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Motion-blurred skater in a Carolina Hurricanes sweater
← Thu, Oct 9 · the slate
Breakdown · NJD at CAR

Hurricanes run the Devils off the ice on the underlying numbers

FinalThu, Oct 9
NJDNew Jersey Devils3CARCarolina Hurricanes6
The verdict · earned

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

NJD 3 · CAR 6
◆ By the ModelJun 16, 2:12 PMxG: 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

Carolina's 6–3 victory over New Jersey landed on the scoreboard, but the truly damning statistic lay underneath: the Devils generated zero high-danger chances yet still netted three goals. This paradox—complete slot dominance by the Hurricanes paired with a seemingly competitive final score—reveals how lopsided the underlying match truly was.

Carolina controlled 69% of expected goals (5.09–2.33) and 60% of shot attempts (33–22), a depth of dominance the scoreline barely captures. New Jersey overperformed their 2.33 xG to score three; Carolina overperformed their 5.09 xG to score six. Both teams exceeded expectation, but only one had created the circumstances to begin with.

Carolina's attack was surgical. They generated 0.070 expected goals per shot compared to New Jersey's 0.052, a quality edge that compounded their volume advantage. The Hurricanes scored three goals from low-danger positions—spots most teams fail to cash. Off the rush, Carolina converted 5 goals on 36 chances while New Jersey converted 3 on 25. Both teams found success in transition, but only one dictated play across sixty minutes.

Goaltending played a supporting role. F. Andersen stopped 19 of 22 shots (0.864 SV%), outperforming expectation by 0.67 goals. J. Markstrom faced heavier traffic, saving 27 of 32 (0.844 SV%), and performed to expectation given the volume differential.

The competitive scoreline masked Hurricanes dominance across nearly every dimension. Carolina didn't just win; they ran the Devils off the ice, and the underlying numbers leave no doubt.

The breakdown in twelve frames

Swipe it

Every number is from this page
Final · Oct 9
NJD
3
CAR
6

Hurricanes run the Devils off the ice on the underlying numbers

Chances 2.3 – 5.1Did they deserve it? →
Did they deserve it?

The Hurricanes earned this one.

Expected goals · chance value
NJD
2.33
CAR
5.09
31% of the chances69%

The board read NJD 3, CAR 6. The chances read NJD 2.3, CAR 5.1.

Our xG model · NHL play-by-play · all situations
Luck check
CAR
+0.9
goals above expected
CAR5.09 expected · 6 scored
Expected
Scored
NJD2.33 expected · 3 scored
Expected
Scored

Both sides finished close to what their chances were worth. This one was earned on the ice.

PDO = sh% + sv% · drifts to 1.000 over a season
Every goal, in order
  1. P1 04:06CART. Hall0–1
  2. P2 08:15NJDD. Hamilton1–1
  3. P2 09:23CARK. Miller1–2
  4. P2 13:54NJDC. Glass2–2
  5. P3 10:21CARK. MillerPP2–3
  6. P3 11:38NJDJ. Bratt3–3
  7. P3 17:17CARS. Jarvis3–4
+2 more on the full breakdown
NHL play-by-play · chance value from our xG model
Where the shots came from
NJD
32 shots
3
Final
86 shots
CAR
54 shots
6
NJD attackCAR attack
NJD CAR Goal
32
shots · 3 in
54
shots · 6 in
Every unblocked shot · press play to replay it
Chances by danger
NJDCAR
0 / 0
0.00 xG
High danger
1 / 9
2.47 xG
3 / 17
1.89 xG
Medium
2 / 16
1.78 xG
0 / 28
0.44 xG
Low
3 / 48
0.83 xG

High-danger looks: NJD 0 of 0, CAR 1 of 9.

Danger tiers by our xG model · high ≥ 20% chance
In the net
C
J. Markstrom
+0.1
NJD · 27/32
D
F. Andersen
−0.7
CAR · 19/22
The numbers, checked
BACKCHECK

