Odds intelligence 2026-10-12
What the sportsbook player-prop market says about this slate, how it moved our published player lines, and how much the market has been worth on settled games.
Games priced2
Players priced38
Book prices1245
Books9
SnapshotPregame
CLE 4 - 5 TBhome win 57.9%
LAD 4 - 3 MILhome win 49.5%
Market blend26 hitters and 4 starters moved toward the market
Player audit0 failures, 619 checks passed
Play by playEvery published line equals its game
Prices from output/odds/20261012/snapshots/odds_20261012T173044Z_6b252f40bc14.csv, written 2026-10-12T17:00:21.404443+00:00.
Books: BetMGM, BetOnline, BetRivers, Bovada, DraftKings, Fanatics, FanDuel, MyBookie, Caesars.
Key takeaways
- The market expects less offense than our model: runs 0.87×, rbi 0.77× of our projection across the slate.
- The published player lines already include the market at the fitted weights below; score, winner and win probability are not changed by it.
- Largest disagreement: Garrett Mitchell, hits + runs + rbi over 0.5: market 55%, our model 81%.
- Best price against the other books: Jo Adell stolen bases over 0.5 at +920 (FanDuel), fair 13.4%.
- Settled evidence so far: 2355 props over 7 date(s). A market needs 300 props over 10 dates for a verdict.
Market against our projection, by stat
| Stat | Players | Market ÷ our model | Our chance minus market's |
|---|---|---|---|
| Hits + runs + RBI | 26 | 0.76× | 12.8% |
| RBI | 26 | 0.77× | 5.5% |
| Runs | 26 | 0.87× | 3.7% |
| Total bases | 26 | 0.96× | 2.0% |
| Home runs | 26 | 1.00× | 0.5% |
| Outs | 4 | 1.00× | 1.0% |
| Hits | 30 | 1.00× | 1.1% |
| Strikeouts | 4 | 1.01× | -0.4% |
| Singles | 26 | 1.01× | -0.4% |
| Walks | 30 | 1.07× | -1.4% |
| Earned runs | 4 | 1.08× | -6.6% |
| Doubles | 26 | 1.12× | -1.6% |
| Triples | 2 | 3.65× | -3.7% |
Below 1.00× the market expects less than our model before odds. A shared gap across a whole slate is a calibration question before it is a player one.
Every priced player
| # | Player | Hits | Home runs | Runs | RBI | Total bases | Walks |
|---|---|---|---|---|---|---|---|
| 1 | Steven KwanCLE | 65%0.93model 0.93we publish 0.96 | 5%0.05model 0.05 | 36%0.44model 0.59we publish 0.46 | 21%0.26model 0.28we publish 0.27 | 63%1.32model 1.31we publish 1.33 | 32%0.36model 0.41we publish 0.37 |
| 3 | Chase DeLauterCLE | 61%0.86model 0.92we publish 0.91 | 9%0.09model 0.13we publish 0.12 | 33%0.40model 0.45we publish 0.41 | 29%0.40model 0.49we publish 0.42 | 60%1.37model 1.55we publish 1.51 | 32%0.37model 0.32we publish 0.36 |
| 4 | Jo AdellCLE | 58%0.78model 0.86we publish 0.82 | 11%0.11model 0.15we publish 0.14 | 31%0.38model 0.39we publish 0.38 | 30%0.41model 0.58we publish 0.43 | 55%1.27model 1.50we publish 1.44 | 26%0.29model 0.17we publish 0.27 |
