062: Quad Conferences

gt_tables
Published

December 10, 2023

Load data

Code 
quad_conf <- readr::read_csv("quad_conf.csv") |> 
  dplyr::select(-`...1`)


yr_df <- dplyr::tibble(
  season = c(2022, 2022, 2022, 2023, 2023, 2023),
  games = c(1662, 1662, 1662, 1736, 1736, 1736),
  pct = c("Under 3 hours", "3 to 4 hours", "Over 4 hours",
          "Under 3 hours", "3 to 4 hours", "Over 4 hours"),
  data = c(3.9,91.1,5.1, 7.5, 89.6, 2.9)
)

yr_df |> 
  dplyr::select(-season) |> 
  tidyr::pivot_wider(names_from = games, values_from = "data") -> plt_bar

GT Tables

Code 
quad_table <- quad_conf |> 
    dplyr::mutate(conf = dplyr::case_match(conf, 
                "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",
                conf ~ conf)) |> 
    dplyr::arrange(-q1s_per) |> 
    gt::gt() |> 
    gt::cols_label(
      teams = "Teams", 
      conf = "Conference", 
      games = "Games",
      avg_net = "AVG NET", 
      q1s_per = "Q1s / Team",
      q1s = "Q1",
      q2s = "Q2",
      q3s = "Q3",
      q4s = "Q4",
    ) |> 
    gt::fmt_number(columns = c(avg_net, q1s_per), decimals = 1) |> 
    gt::fmt_percent(columns = c(q1s, q2s, q3s, q4s), decimals = 1) |> 
    gt::tab_spanner(label = "Percentage of Games in each Quad", 
                    columns = c(q1s, q2s, q3s, q4s)) |> 
    gt::cols_nanoplot(
        columns = c(q1s, q2s, q3s, q4s),
        plot_type = "bar",
        new_col_name = "Quad",
        new_col_label = "Quadrants",
        options = gt::nanoplot_options(
            show_data_line = FALSE,
            show_data_area = FALSE,
            data_bar_stroke_color = "transparent",
            data_bar_fill_color = c("#1b7837", "#d9f0d3",
                                    "#e7d4e8",  "#762a83")
        )
    ) |> 
    gtExtras::gt_hulk_col_numeric(columns = c(avg_net), 
                                  reverse = TRUE) |> 
    gtExtras::gt_hulk_col_numeric(columns = c(q1s,
                                              q2s, q3s, q4s, q1s_per), trim = TRUE) |> 
    gtExtras::gt_theme_excel() |> 
   gt::tab_header(title = "Quadrant Opportunites in Conference Play Only", 
                  subtitle = "Shows percentage of conference games in each 
                  quadrant based on NET rankings as of December 11, 2023") |> 
  gt::tab_source_note(source_note = "Bless your chart | data via cbbdata")


# Football chart
 duration_tbl <-  plt_bar |> 
  gt::gt() |> 
  gt::cols_label(pct = "Duration",
                `1662` = "1662 games",
                 `1736` = "1736 games") |> 
  gt::tab_spanner(label = "2022",
                  columns = c(`1662`)) |>
  gt::tab_spanner(label = "2023",
                  columns = c(`1736`)) |>
  gtExtras::gt_theme_538() |> 
  gt::tab_header(title = "College football game duration: 2022 vs 2023", 
  subtitle = "Percentage of games including at least one FBS team 
             that lasted under 3 hours, between 3 and 4 hours, and over 4 hours")   |> 
  gt::tab_source_note(source_note = "Bless your chart | December 10, 2023") 


