125: NET over 45 days

geom_ribbon
Published

January 16, 2025

Load data

Code 
library(cbbplotR)
library(rlang)

# majority of data wrangling done via evdevbyc repo
# see https://github.com/gallochris/evdev-byc/blob/main/data/college-basketball/

all_net_data <- readr::read_csv("byc_net.csv")

conference_summary <- all_net_data |> 
  dplyr::filter(conf %in% c("ACC", "Big 12", "SEC", 
                            "Big East", "Big Ten", "Mountain West")) |> 
  dplyr::mutate(
    conf = dplyr::case_match(conf,
                             "ACC" ~ "ACC - 18 teams",
                             "SEC" ~ "SEC - 16 teams",
                             "Big 12" ~ "Big 12 - 16 teams",
                             "Big Ten" ~ "Big Ten - 18 teams", 
                             "Big East" ~ "Big East - 11 teams",
                             "Mountain West" ~ "Mountain West - 11 teams", 
                             conf ~ conf
    ),
    conf = factor(conf, levels = c("SEC - 16 teams", "Big 12 - 16 teams", 
                                   "Big Ten - 18 teams", "Big East - 11 teams", 
                                   "ACC - 18 teams", "Mountain West - 11 teams"))
  ) |> 
  dplyr::group_by(date, conf) |> 
  dplyr::summarize(
    min_net = min(net, na.rm = TRUE),
    max_net = max(net, na.rm = TRUE),
    min_team = dplyr::first(team[which.min(net)]),
    max_team = dplyr::first(team[which.max(net)]),
    median_net = median(net, na.rm = TRUE),
    .groups = "drop"
  )

last_date_data <- conference_summary |>
  dplyr::filter(date == max(date))


# load cfb data from sportsoddhistory.com 
cfb <- readr::read_csv("cfb-champs.csv") |> 
  dplyr::select(season = Season, date = Date, where =Location, 
                game = ...4, score = ...5, winner = ...6,
                fav = Favorite)

Geom Ribbon chart

Code 
conf_plot <- ggplot2::ggplot(conference_summary) +
  ggplot2::geom_ribbon(
    ggplot2::aes(x = date, ymin = min_net, ymax = max_net, fill = conf),
    alpha = 0.3
  ) +
  hrbrthemes::theme_ipsum_rc(grid="XY") +
  ggplot2::geom_line(ggplot2::aes(x = date, y = min_net, color = conf), size = 1, linetype = "dashed") +
  ggplot2::geom_line(ggplot2::aes(x = date, y = max_net, color = conf), size = 1, linetype = "dashed") +
  ggplot2::geom_line(
    data = conference_summary,
    ggplot2::aes(x = date, y = median_net, color = conf),
    size = 1.2, 
    linetype = "dotted"
  ) +
  ggplot2::geom_label(
    data = last_date_data,
    ggplot2::aes(x = date, y = min_net, label = min_team),
    hjust = 1, vjust = -0.30,
    size = 4,
    family = "Roboto Condensed",
    label.padding = ggplot2::unit(0.1, "lines"),
    label.size = 0
  ) +
  ggplot2::geom_label(
    data = last_date_data,
    ggplot2::aes(x = date, y = max_net, label = max_team),
    hjust = 1, vjust = 1.7,
    size = 4,
    family = "Roboto Condensed",
    label.padding = ggplot2::unit(0.1, "lines"),
    label.size = 0
  ) +
  ggplot2::scale_y_reverse(breaks = seq(0, 350, by = 50)) + 
  ggplot2::labs(
    title = "NET Ranking Trends by Conference from December 1st to January 16th",
    subtitle = "Tracks 46 days of NET ranking shifts for six conferences.<br>Shows the best and worst-ranked teams today and the median over time.",
    x = "",
    y = "NET",
    color = "Conference",
    caption = "Viz by Chris at Bless your Chart | data via stats.ncaa.org | data through January 16 games"
  ) +
  ggplot2::facet_wrap(
    ~ conf,
    nrow = 3
  ) + 
  ggplot2::coord_flip() +
  ggplot2::coord_cartesian(ylim = c(350, -10)) +  # Expand y-axis limits
  ggplot2::theme(
    axis.text.x = ggplot2::element_text(angle = 75, hjust = 1, face ="bold"),
    axis.title.y = ggplot2::element_text(face = "bold", size = 12),
    legend.position = "none",
    strip.text = ggplot2::element_text(face = "bold"),
    plot.subtitle = ggtext::element_markdown(),
    plot.caption = ggtext::element_markdown(family = "Roboto Condensed")
  )

ggplot2::ggsave(
    "conf_plot.png",
    conf_plot,
    w = 8.75,
    h = 12,
    dpi = 600,
    bg = "white",
    type = 'cairo'
)

