get_event_analytics

Reads only.

Use this for every analytics column of one event as it reads now. Use get_event_analytics_history instead for how those columns read on past days, and screen_events to compare many events. Fetch the full event_analytics row for one event_id: self-relative z-scores (price, pace, vol regime, inventory velocity), cross-sectional pct_rank / robust MAD-z columns, quartile primitives, face-value rollups, marketplace demand levels/deltas (demand_*), and data_quality_score. days_to_event is recomputed from the event date at read time (it keeps counting negative after the event). partial_row: true means the row is HOLLOW: its quality/inventory columns were never computed; treat its nulls as unknown, not zero, and don't rank it against complete rows. When prediction markets attach to the event, a prediction_markets array is included (latest daily snapshot, 0-1 yes-probabilities; INFORMATION about market expectations, not trading advice). Sports events carry BOTH sides' win markets: two opposing probabilities on one event is correct. No key = no market exists. Returns null if no row. A plan limit is never missing data: a reading the account's plan does not include is refused with a plan_required error (entitled false, required_tier the plan that unlocks it, a one line message), and a column or field the plan strips from an answer is named in a top level withheld list with the same three fields. null, an empty list and available false mean the data does not exist.

Parameters

Example

{ "event_id": "ev3rp4z4zhq1" }

Use it to drill into something screen_events surfaced: the full column set, not just the headline projection.