bless your chart - 144: ACC Baseball

Load baseball

Code

library(rlang)
library(cbbplotR)
teams <- tibble::tibble(baseballr:::rds_from_url(
  "https://raw.githubusercontent.com/robert-frey/college-baseball/main/ncaa_team_lookup.rds")
) |> 
  dplyr::filter(year == 2025 & division == 1)


acc_ids <- teams |> 
  dplyr::filter(conference == "ACC") |> 
  dplyr::pull(team_id)

# function to fetch results 
acc_results <- function(id) {
  collegebaseball::ncaa_schedule(team_id = id, year = 2025) |>
    dplyr::filter(home_team_conference == "ACC" & away_team_conference == "ACC") |>
    dplyr::filter(!is.na(home_team_score))
}

acc_scores <- lapply(acc_ids, acc_results)

# grab results and adjust spacing issue with Miami 
acc_results_2025 <- as.data.frame(do.call(rbind, acc_scores)) |>
  dplyr::distinct(contest_id, .keep_all = TRUE )  |> 
  dplyr::mutate(home_team = dplyr::if_else(home_team == "Miami (FL) ", "Miami (FL)", 
                                           home_team),
                away_team = dplyr::if_else(away_team == "Miami (FL) ", "Miami (FL)", 
                                           away_team) 
  ) 


# find standings and run diffs 
home_diffs <- acc_results_2025 |>
  dplyr::mutate(h_diff = home_team_score - away_team_score) |>
  dplyr::group_by(home_team) |>
  dplyr::summarize(home_diff = sum(h_diff)) |>
  dplyr::rename(team = home_team)

away_diffs <- acc_results_2025 |>
  dplyr::mutate(a_diff = away_team_score - home_team_score) |>
  dplyr::group_by(away_team) |>
  dplyr::summarize(away_diff = sum(a_diff)) |>
  dplyr::rename(team = away_team)

full_diffs <- merge(home_diffs, away_diffs, by = "team")|>
  dplyr::mutate(full_diff = (home_diff + away_diff))|>
  dplyr::select(team, full_diff, home_diff, away_diff)

home_results <- acc_results_2025 |>
  dplyr::mutate(h_result = dplyr::if_else(home_team_score > away_team_score, "W", "L")) |>
  dplyr::group_by(home_team, h_result) |>
  dplyr::count() |>
  tidyr::pivot_wider( 
    names_from = h_result,
    values_from = n)|>
  dplyr::rename(team = home_team, h_w = W, h_l = L)

away_results <- acc_results_2025 |>
  dplyr::mutate(a_result = dplyr::if_else(away_team_score > home_team_score, "W", "L")) |>
  dplyr::group_by(away_team, a_result) |>
  dplyr::count() |>
  tidyr::pivot_wider( 
    names_from = a_result,
    values_from = n) |>
  dplyr::rename(team = away_team, a_w = W, a_l = L) |> 
  dplyr::mutate(across(everything(), ~ replace(.x, is.na(.x), 0))) 

# full run differentials 
full_recs <- merge(home_results, away_results, by = "team") |>
  dplyr::mutate(W = (h_w + a_w), L = (h_l + a_l))|>
  dplyr::select(team, W, L, h_w, h_l, a_w, a_l)

diffs_recs <- merge(full_diffs, full_recs, by ="team")

# find leaders
leader_wins <- max(diffs_recs$W)
leader_losses <- min(diffs_recs$L[diffs_recs$W == leader_wins])

# standings
standings <- diffs_recs |>
  dplyr::mutate(
    GB = ((leader_wins - W) + (L - leader_losses)) / 2,
    GB = ifelse(GB == 0, 0, GB),
    Win_Pct = round(W / (W + L), 3)
  ) |>
  dplyr::arrange(desc(Win_Pct)) |> 
  dplyr::mutate(
    overall_rec = paste0(W, "-", L),
    home_rec = paste0(h_w, "-", h_l),
    away_rec = paste0(a_w, "-", a_l),
    full_diff = ifelse(full_diff > 0, 
                       paste0("+", full_diff),
                       full_diff),
    record_diff = paste0(overall_rec, " | ", 
                         sprintf("%.3f", Win_Pct))
  ) |> 
  dplyr::select(
    team, 
    Win_Pct,
    record_diff
  )

