Home Categories Jupyter Notebook

Wrangling Major League Baseball Pitchf&x Data with Python

Learners: 3,097

Instructor: Chaz Henry

Duration:

This course is perfect for coders, SaberMetricians, and baseball fans who want to gain insight into the MoneyBall phenomenon and the next wave of player development. Through the use of Python, learners will be able to wrangle MLB PitchF/x data from Clayton Kershaw's 2014 no-hitter and graph the pitches with MatPlotLib and PyPlot. Along the way, learners will also learn best practices for Jupyter Notebook, Python coding, XML parsing, and more. This course provides new learners with an introduction to SaberMetrics, the empirical study of baseball statistics. Don't miss out on this opportunity to explore the world of SaberMetrics and MoneyBall!▼▲

Course Feature Course Overview Course Provider

Go to class

Course Feature

Cost:

Paid

Provider:

Udemy

Certificate:

Paid Certification

Language:

English

Start Date:

2020-04-21

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 27th, 2023]

This course introduces new learners to SaberMetrics, the empirical study of baseball statistics. Learners will use Python to wrangle MLB PitchF/x data from Clayton Kershaw's 2014 no-hitter and graph the pitches with MatPlotLib and PyPlot. Best practices for Jupyter Notebook, Python coding, XML parsing, and more will also be covered. This course is suitable for coders, SaberMetricians, and baseball fans who are interested in gaining insight into MoneyBall and the next wave of player development.