Chalk of the Day, August 25: Ohtani to homer at +210
The chalkiest home run prop on the Tuesday board, checked against 5,000 play-by-play simulations of the Dodgers at the Braves. The +210 price implies 32.3%. The simulations say 32.6%. Roughly Fair; it becomes a play at +207 or longer.
Written by Jesse, NegativeEV. Last updated 25 August 2026.
- Sample: 5,000 pitch-by-pitch simulations of one game
- Window: 25 August 2026 slate
- Priced at: +210 at Fanatics, as quoted off the board at publication
- Measured: 2026-08-25
The bet
The check:
| Selection | Shohei Ohtani over 0.5 home runs, Dodgers at Braves |
|---|---|
| Price | +210 at Fanatics, as quoted off the board at publication |
| The price implies | 32.3% |
| The simulations say | 32.6% |
| Verdict | Roughly Fair |
| Becomes a play at | +207 or longer |
This is the most-bet home run prop on Tuesday's board, and the simulations land close enough to the price that there is nothing in it. 15 games had odds, 13 of the chalkiest selections were graded against the sims, and the verdicts came back 4 Negative EV, 4 Roughly Fair, 5 Positive EV. Nobody here is picking anything. This is a price the public is already taking, checked.
The board ran from +182 to +230 on this prop across 7 books at the time of the check, against the +207 this needs to break even.
This prop is quoted over-only, so there is no two-sided market to strip the book's rake out of. The honest comparison is the simulated number against what the quoted price implies, and some of that gap is the rake itself.
What the simulations did
Across 5,000 simulations Ohtani's average is 0.38 home runs and the median is 0. The most common outcome by a distance is none at all.
The shape of 5,000 simulations:
| No home run | 67 in 100 |
|---|---|
| Exactly one | 28 in 100 |
| Two or more | 5 in 100 |
The anytime line pays the same for all of the multi-homer games, and there are 5.0 in every 100 of them.
At 5,000 simulations that 32.6% carries a standard error of 0.66 points, so 95 runs in 100 would land between 31.3% and 33.9%. The gap to the price is about 0 points, roughly 0 times that error bar. Said narrowly, and it should be said narrowly: that means only that re-running the simulator would not move the number far enough to reach the price. It is not a claim that we are right and the book is wrong. A number that is systematically off is off to as many standard errors as you like.
How many cracks he gets
How often Ohtani comes to the plate moves this number as much as anything about his swing. Across the runs he comes up 4.92 times on average, at-bats plus walks, and the home run number moves with that count.
Trips to the plate, and what each one is worth:
| 4 trips | 22 in 100 | happens in 21 of every 100 simulations |
|---|---|---|
| 5 trips | 34 in 100 | happens in 64 of every 100 simulations |
| 6 trips | 44 in 100 | happens in 14 of every 100 simulations |
Pooled across every simulation he goes deep on 7.7% of his trips, so whether he bats one more time or one fewer is worth more here than any read on his swing. That extra trip is not his to take either. It depends on the eight hitters around him keeping the order moving, and in the simulations they do not always do it.
What works for him
Two arms clear their own noise on this side, and together they are the story.
- His own career profile, who he is as a hitter, props the number up by about 7.8 points. Neutralize it and 32.6% becomes 24.8%. HR rate .087, 5 of 313 hitters, top 10%. BABIP .327, 31 of 313 hitters, top 10%. K rate .247, 203 of 313 hitters, middle of the pack. Exit velo 94.3, 3 of 313 hitters, top 10%. Launch angle 13.9, 189 of 313 hitters.
- The weather props the number up by about 3.2 points. Neutralize it and 32.6% becomes 29.4%. That arm neutralizes temperature, wind and conditions at once, so the cause is not separable. It is 90 degrees with a 6 mph wind blowing out to centre.
