NFL · Empirical Bayes

True-Talent Leaderboards

A raw single-season rate is a noisy guess at a player’s real ability, and the noise is worst for the smallest samples — so a naïve leaderboard is topped by whoever got lucky in the fewest tries. This one shrinks every rate toward its position-group prior by how much the sample can be trusted, and shows a 90% credible interval instead of a point. Toggle raw vs. shrunk to watch the flukes fall back to the pack.

Catch rate · 2024

Receptions per target, shrunk within position (WR vs TE separately). Depth-of-target confound; catchable-target rate not available here.

Beats raw by
18.3%
lower out-of-sample error
RMSE raw → shrunk
11.1% → 9.1%
odd vs. even weeks
Split-half reliability
0.35
how repeatable the raw stat is
Stabilizes at
61
targets to trust the number
shrunkrawthe shrink90% CI
50%60%70%80%WR avg1Amon-Ra St. BrownDET · 14176.0%2Chris Godwin Jr.TB · 6271.9%3Khalil ShakirBUF · 10071.1%4DeMario DouglasNE · 8770.6%5DeVonta SmithPHI · 9070.5%6Adam ThielenCAR · 6270.3%7Ja'Marr ChaseCIN · 17570.1%8Puka NacuaLA · 10769.9%9Jaxon Smith-NjigbaSEA · 13869.6%10Rashee RiceKC · 2969.4%11Ladd McConkeyLAC · 11369.2%12Devaughn VeleDEN · 5568.5%13Stefon DiggsHOU · 6468.4%14Jayden ReedGB · 7668.2%15Greg DortchARI · 5068.0%16Marvin Mims Jr.DEN · 5368.0%17Jordan WhittingtonLA · 2868.0%18Ray-Ray McCloudATL · 8767.9%19Dyami BrownWAS · 4067.8%20Tylan WallaceBAL · 1267.8%21Tim PatrickDET · 4567.4%22Mecole HardmanKC · 1467.3%23Terry McLaurinWAS · 11867.3%24DJ MooreCHI · 14267.2%25Kendrick BourneNE · 3867.2%26Chris OlaveNO · 4467.1%27DeAndre HopkinsKC · 8067.0%28Kalif RaymondDET · 2266.8%29Olamide ZaccheausWAS · 6466.8%30A.J. BrownPHI · 9766.8%31Malik WashingtonMIA · 3666.5%32Cedrick Wilson Jr.NO · 2766.5%33Derius DavisLAC · 1766.0%34Luke McCaffreyWAS · 2565.7%35Malik HeathGB · 1365.5%36Jake BoboSEA · 1865.2%

Each row is a player: the solid dot is the shrunk estimate, the hollow dot the raw rate, joined by the red pull of regression; the grey bar is the 90% credible interval. A hollow shrunk dot means the sample is below the stabilization line — the number is mostly the position prior. Switch to Raw rank and watch the small-sample names climb.

