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The official Jupyter Conference
August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY

How Data Science Assists Sports: Jupyter Notebook, Analytics, and the 3-point Revolution

Moderated by: Chris Rawles

Who is this presentation for?

General audience, data scientists and engineers

Prerequisite knowledge

* Basic knowledge of Jupyter Notebook and Python * Interest in learning about data science and data visualization

What you'll learn

* Attendees will gain insight into how data analytics is impacting and changing, like many industries, the sports industry, however the talk will be for a general audience. * Attendees will understand how to use Jupyter Notebook combined with Apache Spark for data analytics. * Attendees will gain insight into using Jupyter Notebook for common data science tasks including data exploration, modeling, and visualization. * All data in the talk will use publicly available data and the GitHub source code will be available


The availability of data combined with new analytical tools have fundamentally transformed the sports industry, and in basketball in particular, analytics have shaped how the sport is played at both the amateur level and the professional level. In this talk, I show how Jupyter Notebook combined with powerful analytical tools such as Apache Spark and visualization tools like Matplotlib and Seaborn assist data science. Specifically, I will show using data from the past 35 years, how analytics has led to increased shooting efficiency and a 3-point revolution in basketball, that has started in the NBA and trickled down to college basketball. In addition, I will also demonstrate a typical data science workflow, connecting to Apache Spark and a PostgreSQL database from Jupyter Notebook and using common visualization tools to analyze and visualize data. This talk, while focused on sports analytics, is geared towards a general audience who is interested in learning how data analytics has transformed an entire industry.