DFS data dive: Highest fantasy football ceilings of NFL Week 9

Key to DFS success: Random combinations of historically similar matchups can identify counterintuitive and lower-cost DFS options with exceeding upside.
Best relative DFS values: Aaron Rodgers at quarterback, Kenneth Walker at running back, Allen Lazard and Christian Kirk at wide receiver, Dawson Knox at tight end, Los Angeles Chargers at defense are the best values relative to their DFS price for Week 9.

Estimated reading time: 4 minutes

I publish analyses on the single-game DraftKings showdown slates that use the combination of current projections, historical game results and similarity algorithms to simulate an upcoming game by looking back at the most similar historical matchups. In this analysis, I’m taking the same outline and applying it instead to the DFS main slate by projecting the likelihood each individual quarterback, running back, wide receiver, tight end and D/ST option will be the highest scorer of the slate. In doing this, we can find the unlikely tournament plays who may not have been on your radar.

QUARTERBACKS

Highest %	Player	Team	Opponent	DK Fpts	DK Salary	FD Fpts	FD Salary
11.4	Josh Allen	BUF	NYJ	26.3	8,500	24.7	9,300
9.7	Aaron Rodgers	GB	DET	23.6	5,900	22.2	7,000
8.1	Kyler Murray	ARZ	SEA	22.8	7,400	21.5	8,200
8.0	Justin Herbert	LAC	ATL	22.6	7,200	21.2	7,800
7.2	Joe Burrow	CIN	CAR	22.8	6,600	21.3	8,500
6.3	Marcus Mariota	ATL	LAC	21.0	5,300	19.6	7,100
5.3	Derek Carr	LV	JAX	19.0	5,400	17.6	6,800
5.2	Tua Tagovailoa	MIA	CHI	21.8	6,700	20.3	8,000
5.2	Jared Goff	DET	GB	15.1	5,500	14.2	7,100
5.0	Trevor Lawrence	JAX	LV	17.9	5,200	16.6	6,800
4.4	Justin Fields	CHI	MIA	17.6	5,300	16.4	7,400
4.1	Geno Smith	SEA	ARZ	19.9	5,800	18.5	7,500
4.1	Tom Brady	TB	LA	22.0	6,000	20.2	6,900
3.8	P.J. Walker	CAR	CIN	15.4	5,200	14.3	6,500
3.6	Kirk Cousins	MIN	WAS	17.9	6,200	16.7	7,900
3.2	Matthew Stafford	LA	TB	18.2	5,600	16.9	6,700
2.8	Taylor Heinicke	WAS	MIN	16.9	5,400	15.9	7,200
2.5	Zach Wilson	NYJ	BUF	14.8	5,100	14.0	6,600
1.5	Sam Ehlinger	IND	NE	15.9	5,000	15.0	6,300
0.6	Mac Jones	NE	IND	17.1	5,100	16.1	6,400

RUNNING BACKS

Highest %	Player	Team	Opponent	DK Fpts	DK Salary	FD Fpts	FD Salary
9.1	Austin Ekeler	LAC	ATL	18.5	8,800	15.6	9,400
7.9	Aaron Jones	GB	DET	16.0	7,400	14.0	7,800
7.6	D'Andre Swift	DET	GB	14.3	6,400	12.1	7,500
7.3	Kenneth Walker III	SEA	ARZ	16.4	6,200	14.4	8,300
6.5	Josh Jacobs	LV	JAX	16.4	7,300	14.4	8,800
6.4	Devin Singletary	BUF	NYJ	9.5	5,700	8.5	6,000
6.3	Leonard Fournette	TB	LA	12.7	6,600	11.1	7,100
6.2	James Conner	ARZ	SEA	11.1	5,800	9.8	6,600
5.3	Jonathan Taylor	IND	NE	16.7	7,700	14.5	6,800
5.2	Rhamondre Stevenson	NE	IND	14.0	6,200	12.4	8,000
4.9	Dalvin Cook	MIN	WAS	18.4	7,800	15.8	8,500
4.6	D'Onta Foreman	CAR	CIN	10.4	6,000	9.3	7,300
4.6	Tyler Allgeier	ATL	LAC	9.9	5,400	8.9	6,400
4.5	Raheem Mostert	MIA	CHI	14.4	6,100	12.6	6,500
3.4	Travis Etienne	JAX	LV	15.3	6,300	13.3	7,600
3.4	Antonio Gibson	WAS	MIN	10.7	5,500	9.3	6,100
2.6	James Robinson	NYJ	BUF	8.0	5,400	7.1	6,000
2.1	David Montgomery	CHI	MIA	10.1	6,000	9.0	7,000
2.1	Darrell Henderson	LA	TB	12.0	5,100	10.7	5,700
1.9	Joe Mixon	CIN	CAR	17.6	6,500	15.2	8,100

