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%

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Lowest temperature in San Antonio on May 29, 2026?
kalshi

Lowest temperature in San Antonio on May 29, 2026?

Volume:
$6,418

71° to 72°

 - Kalshi

71° to 72° - Kalshi

1W

News

Positive

Negative

Neutral

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Vol.

·

Resolved May 30, 2026

Closed: May 30, 2:00 AM 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

71° to 72°

View
100%
Yes 100¢No 0¢
100¢
N/A
$3,389
N/A
N/A
$2,847
Settled
Yes
kalshi

73° or above

0%
Yes 0¢No 100¢
100¢
N/A
$863
N/A
N/A
$821
Settled
No
kalshi

67° to 68°

0%
Yes 0¢No 100¢
100¢
N/A
$753
N/A
N/A
$589
Settled
No
kalshi

65° to 66°

0%
Yes 0¢No 100¢
100¢
N/A
$571
N/A
N/A
$551
Settled
No
kalshi

69° to 70°

0%
Yes 0¢No 100¢
100¢
N/A
$526
N/A
N/A
$506
Settled
No
kalshi

64° or below

0%
Yes 0¢No 100¢
100¢
N/A
$315
N/A
N/A
$302
Settled
No
Total markets: 6

Intro

This market tracks whether San Antonio's overnight low temperature will fall within the 69-70° Fahrenheit range on May 29, 2026. On Kalshi, the leading outcome currently stands at 42.0%, with the 71-72° range at 27.0%. Resolution will be determined by the National Weather Service's Climatological Report (Daily), which records the minimum temperature for that date. Watch the National Weather Service's daily forecast updates as May 29, 2026 approaches to assess how seasonal weather patterns and atmospheric conditions are expected to influence overnight lows in the San Antonio area.

Frequently asked questions

Prediction market odds on Kalshi reflect real-money consensus from traders and often diverge from traditional weather analyst forecasts. While meteorologists issue point estimates and confidence intervals based on climate models, prediction markets aggregate dispersed information and financial incentives, sometimes pricing in tail risks or local factors that models underweight. Comparing Kalshi implied probabilities to National Weather Service or private forecaster predictions can reveal where the market is more bullish or bearish on extreme temperatures, offering traders an alternative lens on May 29 conditions in San Antonio.

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the Lowest temperature in San Antonio on May 29 contract is priced as a binary or range-based outcome, with the market price reflecting the collective belief in specific temperature thresholds. Traders buy and sell shares at prices between 0 and 100 cents, where each cent represents a one-percentage-point shift in implied probability. As new weather data, seasonal patterns, and real-time conditions emerge, the price adjusts continuously, allowing traders to enter or exit positions and locking in gains or losses before the May 30, 2026 settlement window.

The Lowest temperature in San Antonio on May 29 market resolves on May 30, 2026, after the calendar day has passed and official temperature data becomes available. Resolution hinges on verified meteorological records for San Antonio on that specific date, ensuring an objective and auditable outcome. Once the lowest temperature reading is confirmed, the contract settles according to the pre-defined outcome criteria, and traders' positions are cash-settled based on whether their prediction matched the realized low.

Several factors can shift odds for San Antonio's May 29 low: updated seasonal forecasts, atmospheric patterns (jet stream position, high-pressure systems), historical climate anomalies, and real-time weather model runs released in the days leading up to May 29. Major weather events elsewhere in North America can alter regional circulation. Additionally, any unusual solar activity, ocean temperature shifts, or local urban heat-island effects may influence trader expectations. As May 29 approaches, short-range forecasts become more precise, typically tightening the market range and reducing uncertainty around the final low temperature.