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Motion-blurred skater in a Pittsburgh Penguins sweater
← Thu, Oct 30 · the slate
Breakdown · PIT at MIN

Penguins run the Wild off the ice on the underlying numbers

FinalThu, Oct 30
PITPittsburgh Penguins4MINMinnesota Wild1
The verdict · earned

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

PIT 4 · MIN 1
◆ By the ModelJul 11, 2:02 PMxG: xgboost-0.758Edited for clarityDrafted from NHL play-by-play by Backcheck's model, worded for clarity by an AI editor that may not change a number. Nobody at Backcheck was at the rink. How this works

The Penguins' 4–1 win over Minnesota looked more dominant than it was underneath. The Wild underperformed their expected goals by 1.99—they generated chances worth 2.99 but scored one, a massive gap suggesting Pittsburgh's goaltending, not pure dominance, decided the game.

Control was real, though. Pittsburgh generated 4.50 expected goals to Minnesota's 2.99, a 60–40 split at 5-on-5. Shot quality favored Pittsburgh decisively: 0.078 xG per shot versus Minnesota's 0.051. On attempts, Minnesota held 44% (27–34), close to even but insufficient.

The Wild created. They crashed the net, building four rebound chances and converting zero. Pittsburgh replied with five rebounding opportunities, one goal—marginally superior execution. High-danger chances slightly favored Pittsburgh (6–5), a small gap that undersells how Pittsburgh controlled positioning and chance quality.

T. Jarry was the difference. He saved 2.0 goals above expected with a 0.963 save percentage (26–27 shots), transforming Minnesota's decent underlying play into a blowout. F. Gustavsson was solid too—1.50 goals above expected—but that couldn't bridge the gap when control already favored Pittsburgh.

Anthony Mantha's wrist shot from the high slot (period 3, 17:18) punctuated the dominance, extending Pittsburgh's lead when a Minnesota comeback remained plausible.

The scoreboard screams rout. The numbers say Pittsburgh controlled play, shot it better, and got what they deserved—amplified by goaltending that turned a respectable showing into a decisive margin.

Three Stars

  • #58 K. Letang (PIT) — 2A in 22:31
  • #5 R. Shea (PIT) — 1G, 1A in 21:54
  • #17 B. Rust (PIT) — 1G, 1A in 16:15
The breakdown in twelve frames

Swipe it

Every number is from this page
Final · Oct 30
PIT
4
MIN
1

Penguins run the Wild off the ice on the underlying numbers

Chances 4.5 – 3.0Did they deserve it? →
Did they deserve it?

The Penguins earned this one.

Expected goals · chance value
PIT
4.50
MIN
2.99
60% of the chances40%

The board read PIT 4, MIN 1. The chances read PIT 4.5, MIN 3.0.

Our xG model · NHL play-by-play · all situations
Luck check
PIT
−0.5
goals above expected
PIT4.50 expected · 4 scored
Expected
Scored
MIN2.99 expected · 1 scored
Expected
Scored

The Wild left 2.0 goals on the table against what their chances were worth.

PDO = sh% + sv% · drifts to 1.000 over a season
Every goal, in order
  1. P1 10:16MINK. Kaprizov0–1
  2. P2 02:18PITR. Shea1–1
  3. P3 06:29PITB. Rust2–1
  4. P3 07:30PITB. KindelPP3–1
  5. P3 17:18PITA. ManthaEN4–1
NHL play-by-play · chance value from our xG model
Where the shots came from
PIT
47 shots
4
Final
89 shots
MIN
42 shots
1
PIT attackMIN attack
PIT MIN Goal
47
shots · 4 in
42
shots · 1 in
Every unblocked shot · press play to replay it
Chances by danger
PITMIN
2 / 6
2.03 xG
High danger
1 / 5
1.08 xG
2 / 16
1.84 xG
Medium
0 / 12
1.28 xG
0 / 36
0.63 xG
Low
0 / 42
0.63 xG

The Penguins buried 2 of 6 high-danger looks.

Danger tiers by our xG model · high ≥ 20% chance
In the net
A
T. Jarry
+2.0
PIT · 26/27
A
F. Gustavsson
+1.5
MIN · 30/33
The numbers, checked
BACKCHECK

Penguins run the Wild off the ice on the underlying numbers

A model, not a newsroom. Every number on these frames comes from the NHL's play-by-play and our own models. Nothing was watched, guessed or heard from anyone.

