Player Props · DraftKings Lines & Edges

August 3, 2026 MLB Strikeouts Props

13 lines · Updated Aug 3, 3:38 PM ET

The Almanac's Take

The board is thin today — 13 lines in, zero projections loaded, and no top plays surfaced. Without model probabilities to compare against the no-vig implied odds, there's no edge to report; every entry is effectively ungraded. The methodology is neutral-biased and Poisson-based, so when numbers do populate, integer lines (like a flat 7.0) will read slightly generous to overs versus how DraftKings actually grades pushes — worth keeping in mind for any whole-number strikeout totals. For now, the K board has nothing to act on.

How we model these edges

Model method:
poisson_per_game
Approximation quality:
Reasonable
Bias direction:
No systematic bias in either direction.
Edge definition:
model_over_prob - no_vig(over_implied_prob)
  • ·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: Replace Poisson tail with ML simulation prop_probs (src/projections/ml/simulation.py) once the sim emits the needed thresholds (TB ≥1/≥4/≥5; full K grid) and the backtest validates calibration improvement.

Strikeouts Board

0 of 13 projected
Strikeouts prop board sorted by signed model edge (over picks first).
#PlayerLineOdds O/UProjModel %Market %EdgePickConf
1
Aaron Nola
5.5+107/ −13746%
2
Brandon Pfaadt
4.5+134/ −17240%
3
Brandon Sproat
5.5−109/ −11749%
4
Bubba Chandler
4.5−139/ +10955%
5
Cam Schlittler
6.5−140/ +11055%
6
Cristian Javier
3.5−137/ +10754%
7
Ian Seymour
4.5−144/ +11356%
8
Logan Webb
4.5−150/ +11757%
9
Matthew Boyd
4.5−141/ +11155%
10
Michael King
4.5−103/ −12348%
11
Michael Lorenzen
3.5+136/ −17440%
12
Michael McGreevy
4.5+123/ −15742%
13
Shane Bieber
4.5+134/ −17240%

More for this date

Want the why behind an edge?

Ask The Almanac about a player's matchup, recent form, or pitcher arsenal in chat — same data, deeper context.

Start a conversation →