Open Data

Political Prediction Markets Dataset

Bell tracks every political prediction market on Polymarket and Kalshi, updated daily. Request access to the full dataset below.

Data Glossary Updated Daily

political_markets_master.csv — One row per market outcome. All markets are classified into 15 political categories.

Identifiers

FieldTypeDescription
market_idstringUnique identifier for the market (platform-specific)
platformstringSource platform: "polymarket" or "kalshi"
pm_condition_idstringPolymarket condition ID (for price lookups)
pm_token_id_yesstringPolymarket YES token ID
pm_token_id_nostringPolymarket NO token ID
k_event_tickerstringKalshi event ticker symbol

Market Details

FieldTypeDescription
questionstringFull market question text
political_categorystringOne of 15 categories: Electoral, Monetary Policy, Party Politics, Military Security, International, Appointments, Regulatory, Political Speech, etc.
volume_usdfloatTotal trading volume in USD
tagsstringComma-separated list of market tags from the platform
date_addeddatetimeWhen the market was first added to our database

Electoral Markets (subset)

FieldTypeDescription
election_typestringType of election: Presidential, Senate, House, Governor, Primary, etc.
countrystringCountry of election
locationstringState/region (for sub-national elections)
officestringOffice being contested (e.g., "President", "Senate", "House")
election_yearfloatYear of the election (e.g., 2024.0)
is_primarybooleanWhether the market is for a primary election (vs. general)
partystringPolitical party: "R", "D", or null
candidatestringCandidate name (if applicable)
election_eve_pricefloatMarket price at 00:00 UTC on election day

Resolution & Accuracy

FieldTypeDescription
is_closedbooleanWhether market has stopped trading
resolution_outcomefloatResolution: 1.0 if outcome occurred, 0.0 if not, null if unresolved
winning_outcomestringThe outcome that won (e.g., "Yes", "Trump")
trading_close_timedatetimeWhen trading closed
scheduled_end_timedatetimeScheduled market end time

Platform-Specific Fields (Kalshi)

FieldTypeDescription
k_last_pricefloatMost recent trade price (0-1)
k_yes_bidfloatCurrent best bid for YES
k_yes_askfloatCurrent best ask for YES
k_volume_contractsintTotal contracts traded
k_open_interestintCurrent open interest
k_liquidityfloatPlatform-reported liquidity measure
k_statusstringMarket status: "active", "closed", "settled"
k_resultstringSettlement result: "yes", "no", null

Methodology

How we measure prediction accuracy and why the choice of when to sample prices is a first-order decision.

Brier Score Calculation

The Brier score measures forecast accuracy: (prediction − outcome)². A score of 0 is perfect; 0.25 is equivalent to random guessing. We calculate Brier scores at multiple time horizons (60, 30, 14, 7, 3, 1 days before the event) and, for electoral markets, using the election eve price.

Election Eve Price (Electoral Markets)

For electoral markets, we use the market price at 00:00 UTC on election day as our primary forecast evaluation price. We call this the election eve price. For U.S. elections on November 5, this corresponds to approximately 7–8 PM Eastern on November 4—before any polls have closed.

This is an event-anchored truncation rule, not a resolution-anchored one. The distinction matters because Polymarket and Kalshi settle contracts at different speeds after outcomes are known (24–48 hours for Polymarket, 3–12 hours for Kalshi). Any truncation rule defined relative to resolution time mixes genuine forecasts with post-outcome convergence and introduces a platform-specific bias into cross-platform comparisons.

The election eve price avoids this. The same election produces the same measurement timestamp on both platforms. The price reflects what the market believed before the outcome was known—which is what forecast accuracy should measure. For full discussion, see our methodological note.

Reference Dates by Market Type

Different market types use different reference dates, reflecting the information available to researchers and the settlement characteristics of each platform:

Market Type Reference Date Rationale
Electoral Markets 00:00 UTC on election day Event-anchored. Uses verified election dates from our lookup table. Price is queried at exact UTC midnight via the Dome API. This is pre-outcome for all U.S. elections and unambiguous across platforms.
Non-Electoral (Polymarket) trading_close_time − 2 days Resolution-anchored with offset. Polymarket markets typically close 24–48 hours after event outcomes are known. The 2-day offset is a conservative pre-event estimate.
Non-Electoral (Kalshi) trading_close_time − 1 day Resolution-anchored with offset. Kalshi markets settle within 3–12 hours. The 1-day offset provides a conservative pre-event window.

Note: For non-electoral markets, we do not have event dates and must rely on resolution-relative offsets. These offsets are less precise than event-anchored dates and may include some post-outcome trading, particularly on Polymarket. We document this limitation transparently. Where possible, we use the electoral approach as the benchmark.

Platform Settlement Windows

Our methodology accounts for documented platform settlement procedures:

  • Polymarket: Per their documentation, "Markets are settled within 24 to 48 hours after the event outcome becomes definitively known." [docs]
  • Kalshi: Markets settle via automated processes typically within 3–12 hours of outcome determination. [settlement sources]

Price Data Sources

Election eve prices are queried from the Dome API at exact Unix timestamps (UTC midnight on election day). This provides point-in-time prices rather than daily candle approximations. For time-horizon Brier scores (1d, 7d, etc.), we use daily price observations at 00:00 UTC intervals.

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Citation

If you use this dataset in your research, please cite:

Hall, A. B., & Paschal, E. J. (2026). Bellwether Political Prediction Markets Dataset [Data set]. Stanford Graduate School of Business. https://elliotjames-paschal.github.io/Bellwether/data.html

BibTeX:

@misc{hall2026bellwether,
  author       = {Hall, Andrew B. and Paschal, Elliot J.},
  title        = {Bellwether Political Prediction Markets Dataset},
  year         = {2026},
  publisher    = {Stanford Graduate School of Business},
  howpublished = {\url{https://elliotjames-paschal.github.io/Bellwether/data.html}}
}