Passenger punctuality is one of the most important measures to indicate and improve the service reliability of public transport operators. Previously, passenger punctuality measurements were mainly based on passenger counts in combination with vehicle locations. With the growing use of Automatic Fare Collection systems, passenger punctuality made a step forward in accuracy where it comes to normal situations. During disruptions, however, passenger journeys may be hindered, causing different journey patterns that are not captured in the normal data. This research introduces, therefore, a reconstruction method to analyze the impact of disruptions on passenger punctuality that is not captured in the currently available methods. This method has been applied to several cases in the Dutch rail network. It appears that passenger punctuality is structurally overestimated by the current methods.