Fantasy tools
Stack Finder: best line and PP1 stacks for Monday, Mar 30
Data updated:
Top 10 stacks
Brayden Schenn32%, Mathew Barzal82%, Calum Ritchie31%
Matchup factors →Robert Thomas90%, Dylan Holloway92%, Jimmy Snuggerud78%
Matchup factors →Anders Lee29%, Bo Horvat90%, Emil Heineman31%
Matchup factors →Mark Stone94%, Ivan Barbashev66%, Jack Eichel99%
Matchup factors →Will Smith95%, Macklin Celebrini100%, Igor Chernyshov54%
Matchup factors →Mark Stone94%, Tomas Hertl85%, Jack Eichel99%, Mitch Marner99%, Pavel Dorofeyev92%
Matchup factors →Ondrej Palat0.1%, Jean-Gabriel Pageau11%, Simon Holmstrom16%
Matchup factors →John Tavares96%, William Nylander99%, Easton Cowan55%
Matchup factors →Jeffrey Viel3.2%, Ryan Poehling6.7%, Cutter Gauthier98%
Matchup factors →Pavel Buchnevich33%, Jordan Kyrou74%, Jake Neighbours29%
Matchup factors →
By game
PIT @ NYI
Brayden Schenn32%, Mathew Barzal82%, Calum Ritchie31%
10.7 min/game · 3.79 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +3%
- Together 3 of last 3
- DK correlation .27
Anders Lee29%, Bo Horvat90%, Emil Heineman31%
11.7 min/game · 3.23 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +3%
- Together 3 of last 3
- DK correlation .26
Ondrej Palat0.1%, Jean-Gabriel Pageau11%, Simon Holmstrom16%
9.9 min/game · 3.24 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +3%
- Together 3 of last 3
- DK correlation .28
Noel Acciari4.1%, Connor Dewar4.2%, Elmer Soderblom4.8%
8.4 min/game · 2.87 xGF/60 · P(intact) 95%
- NYI 5v5 xGA/60 +1%
- Together 3 of last 3
- DK correlation .29
Anthony Mantha45%, Tommy Novak42%, Egor Chinakhov50%
8.3 min/game · 2.67 xGF/60 · P(intact) 95%
- NYI 5v5 xGA/60 +1%
- Together 3 of last 3
- DK correlation .28
Brayden Schenn32%, Bo Horvat90%, Mathew Barzal82%, Calum Ritchie31%, Matthew Schaefer100%
2.1 min/game · 8.78 xGF/60 · P(intact) 95%
- PIT shorthanded time −1%
- PIT PK xGA/60 −8%
- Together 3 of last 3
- DK correlation .19
Casey Cizikas3.3%, Kyle MacLean0.0%, Marc Gatcomb7.3%
7.2 min/game · 2.27 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +3%
- Together 3 of last 3
- DK correlation .26
Erik Karlsson95%, Bryan Rust84%, Rickard Rakell81%, Anthony Mantha45%, Egor Chinakhov50%
2.1 min/game · 7.33 xGF/60 · P(intact) 82%
- NYI shorthanded time −17%
- NYI PK xGA/60 +9%
- Together 2 of last 3
- DK correlation .20
Sidney Crosby100%, Bryan Rust84%, Rickard Rakell81%
9.2 min/game · 2.84 xGF/60 · P(intact) 23%
- NYI 5v5 xGA/60 +1%
- Together 2 of last 3
- DK correlation .27
Justin Brazeau9.8%, Ville Koivunen18%, Ben Kindel51%
7.2 min/game · 3.15 xGF/60 · P(intact) 23%
- NYI 5v5 xGA/60 +1%
- Together 2 of last 3
- DK correlation .28
CGY @ COL
Nazem Kadri71%, Brock Nelson88%, Nathan MacKinnon100%, Martin Necas100%, Cale Makar100%
3.3 min/game · 9.21 xGF/60 · P(intact) 95%
- CGY shorthanded time +8%
- CGY PK xGA/60 +0%
- Together 3 of last 3
- DK correlation .21
