The @zerufinance noted that percentage-return leaderboards tend to rank small accounts higher, with top-ranked traders often holding roughly one-fifth the typical balance of other active wallets. The team’s size-aware approach attempts to credit strong returns while still reflecting absolute dollar outcomes, so that very small accounts do not dominate solely through high percentage figures. This adjustment sits alongside earlier findings on airdrop dumps and sybil patterns, where low-engagement or extractive wallets were more likely to exit quickly. Together the observations point to a recurring measurement challenge: raw volume, raw returns, and raw transaction counts each capture different slices of behavior and can be gamed or skewed by account size. Incorporating multiple dimensions (temporal depth, quality filters, size normalization) increases computational and design complexity but reduces reliance on any single easily manipulated statistic. Protocols adopting similar multi-factor screens will still need to validate thresholds against their own historical recipient outcomes, as the relative importance of size versus engagement can vary by asset and market structure.