Fantasy tools
Stack Finder: best line and PP1 stacks for Friday, May 1
Data updated:
Top 10 stacks
Nikita Kucherov100%, Jake Guentzel100%, Brayden Point95%, Darren Raddysh99%, Brandon Hagel100%
Matchup factors →Nick Schmaltz96%, Lawson Crouse34%, Clayton Keller100%
Matchup factors →Kailer Yamamoto0.2%, Dylan Guenther100%, Logan Cooley94%
Matchup factors →David Pastrnak100%, Pavel Zacha74%, Marat Khusnutdinov11%
Matchup factors →Nick Suzuki100%, Cole Caufield100%, Lane Hutson99%, Juraj Slafkovský99%, Ivan Demidov91%
Matchup factors →Alex Tuch94%, Tage Thompson100%, Peyton Krebs17%
Matchup factors →Jason Zucker22%, Ryan McLeod24%, Jack Quinn50%
Matchup factors →Trevor Moore8.9%, Quinton Byfield85%, Alex Laferriere67%
Matchup factors →Nick Schmaltz96%, Clayton Keller100%, Mikhail Sergachev98%, Dylan Guenther100%, Logan Cooley94%
Matchup factors →Artturi Lehkonen78%, Nathan MacKinnon100%, Martin Necas100%
Matchup factors →
By game
BUF @ BOS
David Pastrnak100%, Pavel Zacha74%, Marat Khusnutdinov11%
16.2 min/game · 3.02 xGF/60 · P(intact) 68%
- BUF 5v5 xGA/60 +6%
- Together 1 of last 3
- DK correlation .28
Alex Tuch94%, Tage Thompson100%, Peyton Krebs17%
11.6 min/game · 2.91 xGF/60 · P(intact) 95%
- BOS 5v5 xGA/60 +3%
- Together 3 of last 3
- DK correlation .26
Jason Zucker22%, Ryan McLeod24%, Jack Quinn50%
10.2 min/game · 3.26 xGF/60 · P(intact) 95%
- BOS 5v5 xGA/60 +3%
- Together 3 of last 3
- DK correlation .28
Elias Lindholm43%, David Pastrnak100%, Pavel Zacha74%, Charlie McAvoy95%, Morgan Geekie95%
2.7 min/game · 8.81 xGF/60 · P(intact) 95%
- BUF shorthanded time −3%
- BUF PK xGA/60 +1%
- Together 3 of last 3
- DK correlation .19
Sean Kuraly0.2%, Tanner Jeannot6.5%, Mark Kastelic17%
7.4 min/game · 2.05 xGF/60 · P(intact) 95%
- BUF 5v5 xGA/60 +6%
- Together 3 of last 3
- DK correlation .29
Elias Lindholm43%, Morgan Geekie95%, Casey Mittelstadt12%
7.3 min/game · 2.72 xGF/60 · P(intact) 68%
- BUF 5v5 xGA/60 +6%
- Together 1 of last 3
- DK correlation .27
Jordan Greenway0.3%, Beck Malenstyn4.1%, Tyson Kozak3.2%
6.5 min/game · 1.67 xGF/60 · P(intact) 95%
- BOS 5v5 xGA/60 +3%
- Together 3 of last 3
- DK correlation .27
Michael Eyssimont0.1%, Alex Steeves4.8%, Fraser Minten46%
5.4 min/game · 2.16 xGF/60 · P(intact) 68%
- BUF 5v5 xGA/60 +6%
- Together 1 of last 3
- DK correlation .28
Josh Doan59%, Noah Ostlund28%, Zach Benson55%
8.9 min/game · 2.42 xGF/60 · P(intact) 23%
- BOS 5v5 xGA/60 +3%
- Together 2 of last 3
- DK correlation .27
Jason Zucker22%, Alex Tuch94%, Tage Thompson100%, Rasmus Dahlin100%, Jack Quinn50%
5.5 min/game · 6.96 xGF/60 · P(intact) 12%
- BOS shorthanded time +11%
- BOS PK xGA/60 +1%
- Together 1 of last 3
- DK correlation .19
