Precipitation is one of the key inputs for hydrological modeling. Although the Multisensor Precipitation Estimator (MPE) from NEXRAD (Next Generation Radar) and the NLDAS (North American Land Data Assimilation System) precipitation data have been extensively used in various hydrological and climatic studies, there has been no systematic investigation of the spatial similarities and differences between them, based on long-term time series data over a large spatial region. In this study, six years of hourly and daily precipitation time series data from NEXRAD and NLDAS were investigated for their spatial similarities, over a subregion of the Ohio River basin. Three spatial metrics were used: Cohen's Kappa coefficient, Forecast Quality Index (FQI), and displacement-based Forecast Quality Measure (FQM). The three metrics were also applied to the two data products after stratification by season (warm, cold). Results show that significant differences exist between NEXRAD MPE and NLDAS. Analyses and discussions are presented on possible causes of the dissimilarities. In addition, results show that a single metric cannot adequately represent their spatial characteristics. The three metrics are complementary to each other and, when used jointly, can provide a more complete picture of the similarities and differences between the two precipitation products. However, if a single metric is desired, then a more comprehensive one needs to be developed to effectively account for magnitude, distance, shape, and neighborhood effects.