In bdilday/GeomMLBStadiums: GeomMLBStadiums: Draw Major League Baseball Stadiums with ggplot2

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
#  fig.path = "README-",
  fig.height = 6,
  fig.width = 6,
  fig.units = "in"
)

GeomMLBStadiums

This package defines a couple of Geoms to draw MLB stadiums in ggplot2. It also provides a Geom to draw a "spraychart" - x and y locations of batted balls with a stadium overlay.

Example use

Install from github and load the necessary libraries

``` {r echo=FALSE, message=FALSE, warning=FALSE} library(GeomMLBStadiums) library(ggplot2) library(dplyr)

``` {r eval=FALSE, message=FALSE}
devtools::install_github("bdilday/GeomMLBStadiums")
library(GeomMLBStadiums)
library(ggplot2)
library(dplyr)

The stadium data

When you load the GeomMLBStadiums package it will attach the stadium paths as a data frame, MLBStadiumsPathData

head(MLBStadiumsPathData)

The data comprise the 30 current MLB stadiums, in addition to a "generic" stadium. The stadia are identified by team name, with the following conventions

unique(MLBStadiumsPathData$team)

The segments are split up into outfield_outer, outfield_inner, infield_inner, infield_outer, foul_lines, and home_plate

unique(MLBStadiumsPathData$segment)

Coordinates

The stadium paths are in the system of the hc_x and hc_y coordinates of MLBAM. These are inverted (because they're based on a display device where y=0 is at top, IIRC) which means by default the field gets displayed upside down. This package provides a helper function, mlbam_xy_transformation, that transforms these values to a system where y increases from bottom to top and home plate is located at (0, 0).

set.seed(101)
batted_ball_data = data.frame(hc_x = rnorm(20, 125, 10), 
                              hc_y = rnorm(20, 100, 20))

head(batted_ball_data)

head(mlbam_xy_transformation(batted_ball_data))

summary(mlbam_xy_transformation(batted_ball_data))

geom_mlb_stadium

This uses geom_mlb_stadium, which implicitly loads the MLBStadiumsPathData data, to plot the 30 current stadiums.

ggplot() + 
  geom_mlb_stadium(stadium_ids = "all_mlb", 
                   stadium_segments = "all") + 
  facet_wrap(~team) + 
  coord_fixed() + 
  theme_void()

An alternative way is to explicitly pass the data to geom_path.

MLBStadiumsPathData %>% 
  filter(team != 'generic') %>% 
  mutate(g=paste(team, segment, sep="_")) %>% 
  ggplot(aes(x, y)) + 
  geom_path(aes(group=g)) + 
  facet_wrap(~team) + 
  coord_fixed() + 
  theme_void()

This shows the generic stadium, which is the default,

ggplot() + 
  geom_mlb_stadium(stadium_segments = "all") + 
  facet_wrap(~team) + 
  coord_fixed() + 
  theme_void()

geom_spraychart

This generates some simulated data.

# first generate the data
set.seed(101)
batted_ball_data = data.frame(hc_x = rnorm(20, 125, 10),
                              hc_y = rnorm(20, 100, 20))
batted_ball_data$team = rep(c("angels", "yankees"), each=10)

This plots the data as a spraychart. By default it uses the "generic" stadium.

batted_ball_data %>% 
  ggplot(aes(x=hc_x, y=hc_y)) + 
  geom_spraychart() 

Add some styling using theme_void and coord_fixed

batted_ball_data %>% 
  ggplot(aes(x=hc_x, y=hc_y)) + 
  geom_spraychart() + 
  theme_void() + 
  coord_fixed()

This transforms the data and the stadium before plotting, passes the team names in stadium_ids, draws all segments, and facets by field.

batted_ball_data %>% mlbam_xy_transformation() %>%  
    ggplot(aes(x=hc_x_, y=hc_y_, color=team)) + 
    geom_spraychart(stadium_ids = unique(batted_ball_data$team),
                    stadium_transform_coords = TRUE, 
                    stadium_segments = "all") + 
    theme_void() + 
    coord_fixed() + 
    facet_wrap(~team) + 
    theme(legend.position = "bottom")

You can make use of any of the other ggplot2 functions, for example, contours from stat_density2d. The mapping argument for geom_spraychart gets passed to the underlying geom_point, as do any extra parameters passed into the ... argument of geom_spraychart, e.g. size=5 in the below.

batted_ball_data %>% mlbam_xy_transformation() %>%  
  ggplot(aes(x=hc_x_, y=hc_y_, color=team)) + 
  geom_spraychart(mapping = aes(shape=team), 
                  stadium_ids = unique(batted_ball_data$team),
                  stadium_transform_coords = TRUE, 
                  stadium_segments = "all", size=5) + 
  theme_void() + 
  coord_fixed() + 
  facet_wrap(~team) + 
  theme(legend.position = "bottom") + 
  stat_density2d(color='gray')

bdilday/GeomMLBStadiums documentation built on Sept. 24, 2023, 6:02 p.m.