035: ACC Football rolling win percentage

gtExtras
rollmean
Published

June 13, 2023

Add data

Code 
# example to scrape sports-reference and grab records 
# this is only for one team 

# url <- "https://www.sports-reference.com/cfb/schools/north-carolina"

# page <- read_html(url)

# table_rows <- page %>%
#  html_nodes("table#north-carolina tbody tr")

# year <- c()
# win <- c()
# loss <- c()

# for (row in table_rows) {

#  cells <- row %>% html_nodes("th, td")
  
#  year <- c(year, cells[2] %>% html_text(trim = TRUE))
#  win <- c(win, cells[8] %>% html_text(trim = TRUE))
#  loss <- c(loss, cells[9] %>% html_text(trim = TRUE))
# }

# unc_table <- data.frame(year = year, win = as.numeric(win), loss = as.numeric(loss)) %>% 
#  slice(1:18) %>% 
#  mutate(team = "North Carolina")

# save data in csv format to load 
acc_hist <- readr::read_csv("acc_hist.csv")

acct <- readr::read_csv("acc_fball.csv")

Make GT Table

Code 
# make table 
acc_wp <- acct |>
  dplyr::filter(team != "Notre Dame") |>
  dplyr::select(-...1) |>
  dplyr::mutate(logo = team) |>
  dplyr::relocate(logo, .before = team) |>
  dplyr::relocate(division, .before = total_wins) |>
  dplyr::arrange(-win_pct) |>
  gt::gt() |>
  gt::cols_label(
    # rename columns
    logo = "",
    team = "Team",
    division = "Division",
    total_wins = "W",
    total_loss = "L",
    win_pct = "Win %",
    title_apps = "Division",
    titles = "League"
  ) |>
  gt::tab_spanner(label = "Titles",
                  columns = c(title_apps, titles)) |>
  cfbplotR::gt_fmt_cfb_logo(columns = "logo") |>
  gt::fmt_number(columns = win_pct,
                 decimals = 3,
                 use_seps = FALSE) |>
  gtExtras::gt_fa_repeats(
    column = titles,
    palette = "orange",
    name = "trophy",
    align = 'left'
  ) |>
  gt::data_color(columns = c(win_pct),
                 colors = scales::col_numeric(
                   c(
                     "#0a4c6a",
                     "#73bfe2",
                     "#cfe8f3",
                     "#fff2cf",
                     "#fdd870",
                     "#fdbf11",
                     "#ca5800"
                   ),
                   domain = NULL
                 )) |>
  gt::tab_header(title = "ACC Football Regular Season Conference Records from 2005 to 2022 Seasons",
                 subtitle = "Excludes wins or losses from conference championship games and non-conference meetings") |>
  gt::tab_source_note(source_note = "@dadgumboxscores | June 13, 2023 | data via sports-reference.com")  |>
  gtExtras::gt_theme_538() |>
  gt::tab_footnote(footnote = "2020 season did not use divisions (Notre Dame was 9-0 in conference play that season).",
                   locations = gt::cells_column_labels(columns = team)) |>
  gt::tab_style(style = list(gt::cell_borders(
    sides = c("left"),
    color = "#c1c1c1",
    weight = gt::px(2)
  )),
  locations = list(gt::cells_body(columns = c(total_wins))))

gt::gtsave(acc_wp, 'acc_wp.png')

