There has been an explosion in popularity regarding football statistics and analytics in recent years.
It is no longer just about which team had the most shots on goal, or enjoyed most of the possession, or even who scored the most goals for some. There’s so much more to consider now, so many more colours to paint the image of the game with.
Among the people igniting the fuse at the other end of the analytics boom was Rob Bateman, also known as “Orbinho” on Twitter.
“The metric is actually changing the game”
Long before the explosion, though, in 1998, Bateman joined Opta, the now behemoth of sports analytics, in its infancy.
Starting with a history degree in hand and experience in advertising, an FA coaching badge and a knack for writing statistical blog posts about Arsenal, Bateman climbed his way to an editorial position at the analytics company.
Now the Head of Opta Data Editorial, he has witnessed its remarkable rise from within, branching out to all kinds of media, as he explains:
“I work with the data to find interesting facts and insight for clients to use for their viewers and readers. We work with pretty much all sports broadcasters, clubs, lots of digital companies, newspapers, sports magazines, big tech like Google, federations, bookmakers, sponsors. Anyone who can use sports data, really.
“I joined before the 1998 World Cup. Six different owners later, I now work in a business that has gone from less than ten full time employees to one that has over a thousand.”
Opta has educated fans and evolved their understanding of the sport they watch every week. In great business sense, it identified something people love – football – and made it even more interesting.
One revolutionary way Bateman was part of the boom was how the popular analytical stat “xG” (Expected Goals), which gives a shot a probability score from 0 to 1, came about.
“I hired Opta’s first ever data scientist back in 2011, Sam Green, who created the first ever Expected Goals model for Opta.
“I believed that data analytics would become more common place in professional football as clubs looked to use data to secure some competitive advantage, just as it had in other sports.
“The work that Green and the team did back then has helped create new roles at clubs and a thirst for more data to try to gain competitive advantage,” he says.
The fuse had been ignited.
In a recent BBC interview, former AFC Bournemouth chairman, Trevor Watkins, echoes Bateman’s words:
“You can’t underestimate the value of data and analysts. For a football club the most important factor is improving your chances of winning.
“Having access to people who can understand that data is critical. Arsene Wenger was a big proponent and the pioneer of using data and analytics. It’s the most under-rated feature of football.”
These kinds of stats weren’t especially new in other sports, however. American sports, like baseball, use all kinds of different data to gain an advantage. The resulting edge could blossom during a game through tactics or, as shown in the movie Moneyball and in football in recent years, by recruiting the ideal players for modest fees by focusing on a catalogue of diversified components.
Bateman isn’t surprised analytics caught on in football, too.
“Arsenal bought their own analytics company. Liverpool, Manchester City, Barcelona and Bayern have all made significant investments in this area. Clubs like Bolton showed how using data could help them compete when not on a financially level playing field, just as the Oakland A’s did in baseball.
“It was only a matter of time before the big clubs saw the success it brought and invested more in that area. It’s common sense though: better information helps businesses make better decisions.”
Regardless if the team is Manchester City or Brentford, data has become a vital part of the football landscape. Analytics can show players where to aim when crossing for better results. What the save percentage is for the opposing goalkeeper on his right side compared to his left. How many touches the other team use per attack. How fatigued your player is before a game. Which spaces on the pitch your opponent gives up. What the quality of their scoring chances are(xG). The rabbit hole is deep.
“Expected Goals puts a number on how inefficient it is to shoot from long range, so clubs have changed their approach. As a result, the number of shots from outside the box has declined to two thirds of what it was when the model was introduced, from roughly 4800 to 3200 per season. The metric is actually changing the way the game is played.”
Data has an increasingly important role in player recruitment, too. Watching transfer targets in the flesh, or on video these days, isn’t enough. The full image is often backed up by the numbers.
Players such as N’golo Kante and Matteo Guendouzi seem to have come from nowhere but are brilliant examples of combining traditional scouting and data, thus finding that competitive advantage.
In a time when everything is affected by the coronavirus pandemic and clubs are reporting losses up to £70 million as a result, finding hidden gems for modest fees is more valuable than ever.
It has also made it much easier for the ‘viewer at home’ to try on the scouting cap and tell the social media sphere about their discoveries and criticisms.
@OptaJoe and how to ‘use’ stats
A key ingredient to the data boom was social media, especially Twitter, where information spreads like an Erling Haaland-led counter-attack. It was something Bateman and his team at Opta realised in 2009, when they created @OptaJoe.
“Twitter came about because a client wanted us to manage their account for them. We didn’t really know much about Twitter, so we figured we’d set up an account for ourselves to test things out. Someone was name-sitting Opta, so I decided we had to find an alternative and came up with @OptaJoe.
“I thought long and hard about standing out from the crowd, so came up with the style that is synonymous with the Opta content of: Number – Sports Facts – Sum up word.”
Like the company itself, that Twitter account from 2009 shot through the roof. @OptaJoe now has 1.2 million followers on the popular platform, and its success has spawned identical company accounts accommodating other leagues too. @OptaJose covers Spanish football and @OptaJohan posts about Dutch football. Hundreds of fake accounts jumped on the hype train, too.
However, evident on Twitter every day, Bateman thinks stats are commonly misunderstood. “Pretty much all data is misused at times,” he says.
Stats have become bargaining chips for fans on social media. Unfair comparisons between players and teams, ignorant or to wind rival fans up, are commonplace. Bateman believes sports data should be a starting point, not necessarily the ultimate argument.
“Football data should pose questions. They’re mostly a starting point for investigation and understanding, rather than a definite answer.“
Some people at Opta started their own, niche accounts. Bateman started “Orbinho”, now at 78.000 followers and a must-follow account for Arsenal fans. Its purpose is for the fun of it but to keep an ear to the ground, as well.
“Mine was to publish all the great facts I could find about Arsenal, because we couldn’t put them all on the company account and some of them are probably only of interest to Arsenal fan groups.
“My main reason for having an account is to engage with fans to see what content they like and don’t like, to try to promote better data usage and to see what others are doing out there.”
Opta set the fuse and saw an explosion that not only made the game more interesting for the fans, but actually changed the game itself. With a bottomless well of information, tactical pragmatism rose in football. Long shots became collateral damage. And we are now watching a ‘smarter’ game. What is next to go out of style? Long corner kicks? The striker position for defensive-minded teams?
Whatever the next evolution of the beautiful game is, the origin will likely come from analytics.