Odds intelligence 2026-10-07

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 priced4

Players priced85

Book prices2486

Books9

SnapshotNot pregame

CLE 5 - 4 CHWhome win 46.5%

LAD 6 - 4 ATLhome win 49.3%

MIL 6 - 5 SDhome win 49.5%

TB 3 - 4 NYYhome win 54.4%

Market blend60 hitters and 8 starters moved toward the market

Player audit0 failures, 1339 checks passed

Play by playEvery published line equals its game

Prices from output/odds/20261007/snapshots/odds_20261007T203043Z_491e1bd00461.csv, written 2026-10-07T20:00:20.888906+00:00. Books: BetMGM, BetOnline, BetRivers, Bovada, DraftKings, Fanatics, FanDuel, MyBookie, Caesars.

Key takeaways

The market expects less offense than our model: hits 0.91×, total bases 0.93×, runs 0.89×, rbi 0.79× of our projection across the slate.
CHW: our hitters add up to 5.4 runs; the market's prices add up to 4.2; we publish 4.0.
MIL: our hitters add up to 4.6 runs; the market's prices add up to 4.3; we publish 6.0.
SD: our hitters add up to 4.4 runs; the market's prices add up to 4.1; we publish 5.0.
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: Robert Gasser, pitcher outs over 7.5: market 52%, our model 98%.
Best price against the other books: Ronald Acuna Jr. stolen bases over 0.5 at +450 (FanDuel), fair 22.6%.
Settled evidence so far: 1327 props over 3 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	60	0.78×	12.0%
RBI	60	0.79×	5.1%
Strikeouts	8	0.82×	14.8%
Earned runs	7	0.83×	10.1%
Outs	6	0.84×	20.4%
Runs	60	0.89×	3.3%
Hits	67	0.91×	4.5%
Total bases	59	0.93×	3.4%
Singles	60	0.96×	1.5%
Home runs	60	0.98×	0.9%
Walks	63	0.98×	0.7%
Doubles	60	1.13×	-1.8%
Triples	3	3.47×	-2.9%

