Guadalajara wins priced at 74.0% on Kalshi, up 41.0 points, on $912K traded
No significant new platform headline in the last 30 minutes; news search recirculated only items already used, web-taken or banned (the $2.7B weekly crypto volume record…
Guadalajara contract reprices sharply
The Kalshi market labeled “Guadalajara wins” was priced at 74.0%, up 41.0 probability points, with $912K traded, according to the supplied market headline published Oct 24, 2026, at 11:24 PM ET.
The figures indicate a substantial shift in pricing, but the accompanying material does not identify the opponent, event date or contract’s settlement conditions. It also does not establish what prompted the move.
What the available data shows
According to predictionbubbles.net, its movers service compares market-implied probabilities over 24 hours using prices from Polymarket and Kalshi, refreshing every 15 minutes. The supplied page records a venue-data snapshot of 25 Oct 2026, 03:17 UTC.
The service ranks changes in probability points rather than relative percentages. Trading volume provides context but does not determine the ranking, and only open markets with a valid 24-hour comparison qualify.
The supplied page text does not include a Guadalajara-specific listing, so it does not independently corroborate the headline’s price, move or volume. The accompanying monitoring summary reports no significant new platform headline in the preceding 30 minutes; that does not establish whether event-specific information drove this contract’s repricing.
What it means for prediction markets
- Read the units correctly: The reported increase is 41.0 probability points, not a 41.0% relative gain.
- Separate turnover from liquidity: The $912K traded figure provides activity context, but the supplied material does not specify its measurement window or current order-book depth.
- Keep the catalyst unresolved: The 74.0% price reflects market positioning. Without event details or verified fresh reporting, the reason for the move remains unconfirmed.
Sources & attribution
- [1]Predictionbubbles (predictionbubbles.net)https://predictionbubbles.net/markets/movers/
Date & time:
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