Predictions.io Launches Free Tools to Compare Odds Across Prediction Market Venues

Prediction markets have surged in popularity and complexity, attracting both unprecedented trading volumes and growing regulatory attention. In this expanding landscape, a significant challenge has emerged: identical event questions listed on different platforms often carry notably divergent odds.

Addressing this fragmentation, Predictions.io has introduced a suite of free analytical tools designed to aggregate and compare prediction market data across leading venues including Kalshi, Polymarket, and Manifold. The platform currently monitors over 9,700 event markets encompassing diverse categories such as U.S. politics, economics, cryptocurrency, sports, and geopolitics.

The timing of Predictions.io’s launch coincides with record-breaking combined trading volumes. For instance, in July 2026, Kalshi, Polymarket, and Polymarket US collectively recorded more than $50.5 billion in volume, with Kalshi alone representing nearly three-quarters of that total. However, this growth has not been without scrutiny: regulatory bodies in New York City and Washington have initiated probes and legal actions targeting these platforms, raising questions about market operations and compliance.

Despite the regulatory spotlight, one less explored but critical issue is the inconsistency in pricing for equivalent event questions across different marketplaces. Predictions.io’s data reveals that questions identically phrased on Kalshi and Polymarket can differ by as much as 8.5 percentage points. For example, forecasts on midterm election outcomes—phrased as “Blue tsunami in 2026?”—show a 44.5% implied probability on Polymarket versus 36.0% on Kalshi. Similar discrepancies appear on related queries like “Blue wave in 2026?”

These pricing gaps extend beyond isolated cases. Examining a broader sample of directly comparable binary markets, the median difference in implied probabilities exceeds four percentage points, with nearly half of the paired markets deviating by five points or more. Such disparities complicate the interpretation of market signals, as the notion of a definitive “market-implied probability” becomes ambiguous when venue-specific odds diverge substantially.

Predictions.io’s platform remedies this by consolidating market data into a unified interface, enabling users to examine the same question side by side across multiple exchanges. This transparency allows traders, analysts, and journalists to better understand the range of market sentiment rather than relying on a single data point.

Complementing the comparative framework, Predictions.io offers two specialized calculators. The Fee Calculator enables users to input trades and receive a detailed breakdown of fees, total costs, and effective prices across venues, accounting for varying fee structures such as Kalshi’s taker formula and maker discounts versus Polymarket’s fee-free model. Meanwhile, the Odds Converter facilitates the translation of American, decimal, and fractional odds into implied probabilities and prediction market prices, stripping out the vig to clarify the underlying probability.

These tools are accessible via Predictions.io’s website, including dedicated pages for direct venue comparisons and live updates on U.S. political markets. Importantly, Predictions.io operates solely as an independent aggregator and comparison service, abstaining from market-making, brokerage, or investment advisory roles.

As prediction markets continue to evolve and attract regulatory oversight, platforms like Predictions.io serve a vital role in enhancing market transparency and equipping users with clearer insights into how odds vary across competing venues. By illuminating the often-overlooked disparities in pricing, this initiative contributes to a more nuanced understanding of prediction market dynamics without endorsing any particular market position.

While the broader implications of regulatory investigations remain unfolding, and precise impacts on market structure are yet to be fully realized, the emergence of tools that facilitate cross-market comparisons marks a significant step forward in the maturation of prediction market ecosystems.