acc_results_long <- dplyr::bind_rows(
  acc_results_2025 |>
    dplyr::transmute(
      season = year,
      date = as.Date(date, format = "%m/%d/%Y"),
      team = home_team,
      team_id = home_team_id,
      team_score = home_team_score,
      team_conference = home_team_conference,
      opp = away_team,
      opp_id = away_team_id,
      opp_score = away_team_score,
      opp_conference = away_team_conference,
      location = dplyr::case_when(
        neutral_site == "TRUE" ~ "neutral",
        TRUE ~ "home"
      ),
      contest_id
    ),
  acc_results_2025 |>
    dplyr::transmute(
      season = year,
      date = as.Date(date, format = "%m/%d/%Y"),
      team = away_team,
      team_id = away_team_id,
      team_score = away_team_score,
      team_conference = away_team_conference,
      opp = home_team,
      opp_id = home_team_id,
      opp_score = home_team_score,
      opp_conference = home_team_conference,
      location = dplyr::case_when(
        neutral_site == "TRUE" ~ "neutral",
        TRUE ~ "away"
      ),
      contest_id
    )
)

# hux table 
huxtable::as_hux(
  diffs_recs |>
    dplyr::mutate(c_games = W + L,
                  diff_per_game = sprintf("%.2f", full_diff / c_games)) |>
    dplyr::arrange(-full_diff) |>
    dplyr::mutate(rpi = c(7, 20, 31, 26, 29,
                          55, 14, 34, 32, 10, 
                          40, 51, 107, 49,
                          75, 52)) |>
    dplyr::select(team, rpi, diff_per_game, full_diff, c_games) |>
    dplyr::arrange(rpi) |>
    dplyr::mutate(seed = c(3, 5, 2, 1,
                           8, 10, 7, 9,
                           4, 11, 13, 12,
                           15, 6, 14, 16)) |>
    dplyr::select(Seed = seed, Team = team, RPI = rpi, `+/- per game` = diff_per_game) |>
    dplyr::arrange(`+/- per game`)
) |>
  huxtable::set_caption("ACC Tournament Seeds with RPI  and League  \nRun Differential Per Game") |>
  huxtable::set_caption_pos("top") |>
  huxtable::set_width(0.8)

ACC Tournament Seeds with RPI and League Run Differential Per Game
Seed	Team	RPI	+/- per game
5	Clemson	10	-0.10
11	Notre Dame	40	-0.53
12	Virginia Tech	51	-0.90
16	California	107	-1.43
13	Stanford	49	-2.33
14	Boston College	75	-2.40
15	Pittsburgh	52	-3.60
9	Miami (FL)	32	0.21
4	NC State	34	0.68
2	Florida St.	14	0.78
6	Virginia	55	0.96
10	Louisville	29	1.23
8	Wake Forest	26	1.30
7	Duke	31	1.93
1	Georgia Tech	20	2.13
3	North Carolina	7	2.38

Standings table

Code

# standings plot 
standings <- diffs_recs |>
  dplyr::mutate(
    GB = ((leader_wins - W) + (L - leader_losses)) / 2,
    GB = ifelse(GB == 0, 0, GB),
    Win_Pct = round(W / (W + L), 3)
  ) |>
  dplyr::arrange(desc(Win_Pct)) |> 
  dplyr::mutate(
    overall_rec = paste0(W, "-", L),
    home_rec = paste0(h_w, "-", h_l),
    away_rec = paste0(a_w, "-", a_l)
  ) |> 
  dplyr::select(
    team, 
    overall_rec, 
    full_diff,
    Win_Pct, 
    home_diff,
    home_rec,
    away_diff,
    away_rec
  )


baseball_header <-glue::glue(
  "<div style='display: flex; justify-content: space-between; align-items: center;'>
      <div>
       <img src='https://a3.espncdn.com/combiner/i?img=%2Fredesign%2Fassets%2Fimg%2Ficons%2FESPN%2Dicon%2Dbaseball.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;'>ACC Baseball Standings</span>
       <span style='font-size: 14px; font-weight: normal; display: block; text-align: center;'>Regular season final standings.</span>
     </div>
     <div>
       <img src='https://a.espncdn.com/combiner/i?img=/i/teamlogos/ncaa_conf/500/1.png'
       style='height: 60px; width: auto; vertical-align: middle;'>
     </div>
   </div>
  <br>"
)

