Best MLB Hits Matchups — Monday, September 21, 2026
Top hits spot: Jonah Cox
Jonah Cox (SF) tops the board at 100, facing RHP Zebby Matthews. The righty is hitting .273 H/PA against righties this year — and .303 over the last two weeks, a strong bat that turns into a hit in about 26% of his trips. And Zebby Matthews has been tough on righties lately — .000 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 Zebby Matthews. It all sets up in a park that leans hitter.
The rest of the top of the board
- Drew Gilbert (SF) (99) vs RHP Zebby Matthews: a solid bat at .245 into an arm tough on the same side (.174), due to bounce back.
- Brett Bateman (TOR) (91) vs RHP Shane Baz: an excellent bat at .279 into an arm getting tattooed by the same side (.297).
- Luke Keaschall (MIN) (82) vs RHP Blade Tidwell: a solid bat at .248 into an arm tough on the same side (.182), hot bat.
- Walker Jenkins (MIN) (81) vs RHP Blade Tidwell: a solid bat at .241 into an arm tough on the same side (.167).
- Bo Davidson (SF) (74) vs RHP Zebby Matthews: a solid bat at .245 into an arm tough on the same side (.174).
- Brooks Lee (MIN) (72) vs RHP Blade Tidwell: a solid bat at .239 into an arm tough on the same side (.167), hot bat.
- Alejandro Kirk (TOR) (70) vs RHP Shane Baz: a solid bat at .249 into an arm tough on the same side (.200), hot bat.
Platoon edges to target
- Brett Bateman (TOR) — lefty bat vs RHP, .303 against righties this year.
- Walker Jenkins (MIN) — lefty bat vs RHP, .231 against righties this year.
- Brooks Lee (MIN) — lefty bat vs RHP, .253 against righties this year.
- Daylen Lile (WSH) — lefty bat vs RHP, .236 against righties this year.
- Nathan Lukes (TOR) — lefty bat vs RHP, .268 against righties this year.
Hot bats and bounce-back spots
Swinging hot bats: Luke Keaschall (MIN), Brooks Lee (MIN), Alejandro Kirk (TOR), and Riley Greene (DET). Cold but due to bounce back: Jonah Cox (SF), Drew Gilbert (SF), George Springer (TOR), Drew Cavanaugh (SF), and Pete Alonso (BAL).
How it played out
7 of the top 10 hits matchups landed at least one hit. Top play Jonah Cox 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 the WizLine 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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