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Lightweight Python SDK for sports data — football, F1, NFL, NBA, WNBA, NHL, MLB, tennis, CFB, CBB, golf, prediction markets, and news

Project description

sports-skills

https://sports-skills.sh

A lightweight, zero-config Python SDK and CLI for live sports data and prediction markets.

Built natively for AI agents, but works perfectly as a standalone Python library for developers. Wraps publicly available sports data sources and APIs into unified, deterministic commands.

Zero API keys. Zero signup. Just works.


📦 Installation

Install as a global CLI tool (recommended for agents):

uv tool install sports-skills
# or
pip install sports-skills

Base install includes all sports modules.

Install as a Python library:

uv add sports-skills
# or
pip install sports-skills

Optional extras:

pip install "sports-skills[all]"
pip install "sports-skills[dev]"

⚡ What's Included

  • Football (Soccer): ESPN, Understat, FPL, Transfermarkt — 21 commands across 30 leagues
  • US Sports: NFL, NBA, WNBA, NHL, MLB, College Football (CFB), College Basketball (CBB) — live scores, standings, depth charts, injuries, and leaders
  • Tennis: ATP and WTA tournament scores, rankings, calendars, and player profiles
  • Golf: PGA, LPGA, and DP World tour scorecards and leaderboards
  • Racing: Formula 1 (via FastF1) — lap times, telemetry, and race results
  • Prediction Markets: Polymarket & Kalshi live odds and order books
  • News: Multi-sport news aggregators

💻 CLI Usage

The package exposes a sports-skills binary.

List all supported sports:

sports-skills --help

List commands for a specific sport:

sports-skills nfl --help

Execute a command:

sports-skills nfl get_scoreboard --date 2026-02-24
sports-skills football get_current_season --competition_id premier-league
sports-skills polymarket get_markets --query "super bowl"
sports-skills news fetch_items --query "Lando Norris" --limit 5

All CLI output is printed as strict JSON, making it perfect for AI agents (Claude, GPT, Gemini) to parse and reason over.


🐍 Python SDK Usage

You can use the exact same commands directly in your Python code:

from sports_skills import nfl, football, polymarket

# Get live NFL scores
scores = nfl.get_scoreboard(date="2026-02-24")
print(scores["data"]["events"])

# Get Premier League standings
table = football.get_season_standings(season_id="premier-league-2025")
print(table["data"]["standings"])

# Fetch live odds from Polymarket
markets = polymarket.get_markets(query="bitcoin")
print(markets["data"]["markets"])

🏗️ AI Agent Integration

sports-skills is built on the Anthropic Level-3 Agent capability spec. Every command is deterministic and automatically generates its own JSON Schema.

To extract the OpenAI/Anthropic compatible tool schema for any module:

from sports_skills import nfl
import json

# Returns a list of dicts formatted exactly like Anthropic/OpenAI tools
schema = nfl.generate_schema()
print(json.dumps(schema, indent=2))

License

MIT

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