Southern Indiana Screaming Eagles vs. Western Illinois Leathernecks (W)
Volume:
$23,665
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 Southern Indiana Screaming Eagles and Western Illinois Leathernecks scheduled for February 19, 2026 at 6:00 PM ET. Markets on Polymarket and Kalshi are tracking the winner of this matchup, with different resolution mechanics across platforms.
Kalshi's resolution logic contains a fundamental contradiction: both Southern Indiana winning AND Western Illinois winning are specified to resolve to YES, making the market unresolvable. Polymarket uses standard binary winner-take-all logic.
Hero Tip:
Do not trade on Kalshi for this event. The market structure is broken and cannot be settled correctly. Polymarket is the only platform with valid, resolvable logic for this matchup.
Critical Divergence Points:
Polymarket: Binary winner-take-all resolution with clear outcome mapping. Southern Indiana win resolves to Southern Indiana, Western Illinois win resolves to Western Illinois. Includes contingency rules: postponement keeps market open until completion, cancellation without makeup resolves 50-50. Resolution based on final score including overtime.
Kalshi: Contradictory dual-YES mapping. Both outcomes specified to resolve YES: 'If Southern Indiana wins...resolves to Yes' AND 'If Western Illinois wins...resolves to Yes'. This logical impossibility makes the market unresolvable and prevents proper settlement.
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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