Backcheck
Recap · TOR at SEA

Kraken pull away from the Maple Leafs

The Kraken stole one. They lost the expected-goals battle 3.98–2.30 and won anyway.

By the ModelJul 12, 3:21 AMxG: xgboost-0.758Edited for clarity
Away
TOR
Toronto Maple Leafs
2
Home
SEA
Seattle Kraken
5
FINAL
Process vs result

The underlying story

3.98Expected goals2.30
63% share for the better side
31Shot attempts (SOG)22
5High-danger chances3
65Corsi (all attempts)38
Score-adjusted: 68% / 33%
Source · NHL play-by-play · XGBoost xG

Seattle won a game the Maple Leafs deserved to win. The Kraken pulled out a 5-2 victory while generating only 37% of expected goals at 5v5, losing the xG battle 2.30–3.98. Toronto had the better play, the better chances—and the worse result.

Seattle controlled the scoreboard through sheer efficiency. They absorbed a 22-to-31 shot-attempt disadvantage and converted high-danger chances at an impossible rate: 3 goals on 5 such chances versus Toronto's 0-for-5. The Kraken also struck 3 times on the rush and buried 2 goals from low-danger spots that no goaltender expects to stop.

J. Daccord saved 1.98 goals above expected—the margin between a competitive game and a rout. A. Stolarz stopped 17 of 21, but his workload fell well short of what his underlying metrics earned; he underperformed his xG concession by 1.70. Toronto's collapse was not their goaltender's fault. It was that they played the better game without finishing it.

The Maple Leafs' precision broke down under pressure. Despite 63% of expected goals and 6 rebound opportunities, they converted only 2 goals—both from low-percentage areas. That underperformance by 1.98 goals against xG doesn't survive often. The Kraken, by contrast, overperformed by 2.70, riding finishing or fortune to a win that left their underlying numbers deep in the red.

Jared McCann's wrist shot from the wing (17:23, third period) was the turning point, but Seattle had already stolen a script Toronto wrote first.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
TOR0 / 5 · 1.19 xG
SEA1 / 3 · 0.93 xG
Medium dangermid-range
TOR0 / 18 · 2.01 xG
SEA3 / 8 · 0.97 xG
Low dangerperimeter & point
TOR2 / 42 · 0.78 xG
SEA1 / 27 · 0.40 xG

SEA went 3-for-8 from medium danger on 0.97 expected goals — 2.0 above expected.

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

Finishing vs expected

expectedactual
TOR
2 G · 3.98 xG · -2.0
SEA
5 G · 2.30 xG · +2.7
0123456
Goalies · GSAx (goals saved above expected)
A. StolarzTOR
-1.7
J. DaccordSEA
+2.0

TOR finished -2.0 against expected, SEA +2.7 — J. Daccord (SEA) saved 2.0 goals above expected.

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

Shot diet

goalsshots
TOR
WRIST1/25
SNAP0/10
TIP IN0/6
BACKHAND0/5
SLAP1/2
WRAP AROUND0/2
OTHER0/15
SEA
WRIST4/18
SNAP0/1
TIP IN0/2
BACKHAND1/3
SLAP0/5
WRAP AROUND0/0
OTHER0/9
TOR
SEA
Off the rush
1 G on 33 · 2.77 xG
3 G on 14 · 1.18 xG
Off rebounds
0 G on 6 · 0.68 xG
1 G on 4 · 0.46 xG

Wrist shots carried the volume: TOR went 1-for-25, SEA 4-for-18. SEA scored 3 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
B. Montour
#62 · D · SEA
1 G · 1 A · 2 SOG · 21:39 TOI · +4
J. McCann
#19 · L · SEA
1 G · 1 A · 1 SOG · 16:12 TOI · +1
S. Wright
#51 · C · SEA
2 G · 0 A · 2 SOG · 15:41 TOI · +2
Ranked from the box score — points first · Backcheck
What the model flagged
  • SEA won despite being outplayed by xG (37%). Goaltending or finishing carried them.
  • J. Daccord (SEA) stopped 2.0 goals above expected.
  • A. Stolarz (TOR) gave up 1.7 goals more than expected — well below their workload.
  • TOR couldn't convert — 0/5 on high-danger chances. That won't happen often.
  • TOR scored 2 goals from low-danger spots — the opposing goalie needs to have those.
  • SEA was lethal off the rush — 3 goals on 14 rush chances.
  • SEA created 4 rebound opportunities (1 converted) — crashing the net effectively.
  • TOR created 6 rebound opportunities (0 converted) — crashing the net effectively.
  • SEA outperformed their expected goals by 2.7 — elite finishing or lucky bounces.
  • TOR underperformed xG by 2.0 — wasted quality chances.
  • J. Daccord (SEA) saved 2.0 goals above expected — stole the show.
Before the game — the model's pre-game read
Preview · TOR at SEA · 10:00 PM ET

Maple Leafs at Kraken: a genuine coin flip

By the ModelJul 12, 3:18 AMEdited for clarity
Win probability

The model's lean

53%
SEA
Model favorite
47%
53%
TOR50SEA

SEA by 6 points of win probability — a modest lean. Projected score TOR 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

TOR← edge
edge →SEA
46.0%5v5 xG%46.0%
45.0%Corsi%45.0%
2.24xGF / 602.13
2.67xGA / 602.51
2.09Goals for / gm1.87
2.52Goals against / gm1.95
1.002PDO — luck, not skill1.011

SEA holds 4 of 6 process categories — and PDO (1.002 vs 1.011) says SEA has run hotter.

Source · MoneyPuck season tables · 5v5

The model projects a 2.4-to-2.5 goal game with Seattle at 53% win probability. This is about as close to a pick'em as analytics get.

On paper, these teams are twins. Both operate at 46.0% expected goals share and 45.0% Corsi percentage at 5v5. The only meaningful divergence: Seattle's PDO of 1.011 edges Toronto's 1.002, suggesting the Kraken benefit slightly from puck luck—the kind of margin that typically evaporates.

Toronto's recent results tell a darker story. The Leafs sit at -12 goal differential over their last 10 games—a brutal proxy for team function, even if underlying metrics look reasonable. Both teams also navigate goaltending fatigue. P. Grubauer is on a back-to-back, as is J. Woll. Expect either a backup or a noticeably tired starter.

Toronto's case depends on elite execution. Auston Matthews generates 1.10 expected goals per 60 minutes, has buried 17, and converts at 10.6%—that's elite confidence. John Tavares (0.91 xG/60, 15 goals, 12.4% shooting) provides secondary scoring at a level most teams would trade for. Seattle counters with Shane Wright (0.77 xG/60, 8 goals) and Berkly Catton (0.68 xG/60, 6 goals), who finish opportunistically but lack Matthews' ceiling.

Here's the wrinkle: neither team scores from high-danger chances or rebounds. Both sit at 0% for these categories. Instead, they convert first-shot opportunities and medium-danger looks with unusual efficiency. This rewards precise play and punishes mistakes. Bo Groulx is Toronto's defensive weak link; Chandler Stephenson exposes Seattle similarly. Whoever executes cleaner beats a team the numbers insist is genuinely, frustratingly even.

Computed danger · scouting

Players to watch

TOR
Auston Matthews17G 13A
1.10 xG/60 · 1 HD · 10.6% sh
John Tavares15G 24A
0.91 xG/60 · 3 HD · 12.4% 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