Motion-blurred skater in a Columbus Blue Jackets sweater

Breakdown · SEA at CBJ

Blue Jackets pull away from the Kraken

FinalSat, Mar 21

SEASeattle Kraken2 CBJColumbus Blue Jackets5

The verdict · earned

The Blue Jackets earned it — the game and the expected-goals battle both.

SEA 2 · CBJ 5

◆ By the ModelJul 12, 8:18 AMxG: xgboost-0.758Edited for clarityDrafted from NHL play-by-play by Backcheck's model, worded for clarity by an AI editor that may not change a number. Nobody at Backcheck was at the rink. How this works

Columbus defeated Seattle 5-2 in a game that expected goals said was nearly even. The xG split was 3.17–2.85 in Columbus's favor—just 53–47—yet the scoreline separated them by three goals.

The mismatch traced to finishing. Seattle's high-danger chances totaled 7 to Columbus's 4, but the Blue Jackets converted 2 goals from low-danger areas. Those are shots the opposing goalie needs to stop. Columbus overperformed their expected goals by 1.83; Seattle underperformed by 0.85. E. Merzlikins finished at 0.882 SV% (+0.85 vs. expected), while J. Daccord posted 0.852 SV% (−0.83 vs. expected).

Transition play defined the gap. Columbus scored 3 goals on 24 rush attempts. Seattle managed 2 on 21. Both teams weaponized the transition, but Columbus's volume advantage decided it. Shot-attempt control favored Columbus at 62% (28–17 on goal).

The incongruity is clear: Seattle generated more dangerous scoring chances, but Columbus finished their moderate opportunities. Cole Sillinger's wrist shot from the wing (P3, 17:34) typified Columbus's efficiency. The final score masks a game where underlying numbers said close and conversion said Columbus.

The breakdown in twelve frames

Swipe it

Every number is from this page

Final · Mar 21

SEA

CBJ

Blue Jackets pull away from the Kraken

Chances 2.9 – 3.2Did they deserve it? →

Did they deserve it?

Dead even on chances. The Blue Jackets took it anyway.

Expected goals · chance value

SEA

2.85

CBJ

3.17

47% of the chances53%

The board read SEA 2, CBJ 5. The chances read SEA 2.9, CBJ 3.2.

Our xG model · NHL play-by-play · all situations

Luck check

CBJ

+1.8

goals above expected

CBJ3.17 expected · 5 scored

Expected

Scored

SEA2.85 expected · 2 scored

Expected

Scored

The Blue Jackets scored 1.8 more than their chances were worth. That does not repeat.

PDO = sh% + sv% · drifts to 1.000 over a season

Every goal, in order

P1 02:48CBJD. Heinen0–1
P1 08:58CBJD. Severson0–2
P1 15:16CBJM. Olivier0–3
P1 16:17SEAV. Dunn1–3
P2 08:31SEAK. KakkoPP2–3
P2 09:33CBJK. Johnson2–4
P3 17:34CBJC. SillingerEN2–5

NHL play-by-play · chance value from our xG model

Where the shots came from

SEA

31 shots

Final

70 shots

CBJ

39 shots

SEA CBJ GoalBigger dot · more dangerous look

shots · 2 in

shots · 5 in

Every unblocked shot · press play to replay it

Chances by danger

SEACBJ

1 / 7

1.65 xG

High danger

1 / 4

1.23 xG

0 / 8

0.79 xG

Medium

2 / 11

1.28 xG

1 / 29

0.41 xG

Low

2 / 37

0.66 xG

High-danger looks: SEA 1 of 7, CBJ 1 of 4.

Danger tiers by our xG model · high ≥ 20% chance

In the net

B+

E. Merzlikins

+0.8

CBJ · 15/17

D-

J. Daccord

−0.8

SEA · 23/27

The numbers, checked

BACKCHECK

Blue Jackets pull away from the Kraken

A model, not a newsroom. Every number on these frames comes from the NHL's play-by-play and our own models. Nothing was watched, guessed or heard from anyone.

