TOTAL VOLUME:
$61.7b
24H VOL:
$229,178,007
24H TRANSACTIONS:
600,069,390
OPEN INTEREST:
$1,336,753,738
577,196
Markets across
14,485
events
MATCHED EVENTS:
4,077
PLATFORM COVERAGE:
4
Polymarket:
50%
VS.
Kalshi:
50%
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a men's college basketball game between Pittsburgh Panthers and Stanford Cardinal scheduled for February 25, 2026 at 8:00 PM ET at Stanford. Markets span moneyline (winner), multiple spread variations, and over/under total points across Kalshi and Polymarket platforms.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi moneyline market contains a logical contradiction where both possible game outcomes (Pittsburgh win and Stanford win) are specified to resolve to Yes, making the market fundamentally unresolvable and creating a guaranteed profit scenario.Hero Tip:
Do not trade the Kalshi moneyline. All Polymarket markets (moneyline, spreads, totals) and all Kalshi spread/total markets are internally consistent and resolvable. Treat Kalshi moneyline as a data error and exclude it from any position reconciliation.Critical Divergence Points:
Kalshi:
Moneyline market states both Pittsburgh win and Stanford win resolve to Yes, creating logical impossibility. Spreads and totals are correctly specified with binary outcomes.Polymarket:
All markets (moneyline, spreads, totals) use mutually exclusive binary outcomes. Moneyline resolves to team name, spreads to team name, totals to Over/Under. All logic is sound.
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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