I'm trying to describe the behavior of a scatter plot I have. I'm looking at the results of a game that occurs in rounds where one player is voted out each round. I'm trying to find a correlation between how many rounds Player A (who wins a particular advantage in the first round of each game) ultimately survives and how many people voted for the person Player A wanted out in the first round. There are 22 iterations of this game total, and each iteration has one data point because there is only one Player A per game. However, each iteration of this game has a different number of rounds, and a different number of people voting in the first round.
Ex: Game 1 - 10 rounds, 12 people voting in first round
Game 2 - 12 rounds, 13 people voting in first round
So to get around this, I converted both variables into percentages (i.e., the percentage of rounds Player A survived vs. the percentage of people who voted for the person Player A wanted out). I ended up with a plot like this:
There are two distinct clusters that appeared, and the fact that there appears to be a negative correlation (r = ~0.349) in the top-right red cluster would be an interesting trend to note. However, I've done some reading on here that states that finding the pearson's r between two percentages is a bad statistical practice, even when the percentages are not compositional. My question has two parts -- 1) Would it be fair to say that there is a negative correlation in the red cluster? 2) Does anyone have suggestions for how to better perform this analysis if finding the correlation between the percentages is incorrect?