The 1% play solved. The 99% pay for it.The only DFS edge
The only DFS edge
that learns.
✓
Best projections — de-vigged and data-driven
✓
The only self-learning ownership in DFS — trains & corrects itself on real results
✓
Auto-built lineups — optimal shape, stacks, leverage & correlations. Explained & adjustable.
✓
Intelligent late swap — re-solves your open slots off odds that move in real time
✓
Slate Review — exactly where you went right or wrong
Start your free trial3 days free · cancel anytime
Auto-built · 1 of 150 · DK Classic SOLVED
| Lineup | Proj | Own | $ |
|---|---|---|---|
| PPaul Skenes | 24.1 | 29% | 10.9K |
| PTarik Skubal | 22.4 | 21% | 10.2K |
| CWill Smith | 9.1 | 14% | 4.8K |
| 1BFreeman | 10.3 | 19% | 5.3K |
| OFBetts | 11.0 | 22% | 5.6K |
| OFOhtani | 12.4 | 34% | 6.4K |
| OFT. Hernández | 9.6 | 11% | 4.9K |
| 2BArraez · bring-back | 8.2 | 7% | 4.1K |
| 3BChapman | 8.9 | 9% | 4.4K |
| SSDe La Cruz | 9.8 | 16% | 5.2K |
Shape 5-2-1 · a measured winnerLeverage +6Bring-back ✓$49,800 · pOwn 61%
Built in the exact shape real GPP winners run — 5-man stack, correlated bring-back, leverage-aware. 149 more like it, one click away.
Where tournaments are won
The only ownership model that learns from what actually happened.
Everyone sells you a static ownership number and asks you to trust it. Ours trains on real contest results and grades itself against what actually happened every single slate— then corrects automatically. Nothing for you to upload or maintain. It doesn't just project the field. It learns the field.
- Machine-learning calibration from real contest results
- Self-graded projected-vs-actual, every slate
- Sharper for the exact pools you play
- Feeds the leverage builder that hunts the low-owned edge
Last 6-game slate · projected vs actualself-graded ✓
Ohtani±3%
Judge±3%
Skenes±3%
Witt Jr.±3%
Carroll±2%
ProjectedActual
Slate Review · your 150 entriesgraded ✓
Best finish4th / 32,900 · +$1,180
Contest P&L−$55 (cashed 41 of 150)
Your avg lineup ownership74% · winners ran 61%
Most over-owned playChalk SP · in 88% of your LUs
Where you went wrong: you were 13% over the winning ownership band and under-leveraged the 5-2-1 shape. Next time, more of your low-owned edge plays — the model already flags them.
The loop closes
See exactly where you went right — and wrong.
Just type in your entry name — no uploads, no CSVs— and get an honest post-mortem on all 150 lineups: your P&L, how your ownership stacked up against the players who actually cashed, and the shapes you should have built more of.
- Real P&L, tracked per contest
- Your ownership vs the winning band
- The exact structural fixes for next time
- Every slate makes your model smarter
Pricing
One plan. Every edge.
Every projection, every sport, and the only ownership that learns — in one subscription.
3-day free trial
Pro · All access
$499/month
Billed monthly · cancel anytime
Start your free trialSecure checkout via Stripe · card required · 3 days free
Projections
De-vigged & data-drivenGlass-box breakdownsMLB · MMA · GolfNFL — coming soonDraftKings + FanDuelMarket + model blend
Ownership
Self-learning modelSelf-corrects every slateGraded vs real resultsPer-player calibrationLeverage scoresLive updates to lock
Lineups
150 auto-builtOptimal winner shapesStacks & bring-backsCorrelation-awareLeverage-awareExposure capsLock / excludeOne-click tweakIntelligent late swapExplained & adjustable
Review & export
Slate ReviewP&L trackingEntry gradingOwnership vs winners1-click DK + FD exportEntry-template CSV