Backcheck
Recap · SEA at STL

Kraken steal one from the Blues against the run of play

The Kraken stole one. They lost the expected-goals battle 2.23–3.79 and won anyway.

By the ModelJul 11, 3:08 PMxG: xgboost-0.758Edited for clarity
Away
SEA
Seattle Kraken
4
Home
STL
St. Louis Blues
3
FINAL / OT
Process vs result

The underlying story

2.23Expected goals3.79
63% share for the better side
30Shot attempts (SOG)19
3High-danger chances4
67Corsi (all attempts)42
Score-adjusted: 65% / 35%
Source · NHL play-by-play · XGBoost xG

The Kraken won 4–3 in overtime despite losing the expected-goals battle 3.79–2.23. St. Louis owned 63% of expected goals at 5v5, claimed 39% of shot attempts (19–30), and won the high-danger-chance count 4–3. They lost anyway. Goaltending told the tale.

P. Grubauer exceeded expectations by 0.79 goals on a 0.842 SV%. J. Hofer came up 1.8 goals short. Seattle's power play did the damage: 2 goals on 10 shots (0.46 xG). The Kraken overperformed their xG by 1.77. Shane Wright's wrist shot from the slot at 01:57 of overtime won it.

The Blues generated dangerous chances off the rush—2 goals on 20 opportunities—and controlled large stretches of the game. But St. Louis couldn't convert. Seattle did. The xG tells you one story; the scoreboard tells another.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
SEA1 / 3 · 0.62 xG
STL0 / 4 · 2.09 xG
Medium dangermid-range
SEA2 / 10 · 0.96 xG
STL2 / 12 · 1.34 xG
Low dangerperimeter & point
SEA1 / 54 · 0.64 xG
STL1 / 26 · 0.36 xG

STL went 0-for-4 from high danger on 2.09 expected goals — 2.1 left on the table.

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

Finishing vs expected

expectedactual
SEA
4 G · 2.23 xG · +1.8
STL
3 G · 3.79 xG · -0.8
012345
Goalies · GSAx (goals saved above expected)
P. GrubauerSEA
+0.8
J. HoferSTL
-1.8

SEA finished +1.8 against expected, STL -0.8 — J. Hofer (STL) allowed 1.8 more goals than expected.

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

Shot diet

goalsshots
SEA
WRIST2/29
SLAP1/7
SNAP1/4
BACKHAND0/4
BAT0/0
TIP IN0/0
DEFLECTED0/0
OTHER0/23
STL
WRIST2/21
SLAP0/4
SNAP1/3
BACKHAND0/0
BAT0/1
TIP IN0/1
DEFLECTED0/1
OTHER0/11
SEA
STL
Off the rush
1 G on 26 · 1.53 xG
2 G on 20 · 2.05 xG
Off rebounds
1 G on 2 · 0.40 xG
0 G on 1 · 0.09 xG

Wrist shots carried the volume: SEA went 2-for-29, STL 2-for-21. STL scored 2 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
E. Tolvanen
#20 · R · SEA
1 G · 2 A · 4 SOG · 15:17 TOI · +1
R. Evans
#41 · D · SEA
1 G · 1 A · 2 SOG · 17:44 TOI · +1
P. Broberg
#6 · D · STL
0 G · 1 A · 2 SOG · 25:32 TOI · +1
Ranked from the box score — points first · Backcheck
What the model flagged
  • SEA stole this one. STL owned 63% of the xG and lost.
  • SEA generated higher-quality looks than the shot total suggests.
  • J. Hofer (STL) gave up 1.8 goals more than expected — well below their workload.
  • STL generated far more dangerous chances — 0.090 xG/shot vs 0.033. Quality over quantity.
  • STL was lethal off the rush — 2 goals on 20 rush chances.
  • SEA outperformed their expected goals by 1.8 — elite finishing or lucky bounces.
  • SEA power play was dominant — 2 PPG on 10 PP shots (0.46 xG).
Before the game — the model's pre-game read
Preview · SEA at STL · 7:00 PM ET

Kraken at Blues: a genuine coin flip

By the ModelJul 11, 3:06 PMEdited 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

The model projects 2.3 to 2.5 goals per team, with St. Louis favored at 55% win probability—about as close to even odds as the NHL gets. This is not a lean; it's a toss.

The underlying metrics explain why. Seattle's season 5v5 numbers reveal a team generating 46.0% expected goals and 45.0% of the Corsi share, both well below parity. St. Louis sits at 49.0% xG and 48.0% Corsi—modest advantages that don't scream dominance. Their PDO of 1.000 tracks expected, while Seattle's 1.011 suggests fortune has played a role. Neither team has established the offensive control or defensive reliability to pull away in a single contest.

The Kraken's scoring depends on Shane Wright and Berkly Catton. Wright carries 0.77 expected goals per 60 minutes, with 8 goals and 10 assists, including 4 high-danger chances converted at a 10.4% shot rate—sustainable but not elite. Catton ranks below at 0.68 xG/60, though his 8.8% shooting on 6 goals and 8 assists suggests he's found dangerous ice. Both players operate within their offensive profiles; neither looms as a difference-maker against competent defense.

St. Louis counters with Jimmy Snuggerud and Dylan Holloway. Snuggerud leads with 0.86 xG/60 and 15 goals, backed by 22 assists and a pristine 11.9% shot rate, yet he's converted just 2 high-danger chances—a sign of volume-driven scoring rather than precision. Holloway (0.82 xG/60, 13 goals, 24 assists, 10.8% shooting) operates similarly, accounting for only 1 high-danger goal. Both thrive on shot volume, not shot quality.

The defensive picture offers little separation. Chandler Stephenson represents Seattle's weak link, while Snuggerud wears the same label for St. Louis—neither commands a matchup. Seattle has converted 0% of high-danger chances into goals and 0% of rebounds, as has St. Louis. These figures are noise this early, not systematic weakness.

If there is a tilting point, it lies in goal. Two evenly matched rosters on paper resolve through goaltending. Whoever performs better between the pipes takes the game. The model doesn't separate them otherwise, and the underlying data confirms it. This one could go either way.

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