nrlR 📊🏉

A powerful R package to scrape, clean, and analyze publicly available Rugby data

🚀 Overview

nrlR provides a streamlined toolkit for R users to scrape, clean, and analyze rugby data from public sources specifically rugby league. It covers:

With nrlR, you can easily pull:

✅ Match fixtures and results
✅ Ladder standings
✅ Player statistics (runs, tries, tackles, points)
✅ Team statistics (totals, differentials)
✅ Venues, crowds & more

Use it to build dashboards, run predictive models, or simply explore your favourite teams.

💿 Installation

Install the development version directly from GitHub using:

# install.packages("devtools")
devtools::install_github("DanielTomaro13/nrlR")

🔥 Quick Examples

library(nrlR)

📊 Get the NRL ladder for 2025

ladder <- fetch_ladder(season = 2025, league = "nrl", source = "nrl")
head(ladder)
#> # A tibble: 6 × 12
#>   position team        played  wins draws losses points_for points_against
#>      <int> <chr>        <int> <int> <int>  <int>      <int>          <int>
#> 1        1 Storm           8     7     0      1        168             98
#> 2        2 Panthers        8     6     1      1        152            106
#> 3        3 Roosters        8     6     0      2        144            112
#> 4        4 Sharks          8     5     1      2        138            118
#> 5        5 Cowboys         8     5     0      3        142            124
#> 6        6 Eels            8     5     0      3        126            128

🏟️ Fetch fixtures for NRL Round 5, 2025

fixtures <- fetch_fixture(season = 2025, round_number = 5)
print(fixtures)
#> # A tibble: 8 × 10
#>   match_id date       round home_team    away_team    venue      crowd result
#>      <int> <date>     <int> <chr>        <chr>        <chr>      <int> <chr> 
#> 1   401234 2025-04-03     5 Storm        Panthers     AAMI Park  18500 19-16
#> 2   401235 2025-04-04     5 Roosters     Sharks       Allianz    35241 24-10
#> 3   401236 2025-04-05     5 Cowboys      Eels         QCB        22000 28-12
#>   # ... with 5 more rows

📈 Fetch Champion Data team stats

# Get the available competitions first
comps <- fetch_cd_competitions()
print(comps)
#> # A tibble: 15 × 4
#>   comp_id competition_name             season year 
#>     <int> <chr>                         <int> <int>
#> 1   12755 NRL Telstra Premiership       2025  2025
#> 2   12754 NRLW Premiership              2025  2025
#> 3   12753 State of Origin               2025  2025
#>   # ... with 12 more rows

# Then fetch team stats, e.g. comp ID 12755
cd_team_stats <- fetch_team_stats_championdata(comp = 12755, round = 4)
head(cd_team_stats)
#> # A tibble: 6 × 20
#>   team          round tries line_breaks tackle_breaks metres_gained
#>   <chr>         <int> <int>       <int>         <int>         <int>
#> 1 Melbourne Storm   4     4          12            18          1450
#> 2 Penrith Panthers  4     3          10            15          1380
#> 3 Sydney Roosters   4     5          14            20          1520
#>   # ... with 3 more rows and 15 more variables

👟 Fetch Champion Data player stats

# For competition ID 12755 (2025 NRL Telstra Premiership)
cd_player_stats <- fetch_player_stats(
  comp = 111, 
  round = 4, 
  source = "championdata"
)
head(cd_player_stats)
#> # A tibble: 6 × 18
#>   player_name    team     position round tries assists line_breaks
#>   <chr>          <chr>    <chr>    <int> <int>   <int>       <int>
#> 1 Nathan Cleary  Panthers Halfback     4     0       3           2
#> 2 Jahrome Hughes Storm    Halfback     4     1       2           4
#> 3 James Tedesco  Roosters Fullback     4     2       1           6
#>   # ... with 3 more rows and 11 more variables

📊 Data Sources

nrlR aggregates data from multiple reliable sources:

