NHL Draftkings_showdown 2019-02-10 Optimal Lineups | Fantasy Cruncher

John Tavares	C	TOR	@ NYR	1	1	3.50	57.1%	12200	45.0	13.4	12.46	12.46	%	%	69	1.02	16.0	1.3
Ryan O'Reilly	C	STL	@ NSH	1	1	2.45	40%	12200	37.0	10.2	7.36	7.36	%	%	65	0.6	14.0	1.1
Mika Zibanejad	C	NYR	vs TOR	1	1	3.00	42.9%	11800	42.0	9.8	9.77	9.77	%	%	62	0.83	16.0	1.4
Roman Josi	D	NSH	vs STL	1	1	3.05	60%	11800	35.2	12.0	10.60	10.60	%	%	74	0.9	24.1	2
Auston Matthews	C	TOR	@ NYR	2	1	3.50	57.1%	11400	47.0	12.9	10.98	10.98	%	%	67	0.96	11.1	1
Viktor Arvidsson	W	NSH	vs STL	1	1	3.05	60%	11000	45.0	10.6	10.21	10.21	%	%	64	0.93	28.0	2.5
Mitchell Marner	W	TOR	@ NYR	1	1	3.50	57.1%	10500	41.0	10.6	10.76	10.76	%	%	63	1.02	8.0	0.8
Filip Forsberg	W	NSH	vs STL	1	1	3.05	60%	10300	46.0	11.7	8.39	8.39	%	%	65	0.81	22.0	2.1
Ryan Johansen	C	NSH	vs STL	1	1	3.05	60%	9700	40.0	9.1	6.76	6.76	%	%	64	0.7	14.0	1.4
Vladimir Tarasenko	W	STL	@ NSH	1	1	2.45	40%	9600	45.1	13.1	6.84	6.84	%	%	68	0.71	44.1	4.6
Morgan Rielly	D	TOR	@ NYR	1	1	3.50	57.1%	9600	31.4	8.8	9.84	9.84	%	%	67	1.03	13.1	1.4
Nazem Kadri	C	TOR	@ NYR	3	1	3.50	57.1%	9200	45.0	9.9	7.52	7.52	%	%	65	0.82	24.0	2.6
Brayden Schenn	W	STL	@ NSH	1	1	2.45	40%	8900	45.0	9.1	4.83	4.83	%	%	61	0.54	0.0
Kevin Hayes	C	NYR	vs TOR	2	1	3.00	42.9%	8800	27.0	7.4	6.08	6.08	%	%	57	0.69	16.0	1.8
David Perron	W	STL	@ NSH			2.45	40%	8800	0.00	7.7	0.00	0.00	%	%	59	0.00
Juuse Saros	G	NSH	vs STL	confirm		2.45	60%	8400	26.4	9.4	8.33	8.33	%	%	68	0.99	4.6	0.5
Alexandar Georgiev	G	NYR	vs TOR	confirm		3.50	42.9%	8300	20.2	7.4	7.53	7.53	%	%	63	0.91	25.0	3
Craig Smith	W	NSH	vs STL	2	2	3.05	60%	8200	43.0	8.8	6.33	6.33	%	%	62	0.77	0.0
Garret Sparks	G	TOR	@ NYR	confirm		3.00	57.1%	8200	21.6	6.3	7.59	7.59	%	%	59	0.93	7.4	0.9
Mats Zuccarello	W	NYR	vs TOR	1	1	3.00	42.9%	8000	36.1	8.8	6.29	6.29	%	%	62	0.79	16.0	2
Ryan Ellis	D	NSH	vs STL	1	2	3.05	60%	7900	28.2	9.0	6.80	6.80	%	%	68	0.86	11.1	1.4
Chris Kreider	W	NYR	vs TOR	1	1	3.00	42.9%	7700	39.0	9.0	7.63	7.63	%	%	60	0.99	13.1	1.7
Jake Allen	G	STL	@ NSH	confirm		3.05	40%	7500	26.0	9.1	6.45	6.45	%	%	70	0.86	16.0	2.1
Zach Hyman	W	TOR	@ NYR	1		3.50	57.1%	7400	26.0	6.9	6.69	6.69	%	%	61	0.9	6.0	0.8
Alex Pietrangelo	D	STL	@ NSH	1	1	2.45	40%	7300	43.4	10.2	5.90	5.90	%	%	71	0.81	18.6	2.5
Andreas Johnsson	W	TOR	@ NYR	4	2	3.50	57.1%	7200	36.1	6.8	7.13	7.13	%	%	40	0.99	0.0
Nick Bonino	C	NSH	vs STL	3		3.05	60%	7000	39.0	7.3	6.14	6.14	%	%	58	0.88	3.1	0.4
Jake Muzzin	D	TOR	@ NYR	1	2	3.50	57.1%	6800	27.3	8.5	8.57	8.57	%	%	66	1.26	4.2	0.6
Jaden Schwartz	W	STL	@ NSH	2	2	2.45	40%	6700	47.1	10.0	4.74	4.74	%	%	65	0.71	9.0	1.3
Tyler Ennis	W	TOR	@ NYR			3.50	57.1%	6600	0.00	6.4	0.00	0.00	%	%	56	0.00	0.0
