131: Non-conference games

gtUtils
Published

February 13, 2025

Load game data

Code 
library(rlang)
library(cbbplotR)
# wab data from this repo: 
# https://github.com/gallochris/evdev-byc/blob/main/data/college-basketball/wab_logs.R

wab_today <- readr::read_csv("wab-today.csv")

teams_to_show <- readr::read_csv("full_wab.csv") |> 
  dplyr::filter(trk_wab < 26 & net_wab < 26) |> 
  dplyr::pull(team)

games <- readr::read_csv("https://raw.githubusercontent.com/gallochris/evdev-byc/refs/heads/main/data/cbb_daily_gamelog.csv")

WAB square table

Code 
wab_tbl <- wab_today |> 
  dplyr::filter(team %in% teams_to_show) |> 
  dplyr::mutate(conf_total = paste0(conf, ": ", round(league, 2), " | NC: ", 
                                    round(non_con, 2))) |> 
  dplyr::select(team, conf_total, league, non_con) |> 
  dplyr::mutate(
    league = ceiling(league),
    non_con = ceiling(non_con),
    dplyr::across(c(league, non_con), ~ purrr::map(.x, ~ ifelse(seq_len(5) <= .x, 1, NA)), .names = "{.col}_vec")
  ) |>
  tidyr::unnest_wider(league_vec, names_sep = "_") |>
  tidyr::unnest_wider(non_con_vec, names_sep = "_") |>
  dplyr::rename_with(~ paste0("league_", seq_along(.)), starts_with("league_vec")) |>
  dplyr::rename_with(~ paste0("nc_", seq_along(.)), starts_with("non_con_vec")) |> 
  dplyr::select(-league, -non_con) |> 
  dplyr::mutate(
    dplyr::across(starts_with("league_"), ~ dplyr::if_else(.x == 1, 0, .x))
  ) |> 
  dplyr::select(league_5, league_4, league_3, league_2, league_1,
                team, conf_total,
                nc_1, nc_2, nc_3, nc_4, nc_5)


wab_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-basketball.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;'>Leaders in Wins-Above-Baseline <br><span style='color: #e66101'>Conference</span> | <span style='color: #1f78b4'>Non-Conference</span></span>
       <span style='font-size: 14px; font-weight: normal; display: block; text-align: center;'>Shows the teams with the highest WAB and compares the totals from conference and non-conference games through February 13.</span>
     </div>
     <div>
       <img src='https://a.espncdn.com/combiner/i?img=/redesign/assets/img/icons/ESPN-icon-basketball.png'
       style='height: 40px; width: auto; vertical-align: middle;'>
     </div>
   </div>
  <br>"
)


wab_plot <- wab_tbl |> 
  dplyr::ungroup() |> 
  cbbplotR::gt_cbb_teams(team, team) |> 
    gt::gt(
    groupname_col = c("conf")
    ) |> 
  gtExtras::gt_merge_stack(col1 = team, col2 = conf_total,
                           palette = c("black", "#333333"),
                           small_cap = FALSE) |> 
  gtUtils::gt_indicator_boxes(key_columns = "team",
                              color_yes = "#1f78b4",
                              color_no = "#e66101",
                              color_na = "#e1e1e1") |> 
gtUtils::gt_theme_gtutils() |>  
gt::fmt_markdown(team) |> 
gt::cols_align(team, align = "center") |> 
  gt::cols_label(team = "",
                 league_5 = "", 
                 league_4 = "", 
                 league_3 = "",
                 league_2 = "",
                 league_1 = "",
                 nc_1 = "", 
                 nc_2 = "", 
                 nc_3 = "", 
                 nc_4 = "", 
                 nc_5 = ""
                 ) |> 
   gt::tab_header(title = gt::html(wab_header)) |>
  gt::tab_source_note(
    source_note =
      gt::html(
        "<hr>WAB computed via data from barttorvik.com. The totals are rounded up to create <em>whole</em> numbers for the squares.<hr>Theme via {gtUtils} and logos from ESPN.<hr><b>Table by Chris at Bless your chart | data through February 13 games</b>"
      )
  ) |>
  gtUtils::gt_border_bars_bottom(c("#636363", "#969696", "#cccccc")) |> 
  gt::tab_options(table.width = gt::px(575)) |>
   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(15.5))),
    locations = gt::cells_body(columns = c(team, conf_total))
  ) 

gtUtils::gt_save_crop(wab_plot,
                      file = "wab_tbl.png",
                      whitespace = 60,
                      bg = "#FFFDF5")

wab_plot
Leaders in Wins-Above-Baseline
Conference | Non-Conference Shows the teams with the highest WAB and compares the totals from conference and non-conference games through February 13.

