Scouting’s Civil War: Will Data or Human Instinct Find Football’s Next Superstar?

In any industry, people who disparage technology’s worth are labelled Luddites and told to accept their new place in the world, but should we consign the people who are tasked with finding the football stars of the future to this same fate? We consider whether data or human instinct will lead us to the next star of the beautiful game

Every professional football club is looking to find the next Cristiano Ronaldo or Lionel Messi; players who make the beautiful game look stupidly simple and bewilderingly complex at the same time.  Where clubs differ, though, is in the methods they use in their search for the sport’s next megastar. Some clubs rely on a data heavy approach – seemingly inspired by Michael Lewis’s book Moneyball: The Art of Winning an Unfair Game, which described how, by meticulously choosing stats the baseball establishment had previously ignored, the Oakland Athletics baseball team were able to compete with wealthier teams. Other clubs, however, prefer the old-school approach of sending a flat-cap sporting scout to watch new recruits kicking a ball around so they can judge them with their own two eyes.

Neither method is beyond reproach, but does one have a distinct advantage over the other? Critics of Moneyball – or what generally passes for Moneyball in football – would cite the case of Aston Villa, who former manager Ron Atkinson described as: “The club that has suffered more in the pursuit of Moneyball than any other in recent times.”

Villa relied heavily on statistical analysis to scout players and seemingly didn’t place much value in having people on the ground looking at players. To give you some idea of how Aston Villa’s scouting department worked, the club’s head European scout, whose main focus was players in the German Bundesliga, allegedly emigrated to Australia and continued to do his job. This approach to identifying player talent didn’t work for Villa (who would’ve guessed) and the club was relegated from the Premier League with the third worst points tally in the competition’s history.

On the other hand, the more traditional way of scouting players also has a number of criticisms levelled against it, many of which essentially come back to the same point: how reliable are a scout’s own subjective, open-to-interpretation conclusions if they aren’t supported by data?

Speaking at the Wearable Technology Show 2017, Peter Tierney, sports scientist and former scout who now works as head of operations for Axsys Performance, described how the coach’s eye led to the existence of a kind of size bias in children’s football. “One of the key tools that has been used over the years is the coach’s eye. It’s good, but it also can also be bad because if in doubt what we ended up doing was going with the biggest all the time,” said Tierney.

Can you spot intelligence?

The accusation that scouts favour physical attributes over characteristics like intelligence, creativity and drive – difficult things to spot during a Saturday morning match – has plagued scouts for years, and has led some to call for young footballers to be organised according to their physical maturity rather than their age, in a technique called ‘bio-banding’.

Previously, Tierney was involved in a talent acquisition for rugby rather than a football and found that, for obvious reasons, rugby scouts are even more susceptible to size bias. In one programme he ran, 85.7% of the intake of future rugby players were born in the first half of the academic year. It’s understandable that scouts would be drawn towards children who already demonstrate skills which will be useful when they reach professional level, so older children, with their physical advantages, will be favoured over children born later in the year, who will always be playing catch up, unless techniques like bio-banding are adopted more widely.

Legendary footballer Andrés Iniesta playing for Spain against Chile. Image courtesy of Clément Bucco-Lechat

Having made the switch to football, Tierney points out that the same problems exist there too. “Children that were born in the first half of the year tended to be more successful in being identified than those born later in the year,” he said. “It depends where you are in the world because different parts of the world have different ways of grouping [children]. In the UK, for example, we group the children from September to August, and when they enter primary school they’re instantly put into those year groups.

“What we’ve found is that children who are born between September and December, they’re the ones that are predominantly playing football at a higher level than those that are born later in the year.”

One club that doesn’t appear to have scouts who pick players based on their physicality is also arguably the best side in world football: FC Barcelona. Raul Pelaez, head of sports technology at FC Barcelona, explains the criteria it uses to choose players by highlighting the example set by one of its most successful graduates from its famed La Masia academy, Andrés Iniesta.

“Iniesta is not endurance, he’s not a speeder, he doesn’t score goals. Iniesta only now hopes to play,” says Pelaez. “For us it’s not important if the player is thin, is fat, t’is speed and endurance. We need that he’s intelligent, and maybe the difference between FC Barcelona players and the rest is that he understands a little bit better the play, what happens in the play, what happens in the direction of the match.”

Increasing the talent pool

For a long time clubs like Aston Villa got scouting very wrong. Its aversion to sending scouts to do the hard yards and actually watch players, while marking them against a criteria which promotes intelligence and seeks to avoid physical bias, like FC Barcelona does, was clearly an incorrect approach. But there are examples of clubs who successfully use data and tech to identify some of the best players in the world.

