Green Bay Phoenix vs. Purdue Fort Wayne Mastodons (W)
Volume:
$7,426
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 Green Bay Phoenix and Purdue Fort Wayne Mastodons scheduled for February 28, 2026 at 2:00 PM ET. Both Polymarket and Kalshi are offering prediction markets on the outcome of this matchup, with resolution based on the final score including overtime.
Kalshi's resolution criteria contains a logical contradiction: both a Purdue Fort Wayne win and a Green Bay win are stated to resolve to YES, making the market unresolvable as a binary outcome market. Polymarket's logic is sound and unambiguous.
Hero Tip:
Avoid trading on Kalshi's version. The market structure is broken and will face settlement failure. Polymarket's market is the only reliably resolvable option.
Critical Divergence Points:
Polymarket: Clear binary winner-take-all logic with explicit mutually exclusive outcomes. Green Bay win = 'Green Bay Phoenix' resolution, Purdue Fort Wayne win = 'Purdue Fort Wayne Mastodons' resolution. Postponement keeps market open; cancellation without makeup = 50-50 split. Resolution based on final score including overtime.
Kalshi: Logically incoherent dual-YES resolution. States both 'If Purdue Fort Wayne wins...resolves to Yes' and 'If Green Bay wins...resolves to Yes', creating identical outcomes for mutually exclusive events. This violates 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.
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