TOTAL VOLUME:
$54.4b
24H VOL:
$224,446,576
24H TRANSACTIONS:
531,611,392
OPEN INTEREST:
$1,198,377,813
501,416
Markets across
13,642
events
MATCHED EVENTS:
1,816
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
Long Beach State Beach vs. Cal Poly Mustangs
Volume:
$149,700
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
A college basketball game between Long Beach State Beach and Cal Poly Mustangs scheduled for February 26, 2026 at 10:00 PM ET. Markets span moneyline (winner), point spread (-4.5, -5.5, -6.5), and over/under totals (159.5 through 175.5 points).
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi and Polymarket use different linguistic conventions for O/U thresholds (exclusive vs. inclusive phrasing), but resolve to identical outcomes in practice. Spread and moneyline logic is unified.Hero Tip:
For O/U markets, treat Kalshi 'over X.5' and Polymarket 'O/U X.5' as equivalent—both require combined score of X+1 or higher. Monitor official NCAA.com final score. Spread markets are safe; no trading friction expected.Critical Divergence Points:
- Kalshi: 11 O/U markets use exclusive threshold language ('over 160.5' means 161+). All resolve Yes if combined score strictly exceeds the stated line. Moneyline and spread logic absent from source data.
- Polymarket: Three O/U markets use inclusive threshold language ('161 or more points'). Spread markets (-4.5, -5.5, -6.5) resolve based on margin of victory. Moneyline resolves to winner. All use NCAA.com as source.
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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