| 5 | Nathaniel LoweCLE | 54%0.70model 0.77we publish 0.76 | 11%0.12model 0.14 | 30%0.36model 0.28we publish 0.34 | 26%0.33model 0.50we publish 0.36 | 55%1.30model 1.39we publish 1.36 | 25%0.28model 0.26we publish 0.28 |
| 7 | Travis BazzanaCLE | 53%0.68model 0.72we publish 0.73 | 9%0.09model 0.11 | 29%0.34model 0.47we publish 0.36 | 23%0.29model 0.39we publish 0.30 | 54%1.22model 1.25we publish 1.25 | 25%0.28model 0.30we publish 0.28 |
| 8 | Patrick BaileyCLE | 48%0.60model 0.73we publish 0.66 | 9%0.10model 0.13we publish 0.12 | 27%0.32model 0.35we publish 0.32 | 22%0.27model 0.41we publish 0.29 | 48%1.06model 1.27we publish 1.19 | 24%0.26model 0.22we publish 0.25 |
| 9 | Brayan RocchioCLE | 52%0.66model 0.71we publish 0.69 | 7%0.07model 0.09 | 28%0.33model 0.40we publish 0.34 | 21%0.26model 0.37we publish 0.28 | 51%1.03model 1.14we publish 1.12 | 22%0.24model 0.18we publish 0.23 |
| Foster GriffinCLE | –4.51model 5.96we publish 5.06 | – | – | – | – | –1.28model 1.35we publish 1.31 | |
| 2 | Jonathan ArandaTB | 63%0.90model 1.06we publish 0.94 | 11%0.12model 0.15 | 40%0.52model 0.45we publish 0.51 | 29%0.39model 0.59we publish 0.42 | –1.58model 1.69we publish 1.56 | 34%0.40model 0.29we publish 0.38 |
| 3 | Junior CamineroTB | 66%0.95model 0.98we publish 0.97 | 18%0.22model 0.22 | 42%0.55model 0.64we publish 0.56 | 35%0.52model 0.54we publish 0.52 | –1.86model 1.85 | 36%0.42model 0.37we publish 0.41 |
| 4 | Ryan ViladeTB | 53%0.70model 0.88we publish 0.77 | 12%0.12model 0.15we publish 0.15 | 34%0.42model 0.33we publish 0.41 | 28%0.37model 0.52we publish 0.39 | 54%1.24model 1.54we publish 1.42 | 26%0.29model 0.28we publish 0.29 |
| 6 | Chandler SimpsonTB | 63%0.87model 1.13we publish 0.91 | 3%0.04model 0.04 | 30%0.36model 0.43 | 24%0.31model 0.34 | 63%1.13model 1.45we publish 1.23 | – |
| 9 | Taylor WallsTB | 54%0.70model 0.75we publish 0.73 | 7%0.07model 0.05 | 31%0.38model 0.48we publish 0.39 | 24%0.30model 0.32we publish 0.31 | 53%0.99model 1.09we publish 1.08 | 28%0.32model 0.29we publish 0.31 |
| Drew RasmussenTB | –4.31model 3.26we publish 3.84 | – | – | – | – | –1.36model 1.13we publish 1.26 | |
| 1 | Mookie BettsLAD | 63%0.90model 0.85we publish 0.91 | 12%0.16model 0.15 | 42%0.54model 0.47we publish 0.53 | 28%0.38model 0.51we publish 0.40 | –1.67model 1.48we publish 1.54 | 32%0.37model 0.34we publish 0.37 |
| 2 | Freddie FreemanLAD | 62%0.87model 0.92we publish 0.89 | 15%0.16model 0.11we publish 0.12 | 39%0.49model 0.48we publish 0.49 | 29%0.40model 0.46we publish 0.41 | –1.58model 1.47 | 33%0.39model 0.42we publish 0.39 |
| 4 | Shohei OhtaniLAD | 59%0.80model 0.85we publish 0.80 | 23%0.26model 0.16we publish 0.17 | 43%0.56model 0.58we publish 0.56 | 36%0.55model 0.48we publish 0.53 | 58%1.58model 1.52 | 38%0.45model 0.51we publish 0.46 |