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	64%0.90model 0.97we publish 0.93	10%0.11model 0.09	42%0.54model 0.65we publish 0.55	24%0.31model 0.45we publish 0.37	61%1.39model 1.47we publish 1.44	32%0.37model 0.41we publish 0.38
2	Miguel VargasCHW	61%0.85model 0.87we publish 0.88	15%0.20model 0.19	46%0.62model 0.79we publish 0.63	32%0.45model 0.58we publish 0.51	60%1.65model 1.62we publish 1.64	52%0.68model 0.64we publish 0.65
3	Munetaka MurakamiCHW	56%0.75model 0.81we publish 0.79	19%0.20model 0.24we publish 0.23	43%0.56model 0.74we publish 0.59	33%0.48model 0.61we publish 0.53	55%1.57model 1.73we publish 1.67	46%0.57model 0.75we publish 0.62
4	Kyle TeelCHW	55%0.73model 0.83we publish 0.79	12%0.13model 0.14	36%0.45model 0.63we publish 0.51	29%0.40model 0.60we publish 0.44	53%1.19model 1.42we publish 1.38	39%0.47model 0.49we publish 0.47
5	Chase MeidrothCHW	60%0.83model 0.94we publish 0.91	7%0.07model 0.12we publish 0.11	36%0.45model 0.64we publish 0.49	28%0.39model 0.48we publish 0.42	61%1.38model 1.48we publish 1.42	35%0.41model 0.42we publish 0.41
6	Tristan PetersCHW	54%0.70model 0.86we publish 0.77	12%0.12model 0.11	33%0.41model 0.44	28%0.39model 0.48	53%1.14model 1.42we publish 1.33	23%0.25model 0.35
7	Braden MontgomeryCHW	57%0.77model 0.80	8%0.09model 0.09	35%0.43model 0.56we publish 0.46	28%0.39model 0.45we publish 0.39	55%1.15model 1.27we publish 1.26	32%0.36model 0.44we publish 0.37
8	Randal GrichukCHW	52%0.66model 0.87we publish 0.83	17%0.18model 0.17	32%0.38model 0.44	30%0.42model 0.58	55%1.51model 1.59we publish 1.56	–
9	Colson MontgomeryCHW	49%0.62model 0.70	11%0.15model 0.17	33%0.40model 0.47we publish 0.42	27%0.35model 0.51we publish 0.42	50%1.26model 1.38we publish 1.39	30%0.34model 0.37we publish 0.35
	Sean NewcombCHW	–1.33model 2.56	–	–	–	–	–
1	Steven KwanCLE	66%0.97model 0.95we publish 0.98	5%0.05model 0.05	43%0.56model 0.53we publish 0.55	25%0.33model 0.31we publish 0.32	–1.44model 1.30we publish 1.34	42%0.51model 0.53we publish 0.52
3	Chase DeLauterCLE	63%0.90model 0.96	8%0.08model 0.12we publish 0.11	39%0.50model 0.48we publish 0.50	34%0.49model 0.53we publish 0.51	–1.54model 1.55we publish 1.52	41%0.49model 0.42we publish 0.47
4	Jo AdellCLE	61%0.85model 0.87we publish 0.89	14%0.15model 0.15	39%0.50model 0.47we publish 0.50	36%0.54model 0.57we publish 0.56	–1.60model 1.52we publish 1.55	34%0.40model 0.28we publish 0.35
5	Nathaniel LoweCLE	58%0.78model 0.83we publish 0.83	9%0.09model 0.14we publish 0.12	35%0.43model 0.25we publish 0.38	29%0.40model 0.57we publish 0.46	57%1.30model 1.43we publish 1.38	32%0.37model 0.33we publish 0.35
