Backcheck
Recap · NSH at STL

Predators run the Blues off the ice on the underlying numbers

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

By the ModelJul 11, 9:14 PMxG: xgboost-0.758Edited for clarity
Away
NSH
Nashville Predators
5
Home
STL
St. Louis Blues
2
FINAL
Process vs result

The underlying story

4.18Expected goals2.60
62% share for the better side
26Shot attempts (SOG)22
5High-danger chances4
53Corsi (all attempts)43
Score-adjusted: 50% / 50%
Source · NHL play-by-play · XGBoost xG

The Predators commanded 62% of 5v5 expected goals (4.18–2.60)—a dominance that would normally predict a narrow victory. Nashville overperformed that xG by 0.82 goals, winning 5-2.

Forsberg's efficiency (3 goals in 16:20) epitomized Nashville's clinical finishing. The Predators converted 2 of 5 high-danger chances (40%) while forcing St. Louis into low-danger looks. Saros made 20 of 22 shots at a 0.909 save percentage, running 0.60 above expected.

The Blues' rush attack threatened to disrupt that control—two goals off 20 chances. But Nashville countered with three rush goals on 27 looks, erasing St. Louis's edge on the rush. Josi (2 assists in 23:41) and O'Reilly (2 assists in 18:45) orchestrated the offense, while Hofer faced 25 shots and allowed 5.

St. Louis was outmatched at evens. Nashville's underlying dominance, combined with their finishing efficiency, made the result inevitable.

How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
NSH2 / 5 · 1.94 xG
STL1 / 4 · 1.04 xG
Medium dangermid-range
NSH1 / 14 · 1.53 xG
STL0 / 10 · 1.09 xG
Low dangerperimeter & point
NSH2 / 34 · 0.71 xG
STL1 / 29 · 0.47 xG

NSH went 2-for-34 from low danger on 0.71 expected goals — 1.3 above expected.

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

Finishing vs expected

expectedactual
NSH
5 G · 4.18 xG · +0.8
STL
2 G · 2.60 xG · -0.6
0123456
Goalies · GSAx (goals saved above expected)
J. SarosNSH
+0.6
J. HoferSTL
+0.2

NSH finished +0.8 against expected, STL -0.6 — J. Saros (NSH) saved 0.6 goals above expected.

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

Shot diet

goalsshots
NSH
WRIST4/27
BACKHAND0/4
SLAP0/3
TIP IN0/3
SNAP0/2
WRAP AROUND1/2
DEFLECTED0/1
OTHER0/11
STL
WRIST1/21
BACKHAND0/4
SLAP0/3
TIP IN0/3
SNAP1/3
WRAP AROUND0/1
DEFLECTED0/0
OTHER0/8
NSH
STL
Off the rush
3 G on 27 · 2.46 xG
2 G on 20 · 1.95 xG
Off rebounds
0 G on 4 · 0.70 xG
0 G on 3 · 0.38 xG

Wrist shots carried the volume: NSH went 4-for-27, STL 1-for-21. NSH scored 3 of theirs off the rush.

Source · Backcheck xG model · NHL shot types
Three stars · computed, not voted
F. Forsberg
#9 · L · NSH
3 G · 0 A · 4 SOG · 16:20 TOI · +2
R. Josi
#59 · D · NSH
0 G · 2 A · 2 SOG · 23:41 TOI · +2
R. O'Reilly
#90 · C · NSH
0 G · 2 A · 1 SOG · 18:45 TOI · +2
Ranked from the box score — points first · Backcheck
What the model flagged
  • NSH was clinical in the high-danger zone — 2/5 on HD chances (40%).
  • NSH scored 2 goals from low-danger spots — the opposing goalie needs to have those.
  • STL was lethal off the rush — 2 goals on 20 rush chances.
  • NSH was lethal off the rush — 3 goals on 27 rush chances.
  • STL created 3 rebound opportunities (0 converted) — crashing the net effectively.
  • NSH created 4 rebound opportunities (0 converted) — crashing the net effectively.
Before the game — the model's pre-game read
Preview · NSH at STL · 8:00 PM ET

Predators at Blues: a genuine coin flip

By the ModelJul 11, 8:30 PMEdited for clarity
Win probability

The model's lean

52%
STL
Model favorite
48%
52%
NSH50STL

STL by 4 points of win probability — effectively a coin flip. Projected score NSH 2.42.6 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

NSH← edge
edge →STL
49.0%5v5 xG%49.0%
50.0%Corsi%48.0%
2.48xGF / 602.34
2.58xGA / 602.40
1.84Goals for / gm2.00
2.21Goals against / gm2.12
0.992PDO — luck, not skill1.000

STL holds 4 of 6 process categories — and PDO (0.992 vs 1.000) says STL has run hotter.

Source · MoneyPuck season tables · 5v5

St. Louis is favored at 52%, with the model projecting a 2.6–2.4 expected score—margins close enough to a pick'em.

The Blues have limped through their last ten games, sitting at minus-10 in goal differential. That's the kind of stretch that either precedes a snap or deepens a funk; this matchup will tell you which.

The underlying metrics suggest near-parity. Both teams are posted at 49.0% expected goals percentage at 5v5. Nashville holds a slight possession edge (50.0% Corsi) over St. Louis (48.0%), though PDO—a proxy for luck—cuts against Nashville: the Predators sit at 0.992 while the Blues ring in at 1.000, suggesting expected regress and regression, respectively.

The goaltending situation adds a variable: J. Annunen is on a back-to-back, which typically invites a backup start or a tired starter. How Nashville responds to fatigue behind the crease could tilt the game.

On offense, Nashville leans on Zachary L'Heureux and Filip Forsberg. L'Heureux carries 0.85 expected goals per 60 minutes, has 4 goals on 1 high-danger chance (16.0% shooting), and is running on fumes from a luck deficit—he's overdue. Forsberg is steadier: 0.80 xG/60 across 23 goals and 17 assists with 4 high-danger chances and a 13.6% shooting rate that suggests real finishing above expectation.

St. Louis counters with Jimmy Snuggerud and Dylan Holloway, both high-volume creators. Snuggerud has authored 15 goals and 22 assists while accumulating 0.86 xG/60 and just 2 high-danger chances—he's relying more on positioning and timing than pure danger. Holloway mirrors the archetype: 0.82 xG/60 across 13 goals, 24 assists, and only 1 high-danger chance, suggesting a player who finds soft areas rather than forcing entry.

Both teams report zero high-danger goal rate and zero rebound goal rate. These shouldn't read as literal zeros; they're either data artifacts or rounding noise. Treat them as such.

St. Louis's defensive vulnerability is Jimmy Snuggerud—an unusual weak link for a forward. Nashville's is Jonathan Marchessault, though the data provides no context on what makes him exposed.

The edge is statistical thinness. With these metrics this tightly clustered and goaltending uncertainty tilting the game, you're picking based on which team's heat-check holds longer or who gets the first break. The model says St. Louis by a tick. The numbers say flip a coin.

Computed danger · scouting

Players to watch

NSH
Zachary L'Heureux4G 0A
0.85 xG/60 · 1 HD · 16.0% sh
Filip Forsberg23G 17A
0.80 xG/60 · 4 HD · 13.6% 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