What happened anyway
Every claim on the scorecard is measured against the days it could have fired but didn’t. This is what those days did. A signal that is followed by a doubling 53% of the time sounds impressive until you know that doubling within a year happened on 53% of all days. This page is the denominator.
Computed from the daily snapshot for 10 September 2026
On every day since 2013, a 40% fall arrived within the next year 34.6% of the time and a doubling 53.0%. The median one-year forward return was 71.9%, and it was positive on 69.6% of starting days.
5001 starting days from 2013-01-01 to 2026-09-10. Windows overlap, so the effective sample is four cycles, not four thousand days.
Forward returns from any day
| Horizon | Worst twentieth 5th percentile /th> | Worst quarter 25th percentile /th> | Middle median | Best quarter 75th percentile /th> | Best twentieth 95th percentile /th> | Share positive | Windows |
|---|---|---|---|---|---|---|---|
| 30 days | -24.9% | -8.5% | 2.7% | 17.5% | 56.4% | 56.4% | 4971 |
| 90 days | -40.6% | -15.0% | 7.6% | 44.0% | 173.6% | 57.6% | 4911 |
| 180 days | -48.4% | -18.9% | 27.2% | 75.2% | 376.9% | 62.4% | 4821 |
| 365 days | -62.3% | -17.3% | 71.9% | 170.5% | 771.3% | 69.6% | 4636 |
The distribution is skewed: at one year the p5 is -62.3% and the p95 is 771.3%. A median of 71.9% with a quarter of starting days losing 17.3% or more is what a volatile asset in a rising trend looks like, and it is the shape every claim on the scorecard is measured against.
The two outcomes the scorecard tests
These are the two outcomes the scorecard tests every rule against: a top rule is judged on the first, a bottom rule on the second. A rule has to beat these on the days it could have fired, or it has told you nothing.
By starting cycle
| Windows starting | Median 1y | 40% fall | Doubled | Windows |
|---|---|---|---|---|
| 2013-16 | 138.9% | 31.8% | 63.2% | 1461 |
| 2017-19 | 47.6% | 48.5% | 55.4% | 1095 |
| 2020-23 | 98.9% | 33.9% | 56.1% | 1461 |
| 2024- (open) | 15.7% | 18.1% | 17.3% | 619 |
By months since the last halving
Every other cycle marker on this site — Pi Cycle’s moving averages, MVRV’s 3.7, the Mayer multiple’s 2.4 — has a threshold someone chose after seeing bitcoin’s history. The halving dates are set by the protocol. This table conditions on them and nothing else.
| Months after halving | Median 1y return | 40% fall within 1y | Doubled within 1y | Windows |
|---|---|---|---|---|
| 00-06 | 318.0% | 6.0% | 80.9% | 698 |
| 06-12 | 114.6% | 12.4% | 57.9% | 732 |
| 12-18 | -44.9% | 71.3% | 23.8% | 689 |
| 18-24 | -47.4% | 100.0% | 1.1% | 549 |
| 24-30 | 47.9% | 37.3% | 26.8% | 549 |
| 30-36 | 128.3% | 7.1% | 88.1% | 546 |
| 36-42 | 125.2% | 23.5% | 72.5% | 549 |
| 42-48 | 223.9% | 17.6% | 83.6% | 324 |
Starting 00-06 months after a halving, a 40% fall within a year happened 6.0% of the time; starting 18-24 months after, 100.0%. That is the four-year cycle in one table, and it is four cycles. A bin of 549 windows is four independent observations. The pattern is unusually clean for a sample that small, and a clean pattern in four observations is exactly what this site declines to call a rule everywhere else.
By where the cycle was when you started
| Starting MVRV | Range | Median 1y return | 40% fall | Doubled | Windows |
|---|---|---|---|---|---|
| Q1 lowest | below 1.29 | 84.9% | 22.0% | 60.8% | 1125 |
| Q2 | 1.29 to 1.70 | 117.7% | 41.0% | 60.6% | 1078 |
| Q3 | 1.70 to 2.18 | 77.4% | 36.5% | 47.7% | 1196 |
| Q4 highest | above 2.18 | 12.6% | 38.6% | 44.4% | 1237 |
Starting in the cheapest quartile of MVRV, the median one-year return was 84.9%; in the dearest, 12.6%. This is the realised-value thesis stated as a base rate rather than a signal: no threshold, no trigger, just the four quartiles and what followed each.
How to read this against the scorecard
The scorecard does not use these figures directly. It restricts the baseline to the days a rule could have fired but didn’t — the transition-matched set — so that a rule is compared with its own opportunity set, not with every day. That is why a rule’s “happened anyway” column differs from the unconditional rate here. The unconditional rate is the floor under both.
To test a rule of your own against these base rates, use the rule builder; to see what the site said on a given day and how it turned out, the forward record.
Windows overlap: a 365-day window starting on Monday shares 364 days with one starting on Tuesday. Thousands of windows are a handful of independent regimes. Every rate on this page is a fact about four cycles.
What this is not
Not a forecast. A forward-return distribution is a description of the past. The halving table in particular reads like a schedule and is four observations of a pattern that has no guarantee of persisting; the page says so beside it.
Recomputed daily by fetch/baserate.py and published as baserate.json. Method on the methods page.