bitunix

Spent Outputs Aged 1w–1m

Range
  • 1M1M
  • 3M3M
  • 6M6M
  • 1Y1Y
  • ALLALL
Scale
  • LinearLinear
  • LogLog
Latest
56.91K
2026-10-27 · 56,911
1D change
+28.09%
Prev. 44.43K
7D change
+12.59%
Prev. 50.55K
30D change
+77.69%
Prev. 32.03K
4Y percentile
33%
All history 63%
All-time high
501.41K
2021-05-02 · -88.65%
1Y range
26.96K – 350.35K
Since 2009-01-12
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About this metric

What it measures

Spent Outputs Aged 1w–1m counts each output consumed during the day after remaining unspent for between one week and one month. It reports the number of outputs reactivated after a weeks-long pause, without weighting them by size.

How to read it

Rising readings indicate more reuse of outputs from the preceding weeks, while declining readings show less spending from that window. The record was 501,412 on May 2, 2021, with BTC around $57,826; the full-history median of 45,220 is much lower, emphasizing the difference between bursts and routine turnover.

A count can fall because fewer outputs were created in the relevant earlier period, not just because holders became less willing to spend. Wallet layout, consolidation and internal transfers also shape activity, so read this band alongside its younger and older neighbours rather than equating it with short-term sentiment alone.

Frequency
Daily (UTC 00:00)
Asset
BTC
Type
Single value
Data since
2009-01-12
Latest data
2026-10-27
Data points
6,498

FAQ

Why can this band rise after activity in younger bands fades?

Outputs created during an earlier busy period can remain untouched for weeks and then be spent. Each spent output is classified by its age at spending, so activity can shift toward older bands without the same outputs being counted in both.

Does a weekly-to-monthly spend reset the output's age?

The old output is consumed permanently. New outputs created by that transaction begin their own lifespans, even when some of the funds return to the same owner as change.

Can this count be compared directly with the one-day-to-one-week band?

The bands cover different durations and contain different numbers of eligible outputs. Comparing their trends is useful, but a larger raw count does not by itself mean a higher probability of spending.