standings |> 
  cbbplotR::gt_cbb_teams(team, team) |> 
  dplyr::arrange(-Win_Pct, -full_diff)|> 
  gt::gt() |> 
  gtUtils::gt_theme_gtutils() |> 
  gt::fmt_markdown(team) |> 
  gtExtras::gt_merge_stack(
    col1 = "home_diff",
    col2 = "home_rec",
    palette = c("black", "#848484"),
    small_cap = FALSE
  ) |> 
  gtExtras::gt_merge_stack(
    col1 = "away_diff",
    col2 = "away_rec",
    palette = c("black", "#848484"),
    small_cap = FALSE
  ) |> 
  gtUtils::gt_column_subheaders(
    home_diff = list(heading = "Home +/-", subtitle = "W-L"),
    away_diff = list(heading = "Away +/-", subtitle = "W-L"),
    heading_color = "black",
    subtitle_color = "gray"
  ) |> 
  gt::cols_label(
    team = "",
    overall_rec = "W-L",
    full_diff = "+/-",
    Win_Pct = "Win %",
  )|>
  gt::fmt(
    columns = c(full_diff, home_diff, away_diff),
    fns = function(x) {
      ifelse(x > 0, paste0("+", x), x)
    }
  )|>
  gt::data_color(
    columns = c(full_diff, home_diff, away_diff),
    direction = c("column"),
    method = c("numeric"),
    palette = c("#d7191c", "#fdae61", 
                "#ffffbf", "#a6d96a", 
                "#1a9641"),
    alpha = 0.5
  ) |> 
  gtUtils::gt_color_pills(Win_Pct,
                          domain = c(0.250, 0.750), format_type = "number", digits = 3,
                          palette = c("#d7191c", "#fdae61", 
                                      "#ffffbf", "#a6d96a", 
                                      "#1a9641"),
                          alpha = 0.5
  ) |> 
  gt::tab_header(title = gt::html(baseball_header)) |>
  gt::tab_source_note(source_note = gt::html("<hr><b>Table by Chris at Bless your chart | data via ncaa.org througn May 17 games</b>")) |>
  gt::cols_align(align = "left", columns = c(team)) |>
  gtExtras::gt_add_divider(columns = c(team, Win_Pct), 
                           sides = "right", color = "black") |> 
  gtUtils::gt_border_bars_bottom(c("#636363", "#969696", "#cccccc")) |> 
  gt::tab_options(table.width = gt::px(675)) |>
  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(14)
      )
    ),
    locations = gt::cells_body(
      rows = gt::everything(),
      columns = gt::everything()
    )
  ) |> 
  gt::tab_options(table.width = gt::px(575)) -> acc_tbl_one


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


acc_tbl_one

ACC Baseball Standings Regular season final standings.
	W-L	+/-	Win %	Home +/- W-L	Away +/- W-L
Georgia Tech	19-11	+64	0.633	+34 9-6	+30 10-5
Florida St.	17-10	+21	0.630	-7 7-5	+28 10-5
North Carolina	18-11	+69	0.621	+30 9-5	+39 9-6
North Carolina St.	17-11	+19	0.607	+21 10-5	-2 7-6
Clemson	18-12	-3	0.600	+3 9-6	-6 9-6
Virginia	16-11	+26	0.593	+15 9-6	+11 7-5
Duke	17-13	+58	0.567	+39 10-5	+19 7-8
Wake Forest	16-14	+39	0.533	+25 9-6	+14 7-8
Miami FL	15-14	+6	0.517	+6 9-5	0 6-9
Louisville	15-15	+37	0.500	+38 10-5	-1 5-10
Notre Dame	14-16	-16	0.467	-5 7-8	-11 7-8
Virginia Tech	12-18	-27	0.400	-24 5-10	-3 7-8
Stanford	11-19	-70	0.367	-56 4-11	-14 7-8
Boston College	11-19	-72	0.367	-25 6-9	-47 5-10
Pittsburgh	10-20	-108	0.333	-42 6-9	-66 4-11
California	9-21	-43	0.300	-32 4-11	-11 5-10
Table by Chris at Bless your chart \| data via ncaa.org througn May 17 games

ACC last 10 chart

Code

leader_wins <- max(diffs_recs$W)
leader_losses <- min(diffs_recs$L[diffs_recs$W == leader_wins])

