Pattern Recognition of On-Chain Behavior: Understanding the True Intentions of Players and Funds

Why Learn On-Chain Behavior Pattern Recognition?

In the crypto market, information always lags behind on-chain funds. The charts, prices, and news investors see are the “results” of player behavior, not the “causes.”

The essence of on-chain behavior pattern recognition is to understand market participants’ motives in advance and anticipate what might happen next.

Three Typical Scenarios

1. A certain address buys a new coin multiple times in small amounts over 3 consecutive days
   This is a typical pattern of smart money stealthily building a position. The market hasn’t noticed yet, but they are already positioning early, providing an early entry opportunity.

2. A team wallet activates a contract deployed 18 months ago, suddenly minting a large number of tokens and transferring them to a CEX
   This signals the team is preparing to sell or launch a “liquidity attack,” usually indicating a spike in short-term risk.

3. A Meme coin sees many small buy orders from new wallets, but all withdrawals come from the same parent address on a single CEX
   This is usually the project team creating fake FOMO (self-generated hype). It’s not worth FOMOing—avoid becoming the bagholder.

Key Insights from Behavior Pattern Recognition

After mastering behavior pattern recognition, investors can identify:

• Which funds are the smartest?
• Which trades are deliberately faked?
• Which team actions hide risks?
• Which coins have genuine hype vs. team wash trading?
• Whether the current market phase is “accumulation,” “distribution,” or “bagholder frenzy”?

All these judgments can be directly read from on-chain behavior.

Four Main Types of On-Chain Participants

Players in the on-chain world can be roughly divided into four types, each with very distinct behavioral traits:

1. Smart Money

Characteristics:

• Low trading frequency but precise
• Positions early and waits patiently
• Tests orders before entering
• Builds positions in batches once value is confirmed
• Sells large amounts at highs without greed for last profits

Visualization Features:

• Buy transactions show “ladder-style accumulation”
• Asset curves rise steadily
• Profitable records in every cycle

Common Examples:

• Wallets frequently tracked by Lookonchain
• Institutional test wallets
• Veteran OG wallets (minted many blue-chip tokens)

2. Fake Volume Makers

Characteristics:

• Frequent small trades
• Many “new wallets” funded by the same address
• Buy orders unusually uniform
• No whales, only scattered fake wallets

Visualization Features:

• Buy curve is “very neat”
• Wallets form obvious “chain structures”
• Activity concentrated on one chain and one token

Judgment Formula: High trade density + new wallets + same source = high probability of fake volume

3. Team Wallets

Characteristics:

• Initiate minting, issuance, burning, etc.
• Fixed timing (quarterly payroll, buybacks, etc.)
• Transfers to CEX usually signal short-term risk

Identification Methods:

• Token mint → Team wallet → CEX
• Multi-sig addresses controlled by contracts
• Publicly mentioned by the official team

Visualization Features:

• Huge holdings
• Intensive liquidity-related operations
• Rarely swap to other tokens

4. Retail Emotions

Characteristics:

• FOMO chasing
• Buy high, sell low
• High-frequency small trades
• Large number of wallets but small individual amounts

Visualization Features:

• Sudden surge of new wallets at price highs
• “Net buy amount” highly positively correlated with price changes
• Large volume of small buys at peaks (typical top)

These player behaviors form the most authentic “market sentiment” in on-chain data.

Five Key Dimensions for Analyzing Address Behavior

Whether analyzing whale wallets, team wallets, or stealth funds, all on-chain behaviors can be broken down into five dimensions:

1. Wallet Age

Older wallets:

• Less likely to be temporary fake accounts
• More likely OG/technical players
• Possibly lower cost basis, different selling pressure patterns

Newer wallets:

• May be fake volume
• May be new accounts quietly building positions
• Early behavior is more worth tracking

2. Fund Source

Main confirmations:

• Funds from CEX (retail or whales?)
• From other on-chain contracts (smart money?)
• From multi-sig (team?)
• Batch occurrences from same source address (fake volume?)

Visualization Tools:

• Arkham / Nansen “Source of Funds”
• Breadcrumbs fund flow charts

3. Behavior Rhythm

Observe:

• Batch buying?
• All-in at once?
• Fixed daily operation times?
• Test trades?

Rhythm reflects “strategy maturity.” Rhythmic → strategic; no rhythm → emotional trading

4. Transaction Structure

Key judgments:

• Presence of test orders?
• Gradual scaling up from small amounts?
• Buy amount changes synchronized with price?
• Concentration in certain projects?

Example: A wallet buys 10 new coins with $50 each, then increases 10x position on 3 that rise → likely a hunter smart money.

5. Exit Pattern

Exit method often more important than entry.

Three typical exit modes:

A. Sell out directly (emotional/small players)

• Usually at extreme spikes or crashes
• No concern for best price
• One or two full clear-outs

B. Batch distribution (experienced profit takers)

• Multiple large sells
• Sell more at higher prices
• Avoid crashing the market

C. Transfer to CEX first (hidden selling pressure/team behavior)

• No direct sell
• Transfer to CEX
• More professional, more dangerous

Visual investors will see: sudden outflow to CEX is one of the strongest risk signals.

Typical On-Chain Behavior Patterns

Below are the most common on-chain behavior patterns summarized by investors, with explanations on how to identify them using visualization tools (Nansen / Arkham / DeBank):

The core of on-chain behavior patterns is that every wallet movement represents the true intentions of different types of funds. Whale accumulation usually happens early; smart money front-running signals a trend is about to start; a surge in new wallets and transaction volume often indicates retail FOMO; rapid stablecoin outflows and high-frequency liquidations indicate the market entering a risk release phase. By recognizing these patterns, ordinary users can spot opportunities earlier and exit in time before risks arrive.