College Basketball Data (CBB)
Before writing queries, consult `references/api-reference.md` for endpoints, conference IDs, team IDs, and data shapes.
Best use case
College Basketball Data (CBB) is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Before writing queries, consult `references/api-reference.md` for endpoints, conference IDs, team IDs, and data shapes.
Teams using College Basketball Data (CBB) should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cbb-data/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How College Basketball Data (CBB) Compares
| Feature / Agent | College Basketball Data (CBB) | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Before writing queries, consult `references/api-reference.md` for endpoints, conference IDs, team IDs, and data shapes.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# College Basketball Data (CBB) 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: ```bash 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: ```bash 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: ```bash sports-skills cbb get_scoreboard sports-skills cbb get_rankings sports-skills cbb get_standings --group=23 ``` ## 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 CBB season runs November–April. If the current month is November or December, use `season = current_year + 1`. If January–April, use `season = current_year`. If May–October (offseason), use `season = current_year` (most recently completed season). ## Important: College vs. Pro Differences - **Standings are per-conference** — use the `group` parameter to filter - **Rankings replace leaders** — college uses AP Top 25 and Coaches Poll - **Ranked teams** have a `rank` field (null = unranked) on scoreboard competitors - **360+ D1 teams** — many games per day during the season (50+ during conference play) - **March Madness** — NCAA Tournament runs in March/April with 68 teams ## Commands | Command | Description | |---|---| | `get_scoreboard` | Live/recent college basketball scores | | `get_standings` | Standings by conference (use `group` parameter) | | `get_teams` | All 360+ D1 men's basketball teams | | `get_team_roster` | Full roster for a team | | `get_team_schedule` | Schedule for a specific team | | `get_game_summary` | Detailed box score and player stats | | `get_rankings` | AP Top 25 and Coaches Poll rankings | | `get_news` | College basketball news | | `get_play_by_play` | Full play-by-play for a game | | `get_win_probability` | Win probability chart data | | `get_schedule` | Schedule for a date or season | | `get_futures` | Futures/odds markets (National Championship, etc.) | | `get_team_stats` | Team statistical profile | | `get_player_stats` | Player 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 basketball rankings?" Actions: 1. Call `get_rankings()` Result: AP Top 25 and Coaches Poll with rank, previous rank, record, and points Example 2: Conference standings User says: "Show me SEC basketball standings" Actions: 1. Derive season year from `currentDate` 2. Call `get_standings(group=23, season=<derived_year>)` (group 23 = SEC) Result: SEC standings with W-L records per team Example 3: Today's scores User says: "What are today's college basketball scores?" Actions: 1. Call `get_scoreboard()` Result: All live and recent CBB games with scores and ranked status Example 4: Team roster User says: "Show me Duke's roster" Actions: 1. Call `get_team_roster(team_id="150")` Result: Full Duke roster with name, position, jersey number Example 5: March Madness futures User says: "Who's favored to win March Madness?" Actions: 1. Call `get_futures(limit=10)` Result: Top National Championship contenders with odds values Example 6: Team statistics User says: "Show me Duke's team stats" Actions: 1. Derive season year from `currentDate` 2. Call `get_team_stats(team_id="150", season_year=<derived_year>)` Result: Duke'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_ap_poll`~~ — 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, check if it's the off-season (CBB runs November–April) 2. If standings are empty without a group filter, try a specific conference 3. During March Madness, the scoreboard will have tournament games 4. 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 on scoreboard Cause: CBB is seasonal (November–April); off-season scoreboard will be empty Solution: Use `get_rankings` or `get_news` year-round; check `get_schedule` for when the season resumes Error: Too many games returned — hard to filter Cause: During the season, 50+ games per day are scheduled Solution: Use `--group` to filter by conference, or `--limit` to cap results Error: Rankings empty Cause: Rankings are published weekly during the season (November–March) only Solution: Use `get_news` in the offseason; rankings resume in November
Related Skills
College Football Data (CFB)
Before writing queries, consult `references/api-reference.md` for endpoints, conference IDs, team IDs, and data shapes.
validating-database-integrity
Process use when you need to ensure database integrity through comprehensive data validation. This skill validates data types, ranges, formats, referential integrity, and business rules. Trigger with phrases like "validate database data", "implement data validation rules", "enforce data integrity constraints", or "validate data formats".
forecasting-time-series-data
This skill enables Claude to forecast future values based on historical time series data. It analyzes time-dependent data to identify trends, seasonality, and other patterns. Use this skill when the user asks to predict future values of a time series, analyze trends in data over time, or requires insights into time-dependent data. Trigger terms include "forecast," "predict," "time series analysis," "future values," and requests involving temporal data.
generating-test-data
This skill enables Claude to generate realistic test data for software development. It uses the test-data-generator plugin to create users, products, orders, and custom schemas for comprehensive testing. Use this skill when you need to populate databases, simulate user behavior, or create fixtures for automated tests. Trigger phrases include "generate test data", "create fake users", "populate database", "generate product data", "create test orders", or "generate data based on schema". This skill is especially useful for populating testing environments or creating sample data for demonstrations.
test-data-builder
Test Data Builder - Auto-activating skill for Test Automation. Triggers on: test data builder, test data builder Part of the Test Automation skill category.
splitting-datasets
Process split datasets into training, validation, and testing sets for ML model development. Use when requesting "split dataset", "train-test split", or "data partitioning". Trigger with relevant phrases based on skill purpose.
scanning-database-security
Process use when you need to work with security and compliance. This skill provides security scanning and vulnerability detection with comprehensive guidance and automation. Trigger with phrases like "scan for vulnerabilities", "implement security controls", or "audit security".
preprocessing-data-with-automated-pipelines
Process automate data cleaning, transformation, and validation for ML tasks. Use when requesting "preprocess data", "clean data", "ETL pipeline", or "data transformation". Trigger with relevant phrases based on skill purpose.
optimizing-database-connection-pooling
Process use when you need to work with connection management. This skill provides connection pooling and management with comprehensive guidance and automation. Trigger with phrases like "manage connections", "configure pooling", or "optimize connection usage".
modeling-nosql-data
This skill enables Claude to design NoSQL data models. It activates when the user requests assistance with NoSQL database design, including schema creation, data modeling for MongoDB or DynamoDB, or defining document structures. Use this skill when the user mentions "NoSQL data model", "design MongoDB schema", "create DynamoDB table", or similar phrases related to NoSQL database architecture. It assists in understanding NoSQL modeling principles like embedding vs. referencing, access pattern optimization, and sharding key selection.
monitoring-database-transactions
Monitor use when you need to work with monitoring and observability. This skill provides health monitoring and alerting with comprehensive guidance and automation. Trigger with phrases like "monitor system health", "set up alerts", or "track metrics".
monitoring-database-health
Monitor use when you need to work with monitoring and observability. This skill provides health monitoring and alerting with comprehensive guidance and automation. Trigger with phrases like "monitor system health", "set up alerts", or "track metrics".