Players 2022 final

1

Travis Kelce

KC· 17 G

1338 Rec yards

2

T.J. Hockenson

MIN· 17 G

914 Rec yards

3

Mark Andrews

BAL· 15 G

847 Rec yards

4

Evan Engram

JAX· 17 G

766 Rec yards

5

George Kittle

SF· 15 G

765 Rec yards

Tight ends — 2022 · ranked by Rec yards

#	Player	Tm	G	Grade	Yds/gm	Rec/gm	Tgt/gm	Rec yds	Rec	TD	Y/R	Catch%	Tgt share	WOPR
1	Travis Kelce	KC	17	88	78.7	6.5	8.9	1338	110	12	12.2	72.4%	25.0%	0.54
2	T.J. Hockenson	MIN	17	79	53.8	5.1	7.6	914	86	6	10.6	66.7%	20.1%	0.43
3	Mark Andrews	BAL	15	77	56.5	4.9	7.5	847	73	5	11.6	64.6%	28.7%	0.65
4	Evan Engram	JAX	17	71	45.1	4.3	5.8	766	73	4	10.5	74.5%	16.8%	0.35
5	George Kittle	SF	15	82	51.0	4.0	5.7	765	60	11	12.8	69.8%	19.7%	0.42
6	Pat Freiermuth	PIT	15	70	48.8	4.2	6.5	732	63	2	11.6	64.3%	20.2%	0.44
7	Dallas Goedert	PHI	12	75	58.5	4.6	5.8	702	55	3	12.8	79.7%	20.2%	0.42
8	David Njoku	CLE	14	74	44.9	4.1	5.7	628	58	4	10.8	72.5%	18.9%	0.38
9	Tyler Higbee	LAR	16	69	38.8	4.5	6.8	620	72	3	8.6	66.7%	21.6%	0.39
10	Dalton Schultz	DAL	15	68	38.5	3.8	5.9	577	57	5	10.1	64.0%	17.9%	0.38
11	Gerald Everett	LAC	15	66	37.0	3.9	5.8	555	58	4	9.6	66.7%	13.6%	0.29
12	Tyler Conklin	NYJ	17	64	32.5	3.4	5.1	552	58	3	9.5	66.7%	14.5%	0.31
13	Cole Kmet	CHI	17	65	32.0	2.9	4.1	544	50	7	10.9	72.5%	18.8%	0.38
14	Dawson Knox	BUF	15	67	34.5	3.2	4.3	517	48	6	10.8	73.8%	13.4%	0.28
15	Hunter Henry	NE	16	59	31.8	2.6	3.7	509	41	2	12.4	69.5%	12.4%	0.28
16	Juwan Johnson	NO	16	65	31.8	2.6	4.1	508	42	7	12.1	64.6%	14.7%	0.33
17	Jordan Akins	HOU	15	62	33.0	2.5	3.6	495	37	5	13.4	68.5%	11.0%	0.22
18	Noah Fant	SEA	17	61	28.6	2.9	3.7	486	50	4	9.7	79.4%	11.7%	0.25
19	Robert Tonyan	GB	17	60	27.6	3.1	3.9	470	53	2	8.9	79.1%	12.0%	0.24
20	Chig Okonkwo	TEN	16	58	28.1	2.0	2.9	450	32	3	14.1	69.6%	12.1%	0.27
21	Austin Hooper	TEN	17	57	26.1	2.4	3.5	444	41	2	10.8	68.3%	13.9%	0.31
22	Foster Moreau	LV	14	59	30.0	2.4	3.9	420	33	2	12.7	61.1%	11.4%	0.24
23	Hayden Hurst	CIN	13	63	31.8	4.0	5.2	414	52	2	8.0	76.5%	14.2%	0.29
24	Greg Dulcich	DEN	10	64	41.1	3.3	5.5	411	33	2	12.5	60.0%	17.7%	0.41
25	Zach Ertz	ARI	10	72	40.6	4.7	6.9	406	47	4	8.6	68.1%	17.9%	0.41
26	Cade Otton	TB	16	56	24.4	2.6	4.1	391	42	2	9.3	64.6%	8.9%	0.19
27	Darren Waller	LV	8	68	48.5	3.5	5.4	388	28	3	13.9	65.1%	15.7%	0.40
28	Isaiah Likely	BAL	14	60	26.6	2.6	4.3	373	36	3	10.4	60.0%	14.8%	0.31
29	Mike Gesicki	MIA	17	55	21.3	1.9	3.1	362	32	5	11.3	61.5%	9.1%	0.20
30	Kyle Pitts	ATL	10	62	35.6	2.8	5.9	356	28	2	12.7	47.5%	27.9%	0.64
31	Will Dissly	SEA	15	56	23.3	2.3	2.5	349	34	3	10.3	89.5%	8.1%	0.16
32	Logan Thomas	WAS	13	58	24.8	3.0	4.7	323	39	1	8.3	63.9%	15.5%	0.31
33	Colby Parkinson	SEA	14	53	23.0	1.8	2.4	322	25	2	12.9	73.5%	7.7%	0.17
34	Jelani Woods	IND	12	57	26.0	2.1	3.3	312	25	3	12.5	62.5%	10.2%	0.26
35	Kylen Granson	IND	13	51	23.2	2.4	3.1	302	31	0	9.7	77.5%	8.8%	0.19
36	Noah Gray	KC	17	46	17.6	1.6	2.0	299	28	1	10.7	82.4%	5.5%	0.11
37	Daniel Bellinger	NYG	11	58	24.4	2.7	3.2	268	30	2	8.9	85.7%	12.0%	0.23
38	Trey McBride	ARI	12	54	22.1	2.4	3.2	265	29	1	9.1	74.4%	9.1%	0.18
39	Jonnu Smith	NE	12	51	20.4	2.2	3.2	245	27	0	9.1	71.1%	10.4%	0.18
40	Harrison Bryant	CLE	14	49	17.1	2.2	3.0	239	31	1	7.7	73.8%	10.0%	0.20
41	C.J. Uzomah	NYJ	14	47	16.6	1.5	1.9	232	21	2	11.0	77.8%	6.4%	0.13
42	Brock Wright	DET	14	53	15.4	1.3	1.7	216	18	4	12.0	75.0%	5.7%	0.10
43	Adam Trautman	NO	12	47	17.2	1.5	1.8	207	18	1	11.5	81.8%	6.8%	0.13
44	Ian Thomas	CAR	13	42	15.2	1.6	2.3	197	21	0	9.4	70.0%	9.1%	0.14
45	Mo Alie-Cox	IND	14	47	13.5	1.4	2.0	189	19	3	9.9	67.9%	6.2%	0.13
46	Irv Smith	MIN	8	61	22.8	3.1	4.5	182	25	2	7.3	69.4%	12.7%	0.24
47	Tommy Tremble	CAR	15	46	11.6	1.3	2.1	174	19	3	9.2	59.4%	8.6%	0.18
48	Cameron Brate	TB	9	50	19.3	2.2	4.2	174	20	0	8.7	52.6%	10.5%	0.22
49	Jake Ferguson	DAL	11	52	15.8	1.7	2.0	174	19	2	9.2	86.4%	6.3%	0.11
50	MyCole Pruitt	ATL	10	55	15.0	1.6	2.1	150	16	4	9.4	76.2%	8.6%	0.17
51	Josh Oliver	BAL	12	44	12.4	1.2	2.1	149	14	2	10.6	56.0%	8.3%	0.18
52	Eric Saubert	DEN	14	36	10.6	1.1	1.7	148	15	1	9.9	62.5%	5.1%	0.12
53	O.J. Howard	HOU	11	45	13.2	0.9	2.1	145	10	2	14.5	43.5%	6.5%	0.17
54	Johnny Mundt	MIN	13	41	10.8	1.5	1.6	140	19	1	7.4	90.5%	4.5%	0.07
55	Mitchell Wilcox	CIN	9	49	15.4	1.9	2.0	139	17	1	8.2	94.4%	5.1%	0.10
56	Dan Arnold	JAX	11	35	12.3	0.8	1.2	135	9	0	15.0	69.2%	3.5%	0.08
57	Zach Gentry	PIT	14	36	9.4	1.4	1.6	132	19	0	6.9	82.6%	4.7%	0.08
58	Tanner Hudson	NYG	6	49	22.0	1.7	2.5	132	10	0	13.2	66.7%	10.6%	0.23
59	Donald Parham	LAC	6	53	21.7	1.7	2.0	130	10	1	13.0	83.3%	5.1%	0.13
60	Durham Smythe	MIA	13	38	9.9	1.2	1.5	129	15	1	8.6	75.0%	5.4%	0.10

