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Recruitment of Suitable Football Player by using Machine Learning Techniques

Chavan, Anamika (2019) Recruitment of Suitable Football Player by using Machine Learning Techniques. Masters thesis, Dublin, National College of Ireland.

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Abstract

In football, player selection is the critical task which leads to a key of success. Coaches and managers form their team by selecting finnest players all around the globe. Each player has his own identity in the team. When the team gets formed and due to some circumstances player moves from one club to another then finding replacement of such a player is again a big task. Finding closest match for the replaced player is the big headache that coaches and manager face. The problem illustrated in this paper is to find closest match for the replaced player by using machine learning algorithm. The players will get classified based on their ratings. In this research six machine leaning algorithms namely SVM, LDA, Naive Bayes, Decision Tree, XGBoost, KNN, have been implemented. Research compares the performances of these machine learning algorithms by using evaluation metrics such as accuracy, precision etc. LDA and SVM performed the best with accuracy of 83.77% and 80.31%. Further, KNN function will give the closest match among the predicted players.
Keywords: Machine Learning, Prediction, Multi -classification, LDA, SVM, KNN

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software

G Geography. Anthropology. Recreation > GV Recreation Leisure > Sports > Soccer
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Dan English
Date Deposited: 17 Jun 2020 17:25
Last Modified: 17 Jun 2020 17:25
URI: http://norma.ncirl.ie/id/eprint/4307

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