Home/NFL DFS Projections

NFL DFS Projections

A projection is not a forecast of what will happen. It is a distribution, and treating it as a single number is the most common mistake in DFS.

Updated 2026-09-09 · rebuilt daily

Projected points per game

NFL season-rate projections · 2025 season · 2026-09-09
#	Player	Team	G	FPPG	Total
1	Christian McCaffreyRB	SF	17	24.5	417
2	Puka NacuaWR	LAR	16	23.5	376
3	Josh AllenQB	BUF	17	22.2	377
4	Bijan RobinsonRB	ATL	17	21.9	372
5	Jahmyr GibbsRB	DET	17	21.6	368
6	Matthew StaffordQB	LAR	17	21.4	363
7	Drake MayeQB	NE	17	21.3	362
8	Jonathan TaylorRB	IND	17	21.3	361
9	Jaxon Smith-NjigbaWR	SEA	17	21.2	361
10	Brock PurdyQB	SF	9	21.0	189
11	Patrick MahomesQB	KC	14	20.9	293
12	Trevor LawrenceQB	JAX	17	20.8	353
13	De'Von AchaneRB	MIA	16	20.2	323
14	Ja'Marr ChaseWR	CIN	16	19.7	315
15	Jalen HurtsQB	PHI	16	19.4	311
16	Caleb WilliamsQB	CHI	17	19.2	326
17	Amon-Ra St. BrownWR	DET	17	19.1	324
18	Dak PrescottQB	DAL	17	18.9	321
19	Justin HerbertQB	LAC	16	18.8	301
20	Trey McBrideTE	ARI	17	18.6	316
21	Jared GoffQB	DET	17	18.4	313
22	Daniel JonesQB	IND	13	18.3	238
23	Bo NixQB	DEN	17	18.3	311
24	James Cook IIIRB	BUF	17	18.0	305
25	Jaxson DartQB	NYG	14	17.7	248
26	Joe BurrowQB	CIN	8	17.4	139
27	Lamar JacksonQB	BAL	13	17.4	226
28	Jacoby BrissettQB	ARI	14	17.2	241
29	George PickensWR	DAL	17	17.1	290
30	Jayden DanielsQB	WSH	7	16.9	118
31	Chris OlaveWR	NO	16	16.8	269
32	Baker MayfieldQB	TB	17	16.8	285
33	Drake LondonWR	ATL	12	16.7	201
34	Derrick HenryRB	BAL	17	16.6	283
35	Chase BrownRB	CIN	17	16.5	281
36	Kyler MurrayQB	ARI	5	16.4	82
37	Jordan LoveQB	GB	15	16.1	241
38	Josh JacobsRB	GB	15	15.9	239
39	Davante AdamsWR	LAR	14	15.9	223
40	Cam SkatteboRB	NYG	8	15.8	127
41	Kyren WilliamsRB	LAR	17	15.6	265
42	C.J. StroudQB	HOU	14	15.5	217
43	Javonte WilliamsRB	DAL	16	15.3	245
44	Justin FieldsQB	NYJ	9	15.3	138
45	Sam DarnoldQB	SEA	17	15.1	256
46	Omarion HamptonRB	LAC	9	15.1	136
47	Nico CollinsWR	HOU	15	15.0	225
48	Tyler ShoughQB	NO	11	15.0	165
49	Travis Etienne Jr.RB	JAX	17	14.9	254
50	A.J. BrownWR	PHI	15	14.7	220
51	George KittleTE	SF	11	14.7	162
52	Carson WentzQB	MIN	5	14.7	73
53	Aaron RodgersQB	PIT	16	14.6	234
54	Bryce YoungQB	CAR	16	14.6	233
55	Brock BowersTE	LV	12	14.5	174
56	Zay FlowersWR	BAL	17	14.5	246
57	Ashton JeantyRB	LV	17	14.5	246
58	Saquon BarkleyRB	PHI	16	14.5	231
59	D'Andre SwiftRB	CHI	16	14.4	231
60	CeeDee LambWR	DAL	14	14.3	201

How these numbers are calculated

Season totals from published play-by-play, scored with DraftKings classic full-PPR values (0.04/passing yard, 4/passing TD, −1/interception, 0.1/rushing and receiving yard, 6/rushing and receiving TD, 1/reception, −1/fumble lost) and divided by games played. Single-game yardage bonuses cannot be recovered from season totals and are excluded, so these figures run slightly below a true DraftKings average.

This is a baseline, not a forecast. It carries no adjustment for opponent, venue, injury or expected game script, and it weights a game in March exactly as heavily as one played yesterday. Use it as the starting point a matchup-aware read departs from, and treat any single figure as the centre of a wide range rather than a prediction.

A number hides the thing that matters

Two players can both project for 14 points and be completely different assets. One is a possession receiver who catches six passes for 60 yards nearly every week. The other is a deep threat who posts 3 points most weeks and 40 when the long ball connects.

In a cash game you want the first. In a large tournament you need the second, because finishing first requires an outcome in the tail — and the steady player has no tail.

Where projections come from

The honest ones are built from workload rather than results: targets, carries, snap share, red-zone usage. Volume is far more stable week to week than efficiency, so a model grounded in opportunity holds up better than one grounded in recent fantasy points.

The remaining inputs are matchup-level: opponent pace, expected game script, and whether the team is likely to be leading (and running) or trailing (and throwing).

Projections do not survive contact with ownership

Knowing a player will score well is only half the problem. If everyone knows, the payoff is split across thousands of identical lineups. The second half of the question — how many other people will arrive at the same answer — is where tournament results are actually decided.