Metrics

Notional volume, open interest, funding, liquidations, trading volume, fees and revenue, in USD. One row per thing per day, at eight grains: project, project and chain, app, app and chain, and each market kind with its token grain.

Tables

Daily perpetual and order-book fees, revenue and volume cover closed UTC days and follow the availability cutoff of each market’s chain.

A tab per grain. Coverage shows which apps report which measure.

One row per project per day. Notional volume comes in two lenses, exchange and interface; read one of them.

Table	Value column	What it holds
`metrics_projects.notional_trading_volume_exchange_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the project whose matching engine settled the trade.
`metrics_projects.notional_trading_volume_interface_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the project whose interface the trade was placed through.
`metrics_projects.trading_volume_daily`	`trading_volume`	Total value of trades executed.
`metrics_projects.fees_daily`	`fees`	Total fees paid by users.
`metrics_projects.fees_supply_side_daily`	`fees_supply_side`	Fees paid out to the supply side.
`metrics_projects.revenue_daily`	`revenue`	Fees retained by the protocol.

One row per project and chain per day.

Table	Value column	What it holds
`metrics_projects_by_chain.notional_trading_volume_exchange_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the project whose matching engine settled the trade.
`metrics_projects_by_chain.notional_trading_volume_interface_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the project whose interface the trade was placed through.
`metrics_projects_by_chain.trading_volume_daily`	`trading_volume`	Total value of trades executed.
`metrics_projects_by_chain.fees_daily`	`fees`	Total fees paid by users.
`metrics_projects_by_chain.fees_supply_side_daily`	`fees_supply_side`	Fees paid out to the supply side.
`metrics_projects_by_chain.revenue_daily`	`revenue`	Fees retained by the protocol.

One row per app per day. The exchange lens credits the venue whose matching engine settled the trade and the interface lens the app the trade was placed through.

Table	Value column	What it holds
`metrics_apps.notional_trading_volume_exchange_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the app whose matching engine settled the trade.
`metrics_apps.notional_trading_volume_interface_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the app whose interface the trade was placed through.
`metrics_apps.trading_volume_daily`	`trading_volume`	Value of trades executed by the app, measured on the quote leg at execution price.
`metrics_apps.fees_daily`	`fees`	Fees paid by users of the app across every chain it runs on.
`metrics_apps.fees_supply_side_daily`	`fees_supply_side`	Fees the app passed through to builders and, on HIP-3 markets, to market deployers.
`metrics_apps.revenue_daily`	`revenue`	Fees the app retained across every chain it runs on.

One row per app and chain per day.

Table	Value column	What it holds
`metrics_apps_by_chain.notional_trading_volume_exchange_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the app whose matching engine settled the trade.
`metrics_apps_by_chain.notional_trading_volume_interface_daily`	`notional_trading_volume`	Notional value of perpetual futures traded, attributed to the app whose interface the trade was placed through.
`metrics_apps_by_chain.trading_volume_daily`	`trading_volume`	Value of trades executed by the app, measured on the quote leg at execution price.
`metrics_apps_by_chain.fees_daily`	`fees`	Fees paid by users of the app across every chain it runs on.
`metrics_apps_by_chain.fees_supply_side_daily`	`fees_supply_side`	Fees the app passed through to builders and, on HIP-3 markets, to market deployers.
`metrics_apps_by_chain.revenue_daily`	`revenue`	Fees the app retained across every chain it runs on.

One row per perpetual market per day. The money tables also have chain_id, project_id and app_id; the position and trader tables are keyed on the market alone.

