While there's 12 games on Monday, including one early this afternoon, it's a bit of a quieter slate for my first inning model. There's a handful of pitchers who don't have a large enough sample size to incorporate into the data, as well as relatively sharp lines around the industry. Sometimes the best bet is the one you don't make.
That leaves us with just one officially recommended bet, but I'll include some other leans below, as well as my justification for why I'm not betting them myself.
The Model
The process is relatively simple. First, I start by assuming that the full game (implied) run totals for either team are roughly efficient. As mentioned above, that tends to be the case more often than not. This saves me the trouble of trying to predict the total runs scored in the game — and allows me to focus strictly on the "when" rather than "how many."
Next, I built a database of pitchers performance the first time through the order, relative to their overall stats. Since the latter is presumably baked into the full game total, I wanted to figure out if those runs are more likely to come early or late. Most — but not all — MLB starters do somewhat better early in games, but with some variance in just how much. The model uses xFIP (expected Fielding Independent Pitching) as the ERA predictor of choice.
That's only half of the equation, though, with the offenses making up the other half. To do this, I looked at what percentage of a team's total runs is produced by the top three batters in the lineup. While a first inning run scored, by definition, needs at least four hitters to come to the plate, one of the first three has to actually score it. The metric of choice here is wRC+, based on the projected lineup for the day from each team.
This is a bit of a tradeoff, as lineups (and run totals) can shift throughout the day, especially if significant contributors miss time. However, in my experience the inefficiency of the morning lines more than makes up for the leakage in the model. With that said, exercise caution if, say, Mike Trout is listed as questionable for the nights game.
The Picks
With all of the picks below, I'll include the pick, the best line and the threshold I'd bet it to. These will go up in the morning, so if any major news breaks between publishing and when you read it, be sure to consider that.
Infrequently, rather than betting on the traditional YRFI/NRFI, the pick will be on one team or the other specifically to score a run, which as of this writing is only a betting option at DraftKings. Since the model handles each team individually, sometimes one team is projecting for a greater proportion of the "run equity" in the first inning than the betting lines are accounting for.
NRFI Odds, Picks for Monday, April 17th
Toronto Blue Jays vs. Houston Astros (NRFI): This game has a relatively small eight run game total, but with two starters who pitch much better early in games. Toronto's Kevin Gausman has a sub 2.00 xFIP his first time through the order last season and through the beginning of 2023. Houston's Cristian Javier isn't quite to that level, but he also does better while he's still fresh.
Pittsburgh Pirates vs. Colorado Rockies (YRFI): Thanks to their high totals, games at Coors Field almost always show up as a YRFI value in my model. However, the juice (-160 or worse) is a lot to pay for such a high-variance bet. I'm not betting this myself, but would certainly take the "yes" side if I had to. At some point this season, we'll hopefully have a Coors-specific method of projecting games there.
Detroit Tigers vs. Cleveland Guardians (NRFI): The -120 line on the NRFI is a pretty solid value, but there's two issues at play here. First, Guardians starter Hunter Gaddis has just 20 big-league innings, so data on him is unreliable. Second, there's a solid chance this game doesn't happen. Similar conditions already forced a PPD in Chicago.
