140: Portal

ggdist
gt
Published

April 21, 2025

Load cfbfastR data for Portal and baseball

Code 
library(rlang)
library(cbbplotR)
options(chromote.headless = "new")

portal <- cfbfastR::cfbd_recruiting_transfer_portal(2025) |> 
  dplyr::mutate(
    transfer_date = as.Date(transfer_date),
    transfer_month = lubridate::month(transfer_date, label = TRUE),
    transfer_year = lubridate::year(transfer_date),
    rating = as.numeric(rating),
    window = ifelse(transfer_month != "Apr", "Winter", "Spring"),
    position = ifelse(position == "ATH", "QB", position),
    position = forcats::fct_infreq(position) |> forcats::fct_rev(),
    rating_tier = dplyr::case_when(
      rating >= 0.95 ~ "Elite",
      rating >= 0.90 ~ "High",
      rating >= 0.85 ~ "Solid",
      TRUE ~ "Depth"
    )
  ) |> 
  dplyr::filter(!is.na(rating))

# data frames 
orgin_dst <- portal |> 
  dplyr::mutate(
    window = ifelse(transfer_date < as.POSIXct("2025-04-01"), "Winter", "Spring")
  ) |> 
  dplyr::filter(!is.na(origin) & !is.na(destination)) |>
  dplyr::count(origin, destination, sort = TRUE)

Portal plots

Code 
portal_plot <- portal |> 
  ggplot2::ggplot(ggplot2::aes(x = rating, order = rating, fill = window)) +
  ggdist::geom_dots(layout = "bar", group = NA, color = NA) +
  ggplot2::scale_fill_manual(
    values = c("Spring" = "#e4572e", "Winter" = "#6a7fd1")
  ) +
  ggplot2::scale_x_continuous(breaks = seq(0.75, 1.00, 0.05), limits = c(0.75, 1.00)) +
  ggplot2::labs(
    title = "College Football Transfer Portal  \nRatings by Window  \n<span style='color:#e4572e;'>Spring</span> and <span style='color:#6a7fd1; font-weight:bold'>Winter</span>",
    subtitle = "Each dot represents players that entered the portal ahead of the 2025 season.  \nDots are ordered by 247Sports Rating and grouped by the window when the player entered.",
     x = "<--- Lower Rating | Higher Rating --->",
    y = "",
    caption = "Only shows players with a 247Sports rating  \nViz by Chris at Bless your chart | data via cfbfastR and 247Sports.com | April 21, 2025"
  ) +
  hrbrthemes::theme_ipsum_rc() +
  ggplot2::theme(
    plot.title = ggtext::element_markdown(
      hjust = 0.5,
      size = 20,
      family = "Roboto Condensed"
    ),
    plot.subtitle = ggtext::element_markdown(
      hjust = 0.5,
      size = 9.5,
      lineheight = 1.5,
      family = "Roboto Condensed"
    ),
    legend.position = "none",
    axis.text.x = ggplot2::element_text(size = 11.5, family = "Roboto Condensed"),
    axis.title.x = ggplot2::element_text(size = 12.5, hjust = 0.5),
    axis.text.y = ggplot2::element_blank(),
    plot.caption = ggplot2::element_text(face = "plain", size = 8, "Roboto Condensed")
  ) +
    ggplot2::annotate(
    geom = "label",
    x = 0.985,
    y = .47,
    color = "#333333",
    fill = "#e4572e",
    label = "Nico Iamaleava  \nTennessee QB  \nApril 12, 2025",
    size = 3.5,
    fontface = 'bold',
    family = 'Roboto condensed',
    alpha = 0.3
  ) +
  ggplot2::annotate(
    geom = "curve",
    color = "#e4572e",
    x = 0.978,
    y = .41,
    xend = 0.98,
    yend = .02,
    curvature = .3,
    linewidth = 0.8,
    arrow = ggplot2::arrow(length = ggplot2::unit(2, "mm")),
    alpha = 0.3
  )


ggplot2::ggsave(
  "portal_plot.png",
  portal_plot,
  w = 7,
  h = 8.5,
  dpi = 600,
  bg = "white",
  type = 'cairo'
)

Table by position and window

Code 
portal_summary <- portal  |>
  dplyr::mutate(position = dplyr::if_else(position == "DT", "DL", position), 
                position = dplyr::if_else(position %in% c("P", "K", "LS"), "ST", position)) |>
  dplyr::mutate(rating = as.numeric(rating)) |>
  dplyr::filter(!is.na(rating)) |>
  dplyr::group_by(window, position) |>
  dplyr::summarise(
    Best = max(rating),
    Median = median(rating),
    Worst = min(rating),
    Total = dplyr::n(),
    .groups = "drop"
  )

position_order <- portal_summary |>
  dplyr::group_by(window) |>
  dplyr::arrange(desc(Total), .by_group = TRUE) |>
  dplyr::mutate(position = factor(position, levels = unique(position))) 


portal_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-football-college.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;'>Transfer Portal: 247Sports Ratings by Position</span>
       <span style='font-size: 14px; font-weight: normal; display: block; text-align: center;'>Best, worst, and median ratings for players in the portal ahead of the 2025 season.</span>
     </div>
     <div>
       <img src='https://a.espncdn.com/combiner/i?img=/redesign/assets/img/icons/ESPN-icon-football-college.png'
       style='height: 40px; width: auto; vertical-align: middle;'>
     </div>
   </div>
  <br>"
)


