California-San Diego Tritons vs. TCU Horned Frogs (W)
Volume:
$625,850
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This market resolves based on the outcome of the NCAA Division I Women's Basketball game between UC San Diego Tritons and TCU Horned Frogs scheduled for March 20, 2026 at 12:00 PM ET. The winner of the game determines the market resolution, with the result based on the final score including any overtime periods.
Kalshi resolves YES for both possible outcomes (San Diego win OR TCU win), creating a logical contradiction that makes the market fundamentally unresolvable. Polymarket correctly resolves to a single winner (San Diego Tritons or TCU Horned Frogs) based on game result, which is the standard sports betting logic.
Hero Tip:
Do NOT trade on Kalshi — the market rules state it resolves YES if San Diego wins AND YES if TCU wins, meaning it resolves YES regardless of outcome. This is a data integrity failure. Polymarket is the only tradeable market in this group with coherent resolution logic.
Critical Divergence Points:
Kalshi: Outlier: Market resolves YES in both scenarios — 'If UC San Diego wins...then the market resolves to Yes' AND 'If TCU wins...then the market resolves to Yes' — creating a logical impossibility where every outcome triggers YES resolution.
Polymarket: Distinct stance: Market resolves to exactly one of two mutually exclusive outcomes: 'California-San Diego Tritons' if San Diego wins, or 'TCU Horned Frogs' if TCU wins, with postponement and cancellation edge cases handled separately.
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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