Group IV O4 catalysts are interesting due to their high activity, isotacticity and molecular weight capabilities for propene polymerization which justifies their use on commercial/industrial scales. However, these catalysts are not as well-studied in academic literature as they are reported in patent literature. This catalyst type is highly flexible which leaves the identity of active species undetermined. Furthermore, precisely how these catalysts exert control over insertion and chain termination reactions is not entirely understood. Computational chemistry has been used to study olefin polymerization catalysts and much understanding has been learned from this technique in a qualitative sense. As of writing this document, few attempts have been made to see if current methods can quantitatively reproduce experimental aspects such as tacticity, regioerrors and molecular weight of resultant polymers. In this thesis, we use a combined high-throughput experimentation (HTE) and high-throughput computation (HTC) approach to answer these uncertainties in the case of propene homopolymerization. A series of structurally different ligands were synthesized, complexed to zirconium and hafnium, then tested for propene polymerization with HTE reactors. Libraries of activities and propene microstructure were accumulated much quicker using less material than by traditional bottle polymerization. HTC was used to identify the active species, models of competing insertion/chain transfer transition states of the active species were matched to HTE data with high accuracy and provided extra insight than just from experiment alone. Traditional studies of coordination and activation chemistry demonstrated the influence of ligand choice: flexible and bulky ligands could make oligomeric products during chelation to metal while catalyst conformation is affected by ligand choice; these aspects are important to consider when designing tetradentate, octahedral catalysts to promote desirable active species equilibria and promote clean metal complexation. In summary, the combined HTE and HTC was successful for a deeper understanding of these catalysts. Our HTC results also demonstrate that it is possible to accurately model experiment with currently available methods. An important outlook of this work suggests that computational “pre-screening” of new catalysts may be beneficial: catalysts that would not produce desired polymer properties can be ruled out prior to resource-consuming synthesis and polymerization testing.