Traditionally subject matter experts’ opinion has been the only way for a tennis player to analyse his/her performance. However, advancements and ease of access to complex algorithms have enhanced the usage of Artificial Intelligence and computer vision computing technologies in tennis. In this paper we focus on computer vision and image processing techniques used to analyse player performance in tennis. While there are so many possible methods for such a study it is quite essential for such studies to consider features at a player level such as expertise, age and sex. There are also many hurdles and challenges in achieving such a study since the video feed is heavily dependent on camera, ambient conditions, angle of view, field of depth etc. Multivariate thought process and methods have been applied mostly analysing the player strategy and Spatio-temporal positions. While some studies attempt to use simple cameras, some other use complex camera systems. MPEG4 is a popular format of files used by many. Different approaches have tried using different algorithms - MDL-MDS combination, custom object detection, pose estimation etc. The approach of this article is to provide a detailed introduction to applications based on computer vision in analysing tennis matches with player as the primary focus.