Austin Watson	W	NSH	vs STL			3.05	60%	6500	0.00	5.1	0.00	0.00	%	%	50	0.00
Anthony Deangelo	D	NYR	vs TOR	1	2	3.00	42.9%	6500	25.1	5.4	3.72	3.72	%	%	50	0.57	5.1	0.8
P.K. Subban	D	NSH	vs STL	2	2	3.05	60%	6400	30.2	10.1	6.02	6.02	%	%	70	0.94	14.2	2.2
Patrick Marleau	W	TOR	@ NYR	2	2	3.50	57.1%	6200	47.0	9.0	5.42	5.42	%	%	63	0.87	11.1	1.8
Colton Parayko	D	STL	@ NSH	2		2.45	40%	6100	30.2	8.6	5.44	5.44	%	%	69	0.89	16.3	2.7
Brett Howden	W	NYR	vs TOR			3.00	42.9%	6000	0.00	4.0	0.00	0.00	%	%	46	0.00	0.0
Mattias Ekholm	D	NSH	vs STL	2		3.05	60%	5800	28.3	6.6	7.70	7.70	%	%	61	1.33	14.1	2.4
Kasperi Kapanen	W	TOR	@ NYR	2		3.50	57.1%	5800	27.0	5.7	6.30	6.30	%	%	48	1.09	12.0	2.1
Fredrik Claesson	D	NYR	vs TOR			3.00	42.9%	5600	0.00	3.4	0.00	0.00	%	%	46	0.00
Vince Dunn	D	STL	@ NSH	3	2	2.45	40%	5500	32.1	6.3	4.19	4.19	%	%	58	0.76	2.2	0.4
Miikka Salomaki	W	NSH	vs STL			3.05	60%	5500	0.00	2.9	0.00	0.00	%	%	41	0.00
Neal Pionk	D	NYR	vs TOR			3.00	42.9%	5500	0.00	7.1	0.00	0.00	%	%	62	0.00	3.1	0.6
Tyler Bozak	C	STL	@ NSH	2	2	2.45	40%	5400	38.0	7.7	3.37	3.37	%	%	58	0.62	16.2	3
William Nylander	W	TOR	@ NYR	3	2	3.50	57.1%	5400	35.0	8.9	5.25	5.25	%	%	63	0.97	6.0	1.1
Colton Sissons	W	NSH	vs STL	3		3.05	60%	5300	36.1	4.9	5.15	5.15	%	%	44	0.97	3.1	0.6
Travis Dermott	D	TOR	@ NYR	3		3.50	57.1%	5300	24.1	5.0	5.51	5.51	%	%	54	1.04	6.0	1.1
Kevin Shattenkirk	D	NYR	vs TOR	3	1	3.00	42.9%	5200	40.6	9.6	4.99	4.99	%	%	66	0.96	7.3	1.4
Kevin Fiala	W	NSH	vs STL	2	2	3.05	60%	5200	31.1	7.6	5.22	5.22	%	%	58	1	7.0	1.3
Calle Jarnkrok	W	NSH	vs STL	3		3.05	60%	5100	37.0	5.2	4.42	4.42	%	%	46	0.87	4.0	0.8
Pavel Buchnevich	W	NYR	vs TOR	2	2	3.00	42.9%	5100	24.0	6.6	4.27	4.27	%	%	55	0.84	6.0	1.2
Filip Chytil	W	NYR	vs TOR	3	2	3.00	42.9%	5100	20.0	5.9	4.15	4.15	%	%	55	0.81	2.0	0.4
Brian Boyle	C	NSH	vs STL	4	1	3.05	60%	4900	35.0	6.0	4.92	4.92	%	%	53	1	8.0	1.6
Jake Gardiner	D	TOR	@ NYR	2	2	3.50	57.1%	4900	29.3	6.6	5.64	5.64	%	%	61	1.15	1.1	0.2
Jimmy Vesey	W	NYR	vs TOR	4		3.00	42.9%	4900	35.0	6.2	4.53	4.53	%	%	52	0.92	12.0	2.4
Ron Hainsey	D	TOR	@ NYR	3		3.50	57.1%	4800	25.1	5.3	4.64	4.64	%	%	62	0.97	2.0	0.4
Oskar Sundqvist	C	STL	@ NSH	3	2	2.45	40%	4800	21.1	3.1	4.25	4.25	%	%	30	0.89	4.0	0.8
Alex Steen	W	STL	@ NSH	2		2.45	40%	4700	38.3	9.2	2.60	2.60	%	%	61	0.55	6.1	1.3
Kyle Turris	C	NSH	vs STL	2	2	3.05	60%	4600	29.3	8.8	4.38	4.38	%	%	65	0.95	6.0	1.3
Carl Gunnarsson	D	STL	@ NSH			2.45	40%	4600	0.00	3.6	0.00	0.00	%	%	52	0.00	0.0
Brady Skjei	D	NYR	vs TOR	2		3.00	42.9%	4600	26.2	6.5	4.08	4.08	%	%	64	0.89	5.3	1.2
Vladislav Namestnikov	W	NYR	vs TOR	3	2	3.00	42.9%	4500	38.1	5.9	3.67	3.67	%	%	51	0.82	3.1	0.7
Ryan Hartman	W	NSH	vs STL	4		3.05	60%	4500	38.1	6.1	3.77	3.77	%	%	53	0.84	2.0	0.4
