sdvplotR plots sports team logos, wordmarks, player headshots and team colors across eight leagues — NFL, NBA, WNBA, MLB, NHL, college football, and men’s and women’s college basketball — in ggplot2 plots, gt tables and reactable tables. It is built on ggpath and unifies the approach established by nflplotR, cfbplotR, nbaplotR and mlbplotR behind one sport argument.
Part of the SportsDataverse family of R packages for sports analytics.
Installation
Once on CRAN, install the released version with:
install.packages("sdvplotR")Install the development version of sdvplotR from GitHub with:
# using the pak package (recommended):
if (!requireNamespace("pak", quietly = TRUE)) {
install.packages("pak")
}
pak::pak("sportsdataverse/sdvplotR")
# or from R-universe (binary builds):
install.packages("sdvplotR", repos = c("https://sportsdataverse.r-universe.dev", "https://cloud.r-project.org"))Usage
Every function takes a sport argument ("nfl", "nba", "wnba", "mlb", "nhl", "cfb", "mbb", "wbb"). Team keys are cleaned automatically: full names, alternate abbreviations used by other data providers and historical abbreviations of relocated franchises ("OAK" → "LV", "SEA" → "OKC") all resolve to the same team.
library(sdvplotR)
library(ggplot2)
# NFL team logos in a grid
df <- data.frame(
a = rep(1:8, 4),
b = sort(rep(1:4, 8), decreasing = TRUE),
teams = valid_team_names("nfl")
)
ggplot(df, aes(x = a, y = b)) +
geom_sdv_logos(aes(team = teams), sport = "nfl", width = 0.075) +
theme_void()
# Logos as axis labels + team colours as fill
df2 <- data.frame(
team = c("KC", "BUF", "SF", "DAL"),
score = c(42, 38, 35, 30)
)
ggplot(df2, aes(x = team, y = score)) +
geom_col(aes(fill = team), show.legend = FALSE) +
scale_fill_sdv(sport = "nfl") +
theme_minimal() +
theme(axis.text.x = element_sdv_logo(sport = "nfl", size = 1))
library(gt)
# Logos inside a gt table, in the SportsDataverse table theme
data.frame(team = c("KC", "BUF", "SF"), wins = c(13, 12, 11)) |>
gt() |>
gt_sdv_logos(columns = "team", sport = "nfl") |>
gt_theme_sdv()
# ...or dressed in one team's colors
data.frame(player = c("Patrick Mahomes", "Travis Kelce"), yards = c(4183, 984)) |>
gt() |>
gt_theme_sdv_team(team = "KC", sport = "nfl")
library(reactable)
# Logos inside a reactable table with team-coloured bars
df3 <- data.frame(team = c("KC", "BUF", "SF"), wins = c(13, 12, 11))
reactable(
df3,
columns = list(
team = colDef(cell = reactable_sdv_logos(sport = "nfl"), html = TRUE),
wins = colDef(style = reactable_sdv_team_color_bar(df3, "team", sport = "nfl"))
)
)gt_theme_sdv() (light or style = "dark") and gt_theme_sdv_team() are the SportsDataverse table themes. The gt side also carries the gtUtils toolkit by Andrew Weatherman: 18 table themes (gt_theme_kenpom(), gt_theme_savant(), gt_theme_athletic(), …), color legends, cut lines, significance notation, outlier flags, faceted grids and gt_save_crop() / gt_social_crop() for publishing.
Dark-mode logo variants are available through variant = "dark" in the table helpers, and team_reference() exposes the full reference data (ESPN ids, colors, conference / division) for every team.
Documentation
The sdvplotR documentation website has the full function reference and these articles:
Per-sport (each with companion SportsDataverse package examples): NFL · CFB · NBA · WNBA · MLB · NHL · MBB · WBB
Cookbooks: Getting Started · Social Posting · Leaderboard Dashboards · reactable Integration · Workflows
A printable sdvplotR cheat sheet will join the set covering every SportsDataverse package.
The SportsDataverse
sdvplotR draws the pictures; the companion packages fetch the data.
| Package | Sport / Scope |
|---|---|
| cfbfastR | College football |
| hoopR | Men’s basketball (NBA and NCAA) |
| wehoop | Women’s basketball (WNBA and NCAA) |
| fastRhockey | Hockey (NHL and PWHL) |
| baseballr | Baseball (MLB, MiLB, NCAA) |
| nflfastR · nflreadr | NFL play-by-play and data loaders |
| oddsapiR | Sports betting odds |
| cfbseedR | CFB seeding and playoff simulation |
| sportyR | Playing-surface plots |
| sportsdataverse-R | Umbrella R metapackage |
| sportsdataverse-py · sportsdataverse.js | Python and Node.js |
See the full ecosystem at sportsdataverse.org.
Code of Conduct
Please note that the sdvplotR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.