Can Artificial Intelligence Modelling Approaches Assist Football Clubs In Identifying Transfer Targets, While Maintaining A Fair Transfer Market Using Player Performance Data?
Cardiff Metropolitan University
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Artificial Intelligence is a new phenomenon that is being embraced in all areas of the real-world. This study will investigate and evaluate Artificial Intelligence methods, techniques, models and integrations, which will enable us to draw conclusions and make decisions on how to construct a model that will be developed in the future. This proposed model will hopefully assist football clubs in identifying potential transfer targets, while maintaining a fair transfer market. To carry out this investigation, we will explore books, journals, academic sources and relevant websites to review past literature and examine methodological approaches in modelling an Artificial Intelligent System. First, we identify the aims and objectives of this study. Then we look at past literature that consisted mainly of Artificial Intelligence approaches, techniques and modelling. Then we carry out experiments based on the system methodologies to seek improvements that may justify which technique to peruse for our future model. We will then critically evaluate the findings of this research and detail how we would implement the model, which assists in solving the problems. To conclude, we will outline how we have met our objectives of this project and how we can further develop the model and expand it to solve more problems in the footballing world. As a result of this study, we were able to conclude the technique/algorithm we would use to develop our model would be a Case-Based Reasoning Expert System as this would help solve all the problems. The k- Nearest neighbour algorithm helped find the most similar case (identifying a player) while also recommending what the value of the player would be. Artificial Neural Network algorithm could not be applied, because there were not enough similar instances (players) to identify a set of patterns or trends in the inputs.
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