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Former analyses of the BOSS data using the Effective Field Theory ofLarge-Scale Structure (EFTofLSS) have measured that the largest countertermsare the redshift-space distortion ones. This allows us to adjust thepower-counting rules of the theory, and to explicitly identify that the leadingnext-order terms have a specific dependence on the cosine of the angle betweenthe line-of-sight and the wavenumber of the observable, $\mu$. Such a specific$\mu$-dependence allows us to construct a linear combination of the datamultipoles, $\slashed{P}$, where these contributions are effectively projectedout, so that EFTofLSS predictions for $\slashed{P}$ have a much smallertheoretical error and so a much higher $k$-reach. The remaining data areorganized in wedges in $\mu$ space, have a $\mu$-dependent $k$-reach becausethey are not equally affected by the leading next-order contributions, andtherefore can have a higher $k$-reach than the multipoles. Furthermore, byexplicitly including the highest next-order terms, we define a `one-loop+'procedure, where the wedges have even higher $k$-reach. We study theeffectiveness of these two procedures on several sets of simulations and on theBOSS data. The resulting analysis has identical computational cost as themultipole-based one, but leads to an improvement on the determination of someof the cosmological parameters that ranges from $10\%$ to $100\%$, depending onthe survey properties.

Taming redshift-space distortion effects in the EFTofLSS and its application to data