TOTAL VOLUME:
$61.8b
24H VOL:
$236,615,189
24H TRANSACTIONS:
600,069,390
OPEN INTEREST:
$1,344,513,070
577,941
Markets across
14,530
events
MATCHED EVENTS:
4,090
PLATFORM COVERAGE:
4
Polymarket:
50%
VS.
Kalshi:
50%
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
A men's college basketball game between Harvard Crimson and Princeton Tigers scheduled for February 27, 2026 at 7:00 PM ET at Princeton. Markets cover moneyline (winner), point spread (-3.5 and -4.5), and total points over/under (129.5, 130.5, and 131.5).
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi moneyline market contains a logical contradiction where both possible game outcomes (Princeton win and Harvard win) are specified to resolve to Yes, making the market fundamentally unresolvable and unable to distinguish between outcomes.Hero Tip:
Do not trade the Kalshi moneyline market. It is unresolvable due to contradictory resolution logic. Use Polymarket moneyline instead. Spread and total markets on both platforms are logically sound and consistent with each other.Critical Divergence Points:
Kalshi:
Moneyline market has critical logical error: both Princeton win and Harvard win resolve to Yes, creating an impossible resolution state. No mechanism to differentiate outcomes.Polymarket:
Moneyline market is logically sound: Harvard win resolves to Harvard Crimson, Princeton win resolves to Princeton Tigers. Includes proper edge case handling for postponement (market remains open) and cancellation (50-50 split).
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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