Hurricanes run the Devils off the ice on the underlying numbers

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 6–9
  1. 04:06CART. Hall(S. Gostisbehere, A. Nikishin)0–1
2ndshots 11–14
  1. 08:15NJDD. Hamilton(J. Bratt, J. Hughes)1–1
  2. 09:23CARK. Miller(W. Carrier, J. Martinook)1–2
  3. 13:54NJDC. Glass(L. Hughes)2–2
3rdshots 5–10
  1. 10:21CARK. Millerpower play(S. Aho, J. Blake)2–3
  2. 11:38NJDJ. Bratt(B. Pesce, L. Hughes)3–3
  3. 17:17CARS. Jarvis(S. Aho, S. Gostisbehere)3–4
  4. 19:05CARS. Jarvisempty net3–5
  5. 19:47CARE. Robinson(T. Hall, J. Kotkaniemi)3–6

score reads NJD–CAR

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

The numbers

XGBoost xG · NHL play-by-play
5.09
CAR chances
Goals their shots were worth
+0.9
Finishing
Goals above what those chances were worth
1.016
CAR puck luck
About 1.000 — a normal night for bounces
61.9%
Shot attempts
Over half — they had the puck more
Split by club

Who controlled the game

2.33Expected goals5.09
CAR 69% of the chance quality
22Shots on goal33
0High-danger chances9
45All attempts (Corsi)73
Adjusted for score: NJD 40% · CAR 60%
Faceoffs · CAR won62%off50%neu47%def
Source · NHL play-by-play · XGBoost xG
How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
NJD0 / 0 · 0.00 xG
CAR1 / 9 · 2.47 xG
Medium dangermid-range
NJD3 / 17 · 1.89 xG
CAR2 / 16 · 1.78 xG
Low dangerperimeter & point
NJD0 / 28 · 0.44 xG
CAR3 / 48 · 0.83 xG

CAR went 3-for-48 from low danger on 0.83 expected goals — 2.2 above expected.

Source · Backcheck xG model · NHL play-by-play
The luck layer

Finishing vs expected

expectedactual
NJD
3 G · 2.33 xG · +0.7
CAR
6 G · 5.09 xG · +0.9
01234567

NJD finished +0.7 against expected, CAR +0.9.

Source · Backcheck xG model
Shot types · rush and rebound chancesopen +
What they shot — and what went in

Shot diet

goalsshots
NJD
SNAP2/10
WRIST0/13
SLAP0/1
BACKHAND1/3
TIP IN0/4
WRAP AROUND0/1
DEFLECTED0/0
OTHER0/13
CAR
SNAP1/26
WRIST1/10
SLAP1/8
BACKHAND0/5
TIP IN2/4
WRAP AROUND0/0
DEFLECTED1/1
OTHER0/19
NJD
CAR
Off the rush
3 G on 25
1.93 xG
5 G on 36
3.80 xG
Off rebounds
0 G on 1
0.04 xG
0 G on 2
0.32 xG

Snap shots carried the volume: NJD went 2-for-10, CAR 1-for-26. CAR scored 5 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. Markstrom
NJD · 27/32 · .844
+0.1
saved above expected
C
the night
By dangerG/attxGsaved
High danger1/92.5+1.5
Medium2/161.8-0.2
Low3/480.8-2.2

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

F. Andersen
CAR · 19/22 · .864
-0.7
saved above expected
D
the night
By dangerG/attxGsaved
Medium3/171.9-1.1
Low0/280.4+0.4

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

86 shots · press play to watch the game back

Where the shots came from

NHL play-by-play coordinates
NJD
32 shots
3
Final
86 shots
CAR
54 shots
6
NJD attackCAR attack
NJD CAR Goal

Each club shoots toward its own end — NJD left, CAR 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
S. Aho
#20 · C · —
0 G · 2 A · 3 SOG · 21:39 on ice
S. Jarvis
#24 · R · —
2 G · 0 A · 3 SOG · 21:12 on ice · +1
L. Hughes
#43 · D · —
0 G · 2 A · 2 SOG · 20:46 on ice
Ranked from the box score — points first · Backcheck
What the model said beforehand

Before the game

Written Thu, Oct 9
Open the pre-game read
Written from the numbers

The read

Edited for clarity
◆ By the ModelSep 22, 12:22 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 favors Carolina at 57% win probability in a projected 3.0 - 3.5 game. The Hurricanes own the underlying play outright.

Carolina's edge sits in shot creation and territorial control. The Hurricanes post 55.7% expected goals and 59.1% Corsi at 5v5, versus New Jersey's 50.7% xG and 51.3% Corsi. That territorial dominance should translate to sustained offensive pressure and defensive containment.

