Backcheck
Recap · TBL at STL

Blues steal one from the Lightning against the run of play

The Blues stole one. They lost the expected-goals battle 4.24–1.97 and won anyway.

By the ModelJul 12, 1:03 AMxG: xgboost-0.758Edited for clarity
Away
TBL
Tampa Bay Lightning
2
Home
STL
St. Louis Blues
3
FINAL / OT
Process vs result

The underlying story

4.24Expected goals1.97
68% share for the better side
36Shot attempts (SOG)21
4High-danger chances2
74Corsi (all attempts)42
Score-adjusted: 65% / 35%
Source · NHL play-by-play · XGBoost xG

St. Louis won 3–2 in a shootout despite controlling just 32% of the xG battle (1.97–4.24). The Lightning's 68% share should have delivered a win; it didn't. That gap defines the night.

J. Hofer made the difference. The Blues netminder stopped 34 of 36 shots (0.944 SV%), outperforming his expected save percentage by 2.24 goals. Against a Lightning team that generated high-danger chances at 4–2 and converted power-play looks at 1.30 xG, Hofer's overperformance was the margin.

A. Vasilevskiy's 19 of 21 saves (0.905 SV%) were solid, but the workload tilted toward Tampa Bay. The Lightning were lethal off the rush—two goals on 33 chances. The Blues held 37% of shot attempts. Possession didn't decide the game.

Jordan Kyrou's backhander from the slot in the shootout ended the standoff.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
TBL0 / 4 · 0.87 xG
STL1 / 2 · 0.44 xG
Medium dangermid-range
TBL2 / 21 · 2.29 xG
STL0 / 10 · 1.10 xG
Low dangerperimeter & point
TBL0 / 49 · 1.08 xG
STL1 / 30 · 0.43 xG

STL went 0-for-10 from medium danger on 1.10 expected goals — 1.1 left on the table.

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

Finishing vs expected

expectedactual
TBL
2 G · 4.24 xG · -2.2
STL
3 G · 1.97 xG · +1.0
012345
Goalies · GSAx (goals saved above expected)
A. VasilevskiyTBL
-0.0
J. HoferSTL
+2.2

TBL finished -2.2 against expected, STL +1.0 — J. Hofer (STL) saved 2.2 goals above expected.

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

Shot diet

goalsshots
TBL
WRIST1/26
SNAP0/14
SLAP1/16
TIP IN0/4
BACKHAND0/2
BAT0/0
POKE0/1
DEFLECTED0/0
WRAP AROUND0/0
OTHER0/11
STL
WRIST2/21
SNAP0/4
SLAP0/1
TIP IN0/0
BACKHAND0/2
BAT0/2
POKE0/0
DEFLECTED0/1
WRAP AROUND0/1
OTHER0/10
TBL
STL
Off the rush
2 G on 33 · 2.68 xG
1 G on 17 · 1.07 xG
Off rebounds
0 G on 4 · 0.51 xG
1 G on 4 · 0.71 xG

Wrist shots carried the volume: TBL went 1-for-26, STL 2-for-21. TBL scored 2 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
D. Raddysh
#43 · D · TBL
0 G · 2 A · 6 SOG · 27:01 TOI · -1
N. Kucherov
#86 · R · TBL
1 G · 1 A · 3 SOG · 23:37 TOI · -2
B. Hagel
#38 · L · TBL
0 G · 1 A · 3 SOG · 25:43 TOI
Ranked from the box score — points first · Backcheck
What the model flagged
  • STL won despite being outplayed by xG (32%). Goaltending or finishing carried them.
  • J. Hofer (STL) stopped 2.2 goals above expected.
  • TBL was lethal off the rush — 2 goals on 33 rush chances.
  • STL created 4 rebound opportunities (1 converted) — crashing the net effectively.
  • TBL created 4 rebound opportunities (0 converted) — crashing the net effectively.
  • TBL underperformed xG by 2.2 — wasted quality chances.
  • J. Hofer (STL) saved 2.2 goals above expected — stole the show.
  • TBL power play was dominant — 2 PPG on 13 PP shots (1.30 xG).
Before the game — the model's pre-game read
Preview · TBL at STL · 8:00 PM ET

Lightning at Blues: a genuine coin flip

By the ModelJul 12, 12:59 AMEdited for clarity
Win probability

The model's lean

52%
TBL
Model favorite
52%
48%
TBL50STL

TBL by 4 points of win probability — effectively a coin flip. Projected score TBL 2.52.4 STL; 18% chance it's tied after 60.

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

Tale of the tape

TBL← edge
edge →STL
54.0%5v5 xG%49.0%
53.0%Corsi%48.0%
2.67xGF / 602.34
2.28xGA / 602.40
2.38Goals for / gm2.00
1.85Goals against / gm2.12
1.019PDO — luck, not skill1.000

TBL holds 6 of 6 process categories — and PDO (1.019 vs 1.000) says TBL has run hotter.

Source · MoneyPuck season tables · 5v5

The model projects a 2.5–2.4 Lightning victory with Tampa Bay at 52% win probability—as close to a pick'em as the numbers allow.

Tampa Bay owns the underlying play. The Lightning generate 54.0% of expected goals at 5v5, compared to 49.0% for St. Louis—a genuine edge in shot quality and volume. Corsi reinforces the dominance: Tampa Bay drives 53.0% of shot attempts, meaning the puck spends the afternoon in St. Louis territory. The Lightning are the better 5v5 team.

The catch is sample noise. Tampa Bay's PDO sits at 1.019—roughly one full goal's worth of variance above expectation. St. Louis operates at a cleaner 1.000. Some of the Lightning's margin depends on puck luck that won't sustain; expect regression.

Brandon Hagel is the engine for Tampa Bay. He's averaging 1.10 expected goals per 60 minutes, a phenomenal rate, and has translated it into 23 goals on a 15.8% shooting percentage. He owns 2 high-danger chances, meaning he's generating the kind of looks that finish. Anthony Cirelli, averaging 0.95 xG/60, carries 15 goals and 18 assists with 5 high-danger chances—a secondary scoring threat with elite efficiency. Cirelli's shooting percentage checks in at 17.0%, well above average, so some regression is inevitable there too.

Jimmy Snuggerud is St. Louis's most efficient producer. At 0.86 xG/60, he ranks below the Lightning's top two but still in the elite echelon. He has 15 goals and 22 assists with 2 high-danger chances on a modest 11.9% shooting rate—room for either improvement or decline. Dylan Holloway rounds out the matchup: 0.82 xG/60, 13 goals and 24 assists, 1 high-danger chance, and 10.8% shooting. Holloway's assist totals suggest playmaking over shot volume, which fits a secondary role.

The underlying territorial advantage belongs to Tampa Bay. St. Louis will need to limit high-danger chances and lean on goaltending to stay close. The Lightning's efficiency numbers, while real, have built-in regression risk that could tighten what looks like a comfortable edge.

This is essentially even money. Take the model at face value.

Computed danger · scouting

Players to watch

TBL
Brandon Hagel23G 26A
1.10 xG/60 · 2 HD · 15.8% sh
Anthony Cirelli15G 18A
0.95 xG/60 · 5 HD · 17.0% sh
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
Source · MoneyPuck skaters