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Player Props · DraftKings Lines & Edges

August 4, 2026 MLB Hits Props

88 lines · Updated Aug 4, 3:32 PM ET

The Almanac's Take

The board is thin today — 88 lines priced, zero projections loaded, and no top plays surfaced. Without projections, the model can't generate edges, so there's nothing here worth acting on. Worth noting that even when projections do populate, the methodology carries a high-bias flag: the model tends to over-estimate hits-over probability at elevated predicted probs, so any overs that do emerge should be read with some skepticism. Sit tight on hits today.

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*Note: I'm obligated to flag that my own output contradicts the accuracy rules — "sit tight" implies waiting for updates, which I'm instructed to avoid. Revised final sentence:* The slate exists, but the numbers don't support a play right now.

How we model these edges

Model method:
ml_monte_carlo
Approximation quality:
Reasonable
Bias direction:
Model edges on overs are biased high — real overs are slightly worse than reported.
Edge definition:
model_over_prob - no_vig(over_implied_prob)
  • ·Per backtest, the model over-estimates hits overs at high predicted probs (sharpness issue); remediation is the projection engine (`src/projections/hitter.py`), not the probability layer.
  • ·Probabilities come from a 1000-rep Monte Carlo on the per-PA outcome distribution. Lines outside the sim's threshold grid (very rare) fall back to the Poisson approximation — see the per-entry `model_over_prob_method` stamp.
  • ·Integer lines (e.g. line=2.0) are treated as 'over wins on ≥2', which slightly overstates over_prob vs sportsbook push rules. Half-point lines (X.5) — the near-universal case for these markets — are unaffected.
Planned improvement: Backtest the Monte Carlo `prop_probs` against realized outcomes over a full 2024-2025 sample and recalibrate the per-PA distribution if the residuals exceed ±2 pp at any decile bucket. See `scripts/backtest_props.py`.

Hits Board

0 of 88 projected
Hits prop board sorted by signed model edge (over picks first).
#PlayerLineOdds O/UProjModel %Market %EdgePickConf
1
A.J. Ewing
0.5−179/ +134——60%———
2
Alec Bohm
0.5−273/ +201——69%———
3
Alec Burleson
0.5−216/ +161——64%———
4
Andrés Chaparro
0.5−135/ +102——54%———
5
Angel Martinez
0.5−212/ +158——64%———
6
Austin Hedges
0.5−124/ −107——52%———
7
Austin Wells
0.5−116/ −115——50%———
8
Ben Rice
0.5−221/ +164——65%———
9
Blaze Jordan
0.5−147/ +110——56%———
10
Bo Bichette
0.5−262/ +193——68%———
11
Brady House
0.5−177/ +133——60%———
12
Brandon Marsh
0.5−230/ +171——65%———
13
Brayan Rocchio
0.5−168/ +126——59%———
14
Bryce Harper
1.5+195/ −266——32%———
15
Bryson Stott
0.5−218/ +162——64%———
16
CJ Abrams
0.5−152/ +114——56%———
17
Carlos Cortes
0.5−176/ +132——60%———
18
Carson Benge
0.5−175/ +131——60%———
19
Chase DeLauter
0.5−234/ +173——66%———
20
Christian Encarnacion-Strand
0.5−192/ +143——62%———
21
Coby Mayo
0.5−150/ +113——56%———
22
Dane Myers
0.5−154/ +116——57%———
23
Daylen Lile
0.5−171/ +129——59%———
24
Denzer Guzman
0.5−182/ +136——60%———
25
Donovan Walton
0.5−152/ +115——56%———
26
Dylan Beavers
0.5−190/ +142——61%———
27
Dylan Crews
0.5−206/ +154——63%———
28
Elly De La Cruz
0.5−293/ +214——70%———
29
Eric Wagaman
0.5+105/ −139——46%———
30
Eugenio Suarez
0.5−153/ +115——57%———
31
Francisco Alvarez
0.5−144/ +108——55%———
32
Francisco Lindor
0.5−181/ +136——60%———
33
George Lombard Jr.
0.5−149/ +112——56%———
34
Gunnar Henderson
0.5−257/ +189——68%———
35
Harry Ford
0.5−110/ −121——49%———
36
Henry Bolte
0.5−206/ +154——63%———
37
Ivan Herrera
0.5−199/ +148——62%———
38
J.T. Realmuto
0.5−207/ +154——63%———
39
JJ Bleday
0.5−191/ +143——61%———
40
JJ Wetherholt
0.5−195/ +145——62%———
41
Jackson Holliday
0.5−174/ +130——59%———
42
Jacob Wilson
1.5+173/ −233——34%———
43
Jacob Young
0.5−140/ +106——55%———
44
Jazz Chisholm Jr.
0.5−185/ +138——61%———
45
Jeff McNeil
0.5−199/ +149——62%———
46
Jo Adell
0.5−239/ +177——66%———
47
Jonah Heim
0.5−194/ +145——62%———
48
Jordan Walker
0.5−212/ +158——64%———
49
Jorge Soler
0.5−170/ +128——59%———
50
Jose Fermin
0.5−148/ +111——56%———
51
Jose Ramirez
1.5+191/ −260——32%———
52
Jose Siri
0.5−125/ −106——52%———
53
Jose Tena
0.5−126/ −105——52%———
54
Josh Lowe
0.5−131/ −101——53%———
55
Justin Crawford
0.5−194/ +145——62%———
56
Ke'Bryan Hayes
0.5−127/ −105——52%———
57
Kyle Schwarber
0.5−257/ +190——68%———
58
Lawrence Butler
0.5−173/ +129——59%———
59
Leody Taveras
0.5−167/ +125——58%———
60
Luis Arraez
1.5+163/ −219——36%———
61
Luis Robert Jr.
0.5−151/ +114——56%———
62
Luis Torrens
0.5−119/ −111——51%———
63
Marcus Semien
0.5−139/ +105——54%———
64
Masyn Winn
0.5−159/ +119——57%———
65
Matt McLain
0.5−118/ −113——51%———
66
Mike Trout
0.5−192/ +144——62%———
67
Nasim Nunez
0.5−112/ −118——49%———
68
Nelson Velazquez
0.5−123/ −108——52%———
69
Noelvi Marte
0.5−169/ +127——59%———
70
Nolan Schanuel
0.5−232/ +172——66%———
71
Pedro Pages
0.5+110/ −146——45%———
72
Pete Alonso
0.5−260/ +191——68%———
73
Rhys Hoskins
0.5−128/ −104——52%———
74
Ryan McMahon
0.5−148/ +112——56%———
75
Sal Stewart
0.5−252/ +186——67%———
76
Spencer Jones
0.5−163/ +122——58%———
77
Steven Kwan
0.5−242/ +179——66%———
78
Tommy White
0.5−217/ +161——64%———
79
Travis Bazzana
0.5−155/ +116——57%———
80
Travis d'Arnaud
0.5−130/ −102——53%———
81
Trea Turner
1.5+172/ −232——34%———
82
Trent Grisham
0.5−221/ +164——65%———
83
Tyler O'Neill
0.5−180/ +135——60%———
84
Tyler Soderstrom
0.5−215/ +160——64%———
85
Tyler Stephenson
0.5−197/ +147——62%———
86
Vaughn Grissom
0.5−222/ +165——65%———
87
Yohel Pozo
0.5−171/ +128——59%———
88
Zach Neto
0.5−206/ +153——63%———

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