Escola Universitària d’Enginyeria Tècnica de Telecomunicació La Salle

Final Thesis

Graduate in Management of Business and Technology

AN INVESTIGATION OF THE MAIN LIMITATIONS FOR THE IMPLEMENTATION OF BIG DATA IN FOOTBALL AND A CONCRETE APPLICATION AS A DIFFERENTIATION SOLUTION FOR U.D. LOGROÑÉS

Student Promoter

ÁLVARO SALARICH ROIG CHRIS KENNETT Management Case Álvaro Salarich, Barcelona 2018-19.

ACTA DE L'EXAMEN DEL TREBALL FI DE GRAU

Meeting of the evaluating panel on this day, the student:

D. ÁLVARO SALARICH ROIG

Presented their final thesis on the following subject:

AN INVESTIGATION OF THE MAIN LIMITATIONS FOR THE IMPLEMENTATION OF BIG DATA IN FOOTBALL AND A CONCRETE APPLICATION AS A DIFFERENTIATION SOLUTION FOR U.D. LOGROÑÉS

At the end of the presentation and upon answering the questions of the members of the panel, this thesis was awarded the following grade:

Barcelona,

MEMBER OF THE PANEL MEMBER OF THE PANEL

PRESIDENT OF THE PANEL

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Management Case Álvaro Salarich, Barcelona 2018-19.

TABLE OF CONTENTS

ACKNOWLEDGEMENTS ...... 3 ABSTRACT...... 4 EXECUTIVE SUMMARY ...... 5 INTRODUCTION TO THE PROBLEM ...... 6 The Spanish Football Pyramid...... 6 BACKGROUND ...... 8 Introduction to Big Data...... 8 Big Data in Football. Key industry players and their interrelation...... 9 But how all this performance data is collected and managed by these major players? ...... 10 Looking to other sports. Where are the next steps? ...... 12 Main limitations and barriers...... 14 SOLUTION PROPOSAL ...... 16 Step 1: The Club (UD Logroñés, S.A.D.) and its current situation ...... 16 What about the currently use of Data in the club? ...... 18 Step 2: The Proposed Solution: Differentiation through Big Data. Best Cases in the industry...... 19 Step 3: Applying the Solution...... 21 Step 4: Club’s Feedback...... 27 Summary of the Process...... 28 FINAL CONCLUSIONS ...... 29 APPENDIX ...... 30 1. Television Rights in Spanish LaLiga (Season 2017-2018): ...... 30 2. UD Logroñés official budget for 2018-2019 season:...... 31 3. Interview with Juan José Guerreros, CEO and Vice-President of UD Logroñés...... 32 4. Interviews with Carlos Lasheras, Sporting Director of UD Logroñés...... 34 Bibliography ...... 37

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Management Case Álvaro Salarich, Barcelona 2018-19.

ACKNOWLEDGEMENTS

I want to thank deeply all people working in UD Logroñés for their availability and the way they do everything easy. I had no doubt that they would help in the project in the way they have done because I am lucky to work with them and know how they are. More concrete, I want to thank Juan José Guerreros, vice-president and the ‘soul’ of the club, for all the help given to carry out this work and for being always there. And also, Carlos Lasheras, club’s Director of Football. To both of you, thanks for the total availability for any type of question and for giving me access to the economic and different data of the club. Your involvement has been vital. I will also want to thank Chris Kennett for his guidance and giving all kinds of advice through this project, and specially for his availability and the way he help me combine the realization of this Management Case with my professional activity. It has been a pleasure to have him as a promoter. And also want to make this extensible to all the teachers that I have had the opportunity to learn from during all these years. To my family, which have been by my side all these academic years, and my friends, who in one way or another have shared their support and willingness to help me, also coming up with useful ideas at different points.

Thank you.

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Management Case Álvaro Salarich, Barcelona 2018-19.

