This study investigates harvesters’ effort in terms of days at using dynamic discrete choice model. Fishing effort as a form of time has been analyzed with trip level data, in which only averaged daily catch is available. On the other hand, daily level data enables us to have the variation of daily catch within a trip. Such variation provides more information than averaged daily catch in two ways. Firstly, it can capture how the harvesters update the expectation of future catch. Secondly, it also captures the daily change in the state variables such as total weight and freshness of caught fish. This study incorporates these factors in a dynamic discrete choice model of a fishing trip. We suggest freshness as a critical factor in determining fishing trip duration. Using daily logbook data from a Japanese-based longline fishery, we find the effect of freshness on trip length. The result shows that the catch older than 15 days significantly decreases the probability of a trip continuation. Our use of daily data resolves the endogeneity present in this related work and identifies the tradeoff between freshness and increased catch, capturing the intra-trip variation that drives the marginal decision to remain at sea or return to port.