# pivot to find record in last 10 ACC games
games_long <- acc_results_2025 |>
  dplyr::select(date, contest_id, home_team, away_team, home_team_score, away_team_score) |>
  dplyr::mutate(home_team = dplyr::if_else(home_team == "Miami (FL) ", "Miami (FL)", 
                                           home_team),
                away_team = dplyr::if_else(away_team == "Miami (FL) ", "Miami (FL)", 
                                           away_team) 
  ) |> 
  dplyr::mutate(
    team_home = home_team,
    team_away = away_team
  ) |>
  tidyr::pivot_longer(
    cols = c(home_team, away_team),
    names_to = "home_away",
    values_to = "team"
  ) |>
  dplyr::mutate(
    opponent = ifelse(home_away == "home_team", team_away, team_home),
    team_score = ifelse(home_away == "home_team", home_team_score, away_team_score),
    opp_score = ifelse(home_away == "home_team", away_team_score, home_team_score),
    result = dplyr::case_when(
      team_score > opp_score ~ "W",
      team_score < opp_score ~ "L",
      TRUE ~ "T"
    ),
    run_diff = team_score - opp_score
  ) |>
  dplyr::arrange(team, date)

# last 10 games 
last_10 <- games_long |>
  dplyr::group_by(team) |>
  dplyr::slice_tail(n = 10) |>
  dplyr::summarize(
    last10_wins = sum(result == "W"),
    last10_losses = sum(result == "L"),
    last10_diff = sum(run_diff),
    .groups = "drop"
  ) |>
  dplyr::mutate(last10_rec = paste0(last10_wins, "-", last10_losses))


standings <- diffs_recs |>
  dplyr::mutate(
    GB = ((leader_wins - W) + (L - leader_losses)) / 2,
    GB = ifelse(GB == 0, 0, GB),
    Win_Pct = round(W / (W + L), 3)
  ) |>
  dplyr::arrange(desc(Win_Pct)) |> 
  dplyr::mutate(
    overall_rec = paste0(W, "-", L),
    home_rec = paste0(h_w, "-", h_l),
    away_rec = paste0(a_w, "-", a_l)
  ) |> 
  dplyr::left_join(last_10, by = "team"
  ) |> 
  dplyr::select(
    overall_rec, 
    full_diff,
    Win_Pct,
    GB,
    last10_rec,
    last10_diff,
    team
  )

standings |>
  dplyr::mutate(repeat_team = team) |>
  dplyr::relocate(repeat_team, .before = overall_rec) |>
  cbbplotR::gt_cbb_teams(team, team, logo_height = 20, include_name = FALSE) |>
  cbbplotR::gt_cbb_teams(repeat_team,
                         repeat_team,
                         logo_height = 20,
                         include_name = FALSE) |>
  dplyr::arrange(GB, -Win_Pct, -full_diff) |>
  gt::gt() |>
  gt::fmt_markdown(columns = c(repeat_team, team)) |>
  gtExtras::gt_theme_dot_matrix() |>
  gt::fmt(
    columns = c(full_diff, last10_diff),
    fns = function(x) {
      ifelse(x > 0, paste0("+", x), x)
    }
  ) |>
  gt::data_color(
    columns = c(full_diff, last10_diff),
    direction = c("column"),
    method = c("numeric"),
    palette = c("#d7191c", "#fdae61", "#ffffbf", "#a6d96a", "#1a9641"),
    alpha = 0.5
  ) |>
  gtUtils::gt_color_pills(
    Win_Pct,
    domain = c(.1, .9),
    format_type = "number",
    digits = 3,
    palette = c("#8B0000", "#FF0000", "#FF4500", "#ADFF2F", "#008000"),
    pill_height = 15,
  ) |>
  gtExtras::gt_add_divider(columns = last10_diff,
                           sides = "left",
                           color = "black") |>
  gtUtils::gt_border_grid(color = "black",
                          weight = 0.5,
                          include_labels = FALSE) |>
  gt::tab_spanner(columns = c(last10_rec, last10_diff),
                  label = "Last 10 Games") |>
  gt::tab_spanner(columns = c(overall_rec, Win_Pct, full_diff, GB),
                  label = "Overall") |>
  gt::cols_label(
    repeat_team = "",
    last10_rec = "W-L",
    last10_diff = "+/-",
    overall_rec = "W-L",
    Win_Pct = "Win %",
    full_diff = "+/-",
    GB = "GB",
    team = "",
  ) |>
  gt::tab_header(title = gt::md("**ACC Baseball Final Regular Season Standings**"),
                 subtitle = "Records and run differentials for the regular season and last 10 games.") |>
  gt::tab_source_note(
    source_note = gt::html(
      "Through May 17 games games<br><b>Table by Chris at Bless your Chart <br> data via baseballR + stats.ncaa.org</b>"
    )
  ) |>
  gt::tab_options (
    source_notes.font.size = gt::px(10),
    row.striping.background_color = '#EEEEEE',
    table.font.size = gt::px(12),
    column_labels.text_transform = 'uppercase'
  ) |>
  gt::tab_style(
    locations = gt::cells_column_labels(),
    style = gt::cell_text(weight = 850, )
  ) |>
  gt::tab_options(table.width = gt::px(450)) -> acc_tbl_two


