×

Create User Account

Create Account An email will be sent to you for verification before account will be active.

Enter Verification Code

A 4 digit verification code has been emailed to you. Please enter the code here.

If you have not received your verification code, please check your spam folder, or click here to resend the code.

Fanduel - NHL
2017-05-21
Filter Players
Apply filters
Line
Power Play Unit
Projected Score
Salary
Value
Consistency
  • ALL
  • C
  • W
  • D
  • G
  • All
  • My Pool
  • Excluded Players
  • Locks
  • Injuries
Pos Team Opp Status / Line PP Unit Win % Salary Ceiling Avg FC Proj My Proj Exposure Con. Value Actual Score Actual Val
Pekka Rinne
G NSH vs ANA prob 60% 8700 60.0 18.4 22.73 22.73 % 65 2.60
Craig Anderson
G OTT @ PIT prob 33.3% 8700 49.6 20.5 17.45 17.45 % 66 2.00 -8.0
Sidney Crosby
C PIT vs OTT 1 1 66.7% 8600 57.8 15.9 18.94 18.94 % 63 2.20 25.8 3
Marc-Andre Fleury
G PIT vs OTT prob 66.7% 8400 48.8 18.9 0.00 0.00 % 63 0.00
Evgeni Malkin
C PIT vs OTT 2 1 66.7% 8400 54.3 15.5 19.41 19.41 % 64 2.30 27.1 3.2
Matt Murray
G PIT vs OTT prob 66.7% 8400 45.6 20.6 22.78 22.78 % 69 2.70 40.0 4.8
John Gibson
G ANA @ NSH prob 40% 8300 50.4 17.6 18.42 18.42 % 60 2.20
Filip Forsberg
W NSH vs ANA 1 1 60% 8000 55.7 12.9 12.82 12.82 % 60 1.60
Ryan Getzlaf
C ANA @ NSH 1 1 40% 7600 46.4 14.1 15.04 15.04 % 65 2.00
Mike Condon
G OTT @ PIT 33.3% 7500 53.6 14.3 0.00 0.00 % 51 0.00 3.2 0.4
Tristan Jarry
G PIT vs OTT prob 66.7% 7500 5.6 5.6 0.00 0.00 % 0 0.00
Juuse Saros
G NSH vs ANA 60% 7500 43.2 18.4 0.00 0.00 % 66 0.00
Jonathan Bernier
G ANA @ NSH 40% 7500 54.4 15.1 0.00 0.00 % 51 0.00
Phil Kessel
W PIT vs OTT 2 1 66.7% 7200 54.6 13.2 14.43 14.43 % 63 2.00 22.6 3.1
Erik Karlsson
D OTT @ PIT 1 1 33.3% 7100 50.3 16.2 13.67 13.67 % 71 1.90 4.8 0.7
Jakob Silfverberg
W ANA @ NSH 2 1 40% 6500 55.7 10.8 12.03 12.03 % 57 1.90
Mike Hoffman
W OTT @ PIT 3 1 33.3% 6500 54.6 12.3 9.33 9.33 % 60 1.40 4.8 0.7
Rickard Rakell
W ANA @ NSH 1 2 40% 6400 45.8 9.5 12.15 12.15 % 54 1.90
Roman Josi
D NSH vs ANA 1 1 60% 6300 38.9 14.4 14.90 14.90 % 72 2.40
Bobby Ryan
W OTT @ PIT 2 1 33.3% 6300 48.8 10.5 7.21 7.21 % 60 1.10 4.8 0.8
Ryan Johansen
C NSH vs ANA 1 1 60% 6300 51.2 11.6 9.88 9.88 % 60 1.60
James Neal
W NSH vs ANA 3 1 60% 6100 45.6 12.1 10.70 10.70 % 60 1.80
Viktor Arvidsson
W NSH vs ANA 1 1 60% 5900 48.8 10.4 13.41 13.41 % 58 2.30
Kyle Turris
C OTT @ PIT 1 2 33.3% 5700 39.2 11.4 8.63 8.63 % 63 1.50 6.4 1.1
Jake Guentzel
W PIT vs OTT 1 2 66.7% 5600 44.5 13.0 18.23 18.23 % 58 3.30 0.0
Corey Perry
W ANA @ NSH 1 2 40% 5600 52.2 12.5 9.62 9.62 % 58 1.70
Patric Hornqvist
W PIT vs OTT 3 1 66.7% 5400 54.1 13.0 11.71 11.71 % 62 2.20
P.K. Subban
D NSH vs ANA 2 2 60% 5300 40.2 12.3 10.79 10.79 % 67 2.00
Justin Schultz