CFB Table

Code 
options(chromote.headless = "new")
cfb_tbl <- cfb |> 
  cbbplotR::gt_cbb_teams(winner, winner, include_name = FALSE) |> 
  dplyr::mutate(winner = 
                  dplyr::if_else(season == 2024, 
                                 "<img src='https://a.espncdn.com/combiner/i?img=/redesign/assets/img/icons/ESPN-icon-football-college.png' style='height: 25px; width: auto; vertical-align: -30%;'>",
                                 winner)) |> 
  dplyr::relocate(season, .after = winner) |> 
  dplyr::relocate(score, .after = winner) |> 
  dplyr::mutate(fav = dplyr::if_else(fav == "Yes", "check", "circle-xmark")) |>  dplyr::mutate(score = dplyr::if_else(is.na(score), "-", score),
                fav = dplyr::if_else(is.na(fav), "-", fav)                                                                               ) |> 
  gt::gt() |> 
  gt::fmt_markdown(winner) |> 
  gtUtils::gt_theme_gtutils() |> 
  gtExtras::gt_merge_stack(col1 = where, col2 = date) |> 
   gt::fmt_icon(
    rows = c(1, 5, 6, 8),
    columns = c(fav),
    fill_color = "#056206",
  ) |> 
   gt::fmt_icon(
    rows = c(2, 3, 4),
    columns = c(fav),
    fill_color = "#ff4c4c",
  ) |> 
  gt::cols_align(align = "right", columns = c(game, season)) |>
   gt::cols_align(align = "left", columns = c(where, winner, score, fav)) |> 
   gtUtils::gt_column_subheaders(
    winner = list(heading = "Champion", subtitle = "Winner"),
    fav = list(heading = "Favorite", subtitle = "Cover?"),
    score = list(heading = "Final", subtitle = "Score"),
    where = list(heading = "Location", subtitle = "Date"),
    season = list(heading = "Season", subtitle = "From Fall"),
    heading_color = "black",
    subtitle_color = "gray"
  ) |> 
  gt::cols_label(
    game = ""
  ) |> 
  gtExtras::gt_add_divider(
    columns = c(where, season),
    sides = "right",
    color = "black"
  ) |> 
    gt::tab_header(
    title = gt::html("National Champonship games with a point spread greater than a touchdown since 1998"),
    subtitle = gt::html(
      "Shows the eight college football championship games since 1998 with a point spread of eight or more points. <br>Ohio State is favored by -8.5 points against Notre Dame on Monday."
    )
  ) |>
  gt::tab_source_note(
    source_note =
      gt::html(
        "<hr>Data via sportsoddshistory.com, theme via {gtUtils}<hr>
        <b>Table by Chris at Bless your chart</b>"
      )
  ) |>
  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")
      )
    ),
    locations = gt::cells_body(
      columns = c(where, date, game)
    )
  ) |> 
  gt::tab_style(
    style = list(gt::cell_fill(color = "#C5C5FF")),
    locations = gt::cells_body(columns = c(game), rows = c(7))
  ) |> 
  gt::tab_options(table.width = gt::px(775)) |> 
   gtUtils::gt_border_bars_bottom(c("#636363", "#969696", "#cccccc"))

gtUtils::gt_save_crop(
  cfb_tbl,
  file = "cfb_chart.png",
  whitespace = 40,
  bg = "#FFFDF5"
)

cfb_tbl
National Champonship games with a point spread greater than a touchdown since 1998
Shows the eight college football championship games since 1998 with a point spread of eight or more points.
Ohio State is favored by -8.5 points against Notre Dame on Monday.
Location
Date
Champion
Winner
Final
Score
Season
From Fall
Favorite
Cover?
Inglewood, CA
1/9/23
Georgia (-13.5) vs TCU

65-7 2022 Check
Tempe, AZ
1/3/03
Miami (-11.5) vs Ohio State

31-24 2002 Circle Xmark
Pasadena, CA
1/6/14
Florida State (-11) vs Auburn

34-31 2013 Circle Xmark
Miami, FL
1/3/01
Florida State (-10.5) vs Oklahoma

13-2 2000 Circle Xmark
Miami, FL
1/7/13
Alabama (-10) vs Notre Dame

42-14 2012 Check
Miami, FL
1/11/21
Alabama (-9.5) vs Ohio State

52-24 2020 Check
Atlanta, GA
1/20/25
Ohio State (-8.5) vs Notre Dame

- 2024 -
Pasadena, CA
1/3/02
Miami (-8) vs Nebraska

37-14 2001 Check
Data via sportsoddshistory.com, theme via {gtUtils}
Table by Chris at Bless your chart