Catch rate · 2024 · full board

Catch rate leaderboard for the 2024 NFL season, shrunk by empirical Bayes with 90% credible intervals, ranked by the shrunk estimate.
#PlayerTeamPostargetsRawShrunk90% interval
1Amon-Ra St. BrownDETWR14181.6%76.0%70.9%80.8%
2Chris Godwin Jr.TBWR6280.7%71.9%65.1%78.4%
3Khalil ShakirBUFWR10076.0%71.1%65.1%76.8%
4DeMario DouglasNEWR8775.9%70.6%64.3%76.6%
5DeVonta SmithPHIWR9075.6%70.5%64.3%76.4%
6Adam ThielenCARWR6277.4%70.3%63.4%76.9%
7Ja'Marr ChaseCINWR17572.6%70.1%65.1%74.9%
8Puka NacuaLAWR10773.8%69.9%64.0%75.6%
9Jaxon Smith-NjigbaSEAWR13872.5%69.6%64.1%74.8%
10Rashee Rice◦ provisionalKCWR2982.8%69.4%61.2%77.1%
11Ladd McConkeyLACWR11372.6%69.2%63.4%74.9%
12Devaughn Vele◦ provisionalDENWR5574.6%68.5%61.3%75.4%
13Stefon DiggsHOUWR6473.4%68.4%61.4%75.0%
14Jayden ReedGBWR7672.4%68.2%61.6%74.6%
15Greg Dortch◦ provisionalARIWR5074.0%68.0%60.6%75.1%
16Marvin Mims Jr.◦ provisionalDENWR5373.6%68.0%60.6%74.9%
17Jordan Whittington◦ provisionalLAWR2878.6%68.0%59.6%75.8%
18Ray-Ray McCloudATLWR8771.3%67.9%61.5%74.1%
19Dyami Brown◦ provisionalWASWR4075.0%67.8%60.0%75.2%
20Tylan Wallace◦ provisionalBALWR1291.7%67.8%58.6%76.4%
21Tim Patrick◦ provisionalDETWR4573.3%67.4%59.8%74.7%
22Mecole Hardman◦ provisionalKCWR1485.7%67.3%58.2%75.9%
23Terry McLaurinWASWR11869.5%67.3%61.5%73.0%
24DJ MooreCHIWR14269.0%67.2%61.7%72.5%
25Kendrick Bourne◦ provisionalNEWR3873.7%67.2%59.2%74.7%
26Chris Olave◦ provisionalNOWR4472.7%67.1%59.4%74.4%
27DeAndre HopkinsKCWR8070.0%67.0%60.4%73.4%
28Kalif Raymond◦ provisionalDETWR2277.3%66.8%58.2%75.1%
29Olamide ZaccheausWASWR6470.3%66.8%59.7%73.5%
30A.J. BrownPHIWR9769.1%66.8%60.5%72.8%
31Nico CollinsHOUWR9968.7%66.5%60.3%72.5%
32Malik Washington◦ provisionalMIAWR3672.2%66.5%58.5%74.1%
33Cedrick Wilson Jr.◦ provisionalNOWR2774.1%66.5%58.0%74.5%
34Jauan JenningsSFWR11368.1%66.4%60.4%72.1%
35Jaylen WaddleMIAWR8568.2%66.1%59.5%72.4%
36Derius Davis◦ provisionalLACWR1776.5%66.0%57.0%74.5%
37Jalen Coker◦ provisionalCARWR4669.6%65.9%58.2%73.2%
38Justin JeffersonMINWR15466.9%65.8%60.4%71.0%
39Mike EvansTBWR11067.3%65.8%59.7%71.6%
40Josh DownsINDWR10767.3%65.8%59.7%71.7%
41Jakobi MeyersLVWR13066.9%65.7%60.0%71.2%
42Luke McCaffrey◦ provisionalWASWR2572.0%65.7%57.1%73.8%
43Lil'Jordan Humphrey◦ provisionalDENWR4568.9%65.5%57.8%72.9%
44Cooper KuppLAWR10067.0%65.5%59.3%71.5%
45Malik Heath◦ provisionalGBWR1376.9%65.5%56.3%74.3%
46Tutu AtwellLAWR6267.7%65.4%58.3%72.3%
47Wan'Dale RobinsonNYGWR14066.4%65.4%59.8%70.8%
48Tee HigginsCINWR11066.4%65.2%59.1%71.1%
49Jake Bobo◦ provisionalSEAWR1872.2%65.2%56.2%73.7%
50Tyler Boyd◦ provisionalTENWR5867.2%65.1%57.8%72.1%
51Justin Watson◦ provisionalKCWR3268.8%65.0%56.8%72.9%
52Tyreek HillMIAWR12365.8%64.9%59.1%70.6%
53Curtis Samuel◦ provisionalBUFWR4667.4%64.9%57.2%72.3%
54JuJu Smith-Schuster◦ provisionalKCWR2669.2%64.9%56.4%73.1%
55CeeDee LambDALWR15465.6%64.9%59.5%70.1%
56Garrett WilsonNYJWR15465.6%64.9%59.5%70.1%
57Tyler LockettSEAWR7466.2%64.8%58.0%71.4%
