Updated September 18, 2026
Prediction markets are increasingly moving beyond dedicated trading platforms. Recent CFTC guidance could make it easier for prediction-market access to appear inside financial apps, while Kalshi and Polymarket are also pushing their probabilities into the news and media people already consume.
That matters because prediction markets do more than create a place to trade. They also produce constantly changing probabilities about elections, interest rates, sports and other events.
Increasingly, those numbers are becoming content of their own.
You may never open Kalshi or Polymarket to trade.
But inside a news article, television broadcast, financial dashboard or newsletter, you could still see something like:
Fed rate decision: 72% probability
Candidate wins election: 58% probability
Team wins championship: 21% probability
Prediction-market companies want their probabilities to be useful even outside their own platforms.
Editor's notes
“The real opportunity may not be getting everyone to trade prediction markets. It may be getting everyone to check them.”
Someone checking Kalshi or Polymarket does not necessarily need to place a trade.
They may simply want to know what the market thinks.
Kalshi said in 2026 that roughly 70% of visitors were using its platform to check forecasts, while about 30% were using it to trade.
That suggests a large part of the audience is already treating prediction markets as an information source.
Kalshi has taken a direct route into traditional media.
The company has partnered with CNN, CNBC and FOX, allowing its prediction-market data to appear across television, digital and other news products.
Those partnerships do not turn CNN or FOX into places where viewers can trade.
What gets distributed is the information generated by the market.
Polymarket has taken a slightly different route.
Alongside outside media partnerships, it has built products such as The Oracle, its own newsletter focused on market movements and forecasts, and expanded its presence on Substack.
The idea is similar: prediction-market data can be useful to people who never place a trade.
The important point is not whether Kalshi or Polymarket should technically be called media companies.
It is that prediction-market data itself is becoming a media product.
Prediction-market probabilities fit naturally into news coverage.
They are easy to understand, constantly changing and simple to visualize.
A story about the Federal Reserve can show economist forecasts alongside the probability traders are assigning to a rate decision.
An election story can show polls alongside prediction-market probabilities.
They are not the same thing, however.
A poll measures responses from a group of people. A prediction-market probability reflects where buyers and sellers are willing to trade on an outcome at that moment.
Prediction markets are therefore another data point, not a guarantee of what will happen.
For prediction-market companies, the benefit is distribution.
Every time a publisher or television network displays a Kalshi or Polymarket probability, that platform reaches people who may never have visited its website.
The bigger goal may be becoming a reference point.
Instead of only asking what polls, economists or analysts expect, people could increasingly ask:
What do the prediction markets say?
Editor's notes
“Prediction markets don’t necessarily need everyone to become a trader. Weather apps don’t need you to be a meteorologist. If the probability itself becomes useful information, the audience can become much bigger than the number of people actually trading.”
This trend goes beyond media.
Recent CFTC guidance could make it easier for prediction-market access to appear inside financial software people already use. At the same time, Kalshi and Polymarket are working to get their probabilities into news products people already consume.
The common theme is distribution.
One user may eventually trade prediction contracts through another financial app.
Another may follow prediction-market probabilities through a news network without ever trading at all.
Either way, prediction markets are moving beyond their own platforms.
Stocks have prices. Elections have polls. Economic reports have forecasts.
Prediction-market companies want their probabilities to become another standard number people look at when trying to understand what could happen next.