Getting Started¶

Installation¶

pip install git+https://github.com/rubenviolinha/pga-tour-unofficial-api.git

Tournament IDs¶

Most functions need a tournament ID in the format {tour_code}{year}{number}:

"R2026027" — 2026 FedEx St. Jude Championship (PGA Tour)
"R2026011" — 2026 THE PLAYERS Championship (PGA Tour)

Use pga_current_tournament() for this week's ID, or pga_schedule() to browse the season:

import pga_tour_api as pga

tid = pga.pga_current_tournament()
schedule = pga.pga_schedule(2026)
print(schedule[["tournament_id", "tournament_name", "display_date", "status"]])

Tracking a Live Tournament¶

Leaderboard¶

tid = pga.pga_current_tournament()
lb = pga.pga_leaderboard(tid)
print(lb[["position", "display_name", "total", "thru"]])

For a quick top-15 snapshot:

pga.pga_current_leaders(tid)

Field¶

pga.pga_field(tid)

Tee Times¶

tt = pga.pga_tee_times(tid)
print(tt[["round_number", "tee_time", "start_tee", "display_name"]])

Tournament Metadata¶

t = pga.pga_tournaments(tid)
print(t["tournament_name"].iloc[0])
print(t["weather_condition"].iloc[0])

Broadcast Schedule¶

pga.pga_coverage(tid)

Odds¶

pga.pga_odds(tid)
pga.pga_odds_markets(tid)
pga.pga_player_odds(tid, "34046")
pga.pga_field_stats(tid)

Player Deep Dive¶

Scorecard¶

sc = pga.pga_scorecard(tid, "34046")
print(sc[["round_number", "hole_number", "par", "score", "status", "round_score"]])

Shot-Level Tracking¶

shots = pga.pga_shot_details(tid, "34046", round=1)
print(shots[["hole_number", "stroke_number", "play_by_play", "distance"]])

Coordinate columns are included for shot visualization (x, y, tourcastX, tourcastY, tourcastZ).

Videos¶

# Highlight clips
pga.pga_videos(player_ids=["34046"], tournament_id="027")

# Shot-by-shot video
pga.pga_tourcast_videos(tid, "34046", round=1)

Note

pga_videos() uses the numeric tournament ID ("027") without the tour code prefix.

Hole-by-hole field scores¶

holes = pga.pga_leaderboard_holes(tid)

Weather and course stats¶

pga.pga_weather(tid)
pga.pga_course_stats(tid)

Tournament overview and past results¶

pga.pga_tournament_overview(tid)
pga.pga_tournament_past_results(tid, year=2025)

Player Profiles¶

Profile Overview¶

profile = pga.pga_player_profile("52955")  # Ludvig Aberg
print(profile["first_name"])   # "Ludvig"
print(profile["country"])      # "Sweden"
print(profile["highlights"])   # DataFrame: wins, FedExCup, world rank
print(profile["overview"])     # DataFrame: career/season/bio/stats

Player Stats (130+ in One Call)¶

stats = pga.pga_player_stats("52955")
print(stats[["stat_id", "title", "rank", "value", "category"]].head(10))

Tournament Results¶

results = pga.pga_player_results("52955")
print(results.groupby("season").size())
print(results[["tournament", "pos", "total", "to_par", "winnings"]])

# One season only
pga.pga_player_results("52955", season=2025)

Career, Bio, and Tournament Status¶

career = pga.pga_player_career("52955")
bio = pga.pga_player_bio("52955")
print(bio["text"][0][:200])  # First bio paragraph

# Is a player in the current tournament?
status = pga.pga_player_tournament_status("34046")

Statistics¶

Pulling Stats¶

sg = pga.pga_stats("02675")  # SG: Total
print(sg[["rank", "player_name", "country"]].head())

# Metadata in attrs
print(sg.attrs["stat_title"])  # "SG: Total"
print(sg.attrs["tour_avg"])    # "0.000"

Finding Stat IDs¶

# Browse by category
putting = pga.STAT_IDS[pga.STAT_IDS["category"] == "Putting"]

# Search by name
driving = pga.STAT_IDS[
    pga.STAT_IDS["stat_name"].str.contains("Driving", case=False)
]

# All categories
print(pga.STAT_IDS["category"].unique())

Common Stat IDs¶

Stat ID	Stat
`02675`	SG: Total
`02674`	SG: Tee-to-Green
`02567`	SG: Off-the-Tee
`02568`	SG: Approach the Green
`02569`	SG: Around-the-Green
`02564`	SG: Putting
`101`	Driving Distance
`102`	Driving Accuracy Percentage
`103`	Greens in Regulation Percentage
`130`	Scrambling
`104`	Putting Average
`120`	Scoring Average (Adjusted)

Historical Comparisons¶

dd_2024 = pga.pga_stats("101", year=2024)
dd_2020 = pga.pga_stats("101", year=2020)

FedExCup and other standings¶

fc = pga.pga_fedex_cup(2026)
print(fc[["display_name", "this_week_rank", "projected_points"]].head())

pga.pga_signature_standings()
pga.pga_priority_rankings()

Player Directory¶

players = pga.pga_players("R")
active = players[players["is_active"] == True]

# Other tours
champions = pga.pga_players("S")
korn_ferry = pga.pga_players("H")
americas = pga.pga_players("Y")

News¶

news = pga.pga_news(limit=10)

# See categories
pga.pga_news_franchises()

# Filter by category
pga.pga_news(franchises=["power-rankings"], limit=5)

Multi-stat and multi-season requests¶

pga_stats accepts a single stat ID or a list, and a single year or a list. The upstream API processes one pair per request; the client batches the calls and combines the results while preserving stat_id and year columns.

# One stat across five seasons
history = pga.pga_stats(
    "02675",
    year=[2022, 2023, 2024, 2025, 2026],
)

# Four strokes-gained categories in one DataFrame
strokes_gained = pga.pga_stats(
    ["02675", "02567", "02568", "02564"],
    year=2026,
)

# The site's "Last 5 events" filter
recent = pga.pga_stats("02675", event_query="LAST_5")

Raw response mode¶

Use PgaApi when you want the upstream dictionaries instead of normalized DataFrames:

from pga_tour_api import PgaApi

api = PgaApi()
tid = api.current_tournament()
raw = api.leaderboard(tid)
print(raw["players"][0]["scoringData"])

Compressed GraphQL payloads are decoded automatically in both interfaces.