  Eccentricity has emerged as a potentially useful tool for helping to identify
the origin of black hole mergers. However, owing to the large number of
harmonics required to compute the amplitude of an eccentric signal, eccentric
templates can be computationally very expensive, making statistical analyses to
distinguish distributions from different formation channels very challenging.
In this paper, we outline a method for estimating the signal-to-noise ratio for
inspiraling binaries at lower frequencies such as those proposed for LISA and
DECIGO. Our approximation can be useful more generally for any quasi-periodic
sources. We argue that surprisingly, the signal-to-noise ratio evaluated at or
near the peak frequency (of the power) is well approximated by using a constant
noise curve, even if in reality the noise strain has power law dependence. We
furthermore improve this initial estimate over our previous calculation to
allow for frequency-dependence in the noise to expand the range of eccentricity
and frequency over which our approximation applies. We show how to apply this
method to get an answer accurate to within a factor of two over almost the
entire projected observable frequency range. We emphasize this method is not a
replacement for detailed signal processing. The utility lies chiefly in
identifying theoretically useful discriminators among different populations and
providing fairly accurate estimates for how well they should work. This
approximation can furthermore be useful for narrowing down parameter ranges in
a computationally economical way when events are observed. We furthermore show
a distinctive way to identify events with extremely high eccentricity where the
signal is enhanced relative to na\"ive expectations on the high frequency end.
