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Scenario finder — crypto

Pick a market, then check off what actually happened today — a gap up, Asia sweeping yesterday's high, and so on. We show every pre-verified finding that matches, with its measured rate against the base rate, sample size, and confidence interval. Nothing here is computed on the fly — every row already survived the research pipeline's multiple-comparisons verification (Bonferroni correction across sectors, correlated-cluster checks). See methodology for how that works. Covers 6 pairs, pooled across weekday and weekend.

Measured odds. No trade calls. what this means →

Calibration: Crypto

When we said a level had an X% chance of being touched, how often did it actually happen? Out-of-sample, bucket by bucket.

Mean gap
1.39 pp
Checks measured
707.8M
707,782,112
Out-of-sample window
—
002525505075751001000-10%: predicted 4.4%, realized 4.3% (-0.1 pp) -- n = 291,267,13310-20%: predicted 14.4%, realized 14.6% (+0.2 pp) -- n = 108,807,06520-30%: predicted 24.9%, realized 25.2% (+0.3 pp) -- n = 61,440,18230-40%: predicted 34.4%, realized 34.3% (-0.1 pp) -- n = 44,213,86240-50%: predicted 45.3%, realized 45.2% (-0.1 pp) -- n = 38,819,52650-60%: predicted 55.1%, realized 55.2% (+0.1 pp) -- n = 52,047,91060-70%: predicted 64.9%, realized 64.3% (-0.6 pp) -- n = 32,951,65570-80%: predicted 75.7%, realized 75.8% (+0.0 pp) -- n = 52,722,07980-90%: predicted 82.0%, realized 82.1% (+0.1 pp) -- n = 25,512,700
PredictedRealized
Mean gap
1.70 pp
Checks measured
117M
117,041,556
Out-of-sample window
—
002525505075751001000-20%: predicted 7.2%, realized 7.3% (+0.1 pp) -- n = 66,230,31220-40%: predicted 28.8%, realized 29.1% (+0.3 pp) -- n = 17,806,80040-60%: predicted 50.9%, realized 50.8% (-0.1 pp) -- n = 14,889,50260-80%: predicted 71.8%, realized 70.9% (-0.9 pp) -- n = 14,133,81280-100%: predicted 81.8%, realized 81.2% (-0.7 pp) -- n = 3,981,130
PredictedRealized
Mean gap
1.35 pp
Checks measured
236.5M
236,491,175
Out-of-sample window
—
002525505075751001000-20%: predicted 7.1%, realized 7.0% (-0.1 pp) -- n = 133,371,36120-40%: predicted 28.9%, realized 28.9% (-0.0 pp) -- n = 35,101,21040-60%: predicted 50.9%, realized 51.0% (+0.0 pp) -- n = 30,469,73060-80%: predicted 71.3%, realized 71.5% (+0.2 pp) -- n = 28,635,11380-100%: predicted 82.0%, realized 82.4% (+0.4 pp) -- n = 8,913,761
PredictedRealized

These are touch probabilities from the model's own reliability check, not graded trade calls — for those, see the live Scorecard.

Per-sector breakdown, not per-symbol — the source data does not carry a per-symbol (e.g. ES vs NQ, or AAPL vs MSFT) calibration split, only per-sector/scope. 20-point-percentage bins (coarser than the 10pp futures/fx/stocks breakdown above) to keep per-sector cells sampled. Stocks: historical period 2020-2026, these 12 names selected ex-post (survivorship) — calibration applies to these names, not a random stock.

What happened today?

Pick one value per condition — or leave it at "not selected" to ignore it.

Prior 4-hour candle direction
Weekday vs. weekend (UTC)
Day of week
7-day narrow range (NR7)
Price position at 08:00 UTC (vs. ATR)
Price position at 16:00 UTC (vs. ATR)
Day-of-month tercile
Turn-of-month window
Volatility regime (vs. 90-day median ATR)
Yesterday's open->close direction
Yesterday's range width vs. ATR

Matching findings

Select at least one condition above to see matching findings.

CI method: wilson score interval, 95%, computed on rate_held/n_held (ci_lo_held/ci_hi_held columns, unchanged). Source: crypto_conditional_tables;daypart=pooled;2026-09-30.