We show you everything. Wins and losses.

Capture: closing-line snapshots from FanDuel + DraftKings at T-10min from first pitch for each of our Best Bets. We capture both Yes and No sides so we can de-vig.

De-vigging: Quoted prob / (sum-of-both-sides quoted prob). Standard market-neutral method - strips the book's margin from the quoted price so we're comparing apples to apples.

Sample: every prediction we ever made (locked pre-game, never edited) where the game has resolved. n = 21073 predictions across 88 days of MLB action. Best Bets = 326 curated picks (~5/day).

Lift definition: our hit rate minus the slate baseline hit rate. The slate baseline is the rate at which any player who appeared in our predictions got at least one hit that day. It IS already filtered to confirmed lineups, so it's already a high bar.

Random baseline: 200 random 5-player samples per day with a seeded RNG (mulberry32, seed=42 - same number every render). Matches the slate rate to within 0.2pp, which is the sanity check that we're not silently sampling the head.

Significance: simple two-sample z-test on Best Bet hit rate vs slate, assuming binomial. z = 0.74, p < 0.01 when |z| > 2.58. The interval is approximate - the true test requires accounting for non-independence within games and across days. Take the number as directional, not publication-grade.

What this audit does NOT include yet: closing-line value (CLV), which would require pulling book lines daily. It is in the queue. Until it ships, lift over the slate (and the season-OBP baseline shown above) are the cleanest defensible edge metrics.