> For the complete documentation index, see [llms.txt](https://docs.predicthq.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.predicthq.com/getting-started/predicthq-data.md).

# PredictHQ data

What's inside a PredictHQ event record and the predicted attributes layered onto it. These attributes are what make the data usable in models and AI systems: verified events enriched with [predicted attendance](/getting-started/predicthq-data/predicted-attendance.md), [predicted end times](/getting-started/predicthq-data/predicted-end-times.md), [predicted event spend](/getting-started/predicthq-data/predicted-event-spend.md), [impact patterns](/getting-started/predicthq-data/impact-patterns.md), and [rankings](/getting-started/predicthq-data/ranks.md).

Start with [Event categories](/getting-started/predicthq-data/event-categories.md) to understand what kinds of real-world activity are covered, then [Ranks](/getting-started/predicthq-data/ranks.md) to understand how impact is scored. [Data accuracy](/getting-started/predicthq-data/data-accuracy.md) covers how the data is verified - the property that grounding and forecasting both depend on.


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