Baseball Data Analysis with R and Python

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Questions and Answers

What is the purpose of loading the MLBAM data in the analysis?

To visualize baseball statistics without any coding

To collect data from different sports leagues

To perform run expectancy analysis using game event data (correct)

To create a new data set from scratch

Which programming language is primarily used for the analysis discussed?

C++

Python

Java

R (correct)

How many rows are available in the MLBAM 2018 data set?

62,000

200,000

185,771 (correct)

100,000

What is the first step when starting the analysis in the Jupyter notebook?

Loading required packages Signup and view all the answers

Which column is immediately dropped from the MLBAM data and why?

Unnamed column that lacks essential information Signup and view all the answers

What data source does the book 'Analyzing Baseball Data with R' primarily use?

Retrosheet data Signup and view all the answers

What is the purpose of setting the option to display a maximum of 100 columns?

To improve readability of the data display Signup and view all the answers

How many columns are included in the MLBAM 2018 data set?

62 Signup and view all the answers

What does the variable start1B represent in the run expectancy analysis?

The player ID at first base before the plate appearance Signup and view all the answers

What is represented by the term NaN in the data set?

Neither a number nor applicable Signup and view all the answers

How does the startOuts variable function within the run expectancy framework?

It indicates the number of outs before the plate appearance Signup and view all the answers

In the context of this analysis, what does runsFuture represent?

Projected runs for the remainder of the season Signup and view all the answers

Which variable would indicate if second base is occupied before the plate appearance?

start2B Signup and view all the answers

What coding value is assigned to start1 if start1B is null?

0, indicating the base is not occupied Signup and view all the answers

What does the 'stand' variable represent in the dataset?

Whether the batter is right handed or left handed Signup and view all the answers

Which of the following variables indicates whether first base is occupied after the plate appearance?

end1B Signup and view all the answers

What does 'start1' represent in this context?

Whether first base is occupied Signup and view all the answers

How is the 'start_state' variable created?

By concatenating the occupied bases and outs as strings Signup and view all the answers

What is the purpose of converting the variables to strings using 'astype string'?

To ensure proper concatenation without mathematical operations Signup and view all the answers

What does 'end1' signify after the plate appearance?

Whether first base is occupied after the play Signup and view all the answers

What does the value of '0' represent for the variable 'end1'?

First base is not occupied after the plate appearance Signup and view all the answers

What is included in the 'end_state' variable?

The occupancy of bases and the current outs after the play Signup and view all the answers

Which statement is true regarding the occupancy variables 'start1', 'start2', and 'start3'?

They indicate base occupancy prior to the plate appearance Signup and view all the answers

What is the significance of the space added in the concatenation of the state variables?

To enhance readability of the variable Signup and view all the answers

What event is excluded from the run expectancy analysis due to its unrelatedness to batting performance?

Foul error Signup and view all the answers

Why is it important to ensure that outsInInning equals 3 in the analysis?

It ensures that ending the inning does not skew expectancy results. Signup and view all the answers

What condition is applied to subset the data in the analysis?

Including rows where start_state differs from end_state. Signup and view all the answers

After preparing the data, how many rows are retained for further analysis?

184,949 Signup and view all the answers

What is the main goal of the changes made to the data set?

To focus only on relevant game events for analysis. Signup and view all the answers

What type of event might occur in a game that would require exclusion from expectancy analysis?

A foul ball that leads to an error Signup and view all the answers

What does the run expectancy analysis aim to evaluate in baseball?

The likelihood of scoring runs in given game situations. Signup and view all the answers

What is the effect of excluding observations where start_state equals end_state?

It focuses the analysis on meaningful changes. Signup and view all the answers

Study Notes

Run Expectancy Analysis

Run expectancy (RE) variables are created for analysis
Analyzing Baseball Data with R, by Marchi and Albert (2013) is a useful resource for further reading
Jupyter Notebook will use MLBAM (Major League Baseball Advanced Media) data
General process of analyzing baseball data is similar to the book's, using R or Python
Packages pandas (pd) and numpy (np) are loaded
MLBAM 2018 data is read into a variable (MLBAM18)
Unnecessary 'unnamed: 0' column is dropped
Maximum display columns set to 100, due to many observations
Data contains event-by-event data for 2018 baseball season
Data has 185,771 rows and 62 columns

Run Expectancy Variables

Variables to keep for analysis are identified (batterName, batterID, eventType, etc.)
A new variable 'RE18' is created from MLBAM18 data, selecting specified columns
Variables 'start1B', 'start2B', 'start3B' represent base occupation before plate appearance

Base State Variables

These variables track base occupation prior to each plate appearance
Null values ('NaN') indicate a base is not occupied
Variables 'start1', 'start2', and 'start3' represent whether first, second, and third base are occupied respectively.

Plate Appearance State

'start_state' variable is created concatenating 'start1', 'start2', 'start3', and the number of outs prior to the plate appearance
The new variable gives a comprehensive state of the game before a given play appearance.

Plate Appearance State (End of Play)

End-of-play state variables ('end1', 'end2', 'end3') are created
A new variable 'end_state' is produced in a similar way to start-state, concatenating end variables and outs.

Data Filtering

Data is filtered, removing:
- Events where start_state is not equal to end_state
- Events with runs on play is equal to zero
- Unnecessary events like dropped foul balls
- Data rows where outsInInning isn't equal to 3
Resulting data set has 184,949 rows and 27 columns

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Description

Explore run expectancy analysis in baseball using R and Python. This quiz focuses on the analysis of MLBAM data and the creation of run expectancy variables. Familiarity with data manipulation in pandas and numpy is beneficial for this exercise.