Fantasy tools
Stack Finder: best line and PP1 stacks for Sunday, Apr 26
Data updated:
Top 10 stacks
Nick Suzuki100%, Cole Caufield100%, Lane Hutson99%, Juraj Slafkovský98%, Ivan Demidov91%
Matchup factors →Zach Hyman95%, Ryan Nugent-Hopkins75%, Leon Draisaitl100%, Connor McDavid100%, Evan Bouchard100%
Matchup factors →Nikita Kucherov100%, Jake Guentzel100%, Brayden Point95%, Darren Raddysh98%, Brandon Hagel99%
Matchup factors →Troy Terry46%, Cutter Gauthier98%, Leo Carlsson95%
Matchup factors →Leon Draisaitl100%, Kasperi Kapanen16%, Vasily Podkolzin83%
Matchup factors →Alex Killorn5.1%, Mikael Granlund53%, Beckett Sennecke95%
Matchup factors →Nick Suzuki100%, Cole Caufield100%, Juraj Slafkovský98%
Matchup factors →Trevor Moore8.9%, Quinton Byfield85%, Alex Laferriere67%
Matchup factors →Artturi Lehkonen78%, Nathan MacKinnon100%, Martin Necas100%
Matchup factors →Anze Kopitar0.4%, Adrian Kempe97%, Artemi Panarin98%
Matchup factors →
By game
BUF @ BOS
Elias Lindholm43%, David Pastrnak100%, Morgan Geekie95%
10.1 min/game · 2.83 xGF/60 · P(intact) 95%
- BUF 5v5 xGA/60 +2%
- Together 3 of last 3
- DK correlation .28
Elias Lindholm43%, David Pastrnak100%, Pavel Zacha74%, Charlie McAvoy96%, Morgan Geekie95%
3.3 min/game · 8.62 xGF/60 · P(intact) 95%
- BUF shorthanded time −2%
- BUF PK xGA/60 −1%
- Together 3 of last 3
- DK correlation .19
Jason Zucker22%, Ryan McLeod24%, Jack Quinn51%
8.5 min/game · 3.28 xGF/60 · P(intact) 95%
- BOS 5v5 xGA/60 +0%
- Together 3 of last 3
- DK correlation .28
Alex Tuch94%, Tage Thompson100%, Peyton Krebs17%
9.6 min/game · 2.78 xGF/60 · P(intact) 95%
- BOS 5v5 xGA/60 +0%
- Together 3 of last 3
- DK correlation .26
Viktor Arvidsson34%, Pavel Zacha74%, Casey Mittelstadt12%
8.0 min/game · 2.57 xGF/60 · P(intact) 95%
- BUF 5v5 xGA/60 +2%
- Together 3 of last 3
- DK correlation .26
Marat Khusnutdinov11%, Fraser Minten46%, James Hagens50%
7.6 min/game · 2.03 xGF/60 · P(intact) 95%
- BUF 5v5 xGA/60 +2%
- Together 3 of last 3
- DK correlation .27
Sean Kuraly0.2%, Tanner Jeannot6.5%, Mark Kastelic17%
6.0 min/game · 2.06 xGF/60 · P(intact) 95%
- BUF 5v5 xGA/60 +2%
- Together 3 of last 3
- DK correlation .29
Jason Zucker22%, Tage Thompson100%, Josh Norris37%, Rasmus Dahlin100%, Jack Quinn51%
5.1 min/game · 8.04 xGF/60 · P(intact) 23%
- BOS shorthanded time +12%
- BOS PK xGA/60 +0%
- Together 2 of last 3
- DK correlation .19
Josh Norris37%, Josh Doan59%, Zach Benson55%
8.3 min/game · 3.22 xGF/60 · P(intact) 23%
- BOS 5v5 xGA/60 +0%
- Together 2 of last 3
- DK correlation .27
Jordan Greenway0.3%, Beck Malenstyn4.1%, Josh Dunne0.0%
6.3 min/game · 1.67 xGF/60 · P(intact) 23%
