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MOVIE
Star OVERALL
IMDB USERS
Rotten Tomatoes CRITICS
Rotten Tomatoes USERS
FilmAffinity USERS
Metacritic CRITICS
Metacritic USERS
Letterboxd USERS
TMDB USERS
Data updated: January 2025 | Created by Pipps

Rating Methodology

Score Calculation

The OVERALL score is calculated in two steps:

  1. First, each platform's rating is individually adjusted considering:
    • The original rating
    • Number of votes for the specific movie
    • Average number of votes across all movies on that platform
  2. Then, all adjusted scores are averaged equally

This two-step process ensures that:

  • Within each platform, movies with more votes have more credibility in their average
  • Each platform contributes equally to the final score, regardless of its total user base

For example, a movie with 100,000 votes will have a more reliable average than one with only 1,000 votes, and its score will stay closer to the platform's true average, supposing the platform's average vote count is closer to 100,000.

Color-Coding System

The color-coding system works differently for the All-Time Top 50 and yearly rankings:

  • For yearly rankings, colors represent percentile rankings within each column. This is necessary because each platform has its own typical rating ranges, using different scales and scoring tendencies. Therefore, the same rating might appear in different colors across platforms, as what matters is how good that score is relative to other movies within that specific platform.
  • For the All-Time Top 50, colors are based on absolute values instead of percentiles. This is because these movies represent the best-rated films across all years, so their scores tend to be consistently high. Using percentiles in this case would show misleading color differences between very similar high scores (for example, showing a 9.9 in red compared to a 10).

This dual approach ensures that colors meaningfully represent both relative performance within a year and absolute quality in the all-time rankings.

This methodology ensures a more balanced and reliable evaluation of each movie, reducing potential bias from low review counts and different rating scales across platforms.