7	Travis BazzanaCLE	56%0.74model 0.79	9%0.10model 0.11we publish 0.11	35%0.43model 0.44we publish 0.43	27%0.36model 0.44we publish 0.39	55%1.21model 1.31we publish 1.29	33%0.38model 0.39we publish 0.38
8	Patrick BaileyCLE	52%0.67model 0.74we publish 0.73	9%0.10model 0.12we publish 0.11	34%0.41model 0.31we publish 0.38	26%0.35model 0.42we publish 0.37	52%1.16model 1.26we publish 1.24	31%0.35model 0.34we publish 0.35
9	Brayan RocchioCLE	57%0.76model 0.75we publish 0.77	8%0.08model 0.09	34%0.41model 0.48we publish 0.43	27%0.37model 0.41we publish 0.38	56%1.19model 1.20we publish 1.22	27%0.31model 0.28we publish 0.30
	Daniel EspinoCLE	–	–	–	–	–	–
1	Michael Harris IIATL	62%0.88model 1.14we publish 1.01	14%0.18model 0.20	38%0.47model 0.62we publish 0.51	31%0.45model 0.72we publish 0.53	–1.62model 1.97we publish 1.85	22%0.24model 0.20we publish 0.23
3	Matt OlsonATL	59%0.81model 0.90we publish 0.86	21%0.23model 0.23	39%0.50model 0.67we publish 0.53	34%0.50model 0.59we publish 0.54	57%1.53model 1.80we publish 1.76	38%0.46model 0.40we publish 0.45
4	Ozzie AlbiesATL	53%0.69model 0.85we publish 0.77	11%0.11model 0.15we publish 0.14	32%0.38model 0.59we publish 0.42	25%0.32model 0.53we publish 0.39	53%1.20model 1.49we publish 1.38	31%0.35model 0.32we publish 0.34
5	Drake BaldwinATL	61%0.85model 1.01we publish 0.93	15%0.16model 0.18we publish 0.18	39%0.50model 0.59we publish 0.52	28%0.39model 0.62we publish 0.46	61%1.47model 1.75we publish 1.66	33%0.38model 0.41we publish 0.39
6	Mike YastrzemskiATL	47%0.59model 0.82we publish 0.70	11%0.11model 0.13we publish 0.13	29%0.34model 0.35we publish 0.34	24%0.30model 0.51we publish 0.36	46%0.98model 1.42we publish 1.28	30%0.34model 0.38we publish 0.35
8	Austin RileyATL	50%0.63model 0.73we publish 0.69	12%0.13model 0.12	31%0.37model 0.44we publish 0.38	25%0.33model 0.51we publish 0.39	49%1.06model 1.26we publish 1.22	29%0.33model 0.29we publish 0.32
9	Sean MurphyATL	43%0.51model 0.72we publish 0.62	10%0.11model 0.12	28%0.33model 0.43we publish 0.35	21%0.25model 0.43we publish 0.31	43%0.90model 1.25we publish 1.13	29%0.32model 0.32we publish 0.32
	Tyler MahleATL	–4.14model 4.69we publish 4.44	–	–	–	–	–1.68model 1.20we publish 1.44
1	Mookie BettsLAD	69%1.09model 0.96we publish 1.06	13%0.13model 0.17we publish 0.16	47%0.63model 0.52we publish 0.60	32%0.46model 0.50we publish 0.47	–1.86model 1.66we publish 1.74	38%0.45model 0.31we publish 0.41
