Best MLB Hits Matchups — Thursday, August 13, 2026
Top hits spot: Shohei Ohtani
Shohei Ohtani (LAD) tops the board at 100, facing LHP Shane Drohan. The lefty is hitting .270 H/PA against lefties this year — and .407 over the last two weeks, an excellent bat that turns into a hit in about 28% of his trips. And Shane Drohan has been thin against lefties lately. 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 Shane Drohan, 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
- Wade Meckler (LAA) (100) vs RHP Jacob deGrom: a strong bat at .255 into an arm mostly holding up against the same side (.235), hot bat.
- Ceddanne Rafaela (BOS) (87) vs RHP Max Scherzer: an excellent bat at .278 into an arm tough on the same side (.167).
- Andy Pages (LAD) (83) vs LHP Shane Drohan: a strong bat at .256 into an arm with little track record against the same side.
- Steven Kwan (CLE) (83) vs RHP Keider Montero: an excellent bat at .272 into an arm tough on the same side (.133), hot bat.
- Byron Buxton (MIN) (82) vs RHP Aaron Nola: a solid bat at .239 into an arm getting tattooed by the same side (.444), due to bounce back.
- Abimelec Ortiz (WSH) (78) vs RHP Kevin Gausman: a solid bat at .245 into an arm getting tattooed by the same side (.308).
- CJ Abrams (WSH) (78) vs RHP Kevin Gausman: a solid bat at .234 into an arm getting tattooed by the same side (.308).
Pitchers getting tattooed today
RHP Aaron Nola has been vulnerable to righties — .271 hits per batter faced. Bats to target: Byron Buxton (MIN), Royce Lewis (MIN), and Ryan Jeffers (MIN).
Platoon edges to target
- Wade Meckler (LAA) — lefty bat vs RHP, .278 against righties this year.
- Andy Pages (LAD) — righty bat vs LHP, .242 against lefties this year.
- Steven Kwan (CLE) — lefty bat vs RHP, .244 against righties this year.
- CJ Abrams (WSH) — lefty bat vs RHP, .256 against righties this year.
- Brandon Lowe (PIT) — lefty bat vs RHP, .242 against righties this year.
Hot bats and bounce-back spots
Swinging hot bats: Wade Meckler (LAA), Steven Kwan (CLE), Spencer Torkelson (DET), Vladimir Guerrero Jr. (TOR), Keibert Ruiz (WSH), and Bryson Stott (PHI). Cold but due to bounce back: Byron Buxton (MIN), Jackson Chourio (MIL), Spencer Horwitz (PIT), Dillon Dingler (DET), and Andrés Chaparro (WSH).
How it played out
6 of the top 10 hits matchups landed at least one hit. Top play Shohei Ohtani finished with 1 hit. 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 hits matchups
Each score (0–100) starts with the hitter's hits 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 hits board is
The Hits board projects the chance a hitter records at least one hit, matchup-adjusted. 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 contact rate vs this pitcher's hand.
- The starter's hit-suppression and the park.
- Recent form, without over-reacting to a hot or cold week.
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?
Hits is an efficient market — the book prices a 1+ hit line about as well as we do, so we publish our number as graded transparency, not a play. Our projection is sharp (the ranking is well-calibrated); the book just isn't leaving room on it.
How to use it
Use it to see who the model likes to square one up, and how that squares with the price — but there's no systematic edge here, so treat it as research, not a lean.
Everything here is a research signal from the model, graded in public — not betting advice, and no outcome is guaranteed.
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