The dynasty tools you already use are good at telling you what the crowd thinks. We're built to tell you when the crowd is wrong, and to prove it. Here's the honest comparison, including the dimensions where the incumbents beat us.
| Dynasty Formula | KeepTradeCut | FantasyCalc | Flock Fantasy | |
|---|---|---|---|---|
| Methodology transparency | We win Full formula published: projection inputs, the convex title-value curve, replacement levels, all of it. Read it here. |
Opaque. Crowd-voted values; no published formula behind the numbers. | Opaque. Proprietary model; no published formula behind the numbers. | Opaque. Consensus of in-house rankers; no published formula behind the numbers. |
| Backtested track record | We win 54.7% vs 42.0% across 569 published historical disagreements, wins and misses both on the page. See the receipts. |
No published backtest. | No published backtest. | No published backtest. |
| Update cadence | Competitive Full refresh weekly in-season, with a light daily pass for injuries, depth charts, and trades. |
Continuous: values move with every crowd vote. | Continuous: values refresh as its inputs move. | Ongoing: updated by rankers through the season. |
| Price | We win Core rankings and calculator free; Pro at $24.99/yr planned. |
Free. | Free. | Free tier; ~$34/season for the Season Pass. |
| Community & size | They win We're new and small. What we have instead of a crowd is a published record. We'd rather be small and right than big and unverified. |
The default trade language of dynasty. Enormous community; every league-mate already speaks KTC. | Large and widely embedded: its values power many tools and trade finders. | Growing community with premium tools and league sync. |
No trash talk: KTC, FantasyCalc, and Flock are serious tools run by serious people, and crowd consensus is genuinely useful information. Our claim is narrower and checkable: our model is published, backtested, and converts scoring to title value on a convex curve. We'd rather win on the dimensions that can be measured than on vibes.
We project every player's fantasy points per game over their projected career: a weighted base of recent production (50/30/20), regressed for small samples; position-specific age curves fit from a decade of history; career length from historical survival data (longer for high producers); draft-capital priors for rookies. Then we convert scoring to championship equity with a convex curve fit from 60,000 simulated seasons, discounted 12% per year:
We subtract replacement level and normalize to a 0–1,000 scale. Because values already carry the stud premium, trade math is just addition: no secret adjustments.