This content originally appeared on Website and blog of Front-end developer and web designer, Dan Davies and was authored by Dan
For the past few months, I have been helping my lad with his data analyst role that he’s volunteering to do for our local team.
Armed with a VEO camera, a spreadsheet and a good nights sleep after a match, we have been building up a ton of data on the team and opposition which after 11 or so games is starting to show an interesting picture.
So what is VEO?
The camera films both halves of the pitch during the match which once uploaded utilises AI to generate events from the match such as shots, corners and goals allowing you to review and feedback to coaches and players. It’s actually very cool shit.
Clipping the game allows us to look at the game and see what went well, what didn’t and look at how things could improve or share ideas on how to do things differently. Basically Monday Night Football punditry but we’re sat on the sofa.
Being able to watch the game back is where we are able to get a lot of the data that we capture. VEO tracks things like corners, shots and goals but it’s not 100% accurate so we have to watch back and amend where it sees a long throw as a corner or a shot as a pass back. The system does have more analytical tools for a cost so for now, we have been doing it the old fashioned way. Sitting down with a mug of tea and counting every pass, every shot and adding to the spreadsheet. From there we can work out passing stats and possession. One thing I would love to do is track passes into zones like defence, mid and final third as well as forward, backward passing as this opens up a whole new view of the game and performance but this requires watching back several times which I could do but life gets in the way.
But that’s not enough
I always thought knowing possession, shots, corners and maybe crosses was enough to see how a game went but the more I delve into it, the more I realise there is a lot more detail you can get from watching and recording.
Let’s take a corner. Is it from the left, the right. Was it an in swinger or out swinger. Did it go to the near post, or far post. What happened after? I’ve been tracking corners and that very detail.
Sad bastard eh?
Goals are goals but what about the goal data. Was it a shot, a header. Which foot, where was it scored from, who assisted it, what was the assist. I’ve tracked that too.
Taking it even further
I wanted to look at working out xG (expected goals) but this is harder than I thought but something I am aiming to do. You have to give weight to the shots taken such as if it’s outside the box, it’s less chance of going in compared to a shot from inside the 6 yard box so you score them differently. Even the goalkeepers position and if he’s moving can have an effect so something else to track.
Once you consider all this and have your numbers, you should be able to work out xG.
Now of course, Premiership clubs have cameras dotted around the grounds, computers and proper data people to work this out, not some designer who’s working it out as he goes.
With regards opposition, I would love to spend time tracking the teams we play, gaining info on how they perform but for now, all I can really track with the time is their passing stats, shots, corners and anything else tracked in VEO. Also, TV coverage is non existent and you have to rely on any YouTube or Twitter footage at this level so having that kind of data is impossible.
I’ve watched a few players to see if the reports added up. One player was given man of the match against us. But the stats showed a very different picture. 9 passes all game, 0 shots, beaten to the ball 5 times but this goes often unnoticed when you are living in the moment of the game. Truth be told, I have been sceptical of a lot of players who have proven to have done really well or some not so well but that’s the way it is. A match is full of passion, mistakes, good luck, bad choices and data is just cold hard facts that shouldn’t define a team’s or players performance but should not be ignored.
Results
One part of the data that does interest me is the goal timings. I’ve been tracking every goal scored this season and the time. The goals are added to zones like 1-4 min, 5-9 mins and so on up to 90min and this season so far, 30 goals have been scored between 40-45+ mins making it 10.9% of all goals scored, 8 more than than those goals scored in the 90+ minute which stands at 22 goals and 8% of all goals. It gives me an idea on which team starts well or can’t manage the game out.
Of course this doesn’t mean I can predict the games but it does give me an idea on how teams may play. One team has scored 16 goals all season and 5 of them came in the first 14 mins which suggests they go for it early on, having seen them play, that is exactly what I saw. Maybe it was luck they played that way in the game I saw. They may also go on a 10 match streak where they can’t score for shit but it does paint a picture of what did happen and should be explored further.
That’s it for now
Data is not the be all and end all when it comes to football. The most important part of any team is players and coaches, the tactics, the training, the data is just a tool to help diagnose issues and provide solutions and something to keep an eye on. It’s much harder to come by the lower you go and it requires a lot of work and maybe, and I still haven’t worked this out yet but maybe it’s nowhere near enough to have such an impact but I’ll keep working with the lad to find ways to extract what we can and help the cause.
It is hard work, long hours and is probably not really of interest to many but it’s bloody interesting and lots of fun looking at it especially with it being football.
Related links
This content originally appeared on Website and blog of Front-end developer and web designer, Dan Davies and was authored by Dan
Dan | Sciencx (2024-09-12T19:47:09+00:00) Data analysis in lower league football. Retrieved from https://www.scien.cx/2024/09/12/data-analysis-in-lower-league-football/
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