- BOS 5v5 xGA/60 +0%
- Together 2 of last 3
- DK correlation .28
TBL @ MTL
Nick Suzuki100%, Cole Caufield100%, Lane Hutson99%, Juraj Slafkovský98%, Ivan Demidov91%
6.2 min/game · 8.78 xGF/60 · P(intact) 95%
- TBL shorthanded time +3%
- TBL PK xGA/60 −6%
- Together 3 of last 3
- DK correlation .20
Nikita Kucherov100%, Jake Guentzel100%, Brayden Point95%, Darren Raddysh98%, Brandon Hagel99%
4.8 min/game · 7.56 xGF/60 · P(intact) 95%
- MTL shorthanded time +9%
- MTL PK xGA/60 +9%
- Together 3 of last 3
- DK correlation .20
Nick Suzuki100%, Cole Caufield100%, Juraj Slafkovský98%
11.9 min/game · 3.11 xGF/60 · P(intact) 95%
- TBL 5v5 xGA/60 −5%
- Together 3 of last 3
- DK correlation .28
Phillip Danault4.9%, Josh Anderson11%, Jake Evans4.9%
8.7 min/game · 2.11 xGF/60 · P(intact) 95%
- TBL 5v5 xGA/60 −5%
- Together 3 of last 3
- DK correlation .28
Jake Guentzel100%, Anthony Cirelli49%, Brandon Hagel99%
8.8 min/game · 3.96 xGF/60 · P(intact) 23%
- MTL 5v5 xGA/60 +8%
- Together 2 of last 3
- DK correlation .27
Nikita Kucherov100%, Brayden Point95%, Gage Goncalves10%
6.8 min/game · 3.60 xGF/60 · P(intact) 23%
- MTL 5v5 xGA/60 +8%
- Together 2 of last 3
- DK correlation .29
Alexandre Texier4.9%, Alex Newhook25%, Ivan Demidov91%
8.8 min/game · 2.46 xGF/60 · P(intact) 23%
- TBL 5v5 xGA/60 −5%
- Together 2 of last 3
- DK correlation .27
Kirby Dach11%, Zachary Bolduc23%, Oliver Kapanen28%
6.3 min/game · 2.45 xGF/60 · P(intact) 23%
- TBL 5v5 xGA/60 −5%
- Together 2 of last 3
- DK correlation .27
Yanni Gourde4.9%, Zemgus Girgensons3.3%, Nick Paul7.3%
7.4 min/game · 1.83 xGF/60 · P(intact) 23%
- MTL 5v5 xGA/60 +8%
- Together 2 of last 3
- DK correlation .29
Corey Perry6.6%, Conor Geekie20%, Dominic James5.6%
5.8 min/game · 1.96 xGF/60 · P(intact) 12%
- MTL 5v5 xGA/60 +8%
- Together 1 of last 3
COL @ LAK
Trevor Moore8.9%, Quinton Byfield85%, Alex Laferriere67%
12.2 min/game · 3.09 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −6%
- Together 3 of last 3
- DK correlation .28
Artturi Lehkonen78%, Nathan MacKinnon100%, Martin Necas100%
9.6 min/game · 3.89 xGF/60 · P(intact) 95%
- LAK 5v5 xGA/60 −12%
- Together 3 of last 3
- DK correlation .28
Anze Kopitar0.4%, Adrian Kempe97%, Artemi Panarin98%
11.2 min/game · 2.93 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −6%
- Together 3 of last 3
- DK correlation .28
Nazem Kadri70%, Gabriel Landeskog51%, Nathan MacKinnon100%, Martin Necas100%, Cale Makar100%
2.7 min/game · 8.57 xGF/60 · P(intact) 95%
- LAK shorthanded time −6%
- LAK PK xGA/60 −11%
- Together 3 of last 3
- DK correlation .20
Joel Armia3.3%, Scott Laughton4.8%, Jared Wright0.0%
