TOTAL VOLUME:
$154.4b
24H VOL:
$290,393,159
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,944,100,805
420,493
Markets across
40,511
events
MATCHED EVENTS:
4,612
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 28, 10:54 PM EST
Polymarket
This prediction market asks for the exact final score of a Major League Soccer (MLS) match between the Chicago Fire FC and Orlando City SC, excluding any extra time or penalty shootouts. The market includes a comprehensive list of possible scores, as well as an 'Any Other Score' option.
In the upcoming MLS game between Chicago Fire FC and Orlando City SC, scheduled for October 28, 2026 at 8:30 PM ET: This market will resolve based on the final score of the Chicago Fire FC vs. Orlando City SC match originally scheduled for October 28, 2026 at 8:30 PM ET, considering only the result at the end of 90 minutes of regulation plus stoppage time; extra time and penalty shoot-outs are excluded. If the actual score is not one of the explicitly listed outcomes, the market resolves to "Any Other Score." If the match is postponed, the market will remain open until it is completed; if it is canceled with no make-up game, the market resolves to "0-0." The primary resolution source for this market is the official statistics of the event as recognized by the governing body or event organizers. However, if the governing body or event organizers have not published final match statistics within 2 hours after the event's conclusion, data from Flashscore may be used; if Flashscore data is unavailable, data from Sofascore may be used; if neither is available, a consensus of credible reporting may be used instead. All markets will settle based on the official final result as recognized by the governing body or event organizers. Revisions to officially declared final scores made after market resolution will not be accounted for in determining the outcome. If no acceptable data is available within 24 hours of the event's conclusion, this market will resolve 50-50, or to "Draw" where applicable.
In the upcoming MLS game between Chicago Fire FC and Orlando City SC, scheduled for October 28, 2026 at 8:30 PM ET: This market will resolve based on the final score of the Chicago Fire FC vs. Orlando City SC match originally scheduled for October 28, 2026 at 8:30 PM ET, considering only the result at the end of 90 minutes of regulation plus stoppage time; extra time and penalty shoot-outs are excluded. If the actual score is not one of the explicitly listed outcomes, the market resolves to "Any Other Score." If the match is postponed, the market will remain open until it is completed; if it is canceled with no make-up game, the market resolves to "0-0." The primary resolution source for this market is the official statistics of the event as recognized by the governing body or event organizers. However, if the governing body or event organizers have not published final match statistics within 2 hours after the event's conclusion, data from Flashscore may be used; if Flashscore data is unavailable, data from Sofascore may be used; if neither is available, a consensus of credible reporting may be used instead. All markets will settle based on the official final result as recognized by the governing body or event organizers. Revisions to officially declared final scores made after market resolution will not be accounted for in determining the outcome. If no acceptable data is available within 24 hours of the event's conclusion, this market will resolve 50-50, or to "Draw" where applicable.
Prediction market odds, like those found for this market, often reflect the collective wisdom of a diverse group of forecasters, potentially offering a different perspective than traditional sportsbooks. Sportsbooks set lines based on models and public betting patterns, while prediction markets allow anyone to trade on their beliefs, creating a dynamic pricing mechanism. This can lead to discrepancies, particularly when public sentiment strongly diverges from underlying probabilities. It's possible to find arbitrage opportunities by comparing the implied probabilities across both types of platforms.