About iRankMovies

iRankMovies exists for one reason: to help you find movies and TV series that are genuinely similar to the ones you already love — not because an algorithm decided they were popular at the same time, nor because they happen to share a single genre tag.

Real similarity is multi-dimensional. A slow-burn psychological thriller set in 1940s London has far more in common with a Scandinavian noir from 2015 than with a generic action film that merely shares the "thriller" label. Our algorithm captures that nuance across eight content dimensions: genre, tone, pace, structure, era, theme, audience and narrative perspective.

On top of similarity, every title carries an iRank Score — a transparent, weighted aggregate of four independent rating sources (IMDb, Rotten Tomatoes, Metacritic and TMDb). No secret sauce, no black box.

Read exactly how it works on our methodology page.

The typical "you might also like" on streaming platforms is driven by what keeps you watching, not by what is actually similar to what you watched. Collaborative filtering ("users who watched X also watched Y") surfaces popularity, not content kinship.

We wanted a tool that works like a knowledgeable friend who has seen thousands of films and can tell you: "if you loved the moral ambiguity and slow escalation of There Will Be Blood, watch Nightcrawler — and here's exactly why."

iRankMovies is an independent project built and maintained by Lluis Enric Mayans, an SEO and content manager with over a decade optimising content-driven projects.

A lifelong film buff, Lluis pairs his obsession with cinema with a background in data and search to build a recommender that understands why two films resemble each other — not just what everyone happens to be watching. When he isn't fine-tuning similarity algorithms, he's revisiting film-noir classics and hunting down gems of world cinema.