Primary Sources

Supported Competitions

Competition Years Available Source Options
NRL 1998-2025 nrl, rugbyproject, championdata
NRLW 2018-2025 nrl, rugbyproject
State of Origin 1998-2025 nrl, rugbyproject
NSW Cup 2008-2025 nrl
QLD Cup 2008-2025 nrl
Super League 2002-2025 superleague
Championship 2009-2025 superleague
League One 2009-2025 superleague

🛠 Core Functions

Fixtures & Results

# Get fixtures for a specific round
fetch_fixture(season = 2025, round_number = 5, league = "nrl")

# Get all results for a season
fetch_results(season = 2024, league = "nrl", source = "nrl")

# Get specific match details
fetch_match_details(match_id = 401234, source = "nrl")

Ladder & Standings

# Current season ladder
fetch_ladder(season = 2025, league = "nrl")

# Historical ladder positions
fetch_historical_ladder(season = 2020, round = 10, league = "nrl")

Player Statistics

# Individual player stats
fetch_player_stats(
  season = 2024, 
  league = "nrl", 
  round = 1:27,
  player_name = "Nathan Cleary"
)

# Top try scorers
fetch_player_leaders(
  season = 2024, 
  stat_type = "tries", 
  league = "nrl"
)

Team Statistics

# Team performance metrics
fetch_team_stats(season = 2024, league = "nrl", source = "rugbyproject")

# Head-to-head records
fetch_h2h_record(team1 = "Storm", team2 = "Panthers", years = 2020:2024)

Advanced Analytics

# Champion Data advanced stats
fetch_cd_player_advanced(comp = 12755, round = 4)

# Team efficiency metrics
fetch_team_efficiency(season = 2024, league = "nrl")

⚙️ Configuration

Rate Limiting

# Set request delays to be respectful to data sources
set_nrl_config(delay_seconds = 1, max_retries = 3)

Caching

# Enable caching to speed up repeated requests
enable_caching(cache_dir = "~/.nrlR_cache", expire_hours = 24)

Data Quality

# Check data completeness
check_data_completeness(season = 2024, league = "nrl")

# Validate scraped data
validate_nrl_data(data = my_nrl_data)

🧪 Testing & Reliability

nrlR includes comprehensive testing to ensure data quality:

# Run package tests
devtools::test()

# Check specific scraper functionality
test_scraper_health("nrl")
test_scraper_health("rugbyproject")
test_scraper_health("championdata")

Error Handling

The package gracefully handles common issues: - Missing data (returns NA with warnings) - Network timeouts (automatic retries) - Structural changes to source websites (informative error messages) - Invalid inputs (parameter validation)

🤝 Contributing

We welcome contributions! Here’s how you can help:

🐛 Bug Reports

Found an issue? Please create an issue with: - Reproducible example - Expected vs actual behavior - Your R session info (sessionInfo())

💡 Feature Requests

Want a new feature? Open an issue describing: - The use case - Expected functionality - Proposed implementation (if any)

🔧 Development

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Make your changes with tests
  4. Run devtools::check() to ensure quality
  5. Submit a pull request

📊 New Data Sources

Adding a new competition or data source: 1. Create scraper functions following existing patterns 2. Add comprehensive tests 3. Update documentation 4. Ensure data format consistency

🚨 Ethical Usage

Please use nrlR responsibly:

🆘 Getting Help

📄 Citation

If you use nrlR in academic research, please cite:

Tomaro, D. (2025). nrlR: An R package for rugby league data analysis. 
R package version 0.1.1. https://github.com/DanielTomaro13/nrlR

BibTeX:

@Manual{nrlR,
  title = {nrlR: An R package for rugby league data analysis},
  author = {Daniel Tomaro},
  year = {2025},
  note = {R package version 0.1.1},
  url = {https://github.com/DanielTomaro13/nrlR},
}

📝 License

MIT © Daniel Tomaro

This package is not affiliated with the NRL, Rugby League Project, Champion Data, or any official rugby league organization. All data is sourced from publicly available information.

📢 Build your next footy model, dashboard, or data viz with nrlR.

Happy coding! 🏉📊

Last updated: August 2025