| 5 | Will SmithLAD | 58%0.78model 0.77we publish 0.79 | 14%0.17model 0.12 | 39%0.49model 0.41we publish 0.48 | 30%0.41model 0.46we publish 0.42 | 57%1.28model 1.30we publish 1.32 | 35%0.40model 0.38we publish 0.40 |
| 7 | Andy PagesLAD | 56%0.74model 0.78we publish 0.77 | 11%0.11model 0.13 | 34%0.42model 0.50we publish 0.43 | 27%0.36model 0.53we publish 0.39 | 56%1.27model 1.34we publish 1.32 | 29%0.33model 0.29we publish 0.33 |
| 8 | Kyle TuckerLAD | 53%0.70model 0.68we publish 0.70 | 12%0.13model 0.10 | 35%0.43model 0.52we publish 0.44 | 27%0.36model 0.41we publish 0.37 | 53%1.17model 1.14we publish 1.18 | 32%0.37model 0.41we publish 0.38 |
| 9 | Tommy EdmanLAD | – | – | – | – | – | 22%0.24model 0.25 |
| Yoshinobu YamamotoLAD | –4.78model 3.48we publish 4.19 | – | – | – | – | –1.84model 1.32we publish 1.61 | |
| 1 | Jackson ChourioMIL | 65%0.94model 0.94we publish 0.97 | 13%0.14model 0.18we publish 0.17 | 41%0.53model 0.69we publish 0.55 | 30%0.41model 0.59we publish 0.44 | –1.72model 1.67 | 26%0.29model 0.33we publish 0.30 |
| 2 | Brice TurangMIL | 57%0.76model 0.83we publish 0.81 | 8%0.08model 0.12we publish 0.11 | 33%0.40model 0.63we publish 0.43 | 27%0.36model 0.56we publish 0.39 | 56%1.25model 1.40we publish 1.35 | 35%0.42model 0.50we publish 0.43 |
| 3 | William ContrerasMIL | 63%0.88model 0.82we publish 0.86 | 11%0.12model 0.11 | 35%0.44model 0.54we publish 0.45 | 28%0.37model 0.55we publish 0.40 | –1.56model 1.32we publish 1.38 | 32%0.37model 0.35we publish 0.37 |
| 4 | Jake BauersMIL | 48%0.61model 0.76we publish 0.67 | 13%0.16model 0.14 | 34%0.41model 0.58we publish 0.43 | 27%0.36model 0.51we publish 0.38 | 46%1.03model 1.34we publish 1.25 | 40%0.49model 0.56we publish 0.50 |
| 5 | Christian YelichMIL | 57%0.77model 0.72we publish 0.79 | 8%0.08model 0.10 | 36%0.44model 0.56we publish 0.46 | 25%0.33model 0.44we publish 0.34 | 56%1.24model 1.19we publish 1.25 | 35%0.41model 0.39we publish 0.41 |
| 6 | Garrett MitchellMIL | 48%0.61model 0.75we publish 0.67 | 7%0.07model 0.08 | 29%0.35model 0.57we publish 0.38 | 25%0.32model 0.42we publish 0.34 | 49%0.98model 1.19we publish 1.11 | 32%0.36model 0.39we publish 0.37 |
| 7 | Cooper PrattMIL | 58%0.78model 0.74we publish 0.79 | 7%0.07model 0.07 | 29%0.34model 0.38we publish 0.35 | 23%0.29model 0.45we publish 0.31 | 56%1.10model 1.11we publish 1.16 | 24%0.27model 0.29we publish 0.27 |
| 8 | Sal FrelickMIL | 54%0.71model 0.70we publish 0.73 | 6%0.06model 0.06 | 28%0.33model 0.34we publish 0.34 | 23%0.29model 0.40we publish 0.31 | 55%1.11model 1.07we publish 1.10 | 26%0.29model 0.29 |
| Logan HendersonMIL | –3.73model 3.06we publish 3.44 | – | – | – | – | –1.34model 1.29we publish 1.32 |
Each cell: the market's chance of at least one (top), the expectation the market's price implies (bold; red below our model, green above), our model before odds, and the published value after the blend.
