Analytics
Polymarket
Algorithmic vs HumanFeesUser LTV AnalysisTop TradersDiversification AnalysisMost Traded QuestionsTaker Speedbump Analysis
Methodology: Algorithmic vs Human Classification
Hypothesis: Humans need to sleep, so their trades cluster during waking hours. Algorithms trade 24/7, so they have a flat hourly distribution.
Method: We analyze the coefficient of variation (CV) of hourly trade counts for each user:
- Low CV (< 0.5) = flat distribution = algorithmic
- High CV (> 1.5) = concentrated distribution = human
- We also consider the number of active hours (algorithms trade in more hours) and total trade count
Classification: Users are classified as algorithmic, likely_algorithmic,likely_human, or human based on their hourly trading patterns.
Key Finding:
While algorithmic and likely algorithmic traders represent only 29.3% of all users, they account for 84.9% of total trading volume, demonstrating their outsized impact on platform activity.
Trading Volume (7-Day Average)
Capitola LabsDaily Active Users (7-Day Average)
Capitola LabsVolume per User
Capitola LabsTrader Type Statistics
| Trader Type | Number of Users | Avg Lifetime Volume | Median Lifetime Volume | Avg Lifetime Trades | Median Lifetime Trades | % Active | % Active (7d) | Avg Trading Duration (days) |
|---|---|---|---|---|---|---|---|---|
| Algorithmic | 32,322 | $4,711,420 | $139,698 | 85,591 | 17,422 | 79.0% | 53.2% | 133 days |
| Likely Algorithmic | 536,419 | $204,249 | $33,659 | 2,238 | 1,123 | 71.3% | 35.6% | 161 days |
| Likely Human | 217,058 | $83,395 | $22,598 | 715 | 629 | 60.1% | 26.6% | 193 days |
| Human | 1,156,933 | $24,723 | $9,150 | 152 | 345 | 53.2% | 23.4% | 59 days |