153: Conference Games

Load data

library(rlang)


# gt save function
gt_save_crop <- function(data,
                         file = NULL,
                         bg = "white",
                         whitespace = 50,
                         zoom = 2,
                         expand = 5) {
  tmp <- tempfile(fileext = ".png")
  
  # Wrap the gtsave_extra call in a tryCatch to handle errors
  tryCatch({
    gtExtras::gtsave_extra(data, tmp, zoom = zoom, expand = expand)
  }, error = function(e) {
    # If there's an error, try using regular gt::gtsave instead
    message("gtsave_extra failed, trying gt::gtsave...")
    gt::gtsave(data, tmp, zoom = zoom, expand = expand)
  })
  
  magick::image_read(tmp) |> 
    magick::image_trim() |> 
    magick::image_border(bg, glue::glue('{whitespace}x{whitespace}')) |> 
    magick::image_write(file)
  unlink(tmp)
}

# load processed games
games <- readr::read_csv("cfb_games_25.csv")

games_processed <- games |>
  dplyr::mutate(
    date = as.Date(game_date),
    # Define P4 conferences
    # home_is_p4 = homeConfShort %in% c("ACC", "SEC", "B12", "B10"),
    # away_is_p4 = awayConfShort %in% c("ACC", "SEC", "B12", "B10"),
    type = dplyr::case_when(
      homeClassification == "fcs" |
        awayClassification == "fcs" ~ "FCS Games",
      conferenceGame == TRUE ~ "Conference Games",
      conferenceGame == FALSE ~ "Non-Conference Games",
      TRUE ~ "Other"
    )
  ) |>
  dplyr::filter(type != "Other")


games_by_type <- games_processed |>
  dplyr::distinct(id, .keep_all = TRUE) |>
  dplyr::group_by(date, type) |>
  dplyr::summarise(count = dplyr::n(), .groups = "drop") |>
  tidyr::complete(date = seq(min(date), max(date), by = "day"),
                  type,
                  fill = list(count = 0)) |>
  dplyr::group_by(type) |>
  dplyr::arrange(date, .by_group = TRUE) |>
  dplyr::mutate(cumulative = cumsum(count)) |>
  dplyr::ungroup()

# count the teams in each conference 
conference_team_counts <- games |>
  dplyr::filter(
    !is.na(homeConference),
    homeClassification == "fbs"  # Only count FBS teams
  ) |>
  dplyr::select(homeTeam, homeConference) |>
  dplyr::distinct() |>
  dplyr::group_by(homeConference) |>
  dplyr::summarise(total_teams = dplyr::n(), .groups = "drop") |>
  dplyr::rename(conference = homeConference)

# conference counts
conference_weekly_counts <- games |>
  dplyr::filter(
    !is.na(homeConference),!is.na(awayConference),!is.na(week),
    homeClassification == "fbs",
    awayClassification == "fbs"
  ) |>
  dplyr::mutate(conference = homeConference) |>
  dplyr::group_by(conference, week) |>
  dplyr::summarise(
    total_games = dplyr::n(),
    conference_games = sum(conferenceGame == TRUE, na.rm = TRUE),
    .groups = "drop"
  ) |>
  dplyr::select(conference, week, conference_games) |>
  tidyr::pivot_wider(names_from = week,
                     values_from = conference_games,
                     names_prefix = "Week_") |>
  dplyr::mutate(dplyr::across(dplyr::starts_with("Week_"), ~ ifelse(is.na(.x), 0, .x))) |>
  dplyr::select(conference,
                dplyr::starts_with("Week_0"),
                dplyr::everything()) |> 
  dplyr::left_join(conference_team_counts, 
                   by = "conference")

