Metrics Daily by Venue 🌱

The hyperliquid.predictions.metrics_daily_by_venue table provides daily activity, fee, user, and open interest metrics for Hyperliquid HIP-4 prediction markets. One row per (day, venue, category, sub_category). Platform-wide totals without a venue split remain on Metrics Daily.

Table Details

Property	Value
Table Name	`hyperliquid.predictions.metrics_daily_by_venue`
Table Status	Beta 🌱
Unique Key	`day`, `venue`, `category`, `sub_category`
Clustering Key(s)	`day`
Search Optimization	`venue`, `category`, `sub_category`

HIP-4 categories: price_binary (Recurring auto-generated price markets), categorical (named outcomes under a question), binary (orphan named outcomes). sub_category is the Recurring underlying asset (e.g. ‘BTC’); ‘none’ for non-Recurring categories. Venue is unknown when Hyperliquid did not publish one. A venue-day can have open interest even when trade counts are zero. Do not sum median_trade_size_usd, active_users, active_makers, or active_takers across venues.

Table Columns

Column Name	Data Type	Description
project	VARCHAR(16777216)	Top-level project namespace (`hyperliquid`).
protocol	VARCHAR(16777216)	Protocol within the project (`hyperliquid_hip4`).
chain	VARCHAR(16777216)	The blockchain network (`hyperliquid`).
day	DATE	Date bucket (UTC).
venue	VARCHAR(16777216)	Venue identifier (for example `txyz`, `out`, `skew`). `unknown` when not published.
category	VARCHAR(16777216)	Market type. One of ‘price_binary’, ‘categorical’, ‘binary’.
sub_category	VARCHAR(16777216)	Underlying asset for Recurring categories (e.g. ‘BTC’). ‘none’ for non-Recurring categories.
trading_volume_usd	FLOAT	USD trade volume for the day.
notional_volume	FLOAT	Trade volume in HL contract units (1 contract = $1 of collateral locked at mint). Different scale from share-based platforms; prefer `trading_volume_usd` for cross-platform comparison.
trade_count	NUMBER(38,0)	Trade count for the day.
avg_trade_size_usd	FLOAT	Average trade size in USD for the day.
median_trade_size_usd	FLOAT	Median trade size in USD for the day.
total_fee_usd	FLOAT	Total transaction fee revenue in USD.
total_buyer_fee_usd	FLOAT	Buyer-side fee revenue in USD.
total_seller_fee_usd	FLOAT	Seller-side fee revenue in USD.
total_builder_fee_usd	FLOAT	Total builder fee revenue in USD.
synthetic_mint_volume_usd	FLOAT	USD volume of synthetic mints.
synthetic_mint_count	NUMBER(38,0)	Synthetic mint count for the day.
markets_traded	NUMBER(38,0)	Distinct events traded (multi-outcome questions count as one event).
outcomes_traded	NUMBER(38,0)	Distinct outcomes traded.
coins_traded	NUMBER(38,0)	Distinct side-tokens traded.
active_users	NUMBER(38,0)	Distinct addresses across maker and taker roles. An address acting as both in the same day counts once.
active_makers	NUMBER(38,0)	Distinct maker addresses.
active_takers	NUMBER(38,0)	Distinct taker addresses.
total_open_interest_usd	FLOAT	HIP-4 open interest in USD for this venue, category, and sub-category on the day.
markets_with_oi	NUMBER(38,0)	Distinct events with open interest on the day.
cumulative_trading_volume_usd	FLOAT	All-time USD volume up to and including the day, scoped to (venue, category, sub_category).
cumulative_notional_volume	FLOAT	All-time notional volume up to and including the day, scoped to (venue, category, sub_category).
cumulative_trade_count	NUMBER(38,0)	All-time trade count up to and including the day, scoped to (venue, category, sub_category).
unique_id	VARCHAR(16777216)	Deterministic unique identifier per row.
_created_at	TIMESTAMP_NTZ(9)	Row creation timestamp.
_updated_at	TIMESTAMP_NTZ(9)	Row last update timestamp.

Sample Query

SELECT
  day,
  venue,
  category,
  sub_category,
  trading_volume_usd,
  trade_count,
  active_users,
  total_open_interest_usd,
  markets_with_oi
FROM hyperliquid.predictions.metrics_daily_by_venue
WHERE day >= CURRENT_DATE - 30
ORDER BY day DESC, venue, category, sub_category

Overview

Data Verticals

Solana

Hyperliquid

Lighter

Bitcoin Ecosystem

EVM

Cosmos Ecosystem

Move Ecosystem

Other Ecosystems

Table Details

Table Columns

Sample Query

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​Table Columns

​Sample Query

Table Details

Table Columns

Sample Query