question on complete confounding and partial confounding in multiple regression

While learning multiple regression, I once meet the concepts of “complete confounding” and “partial confounding”
In the model, the response variable is referred to as Y. There have two predictor variables: X1 and X2. With respect to the complete confounding, the correlation between X1 and X2 is 1.
With respect to the partial confounding, the correlation between X1 and X2 is 0.95237.
I attached the ANOVA tables for both cases. The first one is for complete confounding and the second one is for partial confounding.

I noticed that for complete confounding case, some F-statistics and P-value are just N/A in the corresponding ANOVA table, why?

Secondly, looks like the P-value in the ANOVA table corresponding to the partial confounding is way smaller than the one related to the complete confounding case, why?
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