Geom smooth

type_plot <- games_by_type |>
  ggplot2::ggplot(ggplot2::aes(x = date, y = cumulative, color = type)) +
  ggplot2::geom_smooth(linewidth = 1.2,
                       se = FALSE,
                       method = "loess") +
  ggplot2::scale_x_date(date_labels = "%B", date_breaks = "1 month") +
  ggplot2::scale_y_continuous(limits = c(0, 550), breaks = seq(0, 550, by = 50)) +
  ggplot2::scale_color_manual(
    values = c(
      "Conference Games" = "#e66101",
      "Non-Conference Games" = "#1f78b4",
      "FCS Games" = "#5d4e75",
      "P4 vs P4 Games" = "#d62728"
    )
  ) +
  ggplot2::labs(
    title = "2025 College Football Season <br>Cumulative Games by Type",
    subtitle = paste0(
      "<span style='color: #e66101;'>Conference Games</span><br>",
      "<span style='color: #1f78b4;'>Non-Conference Games</span><br>",
      "<span style='color: #5d4e75;'>Games with FCS opponents</span><br>"
    ),
    caption = "Viz by Chris at Bless your Chart <br> data via collegefootballdata.com",
    x = "",
    y = "Number of Games",
    color = "Game Type"
  ) +
  ggthemes::theme_wsj() +
  ggplot2::geom_vline(
    xintercept = as.Date("2025-09-10"),
    linetype = "dashed",
    color = "#acacac",
    size = 1
  ) +
  ggplot2::theme(
    plot.title = ggtext::element_markdown(
      size = 18,
      face = 'bold',
      family = 'mono'
    ),
    plot.subtitle = ggtext::element_markdown(
      size = 14,
      family = 'mono',
      face = 'bold'
    ),
    legend.position = "none",
    panel.grid.minor = ggplot2::element_blank(),
    plot.caption = ggtext::element_markdown(
      size = 7,
      family = 'mono',
      face = 'bold'
    )
  )

ggplot2::ggsave(
  "game_type_plot.png",
  type_plot,
  w = 7.5,
  h = 9,
  dpi = 600,
  type = 'cairo',
  bg = "white"
)

type_plot

Conference games table

custom_header <- glue::glue(
  "<div style='display: flex; justify-content: space-between; align-items: center;'>
      <div>
       <img src='https://a.espncdn.com/combiner/i?img=/redesign/assets/img/icons/ESPN-icon-football-college.png'
       style='height: 40px; width: auto; vertical-align: middle;'>
     </div>
     <div style='flex-grow:1; margin-left: 30px; margin-right: 30px'>
       <span style='display: block; font-weight: bold; text-align: center; font-size: 24px;'>Conference Games <br>by Week of the Season </span>
       <span style='font-size: 12px; font-weight: normal; display: block; text-align: center;'>Shows the number of regular season conference games each week for FBS conferences over the course of the season.</span>
     </div>
     <div>
       <img src='https://a.espncdn.com/combiner/i?img=/redesign/assets/img/icons/ESPN-icon-football-college.png'
       style='height: 40px; width: auto; vertical-align: middle;'>
     </div>
   </div>
  <br>"
)

week_labels <- setNames(as.character(0:14), paste0("Week_", 0:14))

