This market resolves based on the outcome of the NBA game between the Orlando Magic and Toronto Raptors scheduled for March 29 at 6:00 PM ET. The winner is determined by the final score including any overtime periods, with the market resolving to either "Magic" or "Raptors" accordingly.
Kalshi's moneyline markets resolve YES for both possible outcomes (Orlando wins OR Toronto wins), creating a logical contradiction that makes these markets fundamentally unresolvable. Polymarket uses standard binary resolution logic where each outcome resolves to a distinct result.
Hero Tip:
Avoid Kalshi's moneyline markets entirely — they are logically broken. Use Polymarket's Magic vs. Raptors moneyline for standard binary resolution. All other market types (spreads, totals, player props) on both platforms appear resolvable.
Critical Divergence Points:
Kalshi: Outlier: Both Kalshi moneyline conditions resolve to YES regardless of outcome. Kalshi states 'If Orlando wins the Orlando at Toronto professional basketball game originally scheduled for Mar 29, 2026, then the market resolves to Yes' AND 'If Toronto wins the Orlando at Toronto professional basketball game originally scheduled for Mar 29, 2026, then the market resolves to Yes.' This means the market resolves YES in all scenarios, violating basic binary logic.
Polymarket: Aligned with standard binary logic: Polymarket's moneyline resolves to 'Magic' if Magic win and 'Raptors' if Raptors win, with a 50-50 split only if the game is canceled with no makeup. This is standard mutually exclusive resolution.
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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