What works against him
- Bryce Elder's season form takes about 2.8 points off. Neutralize it and 32.6% becomes 35.4%. HR rate .036 against .032 for his career, 215 of 275 pitchers, bottom quarter. K rate .193 against .189 for his career, 194 of 275 pitchers, middle of the pack. Hits allowed per batter faced .213 against .229 for his career, 145 of 275 pitchers, middle of the pack. Walk rate .085 against .091 for his career, 120 of 275 pitchers, middle of the pack. Flyballs .171, 121 of 275 pitchers, middle of the pack. Groundballs .243, 57 of 275 pitchers, top quarter.
The pitcher
A right-hander, 1,960 pitches into the season and ranked against the 572 pitchers with enough of them to compare. He releases from a high three-quarters slot, 6.06 feet up (86th percentile) and 1.41 feet across (30th), with 6.29 feet of extension (36th percentile).
The ballpark
Truist Park ranks 19th of 30 for home runs, with a park factor of 0.96 where 1.00 is neutral. It is middle of the pack. In the 2026 data home runs land on 4.8 of every 100 balls in play in the Braves' home games against 5.0 in their road games, 2,752 batted balls at home, 2,786 away, the same club on both sides of the split, so what is left is the park. Open roof, grass, 335 feet to left, 400 to centre, 325 to right, 1001 feet of elevation. Tonight it is 90 degrees with a 6 mph wind blowing out to centre.
Shohei Ohtani, recent against season:
| last 20 PA | last 100 | season | career | |
|---|---|---|---|---|
| hits per PA | .050 | - | .242 | .252 |
| BABIP | .320 | .310 | .324 | .327 |
| strikeout rate | .300 | - | .240 | .247 |
| walk rate | .300 | - | .124 | .121 |
| contact rate | .750 | - | .703 | .698 |
| exit velo (mph) | - | 97.1 | 93.5 | 94.3 |
| launch angle (deg) | - | -14.3 | 12.6 | 13.9 |
- usual lineup spot: 1st (over 118 games)
- plate appearances this season: 524
- plate appearances in the recent window: 20
Those are the inputs the simulator was served, not a separate stat source.
The rest of his night
The home run does not arrive alone. Split across the 5,000 simulations on whether it lands:
:
| when it lands | when it doesn't | |
|---|---|---|
| hits | 2.03 | 1.03 |
| total bases | 5.78 | 1.35 |
| runs | 1.63 | 0.56 |
| RBI | 1.94 | 0.28 |
| his team's runs | 7.15 | 5.29 |
The game itself averages 10.40 total runs. His side scores 7.15 when the homer lands against 5.29 when it does not, so this is not an isolated event - it travels with the whole offence.
What this does and does not say
It says that at +210 the price and the simulations are close enough that there is nothing to claim either way. He goes deep in 33 of every 100 simulated games, and the price is asking for about the same. Every play is relative to its price, and the two numbers meet at +207.
Method
The game is simulated pitch by pitch 5,000 times from the projected lineups, and the prop is graded on how often it lands. 37 factors were neutralized one at a time, each arm a separate 4,000-simulation re-run, so one-at-a-time swings do not sum to the projection. Those 37 cover everything that could bear on this hitter rather than every factor in the game: the other hitters' own career, season and recent tiers were skipped on purpose, because they are most of the cost and none of the answer for a prop about one man. 12 of the 37 came back with a direction we can stand behind. The price is +210 as quoted at Fanatics at publication, and the check is against that quoted price, rake included.
Inside the noise floor
25 of the 37 arms sit inside their own noise, including what Bryce Elder has been throwing lately, his pitch mix (+1.1), the ballpark (+0.9), the rest of the order, the other eight, without him (+0.8), his own recent form (+0.2), how long Bryce Elder stays in (+0.1), Bryce Elder's career profile, the pitcher he faces (-1.6), his own season form (-1.1), playing on the road, he is on the AWAY side, so he is guaranteed all nine innings (-0.8). Those numbers are real measurements and they are printed rather than dropped, but at this simulation count the arm cannot tell a small real effect from no effect. So none of them does nothing, and none of them can be named the thing driving this.
Written up for readers: https://negativeev.com/about/home-run-props All findings: https://negativeev.com/research