Players 2024 final

1

Brock Bowers

LV· 17 G

1194 Rec yards

2

Trey McBride

ARI· 16 G

1146 Rec yards

3

George Kittle

SF· 15 G

1106 Rec yards

4

Jonnu Smith

MIA· 17 G

884 Rec yards

5

Travis Kelce

KC· 16 G

823 Rec yards

Tight ends — 2024 · 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	Brock Bowers	LV	17	82	70.2	6.6	9.0	1194	112	5	10.7	73.2%	25.5%	0.53
2	Trey McBride	ARI	16	79	71.6	6.9	9.2	1146	111	2	10.3	75.5%	28.6%	0.61
3	George Kittle	SF	15	88	73.7	5.2	6.3	1106	78	8	14.2	83.0%	20.7%	0.45
4	Jonnu Smith	MIA	17	76	52.0	5.2	6.5	884	88	8	10.0	79.3%	19.3%	0.39
5	Travis Kelce	KC	16	75	51.4	6.1	8.3	823	97	3	8.5	72.9%	23.3%	0.52
6	Sam LaPorta	DET	16	71	45.4	3.8	5.2	726	60	7	12.1	72.3%	17.5%	0.39
7	Tucker Kraft	GB	17	67	41.6	2.9	4.1	707	50	7	14.1	71.4%	15.1%	0.29
8	Hunter Henry	NE	16	65	42.1	4.1	6.1	674	66	2	10.2	68.0%	20.4%	0.44
9	Mark Andrews	BAL	17	72	39.6	3.2	4.1	673	55	11	12.2	79.7%	15.0%	0.35
10	Mike Gesicki	CIN	16	64	41.6	4.1	5.2	665	65	2	10.2	78.3%	13.2%	0.30
11	Zach Ertz	WAS	17	70	38.5	3.9	5.4	654	66	7	9.9	72.5%	17.9%	0.39
12	Pat Freiermuth	PIT	17	69	38.4	3.8	4.6	653	65	7	10.0	83.3%	16.9%	0.35
13	Kyle Pitts	ATL	17	61	35.4	2.8	4.4	602	47	4	12.8	63.5%	13.9%	0.32
14	Cade Otton	TB	14	68	42.9	4.2	6.2	600	59	4	10.2	67.8%	18.4%	0.38
15	Juwan Johnson	NO	15	63	36.5	3.3	4.4	548	50	3	11.0	75.8%	13.6%	0.30
16	Dalton Schultz	HOU	17	57	31.3	3.1	5.0	532	53	2	10.0	62.4%	15.5%	0.34
17	David Njoku	CLE	11	73	45.9	5.8	8.8	505	64	5	7.9	66.0%	22.7%	0.44
18	Noah Fant	SEA	14	60	35.7	3.4	4.6	500	48	1	10.4	75.0%	14.5%	0.29
19	Dallas Goedert	PHI	10	66	49.6	4.2	5.2	496	42	2	11.8	80.8%	19.3%	0.40
20	Jake Ferguson	DAL	14	62	35.3	4.2	6.1	494	59	0	8.4	68.6%	17.4%	0.32
21	Will Dissly	LAC	15	59	32.1	3.3	4.3	481	50	2	9.6	78.1%	15.1%	0.28
22	Chig Okonkwo	TEN	16	58	29.9	3.2	4.4	479	52	2	9.2	74.3%	14.1%	0.29
23	Isaiah Likely	BAL	15	64	31.8	2.8	3.9	477	42	6	11.4	72.4%	13.3%	0.29
24	Austin Hooper	NE	17	56	28.0	2.6	3.5	476	45	3	10.6	76.3%	12.2%	0.25
25	Cole Kmet	CHI	16	58	29.6	2.9	3.4	474	47	4	10.1	85.5%	10.3%	0.22
26	T.J. Hockenson	MIN	10	62	45.5	4.1	6.2	455	41	0	11.1	66.1%	18.1%	0.40
27	Tyler Conklin	NYJ	16	60	28.1	3.2	4.5	449	51	4	8.8	70.8%	12.5%	0.25
28	Dalton Kincaid	BUF	13	61	34.5	3.4	5.8	448	44	2	10.2	58.7%	20.2%	0.42
