I’ve written before about how learning to apply football data is like learning a foreign language. You learn the definitions of words, but the way you put those words together is kind of up to you. It can be artful.
However, that thought might be a little daunting, so let me offer an alternative metaphor. If you’re unsure how to use data or how it can be used, you can think of it like a map.
Now, a map has many functions, particularly in the modern app-based world. At their most basic, all maps help you to orient yourself in unfamiliar territory, and that’s what data can do as well. If you come across a player or team that you don’t know particularly well, you can look for which things they do a lot, and those they do very little of. Instead of checking for your location on a map in relation to the city centre, you can look for which things a particular striker tends to do and how many shots they take. It won’t tell you everything about them, but it’ll be a valuable start.
Once you’ve spotted some landmarks, you can zoom in a little further. If you were getting to grips with a town on holiday this might be checking the best route from hotel to beach. In the data, perhaps it’s something like “ok, I’ve seen that this player shoots a lot, now where or how do they shoot?”. Are these shots inside or outside the box? How many of them are headers? You can look at statistics for that, or you could use a shot map to help get to grips with it.
I hope that that makes the early stages of dealing with data less daunting. Just like how you shouldn’t need to be a geography expert to read a map, you shouldn’t need to be a data savant to get something out of stats.
There are a variety of ways we’ve tried to do this in the Twenty3 Toolbox, whether that be Discover and Insight algorithms to bring you similar players or new stories; visualisations to help see data; or rankings alongside the data.
Once you’ve got yourself oriented and feel a little more comfortable, knowing the basics, it’s easier to explore more freely. Even when you know an area — or a player or team — quite well, it’s always useful to return to the map to check things. Sometimes we forget street names; sometimes we need to check whether a player or team still excels in a skill we remember them having.
For example, Manchester City have always been a strong high-pressing team under Pep Guardiola, but has that changed in the 2020/21 season? Well, the number of ball recoveries in the opposition half has dropped to 29 per game, from around 32 per game in the past two seasons, but that’s still quite high relative to other teams in those years.
You could keep on zooming in, going into more and more detail in the data, and combining the data with what you see when watching the team or player in question. Much of the best statistical work is done by going back and forth in focus from data to video and back again.
How many times when using a map have you looked from map to road to map again, checking that the curve in the road ahead matches how it looks in your hand to be really sure that you’re in the right place? You want to keep checking that you’re in the right place.
However, there’s one final way that the map symbolism works, on a bit of a meta level. When people use maps as a metaphor, they tend to use it as if something is guiding you the way somewhere. They’re talking about treasure maps, really, with palm trees and a dotted line and a big ‘X marks the spot’. Some people try and sell data that way too.
However, maps aren’t like that, and neither’s data. Maps help you navigate, help you explore, can help stop you from getting lost (although only if you’re reading it correctly), and can help you find interesting new places.
We help our customers maximise the potential of football data. Whether you’re a data novice or expert, the Twenty3 Toolbox gives you the tools to do your job quicker and better.
If you think your organisation – whether in the media, broadcast, agency or pro club sector – could benefit from our product, you can request a demo here.