Odds intelligence 2026-10-10
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.
Prices from output/odds/20261010/snapshots/odds_20261010T203040Z_8cd614683355.csv, written 2026-10-10T20:00:18.438268+00:00.
Books: BetMGM, BetOnline, BetRivers, Bovada, DraftKings, Fanatics, FanDuel, MyBookie, Caesars.
Key takeaways
- The market expects less offense than our model: hits 0.88×, total bases 0.92×, runs 0.90×, rbi 0.83× 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: Andrew Benintendi, hits + runs + rbi over 0.5: market 48%, our model 78%.
- Settled evidence so far: 2032 props over 5 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 |
|---|---|---|---|
| Earned runs | 2 | 0.70× | 18.7% |
| Hits + runs + RBI | 15 | 0.72× | 14.2% |
| RBI | 15 | 0.83× | 4.0% |
| Strikeouts | 2 | 0.85× | 15.0% |
| Hits | 17 | 0.88× | 5.3% |
| Runs | 15 | 0.90× | 2.9% |
| Total bases | 15 | 0.92× | 3.3% |
| Singles | 15 | 0.95× | 1.7% |
| Outs | 2 | 0.96× | 6.2% |
| Walks | 17 | 0.96× | 0.1% |
| Home runs | 15 | 1.08× | -0.8% |
| Doubles | 15 | 1.12× | -1.7% |
| Triples | 2 | 4.37× | -2.5% |
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 | Sam AntonacciCHW | 61%0.85model 0.85we publish 0.86 | 8%0.09model 0.07 | 40%0.51model 0.57we publish 0.52 | 23%0.29model 0.36we publish 0.31 | 61%1.34model 1.26we publish 1.29 | 37%0.43model 0.36we publish 0.42 |
| 2 | Kyle TeelCHW | 53%0.69model 0.74we publish 0.72 | 12%0.13model 0.10 | 36%0.45model 0.54we publish 0.46 | 23%0.30model 0.49we publish 0.34 | 52%1.11model 1.23 | 42%0.51model 0.44we publish 0.50 |
| 3 | Miguel VargasCHW | 57%0.77model 0.84we publish 0.80 | 15%0.16model 0.16 | 40%0.51model 0.72we publish 0.55 | 30%0.42model 0.52we publish 0.45 | 57%1.34model 1.47we publish 1.45 | 57%0.76model 0.56we publish 0.72 |
| 4 | Munetaka MurakamiCHW | 51%0.66model 0.75we publish 0.70 | 19%0.21model 0.21 | 39%0.49model 0.60we publish 0.51 | 32%0.45model 0.53we publish 0.47 | 49%1.31model 1.56we publish 1.50 | 46%0.59model 0.66we publish 0.60 |
| 5 | Andrew BenintendiCHW | 43%0.53model 0.72we publish 0.59 | 9%0.09model 0.09 | 27%0.31model 0.40we publish 0.32 | 23%0.29model 0.49we publish 0.34 | 45%0.90model 1.17we publish 1.04 | 25%0.28model 0.32we publish 0.28 |
| 6 | Tristan PetersCHW | 52%0.67model 0.79we publish 0.73 | 11%0.12model 0.08we publish 0.09 | 30%0.35model 0.37we publish 0.35 | 25%0.32model 0.39we publish 0.34 | 52%1.06model 1.25we publish 1.21 | 26%0.29model 0.31we publish 0.30 |
| 7 | Chase MeidrothCHW | 57%0.76model 0.85we publish 0.80 | 7%0.07model 0.09 | 32%0.38model 0.63we publish 0.42 | 23%0.29model 0.37we publish 0.31 | 56%1.12model 1.29we publish 1.24 | 35%0.40model 0.36we publish 0.39 |
| 8 | Colson MontgomeryCHW | 39%0.46model 0.61we publish 0.53 | 14%0.15model 0.13 | 30%0.35model 0.41we publish 0.36 | 24%0.31model 0.41we publish 0.33 | 40%0.91model 1.16we publish 1.08 | 28%0.32model 0.32we publish 0.32 |
| Sean BurkeCHW | –3.41model 4.22we publish 3.75 | – | – | – | – | –1.40model 1.87we publish 1.58 | |
