Taming redshift-space distortion effects in the EFTofLSS and its
  application to data
  Former analyses of the BOSS data using the Effective Field Theory of
Large-Scale Structure (EFTofLSS) have measured that the largest counterterms
are the redshift-space distortion ones. This allows us to adjust the
power-counting rules of the theory, and to explicitly identify that the leading
next-order terms have a specific dependence on the cosine of the angle between
the line-of-sight and the wavenumber of the observable, $\mu$. Such a specific
$\mu$-dependence allows us to construct a linear combination of the data
multipoles, $\slashed{P}$, where these contributions are effectively projected
out, so that EFTofLSS predictions for $\slashed{P}$ have a much smaller
theoretical error and so a much higher $k$-reach. The remaining data are
organized in wedges in $\mu$ space, have a $\mu$-dependent $k$-reach because
they are not equally affected by the leading next-order contributions, and
therefore can have a higher $k$-reach than the multipoles. Furthermore, by
explicitly including the highest next-order terms, we define a `one-loop+'
procedure, where the wedges have even higher $k$-reach. We study the
effectiveness of these two procedures on several sets of simulations and on the
BOSS data. The resulting analysis has identical computational cost as the
multipole-based one, but leads to an improvement on the determination of some
of the cosmological parameters that ranges from $10\%$ to $100\%$, depending on
the survey properties.
