101: Power conference win totals

geom_boxplot
Published

July 24, 2024

Load data

Code 
library(cbbplotR)
cfb_2024_sched <- readr::read_csv("2024_sched_win_totals.csv") 


# check by conferences 
confs_only <- cfbfastR::cfbd_team_info(year = 2024) |>
dplyr::select(opponent = school, opp_conf = conference)

cfb_by_conf <- cfb_2024_sched |>
dplyr::full_join(confs_only, by = "opponent")


p4_nd <- c("ACC", "SEC",
        "Big 12", "Big Ten", "ND")

cfb_by_conf |> 
    dplyr::mutate(opp_conf = dplyr::if_else(opponent == "Notre Dame", "ND", opp_conf)) |> 
    dplyr::filter(opp_conf %in% p4_nd) |> 
    dplyr::group_by(conference) |> 
    dplyr::summarise(
        teams = dplyr::n_distinct(team_name),
        sec_count = sum(opp_conf == "SEC"),
        acc_count = sum(opp_conf == "ACC"),
        big_12_count = sum(opp_conf == "Big 12"),
        big_ten_count = sum(opp_conf == "Big Ten"),
        nd_count = sum(opp_conf == "ND")
    ) |>
    dplyr::rowwise() |>
    dplyr::mutate(
        other_conf_count = sum(c(
            sec_count * (conference != "SEC"),
            acc_count * (conference != "ACC"),
            big_12_count * (conference != "Big 12"),
            big_ten_count * (conference != "Big Ten"),
            nd_count * (conference != "ND")
        )),
        per_team = other_conf_count/teams
    ) |>
    dplyr::ungroup() -> tray_conf

# playoff odds 
podds <- tibble::tribble(
  ~team, ~odds, ~win_total,~conf,
  "Ohio State",-650,10.5,"Big Ten",
  "Georgia",-600,10.5,"SEC",
  "Oregon",-290,10.5,"Big Ten",
  "Texas",-230,10.5,"SEC",
  "Notre Dame",-170,10.5,"Independent",
  "Penn State",-145,9.5,"Big Ten",
  "Ole Miss",-125,9.5,"SEC",
  "Alabama",+100,9.5,"SEC",
  "Michigan",+110,8.5,"Big Ten",
  "LSU",+125,9.5,"SEC",
  "Florida State",+160,9.5,"ACC",
  "Tennessee",+170,8.5,"SEC",
  "Missouri",180,9.5,"SEC",
  "Clemson",200,9.5,"ACC",
  "Miami",210,9.5,"ACC",
  "Texas A&M",240,8.5,"SEC",
  "Utah",260,9.5,"Big 12",
  "Kansas State",310,9.5,"Big 12"
) |> 
  dplyr::mutate(prob = dplyr::if_else(odds > 0,
                              100 / (odds + 100),
                              -odds / (-odds + 100)),
                )

Boxplot

Code 
cfb_2024_sched |> 
  dplyr::filter(conference %in% c("ACC", "SEC", "Big 12", "Big Ten")) |> 
  dplyr::distinct(team_name, .keep_all = TRUE) |> 
  ggplot2::ggplot(ggplot2::aes(x = conference, y = team_total, group = conference)) + 
  ggplot2::geom_boxplot(
    outliers = FALSE,
    color = "#474747", 
    fill = "transparent", 
    stat = "boxplot"
  ) +
  ggthemes::theme_fivethirtyeight() +
  ggplot2::theme(
    axis.text.x = cfbplotR::element_cfb_logo(size = 1.25), 
    axis.text.x.top = cfbplotR::element_cfb_logo(size = 1.25),
    legend.position = "none"
  ) +
  ggplot2::scale_x_discrete(
    position = "top", # Add x-axis to the top
    labels = c("ACC", "Big 12", "Big Ten", "SEC")
  ) +
  ggplot2::labs(title = "2024 College Football: Preseason Win Totals for 'Power' Conferences",
                    subtitle = "Shows the range of preseason win totals for teams in the ACC, Big 12, Big Ten, and SEC.  \nTeams with the highest (9.5 and up) and lowest (4.5 and below) win totals in each league are highlighted.",
                    caption = "Data via FanDuel + cfbfastR + cfbplotR | July 24, 2024  \nPlot by Chris (@dadgumboxscores) | Bless your chart",
                    x = "", 
                    y = "Win Totals") +
  ggplot2::scale_y_continuous(
    breaks = seq(0, 10.5, 3.5),
    labels = c(0, 3.5, 7.0, 10.5)
  ) -> base_plot