gtUtils::gt_save_crop(acc_tbl_two,
                      file = "acc_tbl_last_10.png",
                      whitespace = 30,
                      bg = "white")

acc_tbl_two

ACC Baseball Final Regular Season Standings
Records and run differentials for the regular season and last 10 games.
	Overall				Last 10 Games
	W-L	Win %	+/-	GB	W-L	+/-
	19-11	0.633	+64	0.0	5-5	-21
	17-10	0.630	+21	0.5	5-5	-12
	18-11	0.621	+69	0.5	6-4	+31
	17-11	0.607	+19	1.0	5-5	+6
	18-12	0.600	-3	1.0	5-5	+2
	16-11	0.593	+26	1.5	8-2	+40
	17-13	0.567	+58	2.0	6-4	+36
	16-14	0.533	+39	3.0	6-4	+26
	15-14	0.517	+6	3.5	5-5	+14
	15-15	0.500	+37	4.0	4-6	+4
	14-16	0.467	-16	5.0	8-2	+25
	12-18	0.400	-27	7.0	2-8	-37
	11-19	0.367	-70	8.0	5-5	-12
	11-19	0.367	-72	8.0	3-7	-13
	10-20	0.333	-108	9.0	4-6	-30
	9-21	0.300	-43	10.0	3-7	-24
Through May 17 games games Table by Chris at Bless your Chart data via baseballR + stats.ncaa.org

ACC baseball matrix

Code

standings <- diffs_recs |>
  dplyr::mutate(
    GB = ((leader_wins - W) + (L - leader_losses)) / 2,
    GB = ifelse(GB == 0, 0, GB),
    Win_Pct = round(W / (W + L), 3)
  ) |>
  dplyr::arrange(desc(Win_Pct)) |> 
  dplyr::mutate(
    overall_rec = paste0(W, "-", L),
    home_rec = paste0(h_w, "-", h_l),
    away_rec = paste0(a_w, "-", a_l),
    full_diff = ifelse(full_diff > 0, 
                       paste0("+", full_diff),
                       full_diff),
    record_diff = paste0(overall_rec, " | ", sprintf("%.3f", Win_Pct))
  ) |> 
  dplyr::select(
    team, 
    Win_Pct,
    record_diff
  )

# tidy results for the matrix 
acc_results_long <- dplyr::bind_rows(
  acc_results_2025 |>
    dplyr::transmute(
      season = year,
      date = as.Date(date, format = "%m/%d/%Y"),
      team = home_team,
      team_id = home_team_id,
      team_score = home_team_score,
      team_conference = home_team_conference,
      opp = away_team,
      opp_id = away_team_id,
      opp_score = away_team_score,
      opp_conference = away_team_conference,
      location = dplyr::case_when(
        neutral_site == "TRUE" ~ "neutral",
        TRUE ~ "home"
      ),
      contest_id
    ),
  acc_results_2025 |>
    dplyr::transmute(
      season = year,
      date = as.Date(date, format = "%m/%d/%Y"),
      team = away_team,
      team_id = away_team_id,
      team_score = away_team_score,
      team_conference = away_team_conference,
      opp = home_team,
      opp_id = home_team_id,
      opp_score = home_team_score,
      opp_conference = home_team_conference,
      location = dplyr::case_when(
        neutral_site == "TRUE" ~ "neutral",
        TRUE ~ "away"
      ),
      contest_id
    )
)

# make the matrix table long 
long_tbl <- acc_results_long |> 
  dplyr::group_by(team, opp) |> 
  dplyr::summarise('n_win' = sum(team_score > opp_score, na.rm = T),
                   'n_loss' = sum(team_score < opp_score, na.rm = T)) |> 
  dplyr::mutate('record' = paste0(n_win, '-', n_loss)) |> 
  dplyr::select(team, opp, record) |> 
  dplyr::ungroup() |> 
  dplyr::left_join(standings, by ="team") |> 
  dplyr::arrange(-Win_Pct) |> 
  dplyr::mutate(team = ifelse(team == "NC State", "N.C. State", team),
                team = ifelse(team == "Miami (FL)", "Miami FL", team)) |> 
  cbbplotR::gt_cbb_teams(team, team, logo_height = 25, include_name = FALSE) |>  
  tidyr::pivot_wider(names_from = opp,
                     values_from = record) |> 
  dplyr::select(team, 
                record_diff,
                `Georgia Tech`,
                `Florida St.`, 
                `North Carolina`, 
                `NC State`,
                `Clemson`,
                `Virginia`,
                `Duke`,
                `Wake Forest`,
                `Miami (FL)`,
                `Louisville`,
                `Notre Dame`,
                `Virginia Tech`,
                `Stanford`,
                `Boston College`,
                `Pittsburgh`,
                `California`
  )

