Our model's win probability vs. the market's implied probability. The gap is the edge.
Every factor that moved the model. Every number sourced — no hallucinations.
The Giants' runline sits at +140 despite home-field advantage, a pricing inefficiency Supreme Brain exploits for +5.0% expected value. The model assigns San Francisco a 50.0% probability to cover -1.5 runs against Colorado, matching the market-implied probability at current odds but offering plus money on home chalk—a rare structural edge. The Rockies arrive with 12 players on the injury report, while the Giants carry 14, creating roster uncertainty on both sides. The primary risk is the single-run win, which kills runline value even when the thesis holds. At +140, you're getting paid to fade the one-run margin that typically haunts home favorites. Quarter-Kelly sizing suggests 0.14 units, reflecting the modest edge and binary outcome variance inherent to runline markets.
Supreme Brain assigns the Giants' runline a 50.0% win probability at +140 odds—plus money on home chalk, a structural rarity that typically signals mispriced vig rather than true coin-flip uncertainty.
San Francisco -1.5 offers +5.0% expected value because the market is paying you to take the favorite in a multi-run margin, a bet that normally costs juice but here returns +140.
The single-run win is the thesis-killer. If San Francisco leads 3-2 in the ninth and holds, you lose the same as if they'd been blown out. Runline bets live and die on margin, and home favorites win by one run roughly 25-30% of the time across MLB. A late-inning bullpen meltdown by Colorado that makes it close, or a Giants offense that scores early then coasts, both break the -1.5 cover. The model gives you a coin flip; variance decides whether that flip lands on the right side of two runs.
You're not betting the Giants to win. You're betting the market mispriced the margin, and at +140, you get paid to find out if two runs of separation is more likely than the vig suggests.