Probalytics Probalytics
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For Researchers & Data Scientists

Cross-platform
prediction market analytics

Compare forecasting accuracy across Polymarket, Kalshi & more. One unified dataset, no data wrangling. Query with SQL, export to Parquet.

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41M+

Markets indexed

907M+

Trades tracked

5+

Years of history

2

Platforms unified

The Power of Unified Data

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
Calibration ComparisonSample data
Polymarket0.92 accuracy
Kalshi0.89 accuracy

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,
  status,
  count() as market_count
FROM markets FINAL
WHERE close_date < now()
GROUP BY platform, status
ORDER BY market_count DESC

Data Access

Export in your preferred format

Parquet

For Pandas, Spark, DuckDB

CSV

For Excel, R, general use

SQL

Direct ClickHouse queries

API

REST API 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?

SQL Access

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
SQL Console
-- Compare market activity across platforms
SELECT
  platform,
  count() as market_count,
  sum(size) as total_volume,
  avg(normalized_price) as avg_price
FROM fills
WHERE timestamp > now() - INTERVAL 30 DAY
GROUP BY platform
ORDER BY total_volume DESC
Access the Dataset

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Access the most comprehensive cross-platform prediction market dataset.

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