084: Bid Bandits

cbbplotR
gt
Published

March 17, 2024

AQ data

Code 
library(cbbplotR)

 ### Auto-qualifiers 

autobids <- c("Connecticut", 
              "Iowa St.",
              "Auburn",
              "Saint Mary's",
              "New Mexico",
              "Drake",
              "James Madison",
              "Grand Canyon",
              "UAB",
              "McNeese St.",
              "VCU",
              "Duquesne",
              "Yale",
              "Samford",
              "Vermont",
              "College of Charleston",
              "Akron",
              "Oakland",
              "Morehead St.",
              "Colgate",
              "Western Kentucky",
              "Illinois",
              "Wisconsin",
              "Duquesne",
              "Temple",
              "UC Davis",
              "South Dakota St.",
              "Longwood",
              "Florida",
              "Montana St.",
              "Stetson",
              "Wagner",
              "Grambling St.",
              "Howard",
              "Saint Peter's",
              "Oregon",
              "North Carolina St.")
             

# ACC    thief - 1
#American    thief - 2 
# Atlantic 10    thief - 2 
# Big 12 - 1 
# Big East - 1 
# Big Ten - 2
# Mountain West    thief - 1
# Pacific-12    thief - 1 
# SEC - 
# West Coast
# Missouri Valley    thief

confsPick <- c("ACC", "Amer", "A10", "B12",
               "BE", "B10", "MWC", "P12", "SEC", "WCC", "MVC")

sched_with_rtg <- readr::read_csv("https://raw.githubusercontent.com/gallochris/wab_data_job/main/data/played_sched_rtg.csv")
  
# pull confs 
  sched_with_rtg |> 
    dplyr::filter(team %in% autobids) |>
    dplyr::select(team, conf) |> 
    dplyr::distinct() -> teamConfs
  
  sched_with_rtg |>
    dplyr::filter(team %in% autobids) |>
    dplyr::group_by(team) |>
    dplyr::summarise(
      W = sum(result == "W"),
      L = sum(result == "L"),
      wabTotal = sum(wab)
    ) |>
    dplyr::arrange(-wabTotal) |> 
    dplyr::left_join(teamConfs, by = "team") |> 
    dplyr::filter(conf %in% confsPick) -> confTBL

  
  
  conf_name_lookup <- function(conf_var) {
    conf_var = dplyr::case_match(
      conf_var,
      "B12" ~ "Big 12",
      "BE" ~ "Big East",
      "P12" ~ "Pac-12",
      "B10" ~ "Big Ten",
      "Amer" ~ "American",
      "SB" ~ "Sun Belt",
      "Slnd" ~ "Southland",
      "BW" ~ "Big West",
      "SC" ~ "Southern",
      "AE" ~ "America East",
      "BSth" ~ "Big South",
      "ASun" ~ "Atlantic Sun",
      "Pat" ~ "Patriot",
      "Horz" ~ "Horizon",
      "BSky" ~ "Big Sky",
      "OVC" ~ "Ohio Valley",
      "Sum" ~ "Summit",
      "A10" ~ "Atlantic 10",
      "MWC" ~ "Mountain West",
      "MVC" ~ "Missouri Valley",
      "NEC" ~ "Northeast",
      "MAC" ~ "Mid-American",
      "MAAC" ~ "Metro Atlantic",
      "ind" ~ "Independent",
      conf_var ~ conf_var
    )
  }

Bid Bandit GT Table

Code 
  confTBL |> 
    dplyr::select(team, conf, W, L, wabTotal) |> 
    dplyr::mutate(conf = conf_name_lookup(conf)) |> 
    cbbplotR::gt_cbb_teams(team, team) |>
    gt::gt() |>
    gt::fmt_markdown(team) |>
    gt::cols_label(
      team = "",
      conf = "",
      W = "W", 
      L = "L",
      wabTotal = "WAB",
    ) |>
    gtExtras::gt_theme_538() |> 
    gt::cols_align(align = "left", columns = c("team")) |>
    gtExtras::gt_add_divider(columns = c(W), sides = "left") |> 
    gt::fmt_number(columns = c(wabTotal), decimals = 2) |>
    gtExtras::gt_hulk_col_numeric(columns = c(wabTotal), domain = c(11.5, -11)) |> 
    gt::fmt(
      columns = c(wabTotal),
      fns = function(x) {
        ifelse(x > 0, paste0("+", sprintf("%.1f", x)), sprintf("%.1f", x))
      }
    ) |>
    gt::tab_style(
      style = list(
        gt::cell_text(weight = "bold")
      ),
      locations = gt::cells_body(
        rows = c(7, 8, 10:15),
        columns = c(team, conf)
      )
    ) |> 
    gt::tab_style(
      style = gt::cell_text(
        color = "#333333",
        transform = "uppercase"
      ),
      locations = gt::cells_column_labels(everything())
    ) |>
    gt::tab_header(title = "AQ's and Bid Bandits: Records and Wins-Above-Bubble (WAB)",
                   subtitle = "Shows the record and wins-above-bubble of teams in conferences with potential bid thieves and their actual automatic qualifier. Leagues with actual bid thieves are in bold.") |>
    gt::tab_source_note(source_note = gt::html("<br>Wins-above-bubble (WAB) is a résumé metric that reflects how many more (or fewer)
games a team has won against its schedule than a bubble-quality team would be expected to win against that same schedule.<br>
Big Ten, SEC, American, and Atlantic 10 all complete conference championship games today.<hr>
<b>Fifth Factor + Bless your chart | Through March 16 games | data via cbbdata + cbbplotR</b>")) -> bidBandits

  
  gtExtras::gtsave_extra(bidBandits,
                       filename = "bidbandit_tbl.png",
                       vheight = 875,
                       vwidth = 600)

  
  bidBandits
AQ's and Bid Bandits: Records and Wins-Above-Bubble (WAB)
Shows the record and wins-above-bubble of teams in conferences with potential bid thieves and their actual automatic qualifier. Leagues with actual bid thieves are in bold.
W L WAB

Connecticut

 Big East 31 3 +11.3

Iowa St.

 Big 12 27 7 +6.8

Illinois

 Big Ten 26 8 +6.0

Auburn

 SEC 27 7 +5.4

Wisconsin

 Big Ten 22 13 +3.3

Florida

 SEC 24 11 +2.9

New Mexico

 Mountain West 25 9 +1.7

Drake

 Missouri Valley 27 6 +1.7

Oregon

 Pac-12 23 11 +1.4

Saint Mary’s

 WCC 25 7 +1.4

North Carolina St.

 ACC 22 14 -0.6

Duquesne

 Atlantic 10 23 11 -1.8

UAB

 American 22 11 -2.7

VCU

 Atlantic 10 22 13 -3.9

Temple

 American 15 20 -11.6

Wins-above-bubble (WAB) is a résumé metric that reflects how many more (or fewer) games a team has won against its schedule than a bubble-quality team would be expected to win against that same schedule.
Big Ten, SEC, American, and Atlantic 10 all complete conference championship games today.
Fifth Factor + Bless your chart | Through March 16 games | data via cbbdata + cbbplotR