Mikael Backlund13%, Blake Coleman38%, Joel Farabee11%
11.1 min/game · 2.49 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −8%
- Together 3 of last 3
- DK correlation .27
Ryan Strome4.0%, Victor Olofsson27%, Yegor Sharangovich6.8%
10.3 min/game · 2.55 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −8%
- Together 3 of last 3
- DK correlation .28
Morgan Frost21%, Matt Coronato38%, Matvei Gridin37%
11.4 min/game · 2.08 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −8%
- Together 3 of last 3
- DK correlation .28
Parker Kelly19%, Jack Drury4.8%, Joel Kiviranta0.1%
5.3 min/game · 3.29 xGF/60 · P(intact) 82%
- CGY 5v5 xGA/60 +1%
- Together 2 of last 3
- DK correlation .28
Nazem Kadri71%, Ross Colton7.3%, Logan O'Connor0.2%
6.0 min/game · 2.39 xGF/60 · P(intact) 82%
- CGY 5v5 xGA/60 +1%
- Together 2 of last 3
Blake Coleman38%, Morgan Frost21%, Matt Coronato38%, Zayne Parekh66%, Matvei Gridin37%
1.8 min/game · 6.38 xGF/60 · P(intact) 95%
- COL shorthanded time −3%
- COL PK xGA/60 −11%
- Together 3 of last 3
- DK correlation .19
Gabriel Landeskog50%, Nathan MacKinnon100%, Martin Necas100%
10.7 min/game · 3.70 xGF/60 · P(intact) 23%
- CGY 5v5 xGA/60 +1%
- Together 2 of last 3
- DK correlation .28
Brock Nelson88%, Artturi Lehkonen78%, Valeri Nichushkin56%
4.0 min/game · 2.98 xGF/60 · P(intact) 12%
- CGY 5v5 xGA/60 +1%
- Together 1 of last 3
- DK correlation .27
Martin Pospisil7.2%, John Beecher0.0%, Adam Klapka9.8%
7.4 min/game · 1.58 xGF/60 · P(intact) 12%
- COL 5v5 xGA/60 −8%
- Together 1 of last 3
- DK correlation .27
VAN @ VGK
Mark Stone94%, Ivan Barbashev66%, Jack Eichel99%
10.3 min/game · 3.22 xGF/60 · P(intact) 95%
- VAN 5v5 xGA/60 +4%
- Together 3 of last 3
- DK correlation .28
Mark Stone94%, Tomas Hertl85%, Jack Eichel99%, Mitch Marner99%, Pavel Dorofeyev92%
3.0 min/game · 11.04 xGF/60 · P(intact) 95%
- VAN shorthanded time −6%
- VAN PK xGA/60 +2%
- Together 3 of last 3
- DK correlation .28
Mitch Marner99%, Brett Howden15%, Pavel Dorofeyev92%
11.8 min/game · 2.06 xGF/60 · P(intact) 68%
- VAN 5v5 xGA/60 +4%
- Together 1 of last 3
- DK correlation .27
Brock Boeser63%, Jake DeBrusk43%, Filip Hronek94%, Elias Pettersson93%, Marco Rossi69%
2.3 min/game · 8.40 xGF/60 · P(intact) 95%
- VGK shorthanded time −6%
- VGK PK xGA/60 −11%
- Together 3 of last 3
- DK correlation .19
Reilly Smith, Tomas Hertl85%, Colton Sissons3.3%
6.8 min/game · 2.86 xGF/60 · P(intact) 68%
- VAN 5v5 xGA/60 +4%
- Together 1 of last 3
- DK correlation .27
Nic Dowd3.2%, Keegan Kolesar5.1%, Cole Smith0.1%
5.2 min/game · 1.97 xGF/60 · P(intact) 82%
- VAN 5v5 xGA/60 +4%
- Together 2 of last 3
- DK correlation .28
Evander Kane4.7%, Elias Pettersson93%, Drew O'Connor6.7%
11.1 min/game · 2.90 xGF/60 · P(intact) 23%
- VGK 5v5 xGA/60 −11%
- Together 2 of last 3
- DK correlation .28
Teddy Blueger4.0%, Jake DeBrusk43%, Linus Karlsson11%
8.5 min/game · 2.85 xGF/60 · P(intact) 23%
- VGK 5v5 xGA/60 −11%
- Together 2 of last 3
