Measure a game’s monthly active users (MAU) by counting distinct player identities that produced a clearly defined gameplay activity during a clearly defined period. To make the number interpretable, report the activity event, time window, identity key, game and platform scope, timezone, and policy for offline or late-arriving events. Without those details, two plausible MAU figures may describe different things.
Decide what your MAU number is meant to measure
MAU is an audience count, not a count of sessions, installs, or total activity. For one free-to-play title, the core calculation is:
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MAU = distinct player identities with at least one qualifying activity event in the stated window.
The phrase “qualifying activity” matters. An app open, a login, and a gameplay session are not interchangeable signals. Pick the event that best represents the question you want the metric to answer, then keep that definition stable across reports.
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Choose the measurement window
Use one of these approaches and label it explicitly. A calendar month supports month-to-month reporting; a rolling window updates each day and always looks back the same number of days.
| Window | How it works | Use and caveat |
|---|---|---|
| Calendar month | Count qualifying unique players from the first day of the month, inclusive, to the first day of the next month, exclusive. | Useful for monthly reporting. State the timezone because the exact start and end depend on it. GameAnalytics documents calendar-month unique users; PlayFab reports totals for a given month using its first and last days. |
| Rolling 30 days | Count qualifying unique players in the 30 days before the report’s stated end time. | Useful for a daily-updating audience measure. GameAnalytics and PlayFab document rolling 30-day measures; PlayFab uses UTC reporting timestamps. |
| Rolling 28 days | Count qualifying unique players in the 28 days before the report date. | Google Play Console defines its MAU this way. Do not compare it directly with a 30-day count as if the windows were identical. |
Vendor labels can conceal different windows: Google Analytics Help describes active users in the last 30 days, while Google Play Console uses a rolling 28-day period. When comparing a dashboard with an internal report, identify the actual window rather than relying on the label “MAU.”
Define what counts as activity
For a game-level measure of players, a recorded gameplay session or a specified play event is usually more informative than an install, store-page view, or account registration. The event should indicate that the player actually engaged with the game, according to your instrumentation.
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There is no universal vendor-independent activity rule. Google Play Console describes an app open; PlayFab’s rolling-thirty-day report counts players who logged in; Unity Analytics uses sessions in its FAQ definition. These systems therefore may produce different counts for the same title and period. Name your qualifying event in the metric definition—for example, session_start—rather than assuming the platform’s “active” label means the same thing as yours.
Choose the identity used to count unique players
Count a player once within the stated window when the identity system can support that decision. A stable account or player ID is generally preferable to a device ID when the goal is a player audience measure. If your game permits anonymous play, define how guest IDs behave when a player later signs in, creates an account, resets an ID, or changes devices.
Cross-device or cross-platform deduplication is possible only when you can reliably link identities. Otherwise, the same person may be counted more than once. A Zynga SEC filing from 2012 illustrates the limitation: its company-specific discussion notes that a player using two platforms could be counted twice when deduplication was unavailable. That dated example is a caution about identity resolution, not a universal industry rule.
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Filter the events and count distinct IDs
Once the window, event, and identity key are fixed, filter to the title and platform scope you intend to report, then count distinct identities. A basic SQL pattern is:
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SELECT COUNT(DISTINCT player_id)
FROM events
WHERE game_id = :game
AND event_name IN (:qualifying_events)
AND event_time >= :window_start
AND event_time < :window_end;
The inclusive start and exclusive end form a half-open interval. An event exactly at the end boundary is not counted in the earlier period, avoiding a double count if adjacent windows are queried. Adapt the field names and event filter to your actual event schema; the query is an implementation pattern, not a prescribed vendor query.
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- For 1-4 players, ages 4 and up
Standardize time and late events
Choose one timezone and use it consistently for event timestamps and report boundaries. UTC is a practical convention: GameAnalytics says its metrics are calculated within UTC dates and hours, and PlayFab says its reports use UTC. If you use another timezone, state it and apply it uniformly.
Offline play and delayed uploads can change a period’s count after the player’s session. Unity Analytics documents local event caching and later transmission. Decide whether reports include events by the time they occurred or the time they arrived, and whether you revise past periods when late events arrive. Validate the behavior in your own analytics pipeline; do not assume every event is received immediately.
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Use a compact label that makes the metric reproducible. For example, after replacing the example values with your actual instrumentation and policy:
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Rolling 30-day active players for Game A = distinct player IDs with at least one session_start from 00:00 UTC on [start date] through, but not including, 00:00 UTC on [end date]. Cross-platform players are deduplicated by account ID; guest IDs are counted separately until linked.
A complete reporting definition specifies:
- Whether the window is a calendar month, rolling 28 days, or rolling 30 days, with exact inclusive and exclusive boundaries.
- The qualifying activity event or events.
- The identity key and guest-account linking rule.
- The game, platform, and title scope.
- The timezone and treatment of offline or late-arriving events.
Compare MAU carefully and pair it with other measures
Before comparing two reports, check whether they match on window length, activity event, identity type, cross-platform deduplication, timezone, and late-event handling. If they do not, the difference may reflect measurement choices rather than a change in audience.
MAU describes how many distinct players were active at least once in the window; it does not show how frequently they returned. For frequency, pair it with DAU and a clearly defined DAU/MAU ratio. GameAnalytics describes its ratio as today’s users divided by the rolling 30-day population; Google Analytics Help frames its comparison as the last 24 hours against the last 30 days. For return behavior after installation, use cohort retention measures such as D1, D7, and D30, which Roblox Creator Docs discusses separately. MAU alone does not establish retention, revenue, or game quality.
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