The Illex illecebrosus fishery in the northwestern Atlantic Ocean is trawl-based. I. illecebrosus normally lives less than 1 year. One option for managing such a short-lived species is the use of catch and effort data obtained from fishing vessels during the fishing season to manage the fishery in real time. Verification of the accuracy of data reports is important. Conceivably, information contained in the data stream of vessel position and time provided by a remote data logger could be used to reconstruct the vessel’s activities to assess the reliability of industry reports. This study describes quantitatively the types of vessel operating activities that take place on a typical I. illecebrosus fishing trip and assesses the possibility of reconstructing these activities reliably from the simple data stream of vessel position and time. Seven activities were identified, six of which occurred commonly: steaming to and from port, searching, towing, set-up time between tows, steaming overnight and laying-to overnight. Processing the catch, as a discrete activity, occurred rarely. Each activity could be characterized in terms of its duration and distance traveled, the average vessel speed, and the tendency for vessel speed to change during the activity. Most activities were conducted in a linear manner. Accordingly, reasonable estimates of the distance and duration of these activities could be obtained simply from the knowledge of the starting and ending position and time. Analysis of search time and subsequent catch revealed that searching did not improve catch. More squid would have been caught had the vessels used this time for towing. Catch per unit effort (CPUE) can be calculated using duration or distance in the denominator. In this set of fishing trips, the two were equivalent. Catch bore a nonlinear relationship with CPUE. In particular, larger catches were associated with incrementally larger CPUEs. The uniqueness of each activity when described by its characteristic speed, duration and distance, and the consistency of these characteristics for each activity between vessels suggests that vessel behavior might be assessed remotely using a time series of position and time. Such a capability might be important in any real-time management plan where industry vessels necessarily must be depended upon for data on catch and CPUE.