I found a GreaseMonkey script that integrates torrent search results directly into IMDb pages. It helps you quickly locate downloadable versions of movies while you browse the database for titles, ratings, and cast information.
I downloaded the entire IMDb database to view offline using MovieDb software. I’m also using this local copy to track my progress as I work through watching every movie on the IMDb Top 250 list.
I shared a dataset of the top 1000 most popular IMDb movies, including ratings and vote counts. I marked which ones I've watched to help analyze popular but lousy films, available via an embedded spreadsheet and Excel download.
I used Excel to analyze the IMDb Top 250, identifying outliers in the correlation between ratings, vote counts, and release years. I found that popularity doesn't always match quality for classics like Seven Samurai or blockbusters like The Matrix.
I built a heatmap mapping IMDb ratings against vote counts to find movies I've missed. It helps me visualize popular high-rated outliers, track my viewing progress, and filter by genre to discover hidden gems outside the Top 250.
Snow White (2025) is an unusually extreme IMDb negative outlier even among famously disliked popular films.