A new daily service inspired by Ars Technica's own Steam Gauge project gives a detailed breakdown of estimated sales and player data for every game on Valve's Steam service.

Steam Spy uses the same kind of random sampling methods that we first outlined in our initial Steam Gauge post to estimate total ownership, median play time, recent play time, and more for all the games on Steam. The service is updated everyday, and a simple, clean interface lets users explore the data based on user-reported player location, game genre, release date, developer, and more with just a few clicks.

On the Steam Spy About page, Cypriot gaming blogger Sergey Galyonkin cites a "cool idea of Kyle Orland from Ars Technica" as the basis for the site (thanks!). He also warns users that Steam Spy has many of the same limitations as Steam Gauge before it: a small margin of error inherent to sampling about 100,000 user profiles a day, temporary skews from "free weekend" numbers, missing data from other distribution methods, and results that are "completely unreliable for recently released games." Still, the site represents an invaluable resource for anyone interested in demystifying the usually opaque world of game sales stats.

The site's Alpha launch over the weekend is already having some ripple effects in the industry. Dave Gilbert at Wadjet Eye Games decided to release official sales statistics for all of the company's games rather than have others guess at the accuracy of public estimates available on Steam Spy. "This is the new reality and I suppose developers like me will have to adjust," he writes.

Steam Spy isn't the only project to take the Steam Gauge idea and run in interesting directions with it. Deep Gabe takes the raw data from Steam API sampling and applies machine learning algorithms to compare games based on their similarities. The result is a model that attempts to predict Metacritic scores both pre- and post-launch based on available information.

For our part, we're planning more analyses of our own Steam Gauge data in the weeks to come, including some statistical breakdowns of data that goes past the basic "top sellers" lists.