How accurate are Kalshi’s prices?

Original analysis · updated July 18, 2026 · by the ContractTax team

A prediction market only works if its prices mean what they say, a contract at 70¢ should win about 70% of the time. We tested that on Kalshi by matching our full harvested history of settled markets to the prices they traded at, then checking how often each price level actually resolved YES. Here is what 1,757 settled observations show.

Headline finding
Across 1,757 settled Kalshi market observations, prices were accurate to within
4.4 pointsaverage, of what the price implied
In plain terms: Kalshi’s crowd is well-calibrated. What the price says is close to what actually happens, which is the whole premise of a prediction market working.

What each price actually settled at

PriceActual YES rateActualImpliedn
09¢
13.7%5%146
1019¢
12.2%15%123
2029¢
27.1%25%144
3039¢
32.1%35%187
4049¢
49.7%45%312
5059¢
57.6%55%309
6069¢
67.8%65%214
7079¢
75.4%75%118
8089¢
76.0%85%104
9099¢
80.0%95%100
Bar = actual YES rate · white line = what the price implied. The closer they sit, the better calibrated.

The favorite-longshot bias

Even a well-calibrated market usually shows a small, well-documented distortion: longshots are overbet and favorites are underbet. Our data bears this out.

LONGSHOTS (1–30¢)
Priced around 15%, they actually settled YES 17.9% of the time.
FAVORITES (70–99¢)
Priced around 84%, they actually settled YES 77.0% of the time.
Cite this analysis
ContractTax, "How Accurate Are Kalshi's Prices?", July 18, 2026. https://www.contracttax.com/how-accurate-are-kalshi-markets
Free to cite or reproduce with a link back to this page. Journalists and researchers welcome, reach us via the site.

Accuracy is not one number

Kalshi is a different forecaster depending on what it is forecasting: a market full of economists pricing CPI is not the same crowd as a market full of fans pricing a game. So we publish a separate measured curve for each subject. If you trade one category, its own curve is the number that matters to you, not the blended one above.

politics
How accurate is Kalshi at politics? →
economics
How accurate is Kalshi at economics? →
sports
How accurate is Kalshi at sports? →
crypto
How accurate is Kalshi at crypto? →
tech
How accurate is Kalshi at tech? →
world
How accurate is Kalshi at world? →
entertainment
How accurate is Kalshi at entertainment? →
weather
How accurate is Kalshi at weather? →

Methodology

We continuously harvest Kalshi markets and record their prices, then match each to its settled outcome. Markets are grouped into ten price buckets by their recorded pre-settlement price, and for each bucket we compute the share that resolved YES. The headline figure is the sample-weighted mean absolute difference between the actual YES rate and the price-implied rate, across buckets with at least 20 observations.

Caveats: the dataset grows daily, so figures update over time. Extreme-price buckets (0–9¢ and 90–99¢) can be affected by prices recorded very close to settlement, so we read them with more caution. Prices are our own scanner’s observations, not resold exchange data. See the live view in the Truth Machine, or grab the raw numbers from our open datasets. Not affiliated with Kalshi.