Data quality

How good is this data?

The questions a careful partner or parent should ask of any rating dataset: how much does it cover, how fresh is it, who produced each score, and what happens when a score is wrong. Every number on this page is computed live from the ratings database — none are hand-maintained.

Coverage

22,354

standalone games scored

1,321

UGC experiences scored (Roblox, Fortnite Creative)

1,126

game ratings created or refreshed in the last 30 days

514

store-identifier mappings (Steam appIDs, app package names)

PlatformScored titles
PC15,429
iOS4,731
macOS3,888
PlayStation 42,605
Linux2,520
Xbox One2,323
Nintendo Switch1,959
Android1,879

Platform counts overlap (multi-platform titles count once per platform). Standalone games and UGC experiences are scored on different rubric profiles and are never summed into a single figure.

Who produced each score

Every rating carries a review tier, shown as a badge at the point of decision and served in the API. The current mix:

Review tierReviewsShare
automated22,355100.0%
expert20.0%

Automated scores are produced by a pipeline applying the published rubric, with periodic spot-check auditing; they are not individually verified by a human. That is stated on every rating, not buried here. The methodology (v1.3) documents the rubric, weights, and limitations, and is versioned — every score stores the methodology version that produced it.

Traceability

Every published score is reproducible: the stored review row keeps all 50 per-dimension inputs, composite scores carry the formula version that computed them, adversarially debated titles keep the full debate transcript on file, and since July 2026 every score change is journaled — old value, new value, which dimensions moved, and what triggered the rescore. A score here is never just a number; it is a number with a paper trail.

Update cadence

Ratings refresh through three mechanisms: newly ingested titles are scored on arrival; a metadata watcher flags previously scored titles whose source data changed (needs_rescore); and an age-based sweep re-queues ratings older than 180 days. In the last 7 days, 0 game ratings and 0 experience ratings were created or refreshed. Formal cadence commitment: FILL: re-review SLA — e.g. top titles within N days of a flagged change

Known limitations, disclosed

  • Nearly all scores are automated-tier (see the mix above). Spot-check audits and the published rubric constrain drift, but individual scores reflect a model’s application of the rubric, not a human expert’s judgement. The FAQ says this plainly, and so does the badge on every rating.
  • UGC experience ratings are only as good as their input signals. When there is not enough verified input data (confidence below 0.5), the score is suppressed everywhere — site and API — rather than shown with a caveat. Currently 61 experiences are held back this way.
  • Simulated-gambling content became its own age-floor dimension (R4.6) in methodology v1.2 (July 2026); titles scored before that carried heuristic floors until rescored. The changelog on the methodology page records every such rubric change.
  • Store-identifier mappings extracted from third-party store links start as verified: false and are flagged as such in the API until human-checked.

Report an error

If a score, an age floor, or a factual claim looks wrong, say so. Corrections are reviewed by the editor; confirmed errors are fixed by rescoring (which is journaled, not silently overwritten) and material corrections are noted in the methodology changelog. Response commitment: FILL: correction SLA — e.g. acknowledged within N business days Contact: FILL: error-report address

Methodology questions are answered by the methodology document (PDF) first — most “why is this score X” questions are rubric questions.