conf_tbl <- conference_weekly_counts |>
  dplyr::filter(!conference %in% c("Pac-12", "FBS Independents")) |>
  dplyr::select(-Week_16) |>
  dplyr::mutate(
    conference = dplyr::case_match(
      conference,
      "American Athletic" ~ "American",
      "Conference USA" ~ "CUSA",
      "Mid-American" ~ "MAC",
      conference ~ conference
    ),
    total_teams = paste0(total_teams, " ", "teams")
  ) |>
  gt::gt() |>
  gtUtils::gt_theme_gtutils() |>
  gtExtras::gt_merge_stack(
    col1 = "conference",
    col2 = "total_teams",
    palette = c("black", "#848484"),
    small_cap = FALSE
  ) |> 
  gt::cols_align(conference, align = "left") |>
  gtUtils::gt_column_subheaders(
    conference = list(heading = "Conference", subtitle = "# of teams"),
    heading_color = "black",
    subtitle_color = "gray"
  ) |>
  gt::cols_label(.list = week_labels) |>
  gtUtils::gt_border_grid(color = "black",
                          weight = 0.5,
                          include_labels = FALSE) |>
  gtExtras::gt_add_divider(
    columns = c(conference),
    sides = "right",
    color = "black"
  ) |>
  gt::tab_spanner(columns = c(-conference), label = "Week") |>
  gt::data_color(
    columns = c(-conference),
    direction = c("column"),
    method = c("numeric"),
    palette = c("#d7191c", "#fdae61", "#ffffbf", "#a6d96a", "#1a9641"),
    domain = c(0, 9),
    alpha = 0.6
  ) |>
  gt::tab_header(title = gt::html(custom_header)) |>
  gt::tab_source_note(
    source_note =
      gt::html(
        "<hr>Data via collegefootballdata.com | theme via {gtUtils} <br>
        Only regular season conference games through end of November 2025 shown<br>
        <hr><b>Table by Chris at Bless your chart</b>"
      )
  ) |>
  gtUtils::gt_border_bars_bottom(c("#636363", "#969696", "#cccccc")) |>
  gt::tab_options(table.width = gt::px(500)) |>
  gt::tab_style(
    locations = gt::cells_source_notes(),
    style = gt::cell_text(
      font = gt::google_font("Signika Negative"),
      size = gt::px(11.5),
      weight = 250
    )
  ) |>
  gt::tab_style(
    style = list(gt::cell_text(
      font = gt::google_font("Signika Negative"),
      size = gt::px(14)
    )),
    locations = gt::cells_body(
      rows = gt::everything(),
      columns = gt::everything()
    )
  ) |>
  gt::tab_style(
    locations = gt::cells_column_spanners(),
    style = gt::cell_text(
      font = gt::google_font("Signika Negative"),
      weight = 850,
      size = gt::px(15)
    )
  )

gt_save_crop(conf_tbl,
             file = "conf_tbl.png",
             whitespace = 40,
             bg = "#FFFDF5")

conf_tbl

Conference Games by Week of the Season Shows the number of regular season conference games each week for FBS conferences over the course of the season.
Conference # of teams	Week
	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14
ACC 17 teams	0	0	0	3	3	6	7	4	6	7	8	6	6	6	6
American 14 teams	0	0	1	1	2	4	5	6	6	4	4	6	5	5	7
Big 12 16 teams	1	0	0	2	3	7	7	7	6	7	7	5	6	7	8
Big Ten 18 teams	0	0	0	2	5	6	6	9	8	7	6	7	8	8	9
CUSA 12 teams	1	0	1	1	1	3	2	4	4	4	6	5	5	5	6
MAC 13 teams	0	0	0	1	1	3	5	5	6	6	2	5	6	6	6
Mountain West 12 teams	0	0	0	1	2	1	4	6	5	4	4	4	5	6	6
SEC 16 teams	0	0	1	4	2	5	4	6	8	7	6	5	6	4	6
Sun Belt 14 teams	0	0	0	1	1	3	4	6	7	5	5	5	6	6	7
Data via collegefootballdata.com | theme via {gtUtils} Only regular season conference games through end of November 2025 shown Table by Chris at Bless your chart

Faceted by conference

games_processed <- games |>
  dplyr::mutate(
    date = as.Date(game_date),
    type = dplyr::case_when(
      homeClassification == "fcs" |
        awayClassification == "fcs" ~ "FCS Games",
      conferenceGame == TRUE ~ "Conference Games",
      conferenceGame == FALSE ~ "Non-Conference Games",
      TRUE ~ "Other"
    )
  ) |>
  dplyr::filter(type != "Other")

home_games <- games_processed |>
  dplyr::select(id, date, type, conference = homeConference)

away_games <- games_processed |>
  dplyr::select(id, date, type, conference = awayConference)

