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Trader analytics

Polymarket trader analytics

How each tracked wallet makes its money, from settled history: results, risk, execution patterns, and the markets behind them. A profile is a record of what settled. It does not predict the next trade or prove you can copy it.

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What a profile answers

Three questions before you follow a wallet

What does the history show?

Sharpe, Sortino, drawdown, and expectancy describe the stored sample. They do not prove durable skill.

Where do the results come from?

Pattern clustering, category splits, entry timing, and feature importance show where a wallet's record clusters, not what caused it.

What stops you copying it?

Position size, liquidity, latency, streaks, and drawdowns show where another wallet's execution is not available to you.

Inside the reportPer trader

What the report covers

One report per trader: results, risk, and the execution limits behind them, all from the wallet's stored history. None of it is proof of skill, intent, or a future result.

24 trader-analytics modules
40+ quant and behavioral metrics
Every tracked Polymarket wallet, graded on settled P&L
Comparison

What a tracked record shows past total P&L

A tracked Polymarket record adds risk, timing, category, and execution context. All of it comes from stored history, and none of it proves skill, cause, or that you can copy the trade.

Public trackers
Total P&L
Trade count
Win rate
Basic trade list
No Pro needed
0xinsider analytics
ML pattern clustering
Sharpe and Sortino ratios
Drawdown analysis
Pair-cost diagnostics
SHAP feature importance
Streak & momentum analysis
Position size impact
Hourly performance breakdown
Win rate heatmap
Entry timing distribution
Asset allocation
Anomaly detection
Composite scoring (0-100)
Trader classification
Profit distribution
Kelly fraction & VaR
Category performance splits
Comparative benchmarks
Rolling expectancy
Execution-comparison diagnostics
P&L source breakdown
P&L calendar
Risk profile overview

Up to 24 analytics modules across 3 sections when the tracked record supports them.

Analysis layers

Three layers of analysis on tracked Polymarket profiles

Each layer covers a different part of the record: results, behavior patterns, and risk.

Observed resultsPatterns in the stored trades
Pattern clustering
Machine learning groups stored trades into behavior clusters, each with its win rate, average profit, and position sizing.
Pair-cost diagnostics
Pair cost shows where the stored trades booked profit and where they booked loss. It does not establish an edge that holds.
Profit distribution
A histogram of per-trade P&L: fat tails, tight clusters, or wide variance. Missing source history changes the shape.
Streak analysis
Win and loss streak lengths, averages, and ratios across the stored period.
Position size impact
Results bucketed by position size. It does not name an optimal size, or one you can copy.
Strategy breakdownHow the activity is spread
Category allocation
Volume by market category: crypto, politics, sports, economics, and more. Shows where a wallet concentrates.
Entry timing
When a wallet enters after a market opens. Fast entries can mean automation, but timing does not prove intent.
Win rate heatmap
Win rate by hour on a 24-hour grid. It describes the record; it is not a schedule to trade on.
Pair cost distribution
Histogram of combined YES and NO purchase costs. Below $1.00 is profit, above $1.00 is loss.
Risk profileRisk and consistency across the record
Composite scorecard
0-100 score with an F-to-S letter grade. Realized (banked) profit is about 95% of it. Forecasting edge, track record, win rate, drawdown, and consistency break the tie between near-identical totals.
Rolling Sharpe ratio
Seven-day and 30-day rolling risk-adjusted performance, so you see how the record changed.
Drawdown analysis
Peak-to-trough depth and duration of every decline in the stored history.
SHAP feature importance
Ranks which features line up with modeled profit. A link is not a cause.
Anomaly detection
The most unusual trades by anomaly score. See when a wallet breaks its own pattern.
Profile snapshot

The top of every trader report

Grade, observed trading style, and risk profile first, so you can decide whether the rest of the report is worth reading.

Sample summary
Composite gradeS (92/100)
Trading styleTwo-sided positions
Sharpe (30d)2.41
Max drawdown-$4,200 (0.8%)
Kelly fraction0.34
Win rate89.2%
Why it matters

What sits behind the grade

A grade summarizes settled history. The report shows the sample it came from, the modeled reasons, and how stable the result is.

Why the same returns may be out of reach

Timing, category concentration, drawdown, and position size decide whether another wallet's returns are reachable from your own account.

What each module is for

Each module shows the sample, the risk beside it, and what to research next. None proves intent, skill, causality, or copyability.

Every metric

The scorecard behind each graded profile

Each metric appears once the wallet has enough history to measure it.

Sharpe ratio (7d/30d)
Sortino ratio
Max drawdown
Drawdown duration
Profit factor
Kelly fraction
Value-at-Risk (95%)
Value-at-Risk (99%)
Win rate (all/7d/30d)
Average daily P&L
Best day / worst day
Win-loss streak ratio
Composite grade (0-100)
Observed trading style
Data depth confidence
SHAP importance
Anomaly scores
Rolling expectancy
Copyability score
Category splits
P&L source breakdown
Comparative benchmarks
Next step

Read the whole record behind a trader

No Pro needed for the report: results, risk, timing, and where the source data stops. A module appears when the wallet's stored history supports it. Pro adds the live sync.

See Pro pricingRead API and MCP docs