Ryan Strome	C	NYR	vs TOR	3	2	3.00	42.9%	4400	31.0	6.5	3.37	3.37	%	%	55	0.77	7.2	1.6
Zachary Sanford	W	STL	@ NSH	3		2.45	40%	4400	23.1	3.8	2.51	2.51	%	%	42	0.57	9.5	2.2
Joel Edmundson	D	STL	@ NSH	1		2.45	40%	4300	25.2	5.4	2.44	2.44	%	%	59	0.57	6.2	1.4
Nikita Zaitsev	D	TOR	@ NYR	2		3.50	57.1%	4300	23.0	5.7	5.07	5.07	%	%	61	1.18	5.1	1.2
Jesper Fast	W	NYR	vs TOR	2		3.00	42.9%	4200	30.3	4.7	3.29	3.29	%	%	49	0.78	1.1	0.3
Zac Rinaldo	W	NSH	vs STL			3.05	60%	4200	0.00	2.0	0.00	0.00	%	%	23	0.00
Rocco Grimaldi	W	NSH	vs STL			3.05	60%	4200	0.00	4.5	0.00	0.00	%	%	49	0.00	0.0
Robert Bortuzzo	D	STL	@ NSH	3		2.45	40%	4100	15.4	4.2	2.99	2.99	%	%	57	0.73	6.6	1.6
Connor Brown	W	TOR	@ NYR	3		3.50	57.1%	4100	35.3	5.8	3.85	3.85	%	%	52	0.94	0.0
Justin Holl	D	TOR	@ NYR			3.50	57.1%	4100	0.00	0.8	0.00	0.00	%	%	0	0.00	0.0
Robert Thomas	W	STL	@ NSH	4	1	2.45	40%	4000	23.0	4.6	3.33	3.33	%	%	40	0.83	5.0	1.3
Vinni Lettieri	W	NYR	vs TOR	4		3.00	42.9%	4000	17.1	3.6	2.10	2.10	%	%	47	0.53	0.0
Marc Staal	D	NYR	vs TOR	1		3.00	42.9%	3900	20.4	4.5	3.78	3.78	%	%	61	0.97	1.1	0.3
Pat Maroon	W	STL	@ NSH	3	2	2.45	40%	3900	16.0	4.7	2.44	2.44	%	%	55	0.63	0.0
Jay Bouwmeester	D	STL	@ NSH	2		2.45	40%	3800	19.4	4.8	3.79	3.79	%	%	61	1	12.0	3.2
Par Lindholm	W	TOR	@ NYR	4		3.50	57.1%	3800	17.1	4.3	2.97	2.97	%	%	55	0.78	1.1	0.3
Matt Irwin	D	NSH	vs STL			3.05	60%	3700	0.00	4.1	0.00	0.00	%	%	46	0.00	0.0
Adam McQuaid	D	NYR	vs TOR	2		3.00	42.9%	3700	18.4	3.9	3.48	3.48	%	%	57	0.94	15.3	4.1
Robby Fabbri	W	STL	@ NSH			2.45	40%	3600	0.00	6.1	0.00	0.00	%	%	50	0.00	0.0
Frederik Gauthier	C	TOR	@ NYR	4		3.50	57.1%	3600	16.2	2.7	2.62	2.62	%	%	36	0.73	2.0	0.6
Ivan Barbashev	C	STL	@ NSH	4		2.45	40%	3500	21.2	3.5	2.26	2.26	%	%	38	0.65	2.0	0.6
Boo Nieves	C	NYR	vs TOR	4		3.00	42.9%	3500	19.0	3.1	2.17	2.17	%	%	37	0.62	2.0	0.6
Brendan Smith	D	NYR	vs TOR	3		3.00	42.9%	3400	22.3	4.2	1.57	1.57	%	%	55	0.46	5.1	1.5
Yannick Weber	D	NSH	vs STL	3		3.05	60%	3400	26.0	3.8	2.52	2.52	%	%	45	0.74	2.0	0.6
Frederick Gaudreau	C	NSH	vs STL			3.05	60%	3300	0.00	1.8	0.00	0.00	%	%	19	0.00	0.0
Igor Ozhiganov	D	TOR	@ NYR			3.50	57.1%	3300	0.00	2.7	0.00	0.00	%	%	35	0.00	0.0
Dan Hamhuis	D	NSH	vs STL	3		3.05	60%	3200	22.2	4.7	2.21	2.21	%	%	59	0.69	0.0
Mackenzie Maceachern	W	STL	@ NSH	4		2.45	40%	3100	15.1	3.2	2.02	2.02	%	%	26	0.65	0.0
Eeli Tolvanen	W	NSH	vs STL			3.05	60%	3100	0.00	1.6	0.00	0.00	%	%	0	0.00
Jordan Nolan	W	STL	@ NSH			2.45	40%	3000	0.00	2.5	0.00	0.00	%	%	38	0.00
Chris Butler	D	STL	@ NSH			2.45	40%	3000	0.00	4.2	0.00	0.00	%	%	52	0.00	0.0
Matt Beleskey	W	NYR	vs TOR			3.00	42.9%	3000	0.00	6.6	0.00	0.00	%	%	55	0.00
Cody McLeod	W	NSH	vs STL	4		3.05	60%	3000	18.1	2.6	0.80	0.80	%	%	28	0.27	0.0