games_by_conf <- dplyr::bind_rows(home_games, away_games) |>
  dplyr::filter(!is.na(conference) & conference != "")


games_by_conference_type <- games_by_conf |>
  dplyr::distinct(id, conference, .keep_all = TRUE) |>
  dplyr::group_by(date, conference, type) |>
  dplyr::summarise(count = dplyr::n(), .groups = "drop") |>
  tidyr::complete(date = seq(min(games_processed$date), max(games_processed$date), by = "day"),
                  conference,
                  type,
                  fill = list(count = 0)) |>
  dplyr::group_by(conference, type) |>
  dplyr::arrange(date, .by_group = TRUE) |>
  dplyr::mutate(cumulative = cumsum(count)) |>
  dplyr::ungroup() |>
  dplyr::left_join(conference_team_counts, by = "conference") |>   dplyr::filter(
    conference %in% c(
      "ACC",
      "American Athletic",
      "Big 12",
      "Big Ten",
      "Conference USA",
      "Mid-American",
      "Mountain West",
      "SEC",
      "Sun Belt"
    )
  )

# Create the faceted plot
conf_facet_plot <- games_by_conference_type |>
  dplyr::mutate(conf_display = paste0(conference, "\n", total_teams, " teams"),
                conf_display = forcats::fct_reorder(conf_display, total_teams, .desc = TRUE)) |>
  ggplot2::ggplot(ggplot2::aes(x = date, y = cumulative, color = type)) +
  ggplot2::geom_smooth(
    linewidth = 0.8,
    se = FALSE,
    method = "loess",
    span = 0.7
  ) +
  ggplot2::facet_wrap(~ conf_display, scales = "fixed", ncol = 3) +
  ggplot2::scale_x_date(date_labels = "%b", date_breaks = "1 month") +
  ggplot2::scale_y_continuous(limits = c(0, 85), breaks = c(0, 20, 40, 60, 80)) +
  ggplot2::scale_color_manual(
    values = c(
      "Conference Games" = "#e66101",
      "Non-Conference Games" = "#1f78b4",
      "FCS Games" = "#5d4e75"
    )
  ) +
  ggplot2::labs(
    title = "2025 College Football Season<br>Cumulative Games by Type and Conference",
    subtitle = paste0(
      "<span style='color: #e66101;'>Conference Games</span> | ",
      "<span style='color: #1f78b4;'>Non-Conference Games</span> | ",
      "<span style='color: #5d4e75;'>Games with FCS opponents</span>"
    ),
    caption = "Viz by Chris at Bless your Chart <br> data via collegefootballdata.com",
    x = "",
    y = "Cumulative Games",
    color = "Game Type"
  ) +
  ggthemes::theme_wsj() +
  ggplot2::geom_vline(
    xintercept = as.Date("2025-09-10"),
    linetype = "dashed",
    color = "#acacac",
    size = 0.5,
    alpha = 0.7
  ) +
  ggplot2::theme(
    plot.title = ggtext::element_markdown(
      size = 16,
      face = 'bold',
      family = 'mono'
    ),
    plot.subtitle = ggtext::element_markdown(
      size = 12,
      family = 'mono',
      face = 'bold'
    ),
    legend.position = "none",
    panel.grid.minor = ggplot2::element_blank(),
    plot.caption = ggtext::element_markdown(
      size = 8,
      family = 'mono',
      face = 'bold'
    ),
    strip.text = ggplot2::element_text(
      size = 10,
      face = 'bold',
      family = 'mono'
    ),
    axis.text.x = ggplot2::element_text(size = 8),
    axis.text.y = ggplot2::element_text(size = 8)
  )

ggplot2::ggsave(
  "conf_type_plot.png",
  conf_facet_plot,
  w = 7.5,
  h = 9,
  dpi = 600,
  type = 'cairo',
  bg = "white"
)

conf_facet_plot