Gaming Stats: See How You Really Play With an Activity Heatmap
Most gamers can't say how many games they finished last year, how many hours went into which genre, or whether they play more in winter. Your library already contains the answer. The NXTO Stats page turns it into charts you can read at a glance.
The activity heatmap
The heatmap is a calendar of the last 12 months, like the contribution graph on GitHub. Each square is a day; the brighter it is, the more happened that day. Hover a square to see the details.
- Hours played — taken from your daily Steam sync. Steam only reports lifetime totals, so NXTO stores a snapshot each day and calculates the difference.
- Games added to your backlog that day.
- Games finished — the day you marked something Completed counts the most.
Honest limitation: hours can only be shown from the day you connect Steam. Steam doesn't expose past days, so the heatmap fills up from now on rather than backwards.
The rest of the Stats page
Status breakdown and completion rate
How many games are in Backlog, Playing, Done and Dropped. The completion rate is the number most people don't want to see — and the one that makes you buy fewer games.
Hours: done vs. still to go
The total time of the games you've finished next to the total time still waiting in your backlog. There is also a “when would I finish?” estimate at 5, 10 or 20 hours a week.
Genres, tags and ratings
Your top genres and most common tags, plus how your ratings are distributed. If your average is 4.5 stars, you're easy to please; if you give three stars to everything in one genre, it's time to stop buying it.
Monthly activity
How many games you added each month, which shows when the Steam sale hit your wallet.
Using your stats
- If one genre has a low completion rate, you buy it out of hype but don't enjoy it. Those games can go to Dropped without guilt (see why you abandon games).
- If the heatmap shows long gaps, plan shorter games for the busy months — our list of short games helps.
- Rate every finished game. Your ratings are what the recommendations learn from.