TOTAL VOLUME:

$134.1b

24H VOL:

$133,388,117

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2,388,728,490

OPEN INTEREST:

$1,436,095,462

405,232

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2,693

PLATFORM COVERAGE:

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Sports
New York Y vs Tampa Bay: First 5 Spread
kalshi

What is the first 5 inning run spread result of New York vs Tampa Bay?

Volume:
$21,208

Tampa Bay -1.5 first 5 innings

 - Kalshi

Tampa Bay -1.5 first 5 innings - Kalshi

1W

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Negative

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Vol.

·

Resolved Jul 9, 2026

Closed: Jul 8, 8:00 PM EST

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

Tampa Bay -1.5 first 5 innings

View
100%
Yes 100¢No 0¢
100¢
N/A
$13,577
N/A
N/A
$5,697
Settled
Yes
kalshi

Tampa Bay -2.5 first 5 innings

0%
Yes 0¢No 100¢
100¢
N/A
$4,522
N/A
N/A
$3,236
Settled
No
kalshi

New York Y -1.5 first 5 innings

0%
Yes 0¢No 100¢
100¢
N/A
$2,342
N/A
N/A
$2,063
Settled
No
kalshi

New York Y -2.5 first 5 innings

0%
Yes 0¢No 100¢
100¢
N/A
$767
N/A
N/A
$637
Settled
No
Total markets: 4

Description

This market covers the run spread between the Yankees and Tampa Bay during the first 5 innings of their July 8, 2026 game. Bettors predict whether Tampa Bay or the Yankees will win by specific run margins in the early innings.

Kalshi

Resolution is based on the run differential at the end of the first 5 innings of the New York Y vs Tampa Bay professional baseball game originally scheduled for July 8, 2026 at 6:40 PM EDT. The market resolves to Yes if Tampa Bay wins by more than 2.5 runs or more than 1.5 runs, or if New York Y wins by more than 1.5 runs or more than 2.5 runs in the first 5 innings. Each run differential threshold represents a separate market outcome. If the game is postponed or delayed, the market remains open and closes after the rescheduled game finishes within two days.

Frequently asked questions

On Kalshi, the dashboard for the New York Y vs Tampa Bay first 5 spread tracks real-time odds and historical price movements as traders buy and sell shares tied to the outcome. You can monitor current market sentiment, 24-hour trading volume at $17,048, and cumulative liquidity across all positions. The interface displays how the spread prediction has shifted over time, helping you identify trends and volatility patterns leading up to the game. This live data reflects collective trader expectations about whether New York will cover the first-quarter spread against Tampa Bay.

Prediction market odds and traditional sportsbook odds often diverge because they reflect different participant pools and incentive structures. Sportsbooks set lines to balance action and manage risk, while prediction markets like this one aggregate trader beliefs through continuous price discovery. This market's odds may lead or lag sportsbook spreads depending on information flow and trader conviction. Comparing the two can reveal where smart money is positioning itself, though sportsbook odds remain the primary reference for most bettors and analysts tracking the matchup.

On Kalshi, this market is priced through an order-book mechanism where traders submit bids and asks for shares representing each outcome. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each share reflects the collective probability assigned by active traders, ranging from $0 to $1. As new information emerges or sentiment shifts, traders adjust their positions, moving the price up or down. Your profit or loss depends on the entry price you pay and the final resolution value, creating a direct incentive to forecast accurately.

This market resolves around Jul 9, 2026, once the game concludes and the first-quarter spread result is verified against credible public sources. The outcome is determined by comparing New York's score to Tampa Bay's score during the opening five minutes of play, then checking whether the actual margin matches or exceeds the predicted spread. Resolution is automatic once the data is confirmed, and all shares are settled to $0 or $1 accordingly. Traders holding the winning outcome receive their payout immediately.

Key injury announcements, lineup changes, or weather updates affecting either team can shift trader positioning significantly. Breaking news about player availability, coaching decisions, or last-minute roster moves often triggers sharp price movements as informed traders react first. Public betting trends and sportsbook line adjustments may also influence perception of the spread's accuracy. Game-day momentum, early scoring patterns, and real-time performance in the first five minutes will ultimately determine the outcome, but pre-game catalysts typically drive the largest swings in market pricing.