This event is for the CBB game between TCU Horned Frogs and Ohio State Buckeyes on March 19 at 12:00 AM ET.
If the game is postponed, this market will remain open until the game has been completed.
If the game is canceled entirely, with no make-up game, this market will resolve 50-50.
Kalshi settles on the first-half result of the TCU vs. Ohio State men's college basketball game, while Polymarket settles on the full-game result including overtime. These represent fundamentally different events with different resolution scopes.
Hero Tip:
If you trade on Kalshi, you are betting on only the first half of regulation; if you trade on Polymarket, you are betting on the entire game including any overtime. A team that wins the first half may lose the full game, causing opposite resolutions on the two platforms for the same matchup.
Critical Divergence Points:
Kalshi:
Outlier: Kalshi resolves based on the first-half result only. The market states 'If Ohio St. is the winner of the first half of regulation time... then the market resolves to Yes' and covers all three first-half outcomes (Ohio State win, TCU win, or tie), each resolving to Yes. This is a first-half-only settlement scope.
Polymarket:
Aligned with standard full-game settlement: Polymarket resolves based on the final score of the complete game including any overtime periods. The moneyline market states 'The result will be determined based on the final score including any overtime periods,' and all spread and over/under markets use identical full-game logic. This is a full-game settlement scope.
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.