Backcheck
Recap · SJS at UTA

Utah run the Sharks off the ice on the underlying numbers

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

By the ModelJun 16, 2:57 PMxG: xgboost-0.758Edited for clarity
Away
SJS
San Jose Sharks
3
Home
UTA
Utah Mammoth
6
FINAL
Process vs result

The underlying story

1.89Expected goals4.06
68% share for the better side
21Shot attempts (SOG)34
2High-danger chances5
38Corsi (all attempts)61
Score-adjusted: 43% / 57%
Source · NHL play-by-play · XGBoost xG

Utah didn't just win—they dominated at a scale that makes a 6–3 scoreline look restrained. The Jazz controlled 68 percent of expected goals (4.06–1.89 xG), a margin that reveals the gap between result and dominance.

Shot volume echoed the xG gap: Utah fired 34 attempts to San Jose's 21 (62 percent share). High-danger chances went 5–2. On nearly every metric, Utah's control was overwhelming.

The difference surfaced in shot quality. Utah generated 0.067 xG per shot versus San Jose's 0.050—Utah hunted better locations. On the rush, Utah parlayed 32 chances into six goals; San Jose managed two from 18. In high-danger areas, Utah buried 2 of 5 (40 percent conversion).

Both teams got lucky. Utah overperformed their xG by 1.94 goals—elite finish or fortunate bounces. San Jose posted a 1.11 overperformance, a modest bright spot in a lopsided loss. Y. Askarov (SJS) was worse, allowing 1.94 more goals than expected (0.824 SV%). K. Vejmelka (UTA) allowed 1.11 more than expected (0.857 SV%), but Utah's offensive outperformance masked the weakness.

Three Stars:

  • #8 N. Schmaltz — 3G, 1A in 18:40
  • #9 C. Keller — 1G, 3A in 17:42
  • #71 M. Celebrini — 1G, 1A in 17:24
How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
SJS1 / 2 · 0.57 xG
UTA2 / 5 · 1.28 xG
Medium dangermid-range
SJS1 / 8 · 0.84 xG
UTA4 / 19 · 2.11 xG
Low dangerperimeter & point
SJS1 / 28 · 0.48 xG
UTA0 / 37 · 0.67 xG

UTA went 4-for-19 from medium danger on 2.11 expected goals — 1.9 above expected.

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

Finishing vs expected

expectedactual
SJS
3 G · 1.89 xG · +1.1
UTA
6 G · 4.06 xG · +1.9
01234567
Goalies · GSAx (goals saved above expected)
Y. AskarovSJS
-1.9
K. VejmelkaUTA
-1.1

SJS finished +1.1 against expected, UTA +1.9 — Y. Askarov (SJS) allowed 1.9 more goals than expected.

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

Shot diet

goalsshots
SJS
SNAP2/18
BACKHAND1/2
SLAP0/4
TIP IN0/3
WRIST0/1
DEFLECTED0/0
OTHER0/10
UTA
SNAP5/31
BACKHAND1/6
SLAP0/4
TIP IN0/4
WRIST0/3
DEFLECTED0/1
OTHER0/12
SJS
UTA
Off the rush
2 G on 18 · 1.43 xG
6 G on 32 · 2.99 xG
Off rebounds
1 G on 2 · 0.28 xG
0 G on 4 · 0.50 xG

Snap shots carried the volume: SJS went 2-for-18, UTA 5-for-31. UTA scored 6 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
N. Schmaltz
#8 · C ·
3 G · 1 A · 6 SOG · 18:40 TOI · +3
C. Keller
#9 · R ·
1 G · 3 A · 3 SOG · 17:42 TOI · +3
M. Celebrini
#71 · C ·
1 G · 1 A · 3 SOG · 17:24 TOI
Ranked from the box score — points first · Backcheck
What the model flagged
  • Y. Askarov (SJS) gave up 1.9 goals more than expected — well below their workload.
  • UTA generated far more dangerous chances — 0.067 xG/shot vs 0.050. Quality over quantity.
  • UTA was clinical in the high-danger zone — 2/5 on HD chances (40%).
  • UTA was lethal off the rush — 6 goals on 32 rush chances.
  • SJS was lethal off the rush — 2 goals on 18 rush chances.
  • UTA created 4 rebound opportunities (0 converted) — crashing the net effectively.
  • UTA outperformed their expected goals by 1.9 — elite finishing or lucky bounces.
  • SJS power play was dominant — 2 PPG on 6 PP shots (0.74 xG).
Before the game — the model's pre-game read
Preview · SJS at UTA · 9:00 PM ET

The Utah are the model's lean over the Sharks on the underlying numbers

By the ModelJun 16, 2:55 PMEdited for clarity
Win probability

The model's lean

56%
UTA
Model favorite
44%
56%
SJS50UTA

UTA by 12 points of win probability — a modest lean. Projected score SJS 2.42.7 UTA; 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 →UTA
48.0%5v5 xG%52.0%
47.0%Corsi%53.0%
2.33xGF / 602.64
2.56xGA / 602.39
1.99Goals for / gm2.26
2.32Goals against / gm1.99
0.998PDO — luck, not skill1.003

UTA holds 6 of 6 process categories — and PDO (0.998 vs 1.003) says UTA has run hotter.

Source · MoneyPuck season tables · 5v5

The model projects a 2.4-2.7 Utah victory and gives the visitors a 56% win probability. This edge rests on Utah's control of the underlying play—a decisive advantage in a matchup where possession generates wins.

Utah dominates at 5v5. The Jazz hold a 52.0% expected goals share versus San Jose's 48.0%, a three-point gap that compounds across 60 minutes. On shot volume, Utah's territorial superiority widens: 53.0% Corsi against 47.0%. The Sharks will spend this game defending their zone.

San Jose's scoring depth makes them dangerous despite the deficit in play. Pavol Regenda (1.10 xG/60) is the primary concern—he has 5 goals and 2 high-danger goals, proof of a clean finishing touch at 16.1% shooting. Igor Chernyshov (0.91 xG/60) provides secondary scoring with 6 goals and 8 assists, including 1 high-danger goal, though his 15.0% shooting rate is the softer part of his profile. Both represent significant scoring threats.

Utah's forward group is built on volume. Dylan Guenther leads the way at 1.02 xG/60 with 28 goals and 3 high-danger goals, evidence of finishing skill in the 16.8% range. Daniil But (1.01 xG/60) operates on the margins—2 goals, 2 assists, and 1 high-danger goal suggest he's underperforming his underlying metrics. At 5.6% shooting, he looks due.

The luck component favors Utah slightly. San Jose's PDO of 0.998 sits below neutral; Utah's 1.003 sits above. Neither gap is substantial, but it's one more small edge for the Jazz in a game where their core advantage—control—should manifest in the result.

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
UTA
Dylan Guenther28G 15A
1.02 xG/60 · 3 HD · 16.8% sh
Daniil But2G 2A
1.01 xG/60 · 1 HD · 5.6% sh
Source · MoneyPuck skaters