Choose a CSV contract before exporting
A useful CSV has stable column names, explicit timestamp meaning and a documented missing-value policy. Include match ID so a spreadsheet row can be traced back to the retained API response. Keep kickoff in an offset-aware format and include status; a blank score for a scheduled fixture should not look like a completed 0-0 result.
CSV is a presentation artifact as well as a data format. A spreadsheet may interpret text beginning with an equals sign, plus, minus or at sign as a formula. Treat externally supplied text fields as data and prepare them for the intended spreadsheet consumer without changing your authoritative raw JSON.
Separate machine data from spreadsheet display
The example prefixes potentially formula-like text with an apostrophe before writing the CSV. It applies that policy to names and other display text, while numeric scores are serialized from validated numeric values. This is a practical spreadsheet-oriented policy, not a universal promise about every CSV importer.
Maintain a separate raw export when downstream code needs exact source strings. Document that the spreadsheet version may contain protective prefixes. Otherwise a later re-import can treat those prefixes as part of a team's actual name and corrupt your canonical records.
Run the reproducible example
This Python 3 example uses deliberately synthetic inputs, not a downloaded match or a forecast for a real fixture. Save it as example.py and run python3 example.py. It uses only the standard library and its assertions check the behavior discussed here. Replace the fixture inputs with validated API records when connecting your application; demo identifiers are not production lookup values.
import csv
import io
def spreadsheet_text(value):
text = str(value)
if text.lstrip().startswith(("=","+","-","@")) or text.startswith((chr(9),chr(13),chr(10))):
return "'"+text
return text
fixture = {"id":"match_demo","starts_at":"2026-10-21T18:00:00Z","status":"scheduled",
"home_team":{"name":"=DEMO()","score":0},
"away_team":{"name":"Town, United","score":None}}
stream = io.StringIO(newline="")
writer = csv.writer(stream)
writer.writerow(["match_id","starts_at","status","home","away","home_score","away_score"])
writer.writerow([fixture["id"],fixture["starts_at"],fixture["status"],
spreadsheet_text(fixture["home_team"]["name"]),spreadsheet_text(fixture["away_team"]["name"]),
fixture["home_team"]["score"],fixture["away_team"]["score"]])
rows = list(csv.reader(io.StringIO(stream.getvalue())))
assert rows[1][3] == "'=DEMO()"
assert rows[1][4] == "Town, United"
assert rows[1][5:] == ["0", ""]
print(stream.getvalue(),end="")
Read the result
The CSV contains a protective apostrophe before the synthetic formula-like name, quotes the comma-containing team name, writes a known zero and leaves the unknown score blank. Reading it back verifies the serialized cells rather than merely inspecting the output text.
Keep unknown scores unambiguous
Use an empty cell for a missing score and retain status in the same row. A known zero must be written as 0. If your analysis tool conflates blank and zero, include a companion score-known flag or import schema. Do not ask the spreadsheet to guess the difference from formatting.
The synthetic fixture contains a name beginning with an equals sign and a null away score. The test writes through Python's csv module and reads the result back, checking that quotes and commas survive correctly and that the dangerous-looking text remains text in the exported representation.
Verify the complete export
Fetch all required pages before marking a CSV complete, and record the query filters and retrieval period in an accompanying manifest. For large files, write to a temporary path and rename only after successful completion. A half-written CSV should not replace the previous complete report.
Test non-ASCII names, embedded commas, quotes, line breaks, null scores and known zeroes. Use the csv module rather than concatenating strings with commas. Keep credentials out of both the file and its metadata, and restrict customer-specific exports to the account that requested them.
Connect this to your project
Connect this serializer to a completed, validated match export and publish a short column dictionary with the file. If you also store the data in SQL, retain the original source strings there and generate the spreadsheet representation only at the download boundary.