This paper presents acceleration data of seventy-eight open-wheel, Indy car type, racecar impacts. These data were collected by the “Impact Sensor Program” conducted jointly by the Ford Motor Company and the Championship Auto Racing Teams (CART), Inc. The seventy-eight impacts consisted of forty-two side impacts, thirty rear impacts, three frontal impacts, and three rollover/flipping of cars. Related crash data were used as input to a CAE model of a racecar driver in a typical CART car to perform computer simulations of the impacts. This model was developed using MADYMO software, and was an enhanced version of one previously published. Enhancements to the model included accurate geometrical representations of the cockpit interior, the seat, and the energy-absorbing collar; a more realistic geometry of the driver’s head and an improved representation of the neck; a highly detailed model of the driver’s helmet; and improved contact algorithms to define the head-helmet, helmet-collar, and head-chin strap interactions. Additionally, data collected from twenty-six drivers were used to improve the seating posture of the driver in the model. Results of simulations performed established the validity of the model in predicting the potential injury risk to the drivers in the head and neck areas. Model predictions of injuries based on the “Head Injury Criterion” (HIC), the Injury Assessment Reference Values (IARVs) of upper neck forces and moments, and a biomechanical neck injury predictor compared well with the actual injuries sustained by the drivers. The model predictions of reversible concussions also compared well with results of recent brain injury risk studies. The present study shows that CAE modeling can be effectively used to predict potential injuries to racecar drivers involved in high “G” impacts, and that the model can be used to evaluate countermeasures to improve safety of CART cars.