All data is subjective, no matter how hard proponents of objectivity try to make you think differently. Because all data is subjective a player has different stats for different teams. To think that one set of data describes a player for every team is a simplification that many people are happy to make, because they feel football is too complex without simplifications. FBM takes a different approach and embraces complexity.

For that reason FBM player stats are always the stats for that player only playing for a specific team in a specific league. Most of the time this is of course his current team, but one can also easily look back to see how a player has done in different teams in different leagues.

What is harder to do, is to predict how a player will do in a different team. And it becomes a lot harder to predict how a player will do in a different team in a different league. The FBM transfer model solves this problem by using the power of Bayesian statistics. 

Basic principles of the FBM transfer model

The basic principles of the FBM transfer model are:

• The stronger the league, the less time and space a player gets, the harder it becomes for a player to get good stats. In other words, if a player transfers to a stronger league one may expect that his stats will deteriorate. Of course, this also works the other way around. If a player moves to a weaker league, he will get more time and space and he will probably do better.
• The stronger the team the player plays in, the better his teammates will be and the better his stats will be. In other words, if a player transfers to a stronger team his stats are likely to improve. And vice versa, if a player moves to a weaker team his stats will deteriorate.

The hardest part of predicting how a player will do is when a player transfers to a stronger league, but also to a stronger team. Or when he transfers to a weaker league, but also to a weaker team. Many bad decisions have been made by smaller clubs in weaker leagues that hiring a player in a stronger league would automatically strengthen the team. Unfortunately, there are many occasions where a player from a stronger league actually weakens the team.

Factors in the FBM transfer model

So factors that are used in the FBM transfer model are:

• The FBM stats of the new player.
• The FBM stats of the current player the new player is going to replace on the pitch or backup on the bench.
• The FBM League Strength score of the league the new player is playing in.
• The FBM League Strength score of the league the new team is playing in.
• The FBM Team score of the team the new player is playing in.
• The FBM Team score of the new team.

What the FBM transfer model does

The first step in the FBM transfer model is harmonizing the stats of the new player and the player he is going to replace or backup. This is done by using the ratio between the new league strength and the old league strength. And by using the ratio between the new team strength and the old team strength. This basically applies the two basic principles to the stats of the new player.

The second step is that the current player to be replaced or backuped by the new player is subtracted from his team, i.e. the team the new player is transferring to. Depending on his FBM player stats his contribution is taken out of the FBM club strength. After subtracting the current player from his team, we add the harmonized stats we found in the first step of the new player to the new team to see how the new team would do playing with the new player instead of their current player. The difference between playing with the current player and the new player is both expressed in a difference in FMB team strength and a plus or minus in the number of points a team is expected to get in the competition.

The third and final step is that the predicted stats of the new player playing for the new team are boosted a bit more if his presence strengthens the team. This reflects that if his teammates are going to play with a better teammate, then they are going to improve as well which then is reflected back onto the new player. This way the right new player can lift a whole squad. Of course the opposite also happens. So if the predicted stats for the new player weakens the team, then his teammates are also dragged down a bit which then reflects back on the new player whose stats deteriorate a bit again. That is why hiring the wrong player is not only a financial problem, but also a sporting problem bigger than just the bad player.

Based on the final predicted stats FBM also calculates what the replacement value of the player will be in one, two and three years. So the club will not only know whether the player is likely to be a good player for the team, but also whether the player is likely to net the team a million euro transfer fee or not, and if so in what time frame.

Validation

Unfortunately, there is currently not enough data to validate the FBM transfer model scientifically as until now only 21 transfers have been made where the FBM transfer model played a minor or major role. In total more than 100 FBM transfer reports have been created for clubs and agents, yet in most cases this has not resulted in a transfer. As most results are for clubs we are currently working for, we can only present the following table:

	Predicted success	Predicted failure
Actual success	15	4
Actual failure	1	1

There are two caveats:

1. In some cases it is hard to measure success. For instance, we would consider the player a failure but the club a success and vice versa.
2. The predicted failure, but actual success is quite high compared with the predicted failure and actual failure. This is in part due to the fact that when the FBM transfer report predicts failure clubs are less likely to hire the player so the chance of getting a predicted failure and an actual failure are way smaller than a predicted failure and an actual success. Also because in the latter case, the club has other sources (video scout and/or live scout) that disagree with the predicted failure. So the predicted failure but actual success category has a much bigger chance of happening than the predicted failure and actual failure category.

When you represent a professional club or a player agent and you want a free sample FBM transfer report, fill in the form below so we will contact you to discuss which transfer you would like to see.