Best MLB Home Runs Matchups — Thursday, July 9, 2026
Top home runs spot: Rafael Devers
Rafael Devers (SF) tops the board at 100, facing RHP Ryan Feltner. The lefty is going deep on .058 HR/PA against righties this year — and .200 over the last two weeks, big-time bat that turns into a home run in about 6% of his trips. And Ryan Feltner has been getting taken deep by righties lately — .095 home runs per batter faced. The bullpen behind him is roughly average to that side. He's hitting in a spot worth about 4.3 trips, so the volume's there. He's just .200 in 5 career PA against Ryan Feltner, but that's a tiny sample and the matchup says regression. It all sets up in a neutral park.
The rest of the top of the board
- Kyle Schwarber (PHI) (100) vs RHP Brady Singer: elite bat at .071 into an arm getting taken deep by the same side (.111).
- Hunter Goodman (COL) (89) vs LHP Carson Whisenhunt: big-time bat at .053 into an arm with little track record against the same side, due to bounce back.
- Juan Soto (NYM) (85) vs RHP Michael Wacha: elite bat at .066 into an arm mostly containing the same side (.026).
- Mike Trout (LAA) (84) vs RHP Nathan Eovaldi: real bat at .049 into an arm getting taken deep by the same side (.050), hot bat.
- Shea Langeliers (ATH) (78) vs LHP Framber Valdez: big-time bat at .064 into an arm homer-prone to the same side (.043).
- Sal Stewart (CIN) (76) vs LHP Jesús Luzardo: big-time bat at .053 into an arm keeping the ball in the park against the same side (.000).
- Junior Caminero (TB) (72) vs RHP Paul Blackburn: elite bat at .068 into an arm keeping the ball in the park against the same side (.000), due to bounce back.
Platoon edges to target
- Rafael Devers (SF) — lefty bat vs RHP, .058 against righties this year.
- Kyle Schwarber (PHI) — lefty bat vs RHP, .086 against righties this year.
- Hunter Goodman (COL) — righty bat vs LHP, .063 against lefties this year.
- Juan Soto (NYM) — lefty bat vs RHP, .077 against righties this year.
- Shea Langeliers (ATH) — righty bat vs LHP, .074 against lefties this year.
How it played out
3 of the top 10 home runs matchups landed at least one home run. Top play Rafael Devers finished with 0 home runs. We post the result next to every projection so you can grade the board yourself — and so the model gets re-tuned against what actually happened.
How to read these home runs matchups
Each score (0–100) starts with the hitter's home runs per plate appearance against the hand he's facing — weighted toward the last two weeks, then the season, then a two-year baseline. Then it layers in the bullpen, his spot in the order, and park and weather. Higher means more of it points his way. It's context, not a lock — a great spot still goes 0-for-4 sometimes, and a tough one runs into one. The edge is in stacking the odds, and since we grade every board, you can see how often the top of the list delivers.
What the home runs board is
The Home Runs board projects the chance a hitter goes deep, park and matchup baked in. One statistical model scores every matchup on the slate the same way — a star and a backup judged on the matchup in front of them, not their name — and every number is graded against the real box score once the games go final.
How the model gets its number
It isn't a gut call or a name game. The projection is built from a few things:
- The hitter's power vs the pitcher's hand.
- The park's home-run environment and the wind.
- How hard and how often he hits it in the air.
Those pieces combine into one number, and the model re-tunes itself weekly against how its past calls actually landed.
Is there a betting edge here?
Home runs is one of the most efficiently priced props in the sport — every config we've backtested loses to the line, and our disagreements point away from the book's mistakes, not toward them. So HR is a transparency board: our projection, graded, no play attached. The honest read is the book is simply sharper here.
How to use it
Read it for who's in a live spot to run into one — but don't bet our number against the line; there's no edge to press.
Everything here is a research signal from the model, graded in public — not betting advice, and no outcome is guaranteed.
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