Group-by correlation vs All observations correlation Let's suppose that I have a dataset with datapoints about footballers.

The data are about footballers' performance and information (e.g goals, assists, injuries, age, weight etc) on a monthly basis for the last 2 years.

My goal is to see how the performance and status of a footballer at a particular month is related to his performance and status of the next month.

At a first stage, I just want to run some correlation to detect some of these relationships.

In this case, does it make sense to run a separate correlation at each footballer's data of the last 2 years and then average the correlation results across players or directly run a correlation across all footballer's data at any month?
The name of the procedure you are looking for is


  Autocorrelation


This procedure looks a lot like the first you describe.

Answer fot this question in ResearchGate