# --- function for team headers 
md = function(x) {
  gt::html(x
           
  )
}

team_headers <- c(
  "Georgia Tech", "Florida St.", "North Carolina", "NC State",
  "Clemson", "Virginia", "Duke", 
  "Wake Forest", "Miami (FL)", "Louisville", "Notre Dame", "Virginia Tech",
 "Stanford", "Boston College", "Pittsburgh", "California"
)

# cfbplotR urls from https://github.com/Kazink36/cfbplotR/blob/main/data-raw/logo_ref_2.csv
team_img_urls <- c(
  "http://a.espncdn.com/i/teamlogos/ncaa/500/59.png", # gt
  "http://a.espncdn.com/i/teamlogos/ncaa/500/52.png", # fsu 
  "http://a.espncdn.com/i/teamlogos/ncaa/500/153.png", # unc
  "http://a.espncdn.com/i/teamlogos/ncaa/500/152.png", #ncsu
  "http://a.espncdn.com/i/teamlogos/ncaa/500/228.png", #clemson
  "http://a.espncdn.com/i/teamlogos/ncaa/500/258.png", # uva
  "http://a.espncdn.com/i/teamlogos/ncaa/500/150.png", # duke
  "http://a.espncdn.com/i/teamlogos/ncaa/500/154.png", # wake forest
  "http://a.espncdn.com/i/teamlogos/ncaa/500/2390.png", # miami
  "http://a.espncdn.com/i/teamlogos/ncaa/500/97.png", # lville
  "http://a.espncdn.com/i/teamlogos/ncaa/500/87.png", # notre dame
  "http://a.espncdn.com/i/teamlogos/ncaa/500/259.png", # vt
  "http://a.espncdn.com/i/teamlogos/ncaa/500/24.png", # stanford
  "http://a.espncdn.com/i/teamlogos/ncaa/500/103.png", # bc
  "http://a.espncdn.com/i/teamlogos/ncaa/500/221.png", #pitt
  "http://a.espncdn.com/i/teamlogos/ncaa/500/25.png" # cal
)

add_team_header <- function(team_name, img_url) {
  gtExtras::img_header(
    label = "",
    img_url = img_url,
    height = 25,
    palette = c("white")
  )
}

# add teams headers
team_headers_with_images <- purrr::map2(team_headers, team_img_urls, add_team_header) |>
  purrr::set_names(team_headers)

# table header 
baseball_header <-glue::glue(
  "<div style='display: flex; justify-content: space-between; align-items: center;'>
      <div>
       <img src='https://a3.espncdn.com/combiner/i?img=%2Fredesign%2Fassets%2Fimg%2Ficons%2FESPN%2Dicon%2Dbaseball.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;'>ACC Baseball Record Matrix</span>
       <span style='font-size: 14px; font-weight: normal; display: block; text-align: center;'>Final regular season conference records.</span>
     </div>
     <div>
       <img src='https://a.espncdn.com/combiner/i?img=/i/teamlogos/ncaa_conf/500/1.png'
       style='height: 60px; width: auto; vertical-align: middle;'>
     </div>
   </div>
  <br>"
)


