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submitted 3 days ago by YUART@feddit.org to c/gaming@lemmy.zip

Hey everyone,

Like many of you, I've spent more time hunting for my next game than actually playing. I'm frustrated with recommenders that just push popular titles, ignoring what makes my taste unique.

That's why I've been building Gamescovery (games discovery!).

What is it?

Gamescovery is a new recommendation system designed specifically for games. The goal is simple: use your ratings from the games you've played to find hidden gems and perfect matches you'd otherwise miss.

Why it's different:

  • It's not a generic engine. It's being built from the ground up to understand what you love about games.
  • Future updates will let you fine-tune recommendations based on what matters most to you (genre, mood, developer, etc.).
  • We start by focusing on the incredible world of itch.io indie games to help you uncover amazing projects that big algorithms overlook.

This is where you come in.

The alpha is now live, and it's very much an early build. I'm not a big company, I'm a solo developer who wants to build something the community actually finds useful. That's why your feedback is crucial.

As an alpha tester, you'll get:

  • Early access to a tool designed to beat the "recommendation paradox."
  • A direct line to the developer to shape project's future.
  • The chance to help build a non-biased, community-driven platform.

Ready to try it out?

👉 Sign up for the alpha and start getting recommendations here: https://gamescovery.com/

Want to chat, suggest features, or report bugs? 🎮 Join our Discord community: https://discord.gg/brr7aYezMc

This project has and will always have a free tier. The dream is to support all major platforms, but we're starting with itch.io to prove the concept.

Thanks for your time, and I'm excited to hear what you think!

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[-] TyrianMollusk@infosec.pub 3 points 3 days ago* (last edited 3 days ago)

I notice you are using a nineteen point rating scale, going from 1 to 10 with halves in between and a slider. You will get better ratings if you use a more standard scale that's compatible with other sites and a better method for inputting ratings.

You'll want to link your rating data to other sites (eg, backloggd.com, igdb.com) if you have any hope of this being used, so that's why compatibility is valuable. Mapping a 10 point scale to a 19 point scale is a silly wrench to throw in, and how will you translate your users' 19 point scale to push to sites with 10? You need to be able to keep users from entering scores over again to survive at all.

As to entry, something almost everything gets wrong is you actually get better data if you present ratings with the right number of points to the scale and use a tiered grouping (visually, not as in requiring a series of questions for a single rating). There's basically a right answer here, and its 10 points grouped 3-4-3. The grouping helps cognitively because you're basically picking high-mid-low twice instead of analyzing a 10 point spread. People are significantly statistically worse at using a wide, flat rating scale, and the two-tier version corrects that and gives you richer and more accurate data, especially if you label the tiers, to help reduce individual bias about how they apply their feelings to numbers (eg the modern 6/10=bad syndrome).

We need better rating analyzers than we have, but it will never work without connecting to other rating systems and processing games outside itch.io. And if you keep your recommendation mechanism under wraps with only manual rating entries, especially limited to itch.io games, you're asking far too much from someone to see if it's potentially relevant to them, both in the sense of effort and the sense of trust ("non-biased, community driven").

[-] YUART@feddit.org 2 points 3 days ago

Hi, thanks very much for this feedback, love it ❤️

I never heard about backloggd.com, but it's a good long-term thinking from you, that if the project survives to a stage where it has a big userbase, it's a good idea to have compatibility or "plugins" with other trackers and data sources.

I also like your idea with the rating scale, I will definitely think about implementing your idea or some variation of it.

Yeah, it would be stupid to lock the project inside of itch.io games only. I started from itch.io and indie games for a few reasons:

  • I would like Gamescovery to bring value for indie games community, so authors, who have no money for an advertisement campaign, have more chances for a bigger player base.
  • itch.io data is very chaotic. So I decided that if my system can classify and correctly recommend itch.io games, it would definitely have no problems with better data, like from Steam.

In the future, I definitely plan to support all popular PC game stores in the following order:

  • GOG
  • Steam
  • Epic

I also think about the support of the consoles, but this will be in the rather distant future.

I have one more question, if you don't mind - what is your feeling about game recommendations after you rated 3-4 games? Were recommendations lean towards predicable "correct" way, or were they completely random and off?

[-] TyrianMollusk@infosec.pub 2 points 3 days ago

I have one more question, if you don’t mind - what is your feeling about game recommendations after you rated 3-4 games? Were recommendations lean towards predicable “correct” way, or were they completely random and off?

I didn't rate any games, just looked at what it would take and had some quick feedback to offer. Part of the issue with Itch is that to rate games, you have to first find things on itch, as well as find things that'd be representative so you might see how recs do. For testing something that isn't going to do much right now, that's a fair bit of trouble, especially since my key interest would be whether recommendations really take taste into account or use one of the usual shortcuts that either lump you into categories or fall prey to the "well everyone likes X so X" syndrome. Either of those would take a fair bit of data for me to put in, and a rather surprising amount of data for you to already have at such an early stage.

[-] YUART@feddit.org 2 points 2 days ago

Hi, I see, hopefully you will be willing to participate in further testing (for example, in beta) when the project is in better shape.

The only reason I bring the current alpha to the public is to test the concept and see if people are interested in it at all. I spent around 1 year (1 year of time, not of working hours) to make the current alpha, and there is no sense in spending one more year on a project nobody actually wants. For now, feedback was somewhat positive, so I want to continue and see what I will build next.

The main idea of my recommendation algorithm is to calculate the unique test for every user. It doesn't and wouldn't compare the tastes of different users to calculate assumptions. I hate this, and those kinds of recommendation algorithms seem to never work for me. When doing my research on the beginning of the project, I found that such algorithms were first used for social media, but I don't feel these algorithms are correct (as I feel it, I can't prove this with real numbers for now).

So, hopefully, Gamescovery recommendation algorithms wouldn't have biases like "well everyone likes X so X”, since it never tries to compare 2 or more users. Besides that, Gamescovery will allow users to tweak the algorithm so that users can actually customize it to make the algorithm better for them. That doesn't mean users will be able to completely change the behavior of the algorithm, but rather direct it in a direction they want.

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this post was submitted on 28 Jan 2026
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