How Do Prediction Markets Work?

Consider a yes-or-no market on whether a particular event occurs by a deadline. There is a Yes contract and a No contract, and they are mirror images: their prices add up to about 100 cents. If Yes is trading at 40 cents, No is trading near 60 cents. Buy Yes at 40 and, if the event happens, your contract settles at 100, for a gain of 60 cents per contract. If it does not happen, the contract settles at 0 and you lose the 40 you paid.

Because prices live between 0 and 100, you can read the market as a live probability estimate that updates every time someone trades. A move from 40 to 55 means the crowd, weighted by the money it is willing to commit, now thinks the outcome is meaningfully more likely than it did before.

Prices move for two broad reasons. The first is new information about the underlying event, which changes what participants believe and therefore what they are willing to pay. The second is order flow: the mechanical pressure of buy and sell orders hitting the book. A large buy that clears several price levels pushes the price up even before anyone outside the market knows why.

SharpPredict pays close attention to that second category, because order flow can move ahead of public news. If you want to see how those mechanics look in practice, the explainers on how to read an orderbook and on what a sweep is in order flow break down the specific patterns that tend to matter.

The feature that separates a prediction market from a pure guessing game is that every contract ends in a hard, real-world resolution. The event either happens or it does not, the market settles at 100 or 0, and the payouts are determined by that fact rather than by a house setting a line. This is a core reason SharpPredict treats resolved outcomes as the only honest basis for judging a wallet's record.

It is also why the comparison to sportsbooks matters. In a prediction market you are trading a contract against other participants, with the venue taking fees, rather than betting against a house that has priced a margin into the odds. The dedicated piece on prediction markets versus sportsbooks covers that distinction in detail.

SharpPredict tracks markets across venues, and the two flagship venues behave very differently at the data level. Polymarket is on-chain, so every trade carries a wallet address and large trades can be attributed to the wallet that placed them. Kalshi is a US-regulated exchange whose public data carries no user identities by design, so any read on who is informed there has to be inferred from market behavior rather than from attribution.

That difference shapes the whole product. On Polymarket, SharpPredict can build a Whale Tape and rank Sharp Wallets. On Kalshi, the same curiosity gets answered through order-flow signals like sweeps, book imbalance, and steam. Same underlying question, which is where informed money is moving, answered with the data each venue actually exposes.

The same real-world event can be listed on more than one venue, and the two listings do not always agree on price. SharpPredict normalizes contracts into a single canonical model so the same event lines up side by side, then surfaces the best available price and any gap between venues. A persistent price gap on equivalent contracts is one of the cleaner research signals in the whole space, because it points at a real disagreement or a real friction between the two order books.

All of this is research and comparison. SharpPredict is a data and affiliate front-end: nothing in the app places, routes, or executes a trade, and none of it is a recommendation to take a position.

A prediction-market price is a useful probability estimate, but it is not a flawless one. Liquidity varies enormously from one contract to the next. A heavily traded market with deep resting orders tends to hold a tight, well-informed price, while a thin market can sit at a stale number simply because few participants are active in it. Reading a price without checking how much size stands behind it can be misleading.

Fees and the bid-ask spread also sit between the quoted price and what you would actually pay. The best bid and best ask are rarely the same number, and crossing that gap has a cost. None of this breaks the core idea that price maps to probability, but it does mean a single quoted number is a starting point for research rather than a precise, frictionless truth.