Auburn

SEC: 5.51 | NC: 4.29

Alabama

SEC: 4.92 | NC: 3.43

Florida

SEC: 3.88 | NC: 2.42

Tennessee

SEC: 2.61 | NC: 3.21

Texas A&M

SEC: 3.18 | NC: 2.5

Duke

ACC: 3.83 | NC: 1.71

Houston

Big 12: 5.16 | NC: 0.08

Purdue

Big Ten: 3.7 | NC: 1.47

Iowa St.

Big 12: 2.94 | NC: 1.71

Wisconsin

Big Ten: 2.84 | NC: 1.8

Mississippi

SEC: 2.94 | NC: 1.58

Memphis

American: 1.33 | NC: 3.08

Michigan

Big Ten: 4.61 | NC: -0.34

St. John’s

Big East: 3.56 | NC: 0.5

Marquette

Big East: 1.66 | NC: 2.34

Kentucky

SEC: 1.93 | NC: 1.98

Kansas

Big 12: 1.91 | NC: 1.98

Arizona

Big 12: 4.94 | NC: -1.19

Texas Tech

Big 12: 3.96 | NC: -0.29

Michigan St.

Big Ten: 2.91 | NC: 0.45

Louisville

ACC: 3.38 | NC: -0.26

Mississippi St.

SEC: 0.86 | NC: 2.23

Oregon

Big Ten: -0.14 | NC: 3.16
WAB computed via data from barttorvik.com. The totals are rounded up to create whole numbers for the squares.
Theme via {gtUtils} and logos from ESPN.
Table by Chris at Bless your chart | data through February 13 games

Game type plot

Code 
games_by_type <- games |> 
    dplyr::distinct(game_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()

type_plot <- games_by_type |> 
  ggplot2::ggplot(ggplot2::aes(x = date, y = cumulative, color = type)) +
  ggplot2::geom_line(size = 1) +
  ggplot2::scale_x_date(date_labels = "%B", date_breaks = "1 month") +  
  ggplot2::scale_y_continuous(limits = c(0, 2500)) +
  ggplot2::labs(title = "2024-25 Men's College Basketball<br> Number of Games by Type", 
                subtitle = "<span style='color: #e66101;'>Conference</span> <br> <span style='color: #1f78b4;'>Non-Conference</span>",
                caption = "Viz by Chris at Bless your Chart | data via barttorvik.com & games through February 13, 2025",
                x = "", y = "") +
  ggthemes::theme_wsj() +
  ggplot2::geom_vline(xintercept = as.Date("2024-12-31"), 
                      linetype = "dashed", color = "black", size = 1) +
  ggplot2::scale_color_manual(values = c("#e66101", "#1f78b4")) +
  ggplot2::annotate(
    "label",
    x = as.Date("2024-11-25"), 
    y = 1750,
    label = "~99% of  \nnon-conference  \ngames played  \nbefore January",  
    size = 3.5, color = "black", fill = "#1f78b4",
    family = "mono",
    fontface = "bold",
    alpha = .3
  ) +
   ggplot2::annotate(
    "label",
    x = as.Date("2025-02-01"), 
    y = 750,
    label = "~92% of conference  \ngames played  \nafter December",  
    size = 3.5, color = "black", fill = "#e66101",
    family = "mono",
    fontface = "bold",
    alpha = .3
  ) +
  ggplot2::theme(
    legend.position = "none",
    plot.title = ggtext::element_markdown(
      size = 18,
      face = 'bold',
      family = 'mono'
    ),
    plot.subtitle = ggtext::element_markdown(
      size = 10,
      family = 'mono',
      face = 'bold'
    ),
    plot.caption = ggtext::element_markdown(size = 7, family = 'mono', face = 'bold')
  )


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



type_plot