Disrupting sport with big data

Why is professional sport so averse to technology? Sanjit Atwal argues why the beautiful game should follow business’s example and embrace big data.

Manchester City has won its first title in 44 years, becoming the fifth-ever team to win the league since the Premier League was formed 20 years ago.

The completion of this momentous feat has required monumental spending. The team that brought home the title last Sunday has cost an estimated £310 million – and that was just in transfer fees. The wage bill at City is a staggering £116 million. The prize and TV money paid out to win and then compete at a higher level next season does not cover that figure – it isn’t even close. As a professional business, this is madness.

Imagine a large corporate posting these results at shareholder meetings and then having the gall to ask for more money to further strengthen the team for the coming campaign. I mean, come on, even Groupon is now stating a Q1 profit.

Football is generally not a well-run business; it’s the Yahoo! of the sporting world. Manchester City is by no means the first team to spend big to bring in glory. But with the new UEFA Fair Play rules, it seems there may be a new dawn in the fight for financial regularity and responsibility in the world’s biggest sport. At a time of global economic uncertainty, it couldn’t come quickly enough.

The goals of the UEFA Fair Play rules are as follows:

• to introduce more discipline and rationality in club football finances;
• to decrease pressure on salaries and transfer fees and limit inflationary effect;
• to encourage clubs to compete with(in) their revenues;
• to encourage long-term investments in the youth sector and infrastructure;
• to protect the long-term viability of European club football;
• to ensure clubs settle their liabilities on a timely basis.

I agree and support the financial fair play rules that UEFA are implementing. They will encourage the development of young talent and generally make football a better business as clubs know that they need to shape up or ship out.

However, while the fair play rules are good news, they do not seem to actually attack the problem head on. By this, I refer to the subjective nature of value attribution in football. The reason that European football salaries continue to rise at an alarming rate is that there is no clear definition of value in the marketplace.

American sports, although paying high wages, do not seem to have the problems of ever-increasing costs that mark European football. This is, in part, down to legislation, but also likely to be down to the cross-border nature of European football and the premium that certain players can command when transferred from club to club. While it has been generally proven that, on average, the more you pay your players, the better you do, the actual transfer fees are still shrouded in mystery.

This is where the value attribution falls down. Liverpool paid £35 million for injured striker Andy Carroll, a player who has returned a paltry nine goals this season. That’s around £3.8 million per goal. Carroll was a media darling at the time of the transfer. Young, strong… and English, which instantly puts a strange, undefined premium on his fee.

Liverpool paid the fee, as they had just sold star forward Fernando Torres, hailed by all as one of the great European strikers, to Chelsea for £50 million when the transfer window was on the verge of closing. Ah! Good business, I hear you exclaim. Not really. It isn’t as bad as it could have been, though, as it turns out that Torres would go on to be an even bigger flop than Carroll.

The value proposition of the transfer was assessed without consulting correct data. Not that the data wasn’t available – but perhaps it wasn’t utilized in the correct way.

Scenario: You’re at a friend’s house watching the match, and your friend turns to you and tells you that he thinks your new midfielder is so rubbish that he wouldn’t get a game for the Sunday league outfit around the corner.

How do you build your argument against your friend? You need to objectively assess the performance versus the opposition and also against previous performances, from both the player in question and opposition players. You may have some data to base your argument,such as goals scored, assists, etc. But do you have the maximum amount of relevant data?

This is where technology comes in and where, weirdly, football needs to take a few pointers from the digital advertising industry. I’ve managed the digital advertising strategy of over 35 top brands over the last five years and it all comes down to analyzing the data coming back from campaigns to optimise and improve return on investment. The goal is to run highly-efficient and margin-maximizing campaigns.

Digital marketers have the added benefit of the transparency of the web; a medium that has grown up in compared, aggregated and visualized data and, in the case of display advertising, is certainly moving down the route of real time bidding and value attribution. What then, can football use as a comparison to Google analytics? How do you measure the “funnel”?

What if we had a qualified, universal scoring system that scientifically measured every touch, every pass and the result of each move, both positive and negative? And what about the biological factors involved, such as the breathing patterns, heart rates and even neurological brain patterns during play?

What if we had a true influence score for any player at any time that reflected their real-time price and benchmarked their calculated worth, both in the game and accumulated over the season?

The thought is tantalising and the potential long-term effect, entrancing. And the penny drops when the information gathered becomes freely available to the general public in real time.

There are two key potential output factors here that could fundamentally disrupt sport:

First, normalised player transfer fees and wages. When one player is paid a premium due to his nationality over a less fashionable player that may be more effective, there must be something wrong. A normalized scoring system would help piece together previously unseen data on each player and the manager would then be able to judge the potential impact on his own team.

Clubs are of course free to pay their players whatever they like, as long as they adhere to UEFA rules, but it would be fascinating to see how they correlate these wages with scientific and publically open performance data.

Second, the crowd influencing the media and the media influencing managers and clubs – rather than the media influencing the crowd and clubs. The wisdom of crowds is there for all to see every day. Just turn on Who Wants To Be A Millionaire to see how “ask the audience” is more often than not correct. I’m not suggesting that we crowdsource our football team line-ups, but a manager would have a much easier job without media pressure around a particular player’s inclusion based on subjection from journalists.

Instead, if everyone has the same maximum amount of data, then it would be interesting to understand the differences in the decision-making process for picking a team.

The ultimate impact of such publicly-available data is, in truth, unknown. But, as social psychologist Kurt Lewin famously said, “You cannot understand a system until you try and change it.”

So how far away are we from this system change?

Companies like Opta Sports, Hawkeye, Infostrada, Tracab and ProZone all provide technology that records high levels of data in sports. This is usually supplied to media outlets and clubs for a license fee. The licensee then chooses how much data to show to the fans. The problem here is that the fans aren’t in control of either the nature or the amount of data they receive.

A great example comes when looking at the popular statistic of “action areas”. At the end of a football match, you are shown the action areas of the pitch. Broken into thirds, the pitch is overlaid with percentage figures based on the amount of action in the particular sector. So, as a viewer, do you now know what has happened in the game? Yes? Are you sure? Look harder…

Was it the left-hand side of the pitch or the right? Was it the midfielders or the deep-lying strikers? The defensive-wingers or the attacking full-backs? The cultured centre-backs keeping the ball or the skillful strikers playing the ball around up front? The fact is that when you interrogate the data, it quickly comes to light that it doesn’t hold up.

This brings us full circle, back to the key point regarding the subjectivity and lack of transparency that would surely not be tolerated in any other industry that exists to make money.

It may be that this has existed in football for so long due to the nature of the sport and the tribalisation that it evokes in people (“stop taking the romance out of our sport you boffins!”). However, ignoring the data is to our own detriment.

Ultimately, what does it say about us as a society if we are willing to fight economies on the slide but won’t analyse the massive amount of money being thrown around in football? The only reason we would is because we are afraid of the truth. And that truth is that our midfielder really is rubbish.