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Profiles

The wallet profiles dataset provides a detailed view of how wallets behave on-chain over time, capturing the outcomes of trading activity with financial-grade precision. It measures how well a wallet is trading, how consistently, and across what tokens and timeframes. Each profile is tracked across a rich set of metrics that enable filtering, ranking, and evaluating wallets across various time windows.
All metrics are calculated based on the wallet’s trading activity, excluding transfers, deposits, or other non-trading events.
Supported time windows: 1d, 3d, 7d, 14d, 30d.

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Base

Fundamental identifiers and timestamps for each wallet record.
The unique public key of the wallet being analyzed.
The specific token address if the profile is filtered by a particular token.
The unix timestamp of the wallet’s most recent trade.

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Scores

Overall evaluations of a wallet’s quality. These combine multiple signals into high-level measures of skill, risk management, and consistency.
Represents the level of risk in the wallet’s trading behavior. This score is derived from volatility metrics.Example: 35%
A lower risk score suggests the wallet tends to avoid large swings or unpredictable trades. Higher scores indicate more aggressive or unstable strategies.
Indicates how reliably the wallet performs over time. This score is computed using stability metrics.Example: 82%
A high consistency score reflects steady and dependable performance, with less variability in returns and profit.

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Extremes

These metrics highlight the boundaries of performance and risk exposure.
The highest profit the wallet has made in a single position/trade.Example: $4,200
Reveals the best-case upside from a single position/trade — useful for assessing potential reward.
The biggest loss the wallet has taken in a single position/trade.Example: $1,850
Reveals the worst-case downside from a single position/trade — useful for understanding risk exposure.
The longest streak of consecutive winning position/trades.Example: 8
The wallet had a streak of 8 consecutive winning position/trades, showing strong momentum and consistency
The longest streak of consecutive losing position/trades.Example: 4
The wallet experienced a maximum of 4 consecutive losing position/trades, indicating manageable downside risk
Largest drop in performance during a time window. Example: -27.5% > At one point, the wallet was down 27.5% from its peak

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Averages

Reveals trading style and risk profile by smoothing short‑term variance.
Average size in USD of buy trades. Example: $430.50 > This wallet usually commits around $430 per buy, suggesting moderate-sized entries
Average size in USD of sell trades. Example: $500.00 > Sells tend to be slightly larger than buys, which could imply scaling into positions
Average market cap of tokens bought. Example: $1,200,000 > This wallet typically buys tokens with a market cap around $1.2M, indicating a preference for mid-sized projects
Average market cap of tokens sold. Example: $1,500,000 > Sells are made from tokens with a slightly larger market cap, suggesting a strategy of exiting larger positions
Average number of trades (buys + sells) per day. Example: 12 > A fairly active trader, engaging in about 12 trades per day
Average total daily trading volume in USD. Example: $18,000 > This wallet moves about $18K per day — could be a high-frequency or whale wallet
Average number of unique tokens traded per day. Example: 4 > The wallet diversifies across 4 different tokens daily
Average daily profit or loss, realized, in USD. Example: $320.00 > On average, this wallet is generating $320 in profit daily
Average return on investment per day, as a percentage. Example: 5.4% > The wallet gains an average 5.4% daily over its invested capital
Average time a wallet holds a position before exiting.Example: 300 seconds
This wallet typically holds positions for around 5 minutes before closing — likely a short-term trader.
Average time between consecutive trades.Example: 600 seconds
On average, the wallet waits about 10 minutes between trades — indicating a measured trading pace.
Average profit or loss per position/trade.Example: $200.00
On average, this wallet makes $200 per position/trade.
Average ROI per position/trade.Example: 2.5%
Each position/trade yields an average 2.5% return on the invested amount.
Average PnL per token.Example: $150.00
On average, this wallet makes $150 per token.
Average ROI per token.Example: 2.3%
Each token yields an average 2.3% return on the invested amount.

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Counts

Raw metric counts to reflect trading activity levels.
Total number of trades executed.Example: 163
The wallet executed 163 trades, indicating high activity.
Total number of buy trades executed.Example: 88
The wallet made 88 buy trades — a very active profile.
Total number of sell trades executed.Example: 75
The wallet sold 75 times — indicating a high turnover rate.
Total number of closed positions.Example: 88
The wallet has fully closed 88 positions, showing experience in completing trade cycles.
Number of profitable closed positions/trades.Example: 54
The wallet had 54 winning positions/trades, showing a strong success rate.
Number of losing closed positions/trades.Example: 34
The wallet had 34 losing positions/trades, indicating some risk in its strategy.

