An Image processing Player Acquisition and Tracking System for E-sports

Studying one’s enemy has been the key to winning a war for centuries. This can be seen in the success of the historical success of the Chinese, Greek, and Mongolian empires. Over the years, these dogmas of studying one’s enemy before the battle have now made its way into our modern lives as well, not only in real battle but also on the electronic battlefield. In E-Sports, teams will often study one another to find the strengths and weaknesses that can be exploited and avoided in the next encounters. The manner in which this is done is through the observing of prior matches to determine patterns in the manner in which they operate, play and react. This process is extremely time-consuming as one match is a minimum of an hour in duration. This paper demonstrates a program able to acquire and track player positions throughout a match in order to simplify and automate this process. This tracking data can be used with machine learning and or neural networks as part of a professional E-Sport prediction model.