We read the games you actually play and pick the perfect next one for you.

How NextGame works

NextGame reads the game list on your PlayStation, Nintendo or Steam account, works out which genres you actually spend your hours on and recommends your next game — a well-reviewed title, in your style, that is not in your library yet. Free, no sign-up, and nothing of yours is stored.

1. You connect your account

PlayStation: the app asks for your session token (NPSSO). You sign in on Sony’s own site, open an official page that displays the token and paste it here. NextGame never sees your password — and the token is used in a single request, never written to a database, cookie, file or log.

Nintendo: the login happens on Nintendo’s official site (OAuth with PKCE). You bring back the return URL, which carries a single-use code; the server exchanges it for a temporary 15-minute token, used only to read your play history and discarded when the analysis ends.

Steam: simpler still — there is no login. You paste your profile link (or SteamID) and the app reads your public library straight from Steam. All it takes is having “Game details” set to public.

Why copy and paste for PlayStation and Nintendo instead of a “Sign in with PlayStation” button? Because neither Sony nor Nintendo lets the login return land on a third-party site — that is a protection for your account, and NextGame works within it instead of asking you to switch it off. (Steam needs none of this because it exposes public profiles’ libraries.)

2. The app builds your taste profile

The analysis takes the games you have sunk the most hours into and cross-checks them against a local catalog of thousands of titles, with genre, subgenre and critic score (Metacritic). Your hours become a taste vector: 200 hours in a souls-like weigh far more than five two-hour games. Recent games weigh slightly more than old ones, because they say more about what you want to play now.

3. You get the pick — with the reasoning

The engine drops everything you have already played (including other editions of the same game), filters by quality and ranks the candidates by affinity with your profile. The result carries a match % — how much of your taste that title covers — and a justification derived from your own numbers, never generic filler. A few more options come along with it, so you get a choice.

When the catalog does not recognize enough titles from your library, the app says so on screen (a “sample recommendation” badge) instead of pretending an analysis happened.

The privacy promise

Analyze my profile