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Mariano Navone vs Flavio Cobolli: Game Spread
kalshi

What is the game spread in Navone vs Cobolli at Wimbledon?

Volume:
$3,084

Flavio Cobolli -6.5 games

 - Kalshi

Flavio Cobolli -6.5 games - Kalshi

1W

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Positive

Negative

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Vol.

·

Resolved Jul 1, 2026

Closed: Jul 1, 8:57 AM EST

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Outcome
Trade
Chance %
Price
Spread
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
kalshi

Flavio Cobolli -6.5 games

View
0%
Yes 0¢No 100¢
100¢
N/A
$1,431
N/A
N/A
$1,244
Settled
No
kalshi

Flavio Cobolli -3.5 games

0%
Yes 0¢No 100¢
100¢
N/A
$1,369
N/A
N/A
$1,222
Settled
No
kalshi

Flavio Cobolli -9.5 games

0%
Yes 0¢No 100¢
100¢
N/A
$285
N/A
N/A
$285
Settled
No
Total markets: 3

Description

This market measures the game differential between Flavio Cobolli and Mariano Navone in their 2026 Wimbledon Men's Singles Round of 128 match on June 30. Bettors wager on whether Cobolli will win by a decisive margin or whether Navone can remain competitive throughout the match.

Kalshi

The event resolves based on the game differential across the full match between Mariano Navone and Flavio Cobolli in the 2026 Wimbledon Men's Singles Round of 128. Resolution depends on which player wins more games overall, with outcomes reflecting various margin thresholds. If the match does not occur before play begins due to injury, walkover, forfeiture, or cancellation, the market resolves to a fair price. If postponed or delayed, the market remains open and closes after the rescheduled match concludes within two weeks. If a player retires, markets that can be unconditionally settled based on completed play resolve accordingly; those that cannot are settled at Fair Market Price at the Exchange's discretion.

Frequently asked questions

On Kalshi, the dashboard for the Navone vs Cobolli tennis match tracks real-time odds and historical price movements for a game-spread contract. This market measures whether Flavio Cobolli will win at least 3.5 more games than Mariano Navone in their matchup. The interface displays current implied probability, 24-hour trading volume, and order-book depth, allowing traders to monitor sentiment shifts as the event approaches. Historical charts help identify price trends and volatility patterns leading up to the match.

Prediction market odds and sportsbook odds often diverge because they reflect different participant bases and incentive structures. Sportsbooks set lines to balance action and lock in profit margins, while prediction markets aggregate trader beliefs through continuous price discovery. This market's odds may lead or lag sportsbook spreads depending on which venue attracts sharper early information. Comparing the two can reveal where professional traders and casual bettors disagree on the likely game outcome.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares representing the outcome. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The current implied probability reflects the last traded price, with the spread between bid and ask orders indicating liquidity and conviction. As new information emerges—such as player form, injury updates, or court conditions—traders adjust their positions, moving the price up or down. The contract settles to either 0 or 1 based on the final game result.

This market resolves around Jul 1, 2026, once the match concludes and the final game count is verifiable from credible public sources. The outcome hinges on whether Cobolli wins at least 3.5 more games than Navone across all sets played. Resolution occurs after official scorecards are published and confirmed, ensuring accuracy before payouts are distributed. Traders should monitor official tennis tour announcements and match reports for final confirmation.

Several factors can shift odds before the match begins. Injury announcements or withdrawal news involving either player would trigger sharp repricing. Recent tournament results, head-to-head records, and surface-specific performance data often drive trader activity. Court conditions, weather forecasts, and lineup changes can also influence expectations about game distribution. Media coverage highlighting player form or tactical adjustments may spark volatility as new information reaches the trading community.