First establish that the fixture is real and current
Confirm both teams, competition, season, venue and kickoff time from a current source. A reused provider identifier can refer to a different season. A familiar team name is not enough to establish that an imported fixture belongs in the current schedule.
Check whether the match is scheduled, postponed, cancelled, live or finished. Record the time of the check and the source. If the source and local record disagree, stop and resolve that conflict before building a narrative around the match.
Separate observations from assumptions
Write down which inputs are actually present: verified results, home and away records, sample sizes, confirmed lineups or shot data. Then list the missing inputs. Do not fill a missing injury report with a general statement that both teams are at full strength.
For an illustrative report, separate three lines: recorded evidence, model estimate and unresolved questions. A model may assign a 45 percent home-win probability while the lineup is still unknown. The number and the missing information can both be true; the report should show both.
Finish with an uncertainty check
Ask whether the conclusion depends on one unusual result, a very small sample, a changed venue or a disputed score. Compare the estimate with the model's own prior record using the same scoring convention. Avoid words such as guaranteed, certain or lock.
The Match Insights preview uses shared fixture records that are not all independently verified. Its research pages must keep that warning visible. Information can help readers ask better questions, but it does not remove uncertainty or establish that a paid prediction product is ready for launch.
Common question
What should I do when two sources disagree?
Keep the disagreement visible, check the timestamps and fixture identity, and do not treat the disputed value as verified until the conflict is resolved.
Sources and further reading
Continue your research
- How to compare football form without ignoring the opponent
- Why sample size matters in football research
- What an honest football forecast record should contain