For the development in any field, analytics plays a crucial role. In case of sports, analytics has always existed with or without us knowing it. Sometimes coaches make unbelievable decisions, and the same coaches, at other times make decisions that put most brilliant strategic minds to shame. This leads to a lot of questions about what goes through in their minds when they decide on a substitution or reacting to a situation at a point in a game. There are hundreds of questions like these that people have pondered over for years together until the advent of sports analytics.
While the use of data and technical analysis has become essential for today's football clubs, the big Premier League teams aren’t the only ones playing the game nowadays. Smaller clubs are getting in on the action too, thanks to cheaper and more accessible software. With the immense development in the field of data & technology, a good number of teams across various sports have begun employing analytics to their benefit. Since most professional sports teams function as businesses, they are always seeking ways to improve sales and reduce expenses across their organization. Modern marketing and fan outreach efforts also rely heavily on analytics to predict their consumer base and identify opportunities to increase brand engagement.
Access to data in football clubs, at least within a league, is no longer a distinguisher. With such a level playing field, what’s now more important are the decisions that are made about the data a club buys or captures and what is done with it. Each club is not capable of big money signings and has to be much more economical and play strategically moneyball games in the transfer window to make the most out of the budget they are being provided with. And we see in many small clubs like Brentford, Midtjylland doing wonders when it comes to data handling and market strategies.
Let us see the case of Brentford FC: The rejuvenation of Brentford started in 2012 when Matthew Benham, a professional gambler, betting businessman and lifelong fan saved Brentford FC from bankruptcy by paying the £500,000 debt the club owed. Since then, he has invested over £90 million in improving the team's training facilities, stadium and also in developing a youth academy. He analyzed and saw that the concept that results should drive decisions was the old way, so the next time the club needed recruitment he would use the evaluation of key performance indicators of the player as the scale. It is by consciously doing things differently that Benham did to take a small club like Brentford such great heights.
In 2017, Bleacher Report published an article about how tough decision Benham had to make about the youth academy. Since 2005, no academy player had debut in the first team. The best talents produced by their academy later signed contracts with Big Premier League names. This is why Brentford FC decided to completely close their academy and solely focus on recruitment from other clubs. They created a B-team which included players previously rejected by other clubs and also provided a chance for overseas players looking to trial in English football.
The way Brentford started recruiting players also changed. They began to follow a stock market type approach when evaluating which players should be signed, almost looking at them like assets and taking into consideration market inflation in different countries. They would focus on hiring young and undervalued players who had the motivation and energy to develop further. To do so, they employed statistical modeling to analyze player performance. They particularly focused on the leagues across Europe with less inflated markets but higher player quality when compared to Championship.
Brentford changed their outlook on Team performance as well. Brentford are known to be big fans of models like xG, and use these models to obtain a potentially different view to the existing league table position and match results. They have stated that this takes away the luck factor that can influence football results and instead looks at the quality of performances the team is having while considering the long term sustainability of the club. They found that teams weren’t focusing enough on the set pieces even though set pieces may contribute around a third of the goals scored. They decided to emphasize more in these areas during trainings and even hired coaches who specialized in set pieces. This had a positive impact and resulted in a more planned approached to taking set pieces that ultimately led to more goals.
The long-term philosophy that Brentford FC have been implementing over the last 9 years has generated quite an excitement around the football analysis community, Everyone is impressed to see a club being run by analytics, sound business strategy and statistically-based decision. These strategies have enabled Brentford to finally make their breakthrough into the Premier League after 74 years. In 2021, they were the only non-Premier League club to compete in the semi-finals of the Carabao Cup. The club which was at 4th tier in 1998 will be playing the top flight in the 2021-22 EPL season.
Brian Clough practised something similar to this when he signed Kenny Burns for Nottingham Forest. Kenny Burns was known to be bellicose and inebriate and was not wanted by most clubs, but beneath all that was a shrewd footballing brain, and a man for the big matches. He was a central defender, but Clough and his assistant Peter Taylor converted him to a striker for the 1978 season, when he became the Football Writers’ Footballer of the Year.
In world where analytics in different fields is growing at a great pace, soccer analytics is still under a lot of development as compared to other sports. It has been evolving but still needs a good pace. Data collection, especially in soccer has increased multifold off late to capture various measures that have never been captured before. Also, there are organizations like Opta Sports, which are constantly trying to improve their prediction models by introducing and analyzing new variables such as expected goals, expected assists, sequences and possessions. Furthermore, they also consider the progress made, directness of goals scored when trying to assess the style and chemistry of a team, which goes hand in hand with this research by trying to quantify different unquantifiable measures. To conclude, predictive analytics models in soccer can be made better with the help of descriptive models that help understand the data well.
Graphics Credit: Ridam Hazra
