event16 outcomes

Pan Pacific Open: Alexandra Eala vs Mika Stojsavljevic

Polymarket·Sports·ends Nov 3, 2026

As of 01:30 UTC on 26 Oct 2026, the highest-priced of the 16 markets in “Pan Pacific Open: Alexandra Eala vs Mika Stojsavljevic” on Polymarket are “Pan Pacific Open: Alexandra Eala vs Mika Stojsavljevic” at 86% (+36pp in 24h), “Pan Pacific Open: Alexandra Eala vs Mika Stojsavljevic Set 1 Winner” at 82% (+32pp in 24h) and “Pan Pacific Open: Alexandra Eala vs Mika Stojsavljevic Set Handicap +/-1.5” at 68% (+19pp in 24h). The event has $6.6k in Polymarket-reported 24-hour volume. pdata.world tracks it alongside markets from 8 prediction-market platforms.

vol cum

$6.6k

vol 24h

$6.6k

outcomes

ends

Nov 3, 2026

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TennisSportsGames

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Pan Pacific Open: Alexandra Eala vs Mika Stojsavljevic

rank #1

86¢

▲ 35.5pp

24h change

vol cum

$1.7k

vol 24h

$1.7k

spread

0.01

ends

Nov 3, 2026

This market refers to the tennis match between Alexandra Eala and Mika Stojsavljevic in the Pan Pacific Open, originally scheduled for October 26, 2026 at 10:00PM ET. This market will resolve to 'Alexandra Eala' if Alexandra Eala advances against Mika Stojsavljevic. This market will resolve to 'Mika Stojsavljevic' if Mika Stojsavljevic advances against Alexandra Eala. If the match is canceled (not played at all), ends in a tie, or a winner has not been determined by November 9, 2026, 11:59 PM ET (14 days after the scheduled start), this market will resolve to 50-50. If the match begins but is not completed, and one player advances due to the opponent's retirement, default, or disqualification, this market will resolve to the player who advances. If the match ends in a walkover (player withdraws before the start and the other advances automatically), this market will resolve to 50-50. The primary resolution source will be official information from the WTA Tour. A consensus of credible reporting may also be used.

timeline

opened · Oct 25, 2026opencloses · Nov 3, 2026

Pan Pacific Open: Alexandra Eala vs Mika Stojsavljevic · prices over time

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