58Michael WilsonARIWR7166.2%64.8%57.8%71.5%
59Ryan Flournoy◦ provisionalDALWR1471.4%64.6%55.4%73.4%
60Jalen Nailor◦ provisionalMINWR4266.7%64.5%56.7%72.1%
61Ricky Pearsall◦ provisionalSFWR4766.0%64.3%56.6%71.7%
62Robert Woods◦ provisionalHOUWR3066.7%64.3%55.9%72.3%
63Devin Duvernay◦ provisionalJAXWR1668.8%64.3%55.1%73.0%
64Jamison Crowder◦ provisionalWASWR1369.2%64.2%54.9%73.1%
65Brian Thomas Jr.JAXWR13564.4%64.0%58.3%69.6%
66John Metchie III◦ provisionalHOUWR3764.9%63.8%55.7%71.5%
67Jameson WilliamsDETWR9163.7%63.5%57.0%69.8%
68Jalen McMillan◦ provisionalTBWR5863.8%63.4%56.1%70.5%
69DeAndre Carter◦ provisionalCHIWR1464.3%63.3%54.0%72.2%
70Malik NabersNYGWR17263.4%63.3%58.1%68.4%
71Tyler Johnson◦ provisionalLAWR4163.4%63.2%55.3%70.9%
72Zay FlowersBALWR11763.2%63.2%57.2%69.0%
73Romeo DoubsGBWR7363.0%63.0%56.1%69.8%
74Jordan AddisonMINWR10063.0%63.0%56.7%69.2%
75Deebo Samuel Sr.SFWR8163.0%63.0%56.3%69.6%
76Tank DellHOUWR8163.0%63.0%56.3%69.6%
77Drake LondonATLWR15962.9%62.9%57.5%68.2%
78Noah Brown◦ provisionalWASWR5662.5%62.8%55.4%70.0%
79Rashod BatemanBALWR7262.5%62.8%55.8%69.5%
80Kayshon BoutteNEWR6962.3%62.7%55.6%69.5%
81Mack Hollins◦ provisionalBUFWR5062.0%62.6%54.9%70.0%
82Calvin Austin III◦ provisionalPITWR5862.1%62.6%55.2%69.7%
83Marquise Brown◦ provisionalKCWR1560.0%62.5%53.2%71.4%
84Jalen TolbertDALWR7962.0%62.5%55.7%69.1%
85Bub Means◦ provisionalNOWR1560.0%62.5%53.2%71.4%
86Sterling Shepard◦ provisionalTBWR5261.5%62.4%54.8%69.7%
87Ryan Miller◦ provisionalTBWR2060.0%62.3%53.4%71.0%
88KhaDarel Hodge◦ provisionalATLWR1258.3%62.3%52.9%71.4%
89Jalen Reagor◦ provisionalLACWR1258.3%62.3%52.9%71.4%
90Michael PittmanINDWR11261.6%62.1%56.0%68.1%
91Mike Williams◦ provisionalPITWR3560.0%62.0%53.7%69.9%
92Allen Lazard◦ provisionalNYJWR6160.7%61.9%54.6%69.0%
93Van Jefferson◦ provisionalPITWR4060.0%61.9%53.8%69.7%
94Parker Washington◦ provisionalJAXWR5360.4%61.8%54.3%69.2%
95Quentin JohnstonLACWR9160.4%61.5%54.9%67.9%
96KaVontae Turpin◦ provisionalDALWR5259.6%61.5%53.9%68.9%
97Jerry JeudyCLEWR14860.8%61.5%55.9%66.9%
98DK MetcalfSEAWR10960.6%61.5%55.3%67.5%
99Darnell MooneyATLWR10660.4%61.4%55.1%67.5%
100Jahan Dotson◦ provisionalPHIWR3357.6%61.2%52.8%69.3%
101Andrei Iosivas◦ provisionalCINWR6159.0%61.1%53.7%68.2%
102Elijah MooreCLEWR10259.8%61.0%54.7%67.2%
103Courtland SuttonDENWR13560.0%61.0%55.2%66.6%
104Chris Conley◦ provisionalSFWR1250.0%61.0%51.4%70.1%
105Xavier WorthyKCWR9959.6%60.9%54.5%67.2%
106Davante AdamsNYJWR14259.9%60.8%55.1%66.4%
107Trey Palmer◦ provisionalTBWR2254.5%60.8%51.9%69.4%
108Christian Kirk◦ provisionalJAXWR4757.5%60.6%52.8%68.2%
109Josh Reynolds◦ provisionalJAXWR2454.2%60.6%51.8%69.1%
110DJ Turner◦ provisionalLVWR2955.2%60.6%52.0%68.8%
111Josh PalmerLACWR6758.2%60.5%53.4%67.5%
112Mason Tipton◦ provisionalNOWR2653.8%60.3%51.6%68.8%
113Cedric Tillman◦ provisionalCLEWR5156.9%60.3%52.6%67.7%
114Tre TuckerLVWR8158.0%60.2%53.4%66.9%
115Xavier LegetteCARWR8557.6%59.9%53.2%66.5%
