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

Pittsburgh Penguins

5-on-5 · model-estimated

Penguins: a outshot/run-and-gun team (0.0% 5v5 xG) with league-average goaltending, flagged for regression (2 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.
50.2%
Corsi %
0.00
xGF / 60
1.012
PDO
The bounces are flattering them — expect some giveback.
Strengths
  • Elite top-end talent: Ilya Solovyov.
Weaknesses
  • Out-chanced at 5v5 (0.0% xG share).
Regression watch · luck-reconciliation

Team finishing is +18 goals above xG — shooting luck likely to cool.

Stuart Skinner 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
Elite01
  • Ilya Solovyov
Top15
  • Anthony Mantha
  • Bryan Rust
  • Erik Karlsson
  • Evgeni Malkin
  • Rickard Rakell
  • Tommy Novak
  • Egor Chinakhov
  • Justin Brazeau
  • Ryan Shea
  • Noel Acciari
  • Samuel Girard
  • Connor Clifton
  • Kevin Hayes
  • Rutger McGroarty
  • Ryan Graves
Middle08
  • Sidney Crosby
  • Ben Kindel
  • Connor Dewar
  • Blake Lizotte
  • Parker Wotherspoon
  • Elmer Soderblom
  • Ville Koivunen
  • Jack St. Ivany
Depth01
  • Kris Letang
Rate-first

Special teams

Power play
0.00 xGF/60 · 24.1% SH%
7.24GF/60
Penalty kill
0.8 Kill%
6.68GA/60
Source · MoneyPuck 5-on-5 + ST splits
Team GSAx +0.9

Goaltending

Above expected
GoaltenderGP
Stuart Skinner5088.790+0.0
Arturs Silovs3988.820+0.0
Source · GSAx = xGoals − goals, computed in-app
Roster needs · ranked
01
Depth defensehigh
team 65.3 vs league 87.3
-22
02
Bottom-6 forward depthhigh
team 60.3 vs league 81.9
-22
03
Top-6 forwardhigh
team 66.7 vs league 86.1
-19
04
Top-pair defensemanhigh
team 77.0 vs league 91.5
-15

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

Top players · adjusted impact
PlayerGPTOI/GP
Anthony ManthaR8112.4+66.40+3.0
Sidney CrosbyC6815.2+58.10+2.9
Bryan RustR7214.3+63.00+2.6
Erik KarlssonD7517.4+60.90+2.6
Evgeni MalkinC5613.7+66.40+2.5
Rickard RakellR6014.2+63.20+2.0
Tommy NovakC8212.8+61.80+1.9
Egor ChinakhovR7211.9+61.90+1.9
Justin BrazeauR6411.5+71.00+1.7
Ryan SheaD8016.0+62.10+1.5
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
74/ 100 · pctile vs league

The 9th-heaviest schedule in the league84 games, 1.3 days average rest.

Total travel
31,480
road miles flown
15
Back-to-backs
2 games, 0 days off
18
3-in-4s
3 games / 4 nights
15
4-in-6s
4 games / 6 nights
6
Longest road trip
4,035 mi
Rest-days distribution
0d15
1d42
2d20
3+d6

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

Rest advantage

26 games with more rest than the opponent · 29 with fewer · 28 even.

Hardest stretches
  • 6 games in 12 days with 4,737 travel miles

    Nov 3Nov 14

  • 6 games in 10 days with 3,080 travel miles

    Feb 28Mar 9

  • 6 games in 10 days with 2,514 travel miles

    Nov 19Nov 28

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