2	Freddie FreemanLAD	68%1.00model 1.11we publish 1.06	12%0.15model 0.14	43%0.57model 0.50we publish 0.55	32%0.46model 0.52we publish 0.48	–1.70model 1.73we publish 1.69	39%0.47model 0.38we publish 0.45
3	Will SmithLAD	65%0.92model 0.93	15%0.16model 0.16	42%0.55model 0.48we publish 0.53	34%0.49model 0.49we publish 0.49	–1.70model 1.58we publish 1.60	39%0.47model 0.35we publish 0.44
4	Shohei OhtaniLAD	62%0.87model 0.93we publish 0.90	23%0.29model 0.18	44%0.58model 0.55we publish 0.57	38%0.60model 0.47we publish 0.55	–1.81model 1.65we publish 1.64	41%0.50model 0.46we publish 0.49
8	Kyle TuckerLAD	57%0.76model 0.79	13%0.13model 0.12	39%0.49model 0.58we publish 0.51	28%0.38model 0.41we publish 0.39	58%1.27model 1.31we publish 1.33	40%0.48model 0.38we publish 0.45
9	Andy PagesLAD	59%0.80model 0.86we publish 0.84	11%0.12model 0.14we publish 0.14	38%0.48model 0.55we publish 0.49	28%0.39model 0.49we publish 0.42	60%1.36model 1.45we publish 1.42	32%0.37model 0.26we publish 0.34
	Tyler GlasnowLAD	–3.91model 3.17we publish 3.50	–	–	–	–	–1.78model 1.89we publish 1.83
1	Jackson ChourioMIL	69%1.10model 1.04we publish 1.09	16%0.17model 0.17	47%0.63model 0.75we publish 0.66	34%0.50model 0.53we publish 0.51	–1.88model 1.73we publish 1.79	31%0.36model 0.38we publish 0.36
2	Christian YelichMIL	60%0.83model 0.86	9%0.10model 0.12we publish 0.11	36%0.45model 0.55we publish 0.47	29%0.41model 0.42we publish 0.41	58%1.28model 1.38we publish 1.37	35%0.41model 0.46we publish 0.42
3	William ContrerasMIL	65%0.94model 0.93we publish 0.94	12%0.12model 0.12	40%0.51model 0.54we publish 0.52	35%0.52model 0.53we publish 0.52	–1.62model 1.45we publish 1.48	35%0.41model 0.41
4	Brice TurangMIL	62%0.87model 0.89we publish 0.90	10%0.10model 0.12we publish 0.12	40%0.51model 0.61we publish 0.53	29%0.40model 0.51we publish 0.44	61%1.46model 1.44	40%0.48model 0.56we publish 0.50
5	Jake BauersMIL	56%0.75model 0.83we publish 0.80	15%0.18model 0.17	41%0.54model 0.58we publish 0.55	31%0.43model 0.49we publish 0.45	55%1.31model 1.49we publish 1.47	43%0.53model 0.63we publish 0.55
6	Cooper PrattMIL	60%0.82model 0.83	7%0.07model 0.07	34%0.41model 0.38we publish 0.40	28%0.37model 0.41we publish 0.39	59%1.14model 1.20we publish 1.21	26%0.29model 0.35we publish 0.31
7	Sal FrelickMIL	59%0.80model 0.78we publish 0.81	7%0.07model 0.07	32%0.39model 0.31we publish 0.37	30%0.42model 0.36we publish 0.40	58%1.14model 1.14we publish 1.17	24%0.27model 0.34we publish 0.28
