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GMGN CopyTrade Wallet Scraper

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GMGN CopyTrade Wallet Scraper

GMGN CopyTrade Wallet Scraper

GMGN CopyTrade Wallet Scraper extracts profitable crypto wallet data from GMGN.ai across Ethereum, BSC, Base, Solana, and Tron. Track successful traders, analyze winning crypto strategies, and access key metrics like transactions, profits, and risk to boost your crypto investments.

Pricing

Pay per event

Rating

5.0

(3)

Developer

Muhammet Akkurt

Muhammet Akkurt

Maintained by Community

Actor stats

7

Bookmarked

222

Total users

21

Monthly active users

3 days ago

Last modified

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GMGN CopyTrade Wallet Scraper

GMGN CopyTrade Wallet Scraper

GMGN CopyTrade Wallet Scraper is a powerful web scraping tool developed for the Apify platform. This tool automatically extracts, analyzes, and allows you to monitor successful crypto wallets on the GMGN.ai platform. Working across different blockchain networks (Ethereum, BSC, Base, Solana, and Tron), it collects comprehensive information such as transaction counts, profitability, win rates, and performance indicators.

Why Should You Use GMGN CopyTrade Wallet Scraper?

GMGN CopyTrade Wallet Scraper saves you hours by automating manual data collection processes and provides access to the most up-to-date wallet statistics. This tool offers you the following advantages:

  • Time Saving: Saves hours by automating manual data collection processes
  • Comprehensive Data: Complete statistical data set including transaction counts, profitability ratios, and risk metrics
  • Multi-Blockchain Support: Works on Ethereum, BSC, Base, Solana, and Tron networks
  • Customizable Data Collection: Ability to collect successful wallet data with various filters

Features

  • Extracts comprehensive statistical data from successful crypto traders' wallets on GMGN.ai
  • Can extract wallet data with various filters (PnL, profitability, transaction count, etc.)
  • Can retrieve wallet statistics according to different time periods (1 day, 7 days, 30 days)
  • Stores collected data in Apify data repository and allows export in various formats (JSON, CSV, Excel)
  • Offers faster and more reliable results with proxy support
  • Ability to customize sorting criteria (PnL, profitability, transaction count, win rate, activity, SOL balance, tracked count, and remarked count)

Use Cases

  • Successful Trader Tracking: Analyzing successful traders in the crypto market
  • Wallet Strategy Analysis: Examining trading strategies of profitable wallets
  • Risk Assessment: Risk assessment of wallet profiles and investment strategies
  • Market Research: Researching the performance of crypto assets across different blockchains
  • Data Science Projects: Creating comprehensive statistical datasets for crypto markets

Usage

  1. Run this actor in the Apify console.
  2. Provide the necessary inputs:
    • chain: Blockchain network to scan (eth, bsc, base, sol, tron, monad).
    • traderType: Trader category. Available options: All, Pump SM, Launchpad SM, Smart Money, KOL/VC, Fresh Wallet, Sniper, Top Tracked, Top Renamed, Top Dev, LIVE.
    • sortBy: Sorting criterion. Options include 1D PnL, 7D PnL, 30D PnL, 1D/7D/30D Win Rate, 1D/7D/30D TXs, 1D/7D/30D Volume, 1D/7D/30D Net Inflow, Last Time, Balance, Tracked, Renamed.
    • sortDirection: Sorting direction (desc, asc).
    • Advanced Filtering Options (1D, 7D, 30D): Min and max values for PnL (%), Profit (USD), Win Rate (%), Transaction Count, Volume (USD), and Net Inflow (USD).
    • Average Cost Filter: Min and max values for Average Cost (USD) overall.
    • proxyConfiguration: Proxy configuration.

Example Input

{
"chain": "sol",
"traderType": "smart_degen",
"sortBy": "profit_7days",
"sortDirection": "desc",
"min_pnl_7d": 50,
"min_profit_7d": 5000,
"min_winrate_7d": 40,
"min_txs_7d": 10,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": []
}
}

Output

The collected data is saved to the Apify dataset. The output data includes the following fields:

