Louisiana-Lafayette Ragin' Cajuns vs. Georgia State Panthers (W)
Volume:
$442,568
Markets
Outcome
Chance %
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Liquidity
Volume
24h
7d
Open Interest
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Description
This event group covers a women's college basketball game between Louisiana-Lafayette Ragin' Cajuns and Georgia State Panthers scheduled for February 27, 2026 at 5:00 PM ET. Markets across Polymarket and Kalshi are betting on the winner of this matchup.
Kalshi's resolution logic is logically contradictory, stating both Georgia State win and Louisiana win resolve to Yes, making the market fundamentally unresolvable. Polymarket uses standard binary winner-take-all logic.
Hero Tip:
Avoid trading Kalshi until the platform clarifies whether this is a game-completion market (both outcomes Yes) or a winner-pick market (one Yes, one No). Polymarket is safe to trade based on standard sports betting resolution.
Critical Divergence Points:
Polymarket: Binary winner-take-all market. Louisiana-Lafayette win resolves to Louisiana-Lafayette Ragin' Cajuns; Georgia State win resolves to Georgia State Panthers. Includes postponement (market stays open) and cancellation (50-50 split) provisions. Key Quote: If the Louisiana-Lafayette Ragin' Cajuns win, the market will resolve to Louisiana-Lafayette Ragin' Cajuns.
Kalshi: Logically incoherent dual-Yes resolution. Both If Georgia St. wins and If Louisiana wins explicitly resolve to Yes. No No outcome is defined. Key Quote: If Georgia St. wins... then the market resolves to Yes. If Louisiana wins... then the market resolves to Yes.
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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