Praedictum
Sports simulation intelligence
Simulated Sundays, not a single point projection — built to show you the range of what could happen, and how sure we are about it.
How It Works
1. Simulate
Praedictum simulates each game play by play, not each player alone — when a quarterback and his top receiver connect, it happens inside the same simulated game, together, thousands of times over.
The simulator doesn't model downs, distance, sacks, or kicks. Every defense is graded degraded, on the record, because of it.
2. Forecast
Every player's projection is opportunity times efficiency — expected touches, and what he does with each one — shrunk toward what similar players usually do, and reported with a spread, never a single number.
This hasn't been checked against a real, played-out result yet. No full slate has run end to end here, and no accuracy claim is made.
3. Model the field
Ownership — the share of the contest expected to roster each player — builds a simulated crowd of thousands of opposing lineups, which is then checked for how many would have built the exact same lineup you did.
Ownership here is a model, not a measurement. It isn't fit to real ownership data, and by design it can never read the optimizer's own output — no feedback loop.
4. Optimize
An exact solver searches every legal lineup under the salary cap and the roster rules — rules checked field by field against DraftKings' own published rules page — and returns the best one it can find, honoring your locks and excludes.
“Best” only means the search finished. If it runs out of time first, the result is labelled feasible, not best, and the two are never shown as the same thing.
5. Portfolio
A whole slate of lineups is chosen as a set — rewarding upside across the group and limiting how much of it leans on any one player — then compared against entering your single best lineup that many times over.
Every result today is scored against exactly one real, human-observed DraftKings contest. Nothing here says how it would score in a contest nobody has watched.
What You See
There's no real screenshot to show yet. This section will hold one honest capture of the Player Workspace — central estimate, uncertainty band, model coverage, and where every number came from, all visible without a click. The workspace itself is still being built; we're not going to fake the screenshot in the meantime.
Two Kinds of “We're Not Sure”
When Praedictum reports a result, the error bar is split into two numbers on purpose.
Football randomness
Simulate 60 Sundays and the average is rough; simulate thousands and it smooths out — one measurement of this landed at a −0.49 slope, almost exactly what theory predicts (−0.5). This is the part more simulated Sundays actually fix.
Uncertainty about the crowd
The opponents in the simulated field are one sample of what the real crowd might look like. No number of extra Sundays changes that — you're replaying the same crowd every time, so this number is kept flat instead of letting it shrink (measured: 0.08, 0.07, 0.06, 0.06, 0.07 as the Sunday count grows from 60 to 15,360).
More compute buys less football noise. It doesn't buy more knowledge about the crowd — only real, observed contest results would, and there aren't enough of those yet.
Sports & Sites, Today
NFL, DraftKings Classic — nothing else, yet. See what's supported, provisional and planned →
Join the Beta
We'll invite people in small groups once the beta is ready to accept them — no timeline promised yet.
Join Beta