Prediction Markets

Polymarket, Kalshi, and cross-platform prediction market data — trades, market details, prices, volume, and open interest.

17 tables in this category.

Tables

View Name	Database	Source	ORDER BY
`agent.polymarket_trades`	`agent`	`polymarket_polygon.market_trades`	`block_time, tx_hash, evt_index`
`agent.polymarket_market_details`	`agent`	`polymarket_polygon.market_details`	`condition_id, token_id`
`agent.polymarket_events`	`agent`	`polymarket_polygon.events`	`—`
`agent.polymarket_prices_daily`	`agent`	`polymarket_polygon.market_prices_daily`	`—`
`agent.polymarket_prices_hourly`	`agent`	`polymarket_polygon.market_prices_hourly`	`—`
`agent.polymarket_prices_latest`	`agent`	`polymarket_polygon.market_prices_latest`	`token_id`
`agent.polymarket_volume_daily`	`agent`	`polymarket_polygon.market_volume_daily`	`condition_id, block_date`
`agent.polymarket_volume_hourly`	`agent`	`polymarket_polygon.market_volume_hourly`	`condition_id, block_hour`
`agent.polymarket_rolling_metrics`	`agent`	`polymarket_polygon.market_rolling_metrics`	`—`
`agent.polymarket_open_interest_daily`	`agent`	`polymarket_polygon.market_open_interest_daily`	`condition_id, block_date`
`agent.polymarket_user_activity`	`agent`	`polymarket_polygon.user_activity_v2`	`account, token_id, block_time`
`agent.kalshi_market_details`	`agent`	`kalshi.market_details`	`market_ticker`
`agent.kalshi_trades`	`agent`	`kalshi.trades`	`ticker, created_time, trade_id`
`agent.prediction_markets_daily`	`agent`	`prediction_markets.daily`	`—`
`agent.prediction_markets_matched_markets`	`agent`	`prediction_markets.matched_markets`	`—`
`agent.prediction_markets_matched_daily`	`agent`	`prediction_markets.matched_daily`	`—`
`agent.polymarket_positions`	`agent`	`None`	`—`

agent.kalshi_daily_categorized
agent.kalshi_market_report
agent.prediction_category_daily

Sample Queries

1. Daily volume by platform

SELECT date, source,
       sum(notional_volume_usd) AS volume,
       sum(open_interest_usd) AS oi
FROM agent.prediction_markets_daily
WHERE date >= today() - 30
GROUP BY date, source
ORDER BY date DESC, source

Table Schemas

`agent.polymarket_trades`

Individual Polymarket trade events (OrderFilled) with USD amounts, maker/taker addresses, condition IDs, and outcome context. One row per trade event. The primary source for Polymarket volume and trading activity analysis.

Engine: MergeTree | Partition: toYYYYMM(block_date) | ORDER BY: block_time, tx_hash, evt_index

Column	Type	Description
`block_date`	`Date`	Partition key. Always filter on this.
`block_time`	`DateTime64(3)`	Trade timestamp.
`block_number`	`UInt64`	Block number
`tx_hash`	`String`	Transaction hash
`evt_index`	`UInt32`	Event log index in transaction
`exchange_address`	`String`
`protocol`	`String`
`project`	`String`	Protocol name
`order_hash`	`String`
`maker_address`	`String`	Maker (liquidity provider) address.
`taker_address`	`String`	Taker (liquidity consumer) address.
`maker_asset_id`	`String`
`taker_asset_id`	`String`
`maker_amount_filled`	`UInt256`
`taker_amount_filled`	`UInt256`
`fee_raw`	`UInt256`
`outcome_token_id`	`String`
`shares`	`Float64`
`amount_usd`	`Float64`	Trade notional value in USD (one-sided).
`price`	`Float64`	Token price in USD
`fee_usd`	`Float64`
`condition_id`	`String`	Unique market condition identifier. Links to market_details.
`question`	`String`
`outcome_index`	`UInt8`
`outcome_label`	`String`
`category`	`String`	Market category
`market_slug`	`String`
`market_end_date`	`DateTime`
`neg_risk`	`UInt8`
`question_id`	`String`
`event_slug`	`String`
`event_title`	`String`	Event title

💡 Tip

account = maker captures both sides of a trade — do NOT fan out to both maker and taker
This follows Paradigm methodology: each OrderFilled with account=maker is one-sided volume
934M rows — always filter on block_date or block_time ranges
condition_id links to market_details for market question and metadata
JOIN with polymarket_market_details ON condition_id for market enrichment

⚠️ Warning

On-chain trades only — off-chain order book and cancellations not included
Pipeline lag: Polygon BQ export runs every 1h, typical lag ~1 hour
No aggregator/frontend attribution — all trades appear as CTF Exchange events

`agent.polymarket_market_details`

Polymarket market metadata dimension table. Contains market questions, descriptions, event groupings, resolution status, end dates, tags, and Polymarket links. One row per (condition_id, outcome_index) — use outcome_index=0 for one row per condition.

