Provides students with a basic understanding of how data is used
in decision making in a variety of sports contexts. Topics
include data management, data visualization, and the use of data
analysis within decision making in sports.
Athena Title
Intro to Sports Analytics
Equivalent Courses
Not open to students with credit in KINS 4250E
Prerequisite
KINS 3430 or KINS 3430E
Semester Course Offered
Offered fall and spring
Grading System
A - F (Traditional)
Student learning Outcomes
Following the completion of this course, students will be able to use data in decision-making.
Following the completion of this course, students will be able to create and manage large data sets.
Following the completion of this course, students will be able to use data visualization techniques in order to understand the properties of data.
Following the completion of this course, students will be able to understand basic statistical concepts and how they are applied to settings in the sports industry.
Following the completion of this course, students will be able to effectively use statistical methods to analyze data.
Following the completion of this course, students will be able to determine the appropriate statistical methods to use in order to measure performance and analyze decision making.
Topical Outline
Introductory Topics
-Introduction to 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
-Linear regression to model relationships in sports data
-Binary and limited dependent variable models in sports
-Non-linear models in sports data
Performance Analysis Content Areas
-Baseball analytics
-Football analytics
-Basketball analytics
