How does Premier League transfer spending affect performance?

statistics

Premier League

Inflation adjustments for historical transfers, and an assessment of net spend as a predictive metric.

Author

John Knight

Published

17 August 2026

Fernando Torres made an acrimonious move from Liverpool to Chelsea for £50 million in January 2011. (Wikimedia Commons)

“Here we go!” You’ve got to admit it’s a good catchphrase. Transfers are big business in modern football, and transfer news and rumours have become entire careers for some personalities. But how much do transfers really affect future performance? And what is the best way to measure that?

I looked at data from the fantastic website Transfermarkt to compare all transfers in the Premier League since 1992/93. The first challenge was to adjust all transfers for inflation. There are different ways to approach this, and they are all fairly arbitrary, but I normalized each transfer as a proportion of the total Premier League signings in that season and then added some smoothing in case there were outlier seasons that skewed the results. The top 10 biggest inflation-adjusted signings by Premier League clubs were as follows:

Player	Season	From	To	Adjusted Fee
Most Expensive Premier League Signings
1992/93 to 2025/26 (inflation-adjusted to 2025/26 prices)
Rio Ferdinand	2002-03	Leeds	Man Utd	£228,408,628
Juan Sebastián Verón	2001-02	Lazio	Man Utd	£211,526,252
Fernando Torres	2010-11	Liverpool	Chelsea	£200,657,895
Didier Drogba	2004-05	Marseille	Chelsea	£191,168,091
Alan Shearer	1996-97	Blackburn	Newcastle	£185,466,707
Wayne Rooney	2004-05	Everton	Man Utd	£183,719,984
Andriy Shevchenko	2006-07	AC Milan	Chelsea	£177,345,789
Michael Essien	2005-06	Lyon	Chelsea	£173,789,174
Paul Pogba	2016-17	Juventus	Man Utd	£159,835,299
Rio Ferdinand	2000-01	West Ham	Leeds	£150,617,284

It’s surprising for Rio Ferdinand (£228m adjusted for inflation) to come out on top, not least because he is a defender. I remember thinking at the time it was a crazy fee (£29m from Leeds in 2002, rising to £33m with add-ons) but he spent the following decade as a mainstay of the Manchester United and England defence, so I think we can safely say Alex Ferguson is a better judge of a player than I am.

Despite the huge volumes flying around the Premier League in recent years, it is notable that only one transfer in the last 15 seasons (Paul Pogba to Man Utd for inflation-adjusted £160m) makes the top 10. Why is this? I think it’s fair to say there haven’t been any seismic transfers for quite a while. The last couple of summers are a good example: big-money moves have seen Alexander Isak join Liverpool, Elliot Anderson join Manchester City and Morgan Rogers join Chelsea. But these are all typical moves: the best player from a moderate-sized club to a bigger one.

To imagine a modern equivalent of Fernando Torres joining Chelsea (£200m inflation-adjusted), you would have to consider a star forward from a Big Six club forcing a move to another Big Six club. Perhaps Bukayo Saka to Man City — how much would that transfer fee be? And Alan Shearer (£185m inflation-adjusted) was unquestionably the league’s best goalscorer when he moved to Newcastle at age 26. What price Erling Haaland if he moved to another Premier League club this summer?

I’m sure many of you are curious how other big signings stack up when adjusted for inflation. Below is a table showing the biggest adjusted fee paid by each of the 51 clubs who have competed in the Premier League. This will be a head-in-hands moment for fans of certain teams.