| 1 | Steven KwanCLE | 65%0.94model 0.93we publish 0.95 | 5%0.05model 0.05 | 42%0.54model 0.57we publish 0.55 | 23%0.30model 0.28we publish 0.29 | –1.40model 1.27we publish 1.30 | 39%0.47model 0.59we publish 0.49 |
| 3 | Chase DeLauterCLE | 63%0.89model 0.94 | 13%0.13model 0.11 | 40%0.51model 0.47we publish 0.50 | 34%0.51model 0.47we publish 0.50 | –1.55model 1.49we publish 1.50 | 39%0.48model 0.46we publish 0.47 |
| 4 | Jo AdellCLE | 59%0.80model 0.88we publish 0.83 | 14%0.15model 0.13 | 38%0.48model 0.41we publish 0.47 | 35%0.52model 0.56we publish 0.53 | 58%1.30model 1.45we publish 1.42 | 33%0.39model 0.25we publish 0.36 |
| 5 | Nathaniel LoweCLE | 54%0.71model 0.79we publish 0.76 | 13%0.13model 0.12 | 34%0.41model 0.28we publish 0.38 | 28%0.38model 0.49we publish 0.40 | 55%1.24model 1.34we publish 1.32 | 31%0.36model 0.38we publish 0.36 |
| 6 | Travis BazzanaCLE | 55%0.72model 0.77we publish 0.76 | 9%0.09model 0.10 | 36%0.44model 0.48we publish 0.45 | 27%0.37model 0.39we publish 0.37 | 56%1.22model 1.26we publish 1.25 | 33%0.38model 0.43we publish 0.39 |
| 7 | Patrick BaileyCLE | 52%0.67model 0.76we publish 0.72 | 10%0.10model 0.11 | 33%0.39model 0.36we publish 0.39 | 25%0.33model 0.41we publish 0.35 | 51%1.07model 1.25we publish 1.21 | 29%0.33model 0.32 |
| 9 | Brayan RocchioCLE | 54%0.71model 0.74we publish 0.73 | 9%0.09model 0.08 | 33%0.40model 0.47we publish 0.42 | 26%0.34model 0.38we publish 0.35 | 54%1.08model 1.15 | 27%0.31model 0.27we publish 0.30 |
| Gavin WilliamsCLE | –3.26model 3.73we publish 3.46 | – | – | – | – | –2.08model 2.24we publish 2.14 |
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 |
|---|---|---|---|---|---|---|
| Andrew Benintendi | Hits + runs + RBI over 0.5 | 48% | 78% | 30% | 1.61 → 0.72 | pass |
| Colson Montgomery | Hits + runs + RBI over 0.5 | 48% | 71% | 23% | 1.43 → 0.78 | pass |
| Kyle Teel | Hits + runs + RBI over 0.5 | 58% | 81% | 22% | 1.77 → 0.97 | pass |
| Chase Meidroth | Hits + runs + RBI over 0.5 | 62% | 83% | 21% | 1.85 → 1.03 | pass |
| Munetaka Murakami | Hits + runs + RBI over 0.5 | 57% | 78% | 20% | 1.87 → 1.08 | pass |
| Tristan Peters | Hits + runs + RBI over 0.5 | 57% | 77% | 20% | 1.55 → 0.92 | pass |
| Gavin Williams | Pitcher earned runs over 1.5 | 38% | 58% | 20% | 1.93 → 1.32 | pass |
| Sean Burke | Pitcher strikeouts over 3.5 | 55% | 75% | 19% | 5.09 → 3.94 | pass |
| Brayan Rocchio | Hits + runs + RBI over 0.5 | 59% | 78% | 19% | 1.60 → 0.97 | pass |
| Travis Bazzana | Hits + runs + RBI over 0.5 | 59% | 78% | 19% | 1.64 → 0.99 | pass |
| Sean Burke | Pitcher earned runs over 1.5 | 47% | 64% | 18% | 2.19 → 1.57 | pass |
| Patrick Bailey | Hits + runs + RBI over 0.5 | 58% | 75% | 17% | 1.53 → 0.99 | pass |
| Sean Burke | Pitcher hits allowed over 3.5 | 44% | 61% | 16% | 4.22 → 3.41 | pass |
| Nathaniel Lowe | Hits + runs + RBI over 0.5 | 60% | 76% | 15% | 1.56 → 1.04 | pass |
| Chase Meidroth | Runs over 0.5 | 32% | 47% | 15% | 0.63 → 0.38 | 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
No book is two points or more better than the others.
