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

Anaheim Ducks

5-on-5 · model-estimated

Ducks: a outshot/run-and-gun team (0.0% 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 · outshot/run-and-gun
0.0%
xGoals %
This team gets buried territorially.
52.2%
Corsi %
0.00
xGF / 60
0.981
PDO
The bounces have been cruel — results should improve.
Strengths
  • Elite top-end talent: Leo Carlsson, Cutter Gauthier.
Weaknesses
  • Out-chanced at 5v5 (0.0% xG share).
  • Leaky penalty kill (76% kill rate).
Regression watch · luck-reconciliation

PDO 0.981 — running cold at 5v5; due for positive regression.

Team finishing is -20 goals below xG — finishing should rebound.

Lukas Dostal sv% 88.8% 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
Elite02
  • Leo Carlsson
  • Cutter Gauthier
Top08
  • Beckett Sennecke
  • John Carlson
  • Jackson LaCombe
  • Troy Terry
  • Mikael Granlund
  • Olen Zellweger
  • Ian Moore
  • Radko Gudas
Middle07
  • Chris Kreider
  • Mason McTavish
  • Alex Killorn
  • Jacob Trouba
  • Pavel Mintyukov
  • Nikita Nesterenko
  • Jeffrey Viel
Depth06
  • Ryan Poehling
  • Jansen Harkins
  • Ross Johnston
  • Tim Washe
  • Frank Vatrano
  • Drew Helleson
Rate-first

Special teams

Power play
0.00 xGF/60 · 18.6% SH%
5.57GF/60
Penalty kill
0.8 Kill%
8.66GA/60
Source · MoneyPuck 5-on-5 + ST splits
Team GSAx +0.0

Goaltending

Above expected
GoaltenderGP
Lukas Dostal5688.830+0.0
Ville Husso2088.390+0.0
Source · GSAx = xGoals − goals, computed in-app
Roster needs · ranked
01
Bottom-6 forward depthhigh
team 46.6 vs league 81.9
-35
02
Depth defensehigh
team 63.7 vs league 87.3
-24
03
Top-pair defensemanhigh
team 73.5 vs league 91.5
-18
04
Top-6 forwardhigh
team 70.8 vs league 86.1
-15

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

Top players · adjusted impact
PlayerGPTOI/GP
Leo CarlssonC7014.0+80.70+3.5
Cutter GauthierL7613.4+76.50+3.5
Beckett SenneckeR8214.3+74.20+2.9
John CarlsonD7117.1+73.10+2.8
Jackson LaCombeD8218.4+72.40+2.7
Troy TerryR6113.6+72.80+2.6
Chris KreiderL7512.7+59.10+2.1
Mikael GranlundC5813.4+61.60+1.8
Mason McTavishC7512.6+57.30+1.6
Alex KillornL8212.6+46.50+1.2
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

STRONG
Load index
81/ 100 · pctile vs league

The 7th-heaviest schedule in the league84 games, 1.3 days average rest.

Total travel
45,118
road miles flown
11
Back-to-backs
2 games, 0 days off
16
3-in-4s
3 games / 4 nights
16
4-in-6s
4 games / 6 nights
6
Longest road trip
4,198 mi
Rest-days distribution
0d11
1d49
2d18
3+d5

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

Rest advantage

25 games with more rest than the opponent · 22 with fewer · 36 even.

Hardest stretches
  • 6 games in 11 days with 6,212 travel miles

    Dec 12Dec 22

  • 6 games in 10 days with 4,094 travel miles

    Feb 11Feb 20

  • 6 games in 10 days with 3,438 travel miles

    Nov 14Nov 23

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