ABSTRACT

This management case aims to firstly analyze the current situation of the big data in the world of sports and in concrete in football, from its key players in the industry and their interrelations, its current applications and how they function to the main limitations and barriers, as a background to later proceed with the application. To apply the solution to a lower league club, a previous research, including interviews with people in charge of important departments of the club, has been conducted, in order to fully understand their needs and their objectives. Finally, a concrete, adapted and scalable solution has been presented to the Football Department of the club to try to achieve the demanded differentiation, key for its economical and sportive objectives.

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Management Case Álvaro Salarich, Barcelona 2018-19.

EXECUTIVE SUMMARY

The main objective of this Management Case is to try to shorten the distances so that the use of new technologies or more current ways of proceeding, such as Big Data, are also a reality in football, as is the case in other sports, like basketball, American football or baseball. To achieve this, it has been very important to understand or remember the hierarchy in football and the huge differences between top clubs and the rest, in terms of economical resources, available technology of the leagues or even people -or professionals- available to apply them. But not less important to understand previously how Big Data works, specially applied to sports and football in particular, which are the key players, which are the current limitations or barriers than football is facing in comparison to other sports or depending on the category in which we try to apply it, or what can be Big Data in a few year time. During this research, different case studios in the football industry have been appearing, from the biggest investments of Arsenal FC to some more concrete applications applied by less rich clubs as CD Leganés. And from these best cases in the industry and my own experience of some years working in the football industry, a concrete and feasible application came to my mind. The next step, and probably the most important one, has been to go from the application to a concrete and useful solution for a lower league club. Having the opportunity to work with UD Logroñés, the task has had to consist in understand the most the club, their Departments, their needs and objectives (in both economical and sportive perspective) and their problems and barriers they are facing to not achieving them. And once this research has been conducted, the club’s CEO and Sporting Director have explained the situation and the objective it has been totally clear, the solution has become a reality. Applying the solution, following the different steps, have not only been key for the primary objective of the management case of shorten the distances, and in some way showing that Big Data can be a reality, a useful tool, in 2019 for any football club in the world. It also has put in relevance and confirm the main barriers that the current Big Data in Football have and clarify which should be the next steps in order to achieve the extension of this practice. And also the critical difference between seeing the Big Data as a substitutive of current professionals and its methods or seeing the Big Data as a complementary tool has been explored and asked about to some players in the process, as a part of the feedback after the solution has been applied.

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Management Case Álvaro Salarich, Barcelona 2018-19.

INTRODUCTION TO THE PROBLEM

I have been working in the football industry for the past 2 years and despite it may sound not much time, for me it has been extremely intense, and specially, it has been enough to know, feel and understand the social, economic and even personal implications of succeeding or not, of being within the professional clubs or not. In football, the cake is extremely sweet (and profitable), but it is also very small and it is only shared within a small group of successful companies (clubs) which arrived to the top. Arriving there (and then maintaining the position) it is an obsession for each day more and more entrepreneurs, Asian investors, bored millionaires or Arab sheikhs, but also for the thousands of professionals that see how they life can drastically change in one way or another in only a few months. And also, for the fans, because we cannot forget at any point that is the most followed sport around the globe and all decisions have also a direct implication in the daily basis of entire cities and communities. Let’s start to introduce the situation in Spain:

The Spanish Football Pyramid.