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Volumes

Measures of capital flow. Useful for gauging scale of participation.
Total trading volume in USD.Example: $22,500
The wallet traded a total of $22.5K in volume.
Total buy volume in USD.Example: $12,500
This wallet bought a total of $12,500 worth of assets.
Total sell volume in USD.Example: $10,000
The wallet sold a total of $10,000 worth of assets.
The frequency of trading activity, measured as the ratio of total volume to average capital deployed. Example: 2.5 > A turnover of 2.5 means the wallet trades 2.5x its average capital per period — indicating high trading frequency

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PnL

Direct profit and loss values. The core measure of profitability.
Total profit or loss.Example: $4,200
This wallet earned $4.2K in realized profit.
Total profit from winning positions/trades.Example: $3,500
This wallet made $3.5K in profit from winning positions/trades.
Total loss from losing positions/trades.Example: -$1,200
The wallet incurred $1.2K in losses from losing positions/trades.

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Ratios

Metrics expressed as relative proportions that describe the success rate and return rate.
Ratio of total profit to total volume traded. Example: 0.12 > For every $1 traded, the wallet makes $0.12 in profit — a solid performance
Percentage of tokens traded that were profitable. Example: 85% > 85% of the tokens this wallet trades have been profitable, indicating strong selection
Compares the average size of winning to losing positions/trades. Shows how much is gained when the wallet wins vs. how much is lost when it loses.Example: 1.8
The wallet gains $1.80 for every $1 lost — strong risk-reward per positions/trades.
Compares total gains to total losses over a time period. Reflects the overall profitability of the wallet’s strategy.Example: 2.4
For every $1 lost, the wallet made $2.40 — a solid profit profile.
The expected profit or loss per position/trade based on historical performance.Example: $60.50
On average, each position/trade is expected to generate $60.50 in profit based on historical win/loss patterns
Measures how well the wallet recovers from drawdowns.Example: 3.0
The wallet has recovered 3 times its largest drawdown, indicating resilience.

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Efficiency

Metrics showing how effectively resources are deployed to explain how much “output” is achieved for the amount of trading effort or risk taken.
Win rate based on the number of winning positions/trades over total - each counts equally.Example: 66.7%
Roughly 2 out of every 3 positions/trades are profitable
Win rate where each position/trade is weighted by its size — bigger ones influence the result more. Example: 74.1% > Most of this wallet’s large positions/trades are profitable, even if small ones aren’t
ROI averaged equally across all positions/trades. Example: 3.2% > Each position/trade yielded about 3.2% return on average
ROI averaged based on the size of each position/trade - larger ones have more influence. Example: 4.5% > The wallet’s larger positions/trades yield a 4.5% return on average, indicating strong performance on bigger positions
ROI normalized by the duration of positions/trades — accounts for how long capital was locked. Example: 4.1% > ROI adjusted for time confirms strong short-term gains

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Stability & Volatility

Measures of consistency vs variability in returns and profits.
% consistency of the wallet’s win rate across trades.
Higher values = steadier win rate.Example: 70%
The wallet maintains a reliable win rate.
% fluctuation of the wallet’s win rate relative to its average.
Higher values = bigger streaks and reversals.Example: 40%
The wallet’s win rate fluctuates more, suggesting more volatility.
% consistency of returns across trades.
Higher values = ROI clustered close to average.Example: 70%
ROI is predictable and steady.
% fluctuation of ROI relative to mean ROI.
Higher values = sharper profit/loss swings.Example: 40%
The wallet’s ROI fluctuates sharply, suggesting speculation.
% consistency of profit/loss outcomes over time.
Higher values = smooth equity curve.Example: 85%
The wallet generates steady profits.
% fluctuation of profit/loss relative to average PnL.
Higher values = more variance and risk.Example: $30
PnL outcomes swing moderately around the mean.

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Risk-Adjusted Returns

This ratios adjust profitability for risk and downside volatility, showing whether returns are strong relative to risk taken.
Measures return adjusted for total volatility — higher is better. Example: 1.6 > A Sharpe ratio above 1.0 indicates strong performance relative to risk
Like Sharpe, but only considers downside risk (losses), not all volatility. Example: 2.0 > A high Sortino ratio means strong returns with low downside — ideal for consistent performers
The probability of losing a significant portion of capital based on current trading patterns and risk management. Example: 8.5% > There’s an 8.5% chance of experiencing significant capital loss given the wallet’s current risk profile and trading behavior

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Distributions

Breaks down outcomes into buckets. Useful for spotting biases like frequent small wins vs rare large losses.
Breakdown of the wallet’s traded tokens grouped by ROI buckets.Each bucket shows the number of unique tokens whose ROI falls within that range.
Example
{
    "gt500": 1,
    "200_500": 3,
    "0_200": 6,
    "neg50_0": 2,
    "lt_neg50": 0
}
This wallet traded 1 token with ROI >500%, 3 tokens with ROI between 200% and 500%, etc.