In Bayes Theorem why do we say :given that" when "out of" is more understandable. (Why is Conditional on referred to as "Given") I understood the answer to my problem here when I substituted the "given that" symbol with the phrase "out of"
I got this idea from 3Blue1Brown where Grant points out that people are less confused when this phrase is used.
So why do we persist with using "given that"?
As a software developer I am used to using "given that" in pseudo code for unit tests, so the phrase especially threw me.
[Update]
I realise now that I am falling into the base-rate fallacy and am looking for an easy way to remember how to avoid it. I have often heard the "conditioning on" symbol read as "given that" and when that happens I get confused. For example in "“Given that it’s cloudy, the probability of rain is high”  when we write it as P(Rain|Cloudy) I tend to read this "P(Rain and Cloudy) given it is cloudy"
So I mistakenly think that we already know that it is cloudy (i.e we are given this) so we just need the probability of rain.
[Update]
I reverted to my original question with clarification in brackets. To hopefully make the question read better.
[Update]
Wikipedia mentions that

"the conditional probability of A given B" ...
can also be understood as the fraction of probability B that
intersects with A


Suppose the probability of the Kansas City Chiefs making the playoffs this season is about $72\%$ and the probability of them winning Super Bowl LVI at the end of the season is about $5\%$, then (since they must make the playoffs to progress to the Super Bowl) you can say
"the probability of the Kansas City Chiefs winning Super Bowl LVI given that they make the playoffs is about $7\%$"
but since this season only happens once you cannot say "out of" in a meaningful sense