long_tbl |>
  dplyr::mutate(dplyr::across(-c(team, record_diff),
                              ~ ifelse(is.na(.x), "-", 
                                       as.character(.x)))) |>
  gt::gt() |>
  gt::cols_label(team = "", !!!team_headers_with_images) |>
  gt::cols_align('center') |>
  gt::fmt_markdown('team') |>
  gtUtils::gt_theme_gtutils() |> 
  gtExtras::gt_merge_stack(
    col1 = "team",
    col2 = "record_diff",
    palette = c("black", "black"),
    small_cap = FALSE
  ) |> 
  gt::data_color(columns = c(-team, -record_diff),
                 fn = scales::col_factor(
                   palette = c("#FFFDF5", 
                               "#ffe0e0", "#ff9999", "#eeeeee", "#ffcccc", 
                               "#b2ffb2", "#7FFF7F", "#00FF00"),
                   domain = c("-", 
                              "0-3", "0-2", "1-1", "1-2", 
                              "2-0", "2-1", "3-0")
                 )
  ) |> 
  gt::tab_header(title = gt::html(baseball_header)) |>
  gt::tab_source_note(
    source_note =
      gt::html(
        "<hr>Data via baseballR, stats.ncaa.org | theme via {gtUtils} <br>
        Read the data left to right to see each team's record against other league opponents, plus overall league record and win percentage.<br>
        <hr><b>Table by Chris at Bless your chart | data from May 17</b>"
      )
  ) |>
  gtUtils::gt_border_bars_bottom(c("#636363", "#969696", "#cccccc")) |> 
  gt::tab_options(table.width = gt::px(675)) |>
  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
    )
  ) |> 
  gtUtils::gt_border_grid(color = "black",
                          weight = 0.5,
                          include_labels = FALSE) |> 
  gt::tab_style(
    style = list(
      gt::cell_text(font = gt::google_font("Signika Negative"),
                    size = gt::px(14)
      )
    ),
    locations = gt::cells_body(
      rows = gt::everything(),
      columns = gt::everything()
    )
  ) -> acc_tbl_three


gtUtils::gt_save_crop(acc_tbl_three,
                      file = "acc_tbl_matrix.png",
                      whitespace = 30,
                      bg = "#FFFDF5")

acc_tbl_three

ACC Baseball Record Matrix Final regular season conference records.

19-11 \| 0.633	-	-	-	-	1-2	1-2	2-1	-	0-3	2-1	3-0	2-1	3-0	-	2-1	3-0
17-10 \| 0.630	-	-	1-2	-	2-1	-	-	1-2	2-1	1-2	2-1	3-0	-	3-0	-	2-1
18-11 \| 0.621	-	2-1	-	1-1	-	-	2-1	3-0	2-1	1-2	-	2-1	1-2	2-1	2-1	-
17-11 \| 0.607	-	-	1-1	-	3-0	2-1	1-2	-	0-2	2-1	-	2-1	1-2	-	2-1	3-0
18-12 \| 0.600	2-1	1-2	-	0-3	-	-	1-2	2-1	-	2-1	2-1	-	2-1	-	3-0	3-0
16-11 \| 0.593	2-1	-	-	1-2	-	-	0-3	-	3-0	-	-	2-1	3-0	1-2	2-1	2-1
17-13 \| 0.567	1-2	-	1-2	2-1	2-1	3-0	-	-	1-2	-	-	2-1	0-3	-	3-0	2-1
16-14 \| 0.533	-	2-1	0-3	-	1-2	-	-	-	3-0	2-1	3-0	0-3	2-1	1-2	2-1	-
15-14 \| 0.517	3-0	1-2	1-2	2-0	-	0-3	2-1	0-3	-	-	1-2	-	-	3-0	2-1	-
15-15 \| 0.500	1-2	2-1	2-1	1-2	1-2	-	-	1-2	-	-	1-2	1-2	-	3-0	-	2-1
14-16 \| 0.467	0-3	1-2	-	-	1-2	-	-	0-3	2-1	2-1	-	1-2	3-0	1-2	-	3-0
12-18 \| 0.400	1-2	0-3	1-2	1-2	-	1-2	1-2	3-0	-	2-1	2-1	-	-	-	0-3	-
11-19 \| 0.367	-	0-3	1-2	-	-	2-1	-	2-1	0-3	0-3	2-1	-	1-2	-	2-1	1-2
11-19 \| 0.367	0-3	-	2-1	2-1	1-2	0-3	3-0	1-2	-	-	0-3	-	-	2-1	-	0-3
10-20 \| 0.333	1-2	-	1-2	1-2	0-3	1-2	0-3	1-2	1-2	-	-	3-0	-	1-2	-	-
9-21 \| 0.300	0-3	1-2	-	0-3	0-3	1-2	1-2	-	-	1-2	0-3	-	3-0	2-1	-	-
Data via baseballR, stats.ncaa.org \| theme via {gtUtils} Read the data left to right to see each team's record against other league opponents, plus overall league record and win percentage. Table by Chris at Bless your chart \| data from May 17

