Streaming homepages are flooded with content. Unseen filters that noise using the strongest signals of quality: critic and audience ratings, awards, and major film canon lists.
Just movies — no TV, no filler. Each title gets an Unseen Score— a single 0–100 number blended from multiple sources, weighted by reliability — so you can quickly find what's worth your time.
How the Unseen Score works
The composite score blends multiple ratings sources into a single 0–100 number to help you find movies worth watching.
Target weights
Audience ratings from millions of users. We apply a Bayesian average so movies with fewer votes are pulled toward the global mean — a 9.0 with 2,000 votes counts much less than a 9.0 with 500,000. Movies need roughly 100,000+ votes before their raw rating is fully trusted.
A weighted average of professional critic scores on a 0–100 scale. Unlike Rotten Tomatoes, Metacritic measures how good critics think a film is, not just whether they gave it a thumbs up.
The Tomatometer is the percentage of critics who gave a positive review — but it doesn't distinguish a masterpiece from pretty good. A film can score 95% with critics all saying it's decent. The least reliable input, hence the lower weight.
Why IMDb is required
A movie must have an IMDb rating with at least 1,000 votes to receive an Unseen Score. IMDb is the only source where we can verify a meaningful sample size. Without it, a film might rank highly based on a handful of critic reviews alone, which isn't a reliable signal. Movies without an IMDb match still appear in results with their individual badges, but won't have a composite score.
When other scores are missing
Not every movie has Metacritic or RT scores. When one is unavailable, the remaining weights are proportionally scaled up. For example, if only IMDb and RT are available, IMDb gets ~80% and RT gets ~20%.
The math
Bayesian-adjusted IMDb rating — smooths the raw rating toward the global mean based on how many votes the film has:
adjusted = (v / (v + m)) × R + (m / (v + m)) × C where R = raw IMDb rating (0–10) v = IMDb vote count m = 100,000 (trust threshold) C = 6.8 (global mean rating)
Unseen composite — weighted mean of the sources we have, with weights re-normalized when Metacritic or RT is missing:
composite = round(
Σ (score_i × weight_i / total_weight)
for i in available sources
)
target weights
IMDb (adjusted × 10) 60
Metacritic 25
Rotten Tomatoes 15Worked example: raw IMDb 9.2 with 150,000 votes → adjusted (150k / 250k) × 9.2 + (100k / 250k) × 6.8 ≈ 8.24. With no MC/RT, composite = round(8.24 × 10) = 82.
Where the data comes from
- IMDb — public ratings + vote counts via the official datasets
- Rotten Tomatoes + Metacritic — critic scores via OMDb
- TMDB — posters, runtimes, languages, related films, trailers
- Watchmode — streaming availability per platform
- Awards + canon— Academy Best Picture, AFI Top 100, BFI Sight & Sound, Library of Congress National Film Registry
Scoring methodology v1 — last updated April 2026.