Motion-blurred skater in a San Jose Sharks sweater
Breakdown · TOR at SJS

Sharks pull away from the Maple Leafs

The verdict · earned

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

TOR 1 · SJS 4
◆ By the ModelJul 12, 10:10 AMxG: 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

San Jose's control registered everywhere it mattered. They posted 56% of 5v5 expected goals (3.51–2.73), 56% of shot attempts (25–20), and 6 high-danger chances to Toronto's 3. The 4-1 scoreline reflected that dominance.

Goaltending amplified the gap beyond what underlying play delivered. A. Nedeljkovic (SJS) stopped 1.7 goals above expected, an elite performance. A. Stolarz (TOR) overperformed by only 0.51 goals, meaning Toronto's offense bore the weight: they underperformed their 2.73 expected goals by 1.73, wasting quality looks against a hot backstop.

San Jose's finish from high-risk areas compounded Toronto's misfortune. W. Eklund and Z. Ostapchuk each recorded 1G–1A, while the Sharks converted 2 low-danger attempts—plays that defending teams hope to escape. The rush game was their execution engine: 4 goals on 24 rush chances, a conversion rate that punishes weak transition defense.

Adam Gaudette's wrist shot from the high slot (P3, 19:03) crystallized San Jose's control at a moment when Toronto's seams had already widened. By then, Nedeljkovic's excellence and the Sharks' finishing touch had erased any pathway back.

Toronto generated the structure to compete: 6 high-danger chances, 4 rebound opportunities off crashed nets. Finish separated the teams. The underlying numbers suggested a closer contest than the scoreboard displayed, yet precision and goaltending luck determined the actual margin.

The breakdown in twelve frames

Swipe it

Every number is from this page
Final · Apr 2
TOR
1
SJS
4

Sharks pull away from the Maple Leafs

Chances 2.7 – 3.5Did they deserve it? →
Did they deserve it?

The Sharks earned this one.

Expected goals · chance value
TOR
2.73
SJS
3.51
44% of the chances56%

The board read TOR 1, SJS 4. The chances read TOR 2.7, SJS 3.5.

Our xG model · NHL play-by-play · all situations
Luck check
SJS
+0.5
goals above expected
SJS3.51 expected · 4 scored
Expected
Scored
TOR2.73 expected · 1 scored
Expected
Scored

The Maple Leafs left 1.7 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 03:27SJSZ. Ostapchuk0–1
  2. P1 17:43SJSC. Graf0–2
  3. P2 01:42SJSW. Eklund0–3
  4. P2 06:43TORJ. TavaresPP1–3
  5. P3 19:03SJSA. GaudetteEN1–4
NHL play-by-play · chance value from our xG model
Where the shots came from
TOR
38 shots
1
Final
79 shots
SJS
41 shots
4
TOR attackSJS attack
TOR SJS Goal
38
shots · 1 in
41
shots · 4 in
Every unblocked shot · press play to replay it
Chances by danger
TORSJS
0 / 3
0.62 xG
High danger
1 / 6
1.98 xG
1 / 14
1.55 xG
Medium
1 / 8
0.76 xG
0 / 38
0.56 xG
Low
2 / 43
0.78 xG

The Maple Leafs went 0 for 3 from the slot.

Danger tiers by our xG model · high ≥ 20% chance
In the net
A
A. Nedeljkovic
+1.7
SJS · 19/20
B
A. Stolarz
+0.5
TOR · 21/24
The numbers, checked
BACKCHECK

Sharks pull away from the Maple Leafs

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 6–10
  1. 03:27SJSZ. Ostapchuk(B. Goodrow, D. Orlov)0–1
  2. 17:43SJSC. Graf(M. Misa, T. Toffoli)0–2
2ndshots 5–8
  1. 01:42SJSW. Eklund(A. Wennberg, K. Sherwood)0–3
  2. 06:43TORJ. Tavarespower play(E. Cowan, W. Nylander)1–3
3rdshots 9–7
  1. 19:03SJSA. Gaudetteempty net(W. Eklund, Z. Ostapchuk)1–4

score reads TOR–SJS

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

The numbers

XGBoost xG · NHL play-by-play
3.51
SJS chances
Goals their shots were worth
+0.5
Finishing
Goals above what those chances were worth
1.052
SJS puck luck
Above 1.000 — the bounces went their way
50.9%
Shot attempts
Over half — they had the puck more
Split by club

Who controlled the game

2.73Expected goals3.51
SJS 56% of the chance quality
20Shots on goal25
3High-danger chances6
55All attempts (Corsi)57
Adjusted for score: TOR 56% · SJS 44%
Faceoffs · SJS won64%off27%neu59%def
Source · NHL play-by-play · XGBoost xG
How the game was won

The danger ladder

shotsgoalsexpected
High dangerslot & crease
TOR0 / 3 · 0.62 xG
SJS1 / 6 · 1.98 xG
Medium dangermid-range
TOR1 / 14 · 1.55 xG
SJS1 / 8 · 0.76 xG
Low dangerperimeter & point
TOR0 / 38 · 0.56 xG
SJS2 / 43 · 0.78 xG

SJS went 2-for-43 from low danger on 0.78 expected goals — 1.2 above expected.

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

Finishing vs expected

expectedactual
TOR
1 G · 2.73 xG · -1.7
SJS
4 G · 3.51 xG · +0.5
012345

TOR finished -1.7 against expected, SJS +0.5.

