Wake Forest Demon Deacons vs. Virginia Tech Hokies
Volume:
$423,153
Markets
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24h
7d
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Description
This event group covers a men's college basketball game between Wake Forest Demon Deacons and Virginia Tech Hokies scheduled for March 10, 2026 at 7:00 PM ET at Virginia Tech. Markets span moneyline (winner), point spread, and over/under total points across Kalshi and Polymarket platforms.
Over/Under total-points thresholds differ between platforms. Kalshi provides 11 granular thresholds (137.5–167.5); Polymarket uses two discrete thresholds (151.5 and 152.5). This creates settlement misalignment for identical underlying events.
Hero Tip:
Treat Kalshi and Polymarket over/under markets as separate products with non-overlapping payoff zones. A combined score of 151 triggers Yes on Kalshi's sub-151.5 markets but Under on Polymarket's O/U 151.5. Lock in your platform choice and threshold before game time.
Critical Divergence Points:
Kalshi: 11 separate over/under markets on combined team points. Thresholds: 137.5, 140.5, 143.5, 146.5, 149.5, 152.5, 155.5, 158.5, 161.5, 164.5, 167.5. Each resolves Yes if final combined score exceeds threshold. Quote: 'If Wake Forest and Virginia Tech collectively score over 140.5 total points... then the market resolves to Yes.'
Polymarket: Two over/under markets: O/U 151.5 (Over if 152+) and O/U 152.5 (Over if 153+). Also offers moneyline and two spread markets (-1.5 and -2.5 Virginia Tech). Quote: 'This market will resolve to Over if the Wake Forest Demon Deacons and Virginia Tech Hokies combine to score 152 or more points.'
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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