WIDE RECEIVERS

Highest %	Player	Team	Opponent	DK Fpts	DK Salary	FD Fpts	FD Salary
9.3	Allen Lazard	GB	DET	13.6	6,000	11.1	6,500
7.7	Stefon Diggs	BUF	NYJ	17.8	8,400	14.0	8,900
7.2	Christian Kirk	JAX	LV	13.7	5,500	10.9	6,300
7.0	Josh Palmer	LAC	ATL	12.5	5,100	9.9	6,200
6.5	Cooper Kupp	LA	TB	21.1	8,900	16.3	9,000
6.3	Davante Adams	LV	JAX	17.9	8,100	14.0	8,100
6.1	Jakobi Meyers	NE	IND	13.2	5,400	10.3	6,800
5.8	Mike Evans	TB	LA	19.2	7,200	15.2	7,700
5.7	DeAndre Hopkins	ARZ	SEA	19.5	7,900	15.2	8,600
5.5	Drake London	ATL	LAC	15.9	4,900	12.5	5,600
5.4	Amon-Ra St. Brown	DET	GB	14.7	6,600	11.2	7,100
4.3	Justin Jefferson	MIN	WAS	18.8	8,600	14.8	9,000
4.2	Tee Higgins	CIN	CAR	19.7	7,300	15.7	8,000
4.0	D.K. Metcalf	SEA	ARZ	15.7	6,400	12.6	7,400
3.9	Darnell Mooney	CHI	MIA	11.2	4,700	8.9	6,100
3.7	Michael Pittman Jr.	IND	NE	12.6	6,800	9.8	6,400
3.1	D.J. Moore	CAR	CIN	18.1	5,800	14.0	7,000
2.5	Terry McLaurin	WAS	MIN	13.5	5,900	10.6	7,200
2.3	Garrett Wilson	NYJ	BUF	12.9	4,800	10.2	5,800
2.0	Tyreek Hill	MIA	CHI	23.2	8,500	18.1	8,700

TIGHT ENDS

Highest %	Player	Team	Opponent	DK Fpts	DK Salary	FD Fpts	FD Salary
9.6	Zach Ertz	ARZ	SEA	10.6	5,100	8.3	6,600
9.2	Mike Gesicki	MIA	CHI	8.0	4,000	6.5	5,500
8.1	Dawson Knox	BUF	NYJ	10.2	3,500	8.2	5,100
7.9	T.J. Hockenson	MIN	WAS	9.5	5,000	7.6	6,200
7.3	Gerald Everett	LAC	ATL	12.4	4,800	9.8	5,800
6.8	Darren Waller	LV	JAX	10.0	4,900	7.9	6,000
5.7	Robert Tonyan	GB	DET	11.3	3,800	9.0	5,000
5.7	Hunter Henry	NE	IND	8.0	3,000	6.4	4,700
5.6	Hayden Hurst	CIN	CAR	9.6	3,600	7.6	5,300
5.2	Tommy Tremble	CAR	CIN	5.3	2,700	4.2	4,500
4.7	Cade Otton	TB	LA	7.5	3,100	6.0	4,800
4.4	Brock Wright	DET	GB	8.8	2,500	6.9	4,400
4.3	Tyler Higbee	LA	TB	11.3	3,700	8.7	6,100
3.8	Kyle Pitts	ATL	LAC	13.0	4,500	10.4	6,300
3.3	Logan Thomas	WAS	MIN	6.3	2,900	5.0	5,000
3.0	Tyler Conklin	NYJ	BUF	6.8	3,200	5.2	5,200
2.7	Evan Engram	JAX	LV	9.0	3,300	7.0	5,200
2.5	Noah Fant	SEA	ARZ	7.9	2,900	6.2	4,800
1.8	Cole Kmet	CHI	MIA	7.6	3,000	5.9	4,700
1.1	Kylen Granson	IND	NE	3.2	2,700	2.5	4,400

DEFENSE/SPECIAL TEAMS

Highest %	Player	Team	Opponent	DK Fpts	DK Salary	FD Fpts	FD Salary
8.9	Bengals	CIN	CAR	10.6	4,000	10.6	4,400
8.8	Chargers	LAC	ATL	6.5	3,400	6.5	3,900
8.4	Patriots	NE	IND	7.7	4,100	7.7	4,900
8.2	Bills	BUF	NYJ	8.8	4,300	8.8	5,000
8.0	Vikings	MIN	WAS	7.6	3,500	7.6	4,500
7.7	Dolphins	MIA	CHI	9.6	3,800	9.6	3,600
7.1	Buccaneers	TB	LA	6.8	3,000	6.8	4,700
7.0	Raiders	LV	JAX	6.7	3,200	6.7	3,500
5.9	Packers	GB	DET	7.1	3,700	7.1	4,100
5.9	Cardinals	ARZ	SEA	7.3	2,900	7.3	4,000
5.3	Falcons	ATL	LAC	5.4	2,800	5.4	3,100
4.9	Seahawks	SEA	ARZ	6.2	2,500	6.2	4,100
4.7	Jets	NYJ	BUF	5.2	2,000	5.2	3,400
4.2	Colts	IND	NE	6.7	2,700	6.7	4,200
3.9	Jaguars	JAX	LV	5.7	3,100	5.7	3,800
3.8	Rams	LA	TB	4.3	3,300	4.3	4,300
3.5	Lions	DET	GB	3.5	2,600	3.5	3,200
3.4	Panthers	CAR	CIN	5.4	2,300	5.4	3,300
3.3	Commanders	WAS	MIN	5.8	2,400	5.8	3,700
1.6	Bears	CHI	MIA	5.6	2,500	5.6	3,000

METHODOLOGY

For each game on the DFS Sunday main slate, I looked through thousands of NFL matchups from 2014-2022 and found the closest analogies according to the following parameters: betting spread, over/under and average fantasy points scoring for the top-ranked positional players of both rosters (QB1, RB1, WR1, TE1).

Once I find the 75 most similar matchups for each upcoming game, I simulate the main slate 10,000 times by randomly choosing one of the 75 matchups for each game. Then, I find the highest-scoring quarterback, running back, wide receiver, tight end and D/ST on the entire slate.

The last step is totaling the number of times a particular team shows up as the top option for the slate at each position and dividing by the total simulations. That number is what I call the “highest-scoring %” in the team-labeled bar charts below. Below the charts, I join the highest-projected player on that team for the position, then list their projected fantasy points and salaries for DraftKings and FanDuel.