Event attribution studies assess whether and to what extent human-induced climate change has altered the likelihood or severity of extreme weather events. In recent years, studies have become routine, particularly for heatwaves in many regions, and for heavy rainfall in parts of Asia and Europe. As this body of research grows, a key question emerges: when does a new attribution study add scientific or societal value? We address this question by synthesising findings from existing attribution studies and systematically analysing how results depend on temporal and spatial event definition and dataset. While previous work has shown that quantitative outcomes are sensitive to how events are defined, we find that when similar probabilistic frameworks and comparable datasets are used, attribution results for events of the same type and magnitude within a region are often strikingly consistent. Consequently, additional studies that replicate established methods for well-studied hazards and regions often provide limited new insight unless they incorporate substantial advances in data quality. These findings have implications for operational attribution services and for the use of attribution evidence in decision-making. More broadly, they suggest the need to prioritise understudied regions, and integrative approaches that deepen causal understanding rather than repeatedly reaffirm well-established conclusions.