Leaderboard - PolyEdge

The leaderboard endpoint surfaces the highest-performing Polymarket traders for any rolling time window. Use it to discover “smart money,” build watchlists, or seed your own analytics pipeline. Endpoint: GET /v1/analytics/leaderboard

Filters

Combine filters to zero in on the traders that matter to your strategy.

Parameter	Type	Description
`time_frame`	string	Rolling window for stats: `1H`, `4H`, `1D`, `3D`, `7D`, `30D`. Default: `30D`.
`sort_by`	string	Rank by `pnl`, `roi`, `win_rate`, or `market_count`. Default: `pnl`.
`tag`	string	Market category: `all`, `sports`, `crypto`, `geopolitics`, `politics`, `finance`, `esports`, `pop-culture`, `tech`, `economy`, `weather`, `elections`, `tweets-markets`, `basketball`, `hockey`, `soccer`, `tennis`, `counter-strike-2`, `dota-2`, `league-of-legends`, `5M`, `15M`. Default: `all`. Note: The `sports` tag filters for traditional sports only and does not include `esports` data.
`min_win_rate` / `max_win_rate`	float	Win rate range (0–100).
`min_roi` / `max_roi`	float	ROI percentage range.
`last_active_hours`	int	Only include traders who placed an order in the last N hours.
`min_market_count` / `max_market_count`	int	Filter by number of markets traded in the window.
`min_pnl`	int	Minimum PnL filter in USDC.
`limit`	int	Results per page. Default: `50`, max: `100`.
`offset`	int	Pagination offset. Default: `0`.

On the Demo tier, limit is capped at 20 and offset must be 0. Upgrade your plan to paginate beyond the first page.

Code examples

import PolyEdgeClient from './polyedge.js';

const client = new PolyEdgeClient('YOUR_API_KEY');

const leaderboard = await client.getLeaderboard({
  time_frame: '7D',
  tag: 'crypto',
  sort_by: 'roi',
  min_win_rate: 55,
  min_market_count: 5,
  limit: 10,
});

for (const trader of leaderboard.traders) {
  console.log(`#${trader.rank} ${trader.profile.name}`);
  console.log(`  ROI: ${trader.roi}% | Win rate: ${trader.win_rate}% | Markets: ${trader.markets_count}`);
}

from polyedge import PolyEdgeClient

client = PolyEdgeClient('YOUR_API_KEY')

leaderboard = client.get_leaderboard({
    'time_frame': '7D',
    'tag': 'crypto',
    'sort_by': 'roi',
    'min_win_rate': 55,
    'min_market_count': 5,
    'limit': 10,
})

for trader in leaderboard['traders']:
    print(f"#{trader['rank']} {trader['profile']['name']}")
    print(f"  ROI: {trader['roi']}% | Win rate: {trader['win_rate']}% | Markets: {trader['markets_count']}")

curl -G "https://api.polyedge.dev/v1/analytics/leaderboard" \
  -H "X-PolyEdge-Key: YOUR_API_KEY" \
  --data-urlencode "time_frame=7D" \
  --data-urlencode "tag=crypto" \
  --data-urlencode "sort_by=roi" \
  --data-urlencode "min_win_rate=55" \
  --data-urlencode "min_market_count=5" \
  --data-urlencode "limit=10"

Response fields

Each object in the traders array contains:

Field	Type	Description
`rank`	int	Position on the leaderboard for the requested window.
`profile`	object	Trader metadata: `address`, `name`, `profile_image`, `x_username`, `profile_created_at`, `last_trade_at`.
`total_pnl`	string	Raw profit and loss in micro-USDC (divide by `1e6` for USDC).
`total_volume`	string	Total volume traded in micro-USDC.
`roi`	float	Return on investment as a percentage.
`win_rate`	float	Percentage of markets that resolved in the trader’s favour.
`markets_count`	int	Number of markets traded in the window.
`wins_count`	int	Number of markets won in the window.

Example response

{
  "traders": [
    {
      "profile": {
        "address": "0x96cfcb0c30942cfcd1cdf76c7d408794d66b1acb",
        "name": "mintblade",
        "profile_image": "",
        "x_username": "",
        "profile_created_at": "2026-06-02T14:47:45.193735Z",
        "last_trade_at": "2026-06-16T01:04:03Z"
      },
      "total_pnl": "9109604596452",
      "total_volume": "8522915083091",
      "roi": 106.88,
      "win_rate": 100,
      "rank": 1,
      "markets_count": 4,
      "wins_count": 4
    }
  ],
  "total_count": 229094
}

Combine min_win_rate, min_roi, and a short time_frame (e.g. 1D) to surface traders who are hot right now rather than those coasting on months-old gains. Then cross-reference with last_active_hours to confirm they are still active before you copy a position.