Warmer growing seasons, variations to grape ripening dynamics, and stylistic changes have contributed to increased wine alcohol levels, which can negatively impact sensory properties. As a consequence, winemakers have sought technological innovations to produce reduced alcohol wine (RAW). The sensory methodology used by industry to optimize the ethanol content of RAW is known as ‘alcohol sweetspotting’. However, to date, there is no scientific evidence to support the alcohol sweetspot phenomenon, and the sensory methodology used for alcohol sweetspotting has not been validated. In this study, different methods of presenting wine samples (i.e., ordered vs. randomized, and linear vs. circular) were employed to determine to what extent presentation order influences the outcome of alcohol sweetspotting trials. Two different approaches to statistical analysis of sensory data, i.e., chi-square goodness of fit vs. one proportion tests, were also evaluated. Statistical analyses confirmed alcohol sweetspots were apparent in some sweetspot determination trials, but outcomes were not reproducible in replicate determinations (either by panel or by individual panelists). Analysis of data using the one proportion test improved the likelihood of identifying statistically significant differences between RAWs, but variation in individuals’ sensitivity to differences in sensory properties following ethanol removal prevented validation of the alcohol sweetspot phenomenon based on the wines studied.