It speaks to excellent model calibration, though I seem to detect a residual sigmoidal bias. The true calibration should be Linear in Logit space, after transforming both probabilities p -> x= ln(p/(1-p)).

Deviations from linearity (in Logit space) at either end will indicate partial and possibly simultaneous over and under fitting.