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Scalar Market

A scalar market is a prediction market that resolves to a specific numerical value within a predefined range rather than a simple yes-or-no outcome, with payouts allocated proportionally based on where the resolved figure falls between the upper and lower bounds.

Updated June 25, 2026Market Fundamentals
TL;DR
Scalar markets let you trade on a numerical outcome like an index level or temperature, with payouts proportional to how close the result is to your position.

Key Points

✓Scalar markets define a lower bound and an upper bound; the resolved value anywhere in that range determines payouts.
✓Unlike binary markets, scalar markets are not winner-take-all -- both LONG and SHORT positions can receive partial payouts.
✓Common scalar market questions include economic indicators, asset prices, vote totals, and scientific measurements.
✓A LONG position profits when the resolved value is closer to the upper bound; a SHORT position profits when it is closer to the lower bound.
✓If the resolved value falls at or beyond the upper bound, LONG holders receive the full $1.00; at or below the lower bound, SHORT holders receive the full $1.00.

How Scalar Market Payouts Work

In a scalar market, the platform sets a numeric floor and ceiling at market creation. When the event resolves, the outcome is measured against this range. A LONG share pays out proportionally: payout = (resolved value - lower bound) / (upper bound - lower bound). For example, if the range is 0 to 100 and the outcome resolves at 70, LONG holders receive $0.70 per share and SHORT holders receive $0.30. This proportional structure contrasts sharply with the winner-take-all Binary Market format. Because neither side is completely wiped out unless the outcome reaches the extreme bounds, scalar markets encourage participation from traders with nuanced views about where a number will land rather than just whether an event will happen. The Contract Price in a scalar market reflects the market's expected value of the resolution within the range.

Scalar Markets vs. Binary and Categorical Structures

Scalar markets are best suited for continuous quantitative questions that do not reduce neatly to yes or no. They complement Binary Market and Categorical Market structures by covering domains like inflation rates, electoral vote counts, or cryptocurrency prices. Because payout depends on the precise resolved number, scalar markets carry unique Resolution Criteria challenges: the Resolution Source must provide an exact, auditable figure. Disputes about the measured value can trigger Dispute Resolution processes. Liquidity on scalar markets can be lower than on binary markets because pricing requires traders to estimate a full distribution rather than a single probability. Platforms using Automated Market Maker systems, such as those implementing the Logarithmic Market Scoring Rule, can supply baseline liquidity even when few counterparties are present.

Related Terms

Binary Market
A binary market is a prediction market in which exactly two mutually exclusive outcomes are possible, typically labeled YES and NO, with one contract paying $1.00 and the other paying $0.00 at resolution. It is the most common market structure on platforms like Kalshi and Polymarket.
Categorical Market
A categorical market is a prediction market that lists three or more mutually exclusive discrete outcomes, where exactly one outcome pays $1.00 at resolution and all others pay $0.00. Common examples include multi-candidate elections, tournament winners, or central bank decisions with several possible rate options.
Resolution Criteria
Resolution criteria are the precise rules written into a prediction market contract that define exactly what outcome must occur, what source will confirm it, and how edge cases will be handled.
Contract Price
The contract price is the current market price of a single prediction market share, expressed as a value between $0.00 and $1.00, which simultaneously represents the cost to enter the position and the crowd's probability estimate for that outcome.
Logarithmic Market Scoring Rule
The Logarithmic Market Scoring Rule (LMSR) is a cost-function-based automated market maker designed for prediction markets by economist Robin Hanson. It guarantees continuous liquidity, keeps prices bounded between 0 and 1, and caps the market operator's worst-case loss at a known value.

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