Grambling State Tigers vs. Alabama State Hornets (W)
Volume:
$107,357
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 Grambling State Tigers and Alabama State Hornets scheduled for March 12, 2026 at 5:30 PM ET. The markets resolve based on which team wins the game, with provisions for postponement, cancellation, and overtime.
Kalshi's resolution logic contains a logical contradiction: both possible game outcomes (Alabama State wins OR Grambling State wins) are mapped to the same resolution (Yes), making the No outcome impossible and the market fundamentally unresolvable.
Hero Tip:
Do not trade Kalshi's version until clarification is provided. The market as stated cannot distinguish between outcomes. Polymarket's binary structure is logically sound and should be treated as the authoritative version. Request Kalshi to confirm whether one outcome should resolve to No, or if the market is actually a yes-no on whether the game occurs.
Critical Divergence Points:
Polymarket: Binary winner-prediction market with clear mutually exclusive outcomes. Resolves to team name of winner. Handles edge cases: postponement keeps market open until completion; cancellation with no makeup resolves 50-50. Final score including overtime determines result.
Kalshi: Contradictory dual-Yes resolution. Both "If Alabama St. wins" and "If Grambling St. wins" map to Yes. This creates logical impossibility: every possible game outcome resolves to Yes, leaving no valid No scenario.
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.
Follow the signals, not the noise
Get insights on market conviction, notable shifts, and what the data is quietly signaling.