The Scenario
You are a college football travel blogger. Your content calendar has a big feature planned: "Stadium Tour USA" — every FBS stadium ranked by capacity, with location, surface type, and a verdict on whether it is worth the drive. You need the raw data in an Excel workbook before you can write a single word of the feature.
The CollegeFootballData.com API has venue data for every FBS program. It is Wednesday morning. Your post goes live Sunday.
The bad version:
- You search for the venues endpoint, find it, hit it
- You get back 130+ stadium records in JSON with "grass" as a boolean field instead of a readable label
- You import into Excel via Power Query and the surface type column shows TRUE/FALSE instead of "Grass/Turf"
- You spend two hours reformatting, cleaning city and state, and converting the boolean
- The post goes live Monday, a day late, and your newsletter subscribers notice.
The fast version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI interprets the API's surface boolean and formats the table the way you want it.
Open the SheetXAI sidebar and type:
Pull the full FBS venue list from College Football Data into my Excel workbook with columns for stadium name, home team, capacity, city, and surface type.
SheetXAI pulls all venues, converts the surface type into a readable label, and writes a clean table. Your feature research is done before noon.
What You Get
A clean venue table with all FBS programs:
- Stadium name — official venue name for every FBS program
- Home team — which program plays there
- Capacity — sortable from the largest to the smallest
- City and state — for travel planning and the road trip feature angle
- Surface type — "Grass" or "Turf" written as readable text, not TRUE/FALSE
The top 10 by capacity is the first sidebar in the post. The surface type column lets you filter for natural grass stadiums for the "atmosphere purists" sub-feature.
What If the Data Is Not Quite Ready
Venue data has gaps and analytical follow-up questions. SheetXAI handles both.
When some stadiums have no capacity recorded
A handful of programs — often newer FBS members — may have incomplete venue records.
In this Excel workbook, flag any row where the capacity column is blank or zero with "Capacity Unavailable" in a new column. Do not remove those rows — keep them in the full list but exclude them from the ranked sort.
When you want to group stadiums by region for travel planning
Your tour has a regional structure: Southeast, Midwest, Big 12 country, West Coast. You need a region label per stadium.
Add a "Region" column to this Excel workbook based on the state column. Use these groupings: Southeast = AL, GA, FL, SC, NC, TN, MS, KY, VA; Midwest = OH, MI, IN, IL, WI, MN, IA, MO; Plains/Big 12 = TX, OK, KS, NE, CO; West = CA, OR, WA, UT, AZ, NV, HI; Northeast = PA, NY, NJ, CT, MA, MD; Other = everything else.
When you want to filter to grass-only stadiums above 60,000 capacity
The natural grass filter is a key editorial decision for the "traditional college football experience" angle.
Filter this Excel workbook to stadiums where surface type is "Grass" and capacity is 60,000 or more. Copy those rows to a new tab called "Grass Cathedrals" sorted by capacity descending. Add a column with the state's timezone (Eastern, Central, Mountain, Pacific) for travel scheduling.
When you want the full research table with distance estimates
Your travel planning needs driving distance estimates from a home base.
In this Excel workbook, add a column called "Approx Drive from Columbus OH" that estimates the driving distance in hours from Columbus, Ohio to each stadium's city and state. Use rough regional estimates rather than exact GPS routing — within 1 hour of accuracy is fine. Round to the nearest half hour.
The pattern: the raw venue pull is the research foundation. Every editorial question builds from it.
Try It
Get the 7-day free trial of SheetXAI and ask it to pull all FBS venue data into a workbook. The CollegeFootballData.com integration is included in every SheetXAI plan. For more, see how to pull team season stats or the CollegeFootballData.com in Excel overview.