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$126,324,530

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2,388,728,490

OPEN INTEREST:

$1,434,646,834

406,019

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2,689

PLATFORM COVERAGE:

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Lowest temperature in Minneapolis on Jun 3, 2026?
kalshi

Lowest temperature in Minneapolis on Jun 3, 2026?

Volume:
$4,293

63° or above

 - Kalshi

63° or above - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Jun 4, 2026

Closed: Jun 4, 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

63° or above

View
100%
Yes 100¢No 0¢
100¢
N/A
$2,085
N/A
N/A
$1,861
Settled
Yes
kalshi

59° to 60°

0%
Yes 0¢No 100¢
100¢
N/A
$581
N/A
N/A
$566
Settled
No
kalshi

57° to 58°

0%
Yes 0¢No 100¢
100¢
N/A
$506
N/A
N/A
$406
Settled
No
kalshi

55° to 56°

0%
Yes 0¢No 100¢
100¢
N/A
$436
N/A
N/A
$436
Settled
No
kalshi

54° or below

0%
Yes 0¢No 100¢
100¢
N/A
$418
N/A
N/A
$418
Settled
No
kalshi

61° to 62°

0%
Yes 0¢No 100¢
100¢
N/A
$265
N/A
N/A
$265
Settled
No
Total markets: 6

Description

The overnight low temperature in Minneapolis on June 3, 2026, will be recorded by the National Weather Service.

Frequently asked questions

The PredictionHero dashboard tracks real-time odds and trading activity for the lowest temperature outcome in Minneapolis on June 3, 2026, on Kalshi. You can monitor the current implied probability of each temperature threshold, historical price movements, and $4,015 in 24-hour trading volume. The dashboard updates continuously as traders buy and sell shares, reflecting the market's collective forecast for that day's minimum temperature in Minneapolis. This live data helps you understand how prediction market participants are pricing the likelihood of different low-temperature scenarios.

Prediction market odds on Kalshi for the lowest temperature in Minneapolis on June 3, 2026, represent real-money forecasts from traders with financial incentive to be accurate. Traditional weather analyst forecasts, issued by the National Weather Service and meteorological models, typically focus on expected conditions rather than probability distributions across outcome ranges. Comparing the two reveals whether markets are pricing in more uncertainty, tail risks, or consensus around specific temperature thresholds than official forecasts suggest. Markets often incorporate late-breaking atmospheric data and trader conviction in ways that complement but may diverge from institutional predictions.

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the lowest temperature in Minneapolis on June 3, 2026, is priced as a binary or range-based contract where traders buy and sell shares corresponding to specific temperature outcomes. The market price reflects the collective probability assigned by participants to each outcome bracket. Kalshi's order book and continuous trading mechanism allow prices to adjust in real time as new weather data, seasonal patterns, and atmospheric forecasts emerge. Traders profit by correctly predicting which temperature range will occur, creating incentives for accurate pricing that incorporates available meteorological information and historical climate data for early June in Minneapolis.

The market resolves on Jun 4, 2026, after the close of trading on June 3, 2026. Resolution is determined by the official recorded lowest temperature for Minneapolis on that date. The outcome is typically sourced from the National Weather Service or equivalent official meteorological records to ensure an objective, verifiable result. Once the actual low temperature is recorded and confirmed, the market settles based on which outcome bracket or threshold the recorded value falls into, and traders holding the correct outcome receive their payout.

Several factors could shift market odds for the lowest temperature in Minneapolis on June 3, 2026. Major weather pattern changes—such as shifts in jet stream positioning, development of high or low pressure systems, or tropical activity affecting North American weather—will influence trader expectations. Seasonal climate anomalies, including El Niño or La Niña conditions, affect early June temperatures across the Upper Midwest. Updated medium-range and long-range forecasts from meteorological models will drive trading as June approaches. Historical temperature records and typical early-June climate normals for Minneapolis also serve as reference points. Real-time atmospheric observations and ensemble forecast consensus will be key catalysts for price movement.