When You're In (track)
by Pink Floyd
Year: 1972
From the album Obscured By Clouds (track #2)
Listen on Spotify
When You're In appears on the following album(s) by Pink Floyd:
- Obscured By Clouds (track #2) (this album) (1972)
- The Early Years 1972 Obfusc/ation (track #2) (compilation) (2017)
Upcoming concerts
Listen to When You're In on YouTube
When You're In ratings
Average Rating = (n ÷ (n + m)) × av + (m ÷ (n + m)) × AVwhere:
av = trimmed mean average rating an item has currently received.
n = number of ratings an item has currently received.
m = minimum number of ratings required for an item to appear in a 'top-rated' chart (currently 10).
AV = the site mean average rating.
| Rating | Date updated | Member | Track ratings | Avg. track rating |
|---|---|---|---|---|
| ! | 02/06/2026 08:39 | Foxforce5 | 4,842 | 77/100 |
| ! | 01/17/2026 10:55 | Imaybeparanoid | 51,869 | 69/100 |
| ! | 12/06/2025 05:02 | Exist-en-ciel | 77,258 | 70/100 |
| ! | 12/03/2025 17:34 |  Liedzeit | 9,733 | 77/100 |
| ! | 11/28/2025 17:35 | Siromynian | 16,010 | 71/100 |
Rating metrics:
Outliers can be removed when calculating a mean average to dampen the effects of ratings outside the normal distribution. This figure is provided as the trimmed mean. A high standard deviation can be legitimate, but can sometimes indicate 'gaming' is occurring. Consider a simplified example* of an item receiving ratings of 100, 50, & 0. The mean average rating would be 50. However, ratings of 55, 50 & 45 could also result in the same average. The second average might be more trusted because there is more consensus around a particular rating (a lower deviation).
(*In practice, some tracks can have several thousand ratings)
This track is rated in the top 15% of all tracks on BestEverAlbums.com. This track has a Bayesian average rating of 78.3/100, a mean average of 77.1/100, and a trimmed mean (excluding outliers) of 78.4/100. The standard deviation for this track is 14.5.
When You're In comments
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talinhosgameplay 04/19/2025 23:09 | #308616
Doesn't go anywhere but it's good.
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