The complex effects of genotype (G), environment (E), management (M), and their interactions, complicate the development of sound regional agronomic recommendations. We hypothesize that long-term trials can help to understand these effects and improve recommendations. Our objective was to explore long-term variety performance trials (VPT), usually available in major crop growing regions, to improve management and variety-selection recommendations. We used winter wheat in the U.S. southern Great Plains as a case-study. Data of yield, variety traits, and trial management were collected from 748 wheat VPT conducted in the states of Colorado, Kansas, and Oklahoma over nineteen harvest years (2000-2018) and 92 locations, adding to an unbalanced dataset of 97,996 yield observations. The study region was divided into 11 contiguous sub-regions using 30-yr cumulative yearly precipitation and growing degrees days; division which also accounted for major cropping systems in the region. We used variance components analysis and conditional inference trees to explore the management and variety trait effects in each region. Variance component analysis suggested that E accounted for 78.5% of the total yield variation, while G, G × E, and the residuals accounted for 3.9, 4.3 and 13.5%, respectively. Conditional inference trees proved to be useful tools in identifying management practices associated with yield within each sub-region. For instance, water regime was the most important practice influencing wheat yield in the semi-arid western portion of the study region, followed by sowing dates, which differed for each sub-region. In dryland trials, there was typically an interaction between fungicide, sowing date, and tillage system, depending on the region. Dual-purpose trials (i.e., grazing plus grain) had the lowest yields in the southcentral portion of the study region. Other management practices (e.g. crop rotation and additional N plus fungicide) had significant effects on yield, depending on the region. Here, we propose an approach that uses widely available long-term VPT data to optimize management and variety selection recommendations. Our approach can be used in other regions and crops for which long-term VPT data is available.