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CFB Conference Table

Saiem Gilani
@saiemgilani @saiemgilani

Source: vignettes/recipe-cfb-conference-table.Rmd
recipe-cfb-conference-table.Rmd
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The brief: the season-review newsletter needs the final Big Ten standings as an image: 1600 px wide for the email, plus a square cut for social. Indiana went 16-0 and won the national title, so the table should make that obvious. The records are built from the CollegeFootballData.com schedule through cfbfastR, and the table is gt with sdvplotR’s logo, theme and export helpers.

library(sdvplotR)
library(gt)
library(dplyr, warn.conflicts = FALSE)

season <- 2025
conference <- "Big Ten"
out_dir <- tempfile("sdvplotR-recipe-") # where the exports go; use your own folder
dir.create(out_dir)

1. Get the data

The schedule has one row per game. Stacking the home and away sides gives one row per team per game, which makes every record a group_by(). The margins are kept in date order as one comma-separated string per team, the form gt’s in-cell charts read, for a small chart later. summarise() sees its own earlier results, so the margins and the last game’s score are taken before pf and pa become season averages.

schedule <- cfbfastR::load_cfb_schedules(season) |>
  filter(completed)

side <- function(me, opp) {
  transmute(
    schedule,
    start_date, season_type, conference_game, notes,
    team = .data[[paste0(me, "_team")]],
    conference = .data[[paste0(me, "_conference")]],
    opponent = .data[[paste0(opp, "_team")]],
    pf = .data[[paste0(me, "_points")]],
    pa = .data[[paste0(opp, "_points")]]
  )
}

games <- bind_rows(side("home", "away"), side("away", "home")) |>
  filter(conference == !!conference) |>
  arrange(start_date) |>
  mutate(won = pf > pa)

standings <- games |>
  group_by(team) |>
  summarise(
    margins = paste(pf - pa, collapse = ","),
    # the last game: where a bowl or the playoff shows up
    last_score = paste0(max(last(pf), last(pa)), "-", min(last(pf), last(pa))),
    last_type = last(season_type),
    last_won = last(won),
    last_opponent = last(opponent),
    last_event = last(notes),
    conf_w = sum(won & conference_game),
    conf_l = sum(!won & conference_game),
    w = sum(won),
    l = sum(!won),
    pf = mean(pf),
    pa = mean(pa)
  ) |>
  arrange(desc(conf_w), desc(w), team) # team breaks ties, so the order is the same every run
nrow(standings)
#> [1] 18
standings |>
  select(team, conf_w, conf_l, w, l, last_score, last_opponent, last_event) |>
  head(5)
#> # A tibble: 5 × 8
#>   team       conf_w conf_l     w     l last_score last_opponent last_event      
#>   <chr>       <int>  <int> <int> <int> <chr>      <chr>         <chr>           
#> 1 Indiana         9      0    16     0 27-21      Miami         College Footbal…
#> 2 Ohio State      9      0    12     2 24-14      Miami         College Footbal…
#> 3 Oregon          8      1    13     2 56-22      Indiana       College Footbal…
#> 4 Michigan        7      2     9     4 41-27      Texas         Cheez-It Citrus…
#> 5 USC             7      2     9     4 30-27      TCU           Valero Alamo Bo…

2. The first draft

Hand the frame to gt as it is.

