TOTAL VOLUME:
$134b
24H VOL:
$87,997,338
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,395,155,069
395,664
Markets across
30,076
events
MATCHED EVENTS:
2,626
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Jul 2, 8:14 AM EST
Kalshi
This event group contains two distinct markets about a 2026 Wimbledon ATP match between Taylor Fritz and Patrick Kypson. The Predict platform market resolves on match winner, while the Kalshi platform market resolves on whether either player records a minimum ace threshold during the match.
An ace is defined as a serve that lands in the service box and is not touched by the receiving player, including their racket, body, or clothing, resulting in an immediate point for the server. Each player's market resolves Yes if they record the specified minimum number of total match aces during the full professional tennis match. If the match does not occur before play begins due to injury, walkover, forfeiture, or other cancellation, the market resolves to a fair price. If a retirement occurs during the match, resolution is based on statistics officially completed and recorded prior to the match's discontinuation.
This market refers to the tennis match between Taylor Fritz and Patrick Kypson in the Wimbledon ATP, originally scheduled for July 2, 2026 at 6:00AM ET. This market will resolve to 'Taylor Fritz' if Taylor Fritz advances against Patrick Kypson. This market will resolve to 'Patrick Kypson' if Patrick Kypson advances against Taylor Fritz. If the match is canceled (not played at all), ends in a tie, or is delayed beyond 7 days from the scheduled date without a winner determined, 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 ATP Tour. A consensus of credible reporting may also be used.
Kalshi and Predict track different outcomes: one prices the match winner, the other a specific ace threshold. Kalshi and Predict can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. Beyond that structural difference, each platform attracts distinct trader demographics, liquidity pools, and risk tolerances. Predict's narrower focus on aces may appeal to bettors with strong views on serve dominance, while Kalshi's broader match outcome draws general sports traders. Fee structures, minimum bet sizes, and user interface design also influence where volume concentrates, causing temporary price gaps that arbitrageurs can exploit.
Key catalysts include recent head-to-head records, court surface conditions at Wimbledon, and serve statistics from both players' recent matches. Injury reports or fitness updates on either competitor can shift odds sharply, especially on Predict's ace-specific contract. Pre-match commentary from analysts and betting syndicates often triggers repricing as new information reaches traders. Weather forecasts and draw announcements may also influence perceived advantage. Real-time trading activity itself—large bets or sudden volume spikes—can signal informed positioning and move prices before the match begins.