Photo Credit: Anne-Marie Sorvin – USA TODAY Sports
No matter how the losses mount, the Canucks remain upbeat. You hear game after lost game about how well they felt they played. That they just couldn’t get a bounce, and so on.
That commentary often falls on deaf ears, but I’ve always felt there was some semblance of merit therein. It’s hard to get too invested in their lofty shot totals since they’re trailing in perpetuity, but they’ve had their nights all the same. And their league-worst 960 PDO indicates that they truly have been among the least lucky teams this season.
Considering the extent to which this team’s struggled to score goals though that shouldn’t be overly surprising. I want to peel another layer off the onion and see which players are suffering this misfortune on a personal level.
Before I get too far into this exercise, I have to give credit where due. This isn’t an original idea. Not by any means. I’m borrowing this idea from our good friend Ari at Flames Nation. With that in mind, I’ll use her exact methodology to determine the Canucks in line for bumps in production. Here’s a link to the post that inspired her article, and the passage that explained the way she conducted this exercise using PDO and xPDO.
PDO is basically a luck proxy. It’s the combination of a player’s on-ice shooting and save percentages. Sometimes players just hit a wall and it seems as though, no matter how much offence they try to generate, it just never goes in the net; on the other end of the ice, sometimes no matter how well they play, pucks go in past their goalie when they’re out there.
These numbers can be especially skewed at the start of a season, when the sample size is much smaller. So… like now, pretty much.
xPDO is a little different, in that it adds up a player’s expected Fenwick shooting percentage and expected Fenwick save percentage (and here’s why those stats are important). In theory, a player’s PDO should hit roughly 100; xPDO is more finely tuned to specific players. Most of their numbers are close to 100, but not quite.
So, if a player’s PDO is lower than his xPDO, we can reasonably posit that player’s been unlucky this season. If a player’s PDO is higher than his xPDO, then they’re likely getting lucky and are due to regress. I like this methodology because it’s much more nuanced than just pointing to their unadjusted PDO and yelling foul about their counting stats. xPDO is tailored at a player-by-player level for improved accuracy.
The way to read this graph: the top right indicates a player who’s playing well and garnering results that reflect as much, the top left indicates a player who’s getting lucky and not performing terribly well, the bottom right would indicate they’re playing well, but not getting bounces and the bottom left indicates players are not performing well and not getting lucky.
If you told me Derek Dorsett would have four points by mid-November, I’m not entirely sure how I’d have reacted. If you told me he would achieve this in spite of bad luck, I’d have laughed you out of the room.
That’s the exact situation we’re looking at now. Interestingly enough, Dorsett’s xFSh% (6.1%) isn’t all that far removed from his on-ice Sh% (7.25%). Hell, if anything the Canucks are scoring more often than they should be with Dorsett on the ice.
Where the difference is most stark is on the defensive side of the game. Dorsett’s xFSv% is a reasonable .923, compared to his actual on-ice Sv% of .812. It’s worth noting Dorsett’s xFSv% is among in the bottom-five among Canucks skaters, which indicates he’s not doing a great job of limiting opposition shot quality.
Finding Brandon Sutter’s name on this list comes as no small surprise. This is a player that’s routinely benefited from well above average goaltending behind. It’s part of the reason Sutter’s defensive chops are exaggerated to the extent they are.
Much like Dorsett, though, Sutter is suffering some pretty abhorent luck where keeping pucks out of the net is concerned. Sutter’s on-ice Sv% is sitting at .890, as opposed to his XFSv% of .930. Given Sutter’s played in front of .937 goaltending for much of his career (and likely contributed to that number, to some extent) I’d expect that number will correct itself eventually.
There isn’t any real precedent for these numbers. This is Troy Stecher’s rookie season, after all. Everything he brings statistically is new.
Another factor that could muddy Stecher’s picture is that his sample is relatively small — just ten games. All it takes is a game like Saturday’s, when Stecher was on the ice for two even strength goals against, to make a world of difference. Just another example of why we caution against putting too much stock into small samples.
Stecher is suffering at both ends of the ice. His on-ice Sh% (4.26%) lags behind his xFSh% (4.95%), and his on-ice Sv% (.883) is a fair measure behind his xFv% (.936). I don’t think Stecher’s played especially poor in his own end. I’d expect things to improve.
This one makes a tonne of sense. Alex Burrows has breathed new life into the Bo Horvat-Sven Baertschi pairing. As a trio, they’ve controlled 58% of unblocked shot attempts and only garnered a 40% goals for. There’s obviously a tonne of bad luck involved in driving that large a disparity.
Speaking for Burrows personally, it’s primarily bad shooting luck that’s holding him down. Burrows is carrying a 3.6% on-ice Sh% in contrast to his 5.95% xFSh%.
One of the most interesting findings while conducting this exercise was the impact Burrows should be having on his team’s ability to prevent opposition offence. He’s carrying a respectable .923 on-ice Sv%, but were that to regress close to his xFSv%, he’d be looking at something closer to a .945 mark. That’s bonkers.
If bad starts are a repeatable skill (or lack thereof, I suppose) then Sven Baertschi’s been the flagbearer for the Canucks these past two seasons. His six points don’t strike me as especially bad, but I’m sure everyone involved would like to see Baertschi with more than just one goal to this point in the season.
Baertschi has one of, if not the single best xFSh% among these maligned Canucks at 6.7%. That’s not that large a distance from his on-ice Sh% of 5.5%, but it counts for something. Like most of the Canucks on this list, Baertschi is struggling primarily at his own end of the ice. His .899 on-ice Sv% is a far cry removed from the .934 mark his xFSv% suggests he should be towing.
The Full List
Players Who Could Get Worse
To the nobody’s surprise, the list of Canucks who are due for negative regression isn’t an especially long one. I mean, think about it — this is the team with the league-worst PDO.
Seeing Daniel Sedin on that list makes sense — he’s in the midst of quite the hot streak. The same goes for Jannik Hansen, who’s been one of the most prolific Canucks offensively going as far back as last season. Jake Virtanen comes as
surprise. He hasn’t been on the ice for a single goal against, which indicates he’s suffering poor shooting luck and benefiting greatly from goaltending.