D PIT vs OTT 1 1 66.7% 5200 35.2 8.7 11.06 11.06 % 58 2.10
Jean-Gabriel Pageau
C OTT @ PIT 4 33.3% 5200 56.0 8.6 8.67 8.67 % 52 1.70 4.8 0.9
Cam Fowler
D ANA @ NSH 1 1 40% 5200 31.7 9.3 9.26 9.26 % 64 1.80
Ryan Ellis
D NSH vs ANA 1 2 60% 5100 35.2 10.4 15.09 15.09 % 64 3.00
Mark Stone
W OTT @ PIT 3 2 33.3% 5100 54.1 11.7 6.74 6.74 % 60 1.30 3.2 0.6
Ryan Kesler
C ANA @ NSH 2 1 40% 5100 45.6 11.6 9.30 9.30 % 61 1.80
Patrick Eaves
W ANA @ NSH 1 40% 4800 48.2 10.2 0.00 0.00 % 55 0.00
Derick Brassard
C OTT @ PIT 2 1 33.3% 4800 68.0 10.7 7.25 7.25 % 55 1.50 3.2 0.7
Sami Vatanen
D ANA @ NSH 3 40% 4600 37.0 10.3 8.10 8.10 % 65 1.80
Bryan Rust
W PIT vs OTT 2 66.7% 4300 52.0 7.6 10.40 10.40 % 42 2.40 28.0 6.5
Nick Ritchie
W ANA @ NSH 3 40% 4100 22.4 6.3 5.81 5.81 % 53 1.40
Zack Smith
C OTT @ PIT 3 33.3% 4100 38.4 7.2 3.90 3.90 % 47 1.00 0.0
Conor Sheary
W PIT vs OTT 1 2 66.7% 4000 40.0 8.7 10.56 10.56 % 48 2.60
Nick Bonino
C PIT vs OTT 3 2 66.7% 3900 50.9 9.5 9.63 9.63 % 57 2.50 20.8 5.3
Hampus Lindholm
D ANA @ NSH 2 40% 3900 32.8 8.0 6.66 6.66 % 59 1.70
Mattias Ekholm
D NSH vs ANA 2 60% 3800 30.9 7.2 6.56 6.56 % 57 1.70
Olli Maatta
D PIT vs OTT 2 2 66.7% 3800 22.4 6.6 8.12 8.12 % 62 2.10 18.4 4.8
Clarke MacArthur
W OTT @ PIT 4 1 33.3% 3800 37.8 8.8 5.04 5.04 % 59 1.30 3.2 0.8
Marc Methot
D OTT @ PIT 1 33.3% 3700 28.8 5.5 3.90 3.90 % 54 1.10 8.0 2.2
Dion Phaneuf
D OTT @ PIT 2 2 33.3% 3600 35.4 9.3 5.01 5.01 % 62 1.40 4.8 1.3
Colin Wilson
W NSH vs ANA 3 60% 3500 45.8 8.6 7.41 7.41 % 52 2.10
Carl Hagelin
W PIT vs OTT 66.7% 3500 0.00 8.3 0.00 0.00 % 54 0.00 3.2 0.9
Chris Wideman
D OTT @ PIT 3 2 33.3% 3500 25.6 6.1 4.65 4.65 % 59 1.30 3.2 0.9
Andrew Cogliano
W ANA @ NSH 2 40% 3500 33.6 7.2 4.87 4.87 % 53 1.40
Chris Kunitz
W PIT vs OTT 66.7% 3500 0.00 8.3 0.00 0.00 % 54 0.00 4.8 1.4
Mark Streit
D PIT vs OTT 66.7% 3500 0.00 9.2 0.00 0.00 % 61 0.00 11.2 3.2
Brandon Montour
D ANA @ NSH 1 2 40% 3400 21.6 7.2 6.35 6.35 % 66 1.90
Nate Thompson
C ANA @ NSH 4 40% 3400 32.8 4.5 3.75 3.75 % 43 1.10
Mike Fisher
C NSH vs ANA 2 2 60% 3400 37.3 9.1 7.20 7.20 % 58 2.10
Alexandre Burrows
W OTT @ PIT 1 2 33.3% 3400 34.1 7.6 5.20 5.20 % 52 1.50
Cody Ceci
D OTT @ PIT 2 33.3% 3400 28.5 7.7 5.93 5.93 % 65 1.70 1.6 0.5
Ian Cole
D PIT vs OTT 1 66.7% 3300 26.4 6.7 9.07 9.07 % 58 2.70 11.2 3.4
Antoine Vermette
C ANA @ NSH 3 2 40% 3300 39.7 7.4 4.43 4.43 % 46 1.30
Austin Watson
W NSH vs ANA 4 60% 3300 34.4 5.1 6.30 6.30 % 44 1.90
Matt Cullen
C PIT vs OTT 4 66.7% 3300 30.4 6.7 7.73 7.73 % 48 2.30 18.4 5.6
Tom Kuhnhackl
W PIT vs OTT 4 66.7% 3200 29.6 5.3 5.72 5.72 % 44 1.80
Scott Wilson
W PIT vs OTT 3 66.7% 3200 20.8 6.0 6.11 6.11 % 53 1.90 16.8 5.3
Calle Jarnkrok
C NSH vs ANA 2 2 60% 3200 30.9 5.8 6.02 6.02 % 41 1.90
Ryan Dzingel
