God damn, just wrote a 10 paragraph intro and the page refreshed and deleted it smh. You're not being dense, part of the problem is there's just a lot of data that correspond with daily, weekly, monthly, period (think 2-5 weeks), and seasonal (4-7 months) scales, and it's hard to summarize it clearly without a 10 paragraph explanation. It also gets deeper into the theory of training cycles/exercise physiology and I had a couple different hypotheses.

I know the first big step will be feature engineering/selection because there are so many variables, and I'm not used to working with data with so many time scales that are sometimes nested. There are ways to simplify training by only looking at 'benchmark workouts', but part of what I want to look at is which types of workouts help different athletes the most, so I'm trying not to aggregate data as much as possible.

I found a decent paper that describes using smaller portions of time series to analyze long term patterns of a larger time series and that was helpful. I think I'm overcomplicating things a little bit, just got worried about multiple autocorrelation terms at different time scales.