Backcheck
Team diagnostic
2025-26last seasonAs of Sun, Sep 20

Vancouver Canucks

5-on-5 · model-estimated

Canucks: a balanced team (50.4% 5v5 xG) with league-average goaltending, flagged for regression (3 signals).

How to read this

This is one team through the publication's three layers. The identity row separates process — the chances a club creates and allows (, ) — from luck, which is what measures. Process predicts the future; luck predicts a correction.

Everything below follows that split: regression flags mark places where results have outrun (or trailed) the underlying play, talent tiers and the player table rank the roster by a model-estimated , and roster needs compare each position group against league average. The proxies rank things usefully but share credit with linemates — read orderings as solid and exact magnitudes as approximate.

PROCESS
chance creation and possession — xG%, Corsi. The repeatable part.
RESULT
goals, wins, special-teams conversion. What the standings see.
LUCK
PDO, finishing vs expected, GSAx — the part that mean-reverts.
GOLD/RED
regression flags: gold = watch it, red = act on it
Fine print · verbatim from the model
  • WAR / Impact are model-estimated proxies, not cap-validated
  • Roster-need gaps are ordinal — ranked correctly, magnitudes relative
Identity · balanced
50.4%
xGoals %
This team plays about even.
46.9%
Corsi %
0.03
xGF / 60
0.974
PDO
The bounces have been cruel — results should improve.
Strengths
  • No standout edges flagged.
Weaknesses
  • Leaky penalty kill (71% kill rate).
Regression watch · luck-reconciliation

PDO 0.974 — running cold at 5v5; due for positive regression.

Team finishing is -18 goals below xG — finishing should rebound.

Kevin Lankinen sv% 87.5% is below replacement — goaltending should improve or change.

Flags mark gaps between process and result likely to move toward the mean.

Talent tiers · model impact
Elite00
  • None
Top02
  • Linus Karlsson
  • Pierre-Olivier Joseph
Middle06
  • Elias Pettersson
  • Filip Hronek
  • Marco Rossi
  • Jake DeBrusk
  • Drew O'Connor
  • Evander Kane
Depth12
  • Brock Boeser
  • Max Sasson
  • Teddy Blueger
  • Zeev Buium
  • Arshdeep Bains
  • Aatu Rty
  • Nils Hoglander
  • Tom Willander
  • Liam Ohgren
  • Marcus Pettersson
  • Victor Mancini
  • Elias Pettersson
Rate-first

Special teams

Power play
0.00 xGF/60 · 21.8% SH%
6.54GF/60
Penalty kill
0.7 Kill%
10.89GA/60
Source · MoneyPuck 5-on-5 + ST splits
Team GSAx -1.8

Goaltending

Below expected
GoaltenderGP
Kevin Lankinen4787.550+0.0
Nikita Tolopilo2188.140-1.8
Source · GSAx = xGoals − goals, computed in-app
Roster needs · ranked
01
Depth defensehigh
team 28.9 vs league 87.3
-58
02
Bottom-6 forward depthhigh
team 31.2 vs league 81.9
-51
03
Top-6 forwardhigh
team 52.9 vs league 86.1
-33
04
Top-pair defensemanhigh
team 58.8 vs league 91.5
-33

Gaps are ordinal — needs are ranked correctly; treat the magnitude as relative, not absolute.

Top players · adjusted impact
PlayerGPTOI/GP
Linus KarlssonC7910.8+71.60+1.7
Elias PetterssonC7413.7+50.20+1.7
Filip HronekD8219.7+53.50+1.5
Marco RossiC5013.8+47.80+1.2
Jake DeBruskL8112.3+48.10+1.2
Drew O'ConnorL8212.8+55.30+1.2
Brock BoeserR7513.9+32.60+1.0
Evander KaneL7114.3+44.20+0.8
Max SassonC6611.0+30.90+0.4
Teddy BluegerC3514.2+35.10+0.4
Schedule load · logistics

How hard is this team’s season, logistically? This grades the schedule itself — travel, rest, and clustering — separate from how good the team is.

Logistics, not talent

Schedule load

DEPTH
Load index
16/ 100 · pctile vs league

The 27th-heaviest schedule in the league84 games, 1.3 days average rest.

Total travel
46,041
road miles flown
11
Back-to-backs
2 games, 0 days off
12
3-in-4s
3 games / 4 nights
10
4-in-6s
4 games / 6 nights
7
Longest road trip
5,080 mi
Rest-days distribution
0d11
1d48
2d18
3+d6

Nights of rest before each game · 0 days = red, 3+ = green

Rest advantage

24 games with more rest than the opponent · 24 with fewer · 35 even.

Hardest stretches
  • 6 games in 10 days with 4,090 travel miles

    Feb 18Feb 27

  • 6 games in 11 days with 4,332 travel miles

    Jan 22Feb 1

  • 6 games in 13 days with 5,429 travel miles

    Nov 22Dec 4

Source · NHL schedule · arena coordinates · rest & travel model
By the Model5-on-5 aggregates · MoneyPuck* WAR / Impact are model-estimated proxies, not cap-validated