7.3 min/game · 2.48 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −6%
- Together 3 of last 3
- DK correlation .28
Nazem Kadri70%, Gabriel Landeskog51%, Nicolas Roy14%
8.4 min/game · 2.27 xGF/60 · P(intact) 95%
- LAK 5v5 xGA/60 −12%
- Together 3 of last 3
Anze Kopitar0.4%, Adrian Kempe97%, Artemi Panarin98%, Quinton Byfield85%, Alex Laferriere67%
1.6 min/game · 7.02 xGF/60 · P(intact) 95%
- COL shorthanded time −3%
- COL PK xGA/60 −7%
- Together 3 of last 3
- DK correlation .27
Brock Nelson88%, Valeri Nichushkin56%, Parker Kelly18%
9.5 min/game · 2.05 xGF/60 · P(intact) 23%
- LAK 5v5 xGA/60 −12%
- Together 2 of last 3
- DK correlation .27
Jack Drury4.8%, Logan O'Connor0.2%, Joel Kiviranta0.1%
6.8 min/game · 2.47 xGF/60 · P(intact) 23%
- LAK 5v5 xGA/60 −12%
- Together 2 of last 3
- DK correlation .27
Mathieu Joseph3.2%, Jeff Malott3.2%, Samuel Helenius3.2%
6.1 min/game · 1.93 xGF/60 · P(intact) 23%
- COL 5v5 xGA/60 −6%
- Together 2 of last 3
- DK correlation .28
EDM @ ANA
Zach Hyman95%, Ryan Nugent-Hopkins75%, Leon Draisaitl100%, Connor McDavid100%, Evan Bouchard100%
4.4 min/game · 10.43 xGF/60 · P(intact) 95%
- ANA shorthanded time +3%
- ANA PK xGA/60 +6%
- Together 3 of last 3
- DK correlation .20
Troy Terry46%, Cutter Gauthier98%, Leo Carlsson95%
12.6 min/game · 3.54 xGF/60 · P(intact) 82%
- EDM 5v5 xGA/60 +0%
- Together 2 of last 3
- DK correlation .28
Leon Draisaitl100%, Kasperi Kapanen16%, Vasily Podkolzin83%
11.2 min/game · 2.97 xGF/60 · P(intact) 95%
- ANA 5v5 xGA/60 +11%
- Together 3 of last 3
- DK correlation .27
Alex Killorn5.1%, Mikael Granlund53%, Beckett Sennecke95%
11.9 min/game · 3.08 xGF/60 · P(intact) 95%
- EDM 5v5 xGA/60 +0%
- Together 3 of last 3
- DK correlation .28
Chris Kreider63%, Ryan Poehling6.7%, Mason McTavish51%
8.2 min/game · 2.31 xGF/60 · P(intact) 82%
- EDM 5v5 xGA/60 +0%
- Together 2 of last 3
- DK correlation .28
John Carlson98%, Chris Kreider63%, Mikael Granlund53%, Troy Terry46%, Leo Carlsson95%
1.0 min/game · 8.65 xGF/60 · P(intact) 95%
- EDM shorthanded time −14%
- EDM PK xGA/60 +9%
- Together 3 of last 3
- DK correlation .20
Curtis Lazar0.0%, Trent Frederic4.9%, Colton Dach10%
4.2 min/game · 2.03 xGF/60 · P(intact) 82%
- ANA 5v5 xGA/60 +11%
- Together 2 of last 3
- DK correlation .29
Zach Hyman95%, Connor McDavid100%, Matt Savoie36%
8.0 min/game · 3.54 xGF/60 · P(intact) 23%
- ANA 5v5 xGA/60 +11%
- Together 2 of last 3
- DK correlation .27
Ryan Nugent-Hopkins75%, Jason Dickinson3.2%, Jack Roslovic33%
4.6 min/game · 2.57 xGF/60 · P(intact) 12%
- ANA 5v5 xGA/60 +11%
- Together 1 of last 3
- DK correlation .28
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.