Missouri State Bears vs. Middle Tennessee Blue Raiders (W)
Volume:
$36,314
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a women's college basketball game between Missouri State Bears and Middle Tennessee Blue Raiders scheduled for March 7, 2026 at 2:00 PM ET. Markets resolve based on which team wins the game, with provisions for postponement, cancellation, and overtime.
Kalshi market contains a logical contradiction where both possible game outcomes (Missouri State wins OR Middle Tennessee wins) are mapped to the same resolution value (Yes), making the market fundamentally unresolvable and creating data integrity failure.
Hero Tip:
Avoid trading Kalshi until platform clarifies the intended resolution logic. The market as currently described cannot distinguish between outcomes. Polymarket is the reliable reference for this matchup.
Critical Divergence Points:
Polymarket: Binary winner-take-all structure with clear conditional logic. Missouri State win resolves to Missouri State Bears; Middle Tennessee win resolves to Middle Tennessee Blue Raiders. Includes provisions for postponement (market stays open) and cancellation without makeup (50-50 split). Resolution based on final score including overtime.
Kalshi: Contradictory dual-Yes mapping. Both conditional branches (Middle Tennessee wins OR Missouri State wins) resolve to Yes, leaving no logical path to No resolution. This violates basic binary market structure and makes the market unresolvable.
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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