Fivethirtyeight ggplot2 theme by Dr. Thomas Mock with monospaced axis text

theme_538_mono_demo.R

library(tidyverse)
library(ggtext)
library(espnscrapeR)

# Custom theme function ----

theme_538 <- function(..., base_size = 12) {
  
  theme(
    # plotting components
    
    ## drop minor gridlines
    panel.grid.minor = element_blank(),
    # change grid lines to gray
    panel.grid.major =  element_line(color = "#d0d0d0"),
    # fill the plot and panel spaces with grey and remove border
    panel.background = element_rect(fill = "#f0f0f0", color = NA),
    plot.background = element_rect(fill = "#f0f0f0", color = NA),
    panel.border = element_blank(),
    # remove strip background
    strip.background = element_blank(),
    # adjust the margins of plots and remove axis ticks
    plot.margin = margin(0.5, 1, 0.5, 1, unit = "cm"),
    axis.ticks = element_blank(),
    # change text family, size, and adjust position of titles
    text = element_text(family = "Chivo", size = base_size),
    axis.text = element_text(face = "bold", color = "grey", size = base_size),
    axis.title = element_text(face = "bold", size = rel(1.33)),
    axis.title.x = element_text(margin = margin(0.5, 0, 0, 0, unit = "cm")),
    axis.title.y = element_text(margin = margin(0, 0.5, 0, 0, unit = "cm"), angle =90),
    plot.title = element_text(face = "bold", size = rel(1.67), hjust = 0),
    plot.title.position = "plot",
    plot.subtitle = element_text(size = 16, margin = margin(0.2, 0, 1, 0, unit = "cm"), hjust = 0),
    plot.caption = element_text(size = 10, margin = margin(1, 0, 0, 0, unit = "cm"), hjust = 1),
    strip.text = element_text(size = rel(1.33), face = "bold"),
    ...
  )
}

theme_538_mono <- function(...) {
  theme_538(...) +
    theme(axis.text = element_text(family = "Fira Mono"))
}

# Data ----

diff_df <- readr::read_csv("https://raw.githubusercontent.com/jthomasmock/radix_themockup/master/static/diff_df.csv")
combo_pass <- readr::read_csv("https://raw.githubusercontent.com/jthomasmock/radix_themockup/master/static/combo_pass.csv")

nfl_stand <- 2014:2020 %>% 
  map_dfr(get_nfl_standings)

# Base plot ----

playoff_label_scatter <- tibble(
  differential = c(25,-125), y = c(0.3, 0.8), 
  label = c("Missed<br>Playoffs", "Made<br>Playoffs"),
  color = c("#D50A0A", "#013369")
)

playoff_diff_plot <- nfl_stand %>% 
  mutate(
    color = case_when(
      year < 2020 & playoff_seed <= 6 ~ "#013369",
      year == 2020 & playoff_seed <= 7 ~ "#013369",
      TRUE ~  "#D50A0A"
    )
  ) %>% 
  ggplot(aes(x = differential, y = win_percent)) +
  geom_vline(xintercept = 0, size = 0.75, color = "#737373") +
  geom_hline(yintercept = 0, size = 0.75, color = "#737373") +
  geom_point(
    aes(color = color),
    size = 3, alpha = 0.8
  ) +
  ggtext::geom_richtext(
    data = playoff_label_scatter,
    aes(x = differential, y = y, label = label, color = color),
    fill = "#f0f0f0", label.color = NA, # remove background and outline
    label.padding = grid::unit(rep(0, 4), "pt"), # remove padding
    family = "Chivo", hjust = 0.1, fontface = "bold",
    size = 8
  ) +
  scale_color_identity() +
  labs(x = "Points Differential", y = "Win Percent",
       title = "Playoff teams typically have a positive point differential",
       subtitle = "Data through week 15 of the 2020 NFL Season",
       caption = str_to_upper("Plot: @thomas_mock (Tiny modifications: @long39ng) | Data: ESPN")) +
  scale_y_continuous(
    # Only display unit for the top value ----
    labels = function(y) {
      if_else(
        y == max(y),
        paste0(y * 100, "%"),
        paste0(y * 100, " ")
      )
    },
    breaks = seq(.0, 1, by = .10)
  ) +
  scale_x_continuous(
    breaks = seq(-200, 250, by = 50)
  )

# Print out plot with theme ----

playoff_diff_plot +
  theme_538_mono()

ggsave("theme-538-mono.png", width = 8, height = 6, dpi = "retina")