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Motion-blurred skater in a Carolina Hurricanes sweater
← Sat, Jan 10 · the slate
Breakdown · SEA at CAR

Hurricanes run the Kraken off the ice on the underlying numbers

FinalSat, Jan 10
SEASeattle Kraken2CARCarolina Hurricanes3
The verdict · earned

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

SEA 2 · CAR 3
◆ By the ModelJul 12, 12:10 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

The Hurricanes won 3-2, yet the underlying numbers suggested a more convincing result. Carolina controlled 75% of shot attempts (36–12) and generated 64% of expected goals (3.86–2.22), possession markers that in most games produce wider margins. Yet volume did not translate to danger. The Hurricanes held the shot advantage but could not generate high-quality chances at a rate matching their territorial dominance. Kraken goaltender J. Daccord (33 saves on 36 shots) provided the margin, posting a 0.917 save percentage and stopping 0.86 more goals than expected.

High-danger chances told a closer story. Carolina led 6–4, a narrower margin than raw shot totals indicated. On the rush, the Hurricanes scored three times on 31 attempts while Seattle managed two on 24—nearly identical efficiency despite Carolina's overall control. The Hurricanes created four rebound opportunities but failed to convert any, a rarity for a team spending the evening in the Seattle zone.

William Carrier's deflection in the third period (13:50) provided the decisive goal. Backup B. Bussi made 10 of 12 saves with an 0.833 save percentage, facing far lighter traffic as a consequence of his team's shot volume.

Three Stars

  • #11 J. Staal (CAR) — 2A in 17:41
  • #19 K. Miller (CAR) — 1A in 22:23
  • #10 M. Beniers (SEA) — 1G in 19:54
The breakdown in twelve frames

Swipe it

Every number is from this page
Final · Jan 10
SEA
2
CAR
3

Hurricanes run the Kraken off the ice on the underlying numbers

Chances 2.2 – 3.9Did they deserve it? →
Did they deserve it?

The Hurricanes earned this one.

Expected goals · chance value
SEA
2.22
CAR
3.86
37% of the chances64%

The board read SEA 2, CAR 3. The chances read SEA 2.2, CAR 3.9.

Our xG model · NHL play-by-play · all situations
Luck check
CAR
−0.9
goals above expected
CAR3.86 expected · 3 scored
Expected
Scored
SEA2.22 expected · 2 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 03:23CARL. Stankoven0–1
  2. P1 14:13SEAM. Beniers1–1
  3. P3 05:56SEAB. Catton2–1
  4. P3 10:37CARJ. Martinook2–2
  5. P3 13:50CARW. Carrier2–3
NHL play-by-play · chance value from our xG model
Where the shots came from
SEA
29 shots
2
Final
83 shots
CAR
54 shots
3
SEA attackCAR attack
SEA CAR Goal
29
shots · 2 in
54
shots · 3 in
Every unblocked shot · press play to replay it
Chances by danger
SEACAR
0 / 4
0.94 xG
High danger
1 / 6
1.50 xG
2 / 7
0.84 xG
Medium
2 / 13
1.49 xG
0 / 31
0.44 xG
Low
0 / 47
0.87 xG

The Kraken went 0 for 4 from the slot.

Danger tiers by our xG model · high ≥ 20% chance
In the net
B+
J. Daccord
+0.9
SEA · 33/36
C
B. Bussi
+0.2
CAR · 10/12
The numbers, checked
BACKCHECK

Hurricanes run the Kraken 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 4–12
  1. 03:23CARL. Stankoven(K. Miller)0–1
  2. 14:13SEAM. Beniers1–1
2ndshots 4–11no goals
    3rdshots 4–13
    1. 05:56SEAB. Catton(R. Winterton)2–1
    2. 10:37CARJ. Martinook(J. Staal, S. Jarvis)2–2
    3. 13:50CARW. Carrier(J. Slavin, J. Staal)2–3

    score reads SEA–CAR

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

    The numbers

    XGBoost xG · NHL play-by-play
    3.86
    CAR chances
    Goals their shots were worth
    −0.9
    Finishing
    Goals below what those chances were worth
    0.998
    CAR puck luck
    About 1.000 — a normal night for bounces
    61.1%
    Shot attempts
    Over half — they had the puck more
    Split by club

    Who controlled the game

    2.22Expected goals3.86
    CAR 64% of the chance quality
    12Shots on goal36
    4High-danger chances6
    42All attempts (Corsi)66
    Adjusted for score: SEA 40% · CAR 60%
    Faceoffs · CAR won60%off57%neu37%def
    Source · NHL play-by-play · XGBoost xG
    How the game was won

    The danger ladder

    shotsgoalsexpected
    High dangerslot & crease
    SEA0 / 4 · 0.94 xG
    CAR1 / 6 · 1.50 xG
    Medium dangermid-range
    SEA2 / 7 · 0.84 xG
    CAR2 / 13 · 1.49 xG
    Low dangerperimeter & point
    SEA0 / 31 · 0.44 xG
    CAR0 / 47 · 0.87 xG

    SEA went 2-for-7 from medium danger on 0.84 expected goals — 1.2 above expected.

