Skip to main content

​
Overview

Fetch and analyze on-chain wallet activity to compute cost basis, current position value, and distinguish between active traders and infrastructure/escrow wallets.

​
Prerequisites

  • polymarket CLI installed
  • A wallet address (Ethereum address starting with 0x)
  • The condition_id for the market you want to analyze

​
Workflow

1

Fetch wallet trades

Retrieve the wallet’s trade history:
polymarket -o json data trades <WALLET_ADDRESS> --limit 500
This returns an array of trade objects:
[
  {
    "id": "...",
    "condition_id": "0x...",
    "side": "BUY",
    "size": "100",
    "price": "0.64",
    "timestamp": 1709856000
  }
]
Each trade includes:
  • condition_id: The market’s condition ID
  • side: "BUY" or "SELL"
  • size: Number of shares (decimal string)
  • price: Price per share (decimal string, 0-1 range)
  • timestamp: Unix timestamp (seconds)
Use --limit 500 to get sufficient history. Large traders may need multiple paginated requests.
2

Filter to target market

Filter trades by condition_id to isolate activity for your market of interest:
target_condition = "0x0f49db97f71c68b1e42a6d16e3de93d85dbf7d4148e3f018eb79e88554be9f75"
market_trades = [t for t in trades if t["condition_id"] == target_condition]
3

Separate BUY and SELL trades

Split trades by side:
buys = [t for t in market_trades if t["side"] == "BUY"]
sells = [t for t in market_trades if t["side"] == "SELL"]
For cost-basis analysis, you’ll primarily use BUY trades.
4

Compute cost basis metrics

Calculate the wallet’s position:
# Total cost (in dollars)
total_cost = sum(float(t["size"]) * float(t["price"]) for t in buys)

# Total shares purchased
total_shares = sum(float(t["size"]) for t in buys)

# Average entry price
avg_price = total_cost / total_shares if total_shares > 0 else 0

# Current position (if no sells yet)
shares_held = total_shares - sum(float(t["size"]) for t in sells)
This assumes all shares are still held. For partial exits, subtract SELL volumes from total_shares.
5

Calculate current value and ROI

Fetch the current market price and compute position value:
polymarket -o json markets get <market-slug>
Extract the current price (e.g., 0.28 for 28%), then:
current_price = 0.28  # From market data
current_value = shares_held * current_price

# Win payout if outcome resolves YES
win_payout = shares_held * 1.00

# Profit/loss scenarios
unrealized_pnl = current_value - total_cost
win_pnl = win_payout - total_cost
roi_if_win = (win_pnl / total_cost) * 100 if total_cost > 0 else 0

​
Wallet Profiling: Infrastructure vs. Trader

Not all large wallets are traders. Polymarket uses infrastructure wallets for escrow, collateral management, and neg-risk CTF splits. Here’s how to identify them:

​
Infrastructure Wallet Signals

polymarket -o json data trades <WALLET> --limit 500
Returns [] (empty array). Infrastructure wallets obtain tokens via CTF minting, not trading.
When checking holders:
polymarket -o json data holders <CONDITION_ID>
Infrastructure wallets show "avg_price": "0" because tokens were minted (split from collateral), not purchased.
In a binary YES/NO market, infrastructure wallets hold exactly equal amounts of both outcomes:
{
  "wallet": "0xa5Ef39C3D3e10d0B270233af41CaC69796B12966",
  "yes_shares": "11900000000",
  "no_shares": "11900000000"
}
This is characteristic of CTF collateral splits (1 USDC → 1 YES + 1 NO).
If the wallet has activity, it’s purely yield-farming or liquidity provision, not directional bets.
polymarket data value <WALLET>
Returns billions of dollars (e.g., $11.9B). This is Polymarket’s own infrastructure, not a whale trader.

​
Example: Polymarket Neg-Risk Escrow

polymarket -o json data trades 0xa5Ef39C3D3e10d0B270233af41CaC69796B12966 --limit 500
# Returns: []

polymarket data value 0xa5Ef39C3D3e10d0B270233af41CaC69796B12966
# Returns: ~$11.9B
This wallet is Polymarket’s neg-risk escrow contract, not a bettor.

​
Tips

Large holder ≠ big trader. Always check trade history before assuming a wallet is taking a directional bet. Infrastructure wallets can appear at the top of holder lists.
Use --limit 1000 or paginate if analyzing very active wallets. The default limit may truncate history.
To find the biggest active traders (not infrastructure), filter holders by:
  1. avg_price > 0 (they bought, not minted)
  2. Non-zero trade history
  3. Asymmetric YES vs NO holdings

​
Caveats

Trade history is public on-chain data. You’re analyzing public addresses, which may include smart contracts, aggregators, or privacy-preserving protocols.
Partial exits are not automatically tracked. If the wallet sold some shares, you must manually subtract SELL volumes from the position.
Market makers and LPs may have high trade volumes but no directional bias. Check if BUY and SELL volumes are roughly balanced.

​
Example: Full Wallet Analysis

# 1. Fetch trades
polymarket -o json data trades 0x1234567890abcdef1234567890abcdef12345678 --limit 500 > trades.json

# 2. Filter to a specific market in your code (Python, Node.js, etc.)
# target_condition = "0x0f49db97..."

# 3. Compute cost basis
# total_cost = sum(size × price for BUY trades)
# avg_price = total_cost / total_shares

# 4. Get current price
polymarket -o json markets get gavin-newsom-2028

# 5. Calculate unrealized P&L and win payout
# current_value = shares_held × current_price
# win_payout = shares_held × 1.00
# roi_if_win = (win_payout - total_cost) / total_cost × 100
You now have a complete picture of the wallet’s position: entry price, current value, and profit scenarios.

Build docs developers (and LLMs) love

Get started for freeTalk to us