Cross-platform
prediction market analytics
Compare forecasting accuracy across Polymarket, Kalshi & more. One unified dataset, no data wrangling. Query with SQL, export to Parquet.
Get Started32M+
Markets indexed
812M+
Trades tracked
5+
Years of history
2
Platforms unified
Which platform is better calibrated?
Run one query to find out. No manual data cleaning, no ETL pipelines, no schema mapping. We've already normalized everything.
- Same events tracked across platforms with unified IDs
- Resolution outcomes normalized for accurate comparison
- Cross-platform price history at every timestamp
- Event metadata and categorization included
Cross-platform calibration comparison - one query, instant results
SQL Access
Research query examples
Direct SQL access to cross-platform data via ClickHouse
Calibration by platform
Compare forecasting accuracy across all platforms
SELECT platform, FLOOR(probability * 10) / 10 as bucket, AVG(resolved_yes) as actual_rate, COUNT(*) as n FROM unified_markets WHERE resolved_at IS NOT NULL GROUP BY platform, bucket
Data Access
Export in your preferred format
Parquet
For Pandas, Spark, DuckDB
CSV
For Excel, R, general use
SQL
Direct ClickHouse queries
API
REST & streaming endpoints
Use Cases
What researchers build with Probalytics
Forecasting Calibration
Study how well prediction markets are calibrated. Do 70% predictions resolve "yes" 70% of the time?
Market Efficiency
Analyze how quickly markets incorporate new information. Compare across platforms.
Crowd Wisdom
Research information aggregation dynamics. How do prediction markets outperform polls?
Cross-Platform Comparison
Compare the same events across all platforms. Which is most accurate?
Query data directly with SQL
Connect to our ClickHouse database directly. Run complex analytical queries, export results in any format.
- Direct SQL queries to ClickHouse
- Export results as CSV, JSON, or Parquet
- REST API for programmatic access
-- Compare calibration ACROSS platforms - one query
SELECT
platform,
FLOOR(probability * 10) / 10 as bucket,
AVG(resolved_yes) as actual_rate,
COUNT(*) as n
FROM unified_markets
WHERE resolved_at IS NOT NULL
GROUP BY platform, bucket
ORDER BY platform, bucket
-- Results: instant cross-platform comparison!Ready to start your research?
Access the most comprehensive cross-platform prediction market dataset.
Sign up now