The football league system in Spain consists of several leagues bound together hierarchically by promotion and relegation. The First and Second division (currently LaLiga Santander and LaLiga 1|2|3 respectively and for commercial reasons) are considered fully professional leagues and are operated by LaLiga (Liga Fútbol Profesional or LFP in the past). LaLiga is the national sports association which members are the same 42 teams that form the mentioned leagues (so every year change and can be less than 42 in the case that a reserve team compete on it). In the General Assembly the 42 clubs (usually represented by their presidents or people in charge) choose a President. The current president is Javier Tebas, who was elected to the post in April 2013 and re-elected in October 2016, with 37 of the 42 votes. Two of the main attributions of the President are the negotiation of sponsorship deals and the television rights, which are the main revenue streams of the vast majority of clubs in these 2 divisions. In 2017-18 season, the amount that clubs receive for TV rights was between 154M€ (FC Barcelona) and 43,3M€ (Girona FC and CD Leganés) in 1º Division and between 22,9M€ (Granada CF) and 5,2M€ (Lorca FC) in 2º Division, representing in some cases around 80% of the total income of the club. (For more information see Appendix 1). All Spanish football -included the 2 divisions operated by LaLiga- are under control of the Royal Spanish Football Federation (RFEF, the acronym in Spanish. Luis Rubiales the current President) but their decision power in the top-flight football is effectively very poor. Only the Cup tournament (Copa de S. M. el Rey), the ‘Supercopa’ and the referees and different specific tribunals are operated by the RFEF, and always in agreement with LaLiga. So, their real power starts from leagues under the 2ºDivision, which is from the 3º level of the pyramid. In fact, the RFEF is divided in 19 territorial federations in charge of regulate the lower categories and local leagues of every region.

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Management Case Álvaro Salarich, Barcelona 2018-19.

This 3º category of Spanish football is named Segunda División B (2ºB) -derived from the past hierarchy-, it is considered semi-professional (despite currently only a very few exceptions have no professional players on their teams) and is divided in 4 groups of 20 teams, applying a criterion of proximity in order to be formed. The teams that finish in the top-4 positions of each group (so a total of 16 teams) go into a promotion Play-Off and 4 of them get promoted to 2º Division and LaLiga. Also, 18 teams are relegated each year to the fourth level (Tercera División). In the 2018/19 season 22 out of the 80 teams are reserve teams of LaLiga clubs, which are allowed to be promoted if their first team is in 1º division. There are lots of differences in between being or not in LaLiga categories and these applies to every department of a club, but specially in an economic point of view there is something key: in 2ºB there is not a tv right fix fee for every club (and the individual sell of the tv rights represents only some thousands of euros, too far from the millions that you earn just to participate in LaLiga). This aspect plus the different other problems and poor conditions that 2ºB offers to their teams is what explain that this category is considered for professional clubs as “el pozo” (the hole). Being relegated to 2ºB for a long period puts your economic viability in serious danger, despite you reduce a lot your costs and, given the difficulty to be promoted, assume you may not be a professional’ league club again.

So, it is clear that for a club in 2ºB arriving to LaLiga is clearly The Problem. And in this management case I will present how I have been working with a 2ºB club in order to bring some differentiation to try to gain some advantage in order to improve the results of the players signed, and their consequent global results of the club in the pitch, to try to achieve the promotion.

“We are in a division that is deficient, that to be up in the table you need external injections of individuals and despite that nothing ensures you get promoted. Entering LaLiga allows you, with the correct management of resources, to make the club self-sustaining while the growth of the club could be accelerated dramatically. A club like ours grows more in 1 season in professional football than in 10 years here in 2ºB where resources can hardly be allocated. In LaLIga you also find business opportunities, such as achieving the concession of the stadium for the Matchday revenues, building an Academy or creating a brand that can be expanded internationally through TV, the power of the LaLiga brand or the signing of players of a certain nationality. “ - Juan José Guerreros, CEO and Vice-President of UD Logroñés -2º B club- (See Appendix 3)

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Management Case Álvaro Salarich, Barcelona 2018-19.

BACKGROUND

Introduction to Big Data.