- DK correlation .28
Brock Boeser63%, Marco Rossi69%, Liam Ohgren25%
9.9 min/game · 1.94 xGF/60 · P(intact) 23%
- VGK 5v5 xGA/60 −11%
- Together 2 of last 3
- DK correlation .27
Nils Hoglander8.3%, Aatu Räty9.6%, Max Sasson4.9%
7.0 min/game · 2.24 xGF/60 · P(intact) 12%
- VGK 5v5 xGA/60 −11%
- Together 1 of last 3
- DK correlation .28
TOR @ ANA
John Tavares96%, William Nylander99%, Easton Cowan55%
11.7 min/game · 2.60 xGF/60 · P(intact) 95%
- ANA 5v5 xGA/60 +9%
- Together 3 of last 3
- DK correlation .28
Jeffrey Viel3.2%, Ryan Poehling6.7%, Cutter Gauthier98%
9.5 min/game · 3.21 xGF/60 · P(intact) 95%
- TOR 5v5 xGA/60 +2%
- Together 3 of last 3
- DK correlation .27
Chris Kreider63%, Troy Terry46%, Leo Carlsson95%
10.3 min/game · 3.31 xGF/60 · P(intact) 82%
- TOR 5v5 xGA/60 +2%
- Together 2 of last 3
- DK correlation .28
Alex Killorn5.1%, Mikael Granlund54%, Beckett Sennecke95%
8.7 min/game · 3.06 xGF/60 · P(intact) 95%
- TOR 5v5 xGA/60 +2%
- Together 3 of last 3
- DK correlation .28
Max Domi4.9%, Nick Robertson33%, Matthew Knies95%
7.8 min/game · 2.12 xGF/60 · P(intact) 95%
- ANA 5v5 xGA/60 +9%
- Together 3 of last 3
- DK correlation .27
John Carlson98%, Chris Kreider63%, Mikael Granlund54%, Troy Terry46%, Leo Carlsson95%
1.9 min/game · 8.70 xGF/60 · P(intact) 82%
- TOR shorthanded time +3%
- TOR PK xGA/60 +7%
- Together 2 of last 3
- DK correlation .20
John Tavares96%, Oliver Ekman-Larsson39%, William Nylander99%, Matthew Knies95%, Easton Cowan55%
2.1 min/game · 6.52 xGF/60 · P(intact) 95%
- ANA shorthanded time +3%
- ANA PK xGA/60 +2%
- Together 3 of last 3
- DK correlation .20
Frank Vatrano5.6%, Mason McTavish51%, Tim Washe4.9%
4.4 min/game · 3.83 xGF/60 · P(intact) 68%
- TOR 5v5 xGA/60 +2%
- Together 1 of last 3
- DK correlation .28
Dakota Joshua4.0%, Bo Groulx, Matias Maccelli12%
7.9 min/game · 2.53 xGF/60 · P(intact) 23%
- ANA 5v5 xGA/60 +9%
- Together 2 of last 3
- DK correlation .28
Calle Jarnkrok0.0%, Steven Lorentz0.0%, Jacob Quillan0.0%
6.3 min/game · 1.69 xGF/60 · P(intact) 12%
- ANA 5v5 xGA/60 +9%
- Together 1 of last 3
- DK correlation .27
STL @ SJS
Robert Thomas90%, Dylan Holloway92%, Jimmy Snuggerud78%
11.1 min/game · 3.79 xGF/60 · P(intact) 82%
- SJS 5v5 xGA/60 +8%
- Together 2 of last 3
- DK correlation .28
Will Smith95%, Macklin Celebrini100%, Igor Chernyshov54%
13.5 min/game · 2.80 xGF/60 · P(intact) 95%
- STL 5v5 xGA/60 −9%
- Together 3 of last 3
- DK correlation .28
Pavel Buchnevich33%, Jordan Kyrou74%, Jake Neighbours29%
9.7 min/game · 2.96 xGF/60 · P(intact) 95%
- SJS 5v5 xGA/60 +8%
- Together 3 of last 3
- DK correlation .29
Tyler Toffoli37%, Collin Graf26%, Michael Misa57%
9.6 min/game · 2.78 xGF/60 · P(intact) 82%
- STL 5v5 xGA/60 −9%
- Together 2 of last 3
- DK correlation .27
Alexander Wennberg23%, Kiefer Sherwood57%, William Eklund77%
12.4 min/game · 2.03 xGF/60 · P(intact) 82%
- STL 5v5 xGA/60 −9%
- Together 2 of last 3