Largest disagreements
| Player | Prop | Market chance | Our model | Difference | Expectation: ours → market | Betting decision |
|---|---|---|---|---|---|---|
| Garrett Mitchell | Hits + runs + RBI over 0.5 | 55% | 81% | 26% | 1.74 → 0.85 | pass |
| Yoshinobu Yamamoto | Pitcher hits allowed over 4.5 | 52% | 27% | -25% | 3.48 → 4.78 | pass |
| Drew Rasmussen | Pitcher earned runs over 1.5 | 48% | 24% | -25% | 0.92 → 1.62 | pass |
| Foster Griffin | Pitcher hits allowed over 4.5 | 47% | 71% | 24% | 5.96 → 4.51 | pass |
| Jake Bauers | Hits + runs + RBI over 0.5 | 58% | 81% | 23% | 1.85 → 0.98 | pass |
| Tommy Edman | Hits + runs + RBI over 0.5 | 55% | 77% | 22% | 1.60 → 0.89 | pass |
| Foster Griffin | Pitcher earned runs over 1.5 | 53% | 75% | 22% | 2.71 → 1.79 | pass |
| Andy Pages | Hits + runs + RBI over 0.5 | 60% | 81% | 21% | 1.81 → 1.03 | pass |
| Patrick Bailey | Hits + runs + RBI over 0.5 | 52% | 73% | 21% | 1.49 → 0.86 | pass |
| Travis Bazzana | Hits + runs + RBI over 0.5 | 56% | 76% | 20% | 1.58 → 0.93 | pass |
| Drew Rasmussen | Pitcher hits allowed over 4.5 | 43% | 23% | -20% | 3.26 → 4.31 | pass |
| Brayan Rocchio | Hits + runs + RBI over 0.5 | 56% | 75% | 19% | 1.48 → 0.89 | pass |
| Taylor Walls | Hits + runs + RBI over 0.5 | 59% | 79% | 19% | 1.56 → 0.94 | pass |
| Kyle Tucker | Hits + runs + RBI over 0.5 | 58% | 77% | 19% | 1.60 → 0.97 | pass |
| Foster Griffin | Pitcher outs over 12.5 | 51% | 69% | 18% | 14.57 → 12.77 | pass |
Disagreements are research signals. Every one is a pass until settled games show our model beats the market on that market.
Best prices between books
| Player | Prop | Best price | Book | Fair (other books) | Value vs fair | Books |
|---|---|---|---|---|---|---|
| Jo Adell | Stolen bases over 0.5 | +920 | FanDuel | 13.4% | 36.5% | 2 |
| Chase DeLauter | Stolen bases over 0.5 | +880 | FanDuel | 12.9% | 26.4% | 2 |
| Richie Palacios | Stolen bases over 0.5 | +800 | FanDuel | 13.7% | 23.6% | 2 |
| Angel Martinez | Stolen bases over 0.5 | +800 | FanDuel | 13.7% | 22.8% | 2 |
| Garrett Mitchell | RBI over 0.5 | +345 | DraftKings | 24.9% | 10.8% | 3 |
| Brayan Rocchio | Stolen bases over 0.5 | +630 | FanDuel | 14.7% | 7.4% | 2 |
| Steven Kwan | Stolen bases over 0.5 | +580 | FanDuel | 15.4% | 4.5% | 2 |
| Teoscar Hernandez | Walks over 0.5 | +285 | Fanatics | 27.0% | 3.9% | 3 |
| Ryan Vilade | Hits under 0.5 | +119 | DraftKings | 47.3% | 3.7% | 3 |
| Garrett Mitchell | Hits + runs + RBI under 0.5 | +125 | BetMGM | 45.9% | 3.3% | 4 |
| Taylor Walls | Walks over 0.5 | +255 | DraftKings | 29.1% | 3.2% | 3 |
| Jackson Chourio | Walks over 0.5 | +275 | Fanatics | 27.4% | 2.6% | 3 |
One book's price against the consensus of the others. Hypothetical value between books, not a model view and not a wager.
