itscalledsoccer

Table of Contents

• Background
• Features
• Installation
  • Stable Release
  • Development Version
• Quick Start
• Usage Examples
  • Entities
  • Games
  • Player Statistics
    • Expected Goals (xG)
    • Expected Pass (xPass)
    • Goals Added (g+)
  • Team Statistics
• Advanced Usage
  • Fuzzy Name Matching
• API Reference
• Other Versions
• Contributing
• License

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Background

itscalledsoccer is a Python wrapper around the American Soccer Analysis API, providing programmatic access to advanced soccer analytics across North American leagues.

What you can measure:

• Expected Goals (xG) — Shot quality and finishing efficiency
• Expected Passes (xPass) — Pass difficulty and creative play
• Goals Added (g+) — Total value contribution of players
• Salaries — MLS salary and spend data

The API is free and public — no authentication required.

Supported leagues:

Code	League
mls	Major League Soccer
nwsl	National Women's Soccer League
uslc	USL Championship
usl1	USL League One
usls	USL Super League
nasl	North American Soccer League (historical)
mlsnp	MLS Next Pro

Useful links:

• Full API documentation: american-soccer-analysis.github.io/itscalledsoccer/reference
• Web app: app.americansocceranalysis.com

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Features

• 15 API methods covering players, teams, games, and advanced statistics
• Fuzzy name matching — search by partial names or abbreviations ("LA", "Vela")
• Type hints — full type annotations on all public methods
• Consistent interface — same patterns across all 7 leagues

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Installation

Stable Release

pip install itscalledsoccer

Development Version

git clone https://github.com/American-Soccer-Analysis/itscalledsoccer.git
cd itscalledsoccer
pip install -e ".[dev]"

Requirements: Python 3.10+, requests, pandas, cachecontrol, rapidfuzz

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Quick Start

from itscalledsoccer import AmericanSoccerAnalysis

# Initialize client (no authentication required)
asa = AmericanSoccerAnalysis()

# Get all USLC players
uslc_players = asa.get_players(leagues="uslc")

# Get Expected Goals (xG) data for 2023
xg_data = asa.get_player_xgoals(
    leagues="uslc",
    season_name="2023"
)

For the complete method reference, see Usage Examples below.

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Usage Examples

Entities

Retrieve core soccer entities with optional filtering:

# Same interface for all entity types
uslc_players = asa.get_players(leagues="uslc")
teams = asa.get_teams(leagues=["uslc", "nwsl"])
stadia = asa.get_stadia()
managers = asa.get_managers(leagues="uslc")
referees = asa.get_referees(leagues=["uslc", "mls"])

Available entities: players, teams, stadia, managers, referees

---

Games

# Get games for a specific league and season
uslc_2024_games = asa.get_games(leagues="uslc", seasons="2024")

# Filter by team
lou_games = asa.get_games(leagues="uslc", team_names="Louisville City")

---

Player Statistics

Expected Goals (xG)

Expected Goals measures the quality of shot chances a player creates or faces.

xg = asa.get_player_xgoals(
    leagues="uslc",
    season_name="2025",
    minimum_minutes=900
)

Available filters: minimum_minutes, minimum_shots, minimum_key_passes, shot_pattern, split_by_teams, split_by_seasons, split_by_games, general_position

Expected Pass (xPass)

Expected Pass measures pass difficulty and creative play value.

xpass = asa.get_player_xpass(
    leagues="uslc",
    minimum_minutes=900
)

Goals Added (g+)

Goals Added measures total value contribution across all actions.

gplus = asa.get_player_goals_added(
    leagues="uslc",
    above_replacement=True
)

Note: Goalkeeper statistics use the same interface — get_goalkeeper_xgoals() and get_goalkeeper_goals_added().

---

Team Statistics

# Team Expected Goals
team_xg = asa.get_team_xgoals(
    leagues="uslc",
    split_by_seasons=True
)

# Team Expected Pass
team_xpass = asa.get_team_xpass(
    leagues=["uslc", "nwsl"],
    split_by_seasons=True
)

# Team Salaries (MLS only)
team_salaries = asa.get_team_salaries(
    leagues="mls",
    split_by_teams=True
)

Team-specific filters: home_only, away_only, home_adjusted, even_game_state, zone (1-30), gamestate_trunc (-2 to 2)

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Advanced Usage

Fuzzy Name Matching

Search by partial names, initials, or abbreviations. Returns only the best match:

# Player names
asa.get_players(names="Carlos Vela")

# Team names
asa.get_teams(names="LA")

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API Reference

Complete documentation: american-soccer-analysis.github.io/itscalledsoccer/reference

The reference includes:

• All 15 methods and their parameters
• Complete field descriptions for each endpoint
• Type signatures and defaults

Common questions:

• No API key needed? Correct — the API is public and free.
• Why is my query slow? Large queries may take a moment. Subsequent identical queries are cached.
• What do the metrics mean?
  • xG: Shot quality (0-1 per shot)
  • xPass: Pass completion probability (0-1)
  • g+: Measures a player's total on-ball contribution in attack and defense

For detailed methodology, see American Soccer Analysis.

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Other Versions

• R: itscalledsoccer-r
• JavaScript: itscalledsoccer-js

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Contributing

See CONTRIBUTING.md for code of conduct, development setup, pull request process, and issue reporting.

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License

MIT © itscalledsoccer authors