In the early 1990s, a group of people at Silicon Graphcs realized the need for more effective systems and functions to render 3d graphics onto computer displays. As a result, they created the OpenGL library. In this modern day, statistical data analysis is becoming more and more consequential in importance. As a result, we need systems that can help us visualize our data in three dimensional forms. How else do we get to know, for example, the effect of the number of tackles and distance covered in determining how many shots on target a football team concedes per match? How do we put into visual context the greatness of the 2015-16 Golden State Warriors’ volume shooting and efficiency with respect to other eras of great basketball teams, say, the 1990s Chicago Bulls? Enter the rgl package(that exists on the OpenGL platform), which enables its user to make 3D illustrations of the data being processed into information on monitors for data scientists using the R Programming Language.Rgl provides real time, interactive rendering of 3D graphics that provides additional insight into three-dimensional relationships. Our research question is to highlight the numerous capabilities of the rgl package, and to analyze the statistical ease which it brings.