What the market has been worth
| Market | Props | Players | Games | Dates | Market log loss | Model log loss | Model − market | 95% interval (by game) | Verdict |
|---|---|---|---|---|---|---|---|---|---|
| Doubles | 203 | 106 | 13 | 7 | 0.308 | 0.299 | -0.009 | -0.019 to +0.000 no clear leader | needs 3 more dates and 97 more props |
| Hits | 210 | 106 | 13 | 7 | 0.656 | 0.664 | 0.008 | -0.025 to +0.037 no clear leader | needs 3 more dates and 90 more props |
| Hits + runs + RBI | 229 | 107 | 13 | 7 | 0.696 | 0.775 | 0.080 | +0.007 to +0.150 market ahead | needs 3 more dates and 71 more props |
| Home runs | 239 | 106 | 13 | 7 | 0.291 | 0.280 | -0.010 | -0.021 to +0.001 no clear leader | needs 3 more dates and 61 more props |
| RBI | 203 | 106 | 13 | 7 | 0.579 | 0.591 | 0.012 | -0.008 to +0.030 no clear leader | needs 3 more dates and 97 more props |
| Runs | 203 | 106 | 13 | 7 | 0.621 | 0.637 | 0.016 | -0.010 to +0.037 no clear leader | needs 3 more dates and 97 more props |
| Singles | 203 | 106 | 13 | 7 | 0.676 | 0.686 | 0.011 | -0.012 to +0.033 no clear leader | needs 3 more dates and 97 more props |
| Stolen bases | 186 | 99 | 13 | 7 | 0.258 | 0.253 | -0.006 | -0.027 to +0.020 no clear leader | needs 3 more dates and 114 more props |
| Total bases | 223 | 105 | 13 | 7 | 0.663 | 0.662 | -0.001 | -0.031 to +0.024 no clear leader | needs 3 more dates and 77 more props |
| Triples | 11 | 11 | 10 | 7 | 0.041 | 0.013 | -0.028 | -0.031 to -0.026 model ahead | needs 3 more dates and 289 more props |
| Walks | 197 | 104 | 13 | 7 | 0.604 | 0.617 | 0.013 | -0.001 to +0.028 no clear leader | needs 3 more dates and 103 more props |
| Pitcher earned runs | 25 | 20 | 12 | 6 | 0.665 | 0.691 | 0.026 | -0.079 to +0.147 no clear leader | needs 4 more dates and 275 more props |
| Pitcher hits allowed | 30 | 20 | 12 | 6 | 0.677 | 0.694 | 0.016 | -0.103 to +0.168 no clear leader | needs 4 more dates and 270 more props |
| Pitcher outs | 42 | 20 | 12 | 6 | 0.678 | 0.802 | 0.124 | -0.037 to +0.308 no clear leader | needs 4 more dates and 258 more props |
| Pitcher strikeouts | 35 | 20 | 12 | 6 | 0.641 | 0.650 | 0.009 | -0.083 to +0.136 no clear leader | needs 4 more dates and 265 more props |
| Pitcher walks allowed | 23 | 19 | 12 | 6 | 0.607 | 0.705 | 0.098 | -0.061 to +0.267 no clear leader | needs 4 more dates and 277 more props |
Log loss scores each probability against what happened; lower is better, and a negative model − market means our model was more accurate. Props count only when both the market and our model priced them. The interval resamples whole games, because props in one game are not independent: one at-bat settles a hitter's hits, singles and total bases, and nine hitters face the same pitcher. With 4 games it is wide, which is why a verdict needs 300 props over 10 dates, not just 300 props.
Weights in force
Singles84%
Doubles16%
Triples45%
Walks83%
Hits84%
Home runs17%
Runs84%
RBI84%
Strikeouts50%
Walks (pitcher)59%
Earned runs (pitcher)54%
Hits (pitcher)59%
Outs (pitcher)52%
Strikeouts (pitcher)60%
How far each published stat moves toward the market: 0% keeps the model, 100% takes the market. Fitted on the settled props above.
Data quality and gaps
high
data/market_odds.csv is missing or empty, so no full-game moneyline covers 20261012 (manual pull)
Full-game moneyline context in the team router decision profile, review_prediction_results and the deep slate diagnosis reads this file and reports unavailable for every game since. The event feed carries only inning-period markets (first 1/3/5/7), so it cannot refill it. Ask the odds source to add full-game h2h, totals and spreads.
medium
Markets priced by books but not forecast by the model: batter_first_home_run, batter_stolen_bases, pitcher_record_a_win
Stolen bases have a market and no model expectation. A SB rate from sprint speed, attempt rate and catcher pop time is a self-contained new hitter metric with a market to measure it against.
