Struggling to understand why out of fold predictions with an AUC of 0.56 actually look pretty useful.

I recently ran a model with 25 fold cross validation. I obtained the cross validated predictions, and low and behold, the ROC AUC is only 0.56. Well, shucks. That's not that good. However, when I break these predictions up into 5 quantiles, there is a very blatant trend in the real target, which looks almost too good to be true:

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|Out of Fold Quantile|Average Target|
|:-|:-|
|0|0.096|
|1|0.101|
|2|0.118|
|3|0.133|
|4|0.163|

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Graphically, this looks like:

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https://preview.redd.it/mvqy31fz3bu81.png?width=480&format=png&auto=webp&s=25d5a89d03737d629669113028a33a843827bbb5 …

auc datascience predictions