Players 2015 final

1

Rob Gronkowski

NE· 15 G

1176 Rec yards

2

Greg Olsen

CAR· 16 G

1104 Rec yards

3

Delanie Walker

TEN· 15 G

1088 Rec yards

4

Gary Barnidge

CLE· 16 G

1043 Rec yards

5

Jordan Matthews

PHI· 16 G

997 Rec yards

Tight ends — 2015 · 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	Rob Gronkowski	NE	15	88	78.4	4.8	8.0	1176	72	11	16.3	60.0%	21.0%	0.52
2	Greg Olsen	CAR	16	72	69.0	4.8	7.8	1104	77	7	14.3	62.1%	24.8%	0.55
3	Delanie Walker	TEN	15	78	72.5	6.3	8.9	1088	94	6	11.6	70.7%	26.4%	0.59
4	Gary Barnidge	CLE	16	76	65.2	4.9	7.8	1043	79	9	13.2	63.2%	20.2%	0.47
5	Jordan Matthews	PHI	16	73	62.3	5.3	8.0	997	85	8	11.7	66.4%	21.4%	0.50
6	Jordan Reed	WAS	14	82	68.0	6.2	8.1	952	87	11	10.9	76.3%	24.0%	0.49
7	Travis Kelce	KC	16	69	54.7	4.5	6.4	875	72	5	12.2	69.9%	22.4%	0.48
8	Zach Ertz	PHI	15	68	56.9	5.0	7.5	853	75	2	11.4	67.0%	18.2%	0.44
9	Benjamin Watson	NO	16	68	51.6	4.6	6.9	825	74	6	11.1	67.3%	16.4%	0.38
10	Jason Witten	DAL	16	63	44.6	4.8	6.5	713	77	3	9.3	74.0%	20.5%	0.44
11	Jacob Tamme	ATL	15	61	43.8	3.9	5.4	657	59	1	11.1	72.8%	13.5%	0.30
12	Antonio Gates	LAC	11	70	57.3	5.1	7.7	630	56	5	11.2	65.9%	18.3%	0.41
13	Tyler Eifert	CIN	13	74	47.3	4.0	5.7	615	52	13	11.8	70.3%	17.7%	0.38
14	Jimmy Graham	SEA	11	67	55.0	4.4	6.7	605	48	2	12.6	64.9%	23.9%	0.53
15	Eric Ebron	DET	14	63	38.4	3.4	5.0	537	47	5	11.4	67.1%	13.7%	0.30
16	Heath Miller	PIT	15	60	35.7	4.0	5.4	535	60	2	8.9	74.1%	14.2%	0.27
17	Charles Clay	BUF	13	61	40.6	3.9	5.9	528	51	3	10.4	66.2%	19.5%	0.39
18	Owen Daniels	DEN	16	57	32.3	2.9	4.8	517	46	3	11.2	59.7%	13.0%	0.26
19	Richard Rodgers	GB	16	65	31.9	3.6	5.3	510	58	8	8.8	68.2%	15.3%	0.31
20	Kyle Rudolph	MIN	16	59	30.9	3.1	4.6	495	49	5	10.1	67.1%	16.8%	0.40
21	Coby Fleener	IND	15	59	32.7	3.6	5.6	491	54	3	9.1	64.3%	14.9%	0.33
22	Jared Cook	LAR	16	52	30.1	2.4	4.7	481	39	0	12.3	52.0%	16.8%	0.38
23	Will Tye	NYG	13	58	35.7	3.2	4.8	464	42	3	11.0	67.7%	11.9%	0.24
24	Julius Thomas	JAX	12	65	37.9	3.8	6.7	455	46	5	9.9	57.5%	17.6%	0.37
25	Zach Miller	CHI	13	60	33.8	2.6	3.5	439	34	5	12.9	73.9%	11.8%	0.26
26	Martellus Bennett	CHI	11	66	39.9	4.8	7.3	439	53	3	8.3	66.2%	21.2%	0.43
27	Ladarius Green	LAC	13	58	33.0	2.8	4.8	429	37	4	11.6	58.7%	12.0%	0.27
28	Crockett Gillmore	BAL	10	62	41.2	3.3	4.7	412	33	4	12.5	70.2%	11.4%	0.26