gt(standings)
team margins last_score last_type last_won last_opponent last_event conf_w conf_l w l pf pa
Indiana 13,47,73,53,5,10,25,50,45,3,24,53,3,35,34,6 27-21 postseason TRUE Miami College Football Playoff National Championship Presented by AT&T 9 0 16 0 41.62500 11.687500
Ohio State 7,70,28,18,39,18,34,24,24,38,33,18,-3,-10 24-14 postseason FALSE Miami College Football Playoff Quarterfinal at the Goodyear Cotton Bowl Classic 9 0 12 2 33.42857 9.285714
Oregon 46,66,20,34,6,-10,46,14,2,29,15,12,17,23,-34 56-22 postseason FALSE Indiana College Football Playoff Semifinal at the Chick-fil-A Peach Bowl 8 1 13 2 36.93333 17.866667
Michigan 17,-11,60,3,14,-18,17,11,5,2,25,-18,-14 41-27 postseason FALSE Texas Cheez-It Citrus Bowl 7 2 9 4 27.53846 20.384615
USC 60,39,16,14,-2,18,-10,4,21,5,-15,19,-3 30-27 postseason FALSE TCU Valero Alamo Bowl 7 2 9 4 35.76923 23.000000
Iowa 27,-3,40,10,-5,37,1,38,-2,-5,3,24,7 34-27 postseason TRUE Vanderbilt ReliaQuest Bowl 6 3 9 4 29.30769 16.076923
Illinois 49,26,38,-53,2,16,-18,-17,22,18,-17,7,2 30-28 postseason TRUE Tennessee Liberty Mutual Music City Bowl 5 4 9 4 29.38462 23.615385
Washington 17,60,35,-18,4,19,-17,17,-3,36,34,-12,28 38-10 postseason TRUE Boise State Bucked Up LA Bowl 5 4 9 4 34.07692 18.692308
Minnesota 13,66,-13,3,-39,7,18,-38,3,-29,-3,10,3 20-17 postseason TRUE New Mexico Rate Bowl 5 4 8 5 23.00000 22.923077
Nebraska 3,68,52,-3,11,3,-18,7,-4,7,-27,-24,-22 44-22 postseason FALSE Utah SRS Distribution Las Vegas Bowl 4 5 7 6 28.69231 24.615385
Northwestern -20,35,-20,3,35,1,19,-7,-21,-2,3,-7,27 34-7 postseason TRUE Central Michigan GameAbove Sports Bowl 4 5 7 6 23.38462 19.846154
Penn State 35,34,46,-6,-5,-1,-1,-24,-3,18,27,4,12 22-10 postseason TRUE Clemson Bad Boy Mowers Pinstripe Bowl 3 6 7 6 31.00000 20.538462
UCLA -33,-7,-25,-3,5,25,3,-50,-7,-38,-34,-19 29-10 regular FALSE USC NA 3 6 3 9 18.16667 33.416667
Rutgers 3,28,50,-10,-3,-19,-46,3,-22,15,-33,-4 40-36 regular FALSE Penn State NA 2 7 5 7 28.66667 31.833333
Wisconsin 17,32,-24,-17,-14,-37,-34,-14,3,-24,17,-10 17-7 regular FALSE Minnesota NA 2 7 4 8 12.83333 21.583333
Maryland 32,11,27,17,-4,-3,-3,-45,-15,-18,-25,-10 38-28 regular FALSE Michigan State NA 1 8 4 8 23.50000 26.500000
Michigan State 17,2,17,-14,-11,-25,-25,-11,-3,-18,-3,10 38-28 regular TRUE Maryland NA 1 8 4 8 24.58333 29.916667
Purdue 31,17,-16,-26,-16,-7,-19,-3,-5,-24,-36,-53 56-3 regular FALSE Indiana NA 0 9 2 10 18.75000 31.833333

Every number is there, and none of it is readable: margins printed as text, a dozen decimals, and column names only the analyst knows.

3. Shape it for a reader

Records read as “9-0”, not two columns. Each team’s last game becomes one short line (“W 27-21 vs Miami, CFP National Championship”), which is where the national title shows up. Columns get real labels, conference and overall records sit under spanners, and the averages get one decimal.

event <- function(x) {
  x |>
    sub(" Presented by.*", "", x = _) |>
    sub(" at the .*", "", x = _) |>
    sub("College Football Playoff", "CFP", x = _)
}

table <- standings |>
  mutate(
    conf = paste0(conf_w, "-", conf_l),
    overall = paste0(w, "-", l),
    postseason = if_else(
      last_type == "postseason",
      paste0(if_else(last_won, "W ", "L "), last_score, " vs ", last_opponent, ", ", event(last_event)),
      ""
    )
  ) |>
  select(team, conf, overall, pf, pa, margins, postseason)

draft <- gt(table) |>
  cols_hide(margins) |>
  cols_label(
    team = "Team", conf = "W-L", overall = "W-L",
    pf = "Pts/G", pa = "Opp/G", postseason = "Postseason"
  ) |>
  tab_spanner("Conference", conf) |>
  tab_spanner("Overall", c(overall, pf, pa)) |>
  fmt_number(c(pf, pa), decimals = 1) |>
  cols_align("center", c(conf, overall, pf, pa))
draft
Team
Conference
Overall
 Postseason
W-L W-L Pts/G Opp/G
Indiana 9-0 16-0 41.6 11.7 W 27-21 vs Miami, CFP National Championship
Ohio State 9-0 12-2 33.4 9.3 L 24-14 vs Miami, CFP Quarterfinal
Oregon 8-1 13-2 36.9 17.9 L 56-22 vs Indiana, CFP Semifinal
Michigan 7-2 9-4 27.5 20.4 L 41-27 vs Texas, Cheez-It Citrus Bowl
USC 7-2 9-4 35.8 23.0 L 30-27 vs TCU, Valero Alamo Bowl
Iowa 6-3 9-4 29.3 16.1 W 34-27 vs Vanderbilt, ReliaQuest Bowl
Illinois 5-4 9-4 29.4 23.6 W 30-28 vs Tennessee, Liberty Mutual Music City Bowl
Washington 5-4 9-4 34.1 18.7 W 38-10 vs Boise State, Bucked Up LA Bowl
Minnesota 5-4 8-5 23.0 22.9 W 20-17 vs New Mexico, Rate Bowl
Nebraska 4-5 7-6 28.7 24.6 L 44-22 vs Utah, SRS Distribution Las Vegas Bowl
Northwestern 4-5 7-6 23.4 19.8 W 34-7 vs Central Michigan, GameAbove Sports Bowl
Penn State 3-6 7-6 31.0 20.5 W 22-10 vs Clemson, Bad Boy Mowers Pinstripe Bowl
UCLA 3-6 3-9 18.2 33.4
Rutgers 2-7 5-7 28.7 31.8
Wisconsin 2-7 4-8 12.8 21.6
Maryland 1-8 4-8 23.5 26.5
Michigan State 1-8 4-8 24.6 29.9
Purdue 0-9 2-10 18.8 31.8

