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.

Completion % · 2023

Completions per pass attempt. Depth-of-target confound: a checkdown offense completes more. Pair with CPOE.

Beats raw by
15.6%
lower out-of-sample error
RMSE raw → shrunk
5.2% → 4.4%
odd vs. even weeks
Split-half reliability
0.42
how repeatable the raw stat is
Stabilizes at
255
attempts to trust the number
shrunkrawthe shrink90% CI
50%55%60%65%avg1Tua TagovailoaMIA · 59163.8%2Dak PrescottDAL · 63163.4%3Brock PurdySF · 47263.2%4Kirk CousinsMIN · 32863.0%5Derek CarrNO · 58163.0%6Patrick MahomesKC · 62462.8%7Jared GoffDET · 64062.4%8Josh AllenBUF · 60762.2%9Jake BrowningCIN · 26861.7%10Mason RudolphPIT · 8061.6%11Joe BurrowCIN · 38961.4%12Lamar JacksonBAL · 49561.1%13Trevor LawrenceJAX · 60260.9%14C.J. BeathardJAX · 6060.8%15Tyson BagentCHI · 14960.8%16Jalen HurtsPHI · 57560.7%17Nick MullensMIN · 16060.6%18Cooper RushDAL · 2560.5%19Justin HerbertLAC · 48660.5%20Jordan LoveGB · 61160.5%21Geno SmithSEA · 53260.3%22Mac JonesNE · 36860.3%23Kyler MurrayARI · 29160.0%24Russell WilsonDEN · 49559.8%25Carson WentzLA · 2759.7%26Baker MayfieldTB · 61059.6%27Jimmy GaroppoloLV · 18459.6%28Easton StickLAC · 18859.3%29Marcus MariotaPHI · 2659.2%30Desmond RidderATL · 42259.2%31C.J. StroudHOU · 54159.1%

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.