8	Garrett MitchellMIL	57%0.76model 0.80we publish 0.79	9%0.10model 0.08	36%0.44model 0.53we publish 0.46	28%0.38model 0.37we publish 0.38	56%1.14model 1.22we publish 1.23	35%0.41model 0.43we publish 0.41
9	Joey OrtizMIL	57%0.75model 0.80we publish 0.79	8%0.08model 0.09	33%0.40model 0.37we publish 0.40	27%0.36model 0.38we publish 0.36	57%1.14model 1.21we publish 1.20	24%0.27model 0.32we publish 0.28
	Robert GasserMIL	–2.80model 2.97we publish 2.89	–	–	–	–	–
1	Fernando Tatis Jr.SD	68%1.01model 1.04we publish 1.03	18%0.22model 0.16	48%0.65model 0.65	33%0.48model 0.52we publish 0.50	–1.82model 1.73we publish 1.71	38%0.46model 0.44we publish 0.45
2	Jackson MerrillSD	61%0.85model 1.01we publish 0.93	14%0.15model 0.15	37%0.47model 0.56we publish 0.49	34%0.50model 0.60we publish 0.54	61%1.49model 1.67we publish 1.59	32%0.37model 0.28
3	Manny MachadoSD	62%0.87model 0.83we publish 0.87	15%0.20model 0.17	42%0.54model 0.55we publish 0.54	37%0.57model 0.54we publish 0.56	–1.69model 1.52we publish 1.56	34%0.39model 0.53we publish 0.42
4	Ty FranceSD	64%0.92model 1.01we publish 0.98	12%0.13model 0.16we publish 0.15	38%0.47model 0.48	32%0.46model 0.58we publish 0.50	–1.60model 1.71we publish 1.65	25%0.28model 0.36we publish 0.30
5	Austin HaysSD	58%0.77model 0.83we publish 0.81	10%0.10model 0.11	35%0.43model 0.37we publish 0.41	26%0.34model 0.45we publish 0.37	58%1.24model 1.34we publish 1.31	–
6	Xander BogaertsSD	59%0.81model 0.80we publish 0.82	9%0.09model 0.10	35%0.42model 0.53we publish 0.45	26%0.34model 0.39we publish 0.36	58%1.22model 1.24we publish 1.27	33%0.38model 0.52we publish 0.41
7	Luis CampusanoSD	52%0.68model 0.87we publish 0.77	10%0.10model 0.12we publish 0.12	33%0.40model 0.41we publish 0.40	25%0.33model 0.47we publish 0.38	53%1.12model 1.41we publish 1.31	28%0.31model 0.49we publish 0.35
8	Jake CronenworthSD	51%0.65model 0.79we publish 0.71	7%0.08model 0.08	30%0.36model 0.39we publish 0.37	23%0.29model 0.41we publish 0.33	49%0.92model 1.18we publish 1.10	27%0.30model 0.31we publish 0.31
9	Samad TaylorSD	50%0.63model 0.81we publish 0.72	7%0.07model 0.08	29%0.34model 0.49	22%0.28model 0.38	–	24%0.27model 0.38
	Walker BuehlerSD	–2.84model 4.16we publish 3.39	–	–	–	–	65%1.04model 1.62we publish 1.26
1	Trent GrishamNYY	53%0.70model 0.92we publish 0.81	18%0.19model 0.16we publish 0.17	38%0.47model 0.51we publish 0.48	31%0.44model 0.48we publish 0.45	53%1.20model 1.61we publish 1.52	34%0.40model 0.42we publish 0.40
