Back in 2015, Rajiv Maheswaran gave a TED talk on ‘The Math Behind Basketball’s Wildest Moves’. In the talk, he explained how sports analytics is being used to get an edge over the competition in basketball. It truly explained the potential of performing analytics in sports.
Today, sports analytics is used for not only physical games like basketball or football but also for digital games (e-sports) such as DOTA 2, League of Legends, etc.
In simple words, sports analytics is the science of observing and recording events and actions during competition and training environments.
How to start learning Sports Analytics?
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.
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.
Click here to enroll in ‘Data Science for Sports — Sports Analytics and Visualization‘.
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