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How successful are transfers in the Premier League?

Everyone has an opinion on the quality of the transfers of their favorite club in the Premier League. But can we actually measure successful transfers? Here is the table of successful and unsuccessful transfers in the Premier League. The explanation follows below:

ClubSuccessful transfersUnsuccessful transfersLosses per playerLosses per yearProfit per youth player
Tottenham Hotspur88%12%5.341.0685.87
Watford84%16%3.140.6280
Everton84%16%3.440.68811.48
Leicester84%16%5.371.0742.69
Chelsea83%17%4.740.9484.28
Newcastle80%20%2.80.560.28
Bournemouth80%20%2.580.5160
Brighton80%20%1.80.360
Arsenal78%22%7.851.574.65
Manchester City77%23%8.281.6565.98
Sheffield76%24%0.650.130.97
Liverpool75%25%10.452.0910.44
Burnley74%26%1.530.3060
West Ham73%27%1.830.3663.46
Huddersfield71%29%1.170.2341.65
Average70%30%3.930.793.49
Cardiff70%30%1.10.220
Norwich60%40%3.510.7025.39
Southampton59%41%6.531.3066.26
Wolverhamperton55%45%1.40.280.51
Crystal Palace52%48%3.230.6468.25
Manchester United52%48%9.121.8242.91
Aston Villa43%57%2.510.5021.9
Fulham34%66%2.170.4343.53

The first column indicates the percentage of successful transfers. Here we mainly mean financial success. We have looked at over 800 players who have left their club in the past five years. The basic idea is that if a club received less money than what they paid for the player then it would be an unsuccessful transfer. The idea being that if he was a success at the club, he would have been worth more.

Of course, there are many exceptions. Especially if the player is playing quite some time for the club. For that reason we used a depreciation formula to decrease the amount paid for the player for each year that he actually played at the club. If a player played 5 years for the club, the transfer would be an automatic success this way/ Loan fees were also taken into account.

The second column indicates the percentage of unsuccessful transfers.

The third column indicates what, on average, an unsuccessful transfer cost the club in the past five years in millions of pounds. The fourth column is this amount divided by 5. This number is basically the amount that the club can spend each year to prevent 1 unsuccessful transfer every 5 years. Adding FBM statistics to your data analysis costs a fraction of this amount. Adding FBM statistics immediately reduces the risk of an unsuccessful transfer because we do our own data acquisition and the FBM approach is completely different than any other data provider. For that reason we are 100% complementary to existing data analysis. With FBM statistics you have another data source to confirm or disconfirm that a player will be a success at the club.

The fifth column is how much money a club has made with the transfers of their own youth players. This is an indication on whether the club ought to concentrate on scouting or youth development or both. As FBM uses Bayesian statistics FBM needs way less data before we can draw well founded conclusions. So FBM statistics is ideal for the youth development program of the club as well as youth scouting.

Some caveats in determining successful transfers

First let me stress that these numbers are an indication. One can always use a slightly different formula to divide transfers between successes and failures. Nevertheless, other approaches will basically show the same picture. 

The second point is that only players that have actually left the club are counted. If you think that there are still a lot of bad players on the roster of the club, then it is likely that the club will have worse numbers the year these players leave the club. The opposite is also true. If a club has just shed it’s dead wood, then they will probably do better in the future. But for now, this is how it looks.

Thirdly, and this connects with the second point, the numbers are relatively small. On average we considered about 30 players per club, with only a few of them unsuccessful transfers. That means that if next year a player with an unsuccessful transfer leaves the club, that it will have some impact on these percentages.

Two examples of how FBM Second Opinion would have prevented unsuccessful transfers

Paul Gladon

Paul Gladon transferred for 1.8M pound from Heracles to Wolverhampteron. Here is how FBM statistics view Paul Gladon in his last match for Heracles (see here for an explanation of how to read an FBM contribution chart).

Sparta 1 vs Heracles 1 2018-05-06 20:00:00 (2-5)

We think that it is quite likely that Wolverhampteron would have saved 1.8M euro if they had seen this chart and all our other data on Gladon.

Davy Klaassen

Although Klaassen’s FBM contribution chart is a lot better than Gladon’s chart, it still doesn’t justify the transfer from Ajax to Everton, especially if Everton wanted to use Klaassen to support their attack, rather than their defense:

The Netherlands vs Ivory Coast June 3rd 2017 (5-0)

Very telling is that even though the Netherlands won 5-0 Klaassen’s attack contribution hardly rises. This chart would and all our other data of Klaassen would probably have prevented Everton from misspending 24.3M pound.

Feyenoord needs to defend their #3 spot rather than go for #2 or #1

A huge club like Feyenoord ought to always play for the championship. Nevertheless, the distance between Feyenoord and PSV (currently #2) and Ajax (currently #1) proofs to be to big. In this article I react to the wonderful article “Wat brengt de nabije toekomst voor Feyenoord?” by Enrico Raho. Not to criticize, but to show the differences between a classical approach to football statistics as has been excellently written down by Enrico Raho and our FBM Bayesian approach.

Continue reading “Feyenoord needs to defend their #3 spot rather than go for #2 or #1”

How Heracles found Dalmau using FBM statistics

Dalmau, the Spanish striker, of Heracles, a Dutch Eredivisie club, has been a huge success in his first season in the Eredivisie. He became the number three topscorer in the Eredivisie with 19 goals scored. Quite an achievement for a striker who came to Heracles without a transfer fee being paid and who played for a very reasonable salary.

Topscorers in Dutch Eredivisie season 2018/2019

Heracles, the Dutch Eredivisie club, wondered why they didn’t have a Fran Sol like striker playing for their team. Willem II, one of the competitors of Heracles, found the Spanish striker and he turned out to be quite successful for Willem II. Heracles asked us to find them a Fran Sol like striker.

Through our network we were pointed toward Dalmau. We analyzed him using our proprietary FBM statistics (see here for an explanation) and presented him to Heracles. The scouting of Heracles already had Dalmau on their list of possible targets as he was a Spanish striker whose contacted ended in the summer of 2018. During the meeting we showed Heracles the following contribution chart of Dalmau and Heracles decided to pursue this opportunity. Their technical staff flew to Spain to watch Dalmau live. Within weeks a deal was struck and the rest is history.

Athletic Club Bilbao 2 vs Villarreal II 2018-05-20 20:00:00 (1-3)

As is the case with 90% of the 11.000 players in our database, Dalmau’s contribution chart today is pretty much the same as it was one year ago. Normally, that would not be significant because most graphs are created using averages and averages only change a little through time. But we limit the use of averages as much as possible as an average often distorts a clear view of the player. FBM statistics is very sensitive. In most cases data from 6 matches ago has no influence on the chart of the most recent match. Nevertheless, Dalmau, as most other players, produces the same chart each and every match as can be seen of his most recent chart here:

Heracles 1 vs Excelsior 1 2019-05-12 14:30:00 (4-5)

Basically both charts indicate that it is highly likely that Dalmau strengthens the team overall and the attack of the team, but it is highly unlikely that Dalmau strengthens the defense and transitioning of the team. Normally, that wouldn’t be good, but in the case of a striker we ignore all of that because the only real task for a striker is to score. Preferably, 19 times as in the case of Dalmau.

In April 2018 we calculated that Dalmau would have a replacement value of 1.75 million euro for Heracles at the end of the 18/19 season. In the summer of 2019 Dalmau transfered to FC Utrecht for a transfer fee of 700.000 euro and Dessers (a player valued at 1 million) transfered from FC Utrecht to Heracles.