Read the full breakdown
backcheckreport.com
01 / 08 · Final
Every goal, in order

How it happened

NHL play-by-play
1stshots 6–13
  1. 10:16MINK. Kaprizov(M. Johansson, M. Rossi)0–1
2ndshots 12–6
  1. 02:18PITR. Shea(T. Novak, K. Letang)1–1
3rdshots 16–8
  1. 06:29PITB. Rust(R. Shea, K. Letang)2–1
  2. 07:30PITB. Kindelpower play(B. Rust, E. Malkin)3–1
  3. 17:18PITA. Manthaempty net4–1

score reads PIT–MIN

Source · NHL play-by-play (api-web.nhle.com)
Process vs result

The numbers

XGBoost xG · NHL play-by-play
4.50
PIT chances
Goals their shots were worth
−0.5
Finishing
Goals below what those chances were worth
1.052
PIT puck luck
Above 1.000 — the bounces went their way
49.6%
Shot attempts
Under half — they were outshot
Split by club

Who controlled the game

4.50Expected goals2.99
PIT 60% of the chance quality
34Shots on goal27
6High-danger chances5
58All attempts (Corsi)59
Adjusted for score: PIT 49% · MIN 51%
Faceoffs · MIN won24%off53%neu37%def
Source · NHL play-by-play · XGBoost xG
How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
PIT2 / 6 · 2.03 xG
MIN1 / 5 · 1.08 xG
Medium dangermid-range
PIT2 / 16 · 1.84 xG
MIN0 / 12 · 1.28 xG
Low dangerperimeter & point
PIT0 / 36 · 0.63 xG
MIN0 / 42 · 0.63 xG

MIN went 0-for-12 from medium danger on 1.28 expected goals — 1.3 left on the table.

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

Finishing vs expected

expectedactual
PIT
4 G · 4.50 xG · -0.5
MIN
1 G · 2.99 xG · -2.0
012345

PIT finished -0.5 against expected, MIN -2.0.

Source · Backcheck xG model
Shot types · rush and rebound chancesopen +
What they shot — and what went in

Shot diet

goalsshots
PIT
WRIST2/28
SLAP1/8
TIP IN1/4
SNAP0/1
BACKHAND0/4
DEFLECTED0/2
OTHER0/11
MIN
WRIST0/27
SLAP0/2
TIP IN1/4
SNAP0/6
BACKHAND0/3
DEFLECTED0/0
OTHER0/17
PIT
MIN
Off the rush
1 G on 28
2.06 xG
1 G on 27
2.08 xG
Off rebounds
1 G on 5
0.99 xG
0 G on 4
0.66 xG

Wrist shots carried the volume: PIT went 2-for-28, MIN 0-for-27.

Source · Backcheck xG model · NHL shot types
New to these numbers?

Two things happened in this game: who created the better chances, and who put the puck in the net. They are not the same thing, and this page separates them on purpose.

The one to watch is expected goals— the best single read on who deserved to win. When it disagrees with the scoreboard, that disagreement is usually the story. Nothing here is a projection; every figure is computed from this game's play-by-play. Full glossary →

xG
Expected goals. Every shot scored by how often that exact look goes in. 2.5 xG means the chances were worth about two and a half goals.
HD
High-danger chances — shots from the slot and the crease, where shots actually become goals.
Corsi
Every shot attempt, including the ones that missed or got blocked. A rough read on who had the puck.
Adj.
Score-adjusted. Teams that trail shoot more and teams that lead sit back, so this corrects the attempt count for the scoreboard.
GSAx
Goals saved above expected. A positive number means the goalie stopped more than an average goalie would have on those shots.
PDO
Shooting % plus save % — a luck gauge. It sits near 1.000 over a season, so a game far from it usually means the bounces decided it.
Shot by shot

In the net

Graded on goals saved above expected
T. Jarry
PIT · 26/27 · .963
+2.0
saved above expected
A
the night
By dangerG/attxGsaved
High danger1/51.1+0.1
Medium0/121.3+1.3
Low0/420.6+0.6

A+ ≥ +2.5 saved above expected · A ≥ +1.5 · B+ ≥ +0.75 · B ≥ +0.25 · C ≥ −0.25 · D ≥ −0.75 · F below −1.5

F. Gustavsson
MIN · 30/33 · .909
+1.5
saved above expected
A
the night
By dangerG/attxGsaved
High danger2/62.0+0.0
Medium2/161.8-0.2
Low0/360.6+0.6

A+ ≥ +2.5 saved above expected · A ≥ +1.5 · B+ ≥ +0.75 · B ≥ +0.25 · C ≥ −0.25 · D ≥ −0.75 · F below −1.5

89 shots · press play to watch the game back

Where the shots came from

NHL play-by-play coordinates
PIT
47 shots
4
Final
89 shots
MIN
42 shots
1
PIT attackMIN attack
PIT MIN Goal

Each club shoots toward its own end — PIT left, MIN right — the way you would watch it. A dot's size is how dangerous the look was, from distance and angle; it is a proxy for shot quality, not the xG model the article is written from. Hover a dot for the shooter and the clock.