From the first studies of the games of chance in s. XV and XVI to our current capacity to know the weather in advance, find where is more probable to find a castaway in the sea, show customers the advertisement that suits their feelings, etc. we have been discovering as society the power of the numbers and their consequent applications. As explained in “Prediction by the Numbers” by Daniel McCabe (NOVA Productions for WHGB Educational Foundation in 2018) on a daily basis, data and maths work together to help us visualize the future and understand what happens in our environment. A big data is one of these applications, it consists in extremely large data sets that with the appropriate technology can be used to extract useful information, make decisions, create models for different purposes, extract conclusions or make predictions for the future. Some are the factors that are key for the big data to work properly and give us the appropriate outcome, independently of which application or in which area we are working with the big data. We can talk for example of the importance of data quality (veracity), the velocity to be generated and processed, the variety of forms in which data can be presented or, of course, the volume. So, people and technology have to be prepared to work with these factors and extract useful information to finally create real advantage. As more precise have been our measuring methods to reduce the error margin and more powerful our computers to process, store and work with the huge volumes, more and better applications we have been able to develop using big data, so it is impossible not to be extremely optimistic and enthusiastic on what we will be able to do in the future. And in sports? Probably the pioneer was Billy Beane, when he was Sporting Director of the Major League Baseball team’ Oakland Athletics. As explained in the fantastic book from Michael Lewis: “Moneyball: The Art of Winning an Unfair Game” (2003), Beane applied a quantitative criteria, based on a model designed with big data of past seasons and different equations, to the process of signing players to try to create an advantage for his team, the one with lowest resources in the league, instead of the traditional subjective criteria applied for their scouts for decades, specially motivated for the impossibility to compete for the popular (and in theory best) players of the league and also with the ambitious idea to “change the rules, change this sport”. And he did it, OA’s went 4 consecutive seasons to the Play Off and in 2002 set a new record of consecutive wins: 20. But most important, he was followed by all the different professional in baseball and later in other sports and everyone started to look to quantitative criteria and big data to, at least, complement or enforce their subjective opinions. In fact, nowadays, all baseball, basketball and all this kind of extremely “numeric” sports have their own stats and analytics department that works with big data to try to predict and improve the performance of the players or help decide who can they promote from the second team or sign. In the particular case of football, big data have arrived a few years later and without such big importance as will be detailed in this management case, due to the particularities of this sport: only one time pause in 90 minutes of frenetic action, with a huge playing field with pretty total freedom for players (no without limitations of movement like backcourt violation) and with no clear separation between attack and defense: a game of transitions. 8

Management Case Álvaro Salarich, Barcelona 2018-19.

Big Data in Football. Key industry players and their interrelation.

The main players in the data management in football are the football clubs as customers and the companies providing software and data as the sellers. But clubs are not the only potential user of this data platforms or services, also representative agencies, independent scouts/coaches or the coaches and players itself for personal use are sometimes interested. Taking a close look to the football clubs, we can see that nowadays they all work as a company, with different departments, with a local and global perspective and with the different issues that a non-sportive company have to face, except for one particularity: matches and results affects all the departments and cannot be fully controlled or managed by “the company” (the club). In fact, most of football clubs in Spain are S. A. D. (Sociedad Anónima Deportiva, which is in Spanish corporate law a kind of public limited company for sportive activities). As explained in the “Managing Football. An International Perspective” book written by Sean Hamil & Simon Chadwick, in a modern football club we can find different areas or departments, starting obviously for the one in charge of the football area with a Sporting Director or Director of Football in the top of the structure and followed by different groups of analysts, scouts or coaches, some time distributed by geographical criteria or depends on specialization. Also, clubs that have a 2º team or women team have people specialized on it. Another department in football clubs (and very linked to the football) is the one in charge of the development of youth teams and the academy (or academies) in general. Communication and constant flow of information between these two departments is mandatory to ensure that both works in the same direction, with the same style, goals and mission. But as I said before, apart from these two departments -that are the most technical and special in comparison to other non-sportive companies-, football clubs have other departments, as for example: a communication department (that can be divided between the communication with fans and the attention to media, press conferences etc.), a marketing department (with the consequent merchandising area), a medical department (with different specialized areas), a sponsoring department (absolutely key for the revenues of the club and very linked to the MatchDay experience, hospitality packages etc.), finance department, social department (in charge of the socios renewal, the ticketing, etc.), protocol department (with special attention to the relation with other entities, companies and personalities), facilities management department, etc. And with no exception, all the different departments of the football club, as a company, can take -or are taken- strong advantage from the big data era in which we are living. But for this management case I will focus specially in the football department and the data that they use or can use to improve: the performance data. The other main player in the big data industry in football are the software providers, which include hundreds of different software and technologies specialized for different purposes. The main ones, just to be mentioned as they will be appearing during the case, are: Wyscout, Instat or Scout7 as video and stats database of matches and players events, STATS or OPTA as purely (deeper) stats and data, or Mediacoach or ChyronHego as full solutions for leagues and clubs.

