TOTAL VOLUME:
$54.1b
24H VOL:
$198,735,462
24H TRANSACTIONS:
527,413,651
OPEN INTEREST:
$1,238,334,809
499,092
Markets across
13,695
events
MATCHED EVENTS:
1,769
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
Real Madrid vs. Valencia
Volume:
$277,651
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a professional Euroleague basketball game between Real Madrid and Valencia Basket scheduled for March 12, 2026 at 3:45 PM EDT. Both Polymarket and Kalshi have created markets on the outcome of this single game.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi market contains a logical contradiction where both possible outcomes (Valencia win and Real Madrid win) are stated to resolve to Yes, making the market unresolvable. Polymarket provides coherent binary logic.Hero Tip:
Avoid trading Kalshi until resolution criteria are corrected. Polymarket is the only platform with valid, executable resolution logic for this event.Critical Divergence Points:
- Polymarket: Binary outcome resolution: Real Madrid win resolves to Real Madrid, Valencia win resolves to Valencia. Postponement keeps market open; cancellation without makeup resolves 50-50. Source: Euroleague Basketball official site.
- Kalshi: Logical contradiction: Both "If Valencia Basket wins... resolves to Yes" AND "If Real Madrid wins... resolves to Yes" are stated. This creates an impossible resolution state where the market cannot distinguish between outcomes.
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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