Engine: MergeTree | ORDER BY: condition_id, token_id

Column	Type	Description
`condition_id`	`String`	Primary market identifier. Links to all other Polymarket tables.
`question_id`	`String`	Groups related conditions into a single question (e.g., 'Will X win?' has Yes/No conditions).
`question`	`String`	Market question text (e.g., 'Will Bitcoin reach $100K by December 2026?').
`market_description`	`String`	Longer market description with resolution criteria.
`token_id`	`String`
`outcome_index`	`UInt8`	0 or 1. Use 0 for deduplication (one row per condition).
`outcome_label`	`String`
`token_outcome_name`	`String`
`category`	`String`	Market category
`market_slug`	`String`
`event_slug`	`String`	URL-safe event identifier for Polymarket links.
`event_title`	`String`	Parent event title grouping multiple markets.
`market_end_date`	`DateTime`	Scheduled market end date.
`neg_risk`	`UInt8`	Boolean. True = this is a neg-risk (multi-outcome) market.
`active`	`UInt8`	Boolean. True = market is currently open for trading.
`closed`	`UInt8`	Boolean. True = market has been closed (trading halted).
`archived`	`UInt8`
`volume_total`	`Float64`
`liquidity`	`Float64`
`resolved_at`	`DateTime64(3)`	Resolution timestamp. Null if unresolved.
`created_at`	`DateTime`
`updated_at`	`DateTime`
`market_id`	`UInt64`
`start_time`	`DateTime`
`close_time`	`DateTime`
`game_start_time`	`DateTime`
`tags`	`String`	Array of category tags.
`volume_1wk`	`Float64`
`volume_1mo`	`Float64`
`volume_1yr`	`Float64`
`resolution_source`	`String`
`image`	`String`
`icon`	`String`
`neg_risk_market_id`	`String`
`event_description`	`String`
`event_start_time`	`DateTime`
`event_image`	`String`
`event_resolution_source`	`String`
`status`	`String`	Market status (active, closed, resolved)
`winning_outcome_index`	`Int8`
`polymarket_link`	`String`	Direct URL to this market on polymarket.com.

💡 Tip

Filter outcome_index = 0 for one row per condition (avoids duplicates)
question is the market title/question text
active=true means the market is currently tradeable
closed=true means the market has stopped trading (may or may not be resolved)
Tags is an array — use hasAny(tags, ['politics']) for tag filtering
condition_id is the primary join key to trades, positions, volume, and OI tables

⚠️ Warning

Metadata reflects current state — does not track historical changes to descriptions or end dates
category/subcategory not directly in this table — join with curated ranking or category tables

`agent.polymarket_events`

Polymarket event-level metadata. Events group related markets (conditions) under a single theme (e.g., "2026 US Presidential Election" groups multiple candidate-specific markets). Useful for navigating the market hierarchy.

💡 Tip

Events contain multiple conditions — join with market_details on event_slug for full expansion
Useful for building hierarchical market browsers (event -> conditions -> trades)

⚠️ Warning

Not all markets belong to events — some standalone markets have no parent event

`agent.polymarket_prices_daily`

Daily outcome token prices for Polymarket markets. Tracks the probability (price) of each outcome over time. Useful for building price charts and tracking market sentiment evolution.

💡 Tip

Price represents implied probability (0-1 range, where 1.0 = 100% chance)
Combine with market_details for market question context
For binary markets, only one outcome price is needed (the other is 1 - price)

⚠️ Warning

Daily granularity only — no intraday price snapshots available in this table
Prices reflect last trade of day, not volume-weighted average

`agent.polymarket_prices_hourly`

Hourly CLOB mid-prices per Polymarket outcome token. Provides intraday price (implied probability) resolution for building higher-frequency charts and detecting rapid sentiment shifts.

