Objective: To determine the degree to which skiing-related concussion can be identified from predictive models of neuropsychological testing data or in combination with single-lead electroencephalographic (EEG) data. Method: Adults who suffered traumatic brain injury (TBI; n = 26) while skiing were compared to n = 45 non-injured age matched comparator subjects in a cross-sectional study design under Aspire-IRB supervision. Each participant was tested using a novel single-lead EEG device during an eyes closed (EC) and eyes closed (EO) state. Further testing was performed during a neuropsychological saccade card test. Cognitive metrics (e.g., error-free card recital time) and EEG spectral and wavelet features were extracted from EC/EO baseline and neuropsychological test epochs. Univariate and multivariate logistic regression, linear discriminant analysis and random forest models were compared for the ability to predict a concussive event. Results: Independently, EEG spectral power in the beta band (12–30Hz), relative to overall power, had an overall predictive accuracy of 65% (p < 0.004). Additionally, total card read time alone was 62% accurate (p < 0.015). Combined, these two features were found to be 70% accurate (p < 0.006). However, including age and gender as co-variates with card read time and relative-beta EEG power were 76% accurate at differentiating concussed from control subjects (p < 0.003). Conclusion(s): Neuropsychological testing benefits by the addition of other testing modalities in the predictive performance of concussion/TBI testing. These results are preliminary and need to be independently replicated for validation and expanded to other clinical settings such as team sports and emergency department use.