How often does Bitcoin close UP vs DOWN in 1-hour Polymarket markets? This page breaks down real historical outcomes — by time of day and day of week — so you can spot statistical patterns. Data updates automatically.
Bitcoin shows mild but noticeable tendencies at 1-hour. A few time slots lean one way more often than not, though the edges are modest.
Key takeaway: The standout pattern is 10AM ET, which closed UP 63% of the time across 89 markets.
Across the most recent markets, Bitcoin closed UP 51% of the time in 1-hour slots (2,157 markets analyzed). A reading near 50% means the market is efficient; a strong skew suggests a recurring pattern.
The slot with the strongest UP lean is 10AM (63% UP over 89 occurrences).
The slot with the strongest DOWN lean is 7AM (41% DOWN over 90 occurrences).
| Slot (ET) | UP % | DOWN % | Markets | Significance |
|---|---|---|---|---|
| 10AM | 63% | 37% | 89 | ★★ |
| 6AM | 61% | 39% | 90 | ★★ |
| 7AM | 59% | 41% | 90 | ★ |
| Slot (ET) | UP % | DOWN % | Markets |
|---|---|---|---|
| 12AM ET | 50% | 50% | 90 |
| 1AM ET | 58% | 42% | 90 |
| 2AM ET | 51% | 49% | 90 |
| 3AM ET | 43% | 57% | 90 |
| 4AM ET | 52% | 48% | 90 |
| 5AM ET | 50% | 50% | 90 |
| 6AM ET | 61% | 39% | 90 |
| 7AM ET | 59% | 41% | 90 |
| 8AM ET | 48% | 52% | 90 |
| 9AM ET | 56% | 44% | 90 |
| 10AM ET | 63% | 37% | 89 |
| 11AM ET | 52% | 48% | 89 |
| 12PM ET | 53% | 47% | 89 |
| 1PM ET | 52% | 48% | 90 |
| 2PM ET | 51% | 49% | 90 |
| 3PM ET | 57% | 43% | 90 |
| 4PM ET | 47% | 53% | 90 |
| 5PM ET | 48% | 52% | 90 |
| 6PM ET | 44% | 56% | 90 |
| 7PM ET | 53% | 47% | 90 |
| 8PM ET | 48% | 52% | 90 |
| 9PM ET | 42% | 58% | 90 |
| 10PM ET | 42% | 58% | 90 |
| 11PM ET | 46% | 54% | 90 |
| Slot (ET) | UP % | DOWN % | Markets |
|---|---|---|---|
| Sunday | 52% | 48% | 312 |
| Monday | 49% | 51% | 312 |
| Tuesday | 50% | 50% | 312 |
| Wednesday | 49% | 51% | 302 |
| Thursday | 51% | 49% | 295 |
| Friday | 53% | 47% | 313 |
| Saturday | 53% | 47% | 311 |
Each 1-hour Polymarket market resolves UP or DOWN. We aggregate outcomes by their start time and weekday, then compute the UP rate and a statistical significance score (Z-score). Patterns with more occurrences and higher Z-scores are more reliable. Past patterns do not guarantee future results.