116David Moore◦ provisionalCARWR5756.1%59.7%52.3%67.0%
117Kevin Austin Jr.◦ provisionalNOWR2250.0%59.6%50.7%68.3%
118George PickensPITWR10357.3%59.5%53.1%65.7%
119Odell Beckham Jr.◦ provisionalMIAWR1947.4%59.4%50.3%68.2%
120Keenan AllenCHIWR12356.9%59.0%53.0%64.9%
121Brandon Aiyuk◦ provisionalSFWR4753.2%58.8%50.9%66.5%
122Christian Watson◦ provisionalGBWR5453.7%58.7%51.1%66.1%
123Nelson Agholor◦ provisionalBALWR2948.3%58.3%49.7%66.7%
124Mike Woods◦ provisionalCLEWR1741.2%58.3%49.1%67.3%
125Troy Franklin◦ provisionalDENWR5352.8%58.3%50.7%65.8%
126Darius SlaytonNYGWR7254.2%58.3%51.2%65.2%
127Nick Westbrook-Ikhine◦ provisionalTENWR6053.3%58.3%50.8%65.5%
128Jalin Hyatt◦ provisionalNYGWR1942.1%58.1%49.0%67.0%
129Alec PierceINDWR6953.6%58.1%50.9%65.1%
130Xavier Hutchinson◦ provisionalHOUWR2646.2%58.0%49.3%66.6%
131Simi Fehoko◦ provisionalLACWR1637.5%57.8%48.5%66.9%
132K.J. Osborn◦ provisionalWASWR1838.9%57.6%48.4%66.6%
133Rashid Shaheed◦ provisionalNOWR4148.8%57.4%49.3%65.3%
134Johnny Wilson◦ provisionalPHIWR1533.3%57.2%47.9%66.4%
135Rome OdunzeCHIWR10153.5%57.1%50.7%63.4%
136Gabe Davis◦ provisionalJAXWR4247.6%56.8%48.7%64.7%
137Marvin Harrison Jr.ARIWR11653.4%56.8%50.6%62.8%
138Keon Coleman◦ provisionalBUFWR5850.0%56.7%49.2%64.1%
139Jermaine Burton◦ provisionalCINWR1428.6%56.7%47.2%65.9%
140Calvin RidleyTENWR12053.3%56.6%50.5%62.6%
141Dontayvion WicksGBWR7651.3%56.6%49.6%63.4%
142Amari CooperBUFWR8551.8%56.5%49.7%63.2%
143Dante Pettis◦ provisionalNOWR2941.4%56.1%47.5%64.6%
144Brandin Cooks◦ provisionalDALWR5448.1%56.1%48.4%63.6%
145Diontae JohnsonHOUWR6749.3%55.9%48.6%63.0%
146Jalen Brooks◦ provisionalDALWR3040.0%55.5%46.9%63.9%
147Marquez Valdes-Scantling◦ provisionalNOWR4443.2%54.8%46.8%62.7%
148Demarcus RobinsonLAWR6647.0%54.7%47.4%61.9%
149Jonathan Mingo◦ provisionalDALWR4240.5%53.9%45.8%61.9%
150Ja'Lynn Polk◦ provisionalNEWR3435.3%53.2%44.7%61.5%
151Adonai Mitchell◦ provisionalINDWR5541.8%53.0%45.4%60.6%

How the shrinkage works

Two estimators

Rate stats (completion %, success rate, catch rate) use a beta-binomial model: a Beta(α, β) prior fit by marginal likelihood over each position group, then a Beta posterior per player. Per-play averages (EPA, CPOE, yards) use a normal-normal model with DerSimonian–Laird between-player variance. Both pull each player toward their group by exactly how thin their sample is.

Does it help? & the fine print

The trust panel’s numbers come from a leakage-free odd/even-week holdout: fit on odd weeks, predict even-week raw. Shrinkage lowers out-of-sample error for every stat. Priors are fit per season and per position (WR and TE separately), so a TE’s baseline isn’t a skill. Regular season only, 2016–2025. Rushing and receiving efficiency are heavily scheme-driven — read the wide bands as the honesty they are.

Source: nflverse play-by-play. Counted and computed deterministically — never modeled by a language model. Built by build_nfl_leaderboards.py (byte-reproducible).