Screening is considered the first step in evaluating potential enhanced oil recovery (EOR) techniques for candidate reservoirs; therefore, it is important to update the screening criteria as new technologies are developed. However, most recently published screening criteria regarding polymer flooding were based on data collected from the bi-annual EOR surveys published by the Oil & Gas Journal. These data recorded valuable information for finished and ongoing polymer flooding worldwide, but they are constrained in two ways. Firstly, they do not include some important information, such as the formation water salinity, divalent concentration, and polymer type and concentration. Secondly, the field data do not reflect recent polymer technology developments that are still in the laboratory evaluation and pilot testing stages. To overcome these limitations, a comprehensive dataset that provides the overall picture of polymer flooding research and application is presented in this paper. A total of 865 polymer flooding projects were considered to construct the dataset, including 481 field projects from the Oil & Gas Journal (1974-2012), 329 laboratory experiments (1964-2013), and 55 pilot test projects (1966-2011) recorded in the literature. After enhancing the data quality, graphical and statistical methods were used to analyze and describe the dataset. The distribution of major parameters important to polymer flooding design is presented using histograms, and the range of all parameters and their statistical values are presented using box plots. New screening criteria are presented based on these statistics of the defined parameters. Compared to published screening analyses, the new dataset and criteria provide more information critical to the design of a successful polymer flooding project, such as data pertaining to the formation water salinity, polymer molecular weight and concentration, polymer viscosity, and slug size.