This article uses on-chain liquidity position data in Uniswap V3 to explain liquidity provider (LP) behavior. Using data extracted from the NonfungiblePositionManager contract, we analyze mint and burn events to characterize how LPs allocate and adjust capital across price ranges, fee tiers, and time. By modeling how liquidity providers historically adjust positions around market prices and volatility, this methodology aims to provide a framework for using position data as potential indicators of market dynamics. The proposed method can be applied both to historical datasets and real-time data streams to monitor liquidity position ranges, and the players in the AMM space.