# Bitget Leaderboard Position Tracker With Trading Signals (`brilliant_gum/bitget-scraper`) Actor
Scrape Bitget copy trading leaderboard, track live open positions of top traders, and generate LONG/SHORT trading signals using Three-Signal Analysis — notional, trader count, and volume-weighted consensus.
- **URL**: https://apify.com/brilliant\_gum/bitget-scraper.md
- **Developed by:** [Yuliia Kulakova](https://apify.com/brilliant_gum) (community)
- **Categories:** Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $45.00 / 1,000 trader scrapeds
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## Bitget Copy Trading Scraper
See exactly where Bitget's top copy traders are putting their money — in real time. Track up to **2,184 traders**, scrape their open positions, and get actionable **LONG/SHORT signals** generated by a three-layer analysis engine that separates winners from losers.
Built for crypto traders, quant analysts, and anyone who wants to know what the smart money is doing before the market moves.
---
### What You Get
- **Full leaderboard** — up to 2,184 copy traders ranked by ROI, with PnL, AUM, win rate, and follower count
- **Live open positions** — every trader's current futures positions: coin, direction, leverage, margin, entry price
- **Trading signals** — which coins top traders are loading up on vs. where the losers are sitting
- **Market sentiment** — overall BULLISH / BEARISH / NEUTRAL bias from winners' positioning
---
### Modes
| Mode | What it does |
|------|-------------|
| `leaderboard` | Scrape rankings + full stats for all traders (fast) |
| `positions` | Fetch live positions for specific traders by ID |
| `full` | Leaderboard + open positions for every trader |
| `analytics` | Everything above + Winners vs Losers signal analysis |
---
### How the Signals Work
The analytics engine runs **three independent signal methods** per coin and combines them into a consensus:
- **Notional signal** — raw USD exposure: where are winners putting the most capital?
- **Trader signal** — democratic vote: each trader counts once, regardless of position size
- **Volume signal** — sqrt-weighted to dampen single-whale distortion
**Consensus** = 2 out of 3 signals agree on direction.
**Confidence**: `HIGH` (all 3 agree) · `MEDIUM` (2/3) · `LOW` (split)
> When all leaderboard traders are profitable (common on Bitget), the scraper automatically switches to **winners-only mode** — signals reflect where top performers are positioned with the highest conviction.
---
### Input
| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `mode` | string | `leaderboard` | Scraping mode |
| `maxTraders` | integer | `50` | Traders to analyze (up to 2,184) |
| `traderIds` | array | — | Hex IDs for `positions` mode |
| `fetchPositions` | boolean | `true` | Include open positions |
| `winnersPercent` | integer | `25` | Top N% classified as Winners |
| `losersPercent` | integer | `25` | Bottom N% classified as Losers |
| `proxyConfiguration` | object | — | Custom proxy (leave empty — built-in proxy included) |
---
### Output
**Trader record** (`_type: "trader"`):
```json
{
"traderUid": "bcb44a7286b73953ac96",
"displayName": "LiquidityMatrix",
"pnl": 15265.32,
"roi": 7507.24,
"aum": 60342.59,
"winRate": 93.93,
"followCount": 137,
"positions": [
{
"symbol": "ETH",
"side": "LONG",
"leverage": 40,
"margin": 5099.07,
"notionalValue": 203962.88,
"avgPrice": 2286.45
}
]
}
````
**Analytics record** (`_type: "analytics"`):
```json
{
"marketBias": "STRONGLY_BULLISH",
"tradersAnalyzed": 100,
"winnersCount": 25,
"losersCount": 25,
"topSignals": [
{
"symbol": "BTC",
"signal": "STRONG_LONG",
"confidence": "HIGH",
"volumeBattleScore": 100
}
]
}
```
***
### Pricing
**$45 per 1,000 traders** scraped.
💡 More traders = stronger signals. For analytics mode, we recommend at least 100 traders — the more data, the less noise.
***
### Good to Know
- Bitget positions are always **public** — no login needed
- Handles up to **2,184 traders** (73 pages × 30) in a single run
- Auto-stops at **55 minutes** and runs analytics on collected data — safe within Apify's 1-hour limit
- Rate: ~2 seconds per trader
# Actor input Schema
## `mode` (type: `string`):
leaderboard — Scrape the leaderboard rankings only (fast).
positions — Fetch positions for specific traders by ID.
full — Leaderboard + positions for all traders.
analytics — Full + Winners/Losers analysis and trading signals.
## `maxTraders` (type: `integer`):
Maximum number of traders to scrape. Bitget API calls are fast (~2s per trader).
The leaderboard exposes up to 2,184 traders (73 pages × 30).
💡 More traders = more accurate signals. Larger samples reduce noise and improve signal reliability — we recommend at least 100 traders for analytics mode. With 2,184 available and ~2s per trader, you can analyze the full leaderboard in under 1 hour.
⚠️ Apify's free tier has a 1-hour timeout. For full/analytics modes the safe limit is ~1,500 traders. The actor auto-stops at 55 minutes and runs analytics on collected data.
## `traderIds` (type: `array`):
Bitget copy trader hex IDs (from the trader page URL: https://www.bitget.com/copy-trading/futures-trader-v1/{traderId}). Required for positions mode.
## `fetchPositions` (type: `boolean`):
Retrieve each trader's current open positions (via the same API that powers the 'Active elite trades' button). Positions are always public on Bitget.
