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 professional Euroleague basketball matchup between Paris Basketball and ASVEL Lyon-Villeurbanne scheduled for March 12, 2026 at 4:00 PM EDT. The markets track the binary outcome of which team wins the game.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi market contains a logical contradiction where both possible game outcomes (ASVEL win and Paris win) are mapped to the same resolution value (Yes), making the market fundamentally unresolvable. Polymarket uses standard binary outcome mapping.Hero Tip:
This is a critical data integrity failure on Kalshi. The market as written cannot be settled because there is no path to a No resolution. Contact Kalshi immediately to confirm whether the second condition should resolve to No. Until corrected, treat Kalshi as non-tradeable. Polymarket is safe to trade.Critical Divergence Points:
Kalshi:
Both conditional branches resolve to Yes. ASVEL win = Yes, Paris win = Yes. This creates an impossible binary market where no outcome can resolve to No.Polymarket:
Standard binary structure: Paris win resolves to Paris Basketball, ASVEL win resolves to ASVEL Lyon-Villeurbanne. Includes postponement and cancellation edge cases with 50-50 split for full cancellation.
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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