What we measured, and what we killed

50.8% against the spread at our primary threshold, 95% CI [48.7, 52.9]. Breakeven at −110 is 52.4%. The interval contains a coin flip and the point estimate is below breakeven.

What we did: No NFL game-line model ships. THE LINE launched with no model at all, by decision.

54.1% ATS at the pre-registered threshold, 99% CI [48.3, 59.7] on 501 bets — an interval that still contains a coin flip. The shape across thresholds was incoherent (50.7 → 54.1 → 51.3 → 46.4).

What we did: Refused. 54.1% is exactly the number the pre-registration was written to defend against, and the holdout was never opened. Attempt 3 of 3 remains unspent.

Receiving yards: real but miscalibrated (skill +1.28% Brier skill score, reliability deciles off by more than 10 points at n≥100). Receptions: −0.61% — no better than the player’s own season history.

What we did: Phase B never ran. No prop probability, projection or recommendation ships. We still capture and grade prop PRICES, because storing a market price is not forecasting an outcome.

AUC 0.548 against the book price’s 0.558. The market ranks hitters better than we do, and the constraint is discrimination — no amount of recalibration fixes it.

What we did: No hits probability is ever a recommendation, and the bet picker still shows the market’s de-vigged number alone. The model figure appears in exactly one place — the Edge Board’s analysis lane — where it renders beside the price’s own number, is sorted by the measured band rather than by raw edge, and carries this result and its reliability curve on the surface itself.

Hits priced heavier than −160 lost across their lifetime (−6.6%, n=154). The same market lighter than −160 made +39% (n=231).

What we did: A date-aware −160 cap on single hit plays. Deliberately date-aware, so history stays reported under the rule it was published with — retro-reclassifying would have inflated the track record.

Did not survive its closing-line check.

What we did: The lane was removed from the bet registry rather than left running quietly.

Failed its own baseline.

What we did: Kept as a research ledger, never promoted to a play surface.

Nine markets captured pregame and settled silently for months — n=306,491 settled bets. Every one of them lost to its own closing price: home runs −41.1% ROI, RBIs −22.3%, total bases −18.8%, runs −18.3%, batter strikeouts −18.0%, anytime hits −13.1%, and the three pitcher lanes −8.1% to −12.3%. Average CLV across all of it: 0.00pp — indistinguishable from noise.

What we did: None of these markets was ever promoted to a play surface, and four of them stopped being archived on 2026-09-03. The ledger is now a 14-day rolling window rather than a growing table, because it was re-confirming a settled verdict at ~5,650 rows a day. The full-history numbers above are frozen in the artifact so the result survives the rows.

Measured at 105 inferred routes / 4.6 games — refuted in both units, so it is not an artifact of converting between them.

What we did: We publish our own number and say where the other one came from. YPRR also turned out to be mostly a usage metric: it is TPRR x yards-per-target, and its stability sits beside the usage factor (0.867) not the efficiency one (0.425).

Reversed. Passing xTD per attempt reads r=0.205 and stabilizes at >20.4 games; the raw passing touchdown rate reads 0.244 at >15.4 games.

What we did: The index uses the raw passing rate for quarterbacks — the one place a raw touchdown rate survives. A passer’s touchdown rate carries persistent skill that field position cannot see, which is exactly what xTD removes by design.

Measured over 135 season-weeks, paired: an index of pure opportunity LOSES (WR/TE -0.016 [-0.022, -0.009]). Adding production makes it +0.005 [0.001, 0.010] — but that version contains points per game as a component, so it beats a baseline it is built from.

What we did: The grade ships as a description of where a player stands, never as a ranking of next week. Quarterbacks clear nothing in any configuration tried.

Withdrawn on re-measurement. The two providers agree exactly where both record a player (r=1.0000, 100% exact match). The apparent 14% population gap is entirely weeks 16-18 of one file — coverage is 100.0% in weeks 1-15 and 44/20/6% after.

What we did: We had banned league-wide averages and percentile ranks across 2023 on the strength of an undiagnosed 14%. They are allowed; what is banned is mixing the two 2023 chartings, which double-count.

They are not. `target_share` has 60 non-null rows in 2003, 168 in 2004, ZERO in 2005, 71 in 2006 and 452 in 2007, against ~16,500 a season either side; `air_yards_share` is absent 2003–2005. Our aggregator fell back to 0, so six seasons of "commanded 0% of his team’s targets" entered a training set as measured data.

What we did: Caught because the air-yards projection came out 14.6% WORSE than doing nothing. Nulling the missing values moved target share from +2.0% to +7.9% and its R² from 0.304 to 0.519. Missing is now null and the row is dropped — never a zero that arithmetic accepts.

Both wrong, and wrong the same way. Snap counts start in **2013** (23,800 rows; the original probe tested only 1999, 2006 and 2016). Expected touchdowns cover **2009–2025**, ~5,000 player-games a season — the "three seasons" figure came from a probe that only asked about 2023–2025.

What we did: Each stale bound had kept a real metric out of the projection model — snap share, the fastest-stabilizing usage metric in the sport, and expected touchdowns. Both now project (+7.3/+6.0% and +16.0/+16.5%). The bound is read from `lib/nfl/coverage.ts` in one place instead of being restated in migration headers and script guards, and the 2013–2015 snap seasons were backfilled so the claim is true in the database too.