ACC baseball over time

Code

acc_plot_data <- acc_results_long |> 
  dplyr::arrange(team, date) |> 
  dplyr::mutate(
    win = as.integer(team_score > opp_score),
    loss = as.integer(team_score < opp_score)
  ) |>
  dplyr::group_by(team) |> 
  dplyr::mutate(
    cum_win = cumsum(win),
    cum_loss = cumsum(loss),
    win_diff = cum_win - cum_loss,
    cum_games = cum_win + cum_loss,
    cum_win_pct = cum_win / cum_games
  ) |> 
  dplyr::ungroup()

target_date <- as.Date("2025-05-20")

team_labels <- acc_plot_data |> 
  dplyr::arrange(desc(date), -contest_id) |> 
  dplyr::group_by(team) |> 
  dplyr::slice_max(order_by = date, n = 1) |> 
  dplyr::left_join(standings, by = c("team")) |> 
  dplyr::ungroup() |> 
  dplyr::group_by(cum_win_pct) |>
  dplyr::mutate(
    stagger = dplyr::row_number() - (dplyr::n() + 1) / 2,
    y_staggered = win_diff + stagger * 0.45
  ) |> 
  dplyr::ungroup() |> 
 dplyr::mutate(
     y_staggered = dplyr::case_when(
       team == "Florida St." ~ y_staggered + 0.3,
       team == "North Carolina" ~ y_staggered - 0.3,
       team == "Clemson" ~ y_staggered - 0.45,
       team == "Virginia" ~ y_staggered - 0.1,
       team == "Wake Forest" ~ y_staggered + 0.7,
       team == "Miami (FL)" ~ y_staggered - 0.7,
       team == "Louisville" ~ y_staggered - 0.7,
       team == "Virginia Tech" ~ y_staggered - 0.3,
       team == "Boston College" ~ y_staggered - 0.4,
       TRUE ~ y_staggered
     )
  ) |> 
  dplyr::distinct(team, .keep_all = TRUE)


extension_date <- as.Date("2025-05-25")

extend_rows <- acc_plot_data |> 
  dplyr::group_by(team) |> 
  dplyr::filter(date == max(date)) |> 
  dplyr::mutate(date = extension_date) |> 
  dplyr::ungroup()

acc_plot_data_extend <- dplyr::bind_rows(acc_plot_data, extend_rows)

ggplot2::ggplot(acc_plot_data_extend, ggplot2::aes(x = date, y = win_diff, color = team)) +
  ggplot2::geom_smooth(linewidth = 0.5, se = FALSE) +
  ggplot2::geom_text(
    data = team_labels,
    ggplot2::aes(x = as.Date("2025-05-31"), y = y_staggered, 
                 label = record_diff),
    hjust = -0.1,
    size = 3,
    show.legend = FALSE,
    family = "Roboto Condensed"
  ) +
  ggplot2::scale_x_date(
    limits = c(as.Date("2025-03-07"), as.Date("2025-06-15")),
    breaks = as.Date(c("2025-04-01", "2025-05-01")),
    labels = function(x) format(x, "%B")  # Full month name (e.g., "April")
  ) +
  ggplot2::expand_limits(x = target_date + 5) +
  cbbplotR::scale_color_cbb_teams() +
  cbbplotR::geom_cbb_teams(
    data = team_labels,
    ggplot2::aes(x = as.Date("2025-05-28"), 
                 y = y_staggered, team = team),
    width = 0.025,
    alpha = 0.6, 
    color = NA,
  ) +
  ggplot2::labs(
    title = "ACC Baseball Final Regular Season Standings",
    subtitle = "Shows change in record or win/loss differential over the course of the season.",
    x = "",
    y = "",
    caption = "Data via baseballr + stats.ncaa.org through May 17  \nViz by Chris at Bless your chart"
  ) +
  ggplot2::geom_hline(yintercept = 0, linetype = "dashed", color = "#eeeeee") +
  hrbrthemes::theme_ipsum() +
  ggplot2::theme(
    plot.title = ggtext::element_markdown(
      hjust = 0.5,
      size = 20,
      family = "Roboto Condensed"
    ),
    plot.subtitle = ggtext::element_markdown(
      hjust = 0.5,
      size = 8.5,
      lineheight = 1.5,
      family = "Roboto Condensed"
    ),
    legend.position = "none",
    #xis.text.x = ggplot2::element_blank(),
    axis.title.x = ggplot2::element_text(family = "Roboto Condensed"),
    axis.title.y = ggplot2::element_text(family = "Roboto Condensed"),
    plot.caption = ggplot2::element_text(face = "plain", size = 7.5, "Roboto Condensed")
  ) -> acc_b_plot


ggplot2::ggsave(
  "acc_b_plot.png",
  acc_b_plot,
  h = 8,
  w = 9.5,
  dpi = 600,
  bg = "white",
  type = 'cairo'
)

acc_b_plot