Annotations

Code 
base_plot +
ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3,
    y = 4.4,
    team = "Purdue",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3.2,
    y = 4.4,
    team = "Michigan State",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 2.8,
    y = 4.4,
    team = "Northwestern",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 2.9,
    y = 10.5,
    team = "Oregon",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3.1,
    y = 10.5,
    team = "Ohio State",
    height = .045,
    alpha = 0.8
  ) +
    ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3,
    y = 9.5,
    team = "Penn State",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 2.1,
    y = 9.5,
    team = "Utah",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 1.9,
    y = 9.5,
    team = "Kansas State",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 1.9,
    y = 4.5,
    team = "BYU",
    height = .045,
    alpha = 0.8
  ) +
    ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 2.1,
    y = 4.5,
    team = "Arizona State",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 2,
    y = 3.3,
    team = "Houston",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 1,
    y = 3.3,
    team = "Stanford",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 1.2,
    y = 9.5,
    team = "Florida State",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 1,
    y = 9.5,
    team = "Clemson",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 0.8,
    y = 9.5,
    team = "Miami",
    height = .045,
    alpha = 0.8
  ) +
      ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 0.8,
    y = 4.5,
    team = "Boston College",
    height = .045,
    alpha = 0.8
  ) +
        ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 1,
    y = 4.5,
    team = "Wake Forest",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 1.2,
    y = 4.5,
    team = "Virginia",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 4.1,
    y = 10.5,
    team = "Georgia",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3.9,
    y = 10.5,
    team = "Texas",
    height = .045,
    alpha = 0.8
  ) +
    ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3.7,
    y = 9.7,
    team = "Ole Miss",
    height = .045,
    alpha = 0.8
  ) +
     ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3.9,
    y = 9.7,
    team = "LSU",
    height = .045,
    alpha = 0.8
  ) +
       ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 4.1,
    y = 9.7,
    team = "Alabama",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 4.3,
    y = 9.7,
    team = "Missouri",
    height = .045,
    alpha = 0.8
  ) +
     ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 3.9,
    y = 4.5,
    team = "Arkansas",
    height = .045,
    alpha = 0.8
  ) +
       ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 4.1,
    y = 4.5,
    team = "Florida",
    height = .045,
    alpha = 0.8
  ) +
    ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 4,
    y = 3.5,
    team = "Mississippi State",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    cfbplotR::GeomCFBlogo,
    x = 4,
    y = 2.3,
    team = "Vanderbilt",
    height = .045,
    alpha = 0.8
  ) +
  ggplot2::annotate(
    geom = "label",
    x = 1,
    y = 6.5,
    color = "#333333",
    fill = "#e3e3e3",
    label = "17 teams  \nMax: 9.5  \nMedian: 7.5  \nMin: 3.5",
    size = 3.25,
    fontface = 'bold',
  ) +
  ggplot2::annotate(
    geom = "label",
    x = 2,
    y = 6.5,
    color = "#333333",
    fill = "#e3e3e3",
    label = "16 teams  \nMax: 9.5  \nMedian: 7.5  \nMin: 3.5",
    size = 3.25,
    fontface = 'bold',
  ) +
  ggplot2::annotate(
    geom = "label",
    x = 3,
    y = 6.5,
    color = "#333333",
    fill = "#e3e3e3",
    label = "18 teams  \nMax: 10.5  \nMedian: 6.5  \nMin: 4.5",
    size = 3.25,
    fontface = 'bold'
  ) +
  ggplot2::annotate(
    geom = "label",
    x = 4,
    y = 6.5,
    color = "#333333",
    fill = "#e3e3e3",
    label = "16 teams  \nMax: 10.5  \nMedian: 8.0  \nMin: 2.5",
    size = 3.25,
    fontface = 'bold'
  ) -> win_total_boxplot
  


ggplot2::ggsave(
  "conf_win_totals.png",
  win_total_boxplot,
  w = 9.5,
  h = 8.5,
  dpi = 300,
  type = 'cairo'
)

