Backcheck
Recap · SEA at STL

Blues pull away from the Kraken

The Blues won a genuine coin flip — neither side controlled the run of play.

By the ModelJul 12, 4:37 AMxG: xgboost-0.758Edited for clarity
Away
SEA
Seattle Kraken
1
Home
STL
St. Louis Blues
5
FINAL
Process vs result

The underlying story

3.12Expected goals3.24
51% share for the better side
24Shot attempts (SOG)32
4High-danger chances6
53Corsi (all attempts)55
Score-adjusted: 54% / 46%
Source · NHL play-by-play · XGBoost xG

St. Louis rolled past Seattle 5-1, but the expected goals split of 3.24–3.12 revealed a game that played far closer to even than the scoreboard suggested. The Blues' four-goal margin masked an underlying contest decided entirely by goaltending and finishing variance.

The Blues controlled 57% of shot attempts (32–24 on goal) and translated their slight possession edge into elite efficiency. In the high-danger zone, they converted 4 of 6 chances—a 67% rate that turns tight edges into decisive wins. Dylan Holloway's backhander from the wing in the third period served as the turning point, extending St. Louis's advantage when the outcome was still in question.

J. Hofer saved 2.12 goals above his expected save percentage—a margin so large it accounted for the difference between a close game and a rout. P. Grubauer, meanwhile, underperformed by 0.76, a gap large enough to swing a single game. The Blues' rush attack proved particularly lethal: two goals on 28 chances, a rate that bleeds leads slowly but relentlessly.

The Kraken underperformed their expected goals by 2.1, wasting quality chances created through effective net-front pressure. They generated four rebound opportunities but converted only one—a missed opportunity to capitalize on second chances.

The Blues' overperformance (1.76 goals above xG) and Seattle's underperformance converged on the same villain: variance. Hofer's heroics and St. Louis's finishing sharpness in key moments separated what the underlying play suggested would be a one-goal game.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
SEA0 / 4 · 0.97 xG
STL4 / 6 · 1.39 xG
Medium dangermid-range
SEA1 / 15 · 1.47 xG
STL1 / 10 · 1.08 xG
Low dangerperimeter & point
SEA0 / 34 · 0.69 xG
STL0 / 39 · 0.77 xG

STL went 4-for-6 from high danger on 1.39 expected goals — 2.6 above expected.

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

Finishing vs expected

expectedactual
SEA
1 G · 3.12 xG · -2.1
STL
5 G · 3.24 xG · +1.8
0123456
Goalies · GSAx (goals saved above expected)
P. GrubauerSEA
-0.8
J. HoferSTL
+2.1

SEA finished -2.1 against expected, STL +1.8 — J. Hofer (STL) saved 2.1 goals above expected.

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

Shot diet

goalsshots
SEA
WRIST1/19
TIP IN0/8
SNAP0/6
SLAP0/5
BACKHAND0/3
POKE0/0
OTHER0/12
STL
WRIST0/27
TIP IN0/4
SNAP3/6
SLAP0/4
BACKHAND1/1
POKE1/1
OTHER0/12
SEA
STL
Off the rush
0 G on 29 · 2.28 xG
2 G on 28 · 2.24 xG
Off rebounds
1 G on 4 · 0.52 xG
0 G on 2 · 0.14 xG

Wrist shots carried the volume: SEA went 1-for-19, STL 0-for-27. STL scored 2 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
D. Holloway
#81 · L · STL
3 G · 1 A · 5 SOG · 16:04 TOI · +4
P. Suter
#22 · C · STL
1 G · 2 A · 3 SOG · 15:33 TOI · +3
J. Faulk
#72 · D · STL
0 G · 2 A · 2 SOG · 19:41 TOI · +2
Ranked from the box score — points first · Backcheck
What the model flagged
  • J. Hofer (STL) stopped 2.1 goals above expected.
  • STL was clinical in the high-danger zone — 4/6 on HD chances (67%).
  • STL was lethal off the rush — 2 goals on 28 rush chances.
  • SEA created 4 rebound opportunities (1 converted) — crashing the net effectively.
  • STL outperformed their expected goals by 1.8 — elite finishing or lucky bounces.
  • SEA underperformed xG by 2.1 — wasted quality chances.
  • J. Hofer (STL) saved 2.1 goals above expected — stole the show.
Before the game — the model's pre-game read
Preview · SEA at STL · 8:00 PM ET

Kraken at Blues: a genuine coin flip

By the ModelJul 12, 4:36 AMEdited for clarity
Win probability

The model's lean

55%
STL
Model favorite
45%
55%
SEA50STL

STL by 10 points of win probability — a modest lean. Projected score SEA 2.32.5 STL; 19% chance it's tied after 60.

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

Tale of the tape

SEA← edge
edge →STL
46.0%5v5 xG%49.0%
45.0%Corsi%48.0%
2.13xGF / 602.34
2.51xGA / 602.40
1.87Goals for / gm2.00
1.95Goals against / gm2.12
1.011PDO — luck, not skill1.000

STL holds 5 of 6 process categories — and PDO (1.011 vs 1.000) says SEA has run hotter.

Source · MoneyPuck season tables · 5v5

This matchup reads as a genuine toss-up. The projection model calls for 2.3 to 2.5 Seattle goals, with St. Louis favored at 55% win probability—margins so thin that execution determines everything.

St. Louis owns a structural advantage. They generate 49.0% expected goal share at 5v5 versus Seattle's 46.0%, and control 48.0% of shot attempts against 45.0%. Seattle's 1.011 PDO suggests performance running ahead of talent, while St. Louis's 1.000 aligns perfectly with their underlying output—they are what their metrics promise.

The scoring profiles diverge sharply. Seattle leans on Shane Wright at 0.77 xG/60, with 8 goals and 10 assists while shooting 10.4% and harvesting 4 high-danger goals. Berkly Catton supplies 0.68 xG/60 across 6 goals and 8 assists, shooting 8.8% despite 5 high-danger tallies. St. Louis counters with Jimmy Snuggerud, who converts at 11.9% on 0.86 xG/60, producing 15 goals and 22 assists from just 2 high-danger chances—an efficiency that amplifies volume into dominance. Dylan Holloway adds 0.82 xG/60 at 10.8% shooting, with 13 goals and 24 assists and 1 high-danger goal.

Both teams operate tight defensive structures: 0% of their goals stem from high-danger situations and 0% from rebounds, signaling either disciplined net-front play or perimeter-heavy shot generation. Chandler Stephenson represents Seattle's defensive liability; St. Louis flags Jimmy Snuggerud as a comparable weakness. The outcome hinges on goaltending—whichever starter plays closer to his underlying talent advances.

Computed danger · scouting

Players to watch

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
STL
Jimmy Snuggerud15G 22A
0.86 xG/60 · 2 HD · 11.9% sh
Dylan Holloway13G 24A
0.82 xG/60 · 1 HD · 10.8% sh
Source · MoneyPuck skaters