This event group covers the outcome of the OGC Nice vs. FC Lorient Ligue 1 soccer match scheduled for February 22, 2026. Markets are offered on three mutually exclusive outcomes: a Lorient win, a Nice win, or a draw. All markets measure the result after 90 minutes of regular play plus stoppage time, excluding extra time and penalties.
Polymarket and Kalshi diverge on how a canceled match (with no make-up game) resolves. Polymarket explicitly resolves the draw market to YES and win markets to NO; Kalshi provides no cancellation clause, leaving the outcome undefined.
Hero Tip:
Before trading, confirm with both platforms their exact cancellation protocol. Polymarket's draw-resolves-YES rule creates a logical trap: if the match is canceled, traders holding draw positions win while win positions lose—regardless of the underlying match outcome. Kalshi's silence on cancellation means the market could hang unresolved or require manual settlement.
Critical Divergence Points:
Polymarket: Three separate binary markets (Lorient win, Nice win, Draw). Postponement keeps markets open; cancellation with no make-up resolves draw to YES and win markets to NO. Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve No' (win markets) and 'Yes' (draw market).
Kalshi: Three outcome-based markets (Lorient win, Nice win, Tie). Each resolves YES if its outcome occurs after 90 minutes plus stoppage time. No explicit cancellation clause provided. Quote: 'If Lorient wins...then the market resolves to Yes' (and similarly for Nice and Tie).
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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