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A powerful R package to scrape, clean, and analyze publicly available NRL and Rugby League data
nrlR
provides a streamlined toolkit for R users to
scrape, clean, and analyze rugby league data from public sources. It
covers:
With nrlR
, you can easily pull:
β
Match fixtures and results
β
Ladder standings
β
Player statistics (runs, tries, tackles, points)
β
Team statistics (totals, differentials)
β
Venues, crowds & more
Use it to build dashboards, run predictive models, or simply explore your favourite teams.
Install the development version directly from GitHub using:
# install.packages("devtools")
::install_github("DanielTomaro13/nrlR") devtools
library(nrlR)
<- fetch_ladder(season = 2025, league = "nrl", source = "nrl")
ladder head(ladder)
<- fetch_fixture(season = 2025, round_number = 5)
fixtures print(fixtures)
# Fetch player stats for NRL season 2024, rounds 1-3
<- fetch_player_stats(season = 2024, league = "nrl", round = 1:3, source = "rugbyproject")
player_stats head(player_stats)
# Get the available competitions first
<- fetch_cd_competitions()
comps print(comps)
# Then fetch team stats, e.g. comp ID 12755
<- fetch_team_stats_championdata(comp = 12755, round = 4)
cd_team_stats head(cd_team_stats)
# For competition ID 12755 (2025 NRL Telstra Premiership)
<- fetch_player_stats(comp = 111, round = 4, source = "championdata")
cd_player_stats head(cd_player_stats)
β
Clean, tidy tibbles ready for dplyr
or
data.table
workflows
β
Robust scraping with smart handling of missing or partial data
β
Historical & current season support (1998+)
β
Flexible β works with multiple data sources
PRs are welcome!
If you want to improve scrapers, add new competitions, or help write
tests β open an issue or a pull request.
MIT Β© Daniel Tomaro
π’ Build your next footy model, dashboard, or data viz with
nrlR
.
Happy coding!
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.