Table	Value column	What it holds
`metrics_perp_markets.price_daily`	`price`	Mark price of the perpetual futures market.
`metrics_perp_markets.notional_trading_volume_exchange_daily`	`notional_trading_volume`	Notional value traded in the perpetual futures market, attributed to the app whose matching engine settled the trade.
`metrics_perp_markets.notional_trading_volume_interface_daily`	`notional_trading_volume`	Notional value traded in the perpetual futures market, attributed to the app whose interface the trade was placed through.
`metrics_perp_markets.trade_count_daily`	`trade_count`	Number of trades executed in the perpetual futures market.
`metrics_perp_markets.daily_active_traders_daily`	`daily_active_traders`	Distinct traders active in the perpetual futures market.
`metrics_perp_markets.open_interest_daily`	`open_interest`	Notional value of open positions in the perpetual futures market.
`metrics_perp_markets.open_interest_long_daily`	`open_interest_long`	Notional value of open long positions in the perpetual futures market.
`metrics_perp_markets.open_interest_short_daily`	`open_interest_short`	Notional value of open short positions in the perpetual futures market.
`metrics_perp_markets.volume_to_open_interest_daily`	`volume_to_open_interest`	Notional trading volume divided by open interest.
`metrics_perp_markets.daily_active_traders_long_daily`	`daily_active_traders_long`	Distinct traders with long positions in the perpetual futures market.
`metrics_perp_markets.daily_active_traders_short_daily`	`daily_active_traders_short`	Distinct traders with short positions in the perpetual futures market.
`metrics_perp_markets.position_size_average_long_daily`	`position_size_average_long`	Average notional size of long positions in the perpetual futures market.
`metrics_perp_markets.position_size_average_short_daily`	`position_size_average_short`	Average notional size of short positions in the perpetual futures market.
`metrics_perp_markets.position_size_median_long_daily`	`position_size_median_long`	Median notional size of long positions in the perpetual futures market.
`metrics_perp_markets.position_size_median_short_daily`	`position_size_median_short`	Median notional size of short positions in the perpetual futures market.
`metrics_perp_markets.trader_share_long_top10_daily`	`trader_share_long_top10`	Share of long open interest held by the ten largest long traders.
`metrics_perp_markets.trader_share_short_top10_daily`	`trader_share_short_top10`	Share of short open interest held by the ten largest short traders.
`metrics_perp_markets.funding_rate_daily`	`funding_rate`	Daily funding rate paid between long and short positions in the perpetual futures market.
`metrics_perp_markets.liquidation_volume_long_daily`	`liquidation_volume_long`	Notional value of long positions force-closed in the perpetual futures market.
`metrics_perp_markets.liquidation_volume_short_daily`	`liquidation_volume_short`	Notional value of short positions force-closed in the perpetual futures market.
`metrics_perp_markets.fees_daily`	`fees`	Fees paid by traders on the perpetual market.
`metrics_perp_markets.revenue_daily`	`revenue`	Fees retained by the protocol on the perpetual market, net of the builder tip and HIP-3 deployer cut.
`metrics_perp_markets.fees_supply_side_daily`	`fees_supply_side`	Fees passed through on the perpetual market, being the builder-code tip plus the HIP-3 deployer’s cut.

One row per perpetual market and settlement token per day. Amounts become dollars here, and fees equals revenue plus fees_supply_side for the same market, token and day.

Table	Value column	What it holds
`metrics_perp_markets_by_token.notional_trading_volume_daily`	`notional_trading_volume`	Notional value traded in the perpetual futures market, price times trade amount over crossed (taker) legs.
`metrics_perp_markets_by_token.notional_trading_volume_exchange_daily`	`notional_trading_volume`	Notional value traded in the perpetual futures market, attributed to the app whose matching engine settled the trade.
`metrics_perp_markets_by_token.notional_trading_volume_interface_daily`	`notional_trading_volume`	Notional value traded in the perpetual futures market, attributed to the app whose interface the trade was placed through.
`metrics_perp_markets_by_token.fees_daily`	`fees`	Fees paid by traders on the perpetual market.
`metrics_perp_markets_by_token.revenue_daily`	`revenue`	Fees retained by the protocol on the perpetual market, net of the builder tip and HIP-3 deployer cut.
`metrics_perp_markets_by_token.fees_supply_side_daily`	`fees_supply_side`	Fees passed through on the perpetual market, being the builder-code tip plus the HIP-3 deployer’s cut.

One row per order-book market per day. Every table also has chain_id, project_id and app_id.

Table	Value column	What it holds
`metrics_order_book_markets.trading_volume_daily`	`trading_volume`	Value of trades executed in the order book market, measured on the quote leg at execution price.
`metrics_order_book_markets.fees_daily`	`fees`	Fees paid by traders on the order-book market.
`metrics_order_book_markets.revenue_daily`	`revenue`	Fees retained by the protocol on the order-book market, net of the builder tip.
`metrics_order_book_markets.fees_supply_side_daily`	`fees_supply_side`	Fees passed through on the order-book market, being builder-code tips.

One row per order-book market and quote token per day. Amounts become dollars here, and fees equals revenue plus fees_supply_side for the same market, token and day.

