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Overview

This example demonstrates how to discover and research Polymarket markets using search and filtering. You’ll learn how to:
  • Search for markets by keyword
  • Sort results by trading volume
  • Analyze market metadata and liquidity
  • Understand market types (binary vs multi-outcome)

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Searching Markets

Search for markets related to “election”: 
polymarket markets search "election" --limit 20

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Sorting by Volume

To find the most active markets, sort by trading volume: 
polymarket markets search "election" --order volumeNum --limit 20
The --order parameter uses camelCase, not snake_case:
  • ✅ --order volumeNum
  • ❌ --order volume_num (causes 422 error)

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Sample Output

[
  {
    "id": "0x1a2b3c...",
    "question": "Will Donald Trump win the 2024 Presidential Election?",
    "slug": "will-donald-trump-win-2024-presidential-election",
    "conditionId": "0x0f49db97f71c68b1e42a6d16e3de93d85dbf7d4148e3f018eb79e88554be9f75",
    "outcomePrices": "[\"0.62\",\"0.38\"]",
    "volume": "125678945.50",
    "liquidity": "2456789.30",
    "active": true,
    "closed": false,
    "marketType": "binary",
    "enableOrderBook": true
  },
  {
    "id": "0x2b3c4d...",
    "question": "Will Republicans win the Senate in 2024?",
    "slug": "republicans-win-senate-2024",
    "conditionId": "0x1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z7a8b9c0d1e2f",
    "outcomePrices": "[\"0.71\",\"0.29\"]",
    "volume": "45678912.20",
    "liquidity": "987654.50",
    "active": true,
    "closed": false,
    "marketType": "binary",
    "enableOrderBook": true
  }
]

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Analyzing the Results

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Key Fields

Market Identification:
  • question: The market’s prediction question
  • slug: URL-friendly identifier for direct lookups
  • conditionId: Required for holders, CLOB queries, and token IDs
Trading Activity:
  • volume: Total trading volume in USDC (higher = more liquid)
  • liquidity: Available liquidity for orders
  • outcomePrices: Current YES/NO prices (remember to parse this JSON string)
Market Status:
  • active: true if currently trading
  • closed: true if trading has ended
  • marketType: binary (YES/NO) or categorical (multi-outcome)

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Interpreting Prices

Prices represent the market’s probability estimate: 
import json

market = search_results[0]
prices = json.loads(market['outcomePrices'])
yes_price = float(prices[0])  # 0.62 = 62% probability
no_price = float(prices[1])   # 0.38 = 38% probability

print(f"Market implies {yes_price*100:.0f}% chance of YES")
# Output: Market implies 62% chance of YES
Prices may sum to slightly more than 1.00 (e.g., 1.01) due to the 1% house vig. This is normal.

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Filtering High-Volume Markets

Find the top markets by volume without a keyword: 
polymarket markets search "" --order volumeNum --limit 10
Use an empty search string "" to retrieve all markets sorted by your chosen criterion.

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Why Not markets list?

The markets list command always sorts ascending (lowest to highest), making it useless for finding top markets:
# ❌ Returns lowest-volume markets first
polymarket markets list --limit 20

# ✅ Use search with empty query instead
polymarket markets search "" --order volumeNum --limit 20

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Complete Research Workflow

Here’s a complete workflow for researching election markets:
Step 1: Search
polymarket -o json markets search "2024 election" --order volumeNum --limit 5 > markets.json
Step 2: Get detailed market data
# Pick a slug from the search results
polymarket -o json markets get will-donald-trump-win-2024-presidential-election > market_detail.json
Step 3: Check top holders
# Use the conditionId from market data
polymarket -o json data holders 0x0f49db97f71c68b1e42a6d16e3de93d85dbf7d4148e3f018eb79e88554be9f75 > holders.json
Step 4: Get open interest
polymarket data open-interest 0x0f49db97f71c68b1e42a6d16e3de93d85dbf7d4148e3f018eb79e88554be9f75

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Sample Analysis Script

Combine search with analysis in Python: 
import json
import subprocess

# Search for top markets
result = subprocess.run(
    ["polymarket", "-o", "json", "markets", "search", "",
     "--order", "volumeNum", "--limit", "10"],
    capture_output=True,
    text=True
)

markets = json.loads(result.stdout)

# Analyze each market
for market in markets:
    prices = json.loads(market['outcomePrices'])
    yes_price = float(prices[0])
    volume = float(market['volume'])
    
    print(f"\n{market['question']}")
    print(f"  YES: {yes_price*100:.1f}%")
    print(f"  Volume: ${volume:,.0f}")
    print(f"  Liquidity: ${float(market['liquidity']):,.0f}")

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Next Steps

After finding interesting markets:
  1. Track price history - Generate interactive charts (see Price Tracking)
  2. Analyze holders - Find out who’s betting on each outcome
  3. Monitor events - Look up multi-outcome events (see Event Lookup)

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