It’s our core business to find the best players at an early stage

Like many modern elite football teams, Portugal’s SL Benfica analyses every aspect of its players’ lives, whether they’re working or at home relaxing. The club looks at its players’ eating and sleeping habits, how fast they run, tire and recover and their mental health. No stone is left unturned in the pursuit of making Benfica’s players better. All this data collecting has a point, though, because Benfica considers itself an elite club, but even finishing atop Portugal’s Primeira Liga doesn’t give you the resources needed to compete much wealthier football clubs like Manchester United or Real Madrid. So Benfica has taken its data-driven approach to talent acquisition and improvement and come up with a new revenue stream.

“It’s our core business to find the best players at an early stage,” Benfica chief executive Domingos Oliveira said in an interview with The National. “We try to anticipate the player’s future at the early stage of their development.

“We’ll not buy a player at 26 or 27, but 18 or 19,” adds Oliveira.

Benfica are by no means the only club using data to talent spot, but they are certainly one of the most successful. Already this summer Benfica have sold two players to the Premier League, for a combined total of almost £75m. Add that to previous year’s sales and Benfica have made well over £300m in the last seven years.

Tierney himself is a fan of using data as a method of increasing the size of the talent pool available to clubs. “The benefits of using all this technology now that’s readily available and using things such as your mobile devices is it will increase the size of the talent pool, which has been ever decreasing,” said Tierney. “It allows for earlier identification of potential talent, will help with a more qualitative analysis and it will give clarity because there is not so much scout reliance.

The people who matter

If being relegated as one of the worst teams ever to compete in a competition doesn’t alert you to the fact that something is drastically wrong in your organisation then nothing will, so because of its disastrous season Aston Villa has been forced to take drastic steps to improve the way it identifies talent. Sensibly, the club has gone back to sending scouts out to watch football games and allowing them to spot football’s next superstar. Rather than relying on data and statistics, or results thrown up by using the Moneyball method, these things are now used to back up the opinion of scouts rather than supplanting them.

“We’ve brought in real football people and we’ll mix that with one or two of the guys that have the analytical, Moneyball data that you hear about,” said Steve Round, Aston Villa’s new director of football in an interview with Aston Villa’s supporters club.

“The Moneyball thing came about because of baseball and that’s very statistically developed – like cricket. But football is always in a state of chaos. On any given day, football is a random, human, fluid game, so data and analytics only back up the instinct of the people looking for the talent,” said Round.

“I think football has gone away from that. They’ve gone too analytical and too data-minded, and a lot of people are paying the price for it. You’ve got to get back to the real people who matter. Scouts identify the talent and data backs that up. Villa is a massive club with high expectations, our scouts with a massive knowledge on football need to know that a particular player is capable of thriving at our club.”

In truth, the idea that there was ever another way to identify talented players was a bit of a fallacy. That’s not to discredit data analysis: as US soccer’s high performance director, James Bunce, points out, a player taken on by an academy at eight-years old has a 200-to-1 chance of making the first team, so it’s right that he best clubs collect as much data as possible so that they can make informed choices about which players will be able to survive as professional footballers. That being said, it’s also important we don’t forget the flat-cap sporting scout who has been to watch a million children, playing in hundreds of parks, on a thousand cold Saturday mornings. They have a wealth of knowledge, and football clubs would be foolish to ignore it.

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World-renowned physicist Stephen Hawking has died at the age of 76. When Hawking was diagnosed with motor neurone disease aged 22, doctors predicted he would live just a few more years. But in the ensuing 54 years he married, kept working and inspired millions of people around the world. In his last few years, Hawking was outspoken of the subject of AI, and Factor got the chance to hear him speak on the subject at Web Summit 2017…

Stephen Hawking was often described as being a vocal critic of AI. Headlines were filled with predictions of doom by from scientist, but the reality was more complex.

Hawking was not convinced that AI was to become the harbinger of the end of humanity, but instead was balanced about its risks and rewards, and at a compelling talk broadcast at Web Summit, he outlined his perspectives and what the tech world can do to ensure the end results are positive.

Stephen Hawking on the potential challenges and opportunities of AI

Beginning with the potential of artificial intelligence, Hawking highlighted the potential level of sophistication that the technology could reach.

“There are many challenges and opportunities facing us at this moment, and I believe that one of the biggest of these is the advent and impact of AI for humanity,” said Hawking in the talk. “As most of you may know, I am on record as saying that I believe there is no real difference between what can be achieved by a biological brain and what can be achieved by a computer.

“Of course, there is unlimited potential for what the human mind can learn and develop. So if my reasoning is correct, it also follows that computers can, in theory, emulate human intelligence and exceed it.”

