PREDICTION MARKET DEVELOPMENT
PROPELOO engineers prediction market platforms — market creation, liquidity provision, AMM-based or order-book-based price discovery, oracle integration for resolution, dispute resolution mechanics, and the payout distribution that executes automatically when a market resolves. A prediction market where resolution is controlled by a single party is not a prediction market — it is a betting platform with a dressed-up name.
Prediction markets are information aggregation systems. Participants trade on their beliefs about future outcomes; prices reflect aggregate probability estimates. The value of a prediction market comes from the credibility of resolution: when the event occurs, the market must resolve correctly, automatically, and in a way that cannot be manipulated. PROPELOO designs prediction markets with resolution as the primary engineering concern — oracle integration for objective resolutions (sports scores, price feeds, election results), UMA or Kleros dispute resolution for subjective markets, and the conditional token framework (ERC-1155 outcome tokens) that represents positions correctly regardless of market resolution method. Liquidity mechanisms — LMSR, CPMM, or order book — determine the price discovery quality and the capital efficiency of the platform.
Market creation, liquidity, price discovery and resolution are four distinct engineering systems.
Any account can create a market with defined outcomes, resolution criteria, resolution source and end date. Creator staking as quality signal. Market categories: sports, finance, politics, custom events.
CPMM (constant product market maker) for binary markets, LMSR (logarithmic market scoring rule) for automated market making with guaranteed liquidity. LP positions represented as shares. Trading fees accrued to LPs.
CLOB (central limit order book) for higher-volume markets where price discovery benefits from discrete orders. Limit and market orders. Order book state kept off-chain with on-chain settlement.
Chainlink for financial price feeds, custom oracle for sports data APIs, Chainlink Functions for arbitrary API calls. Oracle result triggers automatic market resolution and payout.
UMA optimistic oracle for subjective markets — anyone can dispute a proposed resolution with a bond, dispute goes to UMA token holder vote. Kleros for decentralised jury-based arbitration.
On resolution, winning outcome tokens redeemable 1:1 for collateral. Losing tokens redeemable for 0. LP fees distributed proportionally to LP shares. Automatic — no admin action required.
The credibility of a prediction market is entirely determined by the trustworthiness of its resolution mechanism.
A market that resolves based on a single admin decision can be manipulated. A market that resolves based on a verifiable on-chain oracle cannot. The choice of resolution source — centralized oracle, decentralized oracle, dispute mechanism — is the most important design decision, not the AMM curve.
Axiom: RESOLUTION FIRST
A prediction market with no liquidity has wide spreads and cannot attract traders who want meaningful position sizes. LPs need sufficient incentive to provide liquidity — trading fee yield plus market creator incentives. LMSR provides guaranteed liquidity but requires capital; CPMM relies on LP capital. The liquidity model must match the expected market volume.
Axiom: LIQUIDITY IS THE PRODUCT UTILITY
ERC-1155 outcome tokens that can be transferred and used in DeFi protocols (as collateral, in yield strategies) increase the utility of holding positions beyond the prediction market itself. This is the architecture that Polymarket and Gnosis Conditional Tokens use — and it is the correct design for any platform targeting DeFi-native users.
Axiom: COMPOSABLE POSITIONS
These choices define resolution credibility, liquidity depth and user experience.
Impact: AMM for new platforms — guaranteed liquidity without requiring active market makers. Add CLOB for high-volume markets where price discovery quality becomes important.
Impact: L2 deployment (Polygon, Base, Arbitrum) for gas cost management. Off-chain order book with on-chain settlement for CLOB markets.
Impact: Chainlink for objective financial/sports data. UMA optimistic oracle for subjective markets. Multisig only for MVP with explicit plan to decentralise.
Impact: USDC as primary collateral. Add ETH/WBTC after initial traction. Native token collateral only if tokenomics specifically benefit from it.
AMM-based sports prediction platform — match outcome markets, score markets, oracle resolution via sports data API.
Price prediction markets — will ETH be above $X by date Y? Chainlink oracle resolution, USDC collateral.
General event markets with UMA dispute resolution for subjective outcomes.
