Backcheck
Recap · SJS at SEA

Y. Askarov stands tall as the Sharks edge the Kraken

The Sharks stole one. They lost the expected-goals battle 2.19–4.62 and won anyway.

By the ModelJul 11, 2:43 PMxG: xgboost-0.758Edited for clarity
Away
SJS
San Jose Sharks
6
Home
SEA
Seattle Kraken
1
FINAL
Process vs result

The underlying story

2.19Expected goals4.62
68% share for the better side
23Shot attempts (SOG)30
2High-danger chances12
45Corsi (all attempts)70
Score-adjusted: 34% / 66%
Source · NHL play-by-play · XGBoost xG

The Sharks won 6-1, but Seattle owned the game that mattered most: they controlled 68% of expected goals and dominated shot quality. Y. Askarov made it irrelevant.

The Kraken generated 4.62 expected goals against Sharks 2.19, built on 57% of shot attempts and 12 high-danger chances to San Jose's 2. Seattle crashed relentlessly, combining higher-quality looks (0.066 xG per shot vs. 0.049) with 9 rebound opportunities — all for naught. This should have been a Kraken victory.

Instead, Y. Askarov stopped 3.62 goals above expectation. He made 29 saves on 30 shots with a 0.967 save percentage, surrendering only his expected output on high-danger chances: 92% on 12 HD shots. San Jose's goaltending wall held Seattle at arm's length.

The Kraken's collapse at the other end sealed the heist. J. Daccord gave up 3.09 goals above expected on just 20 shots (0.750 SV%), while M. Murray saw three shots and stopped two. Seattle's expected goals advantage meant nothing when they needed it most.

San Jose escaped with a smash-and-grab thanks to ruthless transition play: 4 goals from 21 rush chances, converting positional disadvantage into victory. Tyler Toffoli's wrist shot from the high slot at 3:54 of the third period exemplified their efficiency.

M. Celebrini (1G, 2A) led the assault; J. Klingberg (1G, 1A) and W. Smith (1G, 1A) added finishing touches.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
SJS1 / 2 · 0.51 xG
SEA1 / 12 · 2.47 xG
Medium dangermid-range
SJS4 / 12 · 1.24 xG
SEA0 / 12 · 1.46 xG
Low dangerperimeter & point
SJS1 / 31 · 0.45 xG
SEA0 / 46 · 0.69 xG

SJS went 4-for-12 from medium danger on 1.24 expected goals — 2.8 above expected.

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

Finishing vs expected

expectedactual
SJS
6 G · 2.19 xG · +3.8
SEA
1 G · 4.62 xG · -3.6
01234567
Goalies · GSAx (goals saved above expected)
Y. AskarovSJS
+3.6
M. MurraySEA
-0.7
J. DaccordSEA
-3.1

SJS finished +3.8 against expected, SEA -3.6 — Y. Askarov (SJS) saved 3.6 goals above expected.

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

Shot diet

goalsshots
SJS
WRIST3/21
SLAP1/3
TIP IN0/3
SNAP2/6
DEFLECTED0/0
OTHER0/12
SEA
WRIST1/33
SLAP0/7
TIP IN0/5
SNAP0/1
DEFLECTED0/2
OTHER0/22
SJS
SEA
Off the rush
4 G on 21 · 1.70 xG
0 G on 27 · 2.35 xG
Off rebounds
1 G on 1 · 0.26 xG
0 G on 9 · 1.67 xG

Wrist shots carried the volume: SJS went 3-for-21, SEA 1-for-33. SJS scored 4 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
M. Celebrini
#71 · C · SJS
1 G · 2 A · 2 SOG · 18:34 TOI · +2
J. Klingberg
#3 · D · SJS
1 G · 1 A · 1 SOG · 16:14 TOI · +2
W. Smith
#2 · C · SJS
1 G · 1 A · 3 SOG · 14:43 TOI · +2
Ranked from the box score — points first · Backcheck
What the model flagged
  • SJS stole this one. SEA owned 68% of the xG and lost.
  • SJS generated higher-quality looks than the shot total suggests.
  • Y. Askarov (SJS) stopped 3.6 goals above expected.
  • J. Daccord (SEA) gave up 3.1 goals more than expected — well below their workload.
  • SEA generated far more dangerous chances — 0.066 xG/shot vs 0.049. Quality over quantity.
  • SJS was lethal off the rush — 4 goals on 21 rush chances.
  • SEA created 9 rebound opportunities (0 converted) — crashing the net effectively.
  • SEA underperformed xG by 3.6 — wasted quality chances.
  • SJS outperformed their expected goals by 3.8 — elite finishing or lucky bounces.
  • Y. Askarov (SJS) saved 3.6 goals above expected — stole the show.
  • Y. Askarov was a wall on HD chances — 92% SV on 12 high-danger shots.
Before the game — the model's pre-game read
Preview · SJS at SEA · 10:00 PM ET

Sharks at Kraken: a genuine coin flip

By the ModelJul 11, 2:42 PMEdited for clarity
Win probability

The model's lean

51%
SEA
Model favorite
49%
51%
SJS50SEA

SEA by 2 points of win probability — effectively a coin flip. Projected score SJS 2.42.5 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

SJS← edge
edge →SEA
48.0%5v5 xG%46.0%
47.0%Corsi%45.0%
2.33xGF / 602.13
2.56xGA / 602.51
1.99Goals for / gm1.87
2.32Goals against / gm1.95
0.998PDO — luck, not skill1.011

SJS holds 4 of 6 process categories — and PDO (0.998 vs 1.011) says SEA has run hotter.

Source · MoneyPuck season tables · 5v5

The Kraken are favored at 51% win probability in a game the models project to land near 2.4-2.5 goals. This is as close to a pick'em as hockey gets.

That near-parity reflects the teams' underlying numbers. San Jose holds an edge in shot quality, with a 48.0% expected goals share against Seattle's 46.0%, and a similar small advantage in Corsi at 47.0% to 45.0%. Yet Seattle's PDO sits at 1.011—the Kraken are converting better than their shot metrics suggest—while the Sharks' 0.998 indicates they're underperforming their own chance creation.

Recent context tilts the scales. San Jose is -5 on goal differential over its last 10 games, meaning the team's underlying edge has yet to materialize into wins.

Pavol Regenda was San Jose's primary scoring threat on paper: 1.10 expected goals per 60, 5 goals, 2 high-danger chances, 16.1% shooting. He's marked inactive for this matchup. Igor Chernyshov inherits the load with 0.91 xG/60, 6 goals, 8 assists, and 15.0% shooting. Seattle counters with Shane Wright (0.77 xG/60, 8 goals, 10 assists, 4 high-danger chances) and Berkly Catton (0.68 xG/60, 6 goals, 8 assists, 5 HD goals), representing the Kraken's depth scoring punch.

J. Daccord is on the back-to-back, creating the added variable of either a backup or a fatigued starter between the pipes.

Computed danger · scouting

Players to watch

SJS
Pavol Regenda5G 1A
1.10 xG/60 · 2 HD · 16.1% sh
Igor Chernyshov6G 8A
0.91 xG/60 · 1 HD · 15.0% 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