Moving onto the potential impact, he began with an optimistic tone, identifying the technology as a possible tool for health, the environment and beyond.

“We cannot predict what we might achieve when our own minds are amplified by AI. Perhaps with the tools of this new technological revolution, we will be able to undo some of the damage done to the natural world by the last one: industrialisation,” he said.

“We will aim to finally eradicate disease and poverty; every aspect of our lives will be transformed.”

However, he also acknowledged the negatives of the technology, from warfare to economic destruction.

“In short, success in creating effective AI could be the biggest event in the history of our civilisation, or the worst. We just don’t know. So we cannot know if we will be infinitely helped by AI, or ignored by it and sidelined or conceivably destroyed by it,” he said.

“Unless we learn how to prepare for – and avoid – the potential risks, AI could be the worst event in the history of our civilisation. It brings dangers like powerful autonomous weapons or new ways for the few to oppress the many. It could bring great disruption to our economy.

“Already we have concerns that clever machines will be increasingly capable of undertaking work currently done by humans, and swiftly destroy millions of jobs. AI could develop a will of its own, a will that is in conflict with ours and which could destroy us.

“In short, the rise of powerful AI will be either the best or the worst thing ever to happen to humanity.”

In the vanguard of AI development

In 2014, Hawking and several other scientists and experts called for increased levels of research to be undertaken in the field of AI, which he acknowledged has begun to happen.

“I am very glad that someone was listening to me,” he said.

However, he argued that there is there is much to be done if we are to ensure the technology doesn’t pose a significant threat.

“To control AI and make it work for us and eliminate – as far as possible – its very real dangers, we need to employ best practice and effective management in all areas of its development,” he said. “That goes without saying, of course, that this is what every sector of the economy should incorporate into its ethos and vision, but with artificial intelligence this is vital.”

Addressing a thousands-strong crowd of tech-savvy attendees at the event, he urged them to think beyond the immediate business potential of the technology.

“Perhaps we should all stop for a moment and focus our thinking not only on making AI more capable and successful, but on maximising its societal benefit”

“Everyone here today is in the vanguard of AI development. We are the scientists. We develop an idea. But you are also the influencers: you need to make it work. Perhaps we should all stop for a moment and focus our thinking not only on making AI more capable and successful, but on maximising its societal benefit,” he said. “Our AI systems must do what we want them to do, for the benefit of humanity.”

In particular he raised the importance of working across different fields.

“Interdisciplinary research can be a way forward, ranging from economics and law to computer security, formal methods and, of course, various branches of AI itself,” he said.

“Such considerations motivated the American Association for Artificial Intelligence Presidential Panel on Long-Term AI Futures, which up until recently had focused largely on techniques that are neutral with respect to purpose.”

He also gave the example of calls at the start of 2017 by Members of the European Parliament (MEPs) the introduction of liability rules around AI and robotics.

“MEPs called for more comprehensive robot rules in a new draft report concerning the rules on robotics, and citing the development of AI as one of the most prominent technological trends of our century,” he summarised.

“The report calls for a set of core fundamental values, an urgent regulation on the recent developments to govern the use and creation of robots and AI. [It] acknowledges the possibility that within the space of a few decades, AI could surpass human intellectual capacity and challenge the human-robot relationship.

“Finally, the report calls for the creation of a European agency for robotics and AI that can provide technical, ethical and regulatory expertise. If MEPs vote in favour of legislation, the report will go to the European Commission, which will decide what legislative steps it will take.”

Creating artificial intelligence for the world

No one can say for certain whether AI will truly be a force for positive or negative change, but – despite the headlines – Hawking was positive about the future.

“I am an optimist and I believe that we can create AI for the world that can work in harmony with us. We simply need to be aware of the dangers, identify them, employ the best possible practice and management and prepare for its consequences well in advance,” he said. “Perhaps some of you listening today will already have solutions or answers to the many questions AI poses.”

You all have the potential to push the boundaries of what is accepted or expected, and to think big

However, he stressed that everyone has a part to play in ensuring AI is ultimately a benefit to humanity.

“We all have a role to play in making sure that we, and the next generation, have not just the opportunity but the determination to engage fully with the study of science at an early level, so that we can go on to fulfill our potential and create a better world for the whole human race,” he said.

“We need to take learning beyond a theoretical discussion of how AI should be, and take action to make sure we plan for how it can be. You all have the potential to push the boundaries of what is accepted or expected, and to think big.

“We stand on the threshold of a brave new world. It is an exciting – if precarious – place to be and you are the pioneers. I wish you well.”