Best MLB Home Runs Matchups — Wednesday, June 17, 2026
Top home runs spot: Nick Kurtz
Nick Kurtz (ATH) tops the board at 100, facing RHP Braxton Ashcraft. The lefty is going deep on .051 HR/PA against righties this year — and .103 over the last two weeks, real bat that turns into a home run in about 5% of his trips. And Braxton Ashcraft has been getting taken deep by righties lately — .050 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 4.7 trips, so the volume's there. He's just .000 in 1 career PA against Braxton Ashcraft, but that's a tiny sample and the matchup says regression. It all sets up in a neutral park, weather helping.
The rest of the top of the board
- Kyle Schwarber (PHI) (88) vs RHP Sandy Alcantara: big-time bat at .053 into an arm mostly containing the same side (.033), hot bat.
- James Wood (WSH) (84) vs RHP Luinder Avila: real bat at .043 into an arm getting taken deep by the same side (.091), hot bat.
- Yordan Alvarez (HOU) (82) vs RHP Casey Mize: real bat at .047 into an arm with little track record against the same side, hot bat.
- Hunter Goodman (COL) (73) vs RHP Javier Assad: big-time bat at .051 into an arm keeping the ball in the park against the same side (.000).
- Brandon Lowe (PIT) (67) vs RHP Aaron Civale: real bat at .047 into an arm with little track record against the same side.
- Alec Burleson (STL) (65) vs RHP Bradgley Rodriguez: real bat at .042 into an arm keeping the ball in the park against the same side (.000), hot bat.
- Bryce Harper (PHI) (60) vs RHP Sandy Alcantara: real bat at .044 into an arm mostly containing the same side (.033), due to bounce back.
Platoon edges to target
- Nick Kurtz (ATH) — lefty bat vs RHP, .051 against righties this year.
- Kyle Schwarber (PHI) — lefty bat vs RHP, .085 against righties this year.
- James Wood (WSH) — lefty bat vs RHP, .066 against righties this year.
- Yordan Alvarez (HOU) — lefty bat vs RHP, .071 against righties this year.
- Brandon Lowe (PIT) — lefty bat vs RHP, .063 against righties this year.
How it played out
1 of the top 10 home runs matchups landed at least one home run. Top play Nick Kurtz 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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