Read the full breakdown

backcheckreport.com

01 / 08 · Final

Every goal, in order

How it happened

NHL play-by-play

1stshots 7–13

02:48CBJD. Heinen(B. Jenner, Z. Werenski)0–1
08:58CBJD. Severson(C. Sillinger, Z. Werenski)0–2
15:16CBJM. Olivier(C. Sillinger, Z. Werenski)0–3
16:17SEAV. Dunn(K. Kakko, F. Gaudreau)1–3

2ndshots 5–8

08:31SEAK. Kakkopower play(E. Tolvanen, B. Montour)2–3
09:33CBJK. Johnson(C. Garland, A. Fantilli)2–4

3rdshots 5–7

17:34CBJC. Sillingerempty net(M. Olivier)2–5

score reads SEA–CBJ

Source · NHL play-by-play (api-web.nhle.com)

Process vs result

The numbers

XGBoost xG · NHL play-by-play

3.17

CBJ chances

Goals their shots were worth

+1.8

Finishing

Goals above what those chances were worth

1.051

CBJ puck luck

Above 1.000 — the bounces went their way

54.2%

Shot attempts

Over half — they had the puck more

Split by club

Who controlled the game

2.85Expected goals3.17

CBJ 53% of the chance quality

17Shots on goal28

7High-danger chances4

44All attempts (Corsi)52

Adjusted for score: SEA 53% · CBJ 47%

Faceoffs · CBJ won75%off56%neu31%def

Source · NHL play-by-play · XGBoost xG

How the game was won

The danger ladder

shotsgoalsexpected

High dangerslot & crease

SEA1 / 7 · 1.65 xG

CBJ1 / 4 · 1.23 xG

Medium dangermid-range

SEA0 / 8 · 0.79 xG

CBJ2 / 11 · 1.28 xG

Low dangerperimeter & point

SEA1 / 29 · 0.41 xG

CBJ2 / 37 · 0.66 xG

CBJ went 2-for-37 from low danger on 0.66 expected goals — 1.3 above expected.

Source · Backcheck xG model · NHL play-by-play

The luck layer

Finishing vs expected

expectedactual

SEA

2 G · 2.85 xG · -0.8

CBJ

5 G · 3.17 xG · +1.8

0123456

SEA finished -0.8 against expected, CBJ +1.8.

Source · Backcheck xG model

Shot types · rush and rebound chancesopen +

What they shot — and what went in

Shot diet

goalsshots

SEA

WRIST1/10

SNAP0/11

BACKHAND0/5

SLAP1/3

TIP IN0/1

DEFLECTED0/1

OTHER0/13

CBJ

WRIST3/16

SNAP1/13

BACKHAND0/3

SLAP1/3

TIP IN0/3

DEFLECTED0/1

OTHER0/13

SEA

CBJ

Off the rush

2 G on 21

2.43 xG

3 G on 24

2.13 xG

Off rebounds

0 G on 3

0.31 xG

0 G on 1

0.04 xG

Wrist shots carried the volume: SEA went 1-for-10, CBJ 3-for-16. CBJ scored 3 of theirs off the rush.

Source · Backcheck xG model · NHL shot types

New to these numbers?

Two things happened in this game: who created the better chances, and who put the puck in the net. They are not the same thing, and this page separates them on purpose.

The one to watch is expected goals— the best single read on who deserved to win. When it disagrees with the scoreboard, that disagreement is usually the story. Nothing here is a projection; every figure is computed from this game's play-by-play. Full glossary →

xG: Expected goals. Every shot scored by how often that exact look goes in. 2.5 xG means the chances were worth about two and a half goals.
HD: High-danger chances — shots from the slot and the crease, where shots actually become goals.
Corsi: Every shot attempt, including the ones that missed or got blocked. A rough read on who had the puck.
Adj.: Score-adjusted. Teams that trail shoot more and teams that lead sit back, so this corrects the attempt count for the scoreboard.
GSAx: Goals saved above expected. A positive number means the goalie stopped more than an average goalie would have on those shots.
PDO: Shooting % plus save % — a luck gauge. It sits near 1.000 over a season, so a game far from it usually means the bounces decided it.

Shot by shot

In the net

Graded on goals saved above expected

J. Daccord

SEA · 23/27 · .852

-0.8

saved above expected

D-

the night

By dangerG/attxGsaved

High danger1/41.2+0.2

Medium2/111.3-0.7

Low2/370.7-1.3

A+ ≥ +2.5 saved above expected · A ≥ +1.5 · B+ ≥ +0.75 · B ≥ +0.25 · C ≥ −0.25 · D ≥ −0.75 · F below −1.5

E. Merzlikins

CBJ · 15/17 · .882

+0.8

saved above expected

B+

the night

By dangerG/attxGsaved

High danger1/71.6+0.7

Medium0/80.8+0.8

Low1/290.4-0.6

A+ ≥ +2.5 saved above expected · A ≥ +1.5 · B+ ≥ +0.75 · B ≥ +0.25 · C ≥ −0.25 · D ≥ −0.75 · F below −1.5

70 shots · press play to watch the game back

Where the shots came from

NHL play-by-play coordinates

SEA

31 shots

Final

70 shots

CBJ

39 shots

SEA CBJ GoalBigger dot · more dangerous look

Each club shoots toward its own end — SEA left, CBJ right — the way you would watch it. A dot's size is how dangerous the look was, from distance and angle; it is a proxy for shot quality, not the xG model the article is written from. Hover a dot for the shooter and the clock.

