Prediction of football players performance using machine learning and deep learning algorithms

Title

Prediction of football players performance using machine learning and deep learning algorithms

Creator

Manish. S.; Bhagat V.; Pramila R.M.

Description

In modern days the margin of error for football game is low, therefore the ultimate aim of the game is to win the match. The performance of the players in the match affects the results of the game. Due to this it is very important to evaluate the player and know his weakness. Manual evaluation tends to generate many errors and take more time. In the current research the statistical model is proposed to predict the stats of the football player based on previous session data by considering various aspects of the game. Through literature reviews it is observed that machine learning and deep learning algorithms can be used predict the performance of football player. But which model would be more efficient considering the positions of the player is not considered in any article. The proposed model has designed separate model as per the position of the player during the game. This can help to predict the player's performance as per their playing position. The current study has successfully implemented various machine learning and deep learning models and provide comparative analysis of the same. Each position has considered different variables associated with that position. The performance of these models is compared for further clarification 2021 IEEE.

Source

2021 2nd International Conference for Emerging Technology, INCET 2021

Date

2021-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Deep Learning Algorithm; Machine Learning algorithm Linear Regression; Neural networks; Performance Prediction

Coverage

Manish. S., CHRIST(Deemed to Be University), Department of Data Science, Lavasa, Pune, India; Bhagat V., CHRIST(Deemed to Be University), Department of Data Science, Lavasa, Pune, India; Pramila R.M., CHRIST(Deemed to Be University), Department of Data Science, Lavasa, Pune, India

Rights

Restricted Access

Relation

ISBN: 978-172817029-9

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/INCET51464.2021.9456424

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113334181&doi=10.1109%2fINCET51464.2021.9456424&partnerID=40&md5=08439906702208501ed7eeae3af94f5b