Many fish species form social aggregations or shoals. Understanding the conditions under which these groups sometimes coordinate their behavior in space and time, or "school," is important for understanding their ecology, their effects on the ecosystem, and effective management of their stocks. An automated approach to isolate acoustic aggregations in echosounder data relative to the local background scattering is introduced. Aggregations were then identified and characterized in a large dataset acquired from an autonomous platform and a research vessel. Fish schools were statistically distinct from other aggregations of fish, with differences in their geometry, frequency response, scattering intensity, and scattering distribution. The statistical distribution of acoustic scattering from fish shoals generally followed a Rayleigh distribution as predicted for a randomly organized aggregation of homogenous scatterers. Within fish schools, however, the distribution was distinct from Rayleigh, showing a consistent pattern with most values at low relative scattering levels followed by a sharp roll-off and long right tail. These differences in distribution provide the ability to remotely observe the polarized, organized behavior that defines schooling, a difficult to observe response to environmental and internal conditions, which has large implications for our understanding and management of schooling fish.