Gardner-Webb Runnin' Bulldogs vs. Longwood Lancers (W)
Volume:
$21,641
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 Gardner-Webb Runnin' Bulldogs and Longwood Lancers scheduled for February 18, 2026 at 7:00 PM ET. Markets on Polymarket resolve based on the winner (or 50-50 if canceled), while Kalshi's market structure creates a logical inconsistency in its resolution criteria.
Kalshi's market contains a logical contradiction where both possible outcomes (Longwood win and Gardner-Webb win) are stated to resolve to Yes, making the market fundamentally unresolvable and creating a data integrity failure.
Hero Tip:
Do not trade on Kalshi's version of this market. The resolution logic is contradictory and unresolvable. Use Polymarket exclusively, which has clear binary resolution: one team wins and resolves to that team's name, or the game is canceled and resolves 50-50.
Critical Divergence Points:
Polymarket: Clear binary winner-take-all structure. Gardner-Webb win resolves to Gardner-Webb; Longwood win resolves to Longwood. Postponement keeps market open; cancellation without makeup resolves 50-50. Resolution based on final score including overtime. Source: NCAA.com.
Kalshi: Logically contradictory resolution criteria. Both Longwood winning and Gardner-Webb winning are stated to resolve to Yes, creating a tautology where all outcomes produce the same result. This violates basic binary market logic and makes settlement impossible.
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.