Feb 18, 2026
Why Course Fit Matters More Than Recent Form
The data behind strokes-gained profiles and why matching a player's DNA to the course is the most overlooked edge in golf DFS.
Projection models and ownership analytics that separate you from the field. DFS optimization, +EV sports betting, and PrizePicks edges — powered by quantitative models, not opinions.
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Most golf optimizers recycle the same consensus projections. CADDIE runs 10,000 Monte Carlo simulations per slate, factors in course fit DNA, strokes-gained profiles, and real-time ownership shifts to find lineups with asymmetric upside.
| Player | Salary | Proj | Own% | Value |
|---|---|---|---|---|
| S. Scheffler | $11,200 | 78.4 | 28.1% | 7.0x |
| R. McIlroy | $10,600 | 74.2 | 22.5% | 7.0x |
| C. Morikawa | $9,800 | 71.8 | 14.2% | 7.3x |
| S. Burns | $8,400 | 66.1 | 8.7% | 7.9x |
| T. Hatton | $7,900 | 63.5 | 6.1% | 8.0x |
| A. Noren | $7,200 | 61.9 | 3.4% | 8.6x |
The data behind strokes-gained profiles and why matching a player's DNA to the course is the most overlooked edge in golf DFS.
A transparent look at the 10,000-simulation model under the hood—what it captures that simple projections miss.
Ownership leverage is the single biggest factor in GPP profitability. Here's the math behind CADDIE's contrarian engine.
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