Best MLB Hits Matchups — Sunday, August 16, 2026
Top hits spot: Jac Caglianone
Jac Caglianone (KC) tops the board at 100, facing RHP Ryan Johnson. The lefty is hitting .255 H/PA against righties this year — and .500 over the last two weeks, an excellent bat that turns into a hit in about 29% of his trips. And Ryan Johnson has been tough on righties lately — .143 hits 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. No real history against Ryan Johnson. It all sets up in a neutral park.
The rest of the top of the board
- Yordan Alvarez (HOU) (100) vs RHP Bryan Woo: a strong bat at .270 into an arm tough on the same side (.107).
- Otto Lopez (MIA) (99) vs LHP Nick Lodolo: a strong bat at .262 into an arm getting tattooed by the same side (.333).
- Jake McCarthy (COL) (99) vs RHP Blade Tidwell: an excellent bat at .275 into an arm getting tattooed by the same side (.350).
- Sal Stewart (CIN) (95) vs RHP Eury Pérez: a solid bat at .249 into an arm getting tattooed by the same side (.316), hot bat.
- Javier Sanoja (MIA) (94) vs LHP Nick Lodolo: an excellent bat at .285 into an arm getting tattooed by the same side (.333), due to bounce back.
- Gabriel Moreno (AZ) (94) vs RHP Bryce Elder: a strong bat at .265 into an arm tough on the same side (.176), hot bat.
- Jeremy Peña (HOU) (94) vs RHP Bryan Woo: a solid bat at .241 into an arm tough on the same side (.188).
Pitchers getting tattooed today
RHP Blade Tidwell has been vulnerable to righties — .271 hits per batter faced. Bats to target: Jake McCarthy (COL), Mickey Moniak (COL), and Troy Johnston (COL).
Platoon edges to target
- Jac Caglianone (KC) — lefty bat vs RHP, .255 against righties this year.
- Yordan Alvarez (HOU) — lefty bat vs RHP, .278 against righties this year.
- Otto Lopez (MIA) — righty bat vs LHP, .347 against lefties this year.
- Jake McCarthy (COL) — lefty bat vs RHP, .264 against righties this year.
- Javier Sanoja (MIA) — righty bat vs LHP, .311 against lefties this year.
Hot bats and bounce-back spots
Swinging hot bats: Jac Caglianone (KC), Sal Stewart (CIN), Gabriel Moreno (AZ), Brett Bateman (TOR), Yandy Díaz (TB), and Chase DeLauter (CLE). Cold but due to bounce back: Javier Sanoja (MIA), Agustín Ramírez (MIA), Jared Triolo (PIT), CJ Abrams (WSH), and Mickey Moniak (COL).
How it played out
6 of the top 10 hits matchups landed at least one hit. Top play Jac Caglianone finished with 0 hits. 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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