In order to investigate contributing factors to wrong-way crashes on freeways based on information available in crash databases and reports, Haddon matrices, statistic tests, and simulation techniques were used to analyze fatal and injury crashes caused by wrong-way driving from 2004-2009 in Illinois. As a first step, a Haddon matrix was developed for each wrong-way crash in which different factors were identified for before, during, and after the crash. These factors include drivers’ age, drivers’ condition, crash causes, vehicle type, vehicle maneuvers, roadway conditions, weather, and wrong-way entry points. Next, ANOVA and Tukey tests were conducted and a ranking and grouping of the factors was obtained. Furthermore, due to a limitation of ANOVA testing caused by data non-normality, a simulation technique called the bootstrapping was employed. A ranking was then made based on the frequency of each factor as well as the chance of a factor being the leading contributing factor. The analysis results indicated that being alcohol impaired, darkness, and driver’s age are the top contributing factors to wrong-way crashes.