TOTAL VOLUME:
$54.3b
24H VOL:
$198,896,558
OPEN INTEREST:
$1,191,591,877
500,572
Markets across
13,691
events
MATCHED EVENTS:
1,797
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
Boston College Eagles vs. Florida State Seminoles
Volume:
$6,831,340
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
A men's college basketball game between Boston College Eagles and Florida State Seminoles scheduled for February 17, 2026 at 6:00 PM ET. Markets cover moneyline (winner), point spread outcomes at -11.5 and -12.5, and total points over/under at 147.5 and 148.5.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi's moneyline market contains a logical contradiction where both possible game outcomes (BC win and FSU win) are mapped to the same resolution value (Yes), making the market fundamentally unresolvable. Polymarket's equivalent market is logically sound.Hero Tip:
Do not trade the Kalshi moneyline market. It is unresolvable as written. Use Polymarket's moneyline market for winner bets. All spread and total markets across both platforms are consistent and resolvable.Critical Divergence Points:
- Kalshi: Moneyline market: 'If Boston College wins...resolves to Yes' AND 'If Florida St. wins...resolves to Yes'. Both outcomes resolve identically, creating a logical impossibility with no path to No resolution.
- Polymarket: Moneyline market: Resolves to 'Boston College Eagles' if BC wins, 'Florida State Seminoles' if FSU wins. Cancellation resolves 50-50. Logically sound 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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