In other words, it's statement about the skill/strength/power distribution of your population of players.
As I understood it, the general model they are working with (Bradley-Terry) is about how to take a set of win/loss measurements amongst a fixed set of participants, and then try to predict the win/loss probability of unobserved competitions (and I guess also allow you to generate rankings).
Intuitively, I think you can imagine how you could take that type of observation and build out a ranking of participants basically through a series of pairwise comparisons on win/loss rates. But then when it comes time to predict the win/loss ratio of an unobserved competition, you're forced to make assumptions about how to model/extrapolate win/loss ratios. This depth of competition parameter would be part of that extrapolation.
EDIT: Just a thought, I think it's fun to consider the language around "depth of competition". The paper uses "deep" to mean there is a strong gradient in strength. But when we often talk about "depth" in sports, we typically say that "deep" teams or "deep" leagues have a swallow gradient. Think about teams having "deep benches".