Avalanche accidents, particularly those resulting in fatalities, attract substantial attention from policy makers and organizations, as well as from the media and the public. Placing fatal accidents in a wider context requires long-term and robust statistics. However, avalanche accident statistics, like most other accident statistics, often rely on relatively small sample sizes, with single multi-fatality events and random effects having a potentially large influence on summary and trend statistics. Additionally, trend interpretation is challenging because statistics are generally explored at a national level, and studies vary in both the period covered and the methods. Here, we addressed these issues by combining the avalanche fatality data from the European Alps (Austria, France, Germany, Liechtenstein, Italy, Slovenia, and Switzerland) for three different periods between 1937 and 2015 and applying the same data analysis methodology. During the last four decades, about 100 people lost their lives each year in the Alps. Despite considerable inter-annual variation, this number has remained relatively constant in the last decades. However, exploring fatality numbers by the location of the victims at the time of the avalanche revealed two partly opposing trends. The number of fatalities in controlled terrain (settlements and transportation corridors) has decreased significantly since the 1970s. In contrast to this development, the number of fatalities in uncontrolled terrain (mostly recreational accidents) almost doubled between the 1960s and 1980s and has remained relatively stable since then, despite a strong increase in the number of winter backcountry recreationists. Corresponding to these trends, the proportion of fatalities in uncontrolled terrain increased from 72 to 97 %. These long-term trends were evident in most national statistics. Further, the temporal correlation between subsets of the Alpine fatality data, and between some of the national statistics, suggests that time series covering a longer period may be used as an indicator for missing years in shorter-duration datasets. Finally, statistics from countries with very few incidents should be compared to, or analysed together with, those from neighbouring countries exhibiting similar economical and structural developments and characteristics.