 quad_table
Quadrant Opportunites in Conference Play Only
Shows percentage of conference games in each quadrant based on NET rankings as of December 11, 2023
Conference Teams Games AVG NET Q1s / Team Percentage of Games in each Quad Quadrants
Q1 Q2 Q3 Q4
Big 12 14 252 53.9 10.9 60.7% 17.9% 17.9% 3.6%
0.61 0 0.61 0.18 0.18 0.036
Big East 11 220 84.2 10.0 50.0% 27.3% 9.1% 13.6%
0.50 0 0.50 0.27 0.091 0.14
SEC 14 252 75.2 9.6 53.6% 21.4% 14.3% 10.7%
0.54 0 0.54 0.21 0.14 0.11
Big Ten 14 280 74.4 8.6 42.9% 32.1% 21.4% 3.6%
0.43 0 0.43 0.32 0.21 0.036
ACC 15 300 88.5 6.7 33.3% 33.3% 23.3% 10.0%
0.33 0 0.33 0.33 0.23 0.10
Pac-12 12 240 95.9 6.7 33.3% 29.2% 20.8% 16.7%
0.33 0 0.33 0.29 0.21 0.17
Mountain West 11 198 108.5 6.5 36.4% 13.6% 36.4% 13.6%
0.36 0 0.36 0.14 0.36 0.14
Missouri Valley 12 240 128.1 4.2 20.8% 25.0% 33.3% 20.8%
0.33 0 0.21 0.25 0.33 0.21
Atlantic 10 15 270 121.1 2.4 13.3% 33.3% 40.0% 13.3%
0.40 0 0.13 0.33 0.40 0.13
American 14 252 156.4 1.9 10.7% 21.4% 32.1% 35.7%
0.36 0 0.11 0.21 0.32 0.36
Sun Belt 14 252 219.1 1.9 10.7% 3.6% 21.4% 64.3%
0.64 0 0.11 0.036 0.21 0.64
CUSA 9 144 203.1 1.8 11.1% 11.1% 16.7% 61.1%
0.61 0 0.11 0.11 0.17 0.61
WCC 9 144 166.2 1.8 11.1% 16.7% 38.9% 33.3%
0.39 0 0.11 0.17 0.39 0.33
Ivy 8 112 157.8 1.8 12.5% 12.5% 37.5% 37.5%
0.38 0 0.12 0.12 0.38 0.38
Big West 11 220 207.4 0.9 4.5% 13.6% 27.3% 54.5%
0.55 0 0.045 0.14 0.27 0.55
WAC 11 220 166.2 0.9 4.5% 13.6% 54.5% 27.3%
0.55 0 0.045 0.14 0.55 0.27
Southland 10 180 269.6 0.9 5.0% 5.0% 10.0% 80.0%
0.80 0 0.050 0.050 0.10 0.80
America East 9 144 203.9 0.0 0.0% 5.6% 50.0% 44.4%
0.50 0 0 0.056 0.50 0.44
Atlantic Sun 12 192 259.7 0.0 0.0% 0.0% 16.7% 83.3%
0.83 0 0 0 0.17 0.83
Big Sky 10 180 221.2 0.0 0.0% 5.0% 30.0% 65.0%
0.65 0 0 0.050 0.30 0.65
Big South 9 144 211.7 0.0 0.0% 11.1% 33.3% 55.6%
0.56 0 0 0.11 0.33 0.56
CAA 14 252 213.6 0.0 0.0% 17.9% 32.1% 50.0%
0.50 0 0 0.18 0.32 0.50
Horizon 11 220 217.5 0.0 0.0% 18.2% 27.3% 54.5%
0.55 0 0 0.18 0.27 0.55
Metro Atlantic 11 220 246.7 0.0 0.0% 4.5% 27.3% 68.2%
0.68 0 0 0.045 0.27 0.68
Mid-American 12 216 212.6 0.0 0.0% 16.7% 29.2% 54.2%
0.54 0 0 0.17 0.29 0.54
MEAC 8 110 291.5 0.0 0.0% 0.0% 11.8% 88.2%
0.88 0 0 0 0.12 0.88
Northeast 9 144 305.2 0.0 0.0% 0.0% 5.6% 94.4%
0.94 0 0 0 0.056 0.94
Ohio Valley 11 198 271.4 0.0 0.0% 4.5% 13.6% 81.8%
0.82 0 0 0.045 0.14 0.82
Patriot 10 180 287.2 0.0 0.0% 5.0% 10.0% 85.0%
0.85 0 0 0.050 0.10 0.85
Southern 10 180 193.6 0.0 0.0% 10.0% 45.0% 45.0%
0.45 0 0 0.10 0.45 0.45
SWAC 12 216 285.2 0.0 0.0% 0.0% 12.5% 87.5%
0.88 0 0 0 0.12 0.88
Summit 9 144 213.6 0.0 0.0% 0.0% 50.0% 50.0%
0.50 0 0 0 0.50 0.50
Bless your chart | data via cbbdata
Code 
 duration_tbl
College football game duration: 2022 vs 2023
Percentage of games including at least one FBS team that lasted under 3 hours, between 3 and 4 hours, and over 4 hours
Duration 2022 2023
1662 games 1736 games
Under 3 hours 3.9 7.5
3 to 4 hours 91.1 89.6
Over 4 hours 5.1 2.9
Bless your chart | December 10, 2023
Code 
gtExtras::gtsave_extra(quad_table, filename = "quad_table.png", vheight = 975, vwidth = 975)

gtExtras::gtsave_extra(duration_tbl, filename = "dur_table.png", vheight = 475, vwidth = 375)