Central Arkansas Bears vs. Jacksonville Dolphins (W)
Volume:
$29,156
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers the outcome of a women's college basketball game between Central Arkansas Bears and Jacksonville Dolphins scheduled for March 7, 2026 at 12:30 PM ET. The markets across platforms are designed to resolve based on which team wins the game, with provisions for postponement and cancellation scenarios.
Kalshi's resolution rules contain a logical contradiction where both possible game outcomes (Jacksonville win and Central Arkansas win) are stated to resolve to Yes, making the market fundamentally unresolvable. Polymarket provides clear, mutually exclusive binary resolution.
Hero Tip:
Avoid trading on Kalshi until the platform clarifies the intended resolution logic. The current wording violates basic binary market logic. Polymarket's market is resolvable and should be treated as the reference standard for this event.
Critical Divergence Points:
Kalshi: Contradictory logic: states both Jacksonville win and Central Arkansas win resolve to Yes. Quote: 'If Jacksonville wins...resolves to Yes. If Central Arkansas wins...resolves to Yes.' This is logically impossible for a single binary market.
Polymarket: Clear winner-takes-all binary resolution. Quote: 'If Central Arkansas Bears win, resolve to Central Arkansas Bears. If Jacksonville Dolphins win, resolve to Jacksonville Dolphins.' Includes 50-50 cancellation clause if game is canceled with no makeup.
Our PredictionHero Resolution Divergence Alerts (RDA) are there to help users identify potential differences across platforms. They do not replace or supersede the official rules and description of any prediction market. Users are solely responsible for reviewing and understanding the applicable rules and resolution criteria before placing any trade or bet. If you notice a potential inconsistency, discrepancy, or error in an alert, please report it to our team so we can review and improve the accuracy of our data.
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