A scout’s role in the age of data analysis

Big Data’s new role and how it contributes to a scout’s credibility

With the introduction of data analysis and in-depth reporting, scouts had to adapt to modernity and use big data to their advantage, while working in collaboration with their club’s data analysis department. This has altered the scouts’ roles considerably, given that their approach now heavily relies on the interpretation of data. How different is a scout’s job compared to 30 years ago?

Let’s start by saying that this is not a nostalgic piece taking us back to football’s “golden era”, nor is this article an attack on the sport’s modern age. Football has changed, the world has changed, and every major player in the sport industry has had to adapt to the inevitable developments of the manner in which things are carried out in the 21st century. Alex Ferguson has based most of his success and longevity on his ability to change with the times; he updated his backroom staff when needed, and even sold important players for the sake of his team’s continuous success.

Talent scouts have been the most affected by the arrival of data analysis. While this could easily be misconstrued as a threat to their job security, the job of a data analyst is to complement a scout’s findings, and even make their jobs easier. Let’s look at it this way:

Whilst data has always been used in football, its presence has traditionally been less broad than its current extent, with its role hardly as predominant as it is today.

Traditionally, a scout would hear of a young talent and have to travel to see him play in order to compile his set of notes and data before presenting his findings to the club’s manager. Some information was of course known on the player in question, such as his goal-to-shot ratio, appearances, assists, and so on; basic raw data which allowed the club to shortlist the players which fit their requirements.

When the scout would then travel to see the player, this is when he earned his money. Aspects of a player’s game which cannot be put on a spreadsheet, such as the player’s movement around the pitch, his positioning, and even his sheer grit are all factors which need to be examined up close — and no data can ever replace a scout in this regard.

In the 1990’s and earlier, certain managers had an edge over their counterparts in regards to their knowledge of a certain league. For example, Arsene Wenger’s arrival to Arsenal in 1996 saw him arrive in a league where not many French players had played; and his extensive knowledge of his home country allowed him to lure players such as Patrick Vieira, Emmanuel Petit, Sylvain Wiltord, Thierry Henry, and many more. While some of those players were already playing outside of France, they were relatively unknown on the other side of the Channel, which gave Wenger a welcome advantage in his first few years as Arsenal manager.

However, nowadays, in an almost fully-globalised world, the recruitment landscape has changed. Very few top-flight clubs have an edge over their competitors, and their ressources must be used in a much more efficient way in order to identify a potential target before anyone else.

This is where big data comes in.

While it’s clear that no football club will recruit a player solely based on his data, its role is to help the manager compile a shortlist much faster than he previously would. With the advancement of technology and the wide range of things data can do, a manager can tell his data analyst exactly what he is looking for [insert unrealistic expectations here], receive the results in a matter of minutes or hours at most, and send his scout to do the sniffing in order to get a clearer view on the player.

Just like a recommended song on Youtube, a data analyst’s software can suggest a virtually unknown football player which fits the set list of required qualities. It’s almost impossible to know every football player in the world, but it has now become much easier to gain information on any target which fits a manager’s criteria.

Data can be extracted by anyone with the necessary piece of software, however, which increases the importance of data analysts in modern football. When taken into isolation, a player’s statistics can mean very little — it’s the analyst’s ability to form a narrative around this data which can be beneficial to a club.

If the manager is looking for a player who is comfortable passing with both feet, is good in the air, weighs passes perfectly, and efficiently runs in behind the defenders, data can actually reflect all of this into a comprehensive report. In order to save time, an analyst can also analyse the pieces of big data generate this information across several matches in order to determine whether a player’s performance was a one-off or a continuous trend. With every bit of a player’s movement and actions being tracked, the proverbial sky is the limit.

That’s where the scout will work in tandem with the analyst who will extract the core pieces of big data. After all of this information has been scrutinised and a shortlist has been created, the scout will then be able to travel to see the player in action and determine whether these statistics are accurately reflected, as well as gain some deeper insight into the player’s on-pitch performance, as mentioned earlier in this article. Does the player position himself well in crucial situations? Does he cover his team-mates when necessary? How dedicated is he to winning the ball back when he or his team-mates lose it?

A player’s character can understandably not be reflected in an analyst’s report, which further reaffirms a scout’s role in the modern game; his ultimately has the final say, before the manager decides if the player is worth signing.

A football scout, in the traditional sense of the term, has not changed much over the last 30 years. His role is still to attend matches and training sessions to watch football players before reporting back to the manager. He still needs to use his seasoned eye in order to determine whether the player has something special.

With the new trend of younger managers taking over the European leagues, a scout’s role is not one I’d attribute to anyone less than 50 years old — experience and a trained eye is crucial when evaluating a player. You want your scout to have seen thousands of players in order to recognise a special talent when he sees one.

The modern scout is the same kind of irreplaceable asset to a football club, he’s just had to adapt to a new type of playing field.

