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How to get started with Sports Analytics – 3 Best Ways

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How to get started with Sports Analytics – 3 Best Ways

Sports Analytics is one of the most interesting applications of data science and Machine Learning in the world. Most professional-level teams have already started to rely on cutting-edge automated analytics about their game performance both as an individual as well as a team.

Also, Sports Analytics is now not only adopted by physical games such as basketball, football, etc. but also digital games such as DOTA 2, League of Legends, etc. This will help you have a wider perspective about what you are getting into.

Just to keep in check with the real world, at this very moment, there are several sports analytics competitions on Kaggle with a prize pool of over USD $100,000. This clearly shows the rise of importance of analytics and in this article, we will share how to get started with Sports Analytics.

Here are 3 best ways you can get started with Sports Analytics:

1. Enroll in a Sports Analytics Online Course

If you’re looking to work on Sports Analytics, the best action you can take today is to enroll in a Sports Analytics course. Today, there are multiple Sports Analytics courses out there to choose from and you’re able to gain a value of buck by choosing the right course.

We recommend ‘Data Science for Sports – Sports Analytics and Visualization‘ since it provides you with the know-how of working on multiple sports-related datasets as well as visualizing your findings.

Data Science for Sports - Sports Analytics and Visualization - How to get started with Sports Analytics

This course provides insights and knowledge into how you can perform analysis on sports data and then, visualize it using Python. You will start the course by looking at the games in the 2018 NFL season. Then, you will move onto look at the player statistics in order to understand the players in the season. You will also look at the plays of the NFL season and finally, end the course by building a data visualization project where we will be visualizing the American Football Field and players on top of it.

The course has over 7000 students already enrolled with an average rating of 4.5/5 stars so its tried and tested by other learners like you as well. Enrolling in an online course will give you the freedom to learn things from seasoned professionals.

here to enroll in 'Data Science for Sports - Sports Analytics and Visualization'. (opens in a new tab)" href="https://www.udemy.com/course/data-science-for-sports/?referralCode=DFB28D1806CC3DFBD9E4" target="_blank" rel="noreferrer noopener" class="rank-math-link">Click here to enroll in ‘Data Science for Sports – Sports Analytics and Visualization‘.

2. Get a Sports Analytics book

If online courses are not for you, books are a great way to start learning by yourself. Here is a list of three books that can help you learn Sports Analytics with a high level of detail:

  1. Sprawlball: A Visual Tour of the New Era of the NBA
  2. Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football
  3. Trading Bases: How a Wall Street Trader Made a Fortune Betting on Baseball
Get a Sports Analytics book - How to get started with Sports Analytics

3. Learn Python to perform Sports Analytics

The Python programming language is one of the most used programming languages in the sports analytics community. It offers a wide range of out-of-the-box libraries that can expedite your Sports Analytics journey.

To get started with Python for Sports Analytics, we suggest going through the following three courses:

  1. Python for Newbies – Complete Python Bootcamp
  2. NumPy for Scientific Computation with Python
  3. Full Stack Data Science Course – Become a Data Scientist

The above three courses will set up the foundation that you need to start performing Sports Analytics using Python.


If you are interested in more things data, The Click Reader provides you a large collection of data science resources to study from—check it out by clicking here.

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