The goal of this project is to build a moble-based simple TBI repository system that consists of top down classification of players where leaf nodes represent individual players and the parent nodes represent the relationship (Club/ Team/ Sport) that binds the child nodes together. The repository keeps track of different players TBI history as well as capable of delivering a particular player’s instant information through critical condition determination from the instant accelerometer data. If we could get some training data, we can create algorithms to detect TBI just by processing data. This can be achieved by recognizing patterns in the data that guarantee that player went into TBI after impact. We can index these individual player profiles and perform a run- time query processing – (often done in aircraft engine failure detection) to detect in real-time if player can suffer from TBI or can suffer from partial effects of TBI. Continuous plotting of this real-time data can give a good visualization of impact points. Another way of classification is that we can group players where each group consists players corresponding to the type of prominent effect due to TBI, eg. a group where all of the players suffered long term depression after TBI, another group where players went straight to coma after TBI. This will help in visualization of common impacts of TBI. Secondly, visualization can be based on job categories.,eg soldiers in warzones, workers in construction zones or truck drivers can also be prone to TBI due to hazardous nature of their jobs.