From the terraces to social media, football transfer fees have long been a heated topic of discussion amongst supporters of all teams.
With the injection of huge sums of cash from broadcasters and sponsors, transfer fees have multiplied astronomically over the past 30 years.
Could the figures even reach £1 billion? ($1,809,136,922 AUD)
The team here at JD Sports looked at the biggest transfer in each of Europe’s top six leagues since 1980 to figure out when and where the first billion pound player will be.
We predict that France will be the first country to see a £1 billion footballer play in its league, with the transfer due to happen before 2050.
Based on Transfermarkt data and current transfer trends, we believe the first £1 billion football transfer will be in 2048.
Why France? This can largely be attributed to PSG and their huge spending since their takeover by Qatar Sports Investments in 2011.
Since that purchase, the Parisian club has spent over £1.2 billion on transfers so it’s perhaps not surprising to think that, based on this trend, Ligue 1 is the most likely league to see the first ten-figure footballer.
Despite the Italian league being seen as more of a stepping stone for the best in the business in recent years, between 1980 and 2000, Serie A teams broke the world transfer record nine times.
This, in addition to Juventus’ acquisitions of Cristiano Ronaldo and Matthijs de Ligt in recent seasons, has catapulted Italy’s stake in the billion-pound player race.
With these factors in mind, we predict that Serie A will see a ten-figure footballer by 2055.
It may not be too surprising a date, given that Inter Milan and Napoli have both spent big too in recent seasons to try and close the gap to the Old Lady, who have dominated the Italian game for the past 10 years.
La Liga is home to two football giants, Barcelona and Real Madrid, who are responsible for six out of the top 10 biggest transfers of all time.
Furthermore, either Barca or Real has broken the world record transfer fee eight times, with Madrid achieving this feat five times since the turn of the century alone.
Despite this duopoly, the biggest fee paid by a Spanish team to date is the £116 million that Atlético Madrid paid for João Félix in 2019.
Our calculations work out that Spain will see a billion-pound player in its league come 2072, however.
This could be credited to PSG’s recent ability to blow teams out of the water with unprecedented fees as well as the rise of Juventus’ spending power in the last few years.
It may come as a shock that the Premier League is only expected to buy a player for a billion in 2085.
The English league has often been seen as the division to most accelerate transfer fees but the Premier League still hasn’t seen a player signed for £100 million, something which can’t be said for Spain and France, with the record incoming still the £89 million that Manchester United paid for Paul Pogba back in 2016.
English teams, however, do account for 22 of the 50 most expensive transfers of all time, with Manchester City making seven of those alone.
There wasn’t too much to split England and our next country; in fact, there was only one year between the two. According to our research, expect Germany to see a billion-pound footballer in 2086.
It may come as a surprise that a German team has never broken the world transfer record for a footballer and only has one of the top 50 most expensive fees – the £70 million that Bayern Munich paid for Lucas Hernandez in 2019.
With this in mind, don’t expect the Bundesliga to be anywhere near the first billion-pound footballer.
The biggest transfer fee a Dutch team has paid for a footballer is only £14 million – this is what it cost Ajax to bring Daley Blind back to the club from Manchester United in 2018.
It makes no surprise then, to hear that Eredivisie will be the last of Europe’s top six leagues to sign a player for £1 billion.
We predict it could take up to 2161 – nearly 150 years – for the Netherlands’ top division to sign a ten-figure footballer.
All transfer data is from Transfermarkt. The data was put through a Polynomial Regression Data Fit tool in order to add scientific weight to our predictions.