Are today's top Hyperliquid earners consistent over the week and the month?

Take the window=1d leaderboard, then read each wallet's 7d and 30d metrics from /wallets/{address}; a consistent earner is near the top in all three windows, with a sample that grows with the window.

GET /v1/hyperliquid/leaderboard with window=1d ranks wallets by the PnL they realized today and yesterday. For each wallet on it, GET /v1/hyperliquid/wallets/{address} with window=7d and window=30d returns the same metric set over the longer windows. Compare the PnL, the trade count and the win rate across the three. The full parameter lists are on Leaderboard and Wallet summary.

Quick answer

Start with today's board.

cURL

# today's top earners by realized PnL
curl -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hyperliquid/leaderboard?window=1d&limit=5"

Example response

Captured from the live API on 2026-10-24 at 17:15 UTC, trimmed to 3 of 5 rows.

total_realized_pnl is USD realized in the window and win_rate is a fraction. cum_realized_pnl is the wallet's realized PnL since its first recorded trade: the number two earner of the day is $2.08M down over its life, and its pnl_cohort is 3x rekt, the bottom 5%.

Example response

{
  "traders": [
    {
      "wallet": "0xfc667adba8d4837586078f4fdcdc29804337ca06",
      "rank": 1,
      "account_value": 48749226.598805,
      "total_realized_pnl": 3494570.337298,
      "cum_realized_pnl": 21973615.679594684,
      "roi": 7.168463134928304,
      "pnl_pct": 7.168463134928306,
      "total_volume": 349556527.5333299,
      "total_fee": 12459.380226,
      "trade_count": 16,
      "win_count": 15,
      "loss_count": 1,
      "win_rate": 0.9375,
      "long_win_rate": 0.8333333134651184,
      "short_win_rate": 1.0,
      "long_pnl": 189431.588825,
      "short_pnl": 3305138.7484730007,
      "profit_factor": 7481.79736328125,
      "expectancy": 218410.646081125,
      "max_drawdown_pct": 0.0,
      "current_drawdown_pct": 0.0,
      "calmar_ratio": 0.0,
      "recovery_factor": 999.0,
      "max_win_streak": 0,
      "max_loss_streak": 1,
      "avg_leverage": 0.0,
      "avg_duration_seconds": 375469,
      "size_cohort": "4x whale",
      "pnl_cohort": "3x smart",
      "pnl_cohort_tag": "sharp_shooter",
      "style_cohort_tag": "whale_hunter"
    },
    {
      "wallet": "0xfe7ce058edc7cfcde9ef8262ba51f8d4796ab7ae",
      "rank": 2,
      "account_value": 8309013.847202,
      "total_realized_pnl": 1082334.615797,
      "cum_realized_pnl": -2078079.9598528603,
      "roi": 13.0260297515507,
      "pnl_pct": 13.0260297515507,
      "total_volume": 23629507.009184003,
      "total_fee": 3920.516318,
      "trade_count": 4,
      "win_count": 3,
      "loss_count": 1,
      "win_rate": 0.75,
      "long_win_rate": 1.0,
      "short_win_rate": 0.6666666865348816,
      "long_pnl": 5.80267,
      "short_pnl": 1082328.8131270001,
      "profit_factor": 18.003759384155273,
      "expectancy": 270583.65394925,
      "max_drawdown_pct": 11.0,
      "current_drawdown_pct": 11.0,
      "calmar_ratio": 1.1841845512390137,
      "recovery_factor": 1.1841845512390137,
      "max_win_streak": 0,
      "max_loss_streak": 0,
      "avg_leverage": 0.0,
      "avg_duration_seconds": 162269,
      "size_cohort": "3x whale",
      "pnl_cohort": "3x rekt",
      "pnl_cohort_tag": "steady_winner",
      "style_cohort_tag": "whale_hunter"
    },
    {
      "wallet": "0xfdf891f2b214a4c9374d26595ec6d4080262e381",
      "rank": 3,
      "account_value": 1763391.727182,
      "total_realized_pnl": 907765.7735329999,
      "cum_realized_pnl": 1415662.3633014013,
      "roi": 51.47839584025162,
      "pnl_pct": 51.47839584025162,
      "total_volume": 4915356.459621,
      "total_fee": 2063.109551,
      "trade_count": 3,
      "win_count": 1,
      "loss_count": 2,
      "win_rate": 0.3333333432674408,
      "long_win_rate": 0.3333333432674408,
      "short_win_rate": 0.0,
      "long_pnl": 907765.7735329999,
      "short_pnl": 0.0,
      "profit_factor": 9.212410926818848,
      "expectancy": 302588.5911776666,
      "max_drawdown_pct": 15.899999618530273,
      "current_drawdown_pct": 15.899999618530273,
      "calmar_ratio": 3.2376348972320557,
      "recovery_factor": 3.2376348972320557,
      "max_win_streak": 0,
      "max_loss_streak": 0,
      "avg_leverage": 0.0,
      "avg_duration_seconds": 6359511,
      "size_cohort": "whale",
      "pnl_cohort": "3x smart",
      "pnl_cohort_tag": null,
      "style_cohort_tag": "whale_hunter"
    }
  ],
  "totalCount": 26028,
  "nextCursor": "eyJrIjoiMWR8cG5sfGRlc2N8c2l6ZXwiLCJyIjo1LCJ2Ijo4MzE1NDQuMDExOTcyOTk5OCwidyI6IjB4ZDRjMWY3ZThkODc2YzQ3NDkyMjhkNTE1NDczZDM2ZjkxOTU4M2QxZCJ9"
}

