Last weekend I went 30-6 betting football. That's an 83% hit rate across college and the NFL — the best weekend I've ever had betting anything.
I want to walk through exactly how it happened, because the method matters more than the number. The number is partly luck. The method is repeatable.
Heater grades every bet it analyzes into three tiers, and the tiers did most of the work:
One concrete example from Saturday: home-field advantage. The model applies a home-ice, home-field bump, and on average it's right. But averages hide texture. In an SEC matchup — 100,000 people, genuine travel hostility — I let the model's home edge stand at full weight. In a MAC matchup, where the stadium is a quarter full on a Tuesday-caliber atmosphere, I mentally discounted it. A couple of leans flipped from "thin" to "bettable" (or the reverse) on exactly that reasoning.
That's the division of labor: the model does the arithmetic no human can do — efficiency ratings, market anchoring, 10,000 simulations per game, line-movement context — and the human applies the situational texture no feed carries. Neither alone went 30-6. The combination did.
Three things anyone reading this should hold onto:
Betting markets are built by sharp people with good models. Beating them occasionally requires both halves: computation that's immune to narrative (the model never falls in love with a team) and judgment that's alive to context (the human knows a MAC crowd from an SEC crowd). The model's job is to shrink the board from forty games to a handful of genuine disagreements and to say how big each edge is. The human's job is to audit those few with information the data doesn't carry — and to have the discipline to leave the rest alone.
That discipline is the real product of running everything through a model. It's not that the model picks winners; it's that the model makes it structurally hard to bet bored.
Not sustainably. Break-even at standard -110 juice is 52.4%, and elite professionals sustain roughly 55-57% against the spread. An 83% weekend is a hot streak sitting on top of a sound process — enjoy it, but judge any model or bettor by the long-run graded record, not the best weekend.
Follow its high-conviction picks as given — overriding genuine model conviction usually adds noise. But treat its marginal leans as candidates, not commands: that 54-60% zone is where human context (crowd atmosphere, motivation spots, weather you can see) legitimately tips decisions the math calls close.
In Heater's grading, a play is a bet whose simulated hit rate clears 60% — a real edge worth betting as-is. A lean clears 54% but not 60% — a small edge where additional judgment matters. Below 54%, the verdict is a pass: the market's line is about right and there is no bet.
On average yes, but not uniformly. Packed, hostile venues (major conference rivalry games) deserve the full home bump; half-empty stadiums in low-attendance conferences deserve a discount. Average home edges baked into models and betting lines hide that spread, which makes venue texture one of the most useful human adjustments on marginal bets.