Build MLB Combos With Data-Driven Analytics

MLB combos are priced from one run distribution per game, and that distribution starts with the probable starting pitchers. The builder reads the moneyline, run line and total from the public feed, then weighs each starter’s recent form, both teams’ run scoring and pitching statistics, market movement and head-to-head history. Legs — moneyline, run line, game total and team totals — are read from that same distribution.

Baseball’s correlations are pitcher-driven. A dominant starter makes the favourite more likely to win, the game more likely to stay under and the opponent’s team total more likely to fall short — one script, three legs. The builder captures those links because every leg is a region of one run model. Saved tickets are tracked and every leg is graded from the official final score; a leg that lands on its line is a push and drops out of the ticket. MLB player props — pitcher strikeouts, outs, walks, earned runs and hits allowed; batter hits, walks, runs and RBIs — live on the MLB board and are graded from the box score there; they are not a combo leg. Starters can be scratched late, so the model’s inputs can lag the news.

A home favourite at −150 with the total at 8.5 and the away team total at 3.5. The naive ticket multiplies three near-even legs. But the games where the home starter goes deep and allows little are the games that stay under 8.5, keep the visitors under 3.5 and end in a home win. Moneyline, game under and away team under are positively correlated; the joint probability is well above the product.

Swap the under for the run line at −1.5 and the picture changes: winning by two or more in a game that stays under 8.5 requires a narrow band of outcomes, so the joint probability drops. The builder prices each combination from one run distribution for this game, so the ticket reflects those bands instead of a flat multiplication. A scratched starter moves the whole distribution — check the game page before saving.

The general version of this argument — why one score model beats multiplied legs — is on the combos overview, and the rules used to grade every saved ticket are on the pick tracker.