Variations

The same wallet over 30 days. Read the day's leader over the longer window.

cURL — 30 days

# the number one wallet's metrics over 30 days
curl -s -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hyperliquid/wallets/0xfc667adba8d4837586078f4fdcdc29804337ca06?window=30d" \
  | jq '{window, metrics_updated_at, metrics}'

Captured from the live API on 2026-10-24 at 17:16 UTC, trimmed to the metrics block.

{
  "window": "30d",
  "metrics_updated_at": "2026-10-24T17:05:07+00:00",
  "metrics": {
    "wallet": "0xfc667adba8d4837586078f4fdcdc29804337ca06",
    "account_value": 48749226.598805,
    "total_realized_pnl": 8456184.615246003,
    "roi": 17.346294916303947,
    "pnl_pct": 17.346294916303947,
    "total_volume": 8161684145.007959,
    "total_fee": 334682.779919,
    "trade_count": 426,
    "win_count": 229,
    "loss_count": 197,
    "win_rate": 0.5375586748123169,
    "long_win_rate": 0.5,
    "short_win_rate": 0.5747663378715515,
    "long_pnl": 469831.3245520013,
    "short_pnl": 7986353.290693999,
    "profit_factor": 2.202359914779663,
    "expectancy": 19850.198627338035,
    "max_drawdown_pct": 40.70000076293945,
    "current_drawdown_pct": 4.199999809265137,
    "calmar_ratio": 0.42619889974594116,
    "recovery_factor": 0.42619889974594116,
    "max_win_streak": 13,
    "max_loss_streak": 7,
    "avg_leverage": 0.0,
    "avg_duration_seconds": 428022,
    "pnl_cohort_tag": null,
    "style_cohort_tag": "streak_trader"
  }
}

The day's 94% win rate on 16 trades becomes 54% on 426 trades over 30 days, still $8.46M up, through a 40.7% drawdown.

The week in between. The same wallet over 7 days.

cURL — 7 days

# the same wallet over 7 days
curl -s -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hyperliquid/wallets/0xfc667adba8d4837586078f4fdcdc29804337ca06?window=7d" \
  | jq '.metrics | {total_realized_pnl, trade_count, win_rate, profit_factor, max_drawdown_pct}'

Whole boards to intersect. Pull the 30-day board, up to 500 rows a page, and look today's wallets up in it.

cURL — 30-day board

# the 30-day board, wallet, rank and PnL only
curl -s -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hyperliquid/leaderboard?window=30d&limit=500" \
  | jq '.traders | map({wallet, rank, total_realized_pnl, trade_count})'

Before you rely on it

1d covers today and yesterday

A window is the trades closed in the current UTC day plus the 1, 7 or 30 days before it, so 1d can hold up to 48 hours. Metrics are recomputed about once an hour (metrics_updated_at). max_win_streak and max_loss_streak count the trades opened in the window, which is why the day's leader shows a win streak of 0 beside 15 wins. avg_leverage is always 0 on these rows: do not read it.

Ask your agent

Connected to the Vike MCP server (https://vike.io/mcp) in Claude, ChatGPT or Cursor, ask it in plain words. The hl_leaderboard tool answers with view: ranking, one window per call, at 1 credit a call.

Ask your agent

Who are today's top Hyperliquid earners, and were they also up over the last 7 and 30 days?

Are today's top Hyperliquid earners consistent over the week and the month?

Quick answer

Example response

Variations

Before you rely on it

Ask your agent

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