I have data on online competitions that are held weekly. I have data from 2001 all the way up to 2019 but I am considering the data from 2004-2007. Each competition has around 180 entrants, but it is not necessarily the same entrants each week. There are repeated individuals in a fair few of the competitions, yet there are some individuals who only participate once. Individuals essentially pick and choose each week whether they are going to participate or not. The data concerns each entrant's final score in the competition, and their placement in each competition amongst other variables that describe individuals performance.
So altogether, I have data on 180 entrants in each of 3 years worth of weekly competitions, with some individuals competing a lot and some competing once.
It's not repeated cross-section, as I'm not randomly sampling from a population each time, individuals are effectively choosing if they want to participate each week in a competition, and some individuals participate in many competitions.
It's not a balanced panel, as not all individuals participate in each competition.
It's not an unbalanced panel, as the data on those individuals who chose NOT to participate isn't "missing", we know where it is, it's because that individual decided not to participate. It's not like that individual did participate but we've lost the data on how they did during the competition.

Just wondering what type of data I have? This data set has been analysed before and the paper that used it described it as an unbalanced panel, but I'm not convinced.