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Edge Lab

11 survivor-pool theories were tested against real historical NFL seasons using real bookmaker odds. Most of them failed. They're all listed here, with sample sizes, because a list of only the winners isn't evidence — it's marketing.

For how the numbers on the board are actually computed, see the methodology page, or browse the underlying teams, players and odds in Explore.

factors tested
11
validated
1
real, not exploitable
1
flat or failed
9

Hypothesis: Teams with extra rest days beat the closing line.

Result: No detectable edge. Rest is already in the price.

2006-2025 · 5,295 games · z < 1.17 · tested 2026-08-01

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Hypothesis: Familiarity compresses margins and favourites underperform.

Result: Flat. Divisional favourites win at their implied rate.

2006-2025 · 5,295 games · z < 1.17 · tested 2026-08-01

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Hypothesis: Home dogs are systematically undervalued.

Result: Flat. No exploitable deviation from market probability.

2006-2025 · 5,295 games · z < 1.17 · tested 2026-08-01

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Hypothesis: Some coaches own particular opponents.

Result: Flat. Head-to-head history adds nothing beyond the line.

2006-2025 · 5,295 games · z < 1.17 · tested 2026-08-01

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Hypothesis: Turf/grass and Denver altitude create priced-out edges.

Result: Flat. Venue effects are fully absorbed by the market.

2006-2025 · 5,295 games · z < 1.17 · tested 2026-08-01

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Hypothesis: Favourites sandwiched between big games underperform.

Result: Flat. No measurable letdown effect after de-vigging.

2021-2025 · Full odds backfill · n/s · tested 2026-08-02

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Hypothesis: Market/ELO agreement (v1), then bookmaker dispersion and book count (v2), should predict which favourites are safest.

Result: Failed twice. v1 inverted - low-confidence games won 76.9% of the time because the market prices roster news ELO cannot see. v2 came back non-monotonic. Not shipped.

2021-2025 · Full odds backfill · inverted / non-monotonic · tested 2026-08-02

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Referee crew effect

significant · not exploitable

Hypothesis: Head-referee assignment shifts game outcomes against the closing line.

Result: Mixed. Every market-facing angle came back flat - favourite win rate, home win rate, totals and over rate all failed correction for multiple comparisons. But penalty-rate heterogeneity across crews is genuinely real and significant. Real effect, not exploitable.

2006-2025 · 3,024 games, 27 head referees · chi-sq = 45.1, p = 0.0014 (penalty rate); market angles n/s · tested 2026-08-05

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Hypothesis: Closing lines are sharper than midweek lines in games involving teams with nothing to play for.

Result: Validated on the elimination arm: closing lines were significantly more accurate than midweek lines against a week 5/10 control. Waiting for late-week news is a real edge in those spots.

2021-2025, weeks 15-18 · 183 games (144 elimination-proxy, 39 clinch-proxy) · z = 3.21 · tested 2026-08-03

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Hypothesis: A team whose pass rush and pass protection are better than its opponent's wins more often than its de-vigged market price implies.

Result: Season-to-date net sack differential is strongly collinear with the market's own pricing (r = 0.509), so a raw test would look positive for the wrong reason. After regressing de-vigged win probability out of the differential, the residual has no predictive value for outcomes (r = -0.006, z = -0.27). Quintiles of the residual all land within 1.2 points of their implied win rate (|z| <= 0.52, non-monotonic). The PFR pressure-rate version behaves the same way (collinearity r = 0.537, residual r = 0.013, z = 0.59) on ~27.5 player rows per team-week.

2021-2025, weeks 5-18 (REG) · 2,052 team-weeks (4-game minimum rolling window) · collinearity r = 0.509 with de-vigged win prob; residual r = -0.006, z = -0.27 · tested 2026-08-25

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Hypothesis: Favourites underperform their de-vigged market price in primetime standalone windows.

Result: Flat. Primetime is not priced differently to begin with — the mean de-vigged favourite win probability is 0.6673 in primetime and 0.6681 outside it, so there is no collinearity to strip out. Favourites then finished +0.44 sigma above their implied win rate in primetime and -1.11 sigma below it elsewhere, a difference of z = +0.92 — not significant, and directionally the opposite of the premise: primetime favourites slightly overperform. Splitting by win-probability bucket produces no monotonic pattern.

2006-2025 · 1,230 primetime games / 4,051 non-primetime games · collinearity check: 0.6673 vs 0.6681 mean favourite win prob; primetime z = +0.44, non-primetime z = -1.11, difference z = +0.92 · tested 2026-08-25

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What's actually validated

De-vigged market win probability — the strongest single signal available, and the baseline everything else failed to beat.

Certified · Late-week timing

Closing lines beat midweek lines at z = 3.21 in weeks 15–18 games involving teams already out of contention.

Certified · Equity score

Validated as harmless rather than as an edge: across 2021–2025 it cost about one percentage point of average win probability with no measurable survival cost (both strategies averaged ~4.2 weeks; in divergent weeks the equity pick won 84.6% versus chalk's 73.1%).

Certified · Monte Carlo path survival

The simulator's ~1.2% per-season full-survival estimate matched reality: 0 of 5 replayed seasons (2021–2025) survived under greedy picking.

Certified · ELO ratings

Zero-sum verified across every game since 1999, useful as a research baseline, blind to roster news.

The honest summary: the betting market is very hard to beat, surviving a full season is rare, and the value this product adds is disciplined pick sequencing and pool differentiation — not a secret edge. Referee crews are the clearest example of the distinction we hold to: the effect is statistically real, and it still isn't something you can bet.

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