TOTAL VOLUME:
$61.7b
24H VOL:
$229,178,007
24H TRANSACTIONS:
600,069,390
OPEN INTEREST:
$1,336,753,738
577,196
Markets across
14,485
events
MATCHED EVENTS:
4,077
PLATFORM COVERAGE:
4
Polymarket:
50%
VS.
Kalshi:
50%
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
A college basketball game between Wagner Seahawks and Stonehill Skyhawks scheduled for February 14, 2026 at 2:00 PM ET. Markets cover moneyline (winner), point spreads at multiple thresholds, and total points over/under at multiple lines.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi moneyline market contains a logical contradiction where both possible outcomes (Stonehill win and Wagner win) are mapped to the same resolution (Yes), making the market fundamentally unresolvable. Polymarket moneyline uses standard mutually exclusive outcomes.Hero Tip:
Do not trade the Kalshi moneyline. Use Polymarket moneyline as the authoritative source. All spread and total markets across both platforms are logically consistent and resolvable based on final score including overtime.Critical Divergence Points:
Kalshi:
Moneyline market has contradictory logic: both Stonehill win and Wagner win resolve to Yes. Quote: 'If Stonehill wins...resolves to Yes' AND 'If Wagner wins...resolves to Yes.' This violates binary market structure.Polymarket:
Moneyline market uses standard mutually exclusive outcomes. Quote: 'If Wagner wins, resolves to Wagner Seahawks. If Stonehill wins, resolves to Stonehill Skyhawks.' Clear and resolvable.
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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