TOTAL VOLUME:
$54.4b
24H VOL:
$234,875,025
OPEN INTEREST:
$1,205,330,693
501,301
Markets across
13,585
events
MATCHED EVENTS:
1,825
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
Mercer Bears vs. Furman Paladins (W)
Volume:
$22,560
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers the women's college basketball matchup between Mercer Bears and Furman Paladins scheduled for March 5, 2026 at 4:45 PM ET. Markets across Polymarket and Kalshi are pricing the outcome of this single game, with resolution tied to the final score including overtime.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi market contains a logical contradiction where both possible game outcomes (Mercer win and Furman win) are stated to resolve to Yes, making the market fundamentally unresolvable as a binary contract.Hero Tip:
Avoid trading Kalshi until the resolution language is corrected. The market as written cannot distinguish between outcomes. Polymarket is the reliable reference; its binary winner-name resolution is clear and executable.Critical Divergence Points:
- Polymarket: Clean binary resolution: market resolves to the name of the winning team (Mercer Bears or Furman Paladins). Cancellation with no makeup resolves 50-50. Postponement keeps market open. Source: NCAA.org final score including overtime.
- Kalshi: Contradictory resolution logic: states both Mercer win and Furman win resolve to Yes. No explicit No outcome or cancellation clause provided. This creates an unresolvable binary market.
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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