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 | 174 | 104 | 11 | 5 | 0.330 | 0.322 | -0.008 | -0.020 to +0.002 no clear leader | needs 5 more dates and 126 more props |
| Hits | 181 | 104 | 11 | 5 | 0.657 | 0.661 | 0.004 | -0.034 to +0.039 no clear leader | needs 5 more dates and 119 more props |
| Hits + runs + RBI | 196 | 105 | 11 | 5 | 0.699 | 0.765 | 0.066 | -0.006 to +0.135 no clear leader | needs 5 more dates and 104 more props |
| Home runs | 209 | 104 | 11 | 5 | 0.304 | 0.295 | -0.009 | -0.022 to +0.003 no clear leader | needs 5 more dates and 91 more props |
| RBI | 174 | 104 | 11 | 5 | 0.604 | 0.614 | 0.010 | -0.013 to +0.028 no clear leader | needs 5 more dates and 126 more props |
| Runs | 174 | 104 | 11 | 5 | 0.640 | 0.654 | 0.014 | -0.015 to +0.037 no clear leader | needs 5 more dates and 126 more props |
| Singles | 174 | 104 | 11 | 5 | 0.680 | 0.689 | 0.009 | -0.018 to +0.037 no clear leader | needs 5 more dates and 126 more props |
| Stolen bases | 158 | 97 | 11 | 5 | 0.284 | 0.284 | 0.000 | -0.025 to +0.031 no clear leader | needs 5 more dates and 142 more props |
| Total bases | 191 | 103 | 11 | 5 | 0.664 | 0.659 | -0.005 | -0.039 to +0.026 no clear leader | needs 5 more dates and 109 more props |
| Triples | 8 | 8 | 8 | 5 | 0.043 | 0.013 | -0.029 | -0.032 to -0.026 model ahead | needs 5 more dates and 292 more props |
| Walks | 168 | 102 | 11 | 5 | 0.598 | 0.615 | 0.018 | +0.003 to +0.032 market ahead | needs 5 more dates and 132 more props |
| Pitcher earned runs | 21 | 17 | 10 | 4 | 0.674 | 0.710 | 0.036 | -0.096 to +0.184 no clear leader | needs 6 more dates and 279 more props |
| Pitcher hits allowed | 26 | 17 | 10 | 4 | 0.672 | 0.674 | 0.002 | -0.131 to +0.174 no clear leader | needs 6 more dates and 274 more props |
| Pitcher outs | 37 | 17 | 10 | 4 | 0.668 | 0.839 | 0.171 | +0.005 to +0.348 market ahead | needs 6 more dates and 263 more props |
| Pitcher strikeouts | 29 | 17 | 10 | 4 | 0.643 | 0.683 | 0.040 | -0.064 to +0.186 no clear leader | needs 6 more dates and 271 more props |
| Pitcher walks allowed | 19 | 16 | 10 | 4 | 0.606 | 0.676 | 0.069 | -0.105 to +0.273 no clear leader | needs 6 more dates and 281 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
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
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.
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.
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.
One-sided rows are scaled by the market's median hold; a two-way price would remove the estimate.
Books post props for bench players before lineups are out. With confirmed lineups this is information; with projected lineups, rerun once they confirm.
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
| Player | Check | Status | Detail |
|---|---|---|---|
| Kyle Teel | market floor H | explained | market 52.8% for at least 1; 0 in the one realized game that produces the published score; the market gives 47% to exactly that |
| Kyle Teel | market floor HRR | explained | market 58.3% for at least 1; 0 in the one realized game that produces the published score; the market gives 42% to exactly that |
| Kyle Teel | market floor TB | explained | market 51.8% for at least 1; 0 in the one realized game that produces the published score; the market gives 48% to exactly that |
| Miguel Vargas | 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 |
| Miguel Vargas | market floor TB | explained | market 56.7% for at least 1; 0 in the one realized game that produces the published score; the market gives 43% to exactly that |
| Travis Bazzana | market floor H | 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 |
| Travis Bazzana | market floor HRR | explained | market 59.4% for at least 1; 0 in the one realized game that produces the published score; the market gives 41% to exactly that |
| Travis Bazzana | market floor TB | explained | market 56.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 44% 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 | 6.2% |
| Pitcher strikeouts | 6.5% |
| Pitcher walks allowed | 6.6% |
| RBI | 6.8% |
| Hits | 6.8% |
| Hits + runs + RBI | 6.9% |
| Total bases | 7.0% |
| Pitcher hits allowed | 7.1% |
| Pitcher earned runs | 7.5% |
| Runs | 7.5% |
| Singles | 7.5% |
| Stolen bases | 7.5% |
| Walks | 7.7% |
| Pitcher outs | 7.7% |
| FanDuel | 6.0% |
| BetOnline | 6.4% |
| Bovada | 6.6% |
| DraftKings | 7.0% |
| BetMGM | 7.1% |
| Caesars | 7.2% |
| MyBookie | 8.0% |
| Fanatics | 8.3% |
The margin is what a book adds on top of a fair price; lower is a sharper book.