MLB model picks
One drop per game, published 60 minutes before it starts, then graded in public. 20 MLB games priced so far.
Graded
Newest first, with the win–loss of that game’s recommended (tier A/B) legs.
Giants at CardinalsSep 14no A/B legsBraves at CubsSep 141–0Yankees at TwinsSep 141–1Orioles at MetsSep 141–0Tigers at Blue JaysSep 141–0White Sox at GuardiansSep 142–0Dodgers at RedsSep 141–1Padres at GiantsSep 130–3Mariners at AthleticsSep 131–0Royals at Red SoxSep 13no A/B legsPirates at CubsSep 130–0–1White Sox at CardinalsSep 131–1Reds at BrewersSep 131–0Guardians at TwinsSep 130–1Astros at RaysSep 130–1Dodgers at MarlinsSep 132–0Orioles at Blue JaysSep 131–0Angels at NationalsSep 131–0Phillies at BravesSep 131–0Rockies at TigersSep 130–1
How a drop works
A Python model prices every market from public data
Its probabilities meet the posted line; the gap is the edge
The drop opens 60 minutes before the game
Every leg is graded in public once the game ends
Tier A is an edge of six points or more and tier B three to six; both are recommended. Tier C is below three points — it is shown for completeness and is never recommended. A prop market whose calibration gate is failing is marked watch: the model prices it, the record grades it, and nothing here recommends it.