  Online selection is an essential step to collect the most relevant collisions
from the very large number of collisions inside the ATLAS detector at the Large
Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder,
built to greatly improve the ATLAS trigger system capabilities for identifying
interesting physics processes through track-based signatures. The FTK is
reconstructing after each Level-1 trigger all tracks with $ p_{\textrm T}>1 $
GeV, such that the high-level trigger system gains access to track information
at an early stage. FTK track reconstruction starts with a pattern recognition
step. Patterns are found with hits in seven out of eight possible detector
layers.
  Disabled detector modules, as often encountered during LHC operation, lead to
efficiency losses. To recover efficiency, WildCards (WC) algorithms are
implemented in the FTK system. The WC algorithm recovers inefficiency but also
causes high combinatorial background and thus increased data volumes in the FTK
system, possibly exceeding hardware limitations. To overcome this, a refined
algorithm to select patterns is developed and investigated in this article.