## `winnersPercent` (type: `integer`):
Top N% of traders by PnL classified as Winners for signal generation.
## `losersPercent` (type: `integer`):
Bottom N% of traders by PnL classified as Losers.
## `proxyConfiguration` (type: `object`):
Advanced: custom proxy settings. Leave empty to use the built-in proxy (recommended).
## Actor input object example
```json
{
"mode": "leaderboard",
"maxTraders": 50,
"traderIds": [
"b0b64d7587b73053a496"
],
"fetchPositions": true,
"winnersPercent": 25,
"losersPercent": 25
}
```
# Actor output Schema
## `traderUid` (type: `string`):
Unique Bitget copy trader hex identifier.
## `displayName` (type: `string`):
Trader's display name on Bitget.
## `pnl` (type: `string`):
Total profit and loss in USDT over 30 days.
## `roi` (type: `string`):
Return on investment percentage over 30 days.
## `winRate` (type: `string`):
Percentage of winning trades. Available for elite traders only.
## `aum` (type: `string`):
Assets under management in USDT. Available for elite traders only.
## `followCount` (type: `string`):
Number of copy traders following this trader.
## `positions` (type: `string`):
Array of current open futures positions: symbol, side (LONG/SHORT), leverage, margin, notionalValue, avgPrice.
## `positionCount` (type: `string`):
Number of currently open positions.
## `marketBias` (type: `string`):
Overall market sentiment from winners' positioning: STRONGLY\_BULLISH, BULLISH, NEUTRAL, BEARISH, STRONGLY\_BEARISH. Analytics mode only.
## `topSignals` (type: `string`):
Array of trading signals per coin: symbol, signal (STRONG\_LONG/LONG/NEUTRAL/SHORT/STRONG\_SHORT), confidence (HIGH/MEDIUM/LOW), volumeBattleScore. Analytics mode only.
## `tradersAnalyzed` (type: `string`):
Total number of traders used to generate signals. Analytics mode only.
## `_type` (type: `string`):
"trader" for individual trader records, "analytics" for the signal summary record.
## `_scrapedAt` (type: `string`):
ISO 8601 timestamp when this record was collected.
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"traderIds": [
"b0b64d7587b73053a496"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("brilliant_gum/bitget-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "traderIds": ["b0b64d7587b73053a496"] }
# Run the Actor and wait for it to finish
run = client.actor("brilliant_gum/bitget-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"traderIds": [
"b0b64d7587b73053a496"
]
}' |
apify call brilliant_gum/bitget-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=brilliant_gum/bitget-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Bitget Leaderboard Position Tracker With Trading Signals",
"description": "Scrape Bitget copy trading leaderboard, track live open positions of top traders, and generate LONG/SHORT trading signals using Three-Signal Analysis — notional, trader count, and volume-weighted consensus.",
"version": "0.0",
"x-build-id": "Eeuon7Qlxm6nF30hl"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/brilliant_gum~bitget-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-brilliant_gum-bitget-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/brilliant_gum~bitget-scraper/runs": {
"post": {
"operationId": "runs-sync-brilliant_gum-bitget-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/brilliant_gum~bitget-scraper/run-sync": {
"post": {
"operationId": "run-sync-brilliant_gum-bitget-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"mode": {
"title": "🎯 Mode",
"enum": [
"leaderboard",
"positions",
"full",
"analytics"
],
"type": "string",
"description": "leaderboard — Scrape the leaderboard rankings only (fast).
positions — Fetch positions for specific traders by ID.
full — Leaderboard + positions for all traders.
analytics — Full + Winners/Losers analysis and trading signals.",
"default": "leaderboard"
},
"maxTraders": {
"title": "👥 Max traders",
"minimum": 1,
"maximum": 2200,
"type": "integer",
"description": "Maximum number of traders to scrape. Bitget API calls are fast (~2s per trader).
The leaderboard exposes up to 2,184 traders (73 pages × 30).
💡 More traders = more accurate signals. Larger samples reduce noise and improve signal reliability — we recommend at least 100 traders for analytics mode. With 2,184 available and ~2s per trader, you can analyze the full leaderboard in under 1 hour.
⚠️ Apify's free tier has a 1-hour timeout. For full/analytics modes the safe limit is ~1,500 traders. The actor auto-stops at 55 minutes and runs analytics on collected data.",
"default": 50
},
"traderIds": {
"title": "🆔 Trader IDs",
"type": "array",
"description": "Bitget copy trader hex IDs (from the trader page URL: https://www.bitget.com/copy-trading/futures-trader-v1/{traderId}). Required for positions mode.",
"items": {
"type": "string"
}
},
"fetchPositions": {
"title": "📊 Fetch open positions",
"type": "boolean",
"description": "Retrieve each trader's current open positions (via the same API that powers the 'Active elite trades' button). Positions are always public on Bitget.",
"default": true
},
"winnersPercent": {
"title": "🏆 Winners threshold (%)",
"minimum": 5,
"maximum": 50,
"type": "integer",
"description": "Top N% of traders by PnL classified as Winners for signal generation.",
"default": 25
},
"losersPercent": {
"title": "📉 Losers threshold (%)",
"minimum": 5,
"maximum": 50,
"type": "integer",
"description": "Bottom N% of traders by PnL classified as Losers.",
"default": 25
},
"proxyConfiguration": {
"title": "🔒 Proxy configuration",
"type": "object",
"description": "Advanced: custom proxy settings. Leave empty to use the built-in proxy (recommended)."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```