College Football Data
CollegeFootballData.com provides comprehensive college football data, including game scores, statistics, and recruiting information, accessible via a RESTful API.
Verdict
Common use cases
- Compare offensive efficiency across conference rivals
- Track team talent rankings season over season
- Pull betting line movement before kickoff
- Trace conference realignment for historical context
- Build predictive models using Elo and advanced metrics
Integration
- Vendor
- College Football Data
- Category
- developer-tools
- Auth
- API_KEY
- Tools
- 41
- Composio slug
college_football_data
Tools
- Advanced Box Score
Tool to retrieve advanced box score metrics for a single college football game. Use after selecting a specific game to access team- and player-level advanced analytics.
- Advanced Game Stats
Tool to retrieve advanced team metrics at the game level. Use when detailed offensive and defensive metrics (success rates, explosiveness, havoc) are needed.
- Advanced Season Stats by Team
Tool to retrieve advanced season metrics aggregated by team and season. Use after selecting season and team filters.
- Betting Lines
Tool to fetch betting lines and totals by game and provider. Use when you need current or historical betting line data filtered by specific criteria.
- Composite Team Talent
Tool to fetch composite team talent rankings by season. Use when you need 247Sports team talent composites for specified seasons.
- Conference Memberships History
Tool to retrieve historical conference memberships for teams, including years active and division. Use when you need to trace a team's conference history over time.
- Divisions by Conference
Tool to list FBS/FCS conference divisions with active years and metadata. Use after specifying an optional season year to filter active divisions.
- Elo Ratings
Tool to retrieve Elo ratings for college football teams. Use when you need historical Elo ratings by season or for a specific team.
- Get Drive Data
Tool to retrieve drive-level data and results. Use when analyzing detailed drives for specified games after filtering by season, team, or week.
- Get Game Media
Tool to retrieve game media information and broadcast schedules (TV, radio, web, etc.). Use after selecting season year and optional filters (week, team, conference). Example: "Get week 3 TV and radio outlets for 2025 SEC games."
- Get Games and Results
Tool to retrieve games and results for a given season/week/team. Use when you need game schedules or outcomes filtered by specific criteria.
- Get Player Game Stats
Tool to fetch player statistics at the game level. Use when you need detailed stats for players in games after filtering parameters.
- Get Team Game Stats
Tool to fetch team statistics at the game level. Use when you need detailed box score stats for games after filtering parameters.
- Get Team Roster
Tool to fetch roster for a given team and season. Use when you need a team's roster for a specific year.
- List Coaches and History
Tool to get coaching records and history. Use when you need coaches’ season-by-season data with optional filters.
- List Conferences
Tool to list all college football conferences. Use after authenticating to retrieve the up-to-date list of conferences.
- List FBS Teams
Tool to list FBS teams for a given season. Use after selecting the season year to retrieve all FBS teams.
- List FCS Teams
Tool to list FCS teams for a given season and conference. Use when you need a list of FCS programs filtered by season year and conference.
- List Teams
Tool to list college football teams. Use when you need a list of teams filtered by season year and/or conference.
- List Venues and Stadiums
Tool to list college football venues with metadata (name, capacity, location, etc.). Use when you need detailed venue information for a specific season.
- NFL Draft Picks
Tool to list NFL Draft picks. Use when you need draft pick data by year, round, team, player, etc.
- NFL Draft Positions
Tool to list NFL draft positions. Use when you need a standardized set of NFL positions for draft analysis.
- NFL Draft Teams
Tool to list NFL teams used in draft endpoints. Use when preparing to retrieve NFL draft data by team.
- Play-by-Play Data
Tool to fetch play-by-play data for college football games. Use when you need detailed play logs filtered by season, week, team, or game.
- Player PPA by Game
Tool to retrieve player-level PPA/EPA broken down by game. Use when you need per-game PPA/EPA metrics for players filtered by season, week, or team.
- Play Stats Player
Tool to fetch player-level stats tied to individual plays. Use when you need detailed play-by-play player statistics filtered by season, week, game, or athlete.
- Play Stat Types
Tool to fetch all play-level stat type definitions. Use when you need a catalog of available play stat types for filtering or referencing.
- PPA Player By Season
Tool to fetch player-level PPA/EPA aggregated by season. Use when you need seasonal PPA metrics for specific players or groups after applying filters.
- PPA Team By Game
Tool to retrieve team Predicted Points Added (PPA) by game. Use when you need team-level PPA metrics for games after filtering by season, week, team, or date.
- Predict Expected Points (EP)
Tool to get expected points by down, distance, and field position. Use after selecting down (1–4) and distance to explore expected outcomes across the field.