Internal corporate prediction markets for forecasting — product launch dates, sales figures, project timelines.
Polymarket-inspired open prediction market platform on L2 — market creation, CLOB trading, oracle resolution.
Smart contracts for trust, off-chain infrastructure for performance.
Stack: Solidity 0.8+, Gnosis Conditional Tokens, ERC-1155 outcome tokens, UMA optimistic oracle, Foundry (testing)
Stack: CPMM / LMSR contracts, Off-chain order book (CLOB), Chainlink price feeds, Automated market making, Liquidity pool management
Stack: Node.js / Go indexer, The Graph (event indexing), PostgreSQL (positions, markets), Redis (real-time prices), WebSocket (live updates)
Stack: React / Next.js, WalletConnect / MetaMask, Recharts (price history), Market discovery UI, Portfolio dashboard
An oracle that can be manipulated to resolve a market incorrectly enables the attacker to profit from positions taken before the manipulation.
Using a single data source for resolution creates a manipulation target. Multi-source median aggregation, dispute windows, and economic incentives for correct reporting (UMA token staking) reduce this risk.
Low-liquidity AMM markets can have prices manipulated cheaply. Minimum liquidity requirements for market activation, position size limits relative to pool size, and time-weighted price mechanisms reduce manipulation profitability.
Prediction market contracts handle user funds and must be audited before mainnet. Key audit areas: payout calculation correctness, resolution state machine, LP share accounting, reentrancy in payout distribution.
Dispute mechanisms can be griefed by actors who dispute correct resolutions to delay payouts. Dispute bonds must be sized to make frivolous disputes economically irrational.
Outcome token model, liquidity mechanism, resolution source, dispute process, fee structure.
Market factory, conditional tokens, AMM/CLOB contracts, oracle integration, resolution logic.
Chainlink feeds, API oracle setup, UMA/Kleros integration, resolution testing.
Event indexer, market data API, position tracking, WebSocket feeds.
Market discovery, trading interface, portfolio, resolution history.
Smart contract audit, oracle security review, economic attack analysis.
Testnet markets, liquidity seeding, mainnet launch, monitoring.
On the resolution date, an oracle reports the outcome. If the oracle is Chainlink, the contract reads the price feed directly. If UMA, a proposer submits the result and a dispute window opens — if no dispute, the result is accepted. The market contract then allows winning-side token holders to redeem their tokens 1:1 for collateral.
With UMA optimistic oracle, any token holder can dispute a proposed resolution by posting a bond. The dispute goes to UMA token holder vote. If the resolution is overturned, the original proposer loses their bond. This economic mechanism incentivises correct reporting.
LPs deposit collateral into the AMM and receive LP shares. The AMM mints equal quantities of all outcome tokens and holds them. Traders buy/sell outcome tokens from the AMM, with the price determined by the AMM curve. LPs earn a percentage of every trade. On resolution, LP shares are redeemable for their proportional share of the pool value after payout.
Yes — permissionless market creation with creator staking as a quality signal (creators who create markets that resolve invalidly lose their stake). Category review and market quality scoring can be layered on top of permissionless creation to surface high-quality markets.
Using the Gnosis Conditional Token Framework (ERC-1155), markets can support categorical outcomes (e.g., candidate A, B, or C) and combinatorial split conditions. The contract partitions collateral into discrete position tokens that redeem proportionally upon outcome resolution.
We deploy hybrid Central Limit Order Books (CLOB) where traders create and sign limit orders off-chain using EIP-712 structured data. The matching engine matches orders with zero gas overhead, submitting only the final netted settlement batch to the blockchain contract.
We build institutional compliance controls: strict IP geofencing, VPN detection, and tiered KYC verification modules. Operators can configure permitted regional jurisdictions and enforce regulatory exclusions (such as CFTC restricted territory blocking) directly at the gateway layer.
Yes. We design on-chain reward distributor contracts that calculate programmatic liquidity incentives. Liquidity providers and high-volume market makers receive weekly token rewards calculated from order book depth, spread tightness, and total executed turnover.