The Scenario
You are an F1 analytics hobbyist. The 2023 season wrapped in November and you want to chart the championship progression across all 22 rounds — who was leading after each race, how the gap between Verstappen and the field changed, and which constructors had the most consistent scoring runs.
You need every race result: driver, team, finishing position, and points scored, one row per driver per race, across all 22 rounds. That is 484 data rows before you add any analysis.
The bad version:
- You find the API-Sports Formula 1 race results endpoint
- You write a loop in Python to call it 22 times, once per round
- Each response has a different race name in the fixture object and you have to normalise them
- The response schema for DNF finishes is different from finished finishes — you have to handle null points separately
- You get the data exported to CSV, open it in Sheets, discover the round numbers are not in the response and you have to infer them from the race names
- It is 11 PM and you have not opened a chart tool yet.
The faster version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your spreadsheet that loops through the 2023 F1 season race by race and writes the full results table without you writing a single line of code.
Open the SheetXAI sidebar and type:
Pull all 2023 Formula 1 race results — race name, round number, driver, constructor, finishing position, points — and write them into this sheet with one row per driver per race. Sort by round number then by finishing position within each round.
SheetXAI calls the API-Sports Formula 1 fixtures and results endpoints for the 2023 season, handles the DNF/DNS edge cases (writing 0 for points and the relevant status for position), and writes the full 484-row table sorted by round then position. The round numbers are inferred from the schedule order and written into column B so you have a clean numeric axis for your charts.
What You Get
A 484-row results table:
- Race name and round number — one round-identifying column for chart axes
- Driver name and constructor — consistent formatting across all 22 rounds
- Finishing position and points — DNF/DNS rows included with 0 points and status flag
Consistent driver and constructor names across all 22 rounds mean you can build a pivot table or chart immediately without fixing encoding inconsistencies between race 1 and race 22.
What If the Data Is Not Quite Ready
Championship progression charts need more than a flat results table. SheetXAI can add the cumulative layer inline.
When you want cumulative points per driver for each round
You need a running total so you can chart who was leading after round 1, round 5, round 12.
Add a 'Cumulative Points' column to the results table. For each driver, calculate the running sum of their points after each race in round order. Write the cumulative total into column G for each row.
When you want to filter to just the top 5 drivers in the championship
You have 20 drivers in the table but your chart will be unreadable with all of them. You want to isolate the championship fight.
Filter the results table to the five drivers with the highest total points across the season. Move those rows to a new tab called 'Top 5 Championship'. Keep all 22 rounds for each of the five drivers.
When DNF/DNS rows are breaking your pivot table
Your pivot table groups by finishing position and DNF rows are showing up as text in a numeric column, which breaks the aggregation.
In column E (finishing position), replace any non-numeric values (DNF, DNS, DSQ, or blank) with the value 21. Add a separate column F called 'Status' that records the original string for those rows so you can still identify non-finishers separately.
When you want the full championship analysis in one pass
You have not pulled any data yet. You want the results table, cumulative points per driver per round, final standings, and a fastest-lap count per driver, all in one workbook.
Pull all 2023 Formula 1 race results with race name, round number, driver, constructor, finishing position, and points. Write the raw results into the main tab. Add cumulative points per driver in a new column. Create a 'Final Standings' tab with driver name, nationality, team, total points, and number of fastest laps. Sort the Final Standings tab by total points descending.
The pattern: instead of pulling the race data and building the championship analysis as two separate tasks, you describe the full deliverable and SheetXAI runs the API calls and the analytical layers together.
Try It
Get the 7-day free trial of SheetXAI and ask it to pull a full F1 season's race results into your sheet for championship charting. The API-Sports integration is included in every SheetXAI plan. For related workflows, see how to pull head-to-head match history for rival teams or the API-Sports in Google Sheets overview.