We are using the same true Bayesian estimate formula used by the Internet Movie Database, for calculating average ratings.
weighted rank (WR) = (v / (v+m)) * R + (m / (v+m)) * C
where:
R = average review rating for the DZ = (Rating)
v = number of reviews for the DZ = (votes)
m = minimum reviews required to be listed in top 10
C = the mean review rating across all DZs
This formula normalizes scores, that is it pulls a particular score (R) to the mean (C) if the number of reviews is not well above m. In other words, if a particular DZ has only a few reviews above the minimum required reviews to be listed in the top 10 (m), the average score is decreased a little if it is above the mean, or increased a little if it is below the mean in accordance with the normal distribution rule of statistics.
Here is an example:
WR = (17 / 32) * 3.2 + (15 / 32) * 4.6 = 3.86
| | | | | |
v v+m R m v+m C
The formula normalizes the average rating of a relatively low rated DZ/Tunnel from 3.2 to 3.86 since the number of reviews (v=17) is only slightly above the minimum required votes (m=15) and the mean across all DZs (C=4.6) is quite high. If, in the future, this particular DZ/Tunnel gets more reviews, the difference between R and C will increase as the number of reviews increase. The idea is that the more reviews, the more representative the average rating is.
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