Course Description
Provides students with an understanding of how data and data analysis are used in decision-making in a variety of sports contexts. Topics include data collection, data organization and management, data visualization, and the use of regression-based techniques to analyze questions of interest.
Athena Title
Sport Data Analytics
Equivalent Courses
Not open to students with credit in KINS 7700E
Semester Course Offered
Offered fall and spring
Grading System
A - F (Traditional)
Course Objectives
Following the completion of this course, students will be able to: • applying data analysis to inform decisions making • demonstrate how data is used to inform decisions in professional and college sport • effectively manage, organize, maintain, and update a data set • perform basic statistical tests • utilize statistical software to analyze data • visualize data to better understand its properties • select the appropriate statistical tool given the research question • properly conduct regression analysis and a number of advanced extensions of regression analysis • communicate results from data analysis to stakeholders
Topical Outline
Introductory Topics -Introduction to data analysis and "sports analytics" -Relationship between data and decision-making -Applications in team performance (on-field) and firm performance (business and financial) -Introduction to understanding sports data -Organizing and managing large data sets Basics of Statistical Analysis -Describing and summarizing sports data -Data visualization -Understanding relationships in data -Probability in sports data -Using correlation to assess relationships in data -Understanding and developing performance metrics for players and teams -Understanding relationships between performance metrics and team outcomes Statistical Modeling Using Sports Data -Using linear regression to model relationships in sports data -Using binary and limited dependent variable models in sports -Using non-linear models in sports data
Syllabus
Public CV