Contract prices, implied probability, expected value, and how to spot when the market is wrong.
It means the market implies a 62% probability of the event happening. If it resolves YES, you get $1 per contract; if NO, $0.
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Every YES contract trades between $0.01 and $0.99. Multiply by 100 and you have the implied probability. $0.34 = 34% chance.
YES and NO prices on a binary market should sum to roughly $1.00. The gap is the spread — your cost to enter and exit. Once you can read a price, the next step is figuring out where to trade these odds at the lowest cost.
EV = (your probability − market probability) × payout. If you believe an event is 60% likely and the market prices it at 45%, every $1 of YES is worth $1.33 long-run. That's edge.
No edge, no trade. The fees and spreads will grind you down otherwise.
Look for thin markets the algos haven't found, news the crowd hasn't processed, and binary events with structural bias (home-team optimism, recency, headline overreaction).
Cross-check against public data — Google Trends, polling aggregators, on-chain flows. Note the limit of that idea: the 2025 'd4vd' trade that made $1M in 24 hours turned out to be an alleged insider trade — a Google engineer was charged by the DOJ in May 2026 — so public-data edges are legal, non-public ones are not.
It means the market implies a 62% probability of the event happening. If it resolves YES, you get $1 per contract; if NO, $0.
The gap is the spread — bid/ask depth plus market maker margin. Tight, liquid markets get within a cent; thin markets can be 5+ cents apart, which is where much of your cost lives.
Build your own probability estimate first (model, polls, base rates). If your estimate differs from the market by more than the spread plus fees, you have theoretical edge.
Both show YES/NO cents. Kalshi displays some markets as US-style probability percentages; Polymarket almost always shows the raw contract price.
Catie has spent 15 years covering iGaming, sports betting, and now prediction markets — first as a trade reporter, later as head of editorial at two major industry publications. She has tested every regulated US event exchange since Kalshi's 2021 launch and writes the bulk of PredictionWins' platform reviews and tax explainers.
Reviewed against our editorial policy.
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