medium
One snapshot per slate (this run archived an already seen snapshot)
Pull the feed at open, mid-day and near first pitch. Line movement and closing-line value against our early number are the strongest independent checks a single price cannot give.
low
281 rows carry only an over price
One-sided rows are scaled by the market's median hold; a two-way price would remove the estimate.
info
6 players are priced by books but absent from our published lineup (both lineups confirmed: bench players)
Books post props for bench players before lineups are out. With confirmed lineups this is information; with projected lineups, rerun once they confirm.
info
MIL hitter expected runs sum to 4.70 (RBI 4.20) against a published club score of 3
Known (R-27). Anchoring hitter R and RBI to the club target was measured on 1,128 settled hitter-games and lost accuracy, so the lines are left unanchored; the market blend moves R and RBI toward the market instead.
Player audit
Passed619
Explained15
Information57
Failed0
| Player | Check | Status | Detail |
|---|---|---|---|
| Steven Kwan | market floor H | explained | market 64.7% for at least 1; 0 in the one realized game that produces the published score; the market gives 35% to exactly that |
| Steven Kwan | market floor 1B | explained | market 55.2% for at least 1; 0 in the one realized game that produces the published score; the market gives 45% to exactly that |
| Steven Kwan | market floor TB | explained | market 63.3% for at least 1; 0 in the one realized game that produces the published score; the market gives 37% to exactly that |
| Jo Adell | market floor H | explained | market 58.1% for at least 1; 0 in the one realized game that produces the published score; the market gives 42% to exactly that |
| Jo Adell | market floor TB | explained | market 55.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 45% to exactly that |
| Brayan Rocchio | market floor H | explained | market 51.5% for at least 1; 0 in the one realized game that produces the published score; the market gives 48% to exactly that |
| Brayan Rocchio | market floor HRR | explained | market 55.6% for at least 1; 0 in the one realized game that produces the published score; the market gives 44% to exactly that |
| Brayan Rocchio | market floor TB | explained | market 50.5% for at least 1; 0 in the one realized game that produces the published score; the market gives 49% to exactly that |
| Jonathan Aranda | market floor H | explained | market 63.4% for at least 1; 0 in the one realized game that produces the published score; the market gives 37% to exactly that |
| Freddie Freeman | market floor H | explained | market 61.9% for at least 1; 0 in the one realized game that produces the published score; the market gives 38% to exactly that |
| Brice Turang | market floor H | explained | market 56.6% for at least 1; 0 in the one realized game that produces the published score; the market gives 43% to exactly that |
| Brice Turang | market floor TB | explained | market 55.7% for at least 1; 0 in the one realized game that produces the published score; the market gives 44% to exactly that |
| Christian Yelich | market floor H | explained | market 57.3% for at least 1; 0 in the one realized game that produces the published score; the market gives 43% to exactly that |
| Christian Yelich | market floor TB | explained | market 56.3% for at least 1; 0 in the one realized game that produces the published score; the market gives 44% to exactly that |
| Garrett Mitchell | market floor HRR | explained | market 54.7% for at least 1; 0 in the one realized game that produces the published score; the market gives 45% to exactly that |
Every batter and starter is checked: box identities, rate line, the odds step's arithmetic and position, market floors and the play by play. Explained means the market and the single realized game differ for a reason the check names.
Reference
Book margins by market and by book
| Doubles | 6.1% |
| Pitcher strikeouts | 6.7% |
| Hits | 6.8% |
| RBI | 6.9% |
| Pitcher walks allowed | 6.9% |
| Hits + runs + RBI | 7.0% |
| Total bases | 7.1% |
| Pitcher hits allowed | 7.1% |
| Runs | 7.2% |
| Stolen bases | 7.4% |
| Walks | 7.5% |
| Singles | 7.6% |
| Pitcher earned runs | 7.7% |
| Pitcher outs | 7.8% |
| BetOnline | 6.4% |
| FanDuel | 6.7% |
| Bovada | 6.7% |
| BetMGM | 7.0% |
| DraftKings | 7.0% |
| Caesars | 7.1% |
| MyBookie | 8.0% |
| Fanatics | 8.1% |
The margin is what a book adds on top of a fair price; lower is a sharper book.