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Fast, tidy Pro Golf data in R
golfastR provides easy access to professional golf data
from ESPN with functions to get leaderboards and hole-by-hole scores in
tidy data formats ready for analysis. Supports PGA
Tour, LIV Golf, LPGA,
DP World Tour, and Champions Tour.
# Install from CRAN
install.packages("golfastr")
# Or install development version from GitHub
# install.packages("pak")
pak::pak("array-carpenter/golfastr")| Tour | Code | Example |
|---|---|---|
| PGA Tour | "pga" |
load_schedule(2026, tour = "pga") |
| LIV Golf | "liv" |
load_schedule(2026, tour = "liv") |
| LPGA | "lpga" |
load_schedule(2026, tour = "lpga") |
| DP World Tour | "euro" |
load_schedule(2026, tour = "euro") |
| Champions Tour | "champions" |
load_schedule(2026, tour = "champions") |
All functions accept the tour parameter. Default is
"pga".
library(golfastr)
# Get the PGA tournament schedule
schedule <- load_schedule(2026)
# Load a tournament leaderboard
sony <- load_leaderboard(2026, "Sony")
# Get hole-by-hole scoring for top 10
holes <- load_holes(2026, "Sony", top_n = 10)
# LIV Golf works the same way
liv_schedule <- load_schedule(2026, tour = "liv")
adelaide <- load_leaderboard(2026, "Adelaide", tour = "liv")Pre-built PGA Tour strokes gained data ships with the package:
# Get all strokes gained data
sg <- load_strokes_gained()
# Look up a specific player
load_strokes_gained("Scheffler")Returns per-round averages for all six SG categories:
| Field | Description |
|---|---|
| sg_putt | Strokes Gained: Putting |
| sg_arg | Strokes Gained: Around the Green |
| sg_app | Strokes Gained: Approach the Green |
| sg_ott | Strokes Gained: Off the Tee |
| sg_t2g | Strokes Gained: Tee to Green |
| sg_total | Strokes Gained: Total |
# Get schedule for a season
schedule <- load_schedule(2026)
# LIV Golf schedule
liv <- load_schedule(2026, tour = "liv")
# Returns: event_id, tournament_name, start_date, end_date# Load by tournament name (partial match)
masters <- load_leaderboard(2026, "Masters")
phoenix <- load_leaderboard(2026, "Phoenix")
# Load by event ID
lb <- load_leaderboard(2026, "401703504")
# Load all tournaments for the year
all_lb <- load_leaderboard(2026)
# LIV Golf leaderboard
liv_lb <- load_leaderboard(2026, "Adelaide", tour = "liv")# Get scorecards for top finishers
holes <- load_holes(2026, "Sony", top_n = 10)
# Returns: player_id, player_name, round, hole, par, score, score_type# Get players from recent tournaments
players <- load_players(2026)| Field | Description |
|---|---|
| position | Final standing |
| player_id | ESPN athlete ID |
| player_name | Player display name |
| total_score | Total strokes |
| score_to_par | Score vs par (e.g., “-11”) |
| status | Player status |
| Field | Description |
|---|---|
| round | Round number (1-4) |
| hole | Hole number (1-18) |
| par | Par for hole |
| score | Strokes on hole |
| score_type | BIRDIE, PAR, BOGEY, EAGLE, etc. |
Store data locally for faster repeated access:
# Save to RDS (native R format)
save_to_rds(leaderboard_data, file_path = "golf_data.rds")
# Load from RDS
data <- load_from_rds(file_path = "golf_data.rds")
# Or use Parquet for cross-language compatibility (requires arrow)
save_to_parquet(leaderboard_data, file_path = "golf_data.parquet")
data <- load_from_parquet(file_path = "golf_data.parquet")
# Auto-detect format with load_data()
data <- load_data("golf_data.rds")
data <- load_data("golf_data.parquet", tournament = "Masters")# Incrementally fetch all tournaments for a season
build_season(2025, file_path = "pga_2025.rds")
# Check progress
check_season(2025, file_path = "pga_2025.rds")# Player season summary
player_summary("Scheffler", file_path = "golf_data.rds")
# Compare multiple players
compare_players(c("Scheffler", "McIlroy"), file_path = "golf_data.rds")
# Win leaders
win_leaders(file_path = "golf_data.rds")
# Scoring average leaders
scoring_avg_leaders(file_path = "golf_data.rds")Tournament data is sourced from ESPN’s Golf API (https://www.espn.com/golf/). Strokes gained data is sourced from the PGA Tour (https://www.pgatour.com/stats).
MIT
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.