Central Michigan Chippewas vs. Eastern Michigan Eagles
Volume:
$1,149,666
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a men's college basketball game between Central Michigan Chippewas and Eastern Michigan Eagles scheduled for February 17, 2026 at 6:30 PM ET. Markets span moneyline (winner), point spreads at multiple thresholds (-4.5, -5.5, -6.5 favoring Eastern Michigan), and over/under totals at multiple thresholds (141.5, 142.5, 143.5).
Kalshi moneyline market contains a logical contradiction: both Central Michigan win and Eastern Michigan win are stated to resolve to Yes, creating an impossible resolution state with no valid outcome path.
Hero Tip:
Do not trade the Kalshi moneyline. This market is unresolvable as written. All Polymarket markets (moneyline, spreads, totals) have consistent, clear logic and should be treated as the authoritative settlement source for this event group.
Critical Divergence Points:
Polymarket: Moneyline resolves to winner name (Central Michigan Chippewas or Eastern Michigan Eagles). Spreads resolve based on margin thresholds. Totals resolve based on combined points. All include overtime. Postponement keeps market open; cancellation with no makeup = 50-50. Logic is internally consistent and complete.
Kalshi: Moneyline states both Central Michigan win and Eastern Michigan win resolve to Yes, creating a logical impossibility. No resolution path exists for either outcome or edge cases. This contradicts standard binary market design.
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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