Take a look at the tooth brushing example at the very start of Chapter 14 of Andrew Vickers' book What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics. It starts on page 57 or you can use the table of contents button in the bottom left corner to find it.
Here's an excerpt:
[I]f you do nothing else, please try to remember the following
sentence: “the $p$-value is the probability that the data would be at
least as extreme as those observed, if the null hypothesis were true.”
Though I’d prefer that you also understood it—about which, teeth
brushing.
I have three young children. In the evening, before we get to bedtime
stories (bedtime stories being a nice way to end the day), we have to
persuade them all to bathe, use the toilet, clean their teeth, change
into pajamas, get their clothes ready for the next day and then
actually get into bed (the persuading part being a nice way to go
crazy). My five-year-old can often be found sitting on his bed, fully
dressed, claiming to have clean teeth. The give-away is the bone dry
toothbrush: he says that he has brushed his teeth, I tell him that he
couldn’t have.
My reasoning here goes like this: the toothbrush is dry; it is
unlikely that the toothbrush would be dry if my son had cleaned his
teeth; therefore he hasn’t cleaned his teeth. Or using
statistician-speak: here are the data (a dry toothbrush); here is a
hypothesis (my son has cleaned his teeth); the data would be unusual
if the hypothesis were true, therefore we should reject the
hypothesis.
[...]
So here is what to parrot when we run into each other at a bar and I
still haven’t managed to work out any new party tricks: “The $p$-value
is the probability that the data would be at least as extreme as those
observed, if the null hypothesis were true.” When I recover from
shock, you can explain it to me in terms of a toothbrush (“The
probability of the toothbrush being dry if you’ve just cleaned your
teeth”).
The other thing I really like about this example is that it also explains that failing to reject the null does not mean the null is necessarily true. Vickers writes that his son has now worked out the trick and has taken to running his toothbrush under the tap for a second or two before heading to bed. Just because the toothbrush is wet (and the data is consistent with the null hypothesis), it does not mean that his son has cleaned his teeth.