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Documentation Index

Fetch the complete documentation index at: https://pond.dflow.net/llms.txt

Use this file to discover all available pages before exploring further.

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What Prediction Markets Are

In a prediction market, users trade on the outcome of a real-world event, expressed as a yes or no question. For example: Will the Boston Red Sox win the World Series? Users trade either yes or no.
Outcomes are always binary. Even in a matchup like Boston Red Sox vs. New York Yankees, the market does not ask “Which team will win?” Instead, each team has its own yes/no market, such as “Will the Boston Red Sox win the World Series?” and “Will the New York Yankees win the World Series?”
The market price acts like a probability-like signal because it reflects how traders are entering positions under financial incentives. In practice, users do the same things they do in spot markets: discover markets, view prices, place trades, and manage positions. What changes is the asset being traded, and the skill set that can produce an edge. Spot trading often rewards understanding an asset and its market structure. Prediction markets can reward different strengths: interpreting news quickly, reasoning about incentives, estimating odds, and understanding how resolution criteria translate into payouts.

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Why You Should Care

In 2025, total volume across major prediction market platforms reached about $44B, with most volume split between Polymarket and Kalshi. Prediction markets turn real-world events into tradable assets. This creates new opportunities for trading UX, portfolio UX, and post-event settlement UX without inventing a new interaction model.

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Why Tokenization Matters

Tokenizing prediction markets on Solana makes them usable inside the rest of the onchain economy. Instead of keeping positions inside a single venue (Kalshi), builders can treat prediction market positions like other SPL tokens and unlock new product designs. For example, builders can create apps where users:
  • Trade outcomes inside a Solana wallet.
  • Track positions alongside spot holdings.
  • Route trades through Solana trading primitives.
  • Use outcome tokens in other onchain apps while markets are open.
This is the main reason builders often prefer a tokenized integration over direct trading with Kalshi.

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How Prices Map To Probabilities

Prediction market prices are often read as probabilities because they reflect how traders are willing to position under risk. If a “Yes” outcome is trading at 60, traders are collectively pricing that outcome as roughly a 60% chance. If new information appears, traders adjust their positions, and the price moves. This makes prices easy to reason about: they update as information changes, and they summarize many independent views into a single signal. Vitalik Buterin has described prediction markets as useful because they reward being correct and penalize being wrong, which helps prices converge toward accurate expectations over time.

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How DFlow Supports Prediction Markets Today

DFlow’s Prediction Markets API gives builders programmatic access to tokenized Kalshi markets on Solana, so you can offer prediction market trading with the same primitives you use elsewhere on Solana.
Kalshi is a U.S. prediction market platform that offers event contracts and operates under CFTC oversight.

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Outcome Tokens

Outcome tokens are tokens that represent positions in a prediction market outcome. A market typically maps to outcome tokens like “Yes” and “No.” Users can buy, sell, and hold these tokens while the market is open. From a user’s perspective, they behave like other tokens:
  • Users can trade them again before resolution.
  • Users can hold them as a position.
  • Users can redeem after resolution.
For builders, this maps prediction markets to a familiar token model: balances, positions, transfers, and redemption flows.

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How Markets Resolve

Every market resolves to an outcome. Resolution is the transition from “trade” to “settle”:
  • One side becomes redeemable.
  • The other side becomes worthless.
This enables both pre-event trading and post-event payout UX in the same app.

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How Settlement And Redemption Work

After resolution, users redeem outcome tokens for value according to the market result. This creates a second phase of UX that does not exist in spot trading:

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Entering a Position in a Prediction Market

Entering a prediction market position follows this flow:
  1. A user discovers a prediction market.
  2. The user selects an outcome to trade.
  3. A quote is requested for that outcome.
  4. The user signs and submits a trade.
  5. The user receives an outcome token representing their position.
From this point on, outcome tokens behave like other SPL tokens until the market resolves.

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What Builders Can Build

  • Market discovery (categories, search, trending).
  • Market detail pages (price chart, liquidity, positions).
  • Trading UX for outcome tokens (buy/sell, limits, slippage).
  • Portfolio + PnL views across spot and prediction positions.
  • Automation (alerts, conditional trades, rebalancing).
  • Post-resolution redemption UX and receipts.
  • Composable apps that treat outcome tokens like other assets (for example, collateral or lending primitives).

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Compliance

Buying outcome tokens requires KYC verification, and prediction markets are restricted in some jurisdictions. See KYC for Kalshi and Prediction Market Compliance for details.

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Code Recipes