams are generating more offensive chances on the penalty kill (hence “power kill”) in recent years than before, and that increase in offense is not coming at the expense of worse defense/increased chances allowed (if anything, said offense is leading to less time spent defending on the PK).

coming at the expense of worse defense/increased chances allowed (if anything, said offense is leading to less time spent defending on the PK). A big driver of this appears to be teams putting more skilled players on the penalty kill than they traditionally have.

What do the Flyers have to do with it? Well, they were singled out in the presentation as a team that has embraced this:

But if you’ve watched the Flyers over the past few weeks, you probably don’t need me, or anyone, to tell you that they’ve been generating some offense there, particularly from the guy at the top of the list (Kevin Hayes, of course). Still, the trend they point out is a valid one: the Flyers have leaned heavily on some of their strongest players on the penalty kill this year. If you look at the ranking of Flyers forwards on a per-game TOI basis on the PK (this varies slightly from Hall’s ranking above, which appears to be based on overall TOI rather than per-game), you can see that the Flyers are throwing their big guns out there:

(For reference, Oskar Lindblom’s 1:25 per game at the time of his removal from the lineup would have put him fourth.)

We’d have to pull together a similar list for every team to see just how far outside of the norm the Flyers are by rolling three of their best forwards this regularly on the PK. But the biggest way we have to check them relative to the rest of the league seems to indicate that whatever they’re doing — whether a matter of personnel, tactics, or something else — is working: as of this writing on Sunday night, the Flyers are fourth in the NHL in Expected Goals For per 60 minutes on the penalty kill, and third in shots on goal and unblocked shot attempts per 60.

A power kill: the Flyers have one.

(All statistics cited in this section are courtesy of Natural Stat Trick.)

Goalie Positioning

By: Cole Anderson of SportLogiq

Where you can watch it: Here, at about the 5:27:30 mark of the video.

The gist of it: The presentation dove in-depth on how goaltenders position themselves against shots, how they tend to play, where they tend to be relative to the “optimal” location to shut down a chance, and how goalie positioning relative to a shot affects that shot’s expected goal numbers. (That explanation does not do it justice and I’d encourage you to watch the whole thing; this may have been my favorite presentation of the entire day.)

What do the Flyers have to do with it? Again, the Flyers were actually singled out in this presentation, sort of, as Anderson showed an example of Carter Hart getting in the right position to make what would normally be a dangerous shot a less dangerous shot. You can watch that part here, at the 5:43:16 mark, if you’d like to see our pal Carter doing good things and anticipating a pass to make a shot on goal less likely to be successful.

The other remotely Flyers-centric part of this one that caught my attention involved the below chart, which looked at where goalies are lining up relative to the “optimal” location to stop a shot based on where the shooter is. See if you notice the same thing I did, particularly in the upper-left corner of the chart. (This is a screenshot of the chart off the video page, so please forgive the blurriness.)

Yep, that’s Hart as well as Brian Elliott, both in the upper-left side of the chart, both slightly above zero relative to the expected depth that they would have based on the shots they’re facing and both slightly below zero in terms of the optimal angle to take (meaning, per the label on the axis, they both find themselves slightly closer to center ice than optimal). They’re both reasonably far away from the cluster of goalies towards the middle of the graph ... but at the same time, they’re very close to 0.0 on both axes, which, if I understood the point of the thing right, is good. Meaning the Flyers’ goalies are getting the right angles and having good positioning fairly often. So that’s nice to know. The fact that both of them are in very similar spots on the graph makes me wonder if there’s a coaching aspect to this, as well.

Data and NHL Management

By: Panel discussion featuring four people currently working in NHL front offices — Matt Cane (New Jersey), Alexandra Mandrycky (Seattle), Ryan Miller (St. Louis), and Bill Zito (Columbus) — moderated by Craig Custance at The Athletic

Where you can watch it: Here, around the 5:59:00 mark of the video.

The gist of it: This was a wide-ranging panel discussion talking about how management works with numbers, analytics, and data at so many different levels.

What do the Flyers have to do with it? The part here that seems to be worth noting was courtesy of Mandrycky, who — before joining on with the Seattle Kraken’s NHL team’s front office as their Director of Hockey Strategy and Research in 2019 — worked with the Minnesota Wild for parts of four seasons before leaving in 2018. As you may recall, Minnesota’s general manager during that time was none other than Chuck Fletcher, who of course is currently the man running the show here in Philadelphia. Fletcher hired Mandrycky, as well as Andrew Thomas (the founder of the now-defunct War On Ice, and another person who spoke at CBJHAC on Saturday), in January of 2016.

Knowing that backdrop, this bit from Mandrycky (starting just after 6:02:00, here) was interesting to hear:

You know, what I think is interesting is, as hires have happened across the league over the last few years, a lot of times, it’s the management, the executives, that are making those hiring decisions. And you know that you want an analyst on staff, they realize it’s important, that’s why they’re conducting the job search. But you don’t necessarily maybe completely understand all of the skill sets required to make that happen. Five years ago, when I was originally going to work in Minnesota, the only reason that I got that job was because Andrew Thomas, who you just saw up here, when he was talking to Minnesota, he says “you know, I can do all of this analytics work for you, but ultimately, we need to have someone who knows how to work with the technology. We need to have someone who knows how to deal with a database, how to deal with bringing [and] communicating the data that we’re working with to our stakeholders, to the people across the hockey operations department. So as we’re building out this group, it’s not just running the models, it’s managing the data, it’s managing the puck and clear tracking data that will be coming into the league. It’s how we’re communicating that to people. So we’re looking at hiring developers, data engineers, analysts, specializing in kind of these particular areas, whether that’s pro scouting, player development, amateur scouting, and really thinking about, if you had the opportunity to integrate data across every aspect of the hockey ops department, what does that look like?

Mandrycky doesn’t specifically use names outside of Thomas there, but it’s not hard to think about that knowing who the Wild’s general manager was at that time, and it happens to be the guy currently in charge here in Philadelphia.

Now: is it possible that this mostly boils down to Chuck Fletcher finding a pair of outstanding analysts/researchers in Thomas and Mandrycky and letting them do their thing? Perhaps. But even if that’s the case, is that something he can learn from and take to a new location? Particularly as Mandrycky describes it above, in the sense of how to build a team that can do everything needed to get a good data operation working across a franchise? I think so.

Truthfully, we know fairly little about the Flyers’ current analytics work, other than that it is led by Ian Anderson (who has been with the team since 2014) and features developer Jacob Hurlbut (brought on in 2016). They have mostly kept things behind the curtain ever since Anderson arrived under Ron Hextall’s watch. (In addition to Anderson’s and the team’s internal work, Hextall privately brought in multiple outside consultants during his time with the team.)

But back in September, Fletcher added two new members to the team, one of whom (Director of Hockey Information Tom Minton) was also a part of his team in Minnesota. Again, we don’t know a ton about the specific roles and responsibilities of what everyone involved in this side of the operation does. But Mandrycky’s words above about how you build a team — and how, in Minnesota, she was part of a team — that handles every part of the operation, and how that managed to work out well, seems relevant in thinking about Fletcher bringing on more members of the analytics team in Philadelphia. Even if we don’t know much, we can have some confidence that Fletcher knows how to do this right and knows how to find the right people to make this work.