Skip to main content

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sports_skills-0.11.0.tar.gz (226.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sports_skills-0.11.0-py3-none-any.whl (157.3 kB view details)

Uploaded Python 3

File details

Details for the file sports_skills-0.11.0.tar.gz.

File metadata

  • Download URL: sports_skills-0.11.0.tar.gz
  • Upload date:
  • Size: 226.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for sports_skills-0.11.0.tar.gz
Algorithm Hash digest
SHA256 6f596d58773f0afa3cf251b19aac4b11a6657d6787cec1b8eacae159b255281e
MD5 72e4c53816c065724633938b1374028e
BLAKE2b-256 4c23735d1c04013cceca5a2c6c4756547722ab9d704bb89ab6c010bca0809d9b

See more details on using hashes here.

Provenance

The following attestation bundles were made for sports_skills-0.11.0.tar.gz:

Publisher: publish.yml on machina-sports/sports-skills

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sports_skills-0.11.0-py3-none-any.whl.

File metadata

  • Download URL: sports_skills-0.11.0-py3-none-any.whl
  • Upload date:
  • Size: 157.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for sports_skills-0.11.0-py3-none-any.whl
Algorithm Hash digest
SHA256 182daf2a5b82b7a9cfa97af375ba4f92a4c0e25745d79a966dcc0fc81f3477c0
MD5 3c4029bf2bcbe6820faa6ac9ecd51a84
BLAKE2b-256 f36c3b101a99b343dd66643d2d29d3da4c29728ba6b6e2495859c43955b52769

See more details on using hashes here.

Provenance

The following attestation bundles were made for sports_skills-0.11.0-py3-none-any.whl:

Publisher: publish.yml on machina-sports/sports-skills

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page