How We Built Our MLB NRFI Model — A Public Methodology Walkthrough

Demystifying the NRFI Market

The NRFI (No Run First Inning) market is one of the most explosive and popular derivative markets in Major League Baseball. Because it resolves in about 15 minutes, the public loves the instant gratification. However, the public consistently loses money on NRFIs because they base their decisions entirely on the starting pitchers' names.

If Gerrit Cole is pitching against Corbin Burnes, the public blindly takes the NRFI. The market makers know this, and they brutally inflate the juice, turning what looks like a safe play into a severely negative EV trap.

To beat the NRFI market, our data engineering team had to build a specialized algorithmic model from the ground up. Here is a brief look at our methodology.

First-Inning Specific Metrics

Starting pitchers perform differently in the first inning than they do in the rest of the game. Some pitchers require an inning to find their release point, while others are utterly dominant before the opposing lineup has seen all their pitches.

Our model completely ignores a pitcher's overall ERA. Instead, we isolate their first-inning splits, strike-rate percentages, and specifically, their performance against the top three batters in the opponent's lineup.

Umpire Tendencies and Park Factors

A critical flaw in public NRFI logic is ignoring the umpire. Home plate umpires have distinct, documented strike zones. Some are "pitcher-friendly" with wide zones that artificially inflate strikeout rates, while others squeeze the zone, leading to early walks and high-leverage situations. Our sports data analytics platform integrates daily umpire assignments directly into the simulation.

Furthermore, we heavily weight park factors. A fly ball that is a routine out in San Francisco might be a three-run home run in Cincinnati.

The Bottom Line

By processing millions of historical first-inning simulations, our positive EV sports analytics software calculates the true, un-inflated probability of a run being scored. When the public inflates the price of a big-name pitching matchup, our model confidently steps aside—or finds massive value fading the public perception on the YRFI (Yes Run First Inning) side.