In most binary prediction markets, the math looks simple: if a contract trades at 63, that means the market will buy “YES” for 63¢ and “NO” for 37¢. Under clean, competitive conditions, you can read that as an implied probability of about 63%. It’s a neat shortcut—you glance at the price and instantly see what the crowd thinks the odds are.
But here’s the catch: prices don’t always map neatly onto probabilities. They’re shaped—and sometimes distorted—by three big forces: liquidity and spreads, fees, and uneven information.
1. Liquidity and Spreads
Imagine the best “YES” ask is 65 and the best bid is 61. The midpoint (63) is a better proxy for the market’s probability than either quote alone. When spreads are wide, it’s usually a sign that trading is thin or uncertainty is high. In those cases, a single print doesn’t necessarily mean “the odds just changed”—it might just reflect poor liquidity.
2. Fees (The Hidden Tax)
Fee structures can quietly drag prices away from “true” probabilities. Say a market pays $1 at settlement, but the platform takes a 10% cut on winnings. Suddenly, that $1 payout is really worth 90¢. What looks like a fair 50/50 bet might trade closer to 45–46. If you’re comparing prices across platforms, always normalize for fees first—otherwise you’ll think one market is “smarter” when it’s just charging more tolls.
3. Asymmetric Information
Not everyone sees the news at the same time. If a poll drops or a court filing breaks, the traders who catch it first can “pick off” stale quotes. To the outside observer, those trades may look like sudden momentum or irrational volatility. In reality, the market is just digesting new information unevenly.
To summarize, here are some practical takeaways around how to read market prices:
- Use the midpoint of the inside quotes as your starting probability, not just the last trade.
- Adjust for fees if you’re comparing prices across platforms.
- Be extra careful around headlines and scheduled events, when prices can move for structural reasons, not because the crowd’s view truly shifted.
Think of prediction market prices as weather forecasts: they’re quick, useful snapshots of sentiment—but only if you know how to read the instruments correctly.
