--- url: "https://predictiontoolkit.com/tools/functionspace/" publisher: "PredictionToolkit" dateModified: "2026-11-03" --- [← Starter projects & resources]() ![functionSPACE logo]() Learning & media # functionSPACE: Continuous-Outcome Market Design and Payoff Demos functionSPACE offers a way to study how payouts can vary across a numerical outcome range. Its public interactive example sits alongside explanations, research and a developer-package entry point for comparing continuous-outcome designs with binary thresholds. [**3.0**/ 5Editorial rating]() [Editorial assessment]() [Explore functionSPACE]() functionspace.dev **Available on:** Web · Developer package **Pricing:** [See plans and costs ↓]() [Screenshots]() [Explore alternatives]() **Availability: restricted** [Starter projects & resources]() [Learning]() +1 more [Forecasting]() ## Screenshots and interface Product preview1 / 1 The public example is a prototype and does not establish production availability. ## What is functionSPACE? Use the example to compare threshold, interval, linear and custom payoff shapes. The site introduces a core package and related experimental applications, providing material for studying numerical-outcome pricing, payoff surfaces and market construction. The project states that previous markets used play money on an off-chain engine, while its on-chain contracts are a proof of concept. Neither a Polymarket execution integration nor production solvency was verified. Public learning is available, but production availability, builder access and production pricing need confirmation; broader access includes a waitlist. ### Who it is for - Builders studying continuous-outcome market design. - Researchers comparing binary payoffs with other payoff shapes. ## Features and coverage - **Interactive payoffs** Explore yes/no, range, linear and custom payoff shapes. - **Research and learning** Read explanations and studies of markets with numerical outcomes. - **Developer entry point** The site introduces a core package and related experimental applications. ## Workflows with functionSPACE ### Compare payoff shapes Read the public example as a map from a numerical outcome to a payout. Switch between threshold, interval and linear shapes, then compare which parts of the outcome range each covers and how the payout changes. ### Assess a builder concept Read mechanism and status notes before deciding whether the prototype fits a research project. ## Pricing and total cost Budgeting for production use requires information beyond the public learning pages. Those pages and the demo were accessible in the source review, but no production price was established; wider access includes a waitlist. **Access:** Public learning works in the browser. Confirm production and builder availability with the project. ## Getting started **Before you start:** The play-money history and proof-of-concept contracts limit the project’s maturity. 1. Open the public payoff example. 2. Switch among the available payoff shapes. 3. Read the mechanism and maturity notes before evaluating a build. Public browser-based learning is available; production and builder availability must be confirmed with the project. ## Useful links ### What to check - The play-money history and proof-of-concept contracts limit the project’s maturity. - No Polymarket execution integration or production solvency was verified. A closer look ## Ratings & reviews Editorial rating **3.0**/ 5 0 user reviews PredictionToolkit editorial ### Our take on functionSPACE Seeing numerical payout shapes side by side gives this resource a clear learning use. That educational value should guide expectations: prototype documentation is not evidence that the project is ready for production operation. Based on documented features, setup and access terms. [How we rate]() ### User reviews 0 The main score switches to user ratings after 5 published reviews. **Be the first to share your experience** A specific example helps the next person choose the right tool. ## Related tools [Browse category]() ![MKTGAP’s public manual-input prediction-market fee calculator.]() ![MKTGAP logo]()[MKTGAP]() Analytics**4.0**Editorial A public manual calculator separating a gross price gap from fee-adjusted pair costs. - Access Web Study fee-adjusted binary contracts alongside numerical payoff surfaces. ![polymm README explaining the retired Python bot and limitations]() [polymm]() Learning & media**3.5**Editorial Educational source code and a retrospective on a retired Polymarket sports market-making bot. - Access Python · Source code Also in Starter Projects and Builder Resources. ![Kuest official builder-platform presentation]() ![Kuest logo]()[Kuest]() restricted Platform**3.0**Editorial An early-access builder proposition for custom-branded prediction frontends, mirrored markets and developer integrations. - Access Web Compare numerical-outcome experiments with hosted market-building tools. ## Frequently asked questions about functionSPACE ### Is this a live Polymarket trading integration? The reviewed material supports studying market design and trying the public examples. It does not verify a connection that places live Polymarket orders, so a demonstration should not be taken as evidence of that integration. ### Are its on-chain contracts production-proven? The site calls them a proof of concept and says previous markets ran with play money on an off-chain engine. ### What does access cost? Use the public demonstration and learning material to explore the concept. A production budget cannot be inferred from that access: the reviewed sources did not establish production pricing, and broader access includes a waitlist. ### What access is confirmed? Public learning is available in the browser. Confirm production and builder availability with the project. In this profile