In a city like Turin (less than 1 million inhabitants) more than 57% of Public Transport (PT) users are systematic clients; in other words, they take the same bus line twice a day every single workday. These persons know their PT lines and their itinerary much better than Public Transport Companies (or our algorithms) will ever do. In this paper a change of paradigm is proposed: instead of supplying people with complex forecast and aggregated data, we investigate the way to allow them accessing real-time, low level data in a practical and user friendly way. This will enable skilled passengers to put in practice their very personal experience in understanding the status of their PT line and, in short, make their on “forecasts”.