Token incentive models (game theory)
What you'll learn in this Analysis
How token incentives shape user behavior
Why some incentive systems succeed while others fail
The role of game theory in Web3 design
A framework to evaluate token incentive models
1. The Core Idea
Every Web3 protocol is a system of incentives.
Users do not act randomly. They respond to:
Rewards
Risks
Opportunities
Key Insight
A protocol is not just code. It is a game where participants optimize for profit.
2. What is Game Theory in Web3?
Game theory studies how participants make decisions based on incentives.
In Web3:
Users seek maximum returns
Protocols design reward structures
Outcomes depend on collective behavior
Simple Principle
Users will always choose the most profitable strategy available.
3. Types of Incentive Models
1. Emission-Based Incentives
How it works
Tokens are distributed as rewards
Users earn yield
Goal
Attract users
Bootstrap liquidity
Problem
Creates inflation
Encourages short-term behavior
2. Revenue-Based Incentives
How it works
Rewards come from protocol revenue
Users earn from real activity
Goal
Align incentives
Create sustainability
Advantage
Long-term viability
3. Hybrid Models
How it works
Combine emissions + revenue
Goal
Early growth + later sustainability
4. Game Theory Dynamics
Cooperation vs Extraction
Protocols aim for cooperation:
Users provide liquidity
Users contribute value
Users often optimize for extraction:
Maximize rewards
Minimize risk
Exit quickly
Insight
If extraction is more profitable than contribution, the system will break.
5. The “(3,3)” Concept
Popularized by Olympus DAO:
If everyone cooperates → system grows
If users defect → system collapses
Problem
In reality:
Users act individually
Not collectively
Result
Cooperation fails
Selling begins
6. Incentive Misalignment
Common Issue
Protocols reward behaviors that:
Do not create value
Extract value instead
Example
Liquidity mining:
Users deposit funds
Earn tokens
Sell tokens
Outcome
Short-term liquidity
Long-term collapse
7. Sustainable Incentive Design
What Works
1. Value Creation
Users contribute to the system
2. Aligned Rewards
Rewards tied to real activity
3. Long-Term Incentives
Encourage holding
Encourage participation
Example
GMX:
Rewards from trading fees
Incentives aligned with usage
8. The Incentive Trap
High APY Systems
Attract rapid growth
Create unsustainable pressure
Cycle
High rewards attract users
Token supply increases
Selling pressure rises
Price drops
Users leave
Insight
High APY is often a signal of risk, not opportunity.
9. Operator Framework
When evaluating incentive models, ask:
1. Where do rewards come from?
2. Are users contributing or extracting value?
3. What happens when rewards decrease?
4. Is behavior aligned with system growth?
10. Common Mistakes
Mistake 1
Assuming incentives guarantee success
Mistake 2
Ignoring token inflation
Mistake 3
Overvaluing short-term growth
11. Real Insight
Protocols do not fail because users behave incorrectly. They fail because incentives allow harmful behavior.
12. Final Takeaway
Strong incentive models:
Align user behavior with system growth
Reward value creation
Encourage long-term participation
Weak incentive models:
Reward extraction
Depend on emissions
Collapse over time
The key question:
“Does this system reward the behavior it actually needs?”
