Backcheck
Recap · DET at SEA

Red Wings hold off the Kraken

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

By the ModelJul 11, 7:19 PMxG: xgboost-0.758Edited for clarity
Away
DET
Detroit Red Wings
4
Home
SEA
Seattle Kraken
3
FINAL
Process vs result

The underlying story

3.52Expected goals3.11
53% share for the better side
25Shot attempts (SOG)27
5High-danger chances3
61Corsi (all attempts)77
Score-adjusted: 44% / 56%
Source · NHL play-by-play · XGBoost xG

Seattle generated the game's best scoring chances—five high-danger opportunities to Detroit's three—yet lost 4-3. J. Daccord stopped all five of those premium looks. The Red Wings' advantage wasn't in volume but precision: they converted rush chances efficiently (3 goals on 29 attempts) while Seattle could not.

J. Gibson's 0.889 save percentage topped J. Daccord's 0.840, the difference between a win and a loss. Detroit held the edge in expected goals at 3.11–3.52, a tight margin that matched Seattle's 52% share of shot attempts. The game looked close on the surface.

Patrick Kane's wrist shot from the high slot in the third period turned it.

Detroit's shot quality was superior—0.058 expected goals per attempt versus Seattle's 0.040—meaning every Red Wing look carried more danger. Detroit couldn't convert its own high-danger chances (0 for 5), a drought unlikely to repeat. Seattle scored twice from low-danger spots, a reminder that the goaltender needs those. Rebound battles: Seattle crashed the net four times without converting; Detroit crashed six times and found one.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
DET0 / 5 · 1.16 xG
SEA0 / 3 · 0.60 xG
Medium dangermid-range
DET4 / 17 · 1.74 xG
SEA1 / 15 · 1.55 xG
Low dangerperimeter & point
DET0 / 39 · 0.62 xG
SEA2 / 59 · 0.95 xG

DET went 4-for-17 from medium danger on 1.74 expected goals — 2.3 above expected.

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

Finishing vs expected

expectedactual
DET
4 G · 3.52 xG · +0.5
SEA
3 G · 3.11 xG · -0.1
012345
Goalies · GSAx (goals saved above expected)
J. GibsonDET
+0.1
J. DaccordSEA
-0.5

DET finished +0.5 against expected, SEA -0.1 — J. Daccord (SEA) allowed 0.5 more goals than expected.

Source · Backcheck xG model
What they shot — and what went in

Shot diet

goalsshots
DET
WRIST2/26
SLAP0/1
TIP IN0/6
SNAP1/4
BACKHAND0/1
POKE1/2
BAT0/1
OTHER0/20
SEA
WRIST2/31
SLAP0/11
TIP IN1/3
SNAP0/2
BACKHAND0/2
POKE0/0
BAT0/0
OTHER0/28
DET
SEA
Off the rush
3 G on 29 · 2.55 xG
1 G on 34 · 2.02 xG
Off rebounds
1 G on 6 · 0.71 xG
0 G on 4 · 0.49 xG

Wrist shots carried the volume: DET went 2-for-26, SEA 2-for-31. DET scored 3 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
S. Edvinsson
#77 · D · DET
0 G · 2 A · 3 SOG · 24:48 TOI · +3
A. Larsson
#6 · D · SEA
1 G · 1 A · 2 SOG · 21:52 TOI
V. Dunn
#29 · D · SEA
0 G · 1 A · 5 SOG · 24:27 TOI · +1
Ranked from the box score — points first · Backcheck
What the model flagged
  • DET had the higher quality looks — 0.058 xG/shot vs 0.040.
  • DET couldn't convert — 0/5 on high-danger chances. That won't happen often.
  • SEA scored 2 goals from low-danger spots — the opposing goalie needs to have those.
  • DET was lethal off the rush — 3 goals on 29 rush chances.
  • SEA created 4 rebound opportunities (0 converted) — crashing the net effectively.
  • DET created 6 rebound opportunities (1 converted) — crashing the net effectively.
  • J. Daccord was a wall on HD chances — 100% SV on 5 high-danger shots.
Before the game — the model's pre-game read
Preview · DET at SEA · 10:00 PM ET

Red Wings at Kraken: a genuine coin flip

By the ModelJul 11, 7:18 PMEdited for clarity
Win probability

The model's lean

50%
DET
Model favorite
50%
50%
DET50SEA

DET by 0 points of win probability — effectively a coin flip. Projected score DET 2.42.4 SEA; 19% chance it's tied after 60.

Source · Backcheck Poisson projection · season scoring rates
Season profile · edge from the spine

Tale of the tape

DET← edge
edge →SEA
49.0%5v5 xG%46.0%
49.0%Corsi%45.0%
2.38xGF / 602.13
2.50xGA / 602.51
1.73Goals for / gm1.87
2.07Goals against / gm1.95
0.985PDO — luck, not skill1.011

DET holds 4 of 6 process categories — and PDO (0.985 vs 1.011) says SEA has run hotter.

Source · MoneyPuck season tables · 5v5

The model projects a 2.4–2.4 game with the Red Wings at 50% win probability. This is about as close to a pick'em as you'll find.

Both teams are underwater over their last 10. Seattle sits at -7 goal differential; Detroit at -9. The larger deficit masks a territorial advantage that makes the numbers confusing at first. Over the season at 5v5, Detroit controls play decisively—49.0% xG rate, 49.0% Corsi rate—yet trails Seattle in actual results. That's where PDO enters. Detroit's is 0.985, suggesting regression incoming. Seattle's is 1.011, a sign they've converted their chances at an unsustainable clip.

Detroit generates better looks. Alex DeBrincat (17 goals, 28 assists) is the primary weapon at 0.88 xG per 60 minutes, converting at 9.0%. Marco Kasper follows at 0.81 xG/60 with 7 goals and 8 assists, yet his 6.1% shooting rate suggests he's underperforming. For Seattle, Shane Wright (8 goals, 10 assists) operates at 0.77 xG/60, while Berkly Catton (6 goals, 8 assists) ranks at 0.68 xG/60 with 5 high-danger goals—an exceptional finish rate on limited looks.

The goaltending situation is a wash. P. Grubauer (Seattle) and C. Talbot (Detroit) are both on back-to-backs, inviting tired starts or backup deployments. Neither team has an edge here.

Detroit's defensive liability is Axel Sandin-Pellikka; Seattle's is Chandler Stephenson. Watch for each team to attack these pairings—a mismatch on the ice becomes a shortcut to dangerous scoring chances.

The tension is clean: Detroit drives play but hasn't finished. Seattle finishes better than their chances warrant. One team regresses to expected shooting rates and pulls ahead; the other sustains luck and steals it. That's your coin flip.

Computed danger · scouting

Players to watch

DET
Alex DeBrincat17G 28A
0.88 xG/60 · 2 HD · 9.0% sh
Marco Kasper7G 8A
0.81 xG/60 · 1 HD · 6.1% sh
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
Source · MoneyPuck skaters