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This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. It is common knowledge, that the term “Sports Analytics” is used more and more nowadays. Sports Analytics can have various applications, that could affect a variety of fields. These could be for example, the prediction of an athlete’s or a team’s performance, the estimation of an athlete’s talent and market value and the prediction of a possible injury. More and more teams and coaches are willing to embed such “tools” in their training sessions, in order to improve their tactics. This dissertation is divided in two major parts. The first one is a literature review of existing technologies on the subject. The second part focuses on the experiments that were conducted mainly with football data. In these experiments, by using suitable algorithms, a player’s position in the field could be predicted. By accumulating data from past years, we could have an estimation for a player’s goal scoring performance in the next season. Furthermore, in order to make it more specific, the number of a player’s shots can be predicted in each match, something that has a correlation with goal scoring possibility