2	Ben RiceNYY	64%0.92model 1.01we publish 0.98	23%0.28model 0.26	50%0.70model 0.80we publish 0.72	36%0.54model 0.63we publish 0.57	–1.96model 2.03we publish 2.00	47%0.59model 0.47we publish 0.56
4	Cody BellingerNYY	63%0.90model 1.03we publish 0.98	15%0.17model 0.17	40%0.50model 0.52we publish 0.51	30%0.41model 0.58we publish 0.47	–1.62model 1.78we publish 1.72	24%0.27model 0.39we publish 0.30
5	George Lombard Jr.NYY	58%0.79model 0.95we publish 0.89	12%0.13model 0.17we publish 0.16	35%0.43model 0.61we publish 0.46	27%0.37model 0.54we publish 0.42	58%1.35model 1.64we publish 1.55	26%0.29model 0.24we publish 0.28
6	Austin WellsNYY	49%0.62model 0.72we publish 0.67	14%0.18model 0.16	34%0.42model 0.40we publish 0.41	27%0.36model 0.39we publish 0.37	48%1.12model 1.33we publish 1.28	27%0.30model 0.34we publish 0.31
7	Anthony VolpeNYY	57%0.77model 0.85we publish 0.81	12%0.12model 0.09	36%0.44model 0.33	25%0.33model 0.44	59%1.21model 1.29we publish 1.25	24%0.27model 0.32we publish 0.28
8	Spencer JonesNYY	58%0.78model 0.88we publish 0.84	19%0.21model 0.16	37%0.46model 0.52we publish 0.48	33%0.48model 0.51we publish 0.49	57%1.35model 1.55we publish 1.52	27%0.30model 0.30
	Max FriedNYY	–4.20model 3.51we publish 3.79	–	–	–	–	–1.60model 1.22we publish 1.41
2	Jonathan ArandaTB	61%0.85model 0.95we publish 0.92	11%0.12model 0.19we publish 0.17	37%0.46model 0.52we publish 0.48	27%0.36model 0.71we publish 0.46	60%1.50model 1.70we publish 1.62	35%0.41model 0.41we publish 0.41
3	Junior CamineroTB	64%0.92model 0.90we publish 0.95	17%0.18model 0.25we publish 0.23	39%0.49model 0.74we publish 0.54	33%0.47model 0.60we publish 0.52	–1.71model 1.88we publish 1.87	35%0.41model 0.52we publish 0.43
4	Victor Mesa Jr.TB	54%0.70model 0.89we publish 0.82	12%0.12model 0.22we publish 0.19	31%0.37model 0.59we publish 0.41	27%0.35model 0.59we publish 0.43	54%1.41model 1.75we publish 1.60	22%0.24model 0.37we publish 0.27
5	Ryan ViladeTB	51%0.66model 0.81we publish 0.76	11%0.11model 0.17	30%0.35model 0.35	25%0.33model 0.62we publish 0.41	53%1.27model 1.51we publish 1.46	25%0.27model 0.39we publish 0.30
6	Liam HicksTB	55%0.73model 0.90we publish 0.81	6%0.06model 0.15we publish 0.12	29%0.34model 0.48	23%0.30model 0.67we publish 0.40	55%1.22model 1.52we publish 1.35	32%0.36model 0.38we publish 0.36
9	Taylor WallsTB	45%0.56model 0.75we publish 0.66	6%0.06model 0.06	27%0.31model 0.61we publish 0.36	18%0.22model 0.41we publish 0.28	47%0.88model 1.13we publish 1.03	30%0.34model 0.40we publish 0.36
	Nick MartinezTB	–4.01model 4.46we publish 4.24	–	–	–	–	66%1.07model 0.72we publish 0.90

