Predictefy vs CrossOdds: Best Arbitrage Scanner (2026)

Comparison checked October 27, 2026.

What makes Predictefy the stronger scanner foundation?

Predictefy gives a strategy access to the records behind its decisions. You can discover markets across venues, examine available book data, retain timestamps and provenance, and test how a proposed position behaves at your chosen quantity.

CrossOdds packages several ready-made discovery tools together. Its public site describes cross-platform arbitrage scanning, large-trade alerts and a Weather Edge Finder. Its developer feed exposes filters for each signal type, so it can also serve a bot or dashboard. The choice is about how much of that workflow you want to assemble and control yourself.

Read a scanner's output before acting on it

CrossOdds distinguishes gross spread from estimated net spread in its response. It also exposes an LLM confidence score and warnings about a pair. Those fields are useful inputs for review, especially when questions differ between the two venues.

For a practical comparison, choose one matched event and a fixed contract quantity. Save each venue's asks, available sizes and resolution terms at the observation time. Then calculate the cost of the complementary positions, applying the relevant fees and your execution route's additional costs.

Predictefy's arbitrage qualification checks depth, venue fees and resolution equivalence at that requested size. Current market status and non-synthetic asks also matter. Your strategy can use those checks alongside its own exposure and execution rules instead of turning every displayed price gap into an order.

The cross-venue guide explains the distinction between a stored indicative pair difference and the live conditions used for qualification. Keep that distinction in your logs so an alert can be reconstructed later.

Weather edges and whale signals need their own tests

A weather alert compares a forecast with a market price. Its usefulness depends on the station, measurement period, threshold, forecast run and settlement source. A large trade gives you an observation about activity. Each can inform a strategy, but each needs a different evaluation process.

If you already use CrossOdds weather alerts, take one historical alert and record exactly what it meant. Was it the day's maximum temperature at the named station? Which forecast timestamp produced the probability? Was the relevant market still open, and what size was available?

A Predictefy integration can provide the normalized market-data side of your own workflow. Keep your forecast model and its versioned inputs in your strategy, then use market and book observations to assess the trade you intend. That makes it easier to compare model quality separately from execution quality.

Compare the bill for the work you need

CrossOdds Pro includes its full feed and REST API access. The API page publishes 60 requests a minute and up to ten keys. If the packaged Kalshi and Polymarket signals cover your use case, evaluate that product on its own terms rather than dividing a subscription price by an assumed number of opportunities.

Predictefy's Free tier is suitable for evaluating normalized reads and matching. Builder at $48.88 a month adds a larger credit allowance and bulk access. Pro at $149 includes the arbitrage feed and history replay. Credits are weighted by operation, so count your expected calls and streams when estimating usage.

For a commercial product built with Predictefy, discuss Enterprise terms before launch. A paid evaluation plan and a commercial data contract are separate buying decisions.

How to evaluate a switch from CrossOdds

Start with a small watchlist of events you already follow. Store the existing signal alongside the matched market IDs, timestamps and book observations from Predictefy. Keep the original signal category so a weather-model edge does not get mixed into a comparison of complementary contracts.

Paper trade the resulting rules and review rejected candidates as well as accepted ones. Once the data checks and reconciliation are consistent, assess the supported client-signed execution flow for the venues you intend to use. This gives you a migration based on your strategy's behavior rather than a scanner's headline return.