University of Michigan

Prediction Models with Sports Data

This course is part of Sports Performance Analytics Specialization

Taught in English

Some content may not be translated

Youngho Park
Stefan Szymanski

Instructors: Youngho Park

4,921 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.6

(29 reviews)

Intermediate level

Recommended experience

33 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Learn how to generate forecasts of game results in professional sports using Python.

Details to know

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Assessments

5 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.6

(29 reviews)

Intermediate level

Recommended experience

33 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Sports Performance Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 5 modules in this course

This module introduces the regression models in dealing with the categorical outcome variables in sport contest (i.e., Win, Draw, Lose). It explains the Linear Probability Model (LPM) in terms of its theoretical foundations, computational applications, and empirical limitations. Then the module introduces and demonstrates the Logistic Regression as a better substitute of LPM for the categorical dependent variables.

What's included

8 videos8 readings2 quizzes6 ungraded labs

This module explores the relationship between probability and betting markets. It explains the concept of odds, and the relationship between betting odds and probabilities. It then develops a measure of the accuracy of betting odds using sports examples, and assesses the meaning of efficiency in betting markets.

What's included

6 videos3 readings1 quiz5 ungraded labs

This module shows how to forecast the outcome of EPL soccer games using an ordered logit model and publicly available information. It assesses the accuracy of these forecasts against the betting odds and shows that they are remarkably accurate.

What's included

7 videos3 readings1 quiz6 ungraded labs

This module assesses the efficacy of the EPL forecasting model covered in the previous week by replicating the model in the context of three North American team sports leagues (i.e., NHL, NBA, MLB). Specifically, this module shows how to forecast the outcome of NHL, NBA, MLB regular season games using an ordered logit model and publicly available information. It assesses the accuracy of these forecasts against the betting odds.

What's included

4 videos4 readings1 quiz4 ungraded labs

In this module we examine the historical and social consequences of gambling, and the relationship between gambling and statistics. Gambling is explored from the perspective of different ethical and religious systems. Issues of problem gambling are explored and assessed.

What's included

7 videos1 reading

Instructors

Youngho Park
University of Michigan
1 Course4,921 learners
Stefan Szymanski
University of Michigan
3 Courses20,747 learners

Offered by

Recommended if you're interested in Data Analysis

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4.6

29 reviews

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BB
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Reviewed on Jul 10, 2023

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