Kalshi's market structure is logically contradictory and unresolvable: all three outcomes (Nepal win, Tie, Hong Kong win) are specified to resolve to YES, making it impossible to determine a single resolution. Polymarket provides three separate, mutually exclusive markets with clear resolution logic for each outcome.
Hero Tip:
Avoid trading on Kalshi's markets in this group — they contain a fatal logical error where every possible match outcome resolves to YES, making settlement impossible. Trade only on Polymarket's three distinct markets (Nepal win, Hong Kong win, Draw), which have coherent, mutually exclusive resolution criteria.
Critical Divergence Points:
Kalshi: Outlier: Contains a logical contradiction. All three market conditions state 'then the market resolves to Yes' — meaning Nepal win resolves YES, Tie resolves YES, and Hong Kong win resolves YES. This makes the market unresolvable because exactly one outcome will occur, but the rules assign YES to all three. Key quote: 'If Nepal wins...then the market resolves to Yes. If Tie wins...then the market resolves to Yes. If Hong Kong wins...then the market resolves to Yes.'
Polymarket: Aligned with sound resolution logic: Provides three separate, mutually exclusive markets — one for Nepal win (YES if Nepal wins, NO otherwise), one for Hong Kong win (YES if Hong Kong wins, NO otherwise), and one for Draw (YES if draw, NO otherwise). Exactly one market will resolve YES based on the actual match outcome. Key quote: 'If Nepal wins, this market will resolve to Yes. Otherwise, this market will resolve to No.'
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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