2026 Fantasy WR Rankings

The top 60 WRs for 2026 half-PPR leagues, ranked by our machine-learning model's projected fantasy points. Each projection comes with a calibrated 80% confidence interval — meaning 83% of actual outcomes fell inside our intervals in 2025 walk-forward testing.

Wide receiver projections live or die on target share and teammate competition. We explicitly encode prior-season teammate targets so when a star signs elsewhere, our model sees it. 35% MAE edge over ADP.

Rank	Player	Team	Proj Pts	80% CI	ADP	Risk
WR1	Puka Nacua	LAR	179.6	70–289	12	LOW
WR2	Ja'Marr Chase	CIN	178.0	153–203	1	LOW
WR3	Jaxon Smith-Njigba	SEA	160.4	61–260	30	LOW
WR4	Drake London	ATL	145.4	64–227	18	LOW
WR5	Nico Collins	HOU	145.2	81–210	12	LOW
WR6	Amon-Ra St. Brown	DET	144.0	108–180	9	LOW
WR7	Courtland Sutton	DEN	131.8	72–192	50	LOW
WR8	Justin Jefferson	MIN	120.3	46–194	5	LOW
WR9	Ladd McConkey	LAC	118.1	46–190	26	LOW
WR10	Zay Flowers	BAL	115.2	30–200	61	LOW
WR11	CeeDee Lamb	DAL	115.0	52–178	6	LOW
WR12	Brian Thomas Jr.	JAX	110.3	30–191	14	LOW
WR13	Marvin Harrison Jr.	ARI	109.2	33–186	40	LOW
WR14	Rome Odunze	CHI	108.9	37–181	80	LOW
WR15	Davante Adams	LAR	107.4	49–166	42	LOW
WR16	Chris Olave	NO	106.2	27–186	72	LOW
WR17	Jerry Jeudy	CLE	102.1	34–170	68	LOW
WR18	Garrett Wilson	NYJ	100.8	0–213	38	MED
WR19	George Pickens	DAL	100.0	20–180	62	LOW
WR20	Tetairoa McMillan	CAR	98.4	10–187	56	LOW
WR21	Terry McLaurin	WAS	97.8	65–131	36	LOW
WR22	Xavier Worthy	KC	94.8	24–165	56	LOW
WR23	Malik Nabers	NYG	94.6	17–172	9	LOW
WR24	Jameson Williams	DET	94.5	24–165	59	LOW
WR25	DJ Moore	BUF	93.2	36–150	50	LOW
WR26	Tee Higgins	CIN	92.7	35–150	34	LOW
WR27	Khalil Shakir	BUF	89.8	29–150	92	LOW
WR28	Emeka Egbuka	TB	88.9	0–181	94	MED
WR29	Josh Downs	IND	85.0	16–154	113	LOW
WR30	A.J. Brown	PHI	82.5	24–141	22	LOW
WR31	DeVonta Smith	PHI	80.6	39–122	56	LOW
WR32	Matthew Golden	GB	80.4	0–182	90	MED
WR33	Calvin Ridley	TEN	80.1	1–159	68	MED
WR34	Jaylen Waddle	DEN	79.0	17–141	72	LOW
WR35	Wan'Dale Robinson	TEN	74.2	22–127	182	LOW
WR36	Mike Evans	SF	72.8	4–142	42	MED
WR37	Jordan Addison	MIN	71.7	5–139	84	MED
WR38	Romeo Doubs	NE	71.2	5–138	190	MED
WR39	Jauan Jennings	SF	71.0	25–117	102	LOW
WR40	DK Metcalf	PIT	68.9	12–126	51	LOW
WR41	Alec Pierce	IND	67.2	0–134	—	MED
WR42	Michael Pittman	PIT	65.8	0–134	110	MED
WR43	Stefon Diggs	NE	63.9	13–115	89	LOW
WR44	Darnell Mooney	NYG	63.7	15–112	120	LOW
WR45	Rashee Rice	KC	63.1	19–107	62	LOW
WR46	Jakobi Meyers	JAX	61.0	12–110	90	LOW
WR47	Quentin Johnston	LAC	60.7	0–125	—	MED
WR48	Jalen Tolbert	MIA	60.2	4–116	—	LOW
WR49	Cooper Kupp	SEA	59.3	10–108	90	LOW
WR50	DeMario Douglas	NE	57.6	2–114	193	MED
WR51	Chris Godwin Jr.	TB	57.2	0–115	93	MED
WR52	Rashod Bateman	BAL	57.2	0–114	172	MED
WR53	Rashid Shaheed	SEA	56.4	0–113	138	MED
WR54	Keenan Allen	LAC	55.0	11–99	156	LOW
WR55	Deebo Samuel Sr.	WAS	53.5	4–102	86	LOW
WR56	Carnell Tate	TEN	51.9	0–206	0	MED
WR57	Zavion Thomas	CHI	51.7	0–211	0	MED
WR58	Tre Tucker	LV	51.3	0–113	—	MED
WR59	Keon Coleman	BUF	50.9	0–105	116	MED
WR60	Michael Wilson	ARI	50.6	0–130	—	MED

What the model gets right that ADP misses

ADP is a wisdom-of-the-crowd signal — it reflects what drafters collectively think, not what actually happens. In our 2022-2025 walk-forward validation, consensus ADP explained only 6% of actual fantasy-point variance. Our model explained 57% — roughly 9× more variance explained.

The biggest gaps between model and ADP are surfaced on our Top Sleepers and Top Busts pages. The full War Room shows every player with filtering, VBD, scarcity, and draft-tracking.

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