💡 Tip

Prices represent implied probability (0-1 range). Multiply by 100 for percentage.
Filter on block_date first for partition pruning, then narrow by hour if needed
For binary markets, one outcome price is sufficient — the other is 1 - price
JOIN with polymarket_market_details ON condition_id for market question context

⚠️ Warning

Mid-prices from CLOB — may be stale for illiquid markets with wide spreads
Not volume-weighted — reflects order book mid, not trade-weighted average

`agent.polymarket_prices_latest`

Latest snapshot price per Polymarket outcome token. A convenience view that returns the most recent price for each condition, eliminating the need for argMax() queries against the full prices table.

Engine: MergeTree | ORDER BY: token_id

Column	Type	Description
`token_id`	`String`
`condition_id`	`String`	Polymarket condition ID
`question`	`String`
`outcome_index`	`UInt8`
`outcome_label`	`String`
`last_updated`	`Date`
`latest_price`	`Float64`

💡 Tip

One row per condition — no time filter needed
Equivalent to argMax(price, timestamp) from the full prices table but pre-computed
JOIN with polymarket_market_details ON condition_id for enrichment

⚠️ Warning

Point-in-time snapshot — reflects the most recent pipeline run, not tick-level
Stale for markets with no recent trading activity

`agent.polymarket_volume_daily`

Daily aggregated trading volume per Polymarket market condition. Pre-computed from individual trades for efficient time-series queries. One row per (condition_id, block_date).

Engine: MergeTree | Partition: toYYYYMM(block_date) | ORDER BY: condition_id, block_date

Column	Type	Description
`block_date`	`Date`	Date of the volume observation.
`condition_id`	`String`	Market condition identifier.
`trade_count`	`UInt64`
`notional_volume_usd`	`Float64`	Daily notional trading volume (one-sided, USD)

💡 Tip

Much faster than aggregating polymarket_trades for daily volume — prefer this table
JOIN with market_details ON condition_id for market context
For platform-level total volume, sum across all conditions per day

⚠️ Warning

Granularity is daily only — for intraday volume, use polymarket_trades directly

`agent.polymarket_volume_hourly`

Hourly trading volume per Polymarket condition. Pre-aggregated from individual trades for efficient intraday volume analysis without scanning the full trades table.

Engine: MergeTree | Partition: toYYYYMM(toDate(block_hour)) | ORDER BY: condition_id, block_hour

Column	Type	Description
`block_hour`	`DateTime`
`condition_id`	`String`	Polymarket condition ID
`trade_count`	`UInt64`
`notional_volume_usd`	`Float64`	Daily notional trading volume (one-sided, USD)

💡 Tip

Filter on block_date for partition pruning, then refine by hour
Much faster than aggregating polymarket_trades hourly
JOIN with polymarket_market_details ON condition_id for market context

⚠️ Warning

Hourly granularity only — for sub-hour analysis, use polymarket_trades

`agent.polymarket_rolling_metrics`

Pre-computed rolling window metrics for Polymarket markets (e.g., 7-day volume, 30-day volume, trailing unique traders). Useful for ranking and screening markets by recent activity without expensive window function queries.

💡 Tip

Pre-computed rolling windows are much faster than manual window functions on trades
Use for market ranking and filtering — then drill into volume_daily or trades for details

⚠️ Warning

Rolling window definitions are fixed — cannot customize the window period
Updated periodically, not real-time

`agent.polymarket_open_interest_daily`

Cumulative open interest per Polymarket condition derived from on-chain events (splits, merges, redemptions, conversions). SPARSE: only has rows on days with events, not every calendar day. Requires gap-fill logic for time series.

Engine: MergeTree | Partition: toYYYYMM(block_date) | ORDER BY: condition_id, block_date

Column	Type	Description
`block_date`	`Date`	Date of the OI change event. SPARSE — not every day has a row.
`condition_id`	`String`	Market condition identifier.
`daily_net_change_raw`	`Int256`
`daily_net_change_usd`	`Float64`
`open_interest_raw`	`Int256`
`open_interest_usd`	`Float64`	Cumulative OI in USD for this condition on this date. Can be negative for neg-risk conditions.

