MLB moneyline & run totals — Thursday, June 11, 2026
A win probability, a projected game total, and each club's projected runs for every matchup — all set beside the market and graded in the open. It grades out near break-even on the moneyline (52%, n=236) and game total (50%, n=155), but it's beating the book on team totals — 53% at -3% ROI over 336 graded bets. Moneylines and game totals are efficient, so we treat those as transparency. Team totals are a softer market, and that's where the model is finding a real edge — as that sample holds, team-total leans are the first thing we'll surface as plays. Until then, all the numbers are here for you to use as you see fit.
STLSt. Louis Cardinals48%+109fair+124mktModel lean+5.0%
NYMNew York Mets✓52%-109fair-146mkt-5.0%
MINMinnesota Twins51%-103fair+110mktModel lean+4.9%
DETDetroit Tigers✓49%+103fair-130mkt-4.9%
AZArizona Diamondbacks48%+109fair+100mktModel lean+0.0%
MIAMiami Marlins✓52%-109fair-120mkt-0.0%
TEXTexas Rangers✓48%+108fair+100mkt-0.1%
KCKansas City Royals52%-108fair-117mktModel lean+0.1%
CHCChicago Cubs✓47%+112fair-152mkt-10.7%
COLColorado Rockies53%-112fair+129mktModel lean+10.7%
LADLos Angeles Dodgers✓48%+108fair-170mkt-12.2%
PITPittsburgh Pirates52%-108fair+142mktModel lean+12.2%
SEASeattle Mariners45%+120fair-118mkt-6.3%
BALBaltimore Orioles✓55%-120fair-102mktModel lean+6.3%
ATLAtlanta Braves49%+104fair-118mkt-2.9%
CWSChicago White Sox51%-104fair+100mktModel lean+2.9%Win% / Fair = our model's win probability (and that as fair, no-vig odds). Mkt = consensus market line. Edge = our number minus the market's. The gold side is the one we favor more than the market — informational, not a play. Not betting advice.
We grade all three markets against the book, in the open — this is the whole point of shipping the model. The moneyline and game total are efficient and grade out near break-even; the team totals are softer, and that's where the model is actually beating the market.
On the moneyline and game total, a ~50% win rate and ~0% ROI is the honest, expected result — those markets are efficient, priced off the same run estimates we model. The team totals are a thinner, softer market, and the model is clearing the vig there on an early sample. We're posting it all transparently; as the team-total sample grows and holds, those become the first edges we surface as plays.