How to Pull CollegeFootballData.com Into Excel (4 Methods Compared)

The Problem with Getting College Football Data Into Your Workbook

CollegeFootballData.com is one of the best sports data APIs available. It covers every FBS program going back decades: season stats, recruiting rankings, transfer portal entries, AP poll history, SP+ ratings, PPA efficiency metrics, betting lines, Elo ratings, roster data, play-by-play, and more. The API is well-documented and largely free for non-commercial use.

The problem is the gap between "the data exists" and "the data is in my Excel workbook." If you are a sports analytics researcher, a pro scouting intern, or a fantasy analyst compiling stats across every FBS program, you know this gap. The API is not especially hard to call, but pulling it for 130+ teams, parsing the JSON, and writing the results into a clean Excel table requires either scripting experience or a lot of copy-paste time.

Excel users face an extra layer: Excel's native data import tools work well for structured files and databases, but hitting a REST API with dynamic parameters and flattening nested JSON into rows requires Power Query M code or a VBA macro that most users do not have ready to go.

Below are the four common ways people get CollegeFootballData.com data into an Excel workbook. Only the last one handles the full analytical workflow.

Method 1: Export Manually and Paste Into the Workbook

The default for most Excel users is calling the API in a browser or Postman, copying the JSON or pasting into a converter, and reformatting the output before pasting it into the workbook. For one team, one season, this is manageable. For anything broader, the time cost multiplies quickly.

When this works:

• You need a single team's stats for a single season
• You already know exactly which endpoint to call
• It is a one-off project that will not need to be repeated
• The JSON response is flat enough to paste directly

When it breaks:

• You need to loop over all FBS teams
• You want to pull multiple seasons and merge them into one table
• The response is nested and needs flattening before Excel can read it
• You want to combine two data types — draft picks and college stats, for example — in one workbook
• You do not yet know which endpoint covers the metric you want

The manual approach puts the burden on you to understand the API structure before you can ask the analytical question you actually care about.

Method 2: Use Power Automate to Pull Data on a Schedule

Power Automate is the natural choice for Excel files living on OneDrive or SharePoint. You configure a flow that hits the CollegeFootballData.com API on a schedule and writes results into a table in the workbook. For recurring, fixed-shape pulls this is a workable setup.

This works for event-driven or recurring moments:

• Weekly poll rankings refreshed every Tuesday morning
• Transfer portal entries logged as they appear
• ATS records updated after each game week

This fails for analytical or batch work:

• Any query that loops across all 130+ FBS teams in a single run
• Cross-referencing two endpoints in one pass
• Queries where the parameters come from cells already in the workbook
• Anything that requires understanding the data before deciding what to pull

Power Automate fires on triggers, not on analytical intent. It does not know how to look at column A, read team names, and pull Elo ratings for each one. That logic requires scripting.

Method 3: The Previous Generation — Sports Data Connectors

Until recently, the best option for repeatable sports data pulls into Excel was a category of connector add-ins that let you configure an endpoint, map the response fields to worksheet columns, and schedule a refresh. The output was consistent, the refresh was automatic, and you did not need to write code every time.

That was a real step up from purely manual work. The fields landed in the right columns, the schedule ran without intervention, and the team did not have to redo the pull from scratch each week.

But you were still responsible for knowing which endpoint covered the data you wanted, how to handle the nested response fields, and what to do when the query needed to combine two data types. The moment the analytical question drifted past the pre-configured setup, you were back to manual work or a Power Query script. The connector got data in, but the thinking was still on you.

This is the category we think of as the previous generation. It worked for fixed pulls, but it did not generalize.

The Easy Way: Using SheetXAI in Excel

There is a different approach entirely. SheetXAI is an AI agent that lives inside your Excel workbook, both on Excel for the web and Excel desktop. It reads the workbook, understands what you are looking at, and through its built-in CollegeFootballData.com integration it can pull, filter, combine, and analyze data in response to a plain-English prompt. No Power Query, no endpoint configuration, no VBA — you just ask.

Example 1: Your Workbook Is Ready for the Data

You have an Excel workbook with a tab called "Team Stats 2024" and you want season totals for every FBS team.

Pull all FBS team season stats for 2024 and write them into the Team Stats 2024 tab with columns for team, conference, rushing yards, passing yards, and points scored, sorted by total points descending.

SheetXAI calls the CollegeFootballData.com API, flattens the response, and writes the table into the tab. If you want to extend it with advanced metrics next, you ask, and it extends the same table.

Example 2: The Analysis Comes Before the Pull

You want to cross-reference two data sources without configuring anything in advance.

Pull the 2023 NFL Draft picks for wide receivers and tight ends from CollegeFootballData and write them into the Draft Picks tab with round, pick, player name, college, and drafting team. Then look up each player's final college season receiving stats and write yards and touchdowns into adjacent columns.

SheetXAI makes both API calls, joins on player name, and writes the merged result into Excel. One prompt, two endpoints, one table.

Which Method Should You Use

For a single one-off pull from a fixed endpoint you already know, the manual approach is fine. For recurring, fixed-shape pulls on a schedule, Power Automate is a reasonable setup if your files live in OneDrive or SharePoint.

For anything analytical — queries that span teams, combine data types, filter based on cells already in the workbook, or compare across seasons — SheetXAI handles it in one prompt without any pre-configuration. The sports analytics workflow is almost always analytical. The question comes first, the data pull comes second.

Try It

Get the 7-day free trial of SheetXAI and ask it to pull any CollegeFootballData.com dataset into your workbook. The CollegeFootballData.com integration is included in every plan.

For specific workflows, see how to pull FBS team season stats for a power ranking model, how to export game-level PPA metrics, or browse the full integrations directory.