Time zones are the most reliable source of silent errors in a soccer dataset. The failures rarely announce themselves, because a wrong timestamp still looks like a valid one.
A timestamp without a zone is ambiguous
A recorded kickoff of eight in the evening means nothing without knowing where. Stored bare, it will be interpreted as whatever zone the reading system assumes.
Systems commonly assume the server's own zone, so the same file produces different results depending on which machine reads it. That is a reproducibility failure, not a display quirk.
The safe practice is storing an absolute instant plus the local zone separately, because both are needed and neither can be derived from the other.
Late kickoffs land on the wrong day
An evening match on the West Coast is already the next calendar day in universal time, so grouping matches by date can place it in the following round.
Rest-day calculations then come out short by one, which matters enormously in workload analysis where the gap between matches is the variable of interest.
For competitions spanning several zones, the error is not random. It concentrates on late kickoffs in western venues, which is a systematic bias.
Daylight saving shifts do not align internationally
Regions change clocks on different dates, and some do not change at all. The offset between two places is therefore not constant through a season.
Code that stores a fixed offset instead of a zone name is correct for part of the year and wrong for the rest, and the wrongness begins on an arbitrary weekend.
These weeks produce match sequences that appear to overlap or invert, which analysts often chalk up to a source error rather than tracing to the offset.
Event data inherits the problem twice
Within-match events are usually stamped against a match clock and a wall clock, and the two are reconciled during processing. A zone error breaks the reconciliation.
The visible symptom is events attributed to the wrong half or ordered incorrectly around halftime, which corrupts any sequence-based metric.
Because sequence metrics aggregate over thousands of events, a small share of misordered ones shifts the result without producing anything that looks like an error.
The habits that prevent it
Store instants in universal time, keep the venue's zone as a separate field, and convert only at the point where a human reads the output.
Define the analytical day explicitly as local to the venue when grouping by matchday, rather than letting the storage format decide.
These are unremarkable engineering conventions, and in a competition spread across a continent they are the difference between a workload analysis that holds and one that does not.