Table	Value column	What it holds
`metrics_order_book_markets_by_token.trading_volume_daily`	`trading_volume`	Value of trades executed in the order book market, measured on the quote leg at execution price.
`metrics_order_book_markets_by_token.fees_daily`	`fees`	Fees paid by traders on the order-book market.
`metrics_order_book_markets_by_token.revenue_daily`	`revenue`	Fees retained by the protocol on the order-book market, net of the builder tip.
`metrics_order_book_markets_by_token.fees_supply_side_daily`	`fees_supply_side`	Fees passed through on the order-book market, being builder-code tips.

Sample queries

The same trades also sit in metrics_apps.notional_trading_volume_exchange_daily credited to the matching venue, and summing both lenses counts every trade twice.

select
    app_id,
    sum(notional_trading_volume) as volume
from `metrics_apps.notional_trading_volume_interface_daily`
where timestamp >= timestamp('2026-08-01')
  and timestamp < timestamp('2026-08-08')
group by app_id
order by volume desc

chain_id on a per-chain table is the chain the market settled on, and one project’s chain rows add back to its metrics_projects row for the same day.

select
    chain_id,
    sum(notional_trading_volume) as volume
from `metrics_projects_by_chain.notional_trading_volume_interface_daily`
where project_id = 'hyperliquid'
  and timestamp >= timestamp('2026-08-01')
  and timestamp < timestamp('2026-08-08')
group by chain_id
order by volume desc

Each measure is its own table, so a row with all three is a join on perp_market_id and timestamp. Join with full join: a market has open interest on a day nothing traded.

with price as (
    select timestamp, price
    from `metrics_perp_markets.price_daily`
    where perp_market_id = 'hlbtc-hypercore'
      and timestamp >= timestamp('2026-06-01')
),

volume as (
    select timestamp, notional_trading_volume
    from `metrics_perp_markets.notional_trading_volume_exchange_daily`
    where perp_market_id = 'hlbtc-hypercore'
      and timestamp >= timestamp('2026-06-01')
),

open_interest as (
    select timestamp, open_interest
    from `metrics_perp_markets.open_interest_daily`
    where perp_market_id = 'hlbtc-hypercore'
      and timestamp >= timestamp('2026-06-01')
)

select
    timestamp,
    price.price,
    volume.notional_trading_volume,
    open_interest.open_interest
from price
full join volume
    using (timestamp)
full join open_interest
    using (timestamp)
order by timestamp

Long and short liquidation measures are separate USD tables. Join each to the registry on perp_market_id to select the venue and settlement chain.

with liquidations as (
    select timestamp, perp_market_id, 'long' as side, liquidation_volume_long as value
    from `metrics_perp_markets.liquidation_volume_long_daily`
    where timestamp >= timestamp('2026-08-01')
      and timestamp < timestamp('2026-08-08')

    union all

    select timestamp, perp_market_id, 'short' as side, liquidation_volume_short as value
    from `metrics_perp_markets.liquidation_volume_short_daily`
    where timestamp >= timestamp('2026-08-01')
      and timestamp < timestamp('2026-08-08')
)

select
    liquidations.timestamp,
    liquidations.side,
    sum(liquidations.value) as liquidated_notional_usd
from liquidations
join `dimensions.perp_markets` as markets
    using (perp_market_id)
where markets.exchange_app_id = 'mux-perps'
  and markets.chain_id = 'arbitrum'
group by liquidations.timestamp, liquidations.side
order by liquidations.timestamp, liquidations.side

order_book_market_id joins the registry for the pair name, and trading_volume counts one side of each match.

select
    daily.order_book_market_id,
    markets.name,
    daily.app_id,
    daily.trading_volume
from `metrics_order_book_markets.trading_volume_daily` as daily
join `dimensions.order_book_markets` as markets
    using (order_book_market_id)
where daily.timestamp = timestamp('2026-08-01')
order by daily.trading_volume desc
limit 25

Filter on primary_market_sector, the sector the Explorer lists the project under, so the total matches the Explorer and counts every project once.

select
    daily.timestamp,
    sum(daily.notional_trading_volume) as sector_volume
from `metrics_perp_markets.notional_trading_volume_exchange_daily` as daily
join `dimensions.projects` as projects
    on projects.project_id = daily.project_id
where projects.primary_market_sector = 'derivatives'
  and daily.timestamp >= timestamp('2026-08-01')
group by daily.timestamp
order by daily.timestamp

Overview

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Sample queries

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​Sample queries

Tables

Sample queries