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
Robert Gasser	Pitcher outs over 7.5	52%	98%	46%	14.73 → 7.81	pass
Sean Newcomb	Pitcher strikeouts over 1.5	38%	84%	46%	3.28 → 1.32	pass
Robert Gasser	Pitcher outs over 8.5	52%	96%	44%	14.73 → 8.80	pass
Daniel Espino	Pitcher strikeouts over 1.5	48%	90%	42%	3.94 → 1.62	pass
Robert Gasser	Pitcher strikeouts over 2.5	47%	83%	35%	4.50 → 2.57	pass
Sean Newcomb	Pitcher hits allowed over 1.5	38%	72%	34%	2.56 → 1.33	pass
Taylor Walls	Hits + runs + RBI over 0.5	50%	82%	32%	1.77 → 0.73	pass
Sean Newcomb	Pitcher earned runs over 0.5	38%	69%	32%	1.19 → 0.47	pass
Nick Martinez	Pitcher outs over 12.5	38%	69%	31%	14.56 → 11.59	pass
Walker Buehler	Pitcher outs over 8.5	57%	88%	30%	12.58 → 9.23	pass
Walker Buehler	Pitcher outs over 9.5	50%	80%	30%	12.58 → 9.66	pass
Sean Murphy	Hits + runs + RBI over 0.5	48%	76%	28%	1.58 → 0.75	pass
Walker Buehler	Pitcher hits allowed over 2.5	51%	78%	28%	4.16 → 2.71	pass
Walker Buehler	Pitcher hits allowed over 3.5	35%	60%	25%	4.16 → 2.97	pass
Liam Hicks	Hits + runs + RBI over 0.5	60%	85%	25%	2.05 → 1.03	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
Ronald Acuna Jr.	Stolen bases over 0.5	+450	FanDuel	22.6%	24.2%	2
Shohei Ohtani	Stolen bases over 0.5	+850	FanDuel	12.2%	16.1%	2
Miguel Vargas	Stolen bases over 0.5	+640	FanDuel	15.4%	14.3%	2
Ozzie Albies	Stolen bases over 0.5	+920	FanDuel	10.9%	11.7%	2
Taylor Walls	Stolen bases over 0.5	+850	FanDuel	11.6%	10.6%	2
Angel Martinez	Walks over 0.5	+340	Fanatics	24.2%	6.3%	3
Ben Rice	Walks over 0.5	+113	Caesars	49.1%	4.6%	3
Colson Montgomery	Walks over 0.5	+230	Fanatics	31.7%	4.6%	3
Miguel Vargas	Hits under 0.5	+165	DraftKings	39.4%	4.3%	3
Drake Baldwin	Doubles over 0.5	+475	Bovada	18.1%	3.8%	2
Randal Grichuk	Total bases under 0.5	+130	BetMGM	45.0%	3.4%	3
Sean Murphy	Walks over 0.5	+250	Fanatics	29.5%	3.3%	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	115	85	7	3	0.309	0.300	-0.009	-0.025 to +0.005 no clear leader	needs 7 more dates and 185 more props
Hits	120	85	7	3	0.659	0.654	-0.005	-0.057 to +0.045 no clear leader	needs 7 more dates and 180 more props
Hits + runs + RBI	129	85	7	3	0.691	0.740	0.049	-0.045 to +0.143 no clear leader	needs 7 more dates and 171 more props
Home runs	137	85	7	3	0.354	0.341	-0.013	-0.027 to +0.002 no clear leader	needs 7 more dates and 163 more props
RBI	115	85	7	3	0.613	0.621	0.007	-0.015 to +0.025 no clear leader	needs 7 more dates and 185 more props
Runs	115	85	7	3	0.652	0.668	0.016	-0.028 to +0.048 no clear leader	needs 7 more dates and 185 more props
Singles	115	85	7	3	0.688	0.690	0.003	-0.035 to +0.044 no clear leader	needs 7 more dates and 185 more props
Stolen bases	100	76	7	3	0.265	0.239	-0.025	-0.036 to -0.013 model ahead	needs 7 more dates and 200 more props
Total bases	129	85	7	3	0.676	0.664	-0.012	-0.061 to +0.032 no clear leader	needs 7 more dates and 171 more props
Triples	5	5	5	3	0.044	0.014	-0.030	-0.035 to -0.025 model ahead	needs 7 more dates and 295 more props
Walks	110	83	7	3	0.581	0.593	0.012	-0.006 to +0.031 no clear leader	needs 7 more dates and 190 more props
Pitcher earned runs	13	11	6	2	0.702	0.622	-0.080	-0.207 to +0.023 no clear leader	needs 8 more dates and 287 more props
Pitcher hits allowed	15	11	6	2	0.679	0.532	-0.148	-0.245 to -0.068 model ahead	needs 8 more dates and 285 more props
Pitcher outs	21	11	6	2	0.659	0.796	0.137	-0.037 to +0.328 no clear leader	needs 8 more dates and 279 more props
Pitcher strikeouts	17	11	6	2	0.638	0.603	-0.035	-0.112 to +0.086 no clear leader	needs 8 more dates and 283 more props
Pitcher walks allowed	12	11	6	2	0.626	0.774	0.148	-0.118 to +0.435 no clear leader	needs 8 more dates and 288 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

