4 Best Sports Analytics Courses For Beginners in 2024
If you have ever wondered how your favorite team of players has been able to achieve so much success, then Sports Analytics is the answer. Sports analytics is really just a collection of relevant, historical, statistics that can provide a competitive advantage to a team or individual.
Analytics is becoming more and more important in all sports, not only for professional teams but for sports betting as well. After all, a team that uses sports analytics, will have a better chance of winning than a team that doesn't.
What you can do with data can help determine who to play and when, the final score of a game, and which team is likely to be the most successful. To get the best insights you will need to learn from the best sources.
Keeping this in mind, here at Coursesity, we have curated 5 of the Best Online Sports Analytics Courses for you to learn relevant, historical statistics that can provide a competitive advantage to a team or individual.
Top Sports Analytics Tutorials For Beginners List
- Sports Performance Analytics
- Sports Revenue Strategies and Analytics
- Foundations of Sports Analytics: Data, Representation, and Models in Sports
- The Data Science of Sports Management
Disclosure: We're supported by the learners and may earn from course purchases.
1. Sports Performance Analytics
Learn Predictive Sports Analytics with Real Sports Data.
The course includes:
- Foundations of Sports Analytics: Data, Representation, and Models in Sports
- Moneyball and Beyond
- Prediction Models with Sports Data
- Wearable Technologies and Sports Analytics
- Introduction to Machine Learning in Sports Analytics
Initially, you will discover a variety of techniques for representing sports data, as well as how to extract narratives based on these analytical techniques. You will learn how to use Python to program data to test the claims that underpin the Moneyball story, and how to examine the evolution of Moneyball statistics since the book's publication.
The main purpose of this Sports Analytics course is to use regression analysis to analyze team and player performance data, with examples from the National Football League (NFL), the National Basketball Association (NBA), the National Hockey League (NHL), the English Premier League (EPL, soccer), and the Indian Premier League (IPL, cricket).
Additionally, you will also be shown how to use Python to forecast game results in professional sports and how to assess the reliability of a model using betting odds data.
You can take a Sports Performance Analytics certification course on Coursera.
Course rating: 4.5 out of 5.0
Duration: 4 months (10 hours/week)
Certificate: Certificate on completion
2. Sports Revenue Strategies and Analytics
Learn How the Sports Business Ecosystem Works.
The course includes:
- Sports Business Overview
- Ticket Pricing Strategy
- TV & Digital Media
- Global Growth Strategy
In this Sports Analytics course, you will learn how to look at the Sports business as a holistic entity and get an overview of it. You will also understand how the Sports business ecosystem works and get familiar with Key performance indicators to better understand how to evaluate the business.
You can take the Sports Revenue Strategies and Analytics certificate course on Udemy.
Course rating: 4.3 out of 5.0
Duration: 1.5 Hours
Certificate: Certificate on completion
3. Foundations of Sports Analytics: Data, Representation, and Models in Sports
Offered by the University of Michigan. Learn how to use Python to Analyze Team Performance in Sports.
The course includes:
- Introduction to Sports Performance and Data
- Introduction to Data Sources
- Introduction to Sports Data and Plots in Python
- Introduction to Sports Data and Regression Using Python
- More on Regressions
- Is There a Hot Hand in Basketball?
This course provides an introduction to using Python to analyze team performance in sports as you will discover a variety of techniques that can be used to represent sports data and how to extract narratives based on these analytical techniques.
This Sports Analytics class does not simply explain methods and techniques, it enables the learner to apply them to sports datasets of interest so that they can generate their own results, rather than relying on the data processing performed by others.
While the course materials have been developed using Python, code has also been produced to derive all of the results in R, for those who prefer that environment.
You can take the Foundations of Sports Analytics: Data, Representation, and Models in Sports certification course on Coursera.
Course rating: 4.4 out of 5.0
Duration: 49 Hours
Certificate: Certificate on completion
4. The Data Science of Sports Management
Learn Sports Analytics step by step.
The course includes:
- Measuring athlete performance
- Coaching and data science
- Sports and media deals
- Ticket pricing algorithms
- Building an audience in sports
- Audience interactions and projections
- Legal and ethical issues
- Careers in sports management
With this course, you will explore the profound ways in which data science affects the world of sports and sports management, as well as the larger affect it has on audiences and associated industries.
Going further, the course also takes a non-technical approach, ensuring that sports fans of many technical backgrounds can glean insights from his instruction. It also covers how the principles of data science can help with the measurement of athletic performance, as well as ticket pricing, coaching players, and more.
You can take The Data Science of Sports Management, with Barton Poulson Online Class certification course on Linkedin Learning.
Course rating: 4.7 out of 5.0
Duration: 1 Hour
Certificate: Certificate on completion
Hey! We hope you have found this Online Sports Analytics list helpful and intriguing. Since you've made it this far then certainly you are willing to learn more and here at Coursesity, it is our duty to enlighten people with knowledge on topics they are willing to learn.
Here are some more topics that we think will be interesting for you!