Completion % · 2023 · full board

Completion % leaderboard for the 2023 NFL season, shrunk by empirical Bayes with 90% credible intervals, ranked by the shrunk estimate.
#PlayerTeamPosattemptsRawShrunk90% interval
1Tua TagovailoaMIAQB59165.6%63.8%61.0%66.5%
2Dak PrescottDALQB63165.0%63.4%60.7%66.0%
3Brock PurdySFQB47265.3%63.2%60.2%66.1%
4Kirk CousinsMINQB32865.8%63.0%59.7%66.3%
5Derek CarrNOQB58164.5%63.0%60.2%65.7%
6Patrick MahomesKCQB62464.3%62.8%60.2%65.5%
7Jared GoffDETQB64063.6%62.4%59.7%65.0%
8Josh AllenBUFQB60763.4%62.2%59.5%64.9%
9Jake BrowningCINQB26863.8%61.7%58.1%65.1%
10Mason Rudolph◦ provisionalPITQB8068.8%61.6%57.2%66.0%
11Joe BurrowCINQB38962.7%61.4%58.2%64.5%
12Lamar JacksonBALQB49562.0%61.1%58.2%64.0%
13Trevor LawrenceJAXQB60261.5%60.9%58.1%63.6%
14C.J. Beathard◦ provisionalJAXQB6066.7%60.8%56.2%65.3%
15Tyson Bagent◦ provisionalCHIQB14963.1%60.8%56.7%64.7%
16Jalen HurtsPHIQB57561.2%60.7%57.9%63.4%
17Nick Mullens◦ provisionalMINQB16062.5%60.6%56.6%64.5%
18Cooper Rush◦ provisionalDALQB2572.0%60.5%55.7%65.3%
19Justin HerbertLACQB48661.1%60.5%57.6%63.5%
20Jordan LoveGBQB61160.9%60.5%57.7%63.2%
21Geno SmithSEAQB53260.7%60.3%57.4%63.1%
22Mac JonesNEQB36860.9%60.3%57.0%63.5%
23Kyler MurrayARIQB29160.5%60.0%56.5%63.4%
24Russell WilsonDENQB49560.0%59.8%56.8%62.7%
25Carson Wentz◦ provisionalLAQB2763.0%59.7%54.9%64.5%
26Baker MayfieldTBQB61059.7%59.6%56.8%62.3%
27Jimmy Garoppolo◦ provisionalLVQB18459.8%59.6%55.7%63.4%
28Easton Stick◦ provisionalLACQB18859.0%59.3%55.4%63.1%
29Marcus Mariota◦ provisionalPHIQB2657.7%59.2%54.4%64.0%
30Desmond RidderATLQB42259.0%59.2%56.0%62.2%
31C.J. StroudHOUQB54159.0%59.1%56.2%62.0%
32Case Keenum◦ provisionalHOUQB5957.6%59.1%54.5%63.6%
33Tyrod Taylor◦ provisionalNYGQB19858.6%59.0%55.2%62.8%
34Mitchell Trubisky◦ provisionalPITQB11558.3%59.0%54.8%63.2%
35Matthew StaffordLAQB55458.8%59.0%56.2%61.9%
36Drew Lock◦ provisionalSEAQB8357.8%59.0%54.6%63.4%
37Andy Dalton◦ provisionalCARQB6155.7%58.7%54.1%63.2%
38Joe Flacco◦ provisionalCLEQB21357.8%58.7%54.9%62.4%
39Joshua DobbsMINQB45058.2%58.7%55.6%61.7%
40Brian Hoyer◦ provisionalLVQB4353.5%58.5%53.8%63.2%
41Aidan O'ConnellLVQB36857.9%58.5%55.2%61.7%
42Tim Boyle◦ provisionalNYJQB8655.8%58.5%54.1%62.8%
43Sam Darnold◦ provisionalSFQB5253.8%58.5%53.8%63.0%
44Kenny PickettPITQB34857.8%58.5%55.1%61.7%
45Jarrett Stidham◦ provisionalDENQB7354.8%58.4%53.9%62.8%
46Gardner MinshewINDQB52757.9%58.4%55.5%61.3%
47Tyler Huntley◦ provisionalBALQB4151.2%58.3%53.5%62.9%
48Blaine Gabbert◦ provisionalKCQB3650.0%58.2%53.5%62.9%
49Daniel Jones◦ provisionalNYGQB19156.5%58.2%54.3%62.0%
50Ryan TannehillTENQB26256.9%58.1%54.5%61.7%
51Jameis Winston◦ provisionalNOQB4951.0%58.1%53.4%62.7%
52Jeff Driskel◦ provisionalCLEQB2944.8%57.9%53.1%62.7%
53Deshaun Watson◦ provisionalCLEQB18855.9%57.9%54.0%61.7%
54Anthony Richardson◦ provisionalINDQB9353.8%57.9%53.5%62.2%
55Sam HowellWASQB67957.1%57.8%55.1%60.4%
56Clayton Tune◦ provisionalARIQB2842.9%57.8%52.9%62.5%
57Brett Rypien◦ provisionalLAQB4045.0%57.5%52.7%62.1%
58Trevor Siemian◦ provisionalNYJQB16153.4%57.1%53.1%61.1%
59Davis Mills◦ provisionalHOUQB4242.9%57.1%52.3%61.8%
60Bailey Zappe◦ provisionalNEQB23753.6%56.6%52.9%60.3%
61Dorian Thompson-Robinson◦ provisionalCLEQB11950.4%56.5%52.3%60.7%
62Taylor Heinicke◦ provisionalATLQB14451.4%56.5%52.4%60.6%
63Tommy DeVito◦ provisionalNYGQB21553.0%56.5%52.7%60.2%
64Justin FieldsCHIQB41654.6%56.4%53.3%59.5%
65Will LevisTENQB28452.5%55.8%52.2%59.3%
66Zach WilsonNYJQB41653.1%55.5%52.3%58.7%
67Bryce YoungCARQB59053.4%55.2%52.4%58.0%
68PJ Walker◦ provisionalCLEQB12244.3%54.5%50.3%58.7%

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).