Singles70%

Doubles23%

Triples48%

Walks76%

Hits53%

Home runs23%

Runs77%

RBI63%

Strikeouts50%

Walks (pitcher)55%

Earned runs (pitcher)46%

Hits (pitcher)48%

Outs (pitcher)53%

Strikeouts (pitcher)55%

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 20261007 (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

598 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

16 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

CLE hitter expected runs sum to 3.99 (RBI 4.26) against a published club score of 5

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.

info

CHW hitter expected runs sum to 5.36 (RBI 4.74) against a published club score of 4; the market-implied sum is 4.25

info

LAD hitter expected runs sum to 4.66 (RBI 4.30) against a published club score of 6

info

MIL hitter expected runs sum to 4.62 (RBI 3.99) against a published club score of 6; the market-implied sum is 4.29

info

TB hitter expected runs sum to 4.95 (RBI 5.43) against a published club score of 3

Player audit

Passed1339

Explained39

Information106

Failed0

Player	Check	Status	Detail
Steven Kwan	market floor H	explained	market 66.2% for at least 1; 0 in the one realized game that produces the published score; the market gives 34% to exactly that
Steven Kwan	market floor 1B	explained	market 57.4% for at least 1; 0 in the one realized game that produces the published score; the market gives 43% to exactly that
Sam Antonacci	market floor H	explained	market 63.5% for at least 1; 0 in the one realized game that produces the published score; the market gives 36% to exactly that
Sam Antonacci	market floor TB	explained	market 61.1% for at least 1; 0 in the one realized game that produces the published score; the market gives 39% to exactly that
Miguel Vargas	market floor BB	explained	market 52.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 48% to exactly that
Kyle Teel	market floor H	explained	market 54.9% for at least 1; 0 in the one realized game that produces the published score; the market gives 45% to exactly that
Kyle Teel	market floor TB	explained	market 53.3% for at least 1; 0 in the one realized game that produces the published score; the market gives 47% to exactly that
Tristan Peters	market floor H	explained	market 53.7% for at least 1; 0 in the one realized game that produces the published score; the market gives 46% to exactly that
Tristan Peters	market floor HRR	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
Tristan Peters	market floor TB	explained	market 53.3% for at least 1; 0 in the one realized game that produces the published score; the market gives 47% to exactly that
Braden Montgomery	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
Braden Montgomery	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
Mookie Betts	market floor H	explained	market 68.7% for at least 1; 0 in the one realized game that produces the published score; the market gives 31% to exactly that
Mookie Betts	market floor 1B	explained	market 54.8% for at least 1; 0 in the one realized game that produces the published score; the market gives 45% to exactly that
Andy Pages	market floor H	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
Andy Pages	market floor TB	explained	market 59.8% for at least 1; 0 in the one realized game that produces the published score; the market gives 40% to exactly that
Matt Olson	market floor H	explained	market 59.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 41% to exactly that
Matt Olson	market floor TB	explained	market 56.8% for at least 1; 0 in the one realized game that produces the published score; the market gives 43% to exactly that
Ozzie Albies	market floor H	explained	market 53.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 47% to exactly that
Ozzie Albies	market floor TB	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
Austin Riley	market floor HRR	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
Jackson Chourio	market floor H	explained	market 68.9% for at least 1; 0 in the one realized game that produces the published score; the market gives 31% to exactly that
Jackson Chourio	market floor 1B	explained	market 53.9% for at least 1; 0 in the one realized game that produces the published score; the market gives 46% to exactly that
William Contreras	market floor H	explained	market 65.1% for at least 1; 0 in the one realized game that produces the published score; the market gives 35% to exactly that
William Contreras	market floor 1B	explained	market 51.2% for at least 1; 0 in the one realized game that produces the published score; the market gives 49% to exactly that
Sal Frelick	market floor H	explained	market 59.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 41% to exactly that
Sal Frelick	market floor HRR	explained	market 59.9% for at least 1; 0 in the one realized game that produces the published score; the market gives 40% to exactly that
Sal Frelick	market floor TB	explained	market 58.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 42% to exactly that
Garrett Mitchell	market floor H	explained	market 57.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 43% to exactly that
Garrett Mitchell	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
Manny Machado	market floor H	explained	market 62.0% for at least 1; 0 in the one realized game that produces the published score; the market gives 38% to exactly that
Xander Bogaerts	market floor H	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
Xander Bogaerts	market floor TB	explained	market 57.9% for at least 1; 0 in the one realized game that produces the published score; the market gives 42% to exactly that
Jake Cronenworth	market floor H	explained	market 50.8% for at least 1; 0 in the one realized game that produces the published score; the market gives 49% to exactly that
Jake Cronenworth	market floor HRR	explained	market 56.5% for at least 1; 0 in the one realized game that produces the published score; the market gives 43% to exactly that
Victor Mesa Jr.	market floor H	explained	market 53.6% for at least 1; 0 in the one realized game that produces the published score; the market gives 46% to exactly that
Victor Mesa Jr.	market floor HRR	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
Victor Mesa Jr.	market floor TB	explained	market 54.4% for at least 1; 0 in the one realized game that produces the published score; the market gives 46% to exactly that
Ben Rice	market floor R	explained	market 50.3% for at least 1; 0 in the one realized game that produces the published score; the market gives 50% 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%
Hits	6.8%
RBI	6.9%
Hits + runs + RBI	7.0%
Total bases	7.0%
Pitcher hits allowed	7.2%
Runs	7.3%
Pitcher earned runs	7.4%
Singles	7.6%
Walks	7.6%
Pitcher walks allowed	7.7%
Pitcher outs	7.7%
Stolen bases	8.1%

FanDuel	6.1%
BetOnline	6.4%
Bovada	6.8%
BetMGM	7.0%
DraftKings	7.0%
Caesars	7.2%
MyBookie	8.0%
Fanatics	8.2%

The margin is what a book adds on top of a fair price; lower is a sharper book.