TOTAL VOLUME:
$54.4b
24H VOL:
$216,099,358
OPEN INTEREST:
$1,189,677,720
500,754
Markets across
13,672
events
MATCHED EVENTS:
1,801
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
Hapoel Tel Aviv vs. Olimpia Milano
Volume:
$167,393
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a Euroleague basketball game between Hapoel Tel Aviv and Olimpia Milano scheduled for February 26, 2026 at 2:05 PM ET. Markets on Polymarket and Kalshi are tracking the outcome of this professional basketball matchup.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi market has a logical contradiction where both possible game outcomes (Olimpia Milano win OR Hapoel Tel Aviv win) resolve to Yes, making the No outcome impossible and rendering the market fundamentally unresolvable.Hero Tip:
Avoid trading on Kalshi until the platform issues a clarification or amendment. The market as written cannot be settled fairly. Polymarket's binary win/loss structure is logically sound and should be the reference market.Critical Divergence Points:
- Polymarket: Clean binary outcome: Hapoel Tel Aviv win resolves to Hapoel Tel Aviv, Olimpia Milano win resolves to Olimpia Milano. Postponement keeps market open; cancellation with no makeup resolves 50-50. Source: Euroleague Basketball official site.
- Kalshi: Logical contradiction: Both Olimpia Milano win AND Hapoel Tel Aviv win resolve to Yes. No condition resolves to No, making the market incoherent and unresolvable as drafted.
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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