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In our analysis, we manually picked popular game exemplars to create genre groupings.
For each game, we calculated the proportion of its gamers that are female. So for example, when we say High Fantasy MMOs, we specifically mean the group average of gamers who enjoy playing World of Warcraft, Rift, Lord of the Rings Online, Ever Quest II, and The Elder Scrolls Online. So for example, the 69% for Match 3 games means that of the gamers who mentioned a Match 3 game in the data, 69% of them were female.
By sampling gamers who mention a specific game title/franchise, we can generate a profile of that game’s engaged audience.
Note that the data we have is limited to the favorite games listed by a gamer–they are likely playing more games than they are able to list, but this constraint holds true for all respondents in our data, whether male or female.
But when we’re drilling down to a specific game (like Diablo III in the Action RPG genre), the 41% in the ESA sample is not a meaningful benchmark because a large portion of that sample was likely not playing a AAA game to begin with.
The self-selected sampling is very much a limitation of the methodology, so we do try to make it clear how we collected the data to allow readers to interpret the findings in the proper context.
This is a reflection of how hard it is to sample gamers.