Backcheck
Recap · MIN at SEA

Wild run the Kraken off the ice on the underlying numbers

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

By the ModelJul 11, 7:38 PMxG: xgboost-0.758Edited for clarity
Away
MIN
Minnesota Wild
4
Home
SEA
Seattle Kraken
1
FINAL
Process vs result

The underlying story

5.64Expected goals2.75
67% share for the better side
29Shot attempts (SOG)24
8High-danger chances4
67Corsi (all attempts)63
Score-adjusted: 50% / 50%
Source · NHL play-by-play · XGBoost xG

Minnesota's 4–1 victory was dominant by every underlying measure. The Wild controlled 67% of 5v5 expected goals (5.64–2.75), but the starkest gap was Seattle's shot profile: they held 45% of attempts (24–29) while generating only 33% of expected goals. Volume meant nothing without quality.

That quality gap extended to everything. Minnesota averaged 0.084 expected goals per shot; Seattle, 0.044. The high-danger chances split 8–4 Wild. Seattle created four rebound opportunities (converting zero) and threw bodies at the net. Minnesota created three rebounds (also zero conversions) but buried 2 goals on 33 rush chances.

Goaltending masked the margin slightly. F. Gustavsson (MIN) posted a 0.958 save percentage, stopping 1.75 goals above expected. P. Grubauer (SEA) was even more exceptional, saving 3.64 above expected on a 0.926 SV%. Both teams underperformed their xG, yet the underlying dominance still buried Seattle—the game ended as the data promised.

Vladimir Tarasenko's wrist shot from the point sealed the result.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
MIN3 / 8 · 3.20 xG
SEA1 / 4 · 0.90 xG
Medium dangermid-range
MIN0 / 16 · 1.83 xG
SEA0 / 9 · 1.05 xG
Low dangerperimeter & point
MIN1 / 43 · 0.61 xG
SEA0 / 50 · 0.80 xG

MIN went 0-for-16 from medium danger on 1.83 expected goals — 1.8 left on the table.

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

Finishing vs expected

expectedactual
MIN
4 G · 5.64 xG · -1.6
SEA
1 G · 2.75 xG · -1.8
0123456
Goalies · GSAx (goals saved above expected)
F. GustavssonMIN
+1.7
P. GrubauerSEA
+3.6

MIN finished -1.6 against expected, SEA -1.8 — P. Grubauer (SEA) saved 3.6 goals above expected.

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

Shot diet

goalsshots
MIN
WRIST1/24
SNAP1/7
TIP IN1/9
SLAP0/1
BACKHAND1/5
DEFLECTED0/0
BAT0/0
OTHER0/21
SEA
WRIST0/22
SNAP0/7
TIP IN1/5
SLAP0/8
BACKHAND0/0
DEFLECTED0/2
BAT0/1
OTHER0/18
MIN
SEA
Off the rush
2 G on 33 · 2.84 xG
1 G on 26 · 1.94 xG
Off rebounds
0 G on 3 · 0.32 xG
0 G on 4 · 0.50 xG

Wrist shots carried the volume: MIN went 1-for-24, SEA 0-for-22. MIN scored 2 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
J. Eriksson Ek
#14 · C · MIN
1 G · 2 A · 6 SOG · 21:04 TOI · +3
K. Kaprizov
#97 · L · MIN
1 G · 0 A · 3 SOG · 23:08 TOI · +1
M. Boldy
#12 · L · MIN
0 G · 1 A · 2 SOG · 22:49 TOI · +3
Ranked from the box score — points first · Backcheck
What the model flagged
  • SEA had the shot volume but the chances weren't dangerous.
  • F. Gustavsson (MIN) stopped 1.7 goals above expected.
  • MIN had the higher quality looks — 0.084 xG/shot vs 0.044.
  • MIN was lethal off the rush — 2 goals on 33 rush chances.
  • SEA created 4 rebound opportunities (0 converted) — crashing the net effectively.
  • MIN created 3 rebound opportunities (0 converted) — crashing the net effectively.
  • SEA underperformed xG by 1.8 — wasted quality chances.
  • MIN underperformed xG by 1.6 — wasted quality chances.
  • F. Gustavsson (MIN) saved 1.8 goals above expected — stole the show.
  • P. Grubauer (SEA) saved 3.6 goals above expected — stole the show.
Before the game — the model's pre-game read
Preview · MIN at SEA · 10:00 PM ET

Wild at Kraken: a genuine coin flip

By the ModelJul 11, 7:35 PMEdited for clarity
Win probability

The model's lean

53%
MIN
Model favorite
53%
47%
MIN50SEA

MIN by 6 points of win probability — a modest lean. Projected score MIN 2.52.4 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

MIN← edge
edge →SEA
52.0%5v5 xG%46.0%
48.0%Corsi%45.0%
2.55xGF / 602.13
2.40xGA / 602.51
2.04Goals for / gm1.87
1.93Goals against / gm1.95
1.007PDO — luck, not skill1.011

MIN holds 6 of 6 process categories — and PDO (1.007 vs 1.011) says SEA has run hotter.

Source · MoneyPuck season tables · 5v5

The model projects a 2.5-2.4 matchup, Minnesota favored, with the Wild at 53% win probability—that's as close to neutral as forecasts get. Both teams' recent trajectories tell you why.

Minnesota has surged to 7-2-1 over their last 10 games. Seattle has fallen apart in the same span, sitting -7 in goal differential—a decline suggesting sustained play collapse or unlucky variance in close games.

At even strength, Minnesota claims the underlying edge. The Wild post 52.0% xG to the Kraken's 46.0%, and their Corsi% advantage runs 48.0% to 45.0%. Both teams sit near neutral on PDO (MIN 1.007, SEA 1.011), meaning neither has leaned on lucky bounces.

Both starters land on back-to-backs. Watch for J. Daccord or J. Wallstedt to play in relief or appear fatigued; that variable alone could swing the game.

On offense, Matt Boldy anchors Minnesota's attack. He carries 0.89 xG/60, 22 goals, and a 13.7% shooting percentage that has converted his expected chances into actual production; he also owns 5 hard-chance goals. Robby Fabbri pairs 0.88 xG/60 with a 6.9% shooting rate, but is marked likely out. Seattle's Shane Wright checks in at 0.77 xG/60 with 8 goals and 4 hard-chance goals. Berkly Catton (0.68 xG/60, 6 goals, 5 hard-chance goals) provides secondary depth.

Minnesota's Matt Kiersted represents a defensive liability; Seattle's Chandler Stephenson is the weak link on the back end. Both squads show 0% hard-goal and 0% rebound-goal rates—a tracking gap or sign both teams are starved for true high-danger chances. Minnesota's xG% edge is narrow enough that goaltending variance, fatigue, or a single hot streak flips the result.

Computed danger · scouting

Players to watch

MIN
Matt Boldy22G 18A
0.89 xG/60 · 5 HD · 13.7% sh
Robby Fabbri2G 3A
0.88 xG/60 · 1 HD · 6.9% 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