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Management Case Álvaro Salarich, Barcelona 2018-19.

But how all this performance data is collected and managed by major players?

“From kick-off every touch of the ball is captured, including the player involved and pitch location,” explained Paul Neilson in an interview 4, head of performance analysis at Prozone Sports, the company that provides the technology to all twenty French Ligue 1 clubs -and used to provide it to the Premier League clubs before the 2015 agreement with EA Sports. It is not casual that both companies are after the two main football videogames databases (EA Sports’ FIFA and Football Manager, that uses Prozone technology). The way the data is collected is not so different despite the company that do the task. So, for example, ChyronHego that works with Bundesliga using their TRACAB technology operates in a similar way than Prozone and EA Sports: Using around 10 cameras, the programme creates a three-dimensional animation of the playing field and is capable of registering 3,000 touches of the ball per game. At 25 times per second, the system generates live, accurate X, Y and Z coordinates for every viewable object, including players, referees and the ball. It offers real-time, post-match and opposition data to be analysed. “In sport we are looking at an extremely large data set,” continues Paul Neilson. Professional clubs are receiving detailed data of 2,000 to 3,000 ‘events’ per match, and some of them are playing more than 60 matches per year. And that is not the only data to be analysed, clubs are also looking to the upcoming opposition matches, with their respective thousands of events. And even more if we look to the scouting department, which are looking to hundreds of players all around the world with their hundreds of events per match. That is why some important teams apart from using external tools and software, are really investing in data and are recruiting key people to analyse it to develop their own platform and strategy with an internal data analysis department. It was the case, for instance, of FC Bayern München, following Pep Guardiola’s arrival in 2013. According to Michael Niemeyer, club’s head of match analysis, the first thing that the former FC Barcelona coach tell him was: “The match analysis department is the most important department for me.”. He then explained that for him the video sessions and technology are absolutely key to success and to later bring his ideas to the pitch, and to have useful video sessions it is very important to have done a previously outstanding analysis in data and video terms 5. Another example of this extended practice between top flight clubs it can be seen at Arsenal FC, where instead of developing their own performance analytics department they directly bought an entire company, StatDNA, which was US-based and one of the leaders in the sector. It happened in 2014 and cost around 2 million pounds to the gunners, a big sum of money but not that much if we take a look closely to the annual expenditures in transfers or the possibilities and value that, after an appropriate internal restructuration, a leader in the sector tool can offer to the club in terms of scouting, talent identification, game preparation, post-match analysis and tactical, technical and physical insights in general 6. Another team investing in big data in football is West Ham United. Head of performance analysis, David Woodfine, assured that their data are so quickly available and analysed that they can, at least the key stats or insights, be shown on a screen in the dressing room at half time. Also, Woodfine explained that when preparing a game plan for upcoming opponents the club will consider scouts’ reports and video from previous games before matching this up with data. “We will look at the statistical reports

