So instead of starting straight out the door with some deep insight into Excel, I thought it better to provide an overview of a data analysis pathway (of sorts ;)).
Generally when working in sport we collect 2 different “types” of data, one thats collected/altered intermittently (player information, testing data, anthropometrics, max velocity, min/max heart rate, seasonal information) and one thats collected on a regular basis (GPS/HR, VBT, Wellness, Screening, HRV etc.).
I like to store these 2 “types” on separate spreadsheets and then pull them together when needed using PowerPivot (will be covered later in the blog) to produce reports or further analyse the data. The benefit of having it this way is that it helps reduce excessive data building up in one sheet which can really slow down some computers (and most people in sport won’t have the newest processor to speed things up either!). Similarly if you go down the analytics rabbit hole too far, over time data such as GPS can really buildup quickly so having the ability to quickly access a personal details file can be quite beneficial.
So that’s the first tip done with……short and sharp!
Join me the next blog….The first step…2!
EDIT – 30/01/2019
If you have experience with R, it can help streamline these processes by automating them to a much greater degree than PowerPivot/PowerQuery allow.
SportSciData 