In this research project, we have established a set of advanced statistics models that quantify the cause-effect relation between infrastructure failures and train delay. The major model we employed in this project is called the “Wiener process model”, and we are the first researching team to implement the Wiener-process model into traffic analysis area with large scale network data in Swedish railway. The data we based our research on includes a 1) train movement record database—TFÖR 2) infrastructure error reporting system—0FELIA 3) railway facility database—BIS. For TFÖR alone, there is a 27-million data record over 5 different rail classes (from rail class 1, major railway around big city areas to rail class 5 least loaded rail) and 3 different passenger train types (x2000, regional train and commuter train). By merging the database listed above, a specified wiener process model has been estimated for the primary delay caused by system errors and the secondary delay by interaction of trains. The model also quantifies the effects of characteristics of railway system over different rail classes and operation manners. In addition, the Wiener process model also enable further research to derive the fundamental relation between capacity, speed and density (inverse function of time gap) in railway context. Switzerland.