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Management Case Álvaro Salarich, Barcelona 2018-19. we can access and see if there are stats that can back up what we are saying from a statistical point of view”. 16 But the real revolution has arrived with Mediacoach, the software created by Mediapro for LaLiga clubs (1º and 2º division) that since 2018/19 have changed the way matches are analysed live. Previous to the last 2018 World Cup it was forbidden the communication between the coaches in the grass and the analyst and video-analyst in different positions in the stadium and also the electronic devices in the bench, but now both are legal and are practices that can be seen in every club. And in LaLiga, they are all working with the support of this exclusive software. Mediacoach compares constantly the performance of the players that are being caught with their different cameras and technology in the stadiums with the historic of their database of performance per player and per team and show the coaches and analysts the useful information following the criteria and preferences that they have previously introduced in the software. The idea of LaLiga is very clear: make big data available to everyone in their leagues. And with this software the raw data available is the same for everyone, so it is a kind of democratization of football and give all the possibility to work with top technology. Obviously, the resources that clubs may designate to store, analyze and work with these data in terms of other extra technologies or people can vary, but the initial point is the same for Real Madrid CF or for AD Alcorcón and that can help reduce the differences between clubs’ performances in the league. 7 8 But performance data is not only to work on own performance or to change match decisions, it can also be used to narrow down the search for potential transfer targets based on KPIs like physical size or pass completion rate. Suggestions are then evaluated by sending scouts to watch their performances. In a similar way, data analysis can also be used to highlight top performers in the club’s academy youth teams. “The stats can back up and add accountability to decisions the coaching staff make. It gives them a warm fuzzy feeling if they pick a player and when they go to the analysts the stats match” continue Woodfine. In definitive, to try to catch the best talent, the new youth star or the bargain of the next transfer window. To filter among the million players available, to save time and economical resources, to complement their analysis or, in some cases, even to take final decisions. Models are also appearing. The different companies in the data sector are creating their own indexes trying to mix everything and valuating players or teams with a number or creating systems to know the expected goals (xG) that a concrete line-up will assure to a match or a squad to a season. Also models to correctly put together the individual players analysis with the whole team analysis. 15 The majority of clubs, what they do is a combination between performance data provide externally, including a first general analysis, and then, in their different departments, they make their own second analysis looking more in detail to the concrete aspects that matter most for the particular club or situation. This second analysis it is conducted, indifferently on the department, for scouts and data analysts, which in actual football are present in both coaches’ staff and technical secretary & recruitment staff. The ones with less resources or that does not want to designate a big amount to this departments, in general, work in a similar way but without such an extent second analysis, just giving the analysis received to the final players (the coaches or the Director of Football) and they will be in charge of applying it in the appropriate way and with the objective that they consider.

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Management Case Álvaro Salarich, Barcelona 2018-19.

The last group of football clubs where costs are reduced to the minimum due to economic difficulties, with non-professional players and so, data analysis it is still seen as a luxury service instead of a clear possibility to gain advantage to competitors in same circumstances and to reduce the breach with stronger clubs. Also seems important to know how players are interacting with the feeling of knowing that everything they are doing is being registered and analysed. The West Ham employee believes that: “It is becoming a lot easier now with players. This is a generation of players coming through youth teams and under-21 development squads that have got analysts. They have been receiving data about their performances for years. These guys are used to receiving data, and they understand it now”. To go deeper, nowadays, most of the players have laptops or iPads with the appropriate software where they can see their performance, stats, etc. Wyscout, MAS Coach, and pretty every existing software allows coaches or technical staff to create an exchange platform inside the software where the players even can discuss. But players are not only monitored by cameras in stadiums, also by many quirky devices such as accelerometers, heart rate sensors and even local GPS-like systems. Many football fans discovered during the 2014 FIFA World Cup this, for many, unknown world, when was revealed that the German national squad wore Adidas’ miCoach elite team system during training sessions before and during the competition 9. The physiological monitoring service collects and transmits information directly from the players bodies, including heart rate, distance, speed, acceleration and power, and then display those metrics and all this information live to coaches during training, as well as post-session for in-depth analysis. Obviously, MiCoach is not the only device of this kind on the market. The major player is actually Australian company Catapult Sports, focused on Global Navigation Satellite System (GNSS) data. In indoor areas of the stadium when obstacles, like a closed roof, interfere with the satellite, appears ClearSky, which can be installed around the indoor area. ClearSky uses anchor nodes to track players’ movements, while the devices with transmitters are worn at the top of the back, held in place by a compression shirt that looks a bit like a sports bra and can be worn over or under the uniform 10. All these tracking devices were allowed for players to wear them only during training until July 2015, when FIFA approved them in matches – on the condition that they do not endanger player safety and that information is not available to coaches during matches. Despite this, the final decision on whether to adopt or reject these devices depends on every respective association, league or competition.

