Bulk metallic glasses (BMGs) are amorphous alloys with desirable mechanical properties and processing capabilities. To date, the design of new BMGs has largely employed empirical rules and trial-and-error experimental approaches. Ab initio computational methods are currently prohibitively slow to be practically used in searching the vast space of possible atomic combinations for bulk glass formers. Here, we perform molecular dynamics simulations of a coarse-grained, anisotropic potential, which mimics interatomic covalent bonding, to measure the critical cooling rates for metal-metalloid alloys as a function of the atomic size ratio σS/σL and number fraction xS of the metalloid species. We show that the regime in the space of σS/σL and xS where well-mixed, optimal glass formers occur for patchy and LJ particle mixtures, coincides with that for experimentally observed metal-metalloid glass formers. Thus, our simple computational model provides the capability to perform combinatorial searches to identify novel glass-forming alloys.