TBL @ MTL
Nikita Kucherov100%, Jake Guentzel100%, Brayden Point95%, Darren Raddysh99%, Brandon Hagel100%
5.4 min/game · 7.91 xGF/60 · P(intact) 95%
- MTL shorthanded time +7%
- MTL PK xGA/60 +11%
- Together 3 of last 3
- DK correlation .20
Nick Suzuki100%, Cole Caufield100%, Lane Hutson99%, Juraj Slafkovský99%, Ivan Demidov91%
4.2 min/game · 9.05 xGF/60 · P(intact) 95%
- TBL shorthanded time +1%
- TBL PK xGA/60 −4%
- Together 3 of last 3
- DK correlation .20
Alexandre Texier4.9%, Kirby Dach11%, Zachary Bolduc22%
7.5 min/game · 3.14 xGF/60 · P(intact) 95%
- TBL 5v5 xGA/60 −1%
- Together 3 of last 3
- DK correlation .27
Nikita Kucherov100%, Brayden Point95%, Brandon Hagel100%
6.6 min/game · 3.33 xGF/60 · P(intact) 82%
- MTL 5v5 xGA/60 +12%
- Together 2 of last 3
- DK correlation .29
Oliver Bjorkstrand17%, Gage Goncalves10%, Dominic James5.6%
7.6 min/game · 2.45 xGF/60 · P(intact) 82%
- MTL 5v5 xGA/60 +12%
- Together 2 of last 3
- DK correlation .28
Yanni Gourde4.9%, Jake Guentzel100%, Anthony Cirelli49%
4.7 min/game · 1.73 xGF/60 · P(intact) 82%
- MTL 5v5 xGA/60 +12%
- Together 2 of last 3
- DK correlation .28
Nick Suzuki100%, Cole Caufield100%, Juraj Slafkovský99%
9.2 min/game · 3.15 xGF/60 · P(intact) 23%
- TBL 5v5 xGA/60 −1%
- Together 2 of last 3
- DK correlation .28
Alex Newhook25%, Oliver Kapanen28%, Ivan Demidov91%
6.7 min/game · 2.65 xGF/60 · P(intact) 23%
- TBL 5v5 xGA/60 −1%
- Together 2 of last 3
- DK correlation .27
Phillip Danault4.9%, Josh Anderson11%, Jake Evans4.9%
8.1 min/game · 1.94 xGF/60 · P(intact) 23%
- TBL 5v5 xGA/60 −1%
- Together 2 of last 3
- DK correlation .28
Corey Perry6.6%, Zemgus Girgensons3.3%, Nick Paul7.3%
5.1 min/game · 2.10 xGF/60 · P(intact) 12%
- MTL 5v5 xGA/60 +12%
- Together 1 of last 3
- DK correlation .28
COL @ LAK
Trevor Moore8.9%, Quinton Byfield85%, Alex Laferriere67%
11.0 min/game · 3.08 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −3%
- Together 3 of last 3
- DK correlation .28
Artturi Lehkonen78%, Nathan MacKinnon100%, Martin Necas100%
7.5 min/game · 3.87 xGF/60 · P(intact) 95%
- LAK 5v5 xGA/60 −9%
- Together 3 of last 3
- DK correlation .28
Anze Kopitar0.4%, Adrian Kempe97%, Artemi Panarin98%
9.2 min/game · 2.89 xGF/60 · P(intact) 95%
- COL 5v5 xGA/60 −3%
- Together 3 of last 3
- DK correlation .28
Brock Nelson88%, Valeri Nichushkin56%, Ross Colton7.3%
8.1 min/game · 2.73 xGF/60 · P(intact) 82%
- LAK 5v5 xGA/60 −9%
- Together 2 of last 3
- DK correlation .26
Anze Kopitar0.4%, Adrian Kempe97%, Artemi Panarin98%, Alex Laferriere67%, Brandt Clarke95%
2.0 min/game · 7.51 xGF/60 · P(intact) 95%
- COL shorthanded time −4%
- COL PK xGA/60 −6%
- Together 3 of last 3
