Pool-based electricity markets can be simulated with various degrees of accuracy. When compared to actual markets, most of the simulators produce outcomes than cannot be extrapolated beyond the specific scenario analyzed. This is most critical for regulators and market participants which need tools to analyze market power and bidding strategies, respectively, for a broad range of scenarios. Both objectives can be tackled if the possible equilibria of a pool-based multiperiod market are determined. This paper presents a three-step methodology to find these equilibria. First, a detailed model of an electricity market is presented, considering multiperiod bidding, price elasticity, and network modeling. Second, an iterative simulation process is run to detect participants' bidding strategies implicit in the optimized production resulting from the simulation. Finally, output data from the simulator are analyzed to obtain Nash equilibria. Iterated deletion is used in the last step to remove strategies that are dominated by others that generate higher profits. A realistic case study illustrates the proposed technique.