What this is. Finished box-score production from 2022, ranked by Rec yards. Per-game columns divide by games played, not games on the schedule, so a player who missed time is measured on the games he was in — and his season totals still show the games he missed. Minimum 4 games to be ranked, otherwise one big afternoon tops every list.

What it isn’t. None of this is a projection, a pick, or a prop recommendation — it is what already happened. Last season’s rate is a starting point for what a player does in a game, not a forecast of the next one: offense, role, and health all move underneath it. Target share and WOPR describe a player’s share of his own team’s passing game, so they compare roles, not players across teams.

About the grade. 0–100, where 50 is average for the position and 85+ is elite. It is box production, scaled by the defense it came against, pulled toward the positional average when a player has few games, then ranked within position — so a 90 quarterback and a 90 kicker are each elite for their own spot and are not comparable to each other in any other way. It needs 6 games, so players below that show — rather than a number built on a hot month.

What the grade can’t see. There is no charting behind it, so it rewards production over technique: the receiver who ran the route that freed someone else, and the back who picked up the blitz, get nothing for it. It is role-dependent by construction — a back on a run-heavy team gets more chances than an equally good back who touches it half as often. Kickers are not opponent-adjusted, because field goals are contested by distance and weather, not by the defense across the ball. And it grades a season already played; it is not a projection of the next one.

Regular season and postseason are kept separate on purpose. Playoff samples are small and the opponents are better; blending them into a season rate quietly flatters the players who got there. The grade is regular-season only, so it is not offered on the postseason split.