Kalshi and Polymarket differ fundamentally in scope and resolution logic. Kalshi offers four markets based on total goals thresholds (>1.5, >2.5, >3.5, >4.5), while Polymarket offers three markets based on match outcome (NYCFC win, draw, Inter Miami win). These are distinct market types with different underlying events.
Hero Tip:
Kalshi bettors are predicting total goal volume; Polymarket bettors are predicting match outcome. A single match result (e.g., NYCFC 2-1 Inter Miami) resolves differently across platforms: Kalshi's >1.5 and >2.5 markets resolve YES, while Polymarket's NYCFC win market resolves YES. Do not assume cross-platform hedging works — these are independent event types.
Critical Divergence Points:
Kalshi: Distinct stance: Kalshi settles on aggregate goal count thresholds. All four markets measure whether combined goals exceed a specified threshold (1.5, 2.5, 3.5, or 4.5) after 90 minutes plus stoppage time. Resolution source is implicit (official match statistics), and each market is independent: 'If Miami and New York City collectively score more than X total goals... then the market resolves to Yes.'
Polymarket: Distinct stance: Polymarket settles on match outcome (win/draw/loss for NYCFC) after 90 minutes plus stoppage time. All three markets are mutually exclusive outcome markets. Primary resolution source is official MLS statistics (mlssoccer.com/schedule/scores) or credible reporting consensus if unavailable within 2 hours post-match: 'If New York City FC 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.
Follow the signals, not the noise
Get insights on market conviction, notable shifts, and what the data is quietly signaling.