Team	Player	Season	From	Adjusted Fee
Most Expensive Premier League Signing by Club
1992/93 to 2025/26 (inflation-adjusted to 2025/26 prices)
Man Utd	Rio Ferdinand	2002-03	Leeds	£228,408,628
Chelsea	Fernando Torres	2010-11	Liverpool	£200,657,895
Newcastle	Alan Shearer	1996-97	Blackburn	£185,466,707
Leeds	Rio Ferdinand	2000-01	West Ham	£150,617,284
Liverpool	Fernando Torres	2007-08	Atl. Madrid	£147,300,861
Man City	Robinho	2008-09	Real Madrid	£143,710,278
Arsenal	Dennis Bergkamp	1995-96	Inter	£115,916,692
Blackburn	Chris Sutton	1994-95	Norwich	£115,346,797
Tottenham	Sergiy Rebrov	2000-01	Dynamo Kiev	£104,273,504
Middlesbrough	Fabrizio Ravanelli	1996-97	Juventus	£100,770,244
Aston Villa	Stan Collymore	1997-98	Liverpool	£99,533,800
Everton	Duncan Ferguson	1994-95	Rangers	£93,815,395
Fulham	Steve Marlet	2001-02	Lyon	£87,391,127
Wimbledon	John Hartson	1998-99	West Ham	£87,280,785
West Ham	Sébastien Haller	2019-20	Ein. Frankfurt	£70,455,070
Leicester	Youri Tielemans	2019-20	Monaco	£63,409,563
Nott'm Forest	Pierre van Hooijdonk	1996-97	Celtic	£61,822,236
Coventry	Robbie Keane	1999-00	Wolves	£61,538,462
Wolves	Fábio Silva	2020-21	Porto	£56,364,056
Sunderland	Asamoah Gyan	2010-11	Rennes	£54,880,792
Sheff Wed	Andy Sinton	1993-94	QPR	£54,666,078
Bolton	Nicolas Anelka	2006-07	Fenerbahce	£48,499,304
Crystal Palace	Christian Benteke	2016-17	Liverpool	£47,493,917
Birmingham	Emile Heskey	2004-05	Liverpool	£46,277,574
Portsmouth	Peter Crouch	2008-09	Liverpool	£45,786,763
Southampton	Sadio Mané	2014-15	Salzburg	£45,250,766
West Brom	Lee Hughes	2002-03	Coventry	£44,688,645
Bournemouth	Jefferson Lerma	2018-19	Levante	£42,977,593
Watford	Ismaïla Sarr	2019-20	Rennes	£42,273,042
Brighton	Georginio Rutter	2024-25	Leeds	£41,029,386
Stoke	Giannelli Imbula	2015-16	Porto	£40,784,395
Ipswich	Hermann Hreidarsson	2000-01	Wimbledon	£39,102,564
Charlton	Jason Euell	2001-02	Wimbledon	£37,240,537
Sheff Utd	Rhian Brewster	2020-21	Liverpool	£36,636,637
QPR	Christopher Samba	2012-13	Anzhi	£35,547,786
Swansea	Wilfried Bony	2013-14	Vitesse	£35,497,363
Derby	Giorgi Kinkladze	1999-00	Ajax	£34,188,034
Wigan	Emile Heskey	2006-07	Birmingham	£30,312,065
Norwich	Dean Ashton	2004-05	Crewe	£29,792,430
Brentford	Igor Thiago	2024-25	Club Bruges	£28,992,928
Cardiff	Gary Medel	2013-14	Sevilla	£28,841,608
Huddersfield	Terence Kongolo	2018-19	Monaco	£28,182,028
Burnley	Chris Wood	2017-18	Leeds	£24,153,750
Hull	Abel Hernández	2014-15	Palermo	£23,609,095
Bradford	David Hopkin	2000-01	Leeds	£22,013,295
Barnsley	Gjorgji Hristov	1997-98	Partizan	£21,328,671
Oldham	Ian Olney	1992-93	Aston Villa	£19,116,809
Reading	Greg Halford	2006-07	Colchester	£18,187,239
Swindon	Jan Åge Fjørtoft	1993-94	Rapid Vienna	£11,422,763
Luton	Ryan Giles	2023-24	Wolves	£5,287,336
Blackpool	DJ Campbell	2010-11	Leicester	£5,145,074

I mentioned Roman Abramovich above, and his arrival into English football truly was a game-changer. In Abramovich’s first two seasons, Chelsea’s net spend was equivalent to about £1.5 billion today. The table below shows the top 10 net-spend seasons by Premier League clubs, with Chelsea & Abu Dhabi-owned Manchester City occupying all of the top 8 spots.

Team	Season	Net Spend (2025/26 Equivalent)
Biggest Single-Season Net Spend
Premier League 1992/93 to 2025/26 (inflation-adjusted to 2025/26 prices)
Chelsea	2003-04	£826,806,085
Chelsea	2004-05	£761,828,043
Chelsea	2022-23	£616,700,533
Man City	2010-11	£474,529,605
Man City	2008-09	£414,630,519
Man City	2009-10	£380,628,561
Chelsea	2010-11	£347,313,596
Man City	2017-18	£321,195,464
Man Utd	1998-99	£299,804,526
Blackburn	1998-99	£292,877,367

Given the obscene levels of spending, it’s no surprise that Chelsea and Man City have hoovered up a lot of trophies. I’m not going to pull up any trees by concluding that spending leads to success, but let’s try drilling down a bit to see how strongly various spending measures correlate with future team performance.

Is net spend the best measure?

An obvious starting point is comparing each team’s net spend in the summer transfer window with their performance that season, as measured by points-per-game (PPG). Prior to the window’s introduction in 2002, I have used the 1st of September as the cut-off.

As expected, higher net spend is associated with higher PPG, with a Pearson correlation coefficient of 0.26. But is net spend a useful metric? What if we take a separate look at the total fees paid and received by each club? Also, rather than just looking at summer spending, I considered the summer window plus the previous two seasons’ transfer activity to account for the overall investment in the team rather than just the most recent window. The correlation coefficients for the six combinations of these two variables can be seen below.

