MLB NRFI Picks Today, Model Predictions for Friday, May 12
Joe Robbins/Icon Sportswire via Getty Images. Pictured: Michael Kopech
We weren't showing any value on Thursday's abbreviated MLB slate, but we're back on Friday with five more bets.
As the 2023 season rolls on, we're now able to integrate more current-year data, which should sharpen the model a bit relative to early in the season.
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 Friday, May 12th
Detroit Tigers vs. Seattle Mariners NRFI: Detroit starter Matthew Boyd has been bad overall, but reasonably effective his first pass through the order in 2023. It's also a lefty-on-lefty matchup, with both teams ranking in the bottom half of the league against southpaws.
WashingtonNationals vs. New YorkMets YRFI: A -105 first inning over in a game with a 9-run total is almost always a bet. Most of the value is on the Mets' side here, as the top of their lineup does the bulk of their scoring.
Toronto Blue Jays vs. Atlanta Braves NRFI: Spencer Strider games almost always show up as a value on no first inning runs, thanks to his dominant numbers the first time around the order. Toronto's Chris Bassitt is a solid pitcher as well, and the Braves are just average against right-handed pitching.
Cleveland Guardians vs. Los Angeles Angels NRFI: This might be my first Angels NRFI pick of the season, but the model is showing it as a solid value. Cleveland is projected for very little scoring threat here, so we probably just need to get through the top half of the inning to cash this one.
Chicago White Sox vs. Houston Astros YRFI: Houston projects extremely well here, thanks to horrible first time through the order splits by White Sox starter Michal Kopech. The overall YRFI is a value, but I wouldn't fault anyone for waiting for the Houston-only line to post on DraftKings.
How would you rate this article?
Follow Us On Social