The decisive matchup tilts toward Carolina. Timo Meier drives the Devils' offense with 1.08 xG/60, 13 goals, and 3 HD goals; New Jersey's task is asking Jackson Blake (1.06 xG/60, 14 goals, 2 HD goals) to replicate that leverage elsewhere. For Carolina, Blake becomes the shutdown assignment—his 10.9% shooting and 19 assists make him a precision threat. Meanwhile, Meier's 6.7% shooting suggests variance: he's scoring at league-average efficiency despite elite underlying play, a recipe for regression to higher rates if the Hurricanes' model-projected dominance holds.

Jack Hughes reinforces New Jersey's secondary offense at 0.88 xG/60 with 18 goals and an 11.5% shooting rate. Seth Jarvis answers for Carolina at 0.98 xG/60, 17 goals, and matching efficiency. Neither is the edge player; Meier and Blake carry the true accountability.

Both teams' PDOs tell the deeper story. Carolina runs 0.984—cold, due for positive regression in shooting and goaltending luck. New Jersey sits at 0.971, equally cold. This game strips to its modeling truth: the team with superior underlying play is slightly underperforming relative to its shot and save data, while the inferior team is doing the same. Regression would favor whichever club's model projections survive the variance. The Hurricanes' 55.7% xG gives them the margin to survive it.

Johnathan Kovacevic profiles as New Jersey's defensive weak link. Charles Alexis Legault occupies the same role for Carolina.

Season rates in this preview are from 2025-26 — this season's sample isn't live yet.

What the model said beforehand

The model's lean

CAR 57%
57%
CAR
Model favorite
43%
57%
NJD50CAR

CAR by 14 points of win probability — a modest lean. Projected score NJD 3.0–3.5 CAR; 16% 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
NJD← edge
edge →CAR
50.7%55.7%
51.3%59.1%
3.163.59
3.072.85
2.763.55
3.092.88
0.9710.984

CAR holds 6 of 6 process categories — and the luck row (0.971 vs 0.984) says CAR has been getting the bounces, which tends not to last.

Source · NHL stats API + our xG · 5v5
Form · No games yet
NJD
0-0-0
+0 GD · 0d rest
CAR
0-0-0
+0 GD · 0d rest
0.971
NJD PDO
Luck gauge · drifts to 1.000
0.984
CAR PDO
Luck gauge · drifts to 1.000
What decides it

Keys to the game

TACTICALCAR

Shutdown Assignment: Hurricanes

Key matchup: Neutralize Timo Meier (13G, 1.08 xG/60, 3 HD goals)

Key matchup: Neutralize Timo Meier (13G, 1.08 xG/60, 3 HD goals)

TACTICALNJD

Shutdown Assignment: Devils

Key matchup: Neutralize Jackson Blake (14G, 1.06 xG/60, 2 HD goals)

Key matchup: Neutralize Jackson Blake (14G, 1.06 xG/60, 2 HD goals)

WARNINGNJD

Exploitable minutes: Johnathan Kovacevic

Johnathan Kovacevic is on ice for 2.72 xGA/60 and 26 high-danger shots against this season.

Hunt matchups against Johnathan Kovacevic's shifts with the top line.

WARNINGCAR

Exploitable minutes: Charles Alexis Legault

Charles Alexis Legault is on ice for 2.69 xGA/60 and 9 high-danger shots against this season.

Hunt matchups against Charles Alexis Legault's shifts with the top line.

Where the edges live
  • The Hurricanes own the underlying play — 55.7% 5v5 xG vs 50.7%.
  • The Hurricanes drive Corsi at 59.1% — expect territorial tilt.
Regression watch
  • The Hurricanes' PDO is 0.984 — running cold, due for positive regression.
  • The Devils' PDO is 0.971 — running cold, due for positive regression.
Things to watch
  • The Hurricanes own the underlying play — 55.7% 5v5 xG vs 50.7%.
  • The Hurricanes drive Corsi at 59.1% — expect territorial tilt.
  • The Hurricanes' PDO is 0.984 — running cold, due for positive regression.
Computed danger · scouting

Players to watch

NHL stats API · our xG
NJD
Timo Meier13G 15A
1.08 xG/60 · 3 HD · 6.7% sh
Jack Hughes18G 17A
0.88 xG/60 · 1 HD · 11.5% sh
CAR
Jackson Blake14G 19A
1.06 xG/60 · 2 HD · 10.9% sh
Seth Jarvis17G 12A
0.98 xG/60 · 1 HD · 11.9% sh
Keep going

Where to next

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