Ranked from the box score

Three stars

Points first

Three stars · computed, not voted

Z. Werenski

#8 · D · CBJ

0 G · 3 A · 4 SOG · 24:07 on ice · +4

C. Sillinger

#4 · C · CBJ

1 G · 2 A · 5 SOG · 13:59 on ice · +3

K. Kakko

#84 · R · SEA

1 G · 1 A · 1 SOG · 14:58 on ice

Ranked from the box score — points first · Backcheck

What the model said beforehand

Before the game

Written Sat, Mar 21

Open the pre-game read

Written from the numbers

The read

Edited for clarity

◆ By the ModelJul 12, 8:17 AMEdited for clarityDrafted from NHL play-by-play by Backcheck's model, worded for clarity by an AI editor that may not change a number. Nobody at Backcheck was at the rink. How this works

The model projects a 2.3–2.7 goal spread favoring Columbus, with the Blue Jackets at 57% win probability. That lean is driven by what the analytics show: Columbus dominates on the underlying metrics.

Columbus owns 52.0% 5v5 expected goals against Seattle's 46.0%. The territorial advantage is even starker in Corsi—the Blue Jackets hit 51.0% to Seattle's 45.0%, meaning Columbus will spend more time in Seattle's end. Neither team has been fortunate relative to talent (Seattle's 1.011 PDO vs Columbus at 1.003), so luck isn't confounding the picture.

The edge belongs to the team that creates better chances more often. That's Columbus.

Seattle's scoring load flows through Shane Wright, who generates 0.77 expected goals per 60 minutes and has converted at a 10.4% shooting rate—high, but not unsustainably so. His four high-danger goals on just eight total have come at the expense of volume: he's picked up 10 assists in the same span. Berkly Catton runs a similar pattern, posting 0.68 xG/60 with five high-danger goals on eight total, though his 8.8% shooting is lower and suggests some regression risk.

Columbus counters with more prolific production. Boone Jenner's 0.98 xG/60 is the highest single rate in this matchup; he's posted 11 goals and 21 assists while generating high-danger chances at a more sustainable rate—just two of his goals have come from prime scoring areas. Mathieu Olivier sits at 0.89 xG/60 and has scored 12 goals on 9 assists, though his 13.3% shooting rate is elevated enough to merit caution.

The data reveals specific defensive vulnerabilities. Chandler Stephenson represents Seattle's weak link; Conor Garland is Columbus's liability on the back end.

Three Stars

Boone Jenner (CBJ) — 0.98 xG/60, 11G 21A
Shane Wright (SEA) — 0.77 xG/60, 8G 10A
Mathieu Olivier (CBJ) — 0.89 xG/60, 12G 9A

What the model said beforehand

The model's lean

CBJ 57%

57%

CBJ

Model favorite

43%

57%

SEA50CBJ

CBJ by 14 points of win probability — a modest lean. Projected score SEA 2.3–2.7 CBJ; 18% chance it's tied after 60.

Source · Backcheck Poisson projection · season scoring rates

Season rates · 5v5

Tale of the tape

NHL stats API · our xG

SEA← edge

edge →CBJ

46.0%52.0%

45.0%51.0%

2.132.63

2.512.43

1.872.12

1.951.98

1.0111.003

CBJ holds 5 of 6 process categories — and the luck row (1.011 vs 1.003) says SEA has been getting the bounces, which tends not to last.

Source · NHL stats API + our xG · 5v5

Form · No games yet

SEA

0-0-0

+0 GD · 0d rest

CBJ

0-0-0

+0 GD · 0d rest

1.011

SEA PDO

Luck gauge · drifts to 1.000

1.003

CBJ PDO

Luck gauge · drifts to 1.000

What decides it

Keys to the game

Where the edges live

The Blue Jackets own the underlying play — 52.0% 5v5 xG vs 46.0%.
The Blue Jackets drive Corsi at 51.0% — expect territorial tilt.

Things to watch

The Blue Jackets own the underlying play — 52.0% 5v5 xG vs 46.0%.
The Blue Jackets drive Corsi at 51.0% — expect territorial tilt.

Computed danger · scouting

Players to watch

NHL stats API · our xG

SEA

Shane Wright8G 10A

0.77 xG/60 · 4 HD · 10.4% sh

Berkly Catton6G 8A

0.68 xG/60 · 5 HD · 8.8% sh

CBJ

Boone Jenner11G 21A

0.98 xG/60 · 2 HD · 9.6% sh

Mathieu Olivier12G 9A

0.89 xG/60 · 1 HD · 13.3% sh

Keep going

Where to next

Back to the front page