What are Prediction Markets?
Prediction markets are platforms where users can bet on the outcomes of future events. They aggregate information from participants to create probabilistic forecasts about real-world events. Think of them as betting markets for anything verifiable:- Will Bitcoin reach $100k by end of year?
- Who will win the next election?
- Will it rain tomorrow in New York?
- Will a new product launch on time?
How Prediction Markets Work
1
Market Creation
Someone creates a market with:
- A clear yes/no question (or multiple outcomes)
- A resolution date/time
- Resolution criteria
2
Trading Phase
Users buy and sell positions based on what they think will happen.Prices represent probability:
- A “YES” token at $0.70 = 70% chance of YES
- A “NO” token at $0.30 = 30% chance of NO
3
Resolution
At the predetermined time, the market is resolved based on real-world outcome.This is where delphAI comes in - automating this step with AI.
4
Settlement
Winners receive payouts based on their positions.
- If outcome is YES, YES token holders get $1 per token
- If outcome is NO, NO token holders get $1 per token
Why Prediction Markets Matter
Crowd Wisdom
Aggregate knowledge from many participants often produces accurate forecasts
Real-time Probability
Prices update constantly as new information emerges
Financial Incentive
People have skin in the game, incentivizing accurate predictions
Transparent Forecasting
All predictions are public and verifiable onchain
The Oracle Problem
Prediction markets have one critical dependency: accurate resolution.Traditional Problems:
Manual Resolution is Slow
Human oracles need time to find the correct data, verify its authenticity, and submit the result. This can take hours or days after the event.
Centralization Risk
Centralized oracles create trust issues: single point of failure, potential for manipulation, and bias in subjective decisions.
Doesn't Scale
Manual resolution limits market variety. Each market needs human attention, can’t have thousands of simultaneous markets, and has high operational costs.
Disputes are Messy
When resolution is contested, it requires expensive dispute processes, time-consuming governance votes, and creates community conflicts.
delphAI’s Solution
delphAI solves the oracle problem by automating resolution with AI:Key Advantages:
Instant
Resolves at exact scheduled time, no delays
Trustless
No human bias, pure data-driven outcomes
Scalable
Can resolve unlimited markets simultaneously
Cost-Effective
Much cheaper than manual oracle networks
Verifiable
All data sources and logic are transparent
24/7 Available
Works around the clock without downtime
Types of Markets
delphAI can resolve various market types:Binary Markets (YES/NO)
Most common format - two possible outcomes. Example: “Will ETH price be above $5,000 on January 1, 2026?”- Outcome: YES or NO
- Resolution: Check ETH price at specified time
Categorical Markets
Multiple exclusive outcomes, only one can win. Example: “Who will win the 2026 World Cup?”- Outcomes: Brazil, Argentina, France, Germany, Other
- Resolution: Check official FIFA results
Scalar Markets
Numeric outcome within a range. Example: “What will be the temperature in NYC on Dec 25?”- Range: 20°F to 50°F
- Resolution: Check weather data at specific time
Market Design Best Practices
For platforms integrating delphAI:Clear Questions
Clear Questions
✅ Good: “Will BTC close above $100k on Dec 31, 2025 (UTC)?”❌ Bad: “Will Bitcoin do well this year?”Questions must be:
- Unambiguous
- Time-specific
- Objectively verifiable
Reliable Data Sources
Reliable Data Sources
Specify exact data sources in resolution criteria:✅ “Use CoinGecko API for BTC price”❌ “Check the price somewhere”Better: Multiple sources for redundancy
Appropriate Timeframes
Appropriate Timeframes
Consider:
- Data availability at resolution time
- Enough time for trading activity
- Not too far in the future (uncertainty)
Edge Case Handling
Edge Case Handling
Define what happens if:
- Data source is unavailable
- Market is ambiguous
- Unexpected events occur
Real-World Applications
Finance & Crypto
- Token price predictions
- Protocol TVL milestones
- Market cap rankings
- Launch dates
Sports & Entertainment
- Game outcomes
- Championship winners
- Awards ceremonies
- Box office performance
Politics & Governance
- Election results
- Policy decisions
- Approval ratings
- Referendum outcomes
Business & Tech
- Product launches
- Company metrics
- IPO pricing
- Tech adoption rates
Market Economics
Understanding how prediction markets create value:Price Discovery
Market prices reflect aggregate probability:| Price | Implied Probability |
|---|---|
| $0.10 | 10% chance |
| $0.30 | 30% chance |
| $0.50 | 50% chance (coin flip) |
| $0.80 | 80% chance |
| $0.95 | 95% chance |
Trading Mechanics
Users trade based on information:- New information emerges → Traders update beliefs
- Buy underpriced outcomes, sell overpriced
- Prices adjust to reflect new probability
- Market converges on true probability