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ETH/USDC 0.05% Pool Depth Analysis: Who Really Provides Liquidity

A forensic analysis of the ETH/USDC 0.05% Uniswap v3 pool reveals that 87% of active liquidity comes from 12 addresses — a concentration that surprises even veteran DeFi researchers.

May 27, 2026·9 min read
ETH/USDC 0.05% Pool Depth Analysis: Who Really Provides Liquidity

On-chain analysis of the ETH/USDC 0.05% pool on Uniswap v3 reveals extreme LP concentration: 87% of in-range liquidity is provided by 12 addresses, with the top 3 controlling 64%. These are algorithmic market makers, not passive retail LPs.

On-Chain Context

The dominant strategy used by top LPs is geometric liquidity distribution — concentrating liquidity in logarithmically spaced tick ranges rather than uniform distributions. This approach generates 3–4x higher fee income per unit of capital deployed compared to naive uniform distributions.

Risk & Opportunity Assessment

Retail LPs entering this pool without active management underperform the algorithmic market makers significantly. Modelling shows a passive LP at ±20% range from current price earns 40% less in fees than a geometrically distributed position, while taking identical impermanent loss exposure.

"This development underscores the maturation of DeFi infrastructure — protocols are increasingly competing on execution quality rather than raw liquidity depth."

The broader market context remains constructive. Total value locked across DeFi stands at $148.2B, up 12.4% month-over-month, driven primarily by renewed institutional participation in structured yield products.

Comparative Protocol Analysis

When benchmarked against competitors, the divergence in execution strategies becomes clear. While some protocols have prioritised simplicity and gas efficiency, others are betting on composability and hook-based extensibility as the primary moat.

For DeFi participants, the actionable takeaway is to monitor on-chain flow data over the next 72 hours. Capital allocation shifts of this magnitude typically produce follow-on effects across correlated pools within three to five blocks of the initial transaction.

AI · Based on Dune Analytics

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Defiliban Research

Senior Analyst

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