We integrate a probabilistic demand model in the train timetabling problem. We use a logit model that we calibrate to reflect the known demand elasticities. We further include a competing operator as an opt-out option for the passengers. Subsequently, we integrate the train timetabling problem with a ticket pricing problem. We solve the elastic passenger centric train timetabling problem for various types of timetables using a simulated annealing heuristic on a case study of Israeli Railways. The results of our case study show that the generated revenues can be increased by up to 15% when taking into account the passengers behavior along with a specific pricing scheme. This study further confirms the advantages of hybrid cyclicity.