Screener

One row per project in screeners.projects, every figure as of as_of, the last complete day. Each measure has a column per window and aggregation, named <measure>_<window>_<aggregation>: fees_30d_sum is the fees of the 30 days ending on as_of, and tvl_7d_change is TVL on as_of against TVL seven days earlier.

Columns

Keys
Aggregations
Measures

The two key columns, then one FLOAT64 column per measure, window and aggregation. Every row is a project in dimensions.projects, so the join on project_id always matches.

Column	Type	Description
`as_of`	TIMESTAMP	The last complete day, the same on every row. Every window ends on it.
`project_id`	STRING	Project the row belongs to, such as `aave`; joins `dimensions.projects`.

A window is 1d, 7d, 30d, 90d, 180d or 365d, and spans that many days ending on as_of, while the max_ columns read the whole history. Which aggregations a measure has follows its over_time in Metric definitions: only a measure whose over_time is sum has sum.

Column	What it holds
`<measure>_<window>_avg`	Mean of the daily values over the window.
`<measure>_<window>_sum`	Total of the daily values over the window. Flows only: the measures ticked under Sum.
`<measure>_<window>_change`	A comparison of two aggregations: the value on `as_of` against the value one window earlier, as `(now - then) / abs(then)`. Null when either value is missing or the earlier one is 0.
`<measure>_<window>_trend`	A comparison of two aggregations: the window’s average against the average of the window before it, as `(avg - prior) / abs(prior)`. Null unless the window before has a value on every one of its days, and null when its average is 0.
`<measure>_max_latest`	The value on `as_of`. Null when there is none.
`<measure>_max_ath`	The highest daily value over the project’s whole history.
`<measure>_max_atl`	The lowest daily value over the project’s whole history.

Every measure has the avg, change, trend and max_ columns, and the flows also have sum. A distinct count such as daily_active_users or token_holders takes avg, never sum.

Measure	Sum	What it holds
`daily_active_addresses`	✗	Distinct addresses transacting with the project’s contracts per day.
`monthly_active_addresses`	✗	Distinct addresses transacting with the project’s contracts over a rolling 30 days.
`weekly_active_addresses`	✗	Distinct addresses transacting with the project’s contracts over a rolling 7 days.
`monthly_active_developers`	✗	Number of active developers.
`active_loans`	✗	Value of loans outstanding at day end, in USD.
`fees_per_daily_active_user`	✗	Average fees per user.
`revenue_per_daily_active_user`	✗	Average revenue per user.
`assets_staked`	✗	Value staked at day end, in USD.
`bridge_deposits`	✗	USD value of assets held in the project’s bridge contracts on the main chain.
`bridged_supply`	✗	USD value of the project’s stablecoins held outside the chain they were issued on.
`buybacks`	✓	USD value of the project’s own tokens repurchased from the market.
`capital_deployed`	✗	USD value of user deposits an asset manager has allocated into investments.
`code_commit_count`	✓	Commits to public repositories.
`cost_of_revenue`	✓	Direct supply-side cost of revenue.
`earnings`	✓	What the project kept after costs, in USD. Goes negative when a project pays out more than it retains.
`notional_trading_volume_exchange`	✓	Notional value of perpetual futures traded, attributed to the project whose matching engine settled the trade.
`expenses`	✓	What the project spent, in USD: cost of revenue, token incentives and operating expenses, wherever each is reported onchain.
`fees`	✓	Total fees users paid, in USD. Chain gas plus app trading fees.
`fees_supply_side`	✓	The part of those fees the project passed on to the supply side, in USD.
`flash_loan_volume`	✓	Total flash loan volume.
`gas_used`	✓	Gas consumed by transactions calling the project’s contracts.
`gross_profit`	✓	Revenue minus cost of revenue.
`notional_trading_volume_interface`	✓	Notional value of perpetual futures traded, attributed to the project whose interface the trade was placed through.
`liquidation_volume`	✓	USD value of debt covered in liquidations.
`liquidity_turnover`	✗	Trading volume relative to liquidity.
`market_cap_circulating`	✗	Market cap on circulating supply.
`market_cap_fully_diluted`	✗	Market cap on maximum supply.
`open_interest`	✗	USD notional value of all open positions on the project’s derivatives markets.
`operating_expenses`	✓	Onchain operating expenses, excluding token incentives.
`outstanding_supply`	✗	Stablecoin supply issued by the project and outstanding today, in USD. Stablecoin issuers only.
`price_to_fees_circulating`	✗	Circulating market cap over annualized fees (trailing 30d run-rate).
`price_to_fees_fully_diluted`	✗	Fully diluted market cap over annualized fees (trailing 30d run-rate).
`price`	✗	Project token price in USD.
`price_to_revenue_circulating`	✗	Circulating market cap over annualized revenue (trailing 30d run-rate).
`price_to_revenue_fully_diluted`	✗	Fully diluted market cap over annualized revenue (trailing 30d run-rate).
`revenue`	✓	Fees the project kept, in USD.
`staking_market_cap`	✗	USD value of the native token staked to secure the chains the project operates, summed across them.
`take_rate`	✗	Share of fees the project retains as revenue.
`token_incentives`	✓	Value of the project’s own token paid out as rewards, in USD.
`token_supply_circulating`	✗	Circulating token supply.
`token_supply_maximum`	✗	Maximum token supply.
`token_trading_volume`	✓	Trading volume of the project’s own token.
`token_turnover_circulating`	✗	Token trading volume over circulating market cap.
`token_turnover_fully_diluted`	✗	Token trading volume over fully diluted market cap.
`token_holders`	✗	Addresses holding the project’s token.
`trade_count`	✓	Number of trades executed.
`tradeable_asset_count`	✗	Number of tokens tradeable on the exchange.
`tradeable_pair_count`	✗	Number of token pairs available for trading on the exchange.
`trading_volume`	✓	Cash value of the trades that took place, in USD.
`trade_size_average`	✗	Average trading volume per trade.
`trading_volume_per_daily_active_user`	✗	Average trading volume per user.
`transaction_count_contracts`	✓	Transactions calling the project’s contracts.
`transaction_volume`	✓	USD value of transactions processed by the project.
`transfer_volume`	✓	USD value of assets moved through the project’s bridge transfers, counted once per transfer.
`treasury`	✗	Value the project held at day end, in USD, its own token included.
`treasury_net`	✗	Value the project held at day end excluding its own token, in USD.
`tvl`	✗	Value locked in the project’s contracts at day end, in USD.
`daily_active_users`	✗	Distinct addresses that used the project that day. A HyperLogLog estimate, not a sum of the daily series.
`monthly_active_users`	✗	Distinct addresses that used the project in the trailing 30 days. A HyperLogLog estimate.
`weekly_active_users`	✗	Distinct addresses that used the project in the trailing 7 days. A HyperLogLog estimate.

