Forest Fire (track)
by Mount Eerie
Year: 2017
From the album A Crow Looked At Me (track #4)
Listen on Spotify SPOTIFY
Forest Fire appears on the following album(s) by Mount Eerie:
- A Crow Looked At Me (track #4) (this album) (2017)
Listen to Forest Fire on YouTube
Forest Fire 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.
Showing latest 5 ratings for this track. | Show all 98 ratings for this track.
| Rating | Date updated | Member | Track ratings | Avg. track rating |
|---|---|---|---|---|
| 01/14/2026 15:41 | Exist-en-ciel | 102,765 | 71/100 | |
| 08/01/2025 16:53 |  Igtonumama | 31,383 | 81/100 | |
| 06/13/2025 00:29 | sunnydhamm | 18,530 | 57/100 | |
| 02/11/2025 18:11 | BorderFreeAndrew | 5,309 | 74/100 | |
| 02/10/2025 14:41 | daCritic | 36,962 | 75/100 |
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 4% of all tracks on BestEverAlbums.com. This track has a Bayesian average rating of 81.1/100, a mean average of 80.5/100, and a trimmed mean (excluding outliers) of 81.7/100. The standard deviation for this track is 14.7.
Forest Fire comments
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LebowskiRams 05/06/2020 23:30 | #251012
"I reject nature, I disagree" gets me every time
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