Kind of an abnormal post around here I’d guess, but I’m currently a second year masters student in Strength and Conditioning with a huge interest in sports science and working with data. Early on I’ve made the mistake of collecting too much data from my athletes and getting lost in it.

Now I’m super passionate about learning all I can about the art of drawing meaning from data.

What are either some basic skills, base knowledge areas (statistics, math etc) and resource recommendations for really diving deep into data science?

For context I took basic stats in my undergrad, and am taking graduate statistics now (which is more aimed at research, whereas I’m an applied practitioner). I’m currently learning python and the majority of the data I’ll see will be performance KPI’s, and GPS workloads for field sport athletes. So lots of time series data and tracking things over time to look for significant changes.

Things I’ve done in excel are rolling standard deviations/averages, exponentially weighed moving averages, a bit of smallest worthwhile change and CV.

I’m definitely a noob relative to you folks, but any guidance on pursuing this new passion of mine is much appreciated!

P.s. huge goal is to someday incorporate machine learning to give training/nutrition recommendations based on past patterns and responses (lofty goal I know haha) but very determined about this!