The problem is that Steam has over 15,000 games with 500 added a month. Once a game gets momentum it is more highly promoted by Steam, generating more high scores in a snowball effect. Many good games never take off enough to be noticed.
And that's why I'm especially interested in this algorithm, posted on Github, that ferrets out Steam's "hidden gems" using a bit of smart math.
The code here is written by NeoGAF member Wok, who describes it like so: "the score of a game is defined as the product of a quality measure (its Wilson score) and a decreasing function of a popularity measure (its players total forever). The quality measure comes from SteamDB and the popularity measure comes from SteamSpy API."
If I understand correctly (greatly simplified) first it looks at the 1 to 10 star ratings, then it looks at the number of high scored ratings to equate a larger sample size to greater accuracy of the rating (a statistical Wilson score - never heard of that before), then the algorithm divides by how many users own that game.
By that metric a popular game like Half-Life would never show up on the 'Hidden Gems' list.
It might be a good way to find indie games during the sale. The article lists the top 100 gems.
I was proud that I already own one of the hidden gems already, Linelight.
Yes, it's deceptively fun but doesn't look like much at first glance.
Most of the Hidden Gems I had never heard of before.
Take a look!
