Northeastern Huskies vs. North Carolina A&T Aggies (W)
Volume:
$565,053
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers the women's college basketball game between Northeastern Huskies and North Carolina A&T Aggies scheduled for February 20, 2026 at 7:00 PM ET. Markets across platforms are betting on the binary outcome: which team wins the game.
Kalshi's resolution logic contains a logical contradiction where both possible outcomes (Northeastern win and North Carolina A&T win) are mapped to the same resolution state (Yes), making the market fundamentally unresolvable and creating a data integrity failure.
Hero Tip:
Treat Polymarket as the authoritative resolution source for this event. Kalshi's market is logically broken and should not be traded until the platform corrects the contradiction. If you hold Kalshi positions, seek clarification from Kalshi support before settlement.
Critical Divergence Points:
Polymarket: Sound binary logic: Northeastern win resolves to Northeastern Huskies; North Carolina A&T win resolves to North Carolina A&T Aggies. Handles postponement (market stays open) and cancellation without makeup (50-50 split). Key Quote: If the Northeastern Huskies win, the market will resolve to Northeastern Huskies.
Kalshi: Contradictory logic: Both Northeastern win and North Carolina A&T win resolve to Yes, creating logical impossibility. No differentiation between outcomes. Key Quote: If Northeastern wins...resolves to Yes. If North Carolina A&T wins...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.
Follow the signals, not the noise
Get insights on market conviction, notable shifts, and what the data is quietly signaling.