TOTAL VOLUME:
$54.6b
24H VOL:
$283,259,638
OPEN INTEREST:
$1,235,549,422
505,521
Markets across
13,661
events
MATCHED EVENTS:
1,892
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
Harvard Crimson vs. Brown Bears (W)
Volume:
$50,264
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers the women's college basketball game between Harvard Crimson and Brown Bears scheduled for February 14, 2026 at 5:00 PM ET at Brown's venue. The market resolves based on which team wins the game, with provisions for postponement or cancellation.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi contains a logical contradiction where both possible game outcomes (Harvard win and Brown win) are mapped to the same resolution (Yes), making the market unresolvable and creating a data integrity failure.Hero Tip:
Do not trade Kalshi's version of this market. The resolution logic is fundamentally broken. Polymarket's binary structure (Harvard Crimson vs Brown Bears) is the only logically sound version. If you hold Kalshi positions, escalate to support immediately.Critical Divergence Points:
- Kalshi: Declares both Brown victory and Harvard victory resolve to Yes, leaving no valid No outcome. This is a logical contradiction that makes the market unresolvable.
- Polymarket: Standard binary market: Harvard Crimson win resolves to Harvard Crimson, Brown Bears win resolves to Brown Bears. Postponement keeps market open; cancellation with no makeup resolves 50-50.
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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