- DK correlation .27
Jonatan Berggren4.0%, Dalibor Dvorsky29%, Otto Stenberg14%
8.6 min/game · 1.93 xGF/60 · P(intact) 82%
- SJS 5v5 xGA/60 +8%
- Together 2 of last 3
- DK correlation .28
Alexey Toropchenko0.1%, Pius Suter4.1%, Jack Finley0.0%
6.4 min/game · 1.99 xGF/60 · P(intact) 82%
- SJS 5v5 xGA/60 +8%
- Together 2 of last 3
- DK correlation .27
Barclay Goodrow0.1%, Adam Gaudette0.1%, Zack Ostapchuk3.2%
6.9 min/game · 1.45 xGF/60 · P(intact) 95%
- STL 5v5 xGA/60 −9%
- Together 3 of last 3
- DK correlation .28
Robert Thomas90%, Pius Suter4.1%, Philip Broberg63%, Dylan Holloway92%, Jimmy Snuggerud78%
2.5 min/game · 9.91 xGF/60 · P(intact) 12%
- SJS shorthanded time +26%
- SJS PK xGA/60 +6%
- Together 1 of last 3
- DK correlation .19
Dmitry Orlov30%, Alexander Wennberg23%, William Eklund77%, Will Smith95%, Macklin Celebrini100%
2.9 min/game · 5.16 xGF/60 · P(intact) 12%
- STL shorthanded time −5%
- STL PK xGA/60 +3%
- Together 1 of last 3
- DK correlation .20
How it works
- Lines and PP1 come from each team's last three games of shift data: the forward trio with the most 5-on-5 time together, and the power-play five with the most time together.
- Unit strength is expected goals for per 60 minutes, recent games plus the season, shrunk toward league average so a hot two-game sample does not dominate.
- Matchup: the opponent's 5-on-5 expected goals against per 60 (for lines) or its penalty-kill rate and shorthanded minutes (for PP1), relative to the league.
- Goalie: the likely opposing starter from our goalie start model, weighted by probability, with his save % shrunk toward league average; shot-class save % when available.
- Stack score = rate × minutes × P(unit intact) × matchup × goalie, in expected goals for tonight, so lines and power plays rank on one scale.
Methodology: How we detect lines · Expected goals · Goalie shot classes · Goalie start model
Frequently asked questions
What is a stack in fantasy hockey?
A stack is a group of teammates who play together, usually a forward line or the first power-play unit, so one goal pays several of your players at once. It is the main strategy in daily fantasy hockey.
How are stacks ranked?
Each unit gets an expected-goals number for tonight: how many chances it creates per 60 minutes (recent games plus season, shrunk toward league average), how many minutes it plays, how likely it is to stay together, how leaky the opponent is at 5-on-5 or shorthanded, and how good the likely opposing goalie is.
Where do the lines come from?
From the NHL shift charts of each team's last three games: the three forwards who share the most 5-on-5 ice time form a line, and the five skaters with the most power-play time together form PP1.
Why does it say "shot-based"?
While a season is being reprocessed with our expected-goals model, unit rates fall back to shots on goal times a league-average 0.075 xG per shot. The ranking logic is the same.