Chris Thorburn	W	STL	@ NSH			2.45	40%	3000	0.00	2.4	0.00	0.00	%	%	34	0.00
Peter Holland	C	NYR	vs TOR			3.00	42.9%	3000	0.00	5.4	0.00	0.00	%	%	52	0.00
Josh Jooris	W	TOR	@ NYR			3.50	57.1%	3000	0.00	4.1	0.00	0.00	%	%	39	0.00
Tyler Gaudet	C	NSH	vs STL			3.05	60%	3000	0.00	1.6	0.00	0.00	%	%	12	0.00
Martin Marincin	D	TOR	@ NYR			3.50	57.1%	3000	0.00	3.0	0.00	0.00	%	%	43	0.00
Laurent Dauphin	C	NSH	vs STL			3.05	60%	3000	0.00	2.0	0.00	0.00	%	%	10	0.00
Connor Brickley	W	NYR	vs TOR			3.00	42.9%	3000	0.00	2.6	0.00	0.00	%	%	27	0.00
Nikita Soshnikov	W	STL	@ NSH			2.45	40%	3000	0.00	3.3	0.00	0.00	%	%	33	0.00
Anthony Richard	C	NSH	vs STL			3.05	60%	3000	0.00	0.2	0.00	0.00	%	%	0	0.00
Sammy Blais	W	STL	@ NSH			2.45	40%	3000	0.00	3.2	0.00	0.00	%	%	24	0.00
Phil Di Giuseppe	W	NSH	vs STL			3.05	60%	3000	0.00	3.5	0.00	0.00	%	%	36	0.00
Cole Schneider	W	NSH	vs STL			3.05	60%	3000	0.00	2.7	0.00	0.00	%	%	48	0.00
Nicholas Baptiste	W	NSH	vs STL			3.05	60%	3000	0.00	3.6	0.00	0.00	%	%	39	0.00
Jordan Schmaltz	D	STL	@ NSH			2.45	40%	3000	0.00	1.8	0.00	0.00	%	%	21	0.00
Alexandre Carrier	D	NSH	vs STL			3.05	60%	3000	0.00	0.6	0.00	0.00	%	%	17	0.00
Rob O'Gara	D	NYR	vs TOR			3.00	42.9%	3000	0.00	3.2	0.00	0.00	%	%	54	0.00
Frederic Allard	D	NSH	vs STL			3.05	60%	3000	0.00	0.0	0.00	0.00	%	%	0	0.00
Jordan Kyrou	C	STL	@ NSH			2.45	40%	3000	0.00	3.2	0.00	0.00	%	%	45	0.00
Trevor Moore	W	TOR	@ NYR			3.50	57.1%	3000	0.00	2.4	0.00	0.00	%	%	30	0.00
John Gilmour	D	NYR	vs TOR			3.00	42.9%	3000	0.00	5.9	0.00	0.00	%	%	63	0.00
Andreas Borgman	D	TOR	@ NYR			3.50	57.1%	3000	0.00	3.4	0.00	0.00	%	%	43	0.00
Calle Rosen	D	TOR	@ NYR			3.50	57.1%	3000	0.00	2.6	0.00	0.00	%	%	16	0.00
Jake Walman	D	STL	@ NSH			2.45	40%	3000	0.00	4.7	0.00	0.00	%	%	56	0.00
Steven Fogarty	C	NYR	vs TOR			3.00	42.9%	3000	0.00	2.2	0.00	0.00	%	%	29	0.00
Jakub Jerabek	D	STL	@ NSH			2.45	40%	3000	0.00	2.0	0.00	0.00	%	%	16	0.00
Lias Andersson	C	NYR	vs TOR			3.00	42.9%	3000	0.00	3.1	0.00	0.00	%	%	46	0.00
Mitch Reinke	D	STL	@ NSH			2.45	40%	3000	0.00	0.7	0.00	0.00	%	%	1	0.00
Nolan Stevens	C	STL	@ NSH			2.45	40%	3000	0.00	0.0	0.00	0.00	%	%	0	0.00
Michael Lindqvist	C	NYR	vs TOR			3.00	42.9%	3000	0.00	0.2	0.00	0.00	%	%	0	0.00
Ville Meskanen	C	NYR	vs TOR			3.00	42.9%	3000	0.00	0.2	0.00	0.00	%	%	0	0.00
Timothy Gettinger	W	NYR	vs TOR			3.00	42.9%	3000	0.00	2.1	0.00	0.00	%	%	28	0.00
Semyon Der-Arguchintsev	C	TOR	@ NYR			3.50	57.1%	3000	0.00	0.6	0.00	0.00	%	%	0	0.00
Pierre Engvall	W	TOR	@ NYR			3.50	57.1%	3000	0.00	2.6	0.00	0.00	%	%	24	0.00
Jeremy Bracco	W	TOR	@ NYR			3.50	57.1%	3000	0.00	5.5	0.00	0.00	%	%	50	0.00
Carl Persson	C	NSH	vs STL			3.05	60%	3000	0.00	0.0	0.00	0.00	%	%	0	0.00

