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event10 outcomes

Orleans: Cyril Vandermeersch vs Martin Krumich

Polymarket·Sports·ends Nov 15, 2026

As of 16:22 UTC on 8 Nov 2026, the highest-priced of the 10 markets in “Orleans: Cyril Vandermeersch vs Martin Krumich” on Polymarket are “Orleans: Cyril Vandermeersch vs Martin Krumich Set 1 Winner” at 100% (+50pp in 24h), “Orleans: Cyril Vandermeersch vs Martin Krumich Total Sets: O/U 2.5” at 100% (+50pp in 24h) and “Orleans: Cyril Vandermeersch vs Martin Krumich Match O/U 21.5” at 100% (+51pp in 24h). The event has $29.1k in Polymarket-reported 24-hour volume. pdata.world tracks it alongside markets from 8 prediction-market platforms.

vol cum
$20.9k
vol 24h
$29.1k
outcomes
10
ends
Nov 15, 2026
outcomesclick to inspect →
showing 5 of 10
TennisSportsGames
marketselected outcome
Orleans: Cyril Vandermeersch vs Martin Krumich Set 1 Winner
rank #1 · resolved: cyril vandermeersch
100¢
▲ 50.0pp
24h change
vol cum
$0
vol 24h
$0
spread
0.00
ends
Nov 15, 2026

This market refers to the tennis match between Cyril Vandermeersch and Martin Krumich in the Orleans Qualifying, originally scheduled for November 8, 2026 at 7:30AM ET. This market will resolve to “Cyril Vandermeersch” if Cyril Vandermeersch wins the first set. It will resolve to “Martin Krumich” if Martin Krumich wins the first set. If the match begins but is not completed, and the first set is concluded with a winner determined, this market will resolve based on that completed set. If the first set is not completed for any reason, this market will resolve 50-50. If the match is canceled (not played at all) or play has not begun by November 22, 2026, 11:59 PM ET (14 days after the scheduled start), this market will resolve 50-50. Resolution will be based on official ATP Tour match statistics. This market may resolve only when the listed period of play has concluded and the result can be definitively determined by the listed resolution source(s).

timeline
opened · Nov 8, 2026closedresolved · Nov 8, 2026
Orleans: Cyril Vandermeersch vs Martin Krumich Set 1 Winner · prices over time
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