Backcheck
Recap · SJS at DET

Red Wings run the Sharks off the ice on the underlying numbers

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

By the ModelJul 12, 1:02 AMxG: xgboost-0.758Edited for clarity
Away
SJS
San Jose Sharks
2
Home
DET
Detroit Red Wings
4
FINAL
Process vs result

The underlying story

2.60Expected goals5.58
68% share for the better side
22Shot attempts (SOG)25
4High-danger chances8
47Corsi (all attempts)66
Score-adjusted: 43% / 57%
Source · NHL play-by-play · XGBoost xG

The Red Wings controlled 68% of 5v5 expected goals (5.58–2.60) and 53% of shot attempts—the kind of dominance that typically produces a blowout. They won only 4-2 because Y. Askarov saved 2.58 goals above expected and Detroit underperformed its xG by 1.58. Without those offsets, this would've been a rout.

Detroit's advantage in shot quality was stark. They generated 8 high-danger chances to San Jose's 4, and their per-shot efficiency tells the story: 0.085 xG per attempt versus 0.055. The Red Wings exploited their superiority off the rush, converting 2 goals on 34 chances, and created 5 rebound opportunities, though they left all five on the table.

The outlier was Y. Askarov. With a 0.875 SV%, he saved 21 of 24 shots and beat his expected performance by 2.58 goals—a save rate that kept San Jose within striking distance. J. Gibson (DET) was solid with a 0.909 SV%, overperforming by 0.60, but Askarov's night was the difference between a comfortable result and a decisive one.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
SJS1 / 4 · 1.13 xG
DET3 / 8 · 2.71 xG
Medium dangermid-range
SJS1 / 9 · 0.98 xG
DET1 / 19 · 2.23 xG
Low dangerperimeter & point
SJS0 / 34 · 0.48 xG
DET0 / 39 · 0.63 xG

DET went 1-for-19 from medium danger on 2.23 expected goals — 1.2 left on the table.

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

Finishing vs expected

expectedactual
SJS
2 G · 2.60 xG · -0.6
DET
4 G · 5.58 xG · -1.6
0123456
Goalies · GSAx (goals saved above expected)
Y. AskarovSJS
+2.6
J. GibsonDET
+0.6

SJS finished -0.6 against expected, DET -1.6 — Y. Askarov (SJS) saved 2.6 goals above expected.

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

Shot diet

goalsshots
SJS
SNAP0/10
WRIST0/8
BACKHAND1/4
SLAP0/2
TIP IN1/3
DEFLECTED0/1
BAT0/0
OTHER0/19
DET
SNAP2/17
WRIST1/15
BACKHAND1/5
SLAP0/7
TIP IN0/4
DEFLECTED0/0
BAT0/1
OTHER0/17
SJS
DET
Off the rush
1 G on 23 · 2.09 xG
2 G on 34 · 3.13 xG
Off rebounds
0 G on 0 · 0.00 xG
0 G on 5 · 0.87 xG

Snap shots carried the volume: SJS went 0-for-10, DET 2-for-17. DET scored 2 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
L. Raymond
#23 · L · DET
0 G · 3 A · 2 SOG · 16:53 TOI · +2
M. Kasper
#92 · C · DET
1 G · 1 A · 5 SOG · 14:33 TOI · +2
J. van Riemsdyk
#21 · L · DET
0 G · 2 A · 0 SOG · 13:49 TOI · +1
Ranked from the box score — points first · Backcheck
What the model flagged
  • SJS generated higher-quality looks than the shot total suggests.
  • Y. Askarov (SJS) stopped 2.6 goals above expected.
  • DET generated far more dangerous chances — 0.085 xG/shot vs 0.055. Quality over quantity.
  • DET was lethal off the rush — 2 goals on 34 rush chances.
  • DET created 5 rebound opportunities (0 converted) — crashing the net effectively.
  • DET underperformed xG by 1.6 — wasted quality chances.
  • Y. Askarov (SJS) saved 2.6 goals above expected — stole the show.
Before the game — the model's pre-game read
Preview · SJS at DET · 7:00 PM ET

Sharks at Red Wings: a genuine coin flip

By the ModelJul 12, 1:00 AMEdited for clarity
Win probability

The model's lean

53%
DET
Model favorite
47%
53%
SJS50DET

DET by 6 points of win probability — a modest lean. Projected score SJS 2.42.6 DET; 18% 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 →DET
48.0%5v5 xG%49.0%
47.0%Corsi%49.0%
2.33xGF / 602.38
2.56xGA / 602.50
1.99Goals for / gm1.73
2.32Goals against / gm2.07
0.998PDO — luck, not skill0.985

DET holds 5 of 6 process categories — and PDO (0.998 vs 0.985) says SJS has run hotter.

Source · MoneyPuck season tables · 5v5

The model gives Detroit a 53% win probability in a projected 2.4–2.6 goal game. This is a toss-up with a marginal edge.

Detroit has the rest advantage—two days versus San Jose's four. But the Sharks' real problem is their minus-6 goal differential over the last 10 games. That deficit won't vanish with an extra practice day.

The even-strength numbers show parity. San Jose is at 48.0% expected goals with 47.0% Corsi; Detroit counters at 49.0% xG and 49.0% Corsi. PDO is 0.998 for San Jose and 0.985 for Detroit—close enough that neither side is fluking results.

Production is where division emerges. Alex DeBrincat carries 0.88 xG per 60 with 17 goals. Marco Kasper provides 0.81 xG/60 with 7 goals. San Jose's Pavol Regenda (1.10 xG/60, 5 goals, 16.1% shooting) and Igor Chernyshov (0.91 xG/60, 6 goals, 15.0% shooting) show heavier offensive volume on a tighter sample.

Defensively, Chernyshov is San Jose's liability. DeBrincat attacking that space is Detroit's clearest scoring avenue. Axel Sandin-Pellikka is Detroit's soft target; San Jose can exploit him in transition.

Both teams are stuck at 0% high-danger and 0% rebound goals. Second chances haven't materialized. The outcome hinges on clean finishes, not multiple looks.

Detroit's edge is depth: Kasper provides secondary scoring alongside DeBrincat, while San Jose concentrates production through Regenda and Chernyshov. For one game, that structural advantage justifies the 53%. Take the pick'em.

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
DET
Alex DeBrincat17G 28A
0.88 xG/60 · 2 HD · 9.0% sh
Marco Kasper7G 8A
0.81 xG/60 · 1 HD · 6.1% sh
Source · MoneyPuck skaters