Football & Finance: The crucial role of finance in the world of top-flight football

With the football industry considerably and consistently multiplying its revenue stream from advertising partners to TV & image rights, football clubs and professional players have entered a new era. This augmented funding means that football clubs can afford to re-invest in tools and research necessary for the growth of the club and its players on a footballing level, which in turn can be transformed to enhanced performances on the pitch.

All figures are provided by the Deloitte Football Money League and the Daily Express newspaper.


Anyone who watches football has at least some remote knowledge of the high amount of finances which are involved in the sport. Just to give you an idea of how much income the richest football clubs generate, here are some points to get us started:

  • The top 20 clubs in terms of revenue have amassed an aggregated revenue of €6.6 billion during the 2014/2015 season
  • The top three clubs surpassed the €500m revenue mark.
  • Real Madrid, the world’s richest club, generated €577m in 2014/2015. They are followed by Barcelona with €560.8m and Manchester United with €519.5m.

Even though these figures don’t take taxes into account, the preliminary numbers present a healthy profit for the top 3 richest clubs in the world. 

So, how do clubs make money?

There are three main revenue streams which make up a club’s financial profit:

  • Match day revenue (gate receipts)
  • Broadcasting revenue (domestic and international)
  • Commercial revenue

Top 3

Of €577m, Real Madrid made €129.8m of it from match day revenue, €199.9m from broadcasting deals, and €247.3m from commercial deals.

Barcelona’s €560.8m breaks down to €116.9m in gate tickets, €199.8m from broadcasting, and €244.1m from advertising deals.

Third-place Manchester United boasts €114m in match day revenue, €141.6m in broadcasting revenue and €263.9m in commercial deals, all adding up to €519.5m for 2015.

EPL Broadcasting Revenue

With the English Premier League as the most-watched football championship in the world, broadcasters Sky Sports have agreed to pay an average of £10.8m per game from 126 games spanning from the 2016-2017 season until 2018-2019, with BT Sport paying £7.6m for 46 games across the same period.

This amounts to a combined £5.1bn deal only accounting for domestic broadcasting, with foreign broadcasters paying a separate fee. At £81m per season for each top 20 football club, foreign broadcasters’ funding could push that deal over the £100m line per team; with over 95% (£4.9bn) of the total funds going to football clubs.

With matchday revenue and commercial deals pushing clubs’ overall income well into the tens of millions every season, the only factor of the three which is more or less volatile is the income generated from gate receipts; given the fact that the number of matchday attendees will vary from game to game.


Of the massive revenue model cited above, the top 20 English clubs spend about 70% of this income on player wages, which would equal to a collective of £3.42bn going into the pockets of Premier League players and their agents.

Under the current deal, £56m (or 5%) of the EPL TV income is reinvested in grassroots football, charitable causes, and community projects. With the augmented TV deal covering the 2016-2019 seasons, this potentially maintained 5% would translate to £256m across that period, or £85.3m per year.

Of the remaining funds, every individual club has different investment priorities. Some football clubs decide to improve their training facilities, carry out stadium renovations/refurbishments, invest in their data analysis department, or just spend the majority of their funds on player transfers.

New times

Will football change? Yes. Will it ever return to ‘simpler’ times? Not a chance.

What’s set to happen? The game will continue to evolve. Contemporary football teams compete at a much higher level than the best teams of the 1970’s, 80’s or even 90’s. Training facilities will get more sophisticated which in turn will improve players’ levels; analysis will get more detailed which will result in improved scouting and less judgement errors; and clubs will get richer, therefore boosting the continual expansion of the previous two points, along with a hundred of other factors which form the whole makeup of a modern football club.

As much as the football purists would hate to admit, the reality of the matter is that a 21st century football club is a business almost as much as it is a football ‘family’. The fact that the sport’s popularity has grown immensely between 1990 and 2016 means that more businesses want to get involved and consequently, the price of demand rises over time. With football clubs and governing bodies opening their doors to investors — in turn allowing the former’s higher financial power to be reinvested for the purpose of competing with their peers.

Everyone wants a piece of the proverbial cake; with each slice coming at a hefty sum.

The “Moneyball Revolution”
How numbers are turning football into an exact science

With the “Moneyball Revolution” well and truly underway in terms of revolutionising sports such as baseball and American football, football is now next in line. Football clubs have recently been actively looking for means to increase their advantage over their competitors through the extensive use of data which will result in on-field improvements. Going beyond finding data and analysing it, the “Moneyball Revolution” in football presents football clubs with ways to implement this raw data into their player-purchasing and on-field strategic approaches.


The idea that “moneyball” is the answer to any football club’s deep-rooted issues is a massive misconception that must be discounted before we start delving into this subject. The way in which the moneyball strategy can help a football club or a manager achieve better results is far more complicated than simply receiving data and implementing it. It is also important to note that immediate results are not to be expected — this approach mainly offers solutions for the long term; for reasons which we will discuss below.

We have to remember that when moneyball was famously implemented in baseball, it was done so in a game which is, historically, extensively data-driven — thus explaining why it had such a visible impact (Beane’s Oakland A’s reached the MLB playoffs from 2000 to 2003, after Beane’s appointment in 1997). Beane’s on-field success ultimately came from his — and his team’s — ability to identify and field a competitive team on a tight budget. This is where his philosophy applies to football.

