The Ten Most Similar Players How to Use Statistics to Find the Best Soccer Players for Your Team

• Published in: Promoting Statistical Practice and Collaboration in Developing Countries pp. 363 - 370
• Main Author: Marques, Thiago Valentim
• Format: Book Chapter
• Language: English
• Published: CRC Press 2022
• Edition: 1
• Subjects: Exploratory Data Analysis; Undergraduate Statistics Programs; Shiny App; Exponential Ratio Type Estimator; Cristiano Ronaldo; Data Set; Vice Versa; HPD Interval; Pe; Data Science Practice; Mohamed Salah; Preferred Foot; Pennsylvania State University; Statistical Consulting Centers; Dataset; LISA; Data Science Skills; Dataset Variables; Shortest Euclidean Distance; Undergraduate Statistics Students; Kashiwa Reysol; Developing Web Applications; Big Data Modeling; Autoregressive Distributed Lag Model; HPD
• ISBN: 9781032195551; 9781032198507; 103219555X; 1032198508
• DOI: 10.1201/9781003261148-31

The market for electronic games, such as video and computer games, is continually expanding since they are products that increasingly rely on technological advances. Hierarchical clustering was used to identify the players most similar to a given player. Exploratory data analysis was performed to review the dataset variables and investigate possible correlations between them. The application consists of selecting a player to be compared (the default is Cristiano Ronaldo). The user can then select the filters: overall (between 0 and 100), height (between 155 and 203 cm), position, and preferred foot. The creation of the application was highly relevant in the teaching and learning process of Data Science, since the last unit of the discipline is a project serving to put the acquired knowledge into practice. In addition, an article on the largest television channel in the state was dedicated to the application.