29	Brent Celek	PHI	12	56	33.2	2.2	2.9	398	27	3	14.7	77.1%	7.6%	0.18
30	Vernon Davis	SF	13	55	30.4	2.9	4.5	395	38	0	10.4	65.5%	13.2%	0.32
31	Jordan Cameron	MIA	16	53	24.1	2.2	4.4	386	35	3	11.0	50.0%	12.6%	0.29
32	Austin Seferian-Jenkins	TB	7	64	48.3	3.0	5.6	338	21	4	16.1	53.8%	16.9%	0.40
33	Clive Walford	LV	15	52	21.9	1.9	3.3	329	28	3	11.8	56.0%	9.0%	0.21
34	Vance McDonald	SF	14	55	23.3	2.1	3.3	326	30	3	10.9	65.2%	9.7%	0.22
35	Darren Fells	ARI	12	53	25.9	1.8	2.3	311	21	3	14.8	75.0%	7.0%	0.14
36	Anthony Fasano	TEN	14	50	20.6	1.9	3.0	289	26	2	11.1	61.9%	8.6%	0.17
37	Cameron Brate	TB	12	54	24.0	1.9	2.5	288	23	3	12.5	76.7%	7.2%	0.16
38	Mychal Rivera	LV	15	50	18.7	2.1	3.1	280	32	1	8.8	69.6%	8.1%	0.17
39	Maxx Williams	BAL	14	49	19.1	2.3	3.4	268	32	1	8.4	66.7%	7.7%	0.17
40	Scott Chandler	NE	12	54	21.6	1.9	3.5	259	23	4	11.3	54.8%	8.0%	0.18
41	Ryan Griffin	HOU	9	56	27.9	2.2	3.8	251	20	2	12.6	58.8%	11.8%	0.25
42	Lance Kendricks	LAR	14	50	17.5	1.8	2.9	245	25	2	9.8	62.5%	10.0%	0.20
43	Marcedes Lewis	JAX	15	35	15.1	1.1	2.5	226	16	0	14.1	43.2%	6.6%	0.13
44	Jermaine Gresham	ARI	14	44	15.9	1.3	2.3	223	18	1	12.4	56.2%	6.8%	0.14
45	Larry Donnell	NYG	8	57	27.9	3.6	5.1	223	29	2	7.7	70.7%	14.5%	0.30
46	Luke Willson	SEA	13	45	16.4	1.3	2.0	213	17	1	12.5	65.4%	7.1%	0.15
47	Garrett Celek	SF	10	53	18.6	1.9	2.8	186	19	3	9.8	67.9%	10.1%	0.20
48	Blake Bell	SF	9	47	20.7	1.7	2.8	186	15	0	12.4	60.0%	7.4%	0.17
49	Virgil Green	DEN	13	39	13.3	0.9	1.2	173	12	1	14.4	80.0%	3.3%	0.06
50	C.J. Fiedorowicz	HOU	14	38	11.9	1.2	1.7	167	17	1	9.8	70.8%	4.7%	0.08
51	Nick Boyle	BAL	9	47	17.0	2.0	2.6	153	18	0	8.5	78.3%	6.6%	0.13
52	Chris Gragg	BUF	7	48	21.4	1.7	2.9	150	12	0	12.5	60.0%	8.6%	0.18
53	Clay Harbor	JAX	10	46	14.9	1.4	2.0	149	14	1	10.6	70.0%	5.4%	0.10
54	Derek Carrier	WAS	12	44	11.8	1.4	1.8	141	17	1	8.3	77.3%	5.2%	0.11
55	Cooper Helfet	SEA	7	48	18.6	1.9	3.1	130	13	0	10.0	59.1%	9.8%	0.19
56	Tyler Kroft	CIN	12	37	10.8	0.9	1.2	129	11	1	11.7	73.3%	4.2%	0.08
57	Brandon Myers	TB	6	51	21.2	2.0	2.8	127	12	0	10.6	70.6%	9.1%	0.20
58	Dion Sims	MIA	13	39	9.8	1.4	1.9	127	18	1	7.1	72.0%	6.0%	0.12
59	Rhett Ellison	MIN	12	36	10.3	0.9	1.6	124	11	1	11.3	57.9%	5.9%	0.11
60	Craig Stevens	TEN	10	46	12.1	1.2	1.6	121	12	2	10.1	75.0%	4.5%	0.09

What this is. Finished box-score production from 2015, 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.