I have supported Liverpool FC for a long time. I can remember the heady days of the 70s and 80s when they were European champions. For nearly a generation, between 1975 and 1990, Liverpool were dominant. They won 10 titles in England’s top division. They won the European Cup, which preceded the Champions League, four times in eight years. Since then we’ve waited 30 years for a first Premiership title – it may be about to come in 2020. The club are once again amongst the best in the world.
Much of the credit for this goes to their Manager, Jurgen Klopp. But there is another reason they have achieved this success and it’s a fascinating story.
It begins thousands of miles away in Oakland, California. Oakland Athletics baseball team’s general manager, Billy Beane had been hurt by his team’s loss to the New York Yankees in the 2001 American League Division Series. With the impending departure of three star players, Beane needed to assemble a competitive team for 2002 but on Oakland’s very limited budget.
To put it into perspective, the New York Yankees had almost 3 times the budget compared to Oakland’s. Oakland really needed to think outside the box to get value in picking new players.
The film Moneyball, the 2011 film, based on Michael Lewis’s 2003 non-fiction book of the same name, is the true story of the Oakland Athletics baseball team’s 2002 season and their general manager Billy Beane’s attempts to assemble a competitive team using data.
During a scouting visit, Beane met Peter Brand, a young Yale economics graduate with radical ideas about how to assess player value, and subsequently hired Brand as his assistant. Brand is very much of the view that “baseball thinking is medieval…and they’re asking all the wrong questions.”
Rather than relying on scouts’ experience and intuition, much to the Oakland scouts dismay and annoyance, Brand used data, selecting players based on their on-base percentage (OBP) while ignoring their perceived weaknesses. The duo focuses heavily on the data and statistics applying this methodology to hire undervalued players.
“We’re building in all the intelligence we have to project players…using stats the way we read them we’ll see value in players that nobody else can see…”
At first this didn’t go to plan. Oakland lost their first 10 matches applying this approach. Brand argued their sample size was too small to conclude the method did not work, and Beane convinced the team owner to stick to the approach.
In fact, Beane made more changes including trading the traditional first baseman to make way for one of the data signings. Three weeks later, the Athletics were only 4 games behind first place.
And just two months later, the team started an incredible winning streak of 20 consecutive wins and broke the American League all-time record! Oakland eventually clinched the 2002 American League West title.
Beane is contacted by John Henry, the owner of the Boston Red Sox, now the owners of Liverpool FC, who realises that data analytics is the future of baseball. Despite being offered a record-breaking $12.5m salary, which would have made him the highest-paid general manager in history, he declined and returned to Oakland.
Undeterred Henry, who became wealthy from an algorithm he devised that predicted fluctuations in the soybean market, embraced data analytics and two years later the Red Sox won their first World Series since 1918 embracing the philosophy championed in Oakland.
So when John Henry (who famously said “anybody who’s not tearing their team down right now and rebuilding it using your [Beane’s] model, they’re dinosaurs.”) acquired Liverpool FC he introduced data analytics to their recruitment model.
At the time that Henry’s group, now known as Fenway Sports Group, acquired Liverpool, the club hadn’t finished at the top of the Premier League in three decades. Then Fenway bought Liverpool and began implementing its culture. That included hiring Ian Graham as the team’s director of research to build a version of its baseball team’s research department.
Graham grew up an hour’s drive from Cardiff as a Liverpool fan. His childhood in the 1970s and ’80s coincided with Liverpool’s era of dominance. It didn’t hurt that one of the club’s best players, Ian Rush, happened to be Welsh. He was studying for a doctorate in Physics at Cambridge University when someone forwarded him a notice for a job at an analytics start-up that was hoping to consult for football teams, he was intrigued. He landed the job and was told to read “Moneyball.”
For four years, from 2008 to 2012, Graham advised Tottenham. The club was run by a series of managers who had little interest in his suggestions, which would have been true of nearly all the football managers at that time..
Now, before each Liverpool game, Graham and the three analysts who work under him compile a packet of information. By the time Klopp decides which of their insights are worth passing along to the team, the equations are long gone; the players are only dimly aware that some of the suggestions are rooted in doctorate-level mathematics.
Its reliance on numbers, many people believed, was undermining the football men who should have been making its decisions. The main obstacle Klopp would need to overcome if he hoped to succeed at Liverpool, the Independent wrote, “will be the club’s deep attachment to the theory that players’ statistics — analytics — can provide most of the answers.” The reaction to Graham’s appointment, almost uniformly, was scorn. “‘Laptop guys don’t know the game’ — you’d hear that until just a few months ago,” says Barry Hunter, who runs Liverpool’s scouting department.
But since Fenway couldn’t outspend sheikhs and oligarchs, it needed to be smart. In its first six seasons under Fenway’s ownership, Liverpool finished above sixth place only once. It qualified for the Champions League in only one of those years, and was eliminated before the quarterfinals.
Graham hardly noticed. He was immersed in his search for inefficiencies — finding players, some hidden in plain sight, who were undervalued. His team’s weightiest responsibility is helping Liverpool decide which players to acquire. He does that by feeding information on games into his formulae at Melwood, the club’s training complex in Liverpool where he works with his team: Tim Waskett, who studied astrophysics, Dafydd Steele, a former junior chess champion with a graduate math degree who previously worked in the energy industry and Will Spearman, who grew up in Texas, a professor’s son before completing a doctorate in high-energy physics at Harvard. Spearman then worked at CERN, in Geneva, where scientists verified the existence of the subatomic Higgs boson. His dissertation provided the first direct measurement of the particle’s width, and one of the first of its mass.
Another club might conceivably hire an analyst like Graham, or Steele, or Waskett, and maybe even Spearman. But it’s almost impossible to imagine any but Liverpool hiring all of them.
Spearman hasn’t had much to do with Liverpool’s recent success. He does almost none of the work that Klopp sees, and he’s rarely involved with discovering players. His mandate is more ethereal. Spearman knows just enough about the sport, or just little enough, to try to change it. “We’re just starting to ask the question, ‘Why don’t we try to play football in a slightly different way?’ ”
Graham explains. Football is the sum of thousands of individual actions, but the only ones Graham’s model can evaluate are the passes, shots and ball movements that are downloaded from the official play-by-play. “There are still fundamental limitations in the data we have,” Graham says. “It’s still like looking through a very foggy lens.” By working to get the mathematical rendering closer to reflecting what actually happens on the field, recording not just that a defender kicked a pass to a midfielder but how hard it went and what happened when it was received, Spearman is looking to find a path through the fog.
By now you may be asking ‘What has all this football talk got to do with my business?’
Well quite a lot. Data analytics is increasingly becoming the competitive advantage in business just as it is in football. No longer is it possible to just measure the results.
Marketing, for example, is now so complex that keeping the score of how each pillar is performing and finding underperforming pillars that others haven’t is of critical importance.
Embrace data in any and every way possible that will give you an advantage; use it to make smarter decisions and see things others don’t. Data will be your advantage and your secret weapon, even if you have a smaller budget. Think about that; are others working much harder to leverage data and making you look like a dinosaur?