Medical personnel are one group for which simulations and VR training make the highest impact on the actual well-being of the population. Most important is that the simulation has real bases and all information gained in scenarios are usable in real life. TBI (traumatic brain injury) is a very serious medical condition requiring intense medical care. Survival likelihoods, which we estimate, are chillingly low. We investigate whether there is an interplay between various categorical variables (biological sex, mechanisms and locations of accident, trauma mechanism, alcohol intoxication, illicit drug consumption, as well as ocular, verbal, motoric and pupil responses, and survival or death). In the medical scenario of the emergency room into which TBI victims are delivered, physicians habitually convert degrees of injury or neurological impairment severity into cardinal numbers that are then used to compute an index. Because this method is statistically fallacious, we include Bayesian methods that prevent this fallacy. The sequence of analysis steps involves one-hot encoding, dimension reduction, kernel density estimation, clustering algorithms, followed by computing the off-diagonal entries in the confusion matrix, which are a significance measure. We generate heat maps of different clusters to identify how survival rates relate to the categorical variables that characterize the severity of—and mechanisms that caused—TBI. In the realm of serious gaming, the development of realistic and accurate TBI simulation logic necessitates the integration of actual patient data. We discuss the general implications, as well as warnings and cautions when creating simulations as serious games.