Occasion-Associated Potential (ERP) is among the mind sign options that are utilized in Electroencephalography (EEG) based mostly analysis and software improvement, comparable to Mind-Pc Interface (BCI) functions. Just lately, single-trial ERP has been one of many most important pursuits of researchers within the area of BCI and neuroscience. On this paper, an offline research which evaluated the feasibility of growing an internet BCI guessing sport, based mostly on single-trial ERP, was introduced. The target was to find out the optimum strategies and parameters wanted to attain excessive on-line classification accuracy and efficiency. Eight topics participated in our experiments to gather the information for the offline research. Every topic had to decide on one out of six playing cards displayed on a pc monitor. Three totally different algorithms of Linear Discriminant Evaluation (LDA) have been used for classifying the playing cards into targets and non-targets. Canonical Correlation Evaluation (CCA) was utilized as a spatial filter for the 16-channel knowledge. Moreover, the information have been analysed and categorised per channel to infer which channel reached the upper efficiency. The outcomes proved the feasibility of the net software. The very best efficiency was achieved with the personalised knowledge and by taking the bulk vote of the three LDA algorithms.