TOTAL VOLUME:

$134.1b

24H VOL:

$133,388,117

24H TRANSACTIONS:

2,388,728,490

OPEN INTEREST:

$1,436,095,462

405,232

Markets across

30,526

events

MATCHED EVENTS:

2,693

PLATFORM COVERAGE:

5

Polymarket:

39%

VS.

Kalshi:

61%

BETA
Dashboards
Tour
All
Sports
Ben Shelton vs Marcos Giron: Game Spread
kalshi

Ben Shelton vs Marcos Giron: Game Spread

Volume:
$18,930

Ben Shelton -3.5 games

 - Kalshi

Ben Shelton -3.5 games - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Jun 12, 2026

Closed: Jun 12, 11:05 AM EST

kalshi

Kalshi

View
Join Kalshi and score $25 for your first trade.
Outcome
Trade
Chance %
Price
Spread
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
kalshi

Ben Shelton -3.5 games

View
0%
Yes 0¢No 100¢
100¢
N/A
$12,164
N/A
N/A
$10,369
Settled
No
kalshi

Marcos Giron -1.5 games

0%
Yes 0¢No 100¢
100¢
N/A
$6,655
N/A
N/A
$4,664
Settled
No
kalshi

Ben Shelton -6.5 games

0%
Yes 0¢No 100¢
100¢
N/A
$112
N/A
N/A
$112
Settled
No
Total markets: 3

Description

This market predicts the game differential between Ben Shelton and Marcos Giron across their entire match at the 2026 ATP Stuttgart Round of 16. The spread measures how many more games one player wins compared to the other throughout the full match.

Kalshi

The market resolves based on the game differential across the full match, with separate outcomes tracking whether Ben Shelton wins by more than 6.5 games, more than 3.5 games, or whether Marcos Giron wins by more than 1.5 games. If the match does not occur before play begins due to injury, walkover, forfeiture, or cancellation, the market resolves to fair price. If postponed or delayed, the market remains open until the rescheduled match concludes within two weeks. If a player retires, the game differential based on completed play determines resolution; if unconditional settlement is impossible, the market resolves to fair market price at the Exchange's discretion.

Frequently asked questions

On Kalshi, the dashboard for the Shelton vs Giron tennis match displays real-time odds and price movements tied to the game spread outcome. Traders can monitor current market pricing, historical price trends, and trading activity to gauge how the prediction market is valuing each side. The platform shows total liquidity and recent transaction volume, giving participants visibility into market depth and momentum. This data helps traders assess confidence levels and identify potential entry or exit points as new information emerges leading up to the match.

Prediction market odds and traditional sportsbook odds often diverge because they reflect different participant bases and incentive structures. Sportsbooks set lines to balance action and manage risk, while prediction markets aggregate trader beliefs through continuous price discovery. This market may show odds that differ from major sportsbooks, particularly if traders have access to unique information or hold different views on player form and matchup dynamics. Comparing the two can reveal where consensus differs and highlight potential value opportunities for informed bettors.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell contracts reflecting their belief in each outcome. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each contract moves based on supply and demand, with buyers and sellers negotiating in real time. As new match information surfaces—such as player injury reports or recent form—traders adjust their positions, which shifts the market price. This continuous repricing ensures the odds reflect the collective forecast of active participants on the platform.

This market resolves around Jun 13, 2026, once the match concludes and the final game spread is confirmed. The outcome is verified against credible public sources to ensure accuracy. Until that point, traders can adjust positions as the event draws closer and additional context becomes available. Resolution timing depends on when official results are published and validated, after which payouts are distributed to holders of the winning contract.

Several factors could shift this market significantly before resolution. Injury announcements or changes in player availability would alter perceived match dynamics. Recent tournament performance, head-to-head records, and court surface preference could influence trader sentiment. Weather conditions on match day and seeding or ranking shifts may also prompt repricing. Media coverage highlighting either player's form, coaching changes, or unexpected upsets in related tournaments can trigger rapid adjustments as traders reassess the likely outcome and adjust their positions accordingly.