Both Brentford and Brighton have recently reached the dizzy heights of the Premier League after predominantly playing in the lower leagues of English football. Brentford were even playing in League One just seven years ago back in 2014.
However, this hasn’t been achieved through heavy investment from rich owners, but more with savvy business acumen and targeting the right profile of players in the transfer market by focusing on analytics.
The Bees sealed their status in the English top flight for the first time in 74 years after they were promoted in 2021, whilst the Seagulls secured their maiden voyage into the Premier League back in 2017.
Below, we explore how and why the two clubs have been able to achieve such impressive success and how owners Tony Bloom and Matthew Benham have utilised “moneyball” tactics to elevate their respective clubs to the pinnacle of English football. You can find the latest spread betting odds on the English top flight here.
A Frosty Relationship
Interestingly, Brighton’s owner Bloom and Brentford’s owner Benham are familiar foes. The pair originally had a good relationship after Bloom hired Benham in the early 2000s to work for his company Premier Bet. Both owners come from well-educated backgrounds and have a history in using data, mathematics and statistical research.
However, the pair left on bad terms in 2004, eventually becoming business rivals in the football betting market. Following a similar philosophy in using data-driven analytics to predict the outcome of results and thus becoming professional gamblers, the two businessmen were in direct competition.
Expected Goals (xG) had yet to become widely used as a statistic in football and instead they hired people to watch over the chances created in a match, evaluating each opportunity in the process.
Now, Bloom and Benham are Premier League rivals and have both found success by utilising their similar models.
Moneyball
Brentford owner Benham was the catalyst for change in philosophy for the club when he purchased the Bees back in 2012. Instead of focusing on heavy investments on marquee players or facilities, he wanted to place his funds primarily into analytics.
These “moneyball” recruitment strategies allowed the club to triumph on a shoestring budget and to overcome other clubs in the Football League with considerably larger budgets.
This was a similar approach to that of Billy Beane and the Oakland A’s in 2002 which was popularised by the film “Moneyball” – the MLB franchise switched their recruitment and scouting policies to a more analytical approach in order to try and compete with larger and more affluent franchises such as the New York Yankees.
The basis of “Moneyball” was surrounded by the use of sabermetrics and Bloom and Benham were able to filter out the empirical analysis of baseball to that suitable to football. This meant that strategies would focus on key performance indicators. This is related to the use of xG or the slightly different approach to xG used by the two owners. This is because it better analyses how well a team has played over the course of the match, instead of focusing on the end result.
Why Has It Been So Effective?
Several staff members now at the respective clubs were also former employees at both of Bloom and Benham’s betting businesses and thus are fully invested in the approach that they have to football. By using the statistical models from the betting companies, they have been able to target and identify similar players for recruitment.
This has helped both clubs find hidden gems that had been undervalued by the market. Henceforth, instead of investing large sums on talents already identified by the rest of the footballing world, it allowed the clubs to find talents in less demand, meaning their transfer value would be significantly lower.
The theory was also tried and tested on Danish club FC Midtjylland who have certainly seen great success themselves after Benham became majority shareholder in 2014. The club would go on to win their first ever league title just a year later, with Benham being largely attributed to the triumph.
Brentford bought the likes of Ollie Watkins, Said Benrahma and Neil Maupay using these methods, to name just a few. Maupay joined the club from French side Saint-Etienne for under £2 million, making a profit of over £10 million when they sold the striker to rivals Brighton. Clearly, the two recruitment models had identified the same target.
Watkins was signed from Exeter City for £1.8 million in 2017 before Benham would rake in a healthy profit once more after selling the English forward for £28 million to Aston Villa. It would be a club-record fee at the time by the Villans.
Benrahma also offers a fantastic example of the success of using this type of recruitment. The Bees would profit around £25 million on the Algerian winger, purchasing him for £2.7 million in 2018 before offloading him to West Ham United in a deal worth up to £30 million.
Can the Success Continue?
Brighton are also still successfully using these methods and despite a number of high profile sales in the form of Benjamin White, Leandro Trossard and Marc Cucurella, they continue to find excellent replacements.
The Seagulls currently occupy seventh in the Premier League table and are able to churn out high-quality players, despite many of their key players being poached by more affluent clubs. The likes of Pervis Estupinan, Kaoru Mitoma and Moises Caicedo have all been recent acquisitions using the data-driven strategies, proving that it can be an endless cycle of identifying elite talent.
Brentford are just two places below in ninth and head coach Thomas Frank continues to overachieve with his squad. Recent signings in the form of Aaron Hickey, Keane Lewis-Potter and Mikkel Damsgaard will hope to live up to the high expectations of Brentford’s recruitment.
With the current models set up at both clubs, it allows them to continue their success, despite losing their best players to richer rivals, almost creating a conveyor belt of talent that is allowed to continuously filter into the club. Other clubs may start to invest in analytics and follow suit in the near future.