Metric	Window	Correlation
Total Fees Paid	Summer	0.44
Total Fees Paid	Summer + prev. two seasons	0.58
Total Fees Received	Summer	0.27
Total Fees Received	Summer + prev. two seasons	0.39
Net Spend	Summer	0.26
Net Spend	Summer + prev. two seasons	0.44

Unsurprisingly, correlation was improved by including the previous two seasons. But we can also see that net spend isn’t necessarily the best metric; the strongest correlation was found using total transfer fees paid, disregarding fees received altogether.

There is also the question of whether the cumulative sum of fees is the best metric; it is possible to sign a large quantity of players who don’t improve the team. What if we instead look at the biggest fee paid?

Metric	Window	Correlation
Biggest Fee Paid	Summer	0.55
Biggest Fee Paid	Summer + prev. two seasons	0.64
Biggest Fee Received	Summer	0.20
Biggest Fee Received	Summer + prev. two seasons	0.31
Biggest Paid - Biggest Received	Summer	0.25
Biggest Paid - Biggest Received	Summer + prev. two seasons	0.23

That’s an interesting result. The strongest correlation (r = 0.64) to teams’ performance is found by using the biggest transfer fee paid in the summer and the prior two seasons – a larger corelation than with total fees paid. There is some intuition to this result: at any point in time, the biggest transfer fees will generally be paid by the biggest clubs. Whereas, total fees paid and received can be confounded by other aspects of team performance. For example, a team buying a lot of players may be doing so because they have been underperforming and need upgrades, while a team making one or two expensive sales may be doing so off the back of good team performance. So it’s not clear which direction the causal arrow would point.

Controlling for team effects

Of course, looking at overall relationships between transfer spending and performance just leads to a conclusion that a seven-year-old could figure out: rich clubs like Manchester City spend more on players than small clubs like Luton, and therefore they get better results. In addition, clubs go through good and bad cycles, so we can’t just assume each season’s performance is entirely down to recent transfer activity.

To control for these factors, I trained multiple linear regression models with the original transfer features and additional features containing the team as a categorical variable, plus their prior season PPG and goal difference per game (GDPG).

I accounted for promoted teams by training a separate model for the effect of going from the Championship to the Premier League which also included a time variable; as hypothesized, the time variable had a negative slope because the gulf between the Championship and Premier League has increased through the years.

The coefficients from the multiple linear regressons are shown below. The farther the dot is to the right, the more PPG increases as that variable increases.

The strongest predictor of PPG was total fees paid over that summer and the two previous seasons, followed by net spend over the same period. Both the total fees received in the summer window, as well as the size of the biggest fee received in the summer window, had a small negative correlation with the next season’s PPG.

Finally, we can deconstruct the summer window plus two previous seasons into its constituent parts to see how each correlates with PPG (see below). When it comes to fees paid (the plot on the left), in the current summer the biggest fee carries more weight than the cumulative total, whereas it’s the opposite the season before: the total spent is more important. In fact, the total amount of fees spent across the previous season seems to be the most powerful single measure. Going back two seasons, the effects are close to zero.

As for transfer fees received (the plot on the right), the effects for both the cumulative total and the biggest fee are similar. In the current season’s summer window, larger player sales have a small negative correlation with PPG. One season prior, the effect is close to zero, and two seasons prior it is a small positive effect. It seems like selling players for decent fees isn’t an especially bad thing, but perhaps it is some short-term pain for long-term gain, which makes sense.

Conclusions & limitations

To summarize the main findings:

Total fees paid are a better predictor of performance than net spend, with total fees paid over the summer plus the previous two seasons the strongest overall predictor.
Fees received in the current summer window have a small negative correlation with performance.
Total fees paid in the previous season are a better predictor of performance than fees paid in the summer window.

This study has some obvious limitations. Wages are not included, because frankly I don’t know an easy and reliable source for tracking historical player wages. Transfer fees on Transfermarkt are not gospel – some fees are undisclosed, estimated, or may include add-ons. In the modern era the loan-to-buy deal is becoming more commonplace, which means the value on the books may relate to a player who was already at the club the season before. My inflation measure is arbitrary; different methods may produce different results. Fees paid by promoted teams in a lower division may be falsely low because of the Premier League premium paid by top flight teams. And lastly, because spending and performance are interrelated, causality is hard to assess.

That said, I think there are some interesting high-level results and we can see how they pertain to teams in this year’s Premier League. Chelsea are comfortably the biggest spenders over the summer plus the last two seasons with £860m invested, while Liverpool fans will be hoping that the one-year lag benefits them this season after their massive £412m outlay on players last year.

As for negative indicators, both Newcastle and Aston Villa have received north of £200m in player sales, each with a single player going for £100m or more. The good news is, if they can withstand the short-term hit this season, their long-term prognosis may not be too bad.