acc_wp
ACC Football Regular Season Conference Records from 2005 to 2022 Seasons
Excludes wins or losses from conference championship games and non-conference meetings
Team1 Division W L Win % Titles
Division League
Clemson Atlantic 114 31 0.786 8 list(name = "div", attribs = list(title = "8 trophy", `aria-label` = "8 trophy", role = "img"), children = list(list("Trophy Trophy Trophy Trophy Trophy Trophy Trophy Trophy")))
Virginia Tech Coastal 92 53 0.634 6 list(name = "div", attribs = list(title = "3 trophy", `aria-label` = "3 trophy", role = "img"), children = list(list("Trophy Trophy Trophy")))
Florida State Atlantic 87 57 0.604 5 list(name = "div", attribs = list(title = "4 trophy", `aria-label` = "4 trophy", role = "img"), children = list(list("Trophy Trophy Trophy Trophy")))
Pittsburgh Coastal 48 34 0.585 2 list(name = "div", attribs = list(title = "1 trophy", `aria-label` = "1 trophy", role = "img"), children = list(list("Trophy")))
Miami Coastal 81 64 0.559 1 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
Georgia Tech Coastal 78 67 0.538 4 list(name = "div", attribs = list(title = "1 trophy", `aria-label` = "1 trophy", role = "img"), children = list(list("Trophy")))
Louisville Atlantic 37 37 0.500 0 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
North Carolina Coastal 72 74 0.493 2 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
Boston College Atlantic 65 81 0.445 2 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
NC State Atlantic 65 81 0.445 0 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
Wake Forest Atlantic 61 82 0.427 2 list(name = "div", attribs = list(title = "1 trophy", `aria-label` = "1 trophy", role = "img"), children = list(list("Trophy")))
Virginia Coastal 55 89 0.382 1 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
Maryland Atlantic 27 45 0.375 0 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
Syracuse Atlantic 26 56 0.317 0 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
Duke Coastal 40 106 0.274 1 list(name = "div", attribs = list(title = "0 trophy", `aria-label` = "0 trophy", role = "img"), children = list(list("")))
@dadgumboxscores | June 13, 2023 | data via sports-reference.com
1 2020 season did not use divisions (Notre Dame was 9-0 in conference play that season).

Make rolling mean plot

Code 
# make plot
roll_data <- dplyr::group_by(acc_hist, team) |>
  dplyr::arrange(year) |>
  dplyr::mutate(win_pct = win / (win + loss)) |>
  dplyr::mutate(avg_wp = zoo::rollmean(
    win_pct,
    k = 3,
    fill = NA,
    align = 'right'
  )) |>
  dplyr::ungroup()

roll_data |>
  dplyr::mutate(team = forcats::fct_relevel(
    team,
    c(
      "Clemson",
      "Virginia Tech",
      "Florida State",
      "Miami",
      "Georgia Tech",
      "North Carolina",
      "Boston College",
      "NC State",
      "Wake Forest",
      "Virginia",
      "Duke",
      "Pittsburgh",
      "Louisville",
      "Syracuse",
      "Maryland",
      "Notre Dame"
    )
  )) |>
  ggplot2::ggplot(ggplot2::aes(x = year, y = win_pct)) +
  ggplot2::geom_col(alpha = 3 / 10,
                    linetype = 0,
                    ggplot2::aes(fill = team)) +
  ggplot2::geom_line(ggplot2::aes(x = year, y = avg_wp, color = team)) +
  cfbplotR::scale_color_cfb(alpha = .8) +
  cfbplotR::scale_fill_cfb(alpha = .8) +
  ggplot2::facet_wrap( ~ team, nrow = 4) +
  ggplot2::geom_hline(yintercept = .5,
                      linetype = 'dashed',
                      color = "#333333") +
  ggplot2::scale_x_continuous(breaks = c(2005, 2013, 2022),
                              labels = c("2005", "2013", "2022")) +
  ggplot2::scale_y_continuous(breaks = c(0, .5, 1.0),
                              labels = c("0", ".500", "1.000")) +
  ggthemes::theme_solarized() +
  ggplot2::theme(
    strip.text = cfbplotR::element_cfb_logo(size = 1),
    plot.title = ggtext::element_markdown(),
    plot.subtitle = ggtext::element_markdown(),
    text = ggplot2::element_text(family = "Arial"),
    panel.grid = ggplot2::element_blank()
  ) +
  ggplot2::labs(
    x = "",
    y = "",
    title = "ACC Football Regular Season Conference Win Percentages",
    subtitle = "Shows win percentage by season and rolling average over past three seasons",
    caption = "dadgumboxscores | June 13, 2023 | data via sports-reference.com"
  ) -> roll_plot

roll_plot

Code 
ggplot2::ggsave(
  "roll_plot.png",
  roll_plot,
  w = 10,
  h = 7.5,
  dpi = 600,
  type = 'cairo'
)