All featuresSimulation
2,000 runs,every factor shown.
Not a black box: a seeded Monte Carlo model over personal bests, seed times, and this meet's own results. Scroll to watch the histogram build, run by run, and settle into a real p10 / p50 / p90 band.
#1 Girls 11-12 50 Freestyle · Ava Chen (SHRK)
2,000 runs · seeded Monte Carlo · estimate
p10 29.21p50 29.55p90 29.94
0%P(top 3)
- Recent drops-0.22s
- Seed vs best gap-0.08s
- Age curve-0.03s
- Event familiarity-0.04s
- Long day+0.03s
- DQ risk3% — shown separately, never applied
Same logic that scores the meet
Placing and points are the real functions that score results — the model never reimplements them, only feeds them sampled times.
Deterministic, and honest
Every prediction is labeled an estimate and lists the factors behind it. Run it again with the same seed and you get the same number — and a swimmer with too little history is marked low data and skipped rather than guessed.
Every real piece, pinned
What's behind an estimate
The named factors, the determinism, and what happens when there isn't enough history.
Team standings · 2,000 runs · estimate
P(win meet)62%
Swingiest eventEvent 6 · 15/4/1 pts
Ava Chen — 50 Free: low data, skipped
Tap the + marks for detail.