W OTT @ PIT 1 33.3% 3200 28.8 5.7 2.63 2.63 % 44 0.80
Ron Hainsey
D PIT vs OTT 3 66.7% 3200 32.0 6.2 7.44 7.44 % 58 2.30 4.8 1.5
Carter Rowney
W PIT vs OTT 4 66.7% 3200 21.6 4.2 4.95 4.95 % 40 1.50 28.8 9
Chris Wagner
W ANA @ NSH 3 40% 3200 23.2 4.0 3.66 3.66 % 35 1.10
Trevor Daley
D PIT vs OTT 2 2 66.7% 3200 39.7 8.4 6.28 6.28 % 57 2.00 30.6 9.6
Fredrik Claesson
D OTT @ PIT 33.3% 3200 0.00 5.1 0.00 0.00 % 48 0.00 0.0
Ondrej Kase
W ANA @ NSH 4 40% 3100 23.2 4.8 3.01 3.01 % 42 1.00
Josh Manson
D ANA @ NSH 2 40% 3100 20.8 5.3 5.48 5.48 % 55 1.80
Brian Dumoulin
D PIT vs OTT 3 66.7% 3100 24.0 5.5 6.48 6.48 % 58 2.10 6.4 2.1
Vernon Fiddler
C NSH vs ANA 4 60% 3100 36.0 5.4 2.91 2.91 % 38 0.90
Matt Irwin
D NSH vs ANA 3 60% 3100 30.9 6.7 4.51 4.51 % 56 1.50
Ben Harpur
D OTT @ PIT 3 33.3% 3100 12.8 4.0 3.68 3.68 % 53 1.20 3.2 1
Shea Theodore
D ANA @ NSH 3 2 40% 3100 35.2 7.2 6.89 6.89 % 50 2.20
Viktor Stalberg
W OTT @ PIT 2 33.3% 3100 32.0 5.7 4.19 4.19 % 49 1.40 1.6 0.5
Tom Pyatt
W OTT @ PIT 4 33.3% 3100 29.6 6.0 4.00 4.00 % 54 1.30 0.0
Kevin Bieksa
D ANA @ NSH 40% 3100 0.00 6.3 0.00 0.00 % 62 0.00
Colton Sissons
C NSH vs ANA 3 60% 3100 44.0 4.0 5.60 5.60 % 14 1.80
Chris Kelly
W OTT @ PIT 33.3% 3000 0.00 5.2 0.00 0.00 % 48 0.00
Brad Hunt
D NSH vs ANA 60% 3000 0.00 6.2 0.00 0.00 % 57 0.00
Cody McLeod
W NSH vs ANA 60% 3000 0.00 3.5 0.00 0.00 % 32 0.00
Simon Despres
D ANA @ NSH 40% 3000 0.00 6.7 0.00 0.00 % 63 0.00
Oskar Sundqvist
W PIT vs OTT 66.7% 3000 0.00 2.7 0.00 0.00 % 33 0.00
Harry Zolnierczyk
W NSH vs ANA 4 60% 3000 16.8 3.4 4.04 4.04 % 34 1.30
Chad Ruhwedel
D PIT vs OTT 66.7% 3000 0.00 5.5 0.00 0.00 % 58 0.00
Miikka Salomaki
W NSH vs ANA 2 60% 3000 16.8 3.8 3.49 3.49 % 44 1.20
Craig Smith
W NSH vs ANA 60% 3000 0.00 9.0 0.00 0.00 % 54 0.00
Korbinian Holzer
D ANA @ NSH 40% 3000 0.00 4.0 0.00 0.00 % 45 0.00
Josh Archibald
W PIT vs OTT 66.7% 3000 0.00 5.0 0.00 0.00 % 22 0.00 1.6 0.5
P.A. Parenteau
W NSH vs ANA 60% 3000 0.00 8.3 0.00 0.00 % 54 0.00
Nic Kerdiles
W ANA @ NSH 4 40% 3000 3.2 1.2 2.31 2.31 % 45 0.80
Pontus Aberg
W NSH vs ANA 60% 3000 0.00 3.4 0.00 0.00 % 37 0.00
Yannick Weber
D NSH vs ANA 3 60% 3000 33.0 5.1 1.98 1.98 % 47 0.70
Anthony Bitetto
D NSH vs ANA 60% 3000 0.00 4.0 0.00 0.00 % 46 0.00
Tommy Wingels
W OTT @ PIT 33.3% 3000 0.00 6.3 0.00 0.00 % 47 0.00 1.6 0.5
Jared Boll
W ANA @ NSH 40% 3000 0.00 1.6 0.00 0.00 % 15 0.00
Logan Shaw
W ANA @ NSH 40% 3000 0.00 3.9 0.00 0.00 % 44 0.00
Chris Neil
W OTT @ PIT 33.3% 3000 0.00 2.8 0.00 0.00 % 28 0.00
Mark Borowiecki
D OTT @ PIT 33.3% 3000 0.00 4.0 0.00 0.00 % 54 0.00
All
None
My Projections
Add Selected to Group
Create New Group
×
Save As
Name is invalid.
Load Settings
Save Name Last Saved Delete
No saved settings found
Load Settings Please select a save file.
Unique Players