4. Logos and the season at a glance

gt_sdv_logos() turns the team names into logos, and include_name = TRUE keeps the name beside each one, so the column still reads as text. The margins string becomes a nanoplot, gt’s in-cell bar chart: one bar per game, green for a win and red for a loss, so a perfect season is a solid green row.

margin_bars <- nanoplot_options(
  data_bar_fill_color = "#2e8540",
  data_bar_negative_fill_color = "#c0392b",
  data_bar_stroke_color = "transparent",
  data_bar_negative_stroke_color = "transparent",
  show_data_points = FALSE,
  show_reference_line = FALSE,
  show_vertical_guides = FALSE,
  show_y_axis_guide = FALSE,
  interactive_data_values = TRUE # values on hover only, so the saved image stays clean
)

with_marks <- draft |>
  gt_sdv_logos(team, league = "cfb", height = 24, include_name = TRUE) |>
  cols_nanoplot(
    columns = margins, plot_type = "bar", autoscale = TRUE,
    new_col_name = "bars", new_col_label = "Game by game",
    after = "pa", options = margin_bars
  ) |>
  tab_spanner("Margin", bars)
with_marks
Team
Conference
Overall
Margin
 Postseason
W-L W-L Pts/G Opp/G Game by game
Indiana 9-0 16-0 41.6 11.7
W 27-21 vs Miami, CFP National Championship
Ohio State 9-0 12-2 33.4 9.3
L 24-14 vs Miami, CFP Quarterfinal
Oregon 8-1 13-2 36.9 17.9
L 56-22 vs Indiana, CFP Semifinal
Michigan 7-2 9-4 27.5 20.4
L 41-27 vs Texas, Cheez-It Citrus Bowl
USC 7-2 9-4 35.8 23.0
L 30-27 vs TCU, Valero Alamo Bowl
Iowa 6-3 9-4 29.3 16.1
W 34-27 vs Vanderbilt, ReliaQuest Bowl
Illinois 5-4 9-4 29.4 23.6
W 30-28 vs Tennessee, Liberty Mutual Music City Bowl
Washington 5-4 9-4 34.1 18.7
W 38-10 vs Boise State, Bucked Up LA Bowl
Minnesota 5-4 8-5 23.0 22.9
W 20-17 vs New Mexico, Rate Bowl
Nebraska 4-5 7-6 28.7 24.6
L 44-22 vs Utah, SRS Distribution Las Vegas Bowl
Northwestern 4-5 7-6 23.4 19.8
W 34-7 vs Central Michigan, GameAbove Sports Bowl
Penn State 3-6 7-6 31.0 20.5
W 22-10 vs Clemson, Bad Boy Mowers Pinstripe Bowl
UCLA 3-6 3-9 18.2 33.4
Rutgers 2-7 5-7 28.7 31.8
Wisconsin 2-7 4-8 12.8 21.6
Maryland 1-8 4-8 23.5 26.5
Michigan State 1-8 4-8 24.6 29.9
Purdue 0-9 2-10 18.8 31.8

5. Theme it and say what it means

A theme does the typography and rules in one call: gt_theme_sdv(), the SportsDataverse house style. The title says the news, the subtitle how to read the table, and the source note credits the data. The champion’s row gets a soft fill in its own color from sdv_team_colors(), and a footnote owns up to the ordering: teams tied on conference record are listed by overall record, which is not the conference’s tiebreaker.

