TOTAL VOLUME:
$53.9b
24H VOL:
$231,847,320
OPEN INTEREST:
$1,314,157,835
499,417
Markets across
14,310
events
MATCHED EVENTS:
1,754
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
Seton Hall Pirates vs. Butler Bulldogs (W)
Volume:
$103,061
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 Seton Hall Pirates and Butler Bulldogs scheduled for March 1, 2026 at 2:30 PM ET. Markets on Polymarket and Kalshi are tracking the binary outcome of which team wins the game.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi's resolution logic contains a logical contradiction: both a Butler win and a Seton Hall win are stated to resolve to Yes, making the market fundamentally unresolvable and creating a data integrity failure.Hero Tip:
Avoid trading on Kalshi until the platform corrects the resolution logic. Polymarket's binary structure is logically sound and should be your reference. Request clarification from Kalshi on whether one team should resolve to No instead.Critical Divergence Points:
- Polymarket: Clean binary outcome: Seton Hall win resolves to Seton Hall Pirates, Butler win resolves to Butler Bulldogs. Postponements keep market open; cancellations with no makeup resolve 50-50. Resolution based on final score including overtime.
- Kalshi: Contradictory logic: states both Butler win and Seton Hall win resolve to Yes, creating logical impossibility. No specification of No outcome condition or cancellation/postponement handling.
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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