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NotreDameX: Math in Sports

Come learn how you can use mathematics to get a deeper insight into both the sports you love and everyday life.

4 weeks
4–6 hours per week
Instructor-led on a course schedule
This course is archived
Future dates to be announced

About this course

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In this course you will learn to use some mathematical tools that can help predict and analyze sporting performances and outcomes. This course will help coaches, players, and enthusiasts to make educated decisions about strategy, training, and execution. We will discuss topics such as the myth of the Hot Hand and the curse of the Sports Illustrated cover; how understanding data can improve athletic performance; and how best to pick your Fantasy Football team. We will also see how elementary Calculus provides insight into the biomechanics of sports and how game theory can help improve an athlete’s strategy on the field.

In this course you will learn:

  1. How a basic understanding of probability and statistics can be used to analyze sports and other real life situations.
  2. How to model physical systems, such as a golf swing or a high jump, using basic equations of motion.
  3. How to best pick your Fantasy Football, March Madness, and World Cup winners by using ranking theory to help you determine athletic and team performance.

By the end of the course, you will have a better understanding of math, how math is used in the sports we love, and in our everyday lives.

At a glance

  • Institution: NotreDameX
  • Subject: Data Analysis & Statistics
  • Level: Introductory
  • Prerequisites:

    Participants will be expected to have a basic knowledge of high school math up to Algebra II, exposure to some probability, statistics, and geometry will be helpful, but is not required.

  • Language: English
  • Video Transcript: English
  • Associated skills: Game Theory, Basic Math, Biomechanics, Calculus, Probability And Statistics, Team Performance Management

What you'll learn

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  • Draw conclusions from mathematical analysis using inductive reasoning
  • Evaluate data using principles of probability
  • Assess risk and develop strategies that drive event outcomes
  • Model physical processes in order to predict (or change) outcomes

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