When a key player is missing, the figures from before the absence may no longer describe the team. Averages built over months mix games with and without the player. It is worth asking which version of the team a number refers to.
Before and after
If a star player misses ten of thirty games, the average over thirty games describes neither the team with him nor the team without him. Separating the two periods is more informative, as long as you remember that each sample is smaller. The same warning about few games applies to both halves.
Even then, the other factors change in the same period. Other changes may coincide with the absence, so a gap in results is not purely down to one person. Careful writers avoid blaming a single player for a whole run.
The effect of an absence depends on the role and on the replacement. A creative midfielder who is replaced by a similar player may leave little trace, while a goalkeeper who is replaced by an inexperienced one can alter many numbers. Teams with a strong bench lose less.
Among services that show team news alongside figures, the Vave Casino website is a useful example. Lineup and results in one view make it easy to link a change to its cause.
It is worth running a small thought experiment. Imagine a side whose chances were worth about two goals in a match but which scored only one, and ask how often that happens. The answer is that it happens all the time, which is why one match says little about the model or about the team.
Report quality matters too. Wait for confirmed team news instead of relying on rumours. If betting markets are of interest, last-minute lineup changes are a good reason to avoid hurried decisions and to keep to a budget and a time limit set beforehand.
Absences are context that explains results. They help in understanding what happened and never make the next match predictable.