- DK correlation .19
Nazem Kadri71%, Gabriel Landeskog51%, Nathan MacKinnon100%, Martin Necas100%, Cale Makar100%
1.7 min/game · 8.58 xGF/60 · P(intact) 95%
- LAK shorthanded time −7%
- LAK PK xGA/60 −10%
- Together 3 of last 3
- DK correlation .20
Parker Kelly17%, Jack Drury4.8%, Logan O'Connor0.2%
6.5 min/game · 2.30 xGF/60 · P(intact) 82%
- LAK 5v5 xGA/60 −9%
- Together 2 of last 3
- DK correlation .29
Nazem Kadri71%, Gabriel Landeskog51%, Nicolas Roy13%
9.0 min/game · 2.33 xGF/60 · P(intact) 23%
- LAK 5v5 xGA/60 −9%
- Together 2 of last 3
Joel Armia3.3%, Scott Laughton4.8%, Jared Wright0.0%
6.1 min/game · 2.59 xGF/60 · P(intact) 23%
- COL 5v5 xGA/60 −3%
- Together 2 of last 3
- DK correlation .28
Mathieu Joseph3.2%, Jeff Malott3.2%, Samuel Helenius3.2%
6.6 min/game · 2.24 xGF/60 · P(intact) 12%
- COL 5v5 xGA/60 −3%
- Together 1 of last 3
- DK correlation .28
VGK @ UTA
Nick Schmaltz96%, Lawson Crouse34%, Clayton Keller100%
14.0 min/game · 3.07 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −6%
- Together 3 of last 3
- DK correlation .29
Kailer Yamamoto0.2%, Dylan Guenther100%, Logan Cooley94%
13.2 min/game · 3.20 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −6%
- Together 3 of last 3
- DK correlation .28
Nick Schmaltz96%, Clayton Keller100%, Mikhail Sergachev98%, Dylan Guenther100%, Logan Cooley94%
3.4 min/game · 8.72 xGF/60 · P(intact) 95%
- VGK shorthanded time −7%
- VGK PK xGA/60 −6%
- Together 3 of last 3
- DK correlation .21
Reilly Smith, Mark Stone93%, Mitch Marner99%
8.5 min/game · 2.81 xGF/60 · P(intact) 95%
- UTA 5v5 xGA/60 −1%
- Together 3 of last 3
- DK correlation .27
Ivan Barbashev66%, Jack Eichel99%, Pavel Dorofeyev92%
8.5 min/game · 2.91 xGF/60 · P(intact) 82%
- UTA 5v5 xGA/60 −1%
- Together 2 of last 3
- DK correlation .27
Nic Dowd3.2%, Colton Sissons3.3%, Cole Smith0.1%
10.1 min/game · 1.75 xGF/60 · P(intact) 95%
- UTA 5v5 xGA/60 −1%
- Together 3 of last 3
- DK correlation .28
Alexander Kerfoot0.1%, Michael Carcone6.6%, JJ Peterka77%
6.4 min/game · 2.58 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −6%
- Together 3 of last 3
- DK correlation .28
Tomas Hertl84%, Keegan Kolesar5.1%, Brett Howden15%
3.2 min/game · 2.74 xGF/60 · P(intact) 95%
- UTA 5v5 xGA/60 −1%
- Together 3 of last 3
- DK correlation .27
Mark Stone93%, Tomas Hertl84%, Jack Eichel99%, Mitch Marner99%, Pavel Dorofeyev92%
5.4 min/game · 10.84 xGF/60 · P(intact) 12%
- UTA shorthanded time +2%
- UTA PK xGA/60 +9%
- Together 1 of last 3
- DK correlation .28
Liam O'Brien0.1%, Kevin Stenlund0.1%, Brandon Tanev0.1%
5.7 min/game · 2.14 xGF/60 · P(intact) 23%
- VGK 5v5 xGA/60 −6%
- Together 2 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.