99 Nights in the Forest: average growth outpaced its peak
99 Nights in the Forest grew in both its weekly average and its largest observed sample during October 5–11. Its average grew faster, so the result is more informative than simply finding a new large peak.
The recorded comparison
| Metric | Earlier week | Later week | Change |
|---|---|---|---|
| Average concurrent players | 178,926 | 219,889 | +22.9% |
| Observed peak | 1,781,443 | 1,996,474 | +12.1% |
| Hours with samples | 168 / 168 | 168 / 168 | Complete both weeks |
| Recorded samples | 1,072 | 959 | Timing varies |
Weekly averages give each stored hourly mean equal weight. Counts above are rounded for display; percentage changes use the unrounded data.
The whole-week average rose 22.9%
The equal-hour mean increased from about 178,926 concurrent players during September 28–October 4 to 219,889 during October 5–11: an increase of 22.9%, calculated before rounding. The largest observed sample rose from 1,781,443 to 1,996,474, about 12.1%.
These are different summaries of the same observation windows. The peak identifies the busiest captured moment; the average weights all 168 hourly means equally. Faster average growth means the two-week result is not described adequately by the change in the peak alone. It does not prove that every individual hour or day grew.
Growth against a quieter fixed cohort
Across the same 7,508 games with complete hourly coverage in both weeks, summed average concurrency fell 2.5%. 99 Nights moved in the opposite direction. That contrast distinguishes this game’s measured result from the broader cohort result without pretending the cohort represents all of Roblox.
The cohort excludes games discovered too late and games with missing hourly observations. New releases outside it may have performed very differently. Adding more games to the tracker later does not change this frozen comparison, which uses the same included games in both windows.
What the figures leave open
The later week contains 959 underlying samples for 99 Nights and the earlier week 1,072. Each UTC hour has observations, but that is not continuous measurement. A short spike between samples could exceed the reported observed peak, and averages can be affected by uneven timing within an hour.
Player counts alone do not establish whether an update, recommendation or promotion produced the increase. They cannot distinguish automated accounts or report unique weekly players. Repeating the comparison across further complete weeks is the next step for testing whether the larger average persists.
Check the data and follow the game
The figures come from the Oct 5–11, 2026 audience report, which documents the complete-hour cohort, selections and sampling limits. This article preserves those periods rather than updating them silently.
Open this game’s live player count and history or read the collection methodology. For a correction, contact RoVitals.