Looking to other sports. Where are the next steps?

According to Salvador Carmona, a former NBA data collector and analyst that has now founded a company to run big data services to football clubs called Driblab, “football is with no doubt the sport that is more reluctant to change, we can easily prove this fact with the Video Assistant Referee (VAR) technology: nowadays they are still discussing if introducing it or not in some leagues while in other sports we have had hawk-eye or similar techs for 20 years. The reason is probably that people who controls football and their top institutions are extremely traditional, also that is a sport that tends to be played in underdeveloped zones of the world and that it has been dominated by

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Management Case Álvaro Salarich, Barcelona 2018-19.

Latin people, which, stereotyping a bit, is less prone to technology than the USA and its sports, for example” 11. And to clearly find the next steps we have to look to other sports, so, following basketball structure, the applications will be developed (or continue developed, because data management is already being used in some of them) in the following order: 1. Set pieces (corners, free kicks, etc.): football involves a lot of people with an enormous degree of freedom in the pitch and without limitations of movement like backcourt violation, so obviously this kind of plays will be easier to fully analyse using data resources.

2. Transfers: the most popular example is the one involving N’Golo Kanté, the French midfielder, that signed for Leicester City in 2015 from French club Caen after the data management analysts of the Premier League team applied their method. But there are many others as will be more detailed later in the Best Cases section.

3. Improve player skills and technique: with an appropriate data analysis it is possible to see which movements, types of passes or zones of the foot used to kick the ball are less efficient than others. It is something that in other sports seems to have already happened (is said that Stephen Curry improve his shots using some information directly extracted from this data analysis) but in football still have created some doubts, as for example, when Real Madrid’s former manager Rafa Benítez told Croatian midfielder Luka Modric that should avoid continue kicking the ball with the external part of their foot, which according to Benitez’ data analysis is an inefficient type of pass. It may be an inefficient type of pass for the majority of players, but not for one of the most talented which after 10 years performing at the highest level and creating dozens of chances with that particular skill, seems strange to change it. 12

4. Optimize tactical systems and styles (or create them from zero in the lab): probably (as it happened in other sports) the last possible development is to create the full tactics from zero, just according to performance data analytics. It seems difficult in football but maybe in the long run we will see complete Academies of the top teams teaching all their kids to perform in a concrete and efficient style of play, fully develop from a computer and not only from a manager’s brain. But seems more realistic, at least in the short-run, to use data to avoid some movements or parts of the current manager style that data proved that are not as efficient as imagined.

And that is not all. We have seen how performance data management is used (or can be used) when analysing the own team, the opposition or the players to sign, in 3 out of 4 main football categories (physical, technical and tactical) but what about psychological? Can data management help coaches understand his players about this more unexplored world inside football? Or scouts to understand the reasons behinds surprising good or bad streaks? Moods, trust in a style, identification with a club, personal or family situation... All affects a player.

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Management Case Álvaro Salarich, Barcelona 2018-19.

Main limitations and barriers.