  • wallet_address: Wallet Address
  • address: Address
  • last_active: Last Active Time
  • realized_profit_1d: 1 Day Realized Profit
  • realized_profit_7d: 7 Day Realized Profit
  • realized_profit_30d: 30 Day Realized Profit
  • buy: Buy Count
  • buy_1d: 1 Day Buy Count
  • buy_7d: 7 Day Buy Count
  • buy_30d: 30 Day Buy Count
  • sell: Sell Count
  • sell_1d: 1 Day Sell Count
  • sell_7d: 7 Day Sell Count
  • sell_30d: 30 Day Sell Count
  • pnl_1d: 1 Day PnL (%)
  • pnl_7d: 7 Day PnL (%)
  • pnl_30d: 30 Day PnL (%)
  • txs: Total Transaction Count
  • txs_1d: 1 Day Transaction Count
  • txs_7d: 7 Day Transaction Count
  • txs_30d: 30 Day Transaction Count
  • balance: Balance
  • eth_balance: ETH Balance
  • sol_balance: SOL Balance
  • trx_balance: TRX Balance
  • monad_balance: Monad Balance
  • follow_count: Tracked Count
  • remark_count: Remarked Count
  • twitter_username: Twitter Username
  • avatar: Avatar
  • nickname: Nickname
  • tags: Tags
  • twitter_name: Twitter Name
  • twitter_description: Twitter Description
  • name: Name
  • winrate_1d: 1 Day Win Rate
  • winrate_7d: 7 Day Win Rate
  • winrate_30d: 30 Day Win Rate
  • avg_cost_1d: 1 Day Average Cost
  • avg_cost_7d: 7 Day Average Cost
  • avg_cost_30d: 30 Day Average Cost
  • pnl_lt_minus_dot5_num_7d: 7 Day PnL Below -0.5 Count
  • pnl_minus_dot5_0x_num_7d: 7 Day PnL Between -0.5 and 0x Count
  • pnl_lt_2x_num_7d: 7 Day PnL Below 2x Count
  • pnl_2x_5x_num_7d: 7 Day PnL Between 2x-5x Count
  • pnl_gt_5x_num_7d: 7 Day PnL Above 5x Count
  • daily_profit_7d: 7 Day Daily Profit
  • twitch_channel_name: Twitch Channel Name
  • avg_holding_period_1d: 1 Day Average Holding Period
  • avg_holding_period_7d: 7 Day Average Holding Period
  • avg_holding_period_30d: 30 Day Average Holding Period
  • volume_1d: 1 Day Volume
  • volume_7d: 7 Day Volume
  • volume_30d: 30 Day Volume
  • net_inflow_1d: 1 Day Net Inflow
  • net_inflow_7d: 7 Day Net Inflow
  • net_inflow_30d: 30 Day Net Inflow

Example Output

{
"wallet_address": "BAr5csYtpWoNpwhUjixX7ZPHXkUciFZzjBp9uNxZXJPh",
"address": "BAr5csYtpWoNpwhUjixX7ZPHXkUciFZzjBp9uNxZXJPh",
"last_active": 1772863129,
"realized_profit_1d": "-121.28441716936650516184",
"realized_profit_7d": "4909.52803841827237709189",
"realized_profit_30d": "88531.11566588015980262115",
"buy": 682,
"buy_1d": 87,
"buy_7d": 682,
"buy_30d": 4348,
"sell": 184,
"sell_1d": 18,
"sell_7d": 184,
"sell_30d": 1777,
"pnl_1d": "-0.0233919003393499",
"pnl_7d": "0.1100850083282489",
"pnl_30d": "0.2716767642135354",
"txs": 866,
"txs_1d": 105,
"txs_7d": 866,
"txs_30d": 6125,
"balance": "505.223537101",
"eth_balance": "505.223537101",
"sol_balance": "505.223537101",
"trx_balance": "505.223537101",
"monad_balance": "505.223537101",
"follow_count": 9572,
"remark_count": 8202,
"twitter_username": "jackduval",
"avatar": "https://gmgn.ai/defi/images/twitter/3f1b19128409b5e67623c8c884b22ab2.jpg",
"nickname": "",
"tags": [
"axiom",
"top_followed",
"top_renamed",
"wash_trader"
],
"twitter_name": "Jack Duval🌊",
"twitter_description": "Join the Wave.",
"name": "Jack Duval🌊",
"winrate_1d": 0.6111111111111112,
"winrate_7d": 0.651685393258427,
"winrate_30d": 0.6774193548387096,
"avg_cost_1d": "58.8964209664157471",
"avg_cost_7d": "62.5771390771699413",
"avg_cost_30d": "69.208276404089724",
"pnl_lt_minus_dot5_num_7d": 6,
"pnl_minus_dot5_0x_num_7d": 56,
"pnl_lt_2x_num_7d": 126,
"pnl_2x_5x_num_7d": 1,
"pnl_gt_5x_num_7d": 0,
"daily_profit_7d": [
{
"timestamp": 1772236800,
"profit": "-1143.83566675172"
},
{
"timestamp": 1772323200,
"profit": "-86.14215181185084996117"
},
{
"timestamp": 1772409600,
"profit": "184.68177453866977178881"
},
{
"timestamp": 1772496000,
"profit": "781.21015649463323454402"
},
{
"timestamp": 1772582400,
"profit": "1121.36173100064572238445"
},
{
"timestamp": 1772668800,
"profit": "2348.66250200948597566273"
},
{
"timestamp": 1772755200,
"profit": "220.14035893167502783489"
}
],
"twitch_channel_name": "jackduvaltrades",
"avg_holding_period_1d": 42532,
"avg_holding_period_7d": 43603.90476190476,
"avg_holding_period_30d": 44068.41862489121,
"volume_1d": "9638.68108072607",
"volume_7d": "87114.30080467576",
"volume_30d": "644639.10640698919",
"net_inflow_1d": "454.23049741519",
"net_inflow_7d": "2322.79083484107",
"net_inflow_30d": "13054.68793335347"
}

This example output shows statistical data for a single wallet. The actual output will be a list of similar objects for all processed wallets.

Notes

  • The collected data is stored in Apify's default data store.