In an age where the football industry is proverbially drowning in money due to multi-million TV and sponsorship/advertising deals, ‘smaller’ top-tier clubs are finding it hard to compete with clubs who have higher ressources. Working with a budget of $30mil versus your competitor’s $200mil is an obvious hurdle — one which more and more clubs are trying to tackle by adopting the moneyball approach.

So, how can football clubs operate within their financial means by using this method? The first obvious response is to identify ‘quality’ football players at a lower price — relatively unknown football players who meet a manager’s quality requirements, and who can be purchased at a low price.

When scouting players, there are always basic factors to take into consideration such as:

  • Goals scored
  • Assists provided
  • Clean sheets (defenders and goalkeepers)
  • Appearances
  • Distance covered per match

This gives you an overall view of the player and his performance during a game. Then you look at more in-depth data, including:

  • Passes completed (%)
  • Interceptions
  • Shots on target
  • Clearances (defenders and goalkeepers)
  • Saves (Goalkeeper)
  • Sprint speed
  • Accelerations / Decelerations
  • Tackles completed
  • Duels won
  • Aerial duels won
  • Recoveries
  • Shot accuracy (%)
  • Average pass length
  • Average defensive actions
  • Defensive errors
  • Total bookings (Yellow/Red)
  • Total chances created
  • Offside(s)

But of course, it doesn’t stop there. With the help of specific software, you are able to determine a player’s fitness, movement, and physical performance during a game. Does your centre forward feel more comfortable taking an extra touch before shooting or is he more inclined to take his chance on the first touch? Does your goalkeeper position himself before jumping for a save or does he read the game well enough to be in a favourable spot the majority of the time? How many times does your center back get bettered by an opposition player dribbling, and how often does he recover into position in those situations?

As one can imagine, there are dozens upon dozens of pieces of data which contribute towards a player’s overall efficiency on the pitch.

As mentioned above, football mainly benefits from moneyball in the long term because ultimately, a manager will be able to improve certain aspects of the player once he joins the club (strength-building to win duels, drill training for recoveries, etc) but it’s a player’s raw ability (overall shot accuracy, ability to read the game) that gives the manager a fair view of the player. Focus, drive, work rate and sheer heart are also important factors which might push a transfer over the line, but those are aspects which cannot be identified in statistical data.

Coupled with the fact that the use of raw data can be used to analyse a player’s training and in-game performances as well as fitness levels, the moneyball model can only successfully be applied over a longer period in order to identify patterns and inconsistencies — resulting in a lack of immediate results.

Consider the collection of data and its analysis into a coherent narrative as an ongoing process which not only cannot be rushed, but furthermore one which will only yield results over a certain timeframe due to the very nature of its mechanisms.

Because football is a much more free-flowing game than baseball, where the game mainly consists of 1v1 actions, there can be up to 10 thousand on-ball actions during a game of football. The multitude of data collected then has to be interpreted in a comprehensive narrative which can ultimately be used for the purchasing of a player. The manager ultimately decides the most important factors for a certain player in a specific position, and the filtering process goes something like this :

“I’m looking for a centre-back who wins aerial duels over 75% of the time, plays the ball out to the forwards on the counter-attack at least 90% of the time, has a clean sheet record of at least 4 out of 10 games, and commits less than 2 defensive errors per game”. This criteria is then applied to a list of players, from which a shortlist is created.

Then, you can go more in-depth to identify a player’s strong or weak points, such as finding data of a player’s right-footed passes of more than 20 yards, towards the left wing in the final-third of the pitch. You are able to create a list of 10 or 20 of these instances and determine whether the player can be used in a team’s system where he would be required to complete such actions. This process is then repeated a multitude of times for each potential recruit, and interpreted by the manager and his team of data researchers.

A success story of the moneyball concept applied to football is Matthew Benham’s involvement in  FC Midtjylland and Brentford FC. Although some would argue that the moneyball model hardly carries any weight in top-flight football, Benham’s acquisition of Midtjylland in 2014 was shortly followed by their first league championship a year later, since their creation in 1999. Moreover, Benham’s acquisition of Brentford in 2012 was followed with promotion to England’s second-tier in 2014, after a 21 year wait.

Although both clubs are not enjoying consistent success, Benham’s involvement in Midtjylland and Brentford has pushed both clubs to adopt different approaches, which resulted in a league title and promotion, respectively. Both clubs then have to adapt once more when they enter the top-flight and have to compete with bigger teams, though this simply means readjusting their approach and going from strength to strength. Midtjylland’s Europa League funds and Brentford’s promotion funds will allow both clubs to purchase more expensive players and improve their back-room activities.

Sport science has certainly come a long way in the last 20 years, but certain factors can simply not be analysed in a statistical narrative — or at least not as efficiently as a seasoned scout’s eye. As much as the moneyball philosophy has evidently benefited many football clubs, it remains to be seen whether or not its model is sustainable and above all, competitive.