#20 Age x Minutes Played in Top 5 European Leagues

Considering the suspensions of all major leagues, I thought it would be a good chance to catch up on how each one. Specifically here I’m taking a look at the distribution of minutes played by players in each team by the age of those players. The inspiration for this came from Real Sociedad and seeing that the core of their team has been a bunch of early twenty year olds and they currently sit in 4th should the leagues end now. This did seem unusual, but to compare with other teams this sparked a project that I have come across much more time to complete.

The data for this analysis has come from transfermarkt.com. Using the helpful tutorials on FC Python, specifically https://fcpython.com/scraping/introduction-scraping-data-transfermarkt, means all of the data you see is possible to get into a much cleaner, easier to use table or dataframe.

Minutes played is in all competitions during the 2019/2020 season up to the latest round of games before league suspensions.

I’ve taken a look at the top 5 European leagues and noted down some interesting, some weird and some funny things that came up.

La Liga

  • Real Sociedad

The initial inspiration for this project, so it’s nice to confirm the intuition that allocating lots of minutes to a younger group of players isn’t the norm. They have done well this year, I expect this team to have players poached sooner rather than later.

  • Real Madrid

What struck me with this was the gap between the core 7/8 players in their prime ages and the rest of the squad. They are always in ‘win now’ mode so it’s hard to ease in any youngsters, especially with the expectations of the last decade. But they’re going to need to start to trust a few more of the younger players they actually have an abundance of.

  • Atletico Madrid

In my head, Atletico’s team is full of 30+ year olds. They are all just passed their prime and have all the experience and tactical nouse a single team could contain. Then I see that the majority of their team is late 20s, actually just hitting their prime. They’ve got some kind of weird, Simeone style conveyor belt going on behind the scenes there.

Ligue 1

  • Lyon/Lille

Another case of lots of minutes played by young players, not too surprising that it’s Lyon and Lille. However worth pointing out again because this is still very much out of the ordinary and some teams seem to be able to consistently do this.

  • Rennes

This outlier up in the top left corner is Eduardo Camavinga, born on November 2002. He’s still 17. He’s on course to play 3000 minutes this year at centre midfield. He’s pretty good.

  • Montpellier

This other outlier in the top right is Vitorino Hilton, born in September 1977. He’s 42. He’s on course to play 3000 minutes this year at centre back. I had never heard of him before. He’s 42 and playing 3000 minutes in Ligue 1. I have gained much respect for him.

Bundesliga

  • Gladback/BVB

Obligatory lots of minutes for young players alert here. No surprise from Dortmund, but Gladbach are just a notch or two below in terms of the quality and quantity of minutes they’re getting from younger players this year.

  • Liepzig

RB Leipzig should also be in the lots of minutes for young players, but I thought they deserved a separate mention just because they ONLY play young players. There might be a virtual barrier around the training ground which doesn’t let you in after your 30th birthday.

  • Paderborn

Paderborn are currently bottom of the Bundesliga and look to have generally spread the minutes around, maybe trying different players or tactics to find something that works. I haven’t watched them. But interesting that the player with most minutes played is 22 year old Sebastian Vasiliadis in centre midfield. Is he the player the coaches trust the most? Or have they had injury troubles to other key players? He could be staying in the Bundesliga next year.

Serie A

  • Juventus

If there was ever a ‘win now’ team’s age profile, it would be this one. High proportion of minutes given to age 30+ players means that surely a rebuild is coming soon. De Ligt/Demiral are probably the start of that. (Note Buffon in the bottom right skewing the x-axis for every other team.)

  • AC Milan

The only really negatively correlated distribution I’ve seen, lots of minutes for young and not so many minutes for old players. I’d heard that Milan had made a decision to go in a different direction than overpaying just-past-their-prime players on long contracts, seems like they’re at least giving younger guys a go.

  • Atalanta

Special mention here goes to the island of players in their prime that Atalanta seem to have collected together. Hopefully they have a Gasparini type conveyor belt ready to go.

Premier League

  • Dwight Mcneil

This is probably my favourite distribution of all. And yet there is nothing actually surprising about what there is to see. Burnley are a team of all old/in their prime players, and then there’s Dwight McNeil. Come on Sean, give him someone from his own generation to talk to at least.

  • Wolves, Sheffield Utd don’t rotate

There’s definitely something to be said here about team understanding and having consistent line-ups. All these teams have a group of players playing the majority of their minutes, all these teams arguably perform above expectations. This may be confirmation bias as I haven’t checked the cases where core teams underperform. Wolves have played more games than the other teams in Europe, and still don’t rotate. Looking at you Conor Coady at 4000+ minutes already.

  • Aston Villa

The obligatory team with lots of minutes for young players is Aston Villa? They’re not especially seeing the success that other synonymous teams around Europe are having, probably due to this being mostly debut seasons all at once in a relegation fight.

That about wraps it up, if there are any interesting things you have spotted then give me a shout! Once again, this wouldn’t have been possible without starting off with getting the data from transfermarkt so huge props to FCPython and their website which does a great job. Check them out at @FC_Python.

@TLMAnalytics