Bayesian Average Rating

Overview

Bayesian average combines an item's observed average rating with a prior (global average), weighted by review count. Formula: BR = (C × m + Σrᵢ) / (C + n) where m=global mean, C=confidence parameter, n=item reviews, Σrᵢ=sum of item ratings. Items with few reviews are pulled toward the global mean.

When to Use

Trigger conditions:

• Ranking items by continuous ratings (1-5 stars) with varying review counts
• IMDB-style "Top 250" lists that balance quality and popularity
• Any rating aggregation where new items shouldn't dominate with few high ratings

When NOT to use:

• For binary (upvote/downvote) data (use Wilson Score instead)
• When all items have similar review counts (simple average is sufficient)

Algorithm