Industry Context
It’s not just about fees — the whole industry is shifting. A few years ago, prediction markets were niche, almost underground. Fast-forward to now, and they’re entering the mainstream.
The big headline: Polymarket, after years of being blocked in the U.S., is coming back in a legal, regulated form. They recently acquired a regulated exchange and got a green light from the CFTC to operate under U.S. law. That’s huge — it means the biggest, most liquid crypto-driven prediction market is suddenly available to American users without the VPN workaround. This move doesn’t just legitimize Polymarket; it signals that regulators are warming up to prediction markets as a financial instrument, not just a novelty.
Meanwhile, Kalshi has leaned hard into legitimacy by pitching itself not just as a political or economic forecasting tool, but also as a way to trade sports event contracts. Want to buy shares on whether a team makes the playoffs, or if a star QB throws for 300 yards? Kalshi has pushed to make these legal under CFTC oversight. This is where the line between “finance” and “sports betting” gets blurry — some state regulators argue it looks like gambling, while Kalshi frames it as a new category of tradable event derivatives. The debate is still ongoing, but the fact that Kalshi is even allowed to test these waters shows how much the landscape has shifted.
PredictIt, still running under its older “no-action” letter with caps and restrictions, feels stuck in the past compared to these two.
Fee Differences
Polymarket keeps things super lean. There are no trading Polymarket fees when you buy or sell contracts.
Kalshi takes a more “financial exchange” approach. Kalshi fees come from a small transaction charge on your expected earnings as defined here. Depending on whether you’re a market maker / taker and what the contract price is, your fees can range from close to 0% to a maximum of 1.75%.
PredictIt is the most old-school (and arguably the priciest with its fees). They lop off 10% of your profits whenever you cash out a winning trade, plus another 5% fee if you want to withdraw your money. If you lose a bet, there’s no fee — but obviously you’re still out the cash. For casual traders, this model is punishing, and it makes short-term trades particularly unattractive.
Why Fees Matter
Fees also play into how “efficient” markets are. With lower costs, arbitrageurs jump in quickly to correct mispricings. With higher fees, some inefficiencies just linger, which means the market’s “implied probabilities” might not reflect reality as well. That’s part of why Polymarket feels so sharp — traders can move in and out without friction. By contrast, PredictIt’s structure almost disincentivizes active trading, which can leave its markets stale or distorted.
As Polymarket enters the prediction market landscape in the United States with its zero-fee model, I would expect other prediction markets to feel the competitive pressure to lower fees themselves. While this might hurt the bottom line for prediction market companies, lower fees is something all traders can get behind.
As always, if you want to figure out how fees can impact the contract price, you can use Prediction Hunt’s free fee calculator.
How We Incorporate Fees Into Our Estimated Returns
When you see estimated returns in the "Smart Bets" tab on Prediction Hunt, those numbers already factor in platform-specific fees.
On PredictIt, we account for their 10% fee on profits. That means if a trader wins $100 on a contract, they only keep $90 after fees. PredictIt also charges a 5% withdrawal fee, but we don’t incorporate that one since it varies depending on how often users cash out. The 10% profit fee, though, directly impacts returns and must be included to make comparisons realistic.
For Polymarket, things are simpler — they currently have no trading fees on market buys or sells. So for those markets, what you see is what you get: our return estimates reflect pure price differences, without deductions.
Kalshi, on the other hand, operates more like a regulated financial exchange. They charge both maker and taker fees, depending on your order type. To stay conservative, we use the taker fee formula, which is applied to the full contract value:
Fee = 0.0175 × P × (1 - P)
where P is the contract price in dollars (so a 50¢ contract means P = 0.5). This effectively scales the fee with the liquidity and risk of the contract — and we round up to the nearest cent to mirror real-world execution.
These adjustments ensure that when you see a “risk-free return” on Prediction Hunt, it already reflects the fees you’d realistically pay. Arbitrage looks great in theory — but after fees, some edges shrink fast. Our goal is to make those returns as close to real-world performance as possible.