portal_table <- position_order |>
  tidyr::pivot_longer(
    cols = c(Best, Median, Worst, Total),
    names_to = "stat",
    values_to = "value"
  ) |>
  tidyr::pivot_wider(
    names_from = position,
    values_from = value
  ) |>
  dplyr::arrange(window, match(stat, c("Best", "Median", "Worst", "Total"))) |>
  gt::gt(groupname_col = "window") |> 
  gtUtils::gt_theme_gtutils() |> 
    gt::cols_label(
    stat = ""
  ) |> 
    gtUtils::gt_border_grid(color = "black",
                          weight = 0.5,
                          include_labels = FALSE) |> 
  gtExtras::gt_add_divider(
    columns = c(stat),
    sides = "right",
    color = "black"
  ) |> 
  gt::data_color(
    columns = c(-stat),
    rows = c(1:3, 5:7), 
    direction = c("column"),
    method = c("numeric"),
    palette = c("#d7191c", "#fdae61", 
                "#ffffbf", "#a6d96a", 
                "#1a9641"),
    alpha = 0.6
  ) |> 
  gt::cols_align(stat, align = "left") |> 
  gt::fmt_number(
    columns = c(-stat),
    rows = c(1:3, 5:7), 
    decimals = 2
  ) |> 
    gt::fmt_number(
    columns = c(-stat),
    rows = c(4, 8), 
    decimals = 0
  ) |> 
  gt::tab_header(title = gt::html(portal_header)) |>
  gt::tab_source_note(
    source_note =
      gt::html(
        "<hr>Data via cfbfastR | theme via {gtUtils} <br>
        Ratings provided by 247Sports and only surfaces players with an actual rating<br>
        Groups specialists together (K, P, LS) into one position group (ST)<br>
        Orders positions by the total number of players that entered the portal from the position<br>
        <hr><b>Table by Chris at Bless your chart | data from April 21, 2025</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
    )
  ) |> 
  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_style(
    locations = gt::cells_row_groups(),
    style = list(
      gt::cell_text(
        font = gt::google_font("Signika Negative"),
        weight = 850,
        size = gt::px(16),
        color = "black",
        align = "left"
      ),
      gt::cell_fill(
        color = "#C5C5FF"
      )
    )
  ) 


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

portal_table
Transfer Portal: 247Sports Ratings by Position Best, worst, and median ratings for players in the portal ahead of the 2025 season.

WR CB OT EDGE RB DL IOL LB QB S TE ST
Spring
Best 0.92 0.92 0.91 0.92 0.92 0.95 0.88 0.90 0.98 0.88 0.92 0.81
Median 0.86 0.86 0.86 0.86 0.85 0.86 0.86 0.86 0.86 0.85 0.86 0.80
Worst 0.83 0.83 0.83 0.82 0.81 0.83 0.80 0.81 0.82 0.83 0.81 0.79
Total 26 20 20 19 19 17 16 16 11 10 10 2
Winter
Best 0.96 0.93 0.92 0.98 0.92 0.93 0.94 0.91 0.96 0.90 0.94 0.82
Median 0.85 0.85 0.85 0.85 0.85 0.86 0.85 0.85 0.85 0.86 0.85 0.80
Worst 0.79 0.80 0.80 0.80 0.79 0.82 0.78 0.81 0.79 0.81 0.79 0.78
Total 286 169 124 151 131 130 170 115 127 125 102 17
Data via cfbfastR | theme via {gtUtils}
Ratings provided by 247Sports and only surfaces players with an actual rating
Groups specialists together (K, P, LS) into one position group (ST)
Orders positions by the total number of players that entered the portal from the position
Table by Chris at Bless your chart | data from April 21, 2025

ACC baseball standings

Code 
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)


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)

acc_results_2025 <- as.data.frame(do.call(rbind, acc_scores)) |>
  dplyr::distinct(contest_id, .keep_all = TRUE )  

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_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")

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


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;'>Conference standings through April 20 games.</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 April 20 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 


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


acc_tbl
ACC Baseball Standings Conference standings through April 20 games.

W-L +/- Win %
Home +/-
W-L
Away +/-
W-L

Florida St.

 11-4 +30 0.733
-2
4-2
+32
7-2

Clemson

 13-5 +10 0.722
+10
8-4
0
5-1

Georgia Tech

 14-7 +77 0.667
+44
6-3
+33
8-4

North Carolina St.

 11-6 +10 0.647
+2
6-3
+8
5-3

North Carolina

 13-8 +37 0.619
+26
8-4
+11
5-4

Duke

 12-9 +32 0.571
+20
7-2
+12
5-7

Louisville

 10-8 +36 0.556
+35
7-2
+1
3-6

Virginia

 9-9 +4 0.500
+7
6-6
-3
3-3

Miami FL

 9-9 -9 0.500
-6
6-3
-3
3-6

Wake Forest

 10-11 +11 0.476
+15
7-5
-4
3-6

Virginia Tech

 10-11 +7 0.476
-13
4-8
+20
6-3

Boston College

 9-12 -57 0.429
-12
5-4
-45
4-8

Notre Dame

 7-14 -40 0.333
-32
2-7
-8
5-7

California

 6-14 -19 0.300
-26
1-7
+7
5-7

Stanford

 6-15 -59 0.286
-44
3-9
-15
3-6

Pittsburgh

 5-13 -70 0.278
-14
2-4
-56
3-9
Table by Chris at Bless your chart | data via ncaa.org througn April 20 games