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

Carolina Hurricanes

5-on-5 · model-estimated

Hurricanes: 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.
59.1%
Corsi %
0.00
xGF / 60
0.984
PDO
The bounces have been cruel — results should improve.
Strengths
  • Elite top-end talent: Shayne Gostisbehere, K'Andre Miller, Sean Walker.
Weaknesses
  • Out-chanced at 5v5 (0.0% xG share).
Regression watch · luck-reconciliation

PDO 0.984 — running cold at 5v5; due for positive regression.

Team finishing is -9 goals below xG — finishing should rebound.

Brandon Bussi sv% 89.5% 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
Elite05
  • Shayne Gostisbehere
  • K'Andre Miller
  • Sean Walker
  • Mark Jankowski
  • Joel Nystrom
Top13
  • Sebastian Aho
  • Nikolaj Ehlers
  • Andrei Svechnikov
  • Seth Jarvis
  • Jackson Blake
  • Logan Stankoven
  • Taylor Hall
  • Jordan Staal
  • Alexander Nikishin
  • Eric Robinson
  • William Carrier
  • Mike Reilly
  • Jaccob Slavin
Middle01
  • Jordan Martinook
Depth03
  • Jalen Chatfield
  • Jesperi Kotkaniemi
  • Nicolas Deslauriers
Rate-first

Special teams

Power play
0.00 xGF/60 · 24.9% SH%
7.47GF/60
Penalty kill
0.8 Kill%
7.12GA/60
Source · MoneyPuck 5-on-5 + ST splits
Team GSAx +0.0

Goaltending

Above expected
GoaltenderGP
Brandon Bussi3989.470+0.0
Frederik Andersen3587.400+0.0
Source · GSAx = xGoals − goals, computed in-app
Roster needs · ranked
01
Bottom-6 forward depthhigh
team 62.4 vs league 81.9
-20
02
Depth defensehigh
team 70.6 vs league 87.3
-17
03
Top-6 forwardhigh
team 72.1 vs league 86.1
-14
04
Top-pair defensemanhigh
team 77.9 vs league 91.5
-14

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

Top players · adjusted impact
PlayerGPTOI/GP
Sebastian AhoC7913.8+71.60+3.7
Nikolaj EhlersL8213.0+68.30+3.3
Andrei SvechnikovR7913.3+66.60+3.2
Seth JarvisC7113.3+72.40+3.1
Jackson BlakeR8113.8+72.30+2.7
Shayne GostisbehereD5515.5+76.50+2.4
Logan StankovenC8113.5+71.00+2.3
Taylor HallL8012.7+69.10+2.3
K'Andre MillerD7218.9+75.10+2.1
Sean WalkerD8118.3+77.80+2.1
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
26/ 100 · pctile vs league

The 24th-heaviest schedule in the league84 games, 1.3 days average rest.

Total travel
40,045
road miles flown
12
Back-to-backs
2 games, 0 days off
15
3-in-4s
3 games / 4 nights
15
4-in-6s
4 games / 6 nights
5
Longest road trip
4,521 mi
Rest-days distribution
0d12
1d47
2d18
3+d6

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

Rest advantage

16 games with more rest than the opponent · 20 with fewer · 46 even.

Hardest stretches
  • 6 games in 14 days with 6,373 travel miles

    Nov 1Nov 14

  • 6 games in 11 days with 3,840 travel miles

    Oct 17Oct 27

  • 6 games in 10 days with 2,765 travel miles

    Oct 2Oct 11

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