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!