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

    Finishing vs expected

    expectedactual
    SEA
    2 G · 2.22 xG · -0.2
    CAR
    3 G · 3.86 xG · -0.9
    012345

    SEA finished -0.2 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
    SEA
    SNAP1/13
    WRIST1/8
    SLAP0/2
    TIP IN0/3
    BACKHAND0/2
    DEFLECTED0/0
    WRAP AROUND0/1
    OTHER0/13
    CAR
    SNAP2/35
    WRIST0/5
    SLAP0/6
    TIP IN0/3
    BACKHAND0/2
    DEFLECTED1/3
    WRAP AROUND0/0
    OTHER0/12
    SEA
    CAR
    Off the rush
    2 G on 24
    1.96 xG
    3 G on 31
    2.76 xG
    Off rebounds
    0 G on 1
    0.19 xG
    0 G on 4
    0.69 xG

    Snap shots carried the volume: SEA went 1-for-13, CAR 2-for-35. CAR 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 · 33/36 · .917
    +0.9
    saved above expected
    B+
    the night
    By dangerG/attxGsaved
    High danger1/61.5+0.5
    Medium2/131.5-0.5
    Low0/470.9+0.9

    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

    B. Bussi
    CAR · 10/12 · .833
    +0.2
    saved above expected
    C
    the night
    By dangerG/attxGsaved
    High danger0/40.9+0.9
    Medium2/70.8-1.2
    Low0/310.4+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

    83 shots · press play to watch the game back

    Where the shots came from

    NHL play-by-play coordinates
    SEA
    29 shots
    2
    Final
    83 shots
    CAR
    54 shots
    3
    SEA attackCAR attack
    SEA CAR Goal

    Each club shoots toward its own end — SEA 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
    J. Staal
    #11 · C · CAR
    0 G · 2 A · 1 SOG · 17:41 on ice · +2
    K. Miller
    #19 · D · CAR
    0 G · 1 A · 1 SOG · 22:23 on ice · +1
    M. Beniers
    #10 · C · SEA
    1 G · 0 A · 2 SOG · 19:54 on ice · -1
    Ranked from the box score — points first · Backcheck
    What the model said beforehand

    Before the game

    Written Sat, Jan 10
    Open the pre-game read
    Written from the numbers

    The read

    Edited for clarity
    ◆ By the ModelJul 12, 12:08 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 2.2-2.9 goal range with Carolina at 61% win probability. This is a regression play disguised as a matchup.

    Carolina owns the underlying play convincingly. At 5v5, the Hurricanes generate 56.0% of expected goals to Seattle's 46.0%. Corsi confirms it: 60.0% possession to 45.0%. This isn't a close series of territorial battles—it's relentless Carolina pressure.

    But the real edge is PDO. Carolina's sits at 0.984, meaning the Hurricanes are running cold from both shooting and save percentage standpoints. They're due to regress toward league average. Seattle's 1.011 is slightly elevated but not stretched. When Carolina normalizes, this margin expands.

    Jackson Blake and Seth Jarvis drive the volume. Blake reaches 1.06 xG per 60 with 14 goals and 19 assists, posting 2 high-danger goals on 10.9% shooting. Jarvis matches him at 0.98 xG per 60, with 17 goals and 12 assists at 11.9%. Neither is waiting on regression—both are already finishing.

    Seattle leans on Shane Wright and Berkly Catton. Wright generates 0.77 xG per 60 with 8 goals, 10 assists, and 4 high-danger chances, but his 10.4% shooting suggests room for positive variance. Catton posts 0.68 xG per 60 with 6 goals and 8 assists at 8.8%—a rate that may compress back to mean.

    Both teams share a structural quirk: 0% high-danger goal rates and 0% rebound rates. For Seattle, this exposes a lack of dirty-area scoring depth. For Carolina, volume renders it moot.

    Charles Alexis Legault defending Blake and Jarvis and Chandler Stephenson opposite Seattle's top line become the defensive pressure points. Neither backup has relief to redistribute workload.

    Seattle needs Wright to elevate efficiency or Catton to sustain an unsustainable rate. Carolina's path is simpler: territorial control plus PDO normalization collide in the same direction. The Hurricanes win on shot volume and correction.

    What the model said beforehand

    The model's lean

    CAR 61%
    61%
    CAR
    Model favorite
    39%
    61%
    SEA50CAR

    CAR by 22 points of win probability — a clear lean. Projected score SEA 2.2–2.9 CAR; 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 →CAR
    46.0%56.0%
    45.0%60.0%
    2.132.98
    2.512.31
    1.872.26
    1.951.95
    1.0110.984

    CAR holds 6 of 6 process categories — and the luck row (1.011 vs 0.984) says SEA has been getting the bounces, which tends not to last.

    Source · NHL stats API + our xG · 5v5
    Form · Last 0–10
    SEA
    8-0-2
    +17 GD · 1d rest
    CAR
    0-0-0
    +0 GD · 0d rest
    1.011
    SEA PDO
    Luck gauge · drifts to 1.000
    0.984
    CAR PDO
    Luck gauge · drifts to 1.000
    What decides it

    Keys to the game

    Where the edges live
    • The Hurricanes own the underlying play — 56.0% 5v5 xG vs 46.0%.
    • The Hurricanes drive Corsi at 60.0% — expect territorial tilt.
    Regression watch
    • The Hurricanes' PDO is 0.984 — running cold, due for positive regression.
    Things to watch
    • The Hurricanes own the underlying play — 56.0% 5v5 xG vs 46.0%.
    • The Hurricanes drive Corsi at 60.0% — 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
    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
    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

    Back to the front page