Sample queries

One project
Top 25 by 30-day fees
Biggest 7-day TVL moves
Market cap against yearly revenue

Every column of one row shares the same as_of, so the figures read together.

select
    as_of,
    tvl_max_latest,
    tvl_7d_change,
    fees_30d_sum,
    fees_30d_trend
from `screeners.projects`
where project_id = 'aave'

fees_30d_sum is the total of the 30 days ending on as_of. The join to dimensions.projects on project_id adds the name.

select
    projects.name,
    screener.fees_30d_sum,
    screener.revenue_30d_sum,
    screener.fees_30d_trend
from `screeners.projects` as screener
join `dimensions.projects` as projects
    using (project_id)
where screener.fees_30d_sum is not null
order by screener.fees_30d_sum desc
limit 25

tvl_7d_change compares TVL on as_of with TVL seven days earlier, as a fraction. The TVL floor keeps a small base from dominating the ranking.

select
    projects.name,
    screener.tvl_max_latest,
    screener.tvl_7d_change
from `screeners.projects` as screener
join `dimensions.projects` as projects
    using (project_id)
where screener.tvl_max_latest > 10000000
  and screener.tvl_7d_change is not null
order by abs(screener.tvl_7d_change) desc
limit 25

revenue_365d_sum is the revenue of the 365 days ending on as_of, and market_cap_circulating_max_latest the latest circulating market cap. Their ratio is a price-to-sales multiple.

select
    projects.name,
    screener.market_cap_circulating_max_latest,
    screener.revenue_365d_sum,
    safe_divide(
        screener.market_cap_circulating_max_latest,
        screener.revenue_365d_sum
    ) as price_to_sales
from `screeners.projects` as screener
join `dimensions.projects` as projects
    using (project_id)
where screener.revenue_365d_sum > 1000000
  and screener.market_cap_circulating_max_latest > 0
order by price_to_sales
limit 25

Overview

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Columns

Sample queries

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​Sample queries

Columns

Sample queries