More dramatic gain from partial pooling

[armanboyaci]

First of all thanks for the book and the video course. The motivation behind multilevel models is clear: partial pooling is an "adaptive compromise" between no pooling and complete pooling. In the video lecture-12 (https://speakerdeck.com/rmcelreath/statistical-rethinking-2022-lecture-12?slide=40) we show the "gain" of using partial pooling using "cross-validation". But the cross-validation score of partial pooling is very similar to the complete pooling.

1. For this particular example, are there any other (more convincing?) arguments (other than cross-validation) to use partial pooling against complete pooling?
2. Is it possible to create a "simple" example in which we observe a more "dramatic" U-shaped cross-validation line?

Thanks in advance.