29	Noah Gray	KC	16	59	27.3	2.5	3.1	437	40	5	10.9	81.6%	9.2%	0.19
30	Foster Moreau	NO	16	55	25.8	2.0	2.7	413	32	5	12.9	74.4%	9.0%	0.20
31	Brenton Strange	JAX	14	57	29.4	2.9	3.8	411	40	2	10.3	75.5%	11.4%	0.23
32	Jordan Akins	CLE	16	54	24.4	2.5	3.6	390	40	2	9.8	69.0%	9.9%	0.20
33	Evan Engram	JAX	9	66	40.6	5.2	7.1	365	47	1	7.8	73.4%	25.5%	0.49
34	Ja'Tavion Sanders	CAR	15	52	22.8	2.2	2.9	342	33	1	10.4	76.7%	10.3%	0.22
35	Theo Johnson	NYG	11	55	30.1	2.6	3.9	331	29	1	11.4	67.4%	12.3%	0.27
36	Dawson Knox	BUF	14	51	22.2	1.6	2.4	311	22	1	14.1	66.7%	7.9%	0.19
37	Grant Calcaterra	PHI	15	49	19.9	1.6	2.0	298	24	1	12.4	80.0%	8.6%	0.18
38	Colby Parkinson	LAR	16	50	18.4	1.9	3.1	294	30	1	9.8	61.2%	9.7%	0.19
39	Josh Oliver	MIN	12	54	21.5	1.8	2.3	258	22	3	11.7	78.6%	7.7%	0.16
40	Josh Whyle	TEN	15	49	16.5	1.9	2.5	248	28	1	8.9	75.7%	8.0%	0.16
41	AJ Barner	SEA	15	53	16.3	2.0	2.5	245	30	4	8.2	78.9%	8.0%	0.15
42	Luke Schoonmaker	DAL	12	53	20.1	2.2	3.0	241	27	1	8.9	75.0%	7.5%	0.15
43	Tommy Tremble	CAR	10	54	23.4	2.3	3.2	234	23	2	10.2	71.9%	9.8%	0.20
44	Stone Smartt	LAC	9	50	23.1	1.8	2.1	208	16	0	13.0	84.2%	6.8%	0.15
45	Darnell Washington	PIT	13	47	15.4	1.5	1.9	200	19	1	10.5	76.0%	7.1%	0.13
46	Adam Trautman	DEN	13	45	14.5	1.0	1.7	188	13	2	14.5	59.1%	5.3%	0.10
47	Taysom Hill	NO	8	56	23.4	2.9	3.9	187	23	0	8.1	74.2%	13.7%	0.25
48	Kylen Granson	IND	16	32	11.4	0.9	1.9	182	14	0	13.0	45.2%	6.6%	0.14
49	Elijah Higgins	ARI	15	45	11.5	1.3	1.6	172	20	2	8.6	83.3%	5.6%	0.11
50	Erick All	CIN	8	52	19.8	2.5	2.8	158	20	0	7.9	90.9%	8.6%	0.16
51	Michael Mayer	LV	11	46	14.2	1.9	2.9	156	21	0	7.4	65.6%	8.1%	0.17
52	Tanner Hudson	CIN	9	51	17.1	2.1	2.6	154	19	1	8.1	82.6%	6.5%	0.13
53	Lucas Krull	DEN	10	48	15.2	1.9	2.3	152	19	0	8.0	82.6%	7.5%	0.15
54	Mo Alie-Cox	IND	12	43	12.2	1.0	1.8	147	12	1	12.2	54.5%	7.0%	0.15
55	Johnny Mundt	MIN	14	46	10.1	1.4	1.9	142	19	2	7.5	70.4%	7.2%	0.13
56	Nick Vannett	TEN	12	49	11.2	1.4	1.7	135	17	3	7.9	85.0%	5.3%	0.08
57	Cade Stover	HOU	14	40	9.5	1.1	1.6	133	15	1	8.9	68.2%	5.0%	0.10
58	Charlie Kolar	BAL	10	44	13.1	0.9	1.1	131	9	1	14.6	81.8%	3.8%	0.07
59	Daniel Bellinger	NYG	12	36	10.4	1.2	1.4	125	14	0	8.9	82.4%	3.8%	0.07
60	Nate Adkins	DEN	15	41	7.7	0.9	1.0	115	14	3	8.2	93.3%	3.2%	0.06

What this is. Finished box-score production from 2024, 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.