Behavioral classification, performance analysis, and trading style detection for Solana wallets

Wallet Profiling Behavioral classification, performance analysis, and trading style detection for Solana wallets. Profile any wallet to understand how it trades, how well it performs, and whether it is worth following. Why Wallet Profiling Matters Copy Trade Evaluation Before mirroring another wallet's trades, you need evidence that its historical performance is genuine, consistent, and not the result of a single lucky hit. Profiling quantifies win rate, profit factor, hold time, and consistency so you can make informed decisions about which wallets merit attention. Smart Money Identification Wallets that consistently buy tokens early and exit profitably are signal sources. Profiling separates genuinely skilled traders from lucky gamblers and wash trading bots. Key differentiators: sustained profit factor above 2.0, win rates above 45% across 100+ trades, and diversified token selection. Counterparty Analysis When a large wallet enters a position you hold, understanding its historical behavior (sniper vs. holder, bot vs. human) helps you anticipate what will happen next. A sniper wallet buying suggests a quick dump is coming; a swing trader buying suggests multi day conviction. Risk Assessment Token holder analysis benefits from knowing whether top holders are bots, snipers, or genuine investors. A token where 60% of holders are classified as snipers has very different risk characteristics than one held primarily by swing traders. Wallet Classification By Trading Style Classification is based on the median hold time across all closed trades: Style Median Hold Time Characteristics Sniper < 5 minutes First block buyers, MEV adjacent, extremely fast exits Scalper 5 min – 1 hour Quick momentum trades, high frequency Day Trader 1 – 24 hours Intraday positions, moderate frequency Swing Trader 1 – 7 days Multi day conviction holds Position Holder 7 days Long term accumulation, low frequency See references/classification methods.md for the full classification algorithm. By Trade Size Based on median trade size in SOL : Tier Median Trade Size Typical Behavior Whale 100 SOL Market moving entries, often front run Large 10 – 100 SOL Significant but not dominant Medium 1 – 10 SOL Active retail traders Small < 1 SOL Micro cap gamblers, new wallets By Behavior Type Type Detection Method Bot Low inter trade timing variance (CV < 0.3), uniform sizing Human Variable timing, variable sizing, session based activity MEV Sandwich patterns, consistent small profits, high frequency By Focus Area Focus Detection Criteria PumpFun Specialist 70% of trades on PumpFun launched tokens DEX Trader Primarily swaps on Raydium/Orca/Meteora DeFi Farmer Frequent LP add/remove, staking operations NFT Trader Significant NFT marketplace interactions Multi Strategy No single category exceeds 50% Performance Metrics Core Metrics Win Rate — Percentage of trades that are profitable. Minimum 30 trades for statistical significance. A 60% win rate across 200 trades is far more meaningful than 80% across 10 trades. Average ROI Per Trade — Mean return across all closed positions. Include all fees: platform fees, priority fees, and estimated slippage. Profit Factor — Ratio of gross profits to gross losses. Interpretation: 2.0 excellent, 1.5–2.0 good, 1.0–1.5 marginal, < 1.0 losing. Total PnL — Cumulative profit/loss in SOL. Maximum Drawdown — Largest peak to trough decline in cumulative PnL curve. Sharpe Like Ratio — Risk adjusted return metric. See references/performance metrics.md for detailed formulas, edge cases, and interpretation guidelines. Activity Metrics Metric Calculation What It Reveals Trades per day total trades / active days Activity level and capacity Average hold time mean(exit time entry time) Trading style confirmation Token diversity unique tokens / total trades Specialization vs. diversification Peak hours mode(hour of trade) Session patterns, timezone hints Activity streaks consecutive active days Dedication and consistency Data Sources SolanaTracker PnL API (Primary) The SolanaTracker API provides pre computed PnL data per wallet per token. Response includes per token: realized , unrealized , total invested , total sold , num buys , num sells , last trade time . Helius Parsed Transactions (Detailed) For granular transaction level analysis, use the helius api skill to fetch parsed transaction history. This provides exact timestamps, amounts, and program interactions. Birdeye Trader Data Birdeye's trader endpoints provide wallet level analytics. See the birdeye api skill for endpoint details. DexScreener (Free Fallback) DexScreener does not provide wallet level PnL but can be used to validate token prices at trade timestamps. Copy Trade Evaluation Framework Before following a wallet's trades, verify these criteria: Minimum Requirements Trade history : At least 50 closed trades (100+ preferred) Time span : Active for at least 30 days Consistent performance : Rolling 7 day win rate standard deviation < 15% Reasonable sizing : No single trade 20% of observed portfolio Diverse tokens : At least 10 unique tokens traded Green Flags Profit factor 1.8 sustained over 60+ days Win rate 45–65% (unrealistically high rates suggest wash trading) Moderate trade frequency (2–20 trades/day) Mixed hold times indicating adaptive strategy Gradual equity curve growth (not step function jumps) Red Flags New wallet (< 14 days old): Possible sybil or one hit wonder Single big win : One trade accounts for 50% of total PnL Declining performance : Last 30 day metrics significantly below all time Bot like patterns : Uniform timing/sizing without proportional edge Extreme win rate : 80% often indicates small wins with catastrophic losses Concentration : 50% of PnL from a single token Wash trading signals : Repeated buy/sell of same token with minimal price movement Risk Score Calculation Integration with Other Skills whale tracking : Identify large wallets, then profile them here for behavioral context token holder analysis : Profile top holders of a token to assess holder quality solana onchain : Fetch raw transaction data for deep dive analysis helius api : Parsed transaction history for granular trade reconstruction birdeye api : Token price data for PnL validation Quick Start Profile a Single Wallet Compare Multiple Wallets Files File Description references/classification methods.md Hold time, size, bot detection, and focus classification algorithms references/performance metrics.md Detailed metric formulas, interpretation, edge cases, and decay detection scripts/profile wallet.py Profile a single wallet: fetch data, compute metrics, classify, report scripts/compare wallets.py Compare multiple wallets side by side with ranking Dependencies Environment Variables Variable Required Description WALLET ADDRESS For profile wallet.py Solana wallet address to profile WALLET ADDRESSES For compare wallets.py Comma separated wallet addresses ST API KEY No SolanaTracker API key for PnL data

wallet-profiling