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A New Era of Data Analysis in Baseball

Use MLB's Statcast data to compare New York Yankees sluggers Aaron Judge and Giancarlo Stanton.

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Project Description

There's a new era of data analysis in baseball. Using a new technology called Statcast, Major League Baseball is now collecting the precise location and movements of its baseballs and players. In this project, you will use Statcast data to compare the home runs of two of baseball's brightest (and largest) stars, Aaron Judge (6'7") and Giancarlo Stanton (6'6"), both of whom now play for the New York Yankees.

The dataset used in this project is from Baseball Savant.

Project Tasks

  1. 1
    The Statcast revolution
  2. 2
    What can Statcast measure?
  3. 3
    Aaron Judge and Giancarlo Stanton, prolific sluggers
  4. 4
    Analyzing home runs with Statcast data
  5. 5
    Home runs by pitch velocity
  6. 6
    Home runs by pitch location (I)
  7. 7
    Home runs by pitch location (II)
  8. 8
    Aaron Judge's home run zone
  9. 9
    Giancarlo Stanton's home run zone
  10. 10
    Should opposing pitchers be scared?

Technologies

Python Python

Topics

Data ManipulationData Visualization
David Venturi HeadshotDavid Venturi

Data Science Educator

David graduated from Queen's University with a dual degree in Chemical Engineering and Economics. After working for a year, he discovered online education (in the early MOOC era) and became enamored with its potential. He has since created content to help people navigate the space, including a DIY data science master's program, Class Central's Data Science Career Guide, courses for Udacity's Data Analyst Nanodegree program, and several DataCamp courses and projects. Visit his website to say hi!
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