- Rankings Polls
Tool to retrieve weekly human/computer poll rankings. Use after specifying season year and optional week.
- Recruiting Group Dictionary
Tool to list recruiting position group aggregations. Use when you need aggregated team recruiting ratings by position group (e.g., QB, RB, WR).
- Recruiting Transfer Portal
Tool to retrieve transfer portal entries for a given season. Use when you need details of players entering the transfer portal, including from/to teams, position, and recruiting ratings.
- Returning Production by Team
Tool to fetch Bill Connelly–style returning production splits by team and season. Use when evaluating returning offense, defense, and overall production for teams in a given season.
- Season Stats Player
Tool to fetch basic season stats aggregated by player and season. Use when you need overall player performance summaries for a given season.
- Season Team Stats
Tool to get basic season stats aggregated by team and season. Use when you need a summary of team-level statistics for a particular season.
- Season Types Dictionary
Tool to list season types. Uses the season calendar endpoint to extract valid seasonType values.
- SP+ Ratings
Tool to retrieve SP+ team ratings. Use when you need historical SP+ ratings for a specific season after confirming the season year.
- SRS Ratings
Tool to retrieve Simple Rating System (SRS) team ratings. Use when you need historical SRS values for a season, optionally filtering by team or conference.
- Team Matchup History
Tool to retrieve head-to-head team matchup records over a date range. Use after selecting two FBS teams to compare their matchup history.
- Team season records
Tool to fetch team season records by year with optional filters. Use after specifying the year and any optional filters (conference, team, division, seasonType, limit, offset) to retrieve records.
Setup
Setup guide
- 11. Open your Switchy workspace and navigate to Settings > Integrations > MCP Servers. 2. Click Add Server and select College Football Data from the catalog. 3. Visit collegefootballdata.com, sign up for a free account, and generate an API key from your dashboard. 4. Paste the key into the API Key field in Switchy and click Connect. 5. Return to any Space and type '@College Football Data' to confirm the connection—autocomplete should surface the MCP. 6. Test it by asking '@College Football Data show me advanced stats for Ohio State vs Michigan 2023' and verify you receive box score or team metrics in the response. 7. If the connection fails, check that your API key is active and hasn't hit its rate limit.
What teammates see: by default, memories from College Football Data are scoped to the Space (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Spaces have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
Game-Level Explosiveness
@College Football Data pull advanced game stats for Georgia vs Alabama in the 2023 SEC Championship, focusing on explosiveness and success rate for both offenses.Open in a Space →
Season Talent Composite
@College Football Data show me composite team talent rankings for all Big Ten teams in 2024, sorted by overall talent score.Open in a Space →
Historical Elo Trends
@College Football Data retrieve Elo ratings for Michigan from 2018 through 2023 and highlight any season where the rating jumped more than 50 points.Open in a Space →
Betting Line Snapshot
@College Football Data fetch betting lines for the upcoming Ohio State vs Penn State game from all available providers, including opening and current spreads.Open in a Space →
Conference Membership Timeline
@College Football Data list the conference memberships for Texas from 1990 to present, including years active and division assignments.Open in a Space →
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@collegefootballdata show me advanced season stats for Georgia's offense in 2023, focusing on success rate and explosiveness
Based on 2023 season data, Georgia's offense posted a 48.2% success rate (plays gaining 50%+ of needed yards) and an explosiveness rating of 16.8% (plays gaining 16+ yards for passing, 12+ for rushing). Their stuff rate on defense was 19.1%, meaning they stopped nearly 1 in 5 opponent plays at or behind the line. These metrics placed them in the top 5 nationally for both offensive efficiency and defensive disruption. This example illustrates aggregated season-level analytics; actual values depend on the season queried.
This example highlights the MCP's strength in surfacing advanced metrics beyond basic box scores—success rates and explosiveness are key indicators used by analysts but not typically shown in standard stats. Requires an API key with access to premium endpoints; some advanced metrics may be limited to FBS teams or recent seasons only.
@collegefootballdata pull betting lines for the Alabama vs Texas game on September 9, 2023, and show me how the spread moved across providers
For Alabama vs Texas (Week 2, 2023), opening lines varied by sportsbook: Consensus opened Alabama -7.5, closing at -6.5 by kickoff. DraftKings moved from -7 to -6, while FanDuel held at -7 through game day. The total opened at 54.5 and closed at 53. This illustrates how public betting action and sharp money shifted the spread by a full point in Texas's favor leading up to the game. Actual line movement depends on the providers and timestamps available in the API.
