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The Ever Expanding Strikeouts Game

Pau Sanho

Ironhack Data October 2020

Content

Project Description

This project takes a look at the correlation between the velocity and the spin rate of all the pitches thrown during the 2019 MLB season, and the relation between the spin rate and the outcomes of each pitch.

Questions & Hypotheses

The questions that I wanted to answer with this project are:

  • Is there any correlation between the spin rate of the ball and the speed which is thrown? In other words, does a higher spin rate means higher velocity?
  • Do pitches that produce a swinging strike have a higher spin rate that pitches that are put in play?

For the hypothesis testing I assumed the null hypothesis that the mean spin rate of the pitches that produced a swinging strike is equal to the pitches that produced a ball in play.

My alternative hypothesis is that pitches that produced a swinging strike have a higher mean than the pitches that did not.

Dataset

For this project I used the 2019 statcast dataset whith records of all the pitches thrown during that season, which includes, the release spin rate, release velocity and outcomes.

Workflow

Outline the workflow you used in your project. What are the steps you went through?

1-Define project topic 2-Find data set 3-Cleaned the data 4-Analyse data 5-Write project article 6-Prepare Presentation

Organization

To organize the work I created a Trello project where I listed all the items that I had to complete to deliver the project.

This repository contains a readme document with some basic information about the project, a .gitignore document and a folder with two jupyter noteboks, one for the data cleaning and the other one for the data analysis.

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Statistical analysis of the correlation between the velocity and the spin rate of all the pitches thrown during the 2019 MLB season, and the relation between the spin rate and the outcomes of each pitch.

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