colorr: color palettes for sports teams

Package documentation · Function reference

I built colorr so I could use a team's colours in a figure without looking up each hex code. It includes 276 professional teams across 11 leagues. You can use the colours directly or add them to a ggplot with a colour or fill scale.

Author: Charles Crabtree.

Coverage

Function	League	Teams
`soccer.colors()`	All six soccer leagues below, in one namespace	135
`epl.colors()`	English Premier League (2026-27), plus every club from colorr 1.0.1	29
`mlb.colors()`	Major League Baseball (2026)	30
`nba.colors()`	National Basketball Association (2026-27), plus the Seattle SuperSonics	31
`wnba.colors()`	Women's National Basketball Association (2026)	15
`nfl.colors()`	National Football League (2026)	32
`nhl.colors()`	National Hockey League (2026-27), plus the Arizona Coyotes	33

soccer.colors() covers the Premier League (29), LaLiga (20), Serie A (20), the Bundesliga (18), Ligue 1 (18) and Major League Soccer (30).

Usage

library(colorr)

nba.colors("bucks")
#> Good Land Green Cream City Cream Great Lakes Blue            Black
#>      "#00471B"        "#EEE1C6"        "#0077C0"        "#000000"

soccer.colors("bayern_munich")
#>      Blue       Red
#> "#0066B2" "#DC052D"

Use colorr.leagues() and colorr.teams() to see what's available, and colorr.colors() when the league is itself a variable.

colorr.teams("wnba")
lengths(colorr.teams())
colorr.colors("nhl", "kraken")

ggplot2 scales

Every league has scale_colour_*(), scale_color_*() and scale_fill_*() constructors.

library(ggplot2)

ggplot(mtcars, aes(factor(cyl), mpg, fill = factor(cyl))) +
  geom_boxplot() +
  scale_fill_nba("bucks")

# continuous scales interpolate through the team's colors
ggplot(mtcars, aes(wt, mpg, colour = hp)) +
  geom_point(size = 3) +
  scale_colour_wnba("liberty", discrete = FALSE)

colorr.pal() returns the underlying palette function if you'd rather build the scale yourself.

pal <- colorr.pal("nfl", "lions")
pal(3)
pal(9)   # interpolated past the team's own colors

Older palettes

Every palette function takes legacy = TRUE, which returns the palette that shipped with colorr 1.0.1 rather than the current one, so figures made with older versions still reproduce.

epl.colors("man_united")
#>       Red    Yellow
#> "#DA291C" "#FBE122"

epl.colors("man_united", legacy = TRUE)
#>         Red      Yellow      Orange Dark Orange       Black
#>   "#D81A23"   "#F3CA07"   "#F4A614"   "#EF8221"   "#131313"

Teams that have been renamed since 1.0.1 still answer to their old names: mlb.colors("indians") returns the Guardians palette, and nfl.colors("redskins") returns the Commanders palette.

Installation

Install the CRAN release with:

install.packages("colorr")

This site describes the development version. Install it from GitHub for the expanded league coverage:

if (!require("remotes")) install.packages("remotes")
# remotes::install_github("lobsterbush/colorr")
install.packages("colorr", repos = c('https://lobsterbush.r-universe.dev', 'https://cloud.r-project.org'))

Support or contact

Please use the issue tracker for problems, questions, or feature requests. If you would rather email, you can contact Charles Crabtree.

I welcome pull requests. If a palette is wrong or missing, please include the team's name and a source for its colours.

Tests

tests/testthat checks that every palette is a valid, deduplicated, named hex vector, that every team name from colorr 1.0.1 still resolves, and that the ggplot2 scales build.

devtools::test()

Credit

Some of the code from the functions comes from Karl W. Broman's broman::brocolors.

Team colors come mostly from Team Color Codes. Clubs that site hasn't caught up with, mostly those promoted into a top flight for 2026-27 and the newest expansion franchises, come from BrandColorCode, FootyLogos, encycolorpedia, Wikipedia's Module:Sports color, or the clubs' own brand assets. data-raw/provenance.json records the source for every team, and data-raw/README.md documents the pipeline.

Also, thanks to Hadley Wickham for his excellent book, R Packages.

Documentation and provenance

Browse the documentation and function reference.

Human – AI (editor) 👤✏️🤖

I wrote every initial version myself, without AI. I've used AI only for later updates and code fixes. This is my account of how the package was made.

The label follows The Latent Review’s provenance standard, shared under CC BY 4.0. The software remains MIT licensed.

Build the documentation

Install R and the package dependencies listed in DESCRIPTION, then install pkgdown and here. From the repository root, run:

source(here::here("data-raw", "01_build_site.R"))

The site is built locally in docs/. Publish the rendered contents to the gh-pages branch; GitHub Pages serves that branch.