This example demonstrates the MCP's ability to track historical betting market behavior, useful for retrospective analysis or modeling. Note that line data availability depends on sportsbook partnerships and may not cover all games or all providers. No real-time data—this is historical only, so don't use it for live betting decisions.
@collegefootballdata compare the composite talent rankings for Michigan, Ohio State, and Penn State over the last 5 seasons and summarize the recruiting gap
Over 2019–2023, Ohio State consistently ranked in the top 3 nationally for composite talent (average rank: 2.4), while Michigan averaged 9th and Penn State 14th. The talent gap widened in 2021–2022 when Ohio State's composite score exceeded Michigan's by an average of 15 points per recruit. By 2023, Michigan closed the gap slightly (rank 7 vs Ohio State's 2), reflecting their recent recruiting surge. This synthesis pairs 247Sports talent data with multi-season trend analysis to contextualize on-field performance disparities.
This example showcases the MCP's ability to feed longitudinal recruiting data into AI reasoning, enabling comparative analysis across programs and years. Composite talent rankings are third-party data (247Sports), so coverage and methodology are external to the API. Best used for macro-level recruiting trends, not individual player evaluations.
Use-case deep-dives
When this MCP is overkill for casual fantasy play
A 6-person fantasy league tracking weekly college football player performance hits a wall with this MCP. The 41 tools are built for institutional-grade analytics—success rates, havoc metrics, Elo ratings—not the box scores and player stats casual leagues need. The Advanced Box Score tool does surface player-level data, but you're authenticating with an API key and wading through team-level explosiveness metrics to find rushing yards. If your league is just tracking touchdowns and yardage, a simpler sports data MCP or a shared spreadsheet wins. This MCP pays off when your league is scoring on advanced metrics (third-down conversion rates, defensive havoc) or you're running multi-season trend analysis. For standard fantasy scoring, it's a mismatch.
This MCP is the right call for betting analytics
A 2-person team building a college football betting model needs historical lines, team talent composites, and game-level advanced stats in one place. This MCP delivers all three: the Betting Lines tool pulls spreads and totals by provider and season, Composite Team Talent surfaces 247Sports rankings, and Advanced Game Stats gives you success rates and explosiveness to feed your model. The API key auth is straightforward for a dev workflow, and the 41 tools cover the full data surface—conference history, Elo ratings, division metadata—without stitching together three vendor APIs. The threshold: if you're only modeling a single season or conference, the tool count feels heavy. But for multi-year models or live-season updates, this MCP is the fastest path from raw data to backtest.
When this MCP speeds up beat reporting
A solo beat reporter covering a mid-major conference needs to pull historical context and advanced metrics on deadline. This MCP wins when the story requires more than box scores: conference realignment history (Conference Memberships History), season-over-season talent trends (Composite Team Talent), or defensive havoc rates (Advanced Season Stats by Team). The 41 tools feel like a firehose at first, but the representative set maps cleanly to common story angles—betting line movement, Elo rating shifts, division-level performance. The API key setup is a one-time lift. The trade-off: if your beat is a single team and you're writing daily game recaps, the tool breadth is wasted. This MCP pays off when you're writing features, doing multi-season comparisons, or covering conference-wide trends under tight deadlines.
Frequently asked
What does the College Football Data MCP do in Switchy?
It pulls real-time and historical college football stats—box scores, advanced metrics, betting lines, Elo ratings, conference history—into your Switchy workspace. Your team can query 41 endpoints covering games, teams, players, and recruiting without writing API code. Useful for sports analytics, content research, or building dashboards that need NCAA data.
Do I need a College Football Data API key to connect this MCP?
Yes. The MCP uses API key authentication, so you'll need to sign up at collegefootballdata.com and generate a key. Paste it into Switchy's connection form. No OAuth dance—just the key. If your team shares one key, everyone in the workspace can use the same connection.
Can this MCP fetch live scores during games?
No. College Football Data provides post-game box scores and advanced stats, not live play-by-play. If you need real-time scores, use a different service. This MCP is for historical analysis, season aggregates, and betting line history—not in-game updates.
How does this compare to scraping ESPN or using the NCAA's site directly?
College Football Data aggregates stats from multiple sources into a structured API, so you skip the scraping headache. The MCP wraps that API for Switchy, meaning you query in plain English instead of writing fetch requests. Faster setup, cleaner data, no rate-limit surprises from ESPN's CDN.
Who on my team should connect this MCP?
Anyone who needs to pull college football data—analysts, content writers, or developers prototyping dashboards. The API key holder should add the connection in Switchy; after that, all workspace members can run queries. One connection, shared access. No per-seat API limits from Switchy's side.