🎥 How moneyball has changed football transfers forever 🤑 | OneFootball

As late as 2014, Brentford were residing in the third tier of English football.

Following a 2-1 win over Watford on Saturday, they have all but sealed a second consecutive season in the top-flight after a spectacular debut campaign.

And what does owner Matthew Benham believe is the key to that success? Moneyball.

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The data-driven technique was made famous by the former general manager of Major League Baseball side Oakland Athletics, Billy Beane, and has made it’s way into football, revolutionising the transfer market.

And more and more clubs are using data to unearth undervalued gems and bargains on the market.

One of the most common stats recruitment departments look at is expected goals (xG), which measures the probability of a scoring opportunity that may result in a goal, but there are thousands of different types of data that can be collected within a match.

Benham’s club are one of moneyball’s biggest success stories, particularly with the signings of Neal Maupay and Ollie Watkins in 2017 and the arrival of Saïd Benrahma in 2018.

All three were scoring under their xG stat, meaning they were undervalued on the market which allowed the Bees to pick them up for a combined £6.5m.

The trio improved their output dramatically and by 2020 they had all been sold for a collective £77m.

However, moneyball isn’t just about finding undervalued players – data can also help clubs find players to fit into a specific system or certain style of play.

In 2017, Liverpool realised that Roberto Firmino created more expected goals with his passes than almost any other player in his position before identifying that Mohamed Salah was the perfect player to convert those chances.

The Reds paid €42m to Roma for the Egyptian’s service and in his first season Salah scored 32 goals in 37 games.

In its simplest form, moneyball helps clubs find top talent for bargain prices but the technique has adapted to fit the complex world of football – they are now capable of helping teams find players to fit specific systems.

Data has changed the face of the transfer market.