If one had to point to an individual factor going particularly well for the Vancouver Canucks early on in the 2025-26, it would probably be the seemingly restored play of goaltender Thatcher Demko.

One doesn’t exactly need any fancy statistics to reach this conclusion, either. Just watching the games is probably enough to see that Demko is back to his former habit of stealing games via stealing saves. According to the eye-test, he’s performing just as well as he did when he earned a Vezina nomination two seasons ago.

His counting stats are also far better than decent. Demko’s goals against average of 2.28 (as of this Wednesday morning writing) ranks 20th in the NHL, and 13th among goalies who have played at least as much as he has. His save percentage of .922 ranks him 10th overall by the same parameters.

Both numbers, were they to stick for the entire season, would be the best of Demko’s career. And yet, they still don’t paint a complete picture of how well he’s played through his first four starts. To paint that picture, we do need to stock our palette with some advanced stats.

Goalie advanced stats are typically presented as one of two numbers: Goals Saved Above Average and Goals Saved Above Expected. But what do those numbers mean, and why do they represent Demko so well?

We’ll attempt to explain.

We’ll start with Goals Saved Above Average, a statistic tracked by our friends at NaturalStatTrick. According to their number-crunching, Demko currently has a GSAA of 2.64, which is the 12th-best in the league.

To understand what NST means by Goals Saved Above Average, we have to understand how they track and record shots against. Each shot that reaches a goaltender is assigned a level of ‘danger,’ based on its statistical likelihood of ending up as a goal. It’s all measured according to this chart:

As they put it on their website:

“Attempts from the yellow areas are assigned a value of 1, attempts from the red areas are assigned a value of 2, and attempts in the green area are assigned a value of 3.

“Add 1 to this value if the attempt is considered a rush shot or a rebound. A rebound is any attempt made within 3 seconds of another blocked, missed or saved attempt without a stoppage in play in between. A rush shot is any attempt within 4 seconds of any event in the neutral or defensive zone without a stoppage in play in between…

“Decrease this value by 1 if it was a blocked shot.”

From there, each shot is assigned a danger score (cue Kenny Loggins). Shots with a danger-score of one are considered low-danger, shots with a danger-score of two are considered medium-danger, and then shots that are danger-scored at three or higher are considered high-danger chances.

To derive a Goals Saved Above Average from that, all NaturalStatTrick has to do is look at how many goals against a goaltender has allowed, and then how many goals against a goaltender with a league-average save percentage would have allowed if they faced the same number and danger level of shots.

In other words, Demko having a GSAA of 2.64 means that a league-average goaltender would have allowed 2.64 more goals against through four games than the nine Demko actually allowed.

And that sounds impressive enough. But there’s another, more complex number out there to explore, and it presents Demko even more favourably.

The fine folks over at MoneyPuck have another statistic called Goals Saved Above Expected. They currently have Demko ranked fifth overall in the league with a GSAE of 6.6, which trails just Igor Shesterkin, Spencer Knight, Jet Greaves, and Connor Hellebuyck.

To understand GSAE, we’ve got to get a grasp on Expected Goals. But that’s a much more complicated topic than shot danger.

In short, every stat-tracking organization has their own model for Expected Goals – a number that well and truly attempts to measure the likelihood of any play resulting in a goal. Those same factors of shot location and timing featured in shot-danger stats are important here, but they’re only one component of many. According to MoneyPuck, their Expected Goals model uses the following 15 variables:

“1.) Shot Distance From Net

2.) Time Since Last Game Event

3.) Shot Type (Slap, Wrist, Backhand, etc)

4.) Speed From Previous Event

5.) Shot Angle

6.) East-West Location on Ice of Last Event Before the Shot

7.) If Rebound, difference in shot angle divided by time since last shot

8.) Last Event That Happened Before the Shot (Faceoff, Hit, etc)

9.) Other team’s # of skaters on ice

10.) East-West Location on Ice of Shot

11.) Man Advantage Situation

12.) Time since current Powerplay started

13.) Distance From Previous Event

14.) North-South Location on Ice of Shot

15.) Shooting on Empty Net”

…and even that doesn’t quite cover it, as there are a number of other event-specific modifiers that can enter the picture. The inner workings of the model are not public, but one can see that a lot of data goes into it, making the results more refined and accurate than other, less complex statistics.

And what this model tells us is that opposing teams were expected to score about 15.6 goals against the Canucks during Demko’s four starts. That’s almost four goals against per game! Instead, Demko has kept them to just nine goals against. Subtract one number from the other, and you get Demko’s GSAE of 6.6.

MoneyPuck also applies this number to a goalie’s regular goals against average to come up with their “GAA Better Than Expected,” which has Demko at a 1.66 better GAA than expected.

So, what does it really mean? It means exactly what you’ve already seen out there on the ice. The Canucks have allowed scoring chances against Demko that, due to various factors, should have resulted in more goals. But Demko has shut the door all the same, and to a degree that few other goalies have been able to equal in the earliest stretch of the 2025-26 season.

There’s that old saying that statistics should be used like a drunk person uses a lamppost: for support, not illumination. And that’s certainly the case here. Anyone watching the Canucks right now can see that Demko is stealing games for them through the process of making saves that most goalies cannot.

It’s just nice to also have some concrete numbers to back that up.