champ <- standings[1, ]
stopifnot(champ$l == 0, champ$last_won, grepl("National Championship", champ$last_event))
fill <- paste0(sdv_team_colors("cfb", champ$team), "1F") # the primary color at 12% opacity

final <- with_marks |>
  tab_header(
    title = sprintf(
      "%s ran the table: %d-0 in the %s, %d-0 overall and national champion",
      champ$team, champ$conf_w, conference, champ$w
    ),
    subtitle = html(paste0(
      "Final ", season, " ", conference, " standings. Bars are each game's margin, in date order: ",
      "<span style='color:#2e8540'><b>wins</b></span> and ",
      "<span style='color:#c0392b'><b>losses</b></span>."
    ))
  ) |>
  tab_source_note("Data: CollegeFootballData.com via cfbfastR  |  Table: sdvplotR + gt") |>
  tab_footnote(
    "Teams tied on conference record are listed by overall record, then by name.",
    locations = cells_column_labels(columns = conf)
  ) |>
  tab_style(style = cell_fill(color = fill), locations = cells_body(rows = team == champ$team)) |>
  tab_style(
    style = cell_text(weight = "bold"),
    locations = cells_body(columns = team, rows = team == champ$team)
  ) |>
  gt_theme_sdv()
final
Indiana ran the table: 9-0 in the Big Ten, 16-0 overall and national champion
Final 2025 Big Ten standings. Bars are each game's margin, in date order: wins and losses.
Team
Conference
Overall
Margin
 Postseason
W-L1 W-L Pts/G Opp/G Game by game
Indiana 9-0 16-0 41.6 11.7
W 27-21 vs Miami, CFP National Championship
Ohio State 9-0 12-2 33.4 9.3
L 24-14 vs Miami, CFP Quarterfinal
Oregon 8-1 13-2 36.9 17.9
L 56-22 vs Indiana, CFP Semifinal
Michigan 7-2 9-4 27.5 20.4
L 41-27 vs Texas, Cheez-It Citrus Bowl
USC 7-2 9-4 35.8 23.0
L 30-27 vs TCU, Valero Alamo Bowl
Iowa 6-3 9-4 29.3 16.1
W 34-27 vs Vanderbilt, ReliaQuest Bowl
Illinois 5-4 9-4 29.4 23.6
W 30-28 vs Tennessee, Liberty Mutual Music City Bowl
Washington 5-4 9-4 34.1 18.7
W 38-10 vs Boise State, Bucked Up LA Bowl
Minnesota 5-4 8-5 23.0 22.9
W 20-17 vs New Mexico, Rate Bowl
Nebraska 4-5 7-6 28.7 24.6
L 44-22 vs Utah, SRS Distribution Las Vegas Bowl
Northwestern 4-5 7-6 23.4 19.8
W 34-7 vs Central Michigan, GameAbove Sports Bowl
Penn State 3-6 7-6 31.0 20.5
W 22-10 vs Clemson, Bad Boy Mowers Pinstripe Bowl
UCLA 3-6 3-9 18.2 33.4
Rutgers 2-7 5-7 28.7 31.8
Wisconsin 2-7 4-8 12.8 21.6
Maryland 1-8 4-8 23.5 26.5
Michigan State 1-8 4-8 24.6 29.9
Purdue 0-9 2-10 18.8 31.8
1 Teams tied on conference record are listed by overall record, then by name.
Data: CollegeFootballData.com via cfbfastR | Table: sdvplotR + gt

6. Export for the newsletter and for social

gt_save_crop() renders the table in headless Chrome, trims it with an even border and, with width, scales it to the email’s 1600 px. gt_social_crop() centers the same table on a square canvas for Instagram, never cropping it: it pads whichever way the table needs, side padding for a tall table and room above and below for a wide one like this.

newsletter <- gt_save_crop(final, file.path(out_dir, "big_ten_1600.png"), width = 1600)
square <- gt_social_crop(
  final, file.path(out_dir, "big_ten_1080x1080.png"),
  aspect_ratio = "1:1", width = 1080
)
magick::image_info(magick::image_read(c(newsletter, square)))[c("width", "height")]
#> # A tibble: 2 × 2
#>   width height
#>   <int>  <int>
#> 1  1600   1456
#> 2  1080   1080
magick::image_read(newsletter)

The finished Big Ten standings table exported 1600 pixels wide for the newsletter.

The square cut keeps the whole table and pads above and below it:

magick::image_read(square)

The same table centered on a 1080 by 1080 pixel square for Instagram.

Our Authors

Citation

To cite the sdvplotR R package in publications, use:

BibTeX Citation

@misc{gilani_carl_lee_kay_weatherman_sdvplotR,
  author = {Gilani, Saiem and Carl, Sebastian and Lee, Jared and Kay, Camden and Weatherman, Andrew},
  title = {sdvplotR: The SportsDataverse's R Package for Multi-League Sports Plotting.},
  url = {https://sdvplotR.sportsdataverse.org},
  year = {2026}
}