Best MLB Hits Matchups — Monday, June 8, 2026
Top hits spot: Casey Schmitt
Casey Schmitt (SF) tops the board at 100, facing LHP Richard Lovelady. The righty is hitting .357 H/PA against lefties this year — and .400 over the last two weeks, an excellent bat that turns into a hit in about 29% of his trips. And Richard Lovelady has been getting tattooed by lefties lately — .333 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 4.7 trips, so the volume's there. He's just .000 in 2 career PA against Richard Lovelady, 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
- Christian Yelich (MIL) (94) vs LHP Jeffrey Springs: an excellent bat at .272 into an arm getting tattooed by the same side (.429).
- Yordan Alvarez (HOU) (87) vs RHP Grayson Rodriguez: a strong bat at .256 into an arm vulnerable to the same side (.269), hot bat.
- Fernando Tatis Jr. (SD) (85) vs LHP Andrew Abbott: an excellent bat at .289 into an arm tough on the same side (.194).
- Travis Bazzana (CLE) (83) vs RHP Will Warren: an excellent bat at .273 into an arm tough on the same side (.182), due to bounce back.
- Jackson Chourio (MIL) (82) vs LHP Jeffrey Springs: an excellent bat at .280 into an arm giving up plenty to the same side (.259).
- Jeremy Peña (HOU) (81) vs RHP Grayson Rodriguez: an excellent bat at .270 into an arm tough on the same side (.143).
- Kyle Schwarber (PHI) (78) vs LHP Patrick Corbin: a strong bat at .253 into an arm tough on the same side (.182), due to bounce back.
Pitchers getting tattooed today
- LHP Jeffrey Springs has been vulnerable to lefties — .264 hits per batter faced. Bats to target: Christian Yelich (MIL), Jackson Chourio (MIL), and Andrew Vaughn (MIL).
- RHP Grayson Rodriguez has been giving up plenty to righties — .258 hits per batter faced. Bats to target: Yordan Alvarez (HOU), Jeremy Peña (HOU), and Shay Whitcomb (HOU).
Platoon edges to target
- Casey Schmitt (SF) — righty bat vs LHP, .357 against lefties this year.
- Yordan Alvarez (HOU) — lefty bat vs RHP, .250 against righties this year.
- Fernando Tatis Jr. (SD) — righty bat vs LHP, .296 against lefties this year.
- Travis Bazzana (CLE) — lefty bat vs RHP, .272 against righties this year.
- Jackson Chourio (MIL) — righty bat vs LHP, .323 against lefties this year.
Hot bats and bounce-back spots
Swinging hot bats: Yordan Alvarez (HOU), Cole Young (SEA), Blake Dunn (CIN), Luis Arraez (SF), Brandon Marsh (PHI), and Jung Hoo Lee (SF). Cold but due to bounce back: Casey Schmitt (SF), Travis Bazzana (CLE), Kyle Schwarber (PHI), Luis García Jr. (WSH), and Ty France (SD).
How it played out
6 of the top 10 hits matchups landed at least one hit. Top play Casey Schmitt finished with 2 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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