How does IFDB pick games to recommend?

The recommendations on the IFDB home page are "algorithmic" - they're picked by the computer based on statistics in the database. They're not paid ads - they're based purely on ratings from our members and review sites like Baf's Guide. We're not being paid to promote one game over another.

The system picks front-page recommendations by looking for other members with similar patterns of likes and dislikes to your own, as expressed in the ratings they gave to the games they reviewed. IFDB tries to match you up with a few other members, then recommends games that those other members rated highly.

In principle, the more ratings you and other members provide, the more accurate the matching will become. So the recommendations should get better and better as you rate more games.

This approach is sometimes called "collaborative filtering." Some people think it's great, others are skeptical. The obvious objection is that it doesn't capture the reasons that you like the games you like, so it might match you up with someone who happens to like some of the same games, but for completely different reasons. There's obviously no guarantee that the approach will actually produce good advice, but we hope that it gives you at least a few leads on games that you might otherwise have overlooked.

If the algorithmic recommendations on the home page don't work for you, remember that IFDB still offers several ways to get personal recommendations from other users, such as member reviews and Recommended lists.