💡 Tip

SPARSE data — use argMax(open_interest_usd, block_date) per condition to gap-fill (carry forward)
Do NOT use HAVING last_oi > 0 — some conditions legitimately have negative OI (neg-risk markets)
Do NOT filter by market resolution status — resolved markets' OI decreases naturally via PayoutRedemption
For global OI: sum(argMax(open_interest_usd, block_date)) across all conditions
Neg-risk markets: individual conditions can have large negative OI — the group total across sibling conditions is correct
Do NOT apply neg_risk correction (sum/count(DISTINCT condition_id)) — the raw sum is already correct

⚠️ Warning

Sparse — only rows on days with OI-affecting events, not a continuous daily series
~5% undercount vs Polymarket subgraph due to ~97K conditions missing from decoded events
Individual neg-risk condition OI can be large negative — always sum across sibling conditions for market-level OI

`agent.polymarket_user_activity`

Per-user trade activity on Polymarket including buy/sell counts, volume, and realized PnL. Aggregated by (address, condition_id) to show each user's activity within each market.

Engine: MergeTree | Partition: toYYYYMM(block_date) | ORDER BY: account, token_id, block_time

Column	Type	Description
`block_date`	`Date`	UTC block date
`block_time`	`DateTime64(3)`	UTC block timestamp
`block_number`	`UInt64`	Block number
`tx_hash`	`String`	Transaction hash
`evt_index`	`UInt32`	Event log index in transaction
`account`	`String`
`token_id`	`String`
`event_type`	`String`
`side`	`String`
`amount`	`Float64`	Amount in display units (decimal-adjusted)
`price`	`Float64`	Token price in USD
`amount_usd`	`Float64`	USD value of transfer

💡 Tip

Filter by address for single-wallet analysis
account = maker follows Paradigm methodology — captures both sides correctly
JOIN with polymarket_market_details ON condition_id for market context
Aggregated per (address, condition_id) — sum across conditions for total user activity

⚠️ Warning

Uses proxy wallet addresses — no mapping to user identities
PnL is realized only — does not include unrealized gains on open positions

`agent.kalshi_market_details`

Kalshi market metadata and snapshot data. Contains market tickers, titles, categories, settlement details, and status. Kalshi uses a three-level hierarchy: series -> events -> markets. MVE (parlay) markets skip the event layer.

Engine: MergeTree | ORDER BY: market_ticker

Column	Type	Description
`market_ticker`	`String`	Unique market identifier (Kalshi)
`event_ticker`	`String`	Parent event ticker. Empty for MVE (parlay) markets.
`event_title`	`String`	Event title
`event_subtitle`	`String`
`title`	`String`	Market title/question text.
`start_time`	`DateTime64(3)`
`end_time`	`DateTime64(3)`
`close_time`	`DateTime64(3)`
`category`	`String`	Market category
`subcategory`	`String`	Market subcategory
`payout_type`	`String`
`status`	`String`	Market status: 'active', 'closed', 'settled', etc.
`last_price`	`Float64`
`total_volume`	`UInt64`	Cumulative total volume
`daily_volume`	`UInt64`	Daily contract volume
`open_interest`	`Float64`	End-of-day open interest (contracts)
`result`	`String`	Market result (if resolved)
`yes_bid`	`Float64`
`yes_ask`	`Float64`
`no_bid`	`Float64`
`no_ask`	`Float64`
`last_day_open_interest`	`Float64`

💡 Tip

Kalshi hierarchy: series -> events -> markets. MVE markets skip the event layer
event_ticker links to events; series_ticker from events links to series
For MVE markets, derive series_ticker from splitByChar('-', ticker)[1]
Use FINAL if the underlying table is ReplacingMergeTree

⚠️ Warning

Large table (55.6M rows) due to historical snapshots — filter by status or date range
MVE (parlay) markets have different structure than regular markets — see Kalshi data model docs
Centralized exchange data — no on-chain verification possible

`agent.kalshi_trades`

Individual Kalshi trade events. Each row represents a single fill on the Kalshi exchange with price, quantity, side, and market ticker. The raw trade-level data source for Kalshi volume analysis.

Engine: ReplacingMergeTree | Partition: toYYYYMM(trade_date) | ORDER BY: ticker, created_time, trade_id

Column	Type	Description
`trade_id`	`String`
`ticker`	`String`
`num_contracts`	`UInt32`
`taker_side`	`String`
`maker_side`	`String`
`yes_price`	`Float64`
`no_price`	`Float64`
`trade_date`	`Date`
`created_time`	`DateTime64(3)`

💡 Tip

Filter on date or created_time for partition pruning
ticker links to kalshi_market_details for market metadata
Price is in cents (0-100 range for binary markets)
count is the number of contracts in the fill

⚠️ Warning

Centralized exchange data — no on-chain verification
Trade history depth depends on Kalshi API availability
No user/wallet attribution — trades are anonymous

`agent.prediction_markets_daily`

Unified daily prediction market volume and open interest across Kalshi and Polymarket. One row per (date, source, category, subcategory). Uses Paradigm-compatible category taxonomy. Only includes dates where BOTH platforms have data to avoid partial comparisons.

