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[D] Using machine learning to predict video game review scores.

I’m not sure this is the right place for this, but hopefully someone can point me in the right direction if not. I run a site called Fantasy Critic. It’s basically fantasy football for video games, where you “draft” a “team” of video games and compete for the best review scores. On the site, I maintain a list of “master games” that players can select from. You can see that here:

https://www.fantasycritic.games/games

I have a stat that I calculate, called “Hype Factor”, that attempts to calculate how excited people are for a game. Right now, it’s a fairly simple calculation based on how frequently a game is drafted and how early in the draft the game is taken. However, I think my calculation is a little flawed and I’m wondering if machine learning would be a better choice here.

What I’m looking to do is take the various stats that I can gather from the site and use those to predict the critic score (from OpenCritic.com) that the game will get. I have a sample dataset here:

https://www.dropbox.com/s/6vc3dwltbncm8ev/FantasyCriticMasterGameData.csv?dl=0

So there’s a lot complexites that would go into doing something like this I’m sure. One of my concerns is that I may not have enough data here to be able to generate a model. I’m open to any thoughts or advice that people have, and I can expand on anything that’s unclear. Additionally, if anyone feels like they have a decent shot at making this work, I’m open to paying someone to help me with this.

Thanks!

submitted by /u/elitefusion
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.