An expected goals look at the Flames

So the other day on Twitter, Globe & Mail hockey writer James Mirtle tweeted the following:

After gawking at the numbers, I was immediately filled with curiosity regarding how the Flames are doing in that respect – particularly given how many close games they’ve lost. So I ran the numbers. And there are a handful of key players responsible for them being where they are in the standings.


Admittedly, the Expected Goals model I am using here is simplistic. I like it because it’s simplistic, but that does limit its effectiveness sometimes. Here’s the gist: based on a player’s career shooting (or save) percentage, you can project how many goals they should score (or allow) based on the number of shots they have (or have faced). This approach pinpoints individuals that are scoring more or less than they should be, and goalies that are allowing many more (or fewer) goals than they should be.

All shots are equal under this formula, which is one drawback. And for younger players – Sam Bennett, for example – it’s less effective because for them the current season could be their entire career. It’s a tool, but it’s not bulletproof by any means.


Player Goals Expected Difference S% Career%
Johnny Gaudreau 19 18.0 +1.0 16.4 15.5
Sean Monahan 13 15.1 -2.1 13.1 15.3
Mark Giordano 10 7.6 +2.4 9.6 7.3
Sam Bennett 10 9.9 +0.1 14.7 14.5
David Jones 8 7.7 +0.3 14.0 13.5
Michael Frolik 7 5.8 +1.2 9.5 7.8
Dougie Hamilton 6 5.2 +0.8 6.8 5.9
Jiri Hudler 5 7.8 -2.8 9.4 14.8
Mikael Backlund 5 5.9 -0.9 6.5 7.7
Joe Colborne 5 5.6 -0.6 10.2 11.5
T.J. Brodie 4 2.4 +1.6 10.5 6.3
Matt Stajan 4 3.9 +0.1 13.8 13.4
Mason Raymond 4 4.7 -0.7 8.2 9.6
Josh Jooris 3 4.2 -1.2 8.6 12.1
Markus Granlund 3 3.6 -0.6 10.7 12.7
Dennis Wideman 2 4.1 -2.1 2.9 6.1
Kris Russell 2 2.2 -0.2 4.5 4.9
Micheal Ferland 2 2.6 -0.6 3.2 4.2
Brandon Bollig 1 0.8 +0.2 4.3 3.6
Lance Bouma 1 1.0 0 10.0 10.0
Deryk Engelland 0 1.5 -1.5 0 4.8
Kulak 0 0 0 0 0
Smid 0 0.2 -0.2 0.0 3.3
Grant 0 0 0 0.0 0.0
TEAM 114 119.9 -5.9 9.30 9.78


Goalie GA Expected Difference SV% Career%
Karri Ramo 77 80.0 -3.0 91.0 90.6
Jonas Hiller 35 22.9 +12.1 87.0 91.5
Joni Ortio 10 8.1 +1.9 86.8 89.3
TEAM 122 109.7 +12.3 89.8 90.7


The Flames have seen a positive goal difference against expectations from Karri Ramo (3), Mark Giordano (2.4), T.J. Brodie (1.6), Michael Frolik (1.2) and Johnny Gaudreau (1), meaning that ignoring circumstances these players have given the Flames more goals than they were expected to. Considering that Ramo’s played a lot of hockey behind a rather chaotic defensive group and survived waivers and an AHL banishment, that’s pretty impressive. Frolik’s differential is also nice to see for a player brought in primarily for his complementary defensive skills.

On the flip side, the Flames have seen a negative goal difference versus expectations from Jonas Hiller (12.1), Jiri Hudler (2.8), Dennis Wideman (2.1), Sean Monahan (2.1), Joni Ortio (1.9), Deryk Engelland (1.5) and Josh Jooris (1.2). Let’s tackle the scariest one first: Hiller’s numbers are downright horrifying, but bear in mind that he played the majority of his games in October behind a very porous defensive group. We may do a follow-up digging into career adjusted save percentages to see how bad Hiller has been when you control for quality of shots. It probably won’t be pretty, but I doubt it’ll be a difference in the teens either.

Take the shooting percentages of the following (super-young) players with a grain of salt, as this season represents a gigantic chunk of their career: Gaudreau, Bennett, Jooris, Granlund, Ferland, Kulak and Grant. Similarly, Ortio’s save percentage is not wholly representative.

  • piscera.infada

    Expected goals as the blog post uses, is a dumb stat.

    For starters it uses SH%. Why not use Fenwick Sh% or CorsiSH% instead? SInce hitting the net and not hitting the net are pretty random variables.

    Second, it can’t tell you if a winger is playing a puck support role or leaking out on breakaways and the equivalent at every position. Is Kadri really having a star year, or is he just spending way more time in the offensive zone in Babcock’s system taking tougher angle shots?

    I’d like to see more in-depth analysis into expected goals factoring in missed shots, scoring chances, rush chances, all that good stuff.

  • wot96

    Aren’t these results more or less also explained by the deviations in expected versus actual special teams performance to date?

    The three players suffering the biggest negative deviation from expectation are powerplay players. Hiller, meanwhile, played a lot earlier in the season when special teams could only be complimented if described as abysmal (and he didn’t have historically good numbers outside evensies anyway, iirc).