Team Salary
Max salary is $55,000 if left blank.

Offensive Players vs Goalie

Global Exposure Setting
apply exposure as

Randomness Setting
0%
Players Per Team Change All MAX
MIN MAX MIN MAX
OTT
@
PIT
ANA
@
NSH
Add Stack (you can add up to 3) Click here for more info

If you want to create lineups with players from the same team and same Line or PP unit (otherwise known as stacking) this is where to do it. You can add a single stack with the remaining players not needing to be from the same team/line/PP Unit, or you can add multiple stacks per lineup so that all of the players are paired with other players from the same team/line/PP Unit.

To get started, click on the Add Stack link. You will need to select how many players you want used in the stack, which Line/PP units you want possibly stacked and which teams you would like possibly used for the first stack.

You can select multiple Lines/PP Units, or leave this blank and it will just stack players from the same team. You can also choose to stack only Forwards (Centers and Wings) or allow all positions (Centers, Wings and Defense Men) to be stacked.

If you want, you can add a 2nd and 3rd stack the same way as above. This is how you can create a lineup with 4 skaters from 1 team, and 4 skaters from another.

Positional Stacking
Create New Stacking Rule
Stack with of Positions From
Stacking Rules
Save Name Last Saved Delete
No saved settings found
Load Groups There was an error loading your groups.
×
Save As Name is invalid.
×
Load Playerpool
Save Name Last Saved
No Saved playerpools found
Selected  
Load Playerpool Please select a save file.
×
Load Saved Crunches
Name Number of Teams Last Saved Delete
Name Number of Teams
  1. Take a tour

    Check out the features of Lineup Rewind.

  2. Sport Selection

    Select a sport (NBA, NFL) from this drop down menu.

  3. Site Selection

    Select a site (Fanduel, Draftkings etc.) from this drop down menu.

  4. Game Filter

    Use the Game Filter to remove any games you dont want to use. Useful for contests like Late Night NBA, or Sun/Mon night NFL.

  5. Score filter

    Select between projected score and actual scores from the day.

  6. Calculate Teams

    Hit 'calculate' to have Fantasy Cruncher create the best teams based on the actual data.

  7. Tour End

    Thanks for checking out the tour! If you want to use this tool to crunch numbers for fresh games, use lineup cruncher instead! If you have any more questions, check out our tutorials, browse the forums, or send us a message at support@fantasycruncher.com.