Virtual population analysis (VPA) is one of the most powerful techniques available to estimate the abundance of fish stock and study the dynamics of harvested fish populations. As a rule of thumb, VPA is commonly applied in fisheries stock assessment on the assumption of fishing mortality is constant throughout the year. However, the reality of fishery is complicated, and few fisheries will conform to the assumption. A cohort can be classified different fishing stage in terms of instantaneous rate of fishing mortality, e.g. fishing season and non-fishing season. And more importantly, many countries have initiated fishing moratorium measure to protect and restore the fishery resources within the context of the worldwide fisheries collapse. Therefore, we improved and extended the conventional VPA by incorporating the effect of fishing staging, or staging VPA to meet the challenge of fisheries characteristics with fishing season, non-fishing season or fishing moratorium in this paper. Based on the differences fishing mortality during the stage at one year, we analyzed and discussed the performances of four scenarios on the results of assessments using simulated fisheries data. The simulation study suggests that conventional VPA model will leads to 6%–33% biases due to ignoring or incorrect stages in fisheries stocks assessment. We have proved that the staging VPA overcame the shortage of conventional method which based on cohort and the results from this model is more close to the reality owing to it can be used to estimate not only continuous fishing fisheries but discrete fisheries also. This work highlights a need for a more careful treatment of the times of start and end of a fishing season in fish population models. The natural mortality rate and fishing mortality are two important parameters in staging VPA application. Some of the problems of data collection and parameters estimation that will be encountered while implementing staging VPA method are also discussed. In general, considering the staging VPA is appropriate for the reality of the fisheries, we concluded that this method is more reliable for fish stock assessments compared with the conventional VPA.