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402,751

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San Diego vs Texas: Spread
kalshi

San Diego vs Texas: Spread

Volume:
$718,716

San Diego wins by over 1.5 runs

 - Kalshi

San Diego wins by over 1.5 runs - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Jun 20, 2026

Closed: Jun 20, 7:24 PM EST

kalshi

Kalshi

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

San Diego wins by over 1.5 runs

View
100%
Yes 100¢No 0¢
100¢
N/A
$208,547
N/A
N/A
$91,343
Settled
Yes
kalshi

Texas wins by over 1.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$236,967
N/A
N/A
$111,850
Settled
No
kalshi

San Diego wins by over 2.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$193,193
N/A
N/A
$116,861
Settled
No
kalshi

San Diego wins by over 3.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$34,452
N/A
N/A
$17,888
Settled
No
kalshi

Texas wins by over 2.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$33,357
N/A
N/A
$15,051
Settled
No
kalshi

Texas wins by over 3.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$11,900
N/A
N/A
$9,151
Settled
No
kalshi

Padres wins by over 4.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$301
N/A
N/A
$301
Settled
No
Total markets: 7

Description

This market focuses on the final margin of victory in the San Diego vs Texas game. Bettors can wager on whether either team will win by specific run margins, with thresholds ranging from 1.5 to 3.5 runs.

Kalshi

Resolution is based on the final run differential in the San Diego vs Texas professional baseball game originally scheduled for Jun 20, 2026 at 4:05 PM EDT. Each outcome resolves to Yes if the specified team wins by more than the stated run margin. Texas outcomes cover winning margins of more than 1.5, 2.5, and 3.5 runs, while San Diego outcomes cover winning margins of more than 1.5, 2.5, and 3.5 runs.

Frequently asked questions

On Kalshi, the San Diego vs Texas spread market dashboard tracks real-time odds and price movements for this matchup's point spread. The interface displays current market pricing, historical price charts, and trading volume data to help you monitor how traders are positioning on the spread throughout the event window. You can observe shifts in implied probability as new information emerges, giving you a live view of collective market sentiment on whether San Diego will cover the spread against Texas.

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 beliefs from traders risking real capital. This market's odds may lead or lag sportsbook spreads depending on information flow and trader conviction. Comparing the two can reveal whether professional oddsmakers or the broader prediction market crowd has a more accurate read on the spread.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell contracts reflecting different spread outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each contract reflects the implied probability that the spread will land in that range, with bids and asks set by participants. As new trades execute, the market price adjusts in real time, allowing you to enter or exit positions at the prevailing rate.

This market resolves around Jun 20, 2026, once the San Diego versus Texas game concludes and the final spread outcome is verifiable from credible public sources. The resolution hinges on the official final score and how it compares to the spread specified in the market. Traders holding contracts aligned with the actual spread result will see their positions settle at full value, while opposing positions expire worthless.

Key catalysts include injury announcements to star players, lineup changes, or coaching decisions that shift team strength. Weather conditions, travel schedules, and rest advantages can also influence spread expectations. Breaking news about team performance, recent form, or head-to-head matchup history typically triggers sharp repricing. As game day approaches, late-breaking developments and sharp money entering the market often drive final adjustments to the odds.