Backcheck
Recap · STL at SJS

Sharks hold off the Blues

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

By the ModelJul 12, 9:41 AMxG: xgboost-0.758Edited for clarity
Away
STL
St. Louis Blues
4
Home
SJS
San Jose Sharks
5
FINAL
Process vs result

The underlying story

2.87Expected goals3.79
57% share for the better side
26Shot attempts (SOG)29
4High-danger chances6
52Corsi (all attempts)56
Score-adjusted: 51% / 49%
Source · NHL play-by-play · XGBoost xG

The Sharks held off the Blues 5–4 despite matching them in rush goals: each team scored four on identical 27-chance rushes. The separation came via San Jose's power play efficiency—3 PPG on 1.05 xG versus 2 PPG on 0.49 xG—and their 57% xG share (3.79–2.87), which converted a competitive game into a one-goal win.

High-danger chances favored San Jose 6–4, reflecting their ability to generate scoring opportunities from the most dangerous areas. Both teams significantly overperformed their expected goals—San Jose by 1.21, St. Louis by 1.13—indicating that variance and shot execution played outsized roles in deciding the game.

Adam Gaudette's wrist shot from the top of the circles (P3, 19:38) proved decisive. Y. Askarov stopped 22 of 26 shots (0.846 SV%) to keep San Jose in control, while J. Hofer's 24 saves on 29 shots (0.828 SV%) underperformed expected save rate by 1.21 goals.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
STL0 / 4 · 0.94 xG
SJS2 / 6 · 1.64 xG
Medium dangermid-range
STL2 / 12 · 1.41 xG
SJS2 / 15 · 1.67 xG
Low dangerperimeter & point
STL2 / 36 · 0.53 xG
SJS1 / 35 · 0.48 xG

STL went 2-for-36 from low danger on 0.53 expected goals — 1.5 above expected.

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

Finishing vs expected

expectedactual
STL
4 G · 2.87 xG · +1.1
SJS
5 G · 3.79 xG · +1.2
0123456
Goalies · GSAx (goals saved above expected)
J. HoferSTL
-1.2
Y. AskarovSJS
-1.1

STL finished +1.1 against expected, SJS +1.2 — J. Hofer (STL) allowed 1.2 more goals than expected.

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

Shot diet

goalsshots
STL
WRIST3/27
SLAP0/3
BACKHAND0/3
TIP IN1/2
SNAP0/0
OTHER0/17
SJS
WRIST4/22
SLAP1/8
BACKHAND0/4
TIP IN0/4
SNAP0/1
OTHER0/17
STL
SJS
Off the rush
4 G on 27 · 2.05 xG
4 G on 27 · 2.64 xG
Off rebounds
0 G on 4 · 0.51 xG
1 G on 4 · 0.85 xG

Wrist shots carried the volume: STL went 3-for-27, SJS 4-for-22. STL scored 4 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
A. Wennberg
#21 · C · SJS
2 G · 1 A · 2 SOG · 19:57 TOI · -2
M. Celebrini
#71 · C · SJS
2 G · 1 A · 5 SOG · 19:45 TOI · +1
W. Smith
#2 · C · SJS
0 G · 2 A · 3 SOG · 19:51 TOI · +1
Ranked from the box score — points first · Backcheck
What the model flagged
  • J. Hofer (STL) gave up 1.2 goals more than expected — well below their workload.
  • STL scored 2 goals from low-danger spots — the opposing goalie needs to have those.
  • SJS was lethal off the rush — 4 goals on 27 rush chances.
  • STL was lethal off the rush — 4 goals on 27 rush chances.
  • SJS created 4 rebound opportunities (1 converted) — crashing the net effectively.
  • STL created 4 rebound opportunities (0 converted) — crashing the net effectively.
  • SJS power play was dominant — 3 PPG on 7 PP shots (1.05 xG).
  • STL power play was dominant — 2 PPG on 7 PP shots (0.49 xG).
Before the game — the model's pre-game read
Preview · STL at SJS · 10:00 PM ET

Blues at Sharks: a genuine coin flip

By the ModelJul 12, 9:39 AMEdited for clarity
Win probability

The model's lean

50%
SJS
Model favorite
50%
50%
STL50SJS

SJS by 0 points of win probability — effectively a coin flip. Projected score STL 2.52.5 SJS; 19% chance it's tied after 60.

Source · Backcheck Poisson projection · season scoring rates
Season profile · edge from the spine

Tale of the tape

STL← edge
edge →SJS
49.0%5v5 xG%48.0%
48.0%Corsi%47.0%
2.34xGF / 602.33
2.40xGA / 602.56
2.00Goals for / gm1.99
2.12Goals against / gm2.32
1.000PDO — luck, not skill0.998

STL holds 6 of 6 process categories — and PDO (1.000 vs 0.998) says STL has run hotter.

Source · MoneyPuck season tables · 5v5

The model projects a 2.5–2.5 game with the Sharks at 50% win probability. This is a perfect pick'em.

The Blues are 7-1-2 over their last 10; the Sharks sit at -15 goal differential in the same span. Over the full season, though, the gulf vanishes. At 5v5, STL leads in xG% (49.0% to 48.0%) and Corsi% (48.0% to 47.0%)—margins indistinguishable from noise. Both teams' PDOs sit at or near 1.000, meaning neither has been luckier than expected.

What separates them is individual shot creation. Jimmy Snuggerud anchors St. Louis at 0.86 xG/60 with 15 goals and 22 assists; his 11.9% shooting rate is sustainable for a high-volume player. Dylan Holloway mirrors him at 0.82 xG/60 with 13 goals, 24 assists, and 10.8% shooting. This duo drives the Blues.

San Jose's offense centers on Pavol Regenda (1.10 xG/60, 5 goals, 1 assist, 16.1% shooting) and Igor Chernyshov (0.91 xG/60, 6 goals, 8 assists, 15.0% shooting). Regenda generates the highest expected goals per 60 among the four but is marked as likely inactive. Should he sit, Chernyshov becomes the primary scorer.

Close team metrics, recent momentum favoring St. Louis, and Regenda's status uncertainty keep this a true coin flip.

Computed danger · scouting

Players to watch

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
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
Source · MoneyPuck skaters