This event group covers the FC Lorient vs. AJ Auxerre Ligue 1 match scheduled for March 1, 2026. Kalshi offers four markets based on goal-margin thresholds (>1.5 and >2.5 goals for each team), while Polymarket offers three binary markets covering Lorient win, draw, and Auxerre win outcomes. Both platforms resolve based on the result after 90 minutes plus stoppage time, excluding extra time and penalties.
Kalshi offers goal-margin threshold markets (>1.5 and >2.5 goals) while Polymarket offers binary match-outcome markets (win/draw/loss). These are different settlement value archetypes and require separate resolution logic.
Hero Tip:
Recognize that Kalshi and Polymarket serve different trader profiles. Kalshi bettors are hedging on margin size; Polymarket bettors are betting on pure outcome. A single match result may resolve differently across platforms depending on the goal margin. Ensure your position sizing accounts for this structural divergence.
Critical Divergence Points:
Kalshi:
Four goal-margin threshold markets. Resolves Yes if Lorient wins by >1.5 goals, Lorient wins by >2.5 goals, Auxerre wins by >1.5 goals, or Auxerre wins by >2.5 goals. These are overlapping SKU/subset markets. Key Quote: 'If Lorient wins by more than 1.5 goals... then the market resolves to Yes.'
Polymarket:
Three mutually exclusive binary outcome markets: Lorient win, draw, or Auxerre win. Each resolves Yes or No based on the final match result. Key Quote: 'If FC Lorient 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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