Prediction markets face credibility challenges following a significant forecasting failure in Wisconsin's primary election. Major platforms Kalshi and Polymarket dramatically underestimated David Crowley's competitive strength, assigning Francesca Hong a 95% victory probability hours before the upset. This miscalculation highlights inherent limitations in algorithmic prediction models and raises questions about market efficiency, data quality, and the reliability of betting-based forecasting for electoral outcomes.

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