Understanding the dynamics behind bubbly flows is critical to the analysis of a pressurized water reactor (PWR) system, but there are still phenomena within bubbly flows that are not fully understood. Utilizing direct numerical simulations (DNS) coupled with interface tracking methods (ITM), high-fidelity numerical data can be extracted from bubbly flow simulations for use in the development of closure laws and mechanistic models. With the use of a bubble tracking algorithm that can record information specific to individual bubbles within the flow, numerical data can be gathered on a fundamental level. State-of-the-art high performance computing (HPC) facilities were used to simulate two-phase, turbulent flow within the subchannel of a PWR for both a simple subchannel geometry and one with a spacer grid and mixing vanes included. A statistical analysis of the numerical data gathered from these simulations can then be studied to discover the dependency of bubble dynamics upon flow conditions. Bubbles can be split into groups in relation to their distance to the wall, and the dependency of quantities such as the relative velocity or the drag coefficient upon the distance to the wall can be investigated. This work splits previously generated numerical data into seven bubble groups for further statistical analysis, as well as dividing the subchannel into “quadrants” to check for time averaged imbalances in bubble population resulting from geometric influences. These post processing techniques seek to offer insight into the physics behind bubbly flow conditions.