Best MLB Home Runs Matchups — Monday, August 31, 2026
Top home runs spot: Rafael Devers
Rafael Devers (SF) tops the board at 100, facing RHP Bryce Elder. The lefty is going deep on .063 HR/PA against righties this year — and .121 over the last two weeks, big-time bat that turns into a home run in about 6% of his trips. And Bryce Elder has been keeping the ball in the park against righties lately — .000 home runs per batter faced. One catch: the bullpen behind him has been stingy to that side late. He's hitting in a spot worth about 4.5 trips, so the volume's there. He's owned Bryce Elder too — .625 across 8 career trips. It all sets up in a neutral park, weather helping.
The rest of the top of the board
- Kyle Schwarber (PHI) (100) vs RHP Brandon Pfaadt: elite bat at .070 into an arm getting taken deep by the same side (.148).
- Pete Alonso (BAL) (94) vs RHP Tanner Gordon: big-time bat at .057 into an arm getting taken deep by the same side (.067).
- Munetaka Murakami (CWS) (89) vs RHP Peter Lambert: elite bat at .065 into an arm mostly containing the same side (.029), due to bounce back.
- Ben Rice (NYY) (81) vs RHP Walbert Ureña: big-time bat at .057 into an arm keeping the ball in the park against the same side (.000).
- Junior Caminero (TB) (79) vs RHP Robert Stock: big-time bat at .060 into an arm keeping the ball in the park against the same side (.000), hot bat.
- Bryce Harper (PHI) (78) vs RHP Brandon Pfaadt: big-time bat at .054 into an arm getting taken deep by the same side (.148).
- Matt Olson (ATL) (75) vs RHP Anthony Molina: big-time bat at .052 into an arm keeping the ball in the park against the same side (.000).
Platoon edges to target
- Rafael Devers (SF) — lefty bat vs RHP, .063 against righties this year.
- Kyle Schwarber (PHI) — lefty bat vs RHP, .075 against righties this year.
- Munetaka Murakami (CWS) — lefty bat vs RHP, .076 against righties this year.
- Ben Rice (NYY) — lefty bat vs RHP, .068 against righties this year.
- Bryce Harper (PHI) — lefty bat vs RHP, .064 against righties this year.
How it played out
2 of the top 10 home runs matchups landed at least one home run. Top play Rafael Devers finished with 1 home run. 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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