General
Position Stacks
Team Line PP Stacks
Groups
My Data

Save General Settings Load Saved Settings Restore Default Settings

Save As

include position stacks

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Unique Players per Lineup

Team Salary

Max salary is $50,000 if left blank.

Offensive Players vs Goalie

Global Exposure Setting

calculate exposure caps

After each lineup is created

Based on number of lineups requested

% change ALL players

Randomness

Use Randomness

% change ALL players

Min Proj. Included in Calc

Players Per Team Change All MAX

MIN MAX MIN MAX

STL

NSH

DET

CHI

COL

BOS

WPG

BUF

CAR

MIN

NYI

FLA

TOR

NYR

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

Stack Rule
Limit Rule

Create New Stacking Rule

Stack with of Positions From

Optional for this rule Players from the following teams

add stacking rule

Stacking Rules

Load Saved Groups

	Save Name	Last Saved	Delete
No saved settings found

Load Groups

create new group

Enable all groups Disable all groups Delete all groups

If you have uploaded your own data columns, you can use the data to enforce restrictions on the lineups created. A good use case may be uploading ownership projections and then restricting each lineup to a maximum ownership total.

Create New Rule using My Data

Use and allow a of Per Lineup add rule

Additional Rules

Load Playerpool

Save Name	Last Saved
No Saved playerpools found

Selected Show all sites

Load Playerpool

Load Saved Crunches

	Name	Number of Teams	Last Saved	Delete

	Name	Number of Teams

Load Selected Crunches Delete Selected Crunches

recover deleted tabs

Auto save my crunches

Auto recover open tabs on refresh

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