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

Columbus Blue Jackets

5-on-5 · model-estimated

Blue Jackets: a outshot/run-and-gun team (0.0% 5v5 xG) with league-average goaltending, flagged for regression (1 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.
51.1%
Corsi %
0.00
xGF / 60
1.003
PDO
Luck is about neutral; the record is earned.
Strengths
  • Elite top-end talent: Zach Werenski, Damon Severson, Mathieu Olivier.
Weaknesses
  • Out-chanced at 5v5 (0.0% xG share).
  • Leaky penalty kill (76% kill rate).
Regression watch · luck-reconciliation

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

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

Talent tiers · model impact
Elite03
  • Zach Werenski
  • Damon Severson
  • Mathieu Olivier
Top07
  • Kirill Marchenko
  • Charlie Coyle
  • Mason Marchment
  • Denton Mateychuk
  • Dmitri Voronkov
  • Ivan Provorov
  • Danton Heinen
Middle05
  • Adam Fantilli
  • Boone Jenner
  • Sean Monahan
  • Cole Sillinger
  • Miles Wood
Depth09
  • Conor Garland
  • Kent Johnson
  • Zachary Aston-Reese
  • Brendan Gaunce
  • Jake Christiansen
  • Dante Fabbro
  • Isac Lundestrm
  • Egor Zamula
  • Erik Gudbranson
Rate-first

Special teams

Power play
0.00 xGF/60 · 18.9% SH%
5.67GF/60
Penalty kill
0.8 Kill%
8.62GA/60
Source · MoneyPuck 5-on-5 + ST splits
Team GSAx +0.0

Goaltending

Above expected
GoaltenderGP
Jet Greaves5590.770+0.0
Elvis Merzlikins3088.300+0.0
Source · GSAx = xGoals − goals, computed in-app
Roster needs · ranked
01
Depth defensehigh
team 51.4 vs league 87.3
-36
02
Bottom-6 forward depthhigh
team 48.4 vs league 81.9
-34
03
Top-6 forwardhigh
team 69.7 vs league 86.1
-16
04
Top-pair defensemanmoderate
team 85.7 vs league 91.5
-6

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

Top players · adjusted impact
PlayerGPTOI/GP
Zach WerenskiD7521.2+87.20+4.4
Kirill MarchenkoR7615.1+63.00+2.9
Charlie CoyleC8213.1+73.20+2.9
Adam FantilliC8215.5+59.50+2.4
Mason MarchmentL6814.6+68.00+2.2
Damon SeversonD7118.7+84.20+2.1
Denton MateychukD7516.5+74.00+1.8
Dmitri VoronkovL6311.6+73.40+1.7
Mathieu OlivierR6113.0+76.50+1.5
Ivan ProvorovD8219.8+64.80+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

AVERAGE
Load index
68/ 100 · pctile vs league

The 11th-heaviest schedule in the league84 games, 1.3 days average rest.

Total travel
37,881
road miles flown
13
Back-to-backs
2 games, 0 days off
16
3-in-4s
3 games / 4 nights
15
4-in-6s
4 games / 6 nights
4
Longest road trip
3,146 mi
Rest-days distribution
0d13
1d48
2d13
3+d9

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

Rest advantage

21 games with more rest than the opponent · 19 with fewer · 43 even.

Hardest stretches
  • 6 games in 10 days with 4,908 travel miles

    Feb 11Feb 20

  • 6 games in 10 days with 3,665 travel miles

    Jan 15Jan 24

  • 6 games in 11 days with 3,560 travel miles

    Jan 2Jan 12

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