💡 Tip

source is 'Kalshi' or 'Polymarket' — filter for single-platform or compare both
Both platforms must have data for a date to appear — gaps mean one platform had no data
notional_volume_usd is one-sided volume in USD
open_interest_usd is cumulative OI in USD
For total market volume: sum both sources

⚠️ Warning

Only dates with data from BOTH platforms — single-platform activity on gap days is lost
Category taxonomy depends on upstream categorization models — some markets may be 'UNKNOWN'
Volume methodology may differ slightly between platforms (both aim for one-sided)

`agent.prediction_markets_matched_markets`

Polymarket-to-Kalshi matched market pairs. Each row is a strict one-to-one (condition_id, market_ticker) pair linking the same event across platforms. Enriched with live volume and OI from both sides. Generated via LLM matching (Grok) with confidence scoring.

💡 Tip

match_type is 'exact' (same question) or 'related' (same event, different angle)
confidence ranges from 75-100 — higher is more reliable
One-to-one mapping — no fan-out or duplication
JOIN with platform-specific tables for additional enrichment

⚠️ Warning

Coverage depends on LLM matching quality — not all markets are matched
Confidence threshold at 75+ — some lower-confidence matches may be excluded
Seed-based — new markets require re-running the matching pipeline

`agent.prediction_markets_matched_daily`

Daily volume and open interest comparison for matched Polymarket-Kalshi market pairs. One row per (condition_id, market_ticker, date) with side-by-side volume and OI from both platforms. The time-series companion to matched_markets.

💡 Tip

Filter on date for partition pruning
Compare polymarket_volume_usd vs kalshi_volume_usd for platform share on matched events
JOIN with prediction_markets_matched_markets for match metadata (confidence, match_type)

⚠️ Warning

Only includes matched markets — unmatched markets on either platform are excluded
Date coverage limited to overlap period where both platforms have data

`agent.polymarket_positions`

Current Polymarket user positions with market context. A custom view that JOINs user_positions_v2 (on-chain position tracking) with market_details for enrichment. Shows open positions with balance, PnL, cost basis, and market metadata. Filters to positions with net_shares > 0.000001 (non-dust).

💡 Tip

Filter by address for wallet-specific portfolio view
holdings_usd = net_shares * value_per_share (current market value of position)
pnl is the realized + unrealized PnL for this position
cost_basis is the total USD spent acquiring the position
avg_buy_price is the volume-weighted average entry price
resolution_status shows if the market has resolved (won/lost/open)

⚠️ Warning

Current state snapshot — does not track historical position changes
Only shows positions with net_shares > 0.000001 — fully closed positions are excluded
Proxy wallet address, not the user's main wallet — address mapping not included

Prediction Markets

Tables

Related Tables

Sample Queries

1. Daily volume by platform

Table Schemas

agent.polymarket_trades

agent.polymarket_market_details

agent.polymarket_events

agent.polymarket_prices_daily

agent.polymarket_prices_hourly

agent.polymarket_prices_latest

agent.polymarket_volume_daily

agent.polymarket_volume_hourly

agent.polymarket_rolling_metrics

agent.polymarket_open_interest_daily

agent.polymarket_user_activity

agent.kalshi_market_details

agent.kalshi_trades

agent.prediction_markets_daily

agent.prediction_markets_matched_markets

agent.prediction_markets_matched_daily

agent.polymarket_positions

`agent.polymarket_trades`

`agent.polymarket_market_details`

`agent.polymarket_events`

`agent.polymarket_prices_daily`

`agent.polymarket_prices_hourly`

`agent.polymarket_prices_latest`

`agent.polymarket_volume_daily`

`agent.polymarket_volume_hourly`

`agent.polymarket_rolling_metrics`

`agent.polymarket_open_interest_daily`

`agent.polymarket_user_activity`

`agent.kalshi_market_details`

`agent.kalshi_trades`

`agent.prediction_markets_daily`

`agent.prediction_markets_matched_markets`

`agent.prediction_markets_matched_daily`

`agent.polymarket_positions`