win_total_boxplot

GT Table for playoff odds

Code 
podds |>
  cbbplotR::gt_cbb_teams(team, team) |>
  dplyr::mutate(sentence = paste0(conf, " | Win Total: ", win_total)) |>
  dplyr::select(team, sentence, odds, prob) |>
  gt::gt() |>
  gt::fmt_markdown(team) |>
  gtExtras::gt_merge_stack(
    col1 = team,
    col2 = sentence,
    palette = c("black", "black"),
    font_weight = c("normal", "bold")
  ) |>
  gt::cols_label(
    team = "",
    sentence = "",
    odds = "Odds",
    prob = "% Chance"
  ) |>
  gt::tab_spanner(label = "Playoff Chances", columns = c(odds, prob)) |>
  gt::cols_align(align = "left", columns = c(team)) |>
  gt::data_color(
    columns = odds,
    direction = c("column"),
    method = c("numeric"),
    palette = c("Greens"),
    reverse = TRUE
  ) |>
  gt::data_color(
    columns = prob,
    direction = c("column"),
    method = c("numeric"),
    palette = c("Greens")
  ) |>
  gt::fmt_percent(columns = c(prob), decimals = 1) |>
  gtExtras::gt_add_divider(columns = c(team),
                           sides = "right",
                           color = "black") |>
  gt::tab_header(
    title = "2024 College Football: Preseason Win Totals and Odds to Make College Football Playoff",
    subtitle = gt::html(
      "Shows the probability to make college football playoff and preseason win totals using FanDuel data."
    )
  ) |>
  gt::tab_source_note(
    source_note = gt::html(
      "<br>Odds and win totals from FanDuel as of July 24, 2024<br>
      <hr><b>Table by Chris (@dadgumboxscores) + Bless your chart</b>"
    )
  ) |>
  gt::fmt(
    columns = c(odds),
    fns = function(x) {
      ifelse(x > 0, paste0("+", x), x)
    }
  ) |>
  gtExtras::gt_theme_excel() |>
  gt::tab_style(
    style = gt::cell_borders(
      sides = c("top"),
      color = 'black',
      weight = gt::px(1.5),
      style = 'solid'
    ),
    locations = gt::cells_body(rows = gt::everything())
  ) |>
  gt::tab_style(
    locations = gt::cells_row_groups(groups = gt::everything()),
    style = list(
      gt::cell_text(align = "center"),
      gt::cell_borders(
        sides = c("all"),
        color = "black",
        weight = gt::px(2)
      )
    )
  ) -> podds_tbl

gtExtras::gtsave_extra(podds_tbl,
                       filename = "podds-tbl.png",
                       vwidth = 550,
                       expand = 10)

podds_tbl
2024 College Football: Preseason Win Totals and Odds to Make College Football Playoff
Shows the probability to make college football playoff and preseason win totals using FanDuel data.
Playoff Chances
Odds % Chance

Ohio St.

Big Ten | Win Total: 10.5
-650 86.7%

Georgia

SEC | Win Total: 10.5
-600 85.7%

Oregon

Big Ten | Win Total: 10.5
-290 74.4%

Texas

SEC | Win Total: 10.5
-230 69.7%

Notre Dame

Independent | Win Total: 10.5
-170 63.0%

Penn St.

Big Ten | Win Total: 9.5
-145 59.2%

Mississippi

SEC | Win Total: 9.5
-125 55.6%

Alabama

SEC | Win Total: 9.5
+100 50.0%

Michigan

Big Ten | Win Total: 8.5
+110 47.6%

LSU

SEC | Win Total: 9.5
+125 44.4%

Florida St.

ACC | Win Total: 9.5
+160 38.5%

Tennessee

SEC | Win Total: 8.5
+170 37.0%

Missouri

SEC | Win Total: 9.5
+180 35.7%

Clemson

ACC | Win Total: 9.5
+200 33.3%

Miami FL

ACC | Win Total: 9.5
+210 32.3%

Texas A&M

SEC | Win Total: 8.5
+240 29.4%

Utah

Big 12 | Win Total: 9.5
+260 27.8%

Kansas St.

Big 12 | Win Total: 9.5
+310 24.4%

Odds and win totals from FanDuel as of July 24, 2024
Table by Chris (@dadgumboxscores) + Bless your chart