University of Michigan - Prediction Models with Sports Data
- Offered byCoursera
Prediction Models with Sports Data at Coursera Overview
Duration | 33 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Prediction Models with Sports Data at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 5 in the Sports Performance Analytics Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 33 hours to complete
- English Subtitles: English
Prediction Models with Sports Data at Coursera Course details
- In this course the learner will be shown how to generate forecasts of game results in professional sports using Python. The main emphasis of the course is on teaching the method of logistic regression as a way of modeling game results, using data on team expenditures. The learner is taken through the process of modeling past results, and then using the model to forecast the outcome games not yet played. The course will show the learner how to evaluate the reliability of a model using data on betting odds. The analysis is applied first to the English Premier League, then the NBA and NHL. The course also provides an overview of the relationship between data analytics and gambling, its history and the social issues that arise in relation to sports betting, including the personal risks.
Prediction Models with Sports Data at Coursera Curriculum
Week 1
Introduction to Prediction Models
Binary Outcome and Regression Part 1
Binary Outcome and Regression Part 2
Logistic Regression Part 1
Logistic Regression Part 2
Ordered Logistic Regression Part 1
Ordered Logistic Regression Part 2
Predictive Modeling - Basics of Forecasting
Prediction Models Course Syllabus
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Assignment Overview
Assignment Instructions - Part 1
Week 1 - Part 1 - Sample Notebook
Assignment Instructions - Part 2
Week 1 - Part 2 - Sample Notebook
Week 1 R Content
Week 1 - Quiz 1
Week 1 - Quiz 2
Week 2
Gambling and Betting Markets
Betting Odd and Types of Bets
Betting Odds and Win Probabilities
Evaluating Betting Odds Using Brier Scores Part 1
Evaluating Betting Odds Using Brier Scores Part 2
Market Efficiency and Beating the Bookmaker
Assignment Overview
Week 2 - Sample Notebook
Week 2 R Content
Week 2 Quiz
Week 3
Forecasting EPL results: 1. Wages and Transfermarket Part 1
Forecasting EPL results: 1. Wages and Transfermarket Part 2
Forecasting EPL results: Within sample prediction Part 1
Forecasting EPL results: Within sample prediction Part 2
Forecasting EPL results: Out of sample forecasting Part 1
Forecasting EPL results: Out of sample forecasting Part 2
Forecasting EPL results: Forecasting the League Table
Assignment Overview
Week 3 - Sample Notebook
Week 3 R Content
Week 3 Quiz
Week 4
Forecasting Model: MLB
Forecasting Model: NHL Part 1
Forecasting Model: NHL Part 2
Forecasting Model: NBA
Assignment Overview
Assignment Instructions
Week 4 - Sample Notebooks
Week 4 R Content
Week 4 Quiz
Week 5
Gambling and the Development of Probability Theory
Gambling, Morality, and Sports Part 1
Gambling, Morality, and Sports Part 2
Social Policy and Sports Gambling
Problem Gambling Part 1
Problem Gambling Part 2
Match Fixing, Gambling and Sports
Post-Course Survey
Prediction Models with Sports Data at Coursera Admission Process
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