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

Shot diet

goalsshots
TOR
WRIST0/19
SLAP0/6
TIP IN0/6
SNAP1/3
BACKHAND0/4
OTHER0/17
SJS
WRIST4/25
SLAP0/7
TIP IN0/5
SNAP0/3
BACKHAND0/1
OTHER0/16
TOR
SJS
Off the rush
1 G on 25
2.30 xG
4 G on 24
2.74 xG
Off rebounds
0 G on 4
0.20 xG
0 G on 3
0.51 xG

Wrist shots carried the volume: TOR went 0-for-19, SJS 4-for-25. SJS scored 4 of theirs off the rush.

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
A. Stolarz
TOR · 21/24 · .875
+0.5
saved above expected
B
the night
By dangerG/attxGsaved
High danger1/62.0+1.0
Medium1/80.8-0.2
Low2/430.8-1.2

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

A. Nedeljkovic
SJS · 19/20 · .950
+1.7
saved above expected
A
the night
By dangerG/attxGsaved
High danger0/30.6+0.6
Medium1/141.6+0.6
Low0/380.6+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

79 shots · press play to watch the game back

Where the shots came from

NHL play-by-play coordinates
TOR
38 shots
1
Final
79 shots
SJS
41 shots
4
TOR attackSJS attack
TOR SJS Goal

Each club shoots toward its own end — TOR left, SJS 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
W. Eklund
#72 · L · SJS
1 G · 1 A · 2 SOG · 15:01 on ice · +2
Z. Ostapchuk
#63 · C · SJS
1 G · 1 A · 1 SOG · 11:15 on ice · +2
E. Cowan
#53 · R · TOR
0 G · 1 A · 0 SOG · 19:22 on ice · -1
Ranked from the box score — points first · Backcheck
What the model said beforehand

Before the game

Written Thu, Apr 2
Open the pre-game read
Written from the numbers

The read

Edited for clarity
◆ By the ModelJul 12, 10:27 AMEdited 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 2.4 to 2.6 xG game favoring San Jose at 54% win probability. This is as close to a pick'em as you'll find.

San Jose's form is a cautionary tale: -11 goal differential over the last 10 games. That's a sustained trend, not noise. Toronto's 5v5 picture—46.0% xG%, 45.0% Corsi%—suggests they're the healthier team structurally. San Jose's advanced metrics (48.0% xG%, 47.0% Corsi%) look stronger on paper, but their PDO of 0.998 reveals a squad getting unlucky; Toronto's 1.002 reflects the opposite.

On Toronto's side, Auston Matthews carries 1.10 xG/60 with 17G 13A and 1 high-danger goal—a volume threat converting at a level slightly above what his shot selection alone would predict. John Tavares is more prolific by assist (15G 24A with 3 high-danger goals) though his 0.91 xG/60 and 12.4% shooting suggest he's benefiting from better finishing relative to his shot creation.

San Jose counters with Pavol Regenda's 1.10 xG/60 (matching Matthews' rate) and 16.1% shooting—a rate that signals overdrive. His 5G 1A with 2 high-danger goals reflects explosive efficiency on limited volume. Igor Chernyshov (0.91 xG/60, 6G 8A, 15.0% shooting, 1 high-danger goal) is running similarly hot, though at higher productivity than Regenda.

The defensive angle will decide this. Toronto must contain Regenda's dangerous rate; San Jose must neutralize Matthews' volume and consistency. Both teams have internal vulnerabilities. Bo Groulx is Toronto's defensive liability. Igor Chernyshov carries the dual burden of being San Jose's defensive weak link while also being an offensive threat.

San Jose's -11 recent slide is the visible tell: a team generating respectable shot metrics yet leaking goals consistently. Whether that trend reverses or deepens will determine the variance in a fundamentally even matchup. At 54% for the Sharks, the model is essentially calling this a coin flip. Execution—which team's stars stay clinical and which defense tightens—will likely decide.

What the model said beforehand

The model's lean

SJS 54%
54%
SJS
Model favorite
46%
54%
TOR50SJS

SJS by 8 points of win probability — a modest lean. Projected score TOR 2.4–2.6 SJS; 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
TOR← edge
edge →SJS
46.0%48.0%
45.0%47.0%
2.242.33
2.672.56
2.091.99
2.522.32
1.0020.998

SJS holds 5 of 6 process categories — and the luck row (1.002 vs 0.998) says TOR has been getting the bounces, which tends not to last.

Source · NHL stats API + our xG · 5v5
Form · Last 10
TOR
5-3-2
-3 GD · 2d rest
SJS
4-5-1
-11 GD · 2d rest
1.002
TOR PDO
Luck gauge · drifts to 1.000
0.998
SJS PDO
Luck gauge · drifts to 1.000
What decides it

Keys to the game

Things to watch
  • The Sharks are underwater at -11 goal differential over their last 10.
Last game's lineup · confirmed at warm-up

Lineups

NHL box score
TOR
Expected in goal
A. Stolarz
2 days rest.875 last start
Backup Joseph Woll · -6.6 GSAx this season

No completed game on file for this club yet.

SJS
Expected in goal
Y. Askarov
2 days rest.846 last start
Backup Yaroslav Askarov · -18.9 GSAx this season

No completed game on file for this club yet.

Lineups are the players who dressed in each club's last game, with their minutes; clubs confirm tonight's at warm-up. Every player this preview names was in that lineup.

Computed danger · scouting

Players to watch

NHL stats API · our xG
TOR
Auston Matthews17G 13A
1.10 xG/60 · 1 HD · 10.6% sh
John Tavares15G 24A
0.91 xG/60 · 3 HD · 12.4% 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
Keep going

Where to next