Ranked from the box score

Three stars

Points first
Three stars · computed, not voted
K. Letang
#58 · D · PIT
0 G · 2 A · 3 SOG · 22:31 on ice · +2
R. Shea
#5 · D · PIT
1 G · 1 A · 2 SOG · 21:54 on ice · +2
B. Rust
#17 · R · PIT
1 G · 1 A · 2 SOG · 16:15 on ice · +1
Ranked from the box score — points first · Backcheck
What the model said beforehand

Before the game

Written Thu, Oct 30
Open the pre-game read
Written from the numbers

The read

Edited for clarity
◆ By the ModelJul 11, 1:53 PMEdited for clarityDrafted from NHL play-by-play by Backcheck's model, worded for clarity by an AI editor that may not change a number. Nobody at Backcheck was at the rink. How this works

The model projects a 2.5–2.7 goal game with the Wild at 52% win probability. That's about as close to a pick'em as you'll find.

On paper, these teams are mirror images of structural mediocrity. Pittsburgh owns 51.0% expected-goals share at 5v5 but just 50.0% shot attempts, suggesting offensive creativity without efficiency. Minnesota flips that—52.0% xG%, 48.0% Corsi—creating more chances but converting them at a lower rate. Pittsburgh's PDO sits at 1.012, Minnesota's at 1.007, meaning neither team is banking on lucky bounces.

The absence of Filip Hallander (likely out, IR) removes Pittsburgh's most dangerous creator; his 1.28 xG/60 represented the team's offensive ceiling. But Rickard Rakell (13G, 12.1% shooting, 1.01 xG/60) remains lethal at 5v5, and his conversion rate sits well above his underlying volume—a sign he's either elite at the net-front or benefiting from prime positioning.

Minnesota counters with Matt Boldy (22G, 13.7% shooting, 0.89 xG/60), who operates in the same elite finishing tier. Robby Fabbri (0.88 xG/60, 6.9% shooting) generates chances but has struggled to finish; with just 2G on that volume, he's due for regression—either positive or a continued dry spell.

Here's the tactical quirk: both teams rank at 0% for high-danger rebound goals. That's not bad luck; it's a red flag for neither consistently winning the space where goals happen. Pittsburgh's Caleb Jones and Minnesota's Matt Kiersted represent defensive vulnerabilities that cut both ways—sloppy coverage is sloppy coverage.

The deciding factor won't be a skill mismatch. It'll be goaltending. The model saw two evenly matched teams at 5v5 and assigned the edge to Minnesota by the narrowest margin. That's a true coin flip, with the winner determined by who makes the third-period save when it matters.

What the model said beforehand

The model's lean

MIN 53%
53%
MIN
Model favorite
47%
53%
PIT50MIN

MIN by 6 points of win probability — a modest lean. Projected score PIT 2.5–2.7 MIN; 18% chance it's tied after 60.

Source · Backcheck Poisson projection · season scoring rates
Season rates · 5v5

Tale of the tape

NHL stats API · our xG
PIT← edge
edge →MIN
51.0%52.0%
50.0%48.0%
2.662.55
2.552.40
2.452.04
2.121.93
1.0121.007

The season numbers split 3–3 — no clear process edge — and the luck row (1.012 vs 1.007) says PIT has been getting the bounces, which tends not to last.

Source · NHL stats API + our xG · 5v5
Form · No games yet
PIT
0-0-0
+0 GD · 0d rest
MIN
0-0-0
+0 GD · 0d rest
1.012
PIT PDO
Luck gauge · drifts to 1.000
1.007
MIN PDO
Luck gauge · drifts to 1.000
What decides it

Keys to the game

Things to watch
  • Two evenly matched teams on paper — this one tilts on goaltending.
Computed danger · scouting

Players to watch

NHL stats API · our xG
PIT
Filip Hallander0G 3A
1.28 xG/60 · 0 HD · 0.0% sh
Rickard Rakell13G 13A
1.01 xG/60 · 3 HD · 12.1% sh
MIN
Matt Boldy22G 18A
0.89 xG/60 · 5 HD · 13.7% sh
Robby Fabbri2G 3A
0.88 xG/60 · 1 HD · 6.9% sh
Keep going

Where to next

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