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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.