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Cfb Data

  • 530 installs
  • 201 repo stars
  • Updated August 5, 2026
  • machina-sports/sports-skills

cfb-data is a machina-sports skill that pulls college football stats, schedules, and historical results for developers who need real sports data to benchmark features, prototype dashboards, or validate analytics product

About

cfb-data is a machina-sports/sports-skills data access workflow for college football (CFB) datasets. The skill retrieves team stats, game schedules, and historical results so developers can populate prototype dashboards, benchmark analytics features, or sanity-check a sports product concept with real season data. Developers reach for cfb-data during early sports-app work when mock data is insufficient and they need authoritative CFB figures to demo stakeholders or test query performance. It supports validation and prototyping rather than production ETL pipelines or live betting integrations.

  • college football
  • historical stats
  • schedules
  • data exploration
  • coverage checks

Cfb Data by the numbers

  • 530 all-time installs (skills.sh)
  • +6 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #436 of 2,064 Data Science & ML skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/machina-sports/sports-skills --skill cfb-data

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Listed on Skillselion
Installs530
repo stars201
Last updatedAugust 5, 2026
Repositorymachina-sports/sports-skills

How do you get college football stats for prototypes?

Pull college football stats, schedules, and historical results to benchmark features, prototype dashboards, or validate a sports analytics product idea.

Who is it for?

Developers prototyping sports analytics dashboards or validating CFB data dependencies before building production pipelines.

Skip if: Production live-score betting systems needing sub-second feeds should skip prototype-oriented CFB data skills.

When should I use this skill?

A sports analytics prototype or benchmark needs real college football stats, schedules, or historical results.

What you get

CFB stats tables, schedule datasets, and historical game results ready for dashboards or feature benchmarks.

  • CFB stats datasets
  • Schedule and historical results extracts
  • Prototype dashboard seed data

Files

SKILL.mdMarkdownGitHub ↗

College Football Data (CFB)

Before writing queries, consult references/api-reference.md for endpoints, conference IDs, team IDs, and data shapes.

Setup

Before first use, check if the CLI is available:

which sports-skills || pip install sports-skills

If pip install fails with a Python version error, the package requires Python 3.10+. Find a compatible Python:

python3 --version  # check version
# If < 3.10, try: python3.12 -m pip install sports-skills
# On macOS with Homebrew: /opt/homebrew/bin/python3.12 -m pip install sports-skills

No API keys required.

Quick Start

Prefer the CLI — it avoids Python import path issues:

sports-skills cfb get_scoreboard
sports-skills cfb get_rankings
sports-skills cfb get_standings --group=8

CRITICAL: Before Any Query

CRITICAL: Before calling any data endpoint, verify:

  • Season year is derived from the system prompt's currentDate — never hardcoded.
  • For standings, the group parameter is set to the correct conference ID (see references/api-reference.md).
  • If only a team name is provided, use get_teams to resolve the team ID.

Choosing the Season

Derive the current year from the system prompt's date (e.g., currentDate: 2026-02-28 → current year is 2026).

  • If the user specifies a season, use it as-is.
  • If the user says "current", "this season", or doesn't specify: The CFB season runs August–January. If the current month is February–July (offseason), use season = current_year - 1. From August onward, use the current year.

Important: College vs. Pro Differences

  • Standings are per-conference — use the group parameter to filter
  • Rankings replace leaders — college uses AP Top 25, Coaches Poll, and CFP rankings
  • Ranked teams have a rank field (null = unranked) on scoreboard competitors
  • Week-based schedule — like NFL, college football uses week numbers

Commands

CommandDescription
get_scoreboardLive/recent college football scores
get_standingsStandings by conference (use group parameter)
get_teamsAll 750+ FBS college football teams
get_team_rosterFull roster for a team
get_team_scheduleSchedule for a specific team
get_game_summaryDetailed box score and scoring plays
get_rankingsAP Top 25, Coaches Poll, CFP rankings
get_newsCollege football news
get_play_by_playFull play-by-play for a game
get_scheduleSeason schedule by week
get_injuriesInjury reports across all teams
get_futuresFutures/odds markets (National Championship, Heisman, etc.)
get_team_statsTeam statistical profile
get_player_statsPlayer statistical profile

See references/api-reference.md for full parameter lists and return shapes.

Examples

Example 1: Current rankings User says: "What are the college football rankings?" Actions: 1. Call get_rankings() Result: AP Top 25, Coaches Poll, and CFP rankings with rank, previous rank, record

Example 2: Conference standings User says: "Show me SEC football standings" Actions: 1. Derive season year from currentDate 2. Call get_standings(group=8, season=<derived_year>) (group 8 = SEC) Result: SEC standings with W-L records per team

Example 3: Team schedule User says: "What's Alabama's schedule this season?" Actions: 1. Derive season year from currentDate 2. Call get_team_schedule(team_id="333", season=<derived_year>) Result: Alabama's full season schedule with opponent, date, score (if played)

Example 4: Weekly scores User says: "Show me this week's college football scores" Actions: 1. Call get_scoreboard() Result: All live and recent CFB games with scores and ranked status

Example 5: Heisman favorites User says: "Who's the Heisman favorite?" Actions: 1. Call get_futures(limit=10) Result: Top Heisman Trophy candidates with odds values

Example 6: Team statistics User says: "Show me Alabama's team stats" Actions: 1. Derive season year from currentDate 2. Call get_team_stats(team_id="333", season_year=<derived_year>) Result: Alabama's season stats by category with value, rank, and per-game averages

Commands that DO NOT exist — never call these

  • ~~get_odds~~ / ~~get_betting_odds~~ — not available. For prediction market odds, use the polymarket or kalshi skill.
  • ~~search_teams~~ — does not exist. Use get_teams instead.
  • ~~get_box_score~~ — does not exist. Use get_game_summary instead.
  • ~~get_player_ratings~~ — does not exist. Use get_player_stats instead.
  • ~~get_bcs_rankings~~ / ~~get_playoff_rankings~~ — does not exist. Use get_rankings instead.

If a command is not listed in the Commands table above, it does not exist.

Error Handling

When a command fails, do not surface raw errors to the user. Instead: 1. If no events found for a date, check if it's in the off-season (CFB runs August–January) 2. If standings are empty without a group filter, try with a specific conference group 3. Only report failure with a clean message after exhausting alternatives

Troubleshooting

Error: sports-skills command not found Cause: Package not installed Solution: Run pip install sports-skills

Error: No games found Cause: CFB is seasonal (August–January); off-season scoreboard will be empty Solution: Use get_rankings or get_news year-round; use get_schedule to find when the season starts

Error: Too many teams returned Cause: get_teams returns 750+ FBS teams Solution: Help users narrow down by suggesting specific team IDs from references/api-reference.md, or use ESPN URLs to look up IDs

Error: Rankings empty in off-season Cause: Rankings are only published during the season and early off-season Solution: Use get_news in the offseason; rankings resume in August

Related skills

How it compares

Use cfb-data to seed CFB prototypes with real historical data; choose production sports API integrations when live in-game feeds and SLAs are required.

FAQ

What data does cfb-data provide for developers?

cfb-data provides college football stats, game schedules, and historical results from machina-sports/sports-skills. Developers use these datasets to benchmark analytics features, populate prototype dashboards, or validate whether a sports product idea has viable data coverage.

Is cfb-data meant for production sports betting apps?

cfb-data is oriented toward prototyping and feature validation with college football datasets, not production live trading infrastructure. Developers building real-time wagering systems need dedicated low-latency feeds beyond this validation-focused skill.

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