Probably the main barrier that any development in data management will face will be related to the velocity factor, to the difficulty to manage, analyse and extract useful information for such big tones of data in extremely short periods of time. With 2 matches per week and 5 training session, with 3000 events per match and per player recorded, with thousands of cameras extracting data, with physical GPS, ... Development in data has been driven by clubs while Federations and Associations seemed to still live in the past century -at least in these related aspects-, but probably, arrived to that point, it is necessary a cooperation between the whole industry to fully take advantage of data that only the ones in the power can lead. And the recent check of the laws about the use of real time data during matches sounds as a good starting point. Of course, technology plays an important role in trying to predict what is next in data management. As soon as better, more efficient and more complete (if possible) biometrics, tools and software appears, more the data management can develop. Furthermore, economic resources are very limited for hundreds of clubs, specially the ones that are not on the top divisions. And the available software in most cases don’t have access to data of lower categories (in the particular case of Spain, as it was said, MediaCoach only covers LaLiga matches which are the ones of 1º and 2º division teams). Because as lower the division is, more clubs are playing on it (more matches, more data needed) and less money can pay for the service, so obviously for the company is less cost-efficient to try to catch, store and manage data of 3º division than 1º division. And despite the 1º division clubs that can pay for an internal department that gains them advantage and complement the software, these 3º category clubs or so cannot pay for a service. So, if the software available didn’t give them the data and they cannot catch the data for themselves, these is the main barrier for them to follow the trend. And as it was said, football is extremely reluctant to changes, specially to drastic ones as the some of the data analysts as Salvador Carmona proposed. The controversy about this topic is already created and of course majority of current football professionals have many different arguments against the fully implementation of performance data analysis, at least as a substitutive of people (scouts, coaches, ...), the ones that accept it, see it as a tool, a perfect tool in fact, to help, to improve, to complement the reports, to reduce time, to save resources, to try to avoid failure in transfers or to help the development of players and tactics. 17 “A data analysis can help a player to take better decisions in some situations or to know better the opponent, for example in case of goalkeepers in the penalty shot-out, but a coach, specially a coach of under age categories, have a commitment of canalize the creativity, of potentiate the innate talent, he can’t prevent a player of doing for example a skill that his player performs extremely well only because the analysis said that is not efficient at all. Football is absolutely unpredictable and specially in terms of profiles. In our current era of tall goalkeepers, Keylor Navas is winning titles at Real Madrid, or nowadays seems that old-school area strikers as Gerd Müller have disappear and only skilful forwards are useful, but Radamel Falcao is scoring dozens of goals with a ‘traditional’ forward profile. We cannot prevent this innate talent to arrive to the elite just because the data said are not efficient enough. That is extremely radical” argue Abel Rojas, a journalist in beIN Sports and coach. 11 13

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Management Case Álvaro Salarich, Barcelona 2018-19.

“Of course, we have to use the performance data analysis and evolve, but as a background, to back-up argumentation, not as a substitute. Data management in football is a help, not a finished product” believes Ted Knutson, StatsBomb, in an interesting argumentation. “It is certainly true that some people inside the game are reluctant to embrace data. There are plenty of holdouts and that is totally understandable. Some people feel that the use of data suggests that their last 30 years of knowledge are irrelevant. But: one, that is not true; and two, you need to be open to new ideas to improve. The game has always been about opinions and plenty of people have valid opinions based on years of experience. Analytics is about enhancing that experience”. 14

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Management Case Álvaro Salarich, Barcelona 2018-19.

SOLUTION PROPOSAL

Step 1: The Club (UD Logroñés, S.A.D.) and its current situation

Unión Deportiva Logroñés is a Spanish football club based in Logroño, La Rioja, currently -2018/19 season- competing in the previously explained 2ºB division but with the clear and expressed objective of promote to LaLiga and professional football as soon as possible and with a yearly budget that situates the club approximately in the top-10 of richest clubs of the category (excluding reserve teams). The club was founded in 2009 after buying the spot of the CD Varea (a very small neighbour club, surprisingly promoted from Tercera División, that accept to convert the team), so is one of the youngest in the Spanish football and have played all his 9 seasons in the same 2ºB division but with this aim of getting to the elite. UD Logroñés was founded months after the final retirement of competitions of the historical CD Logroñés, due to deep financial problems. This club was very popular in Spain in the 90’s and played 9 seasons in 1º division between 1987 and 1997, with some famous players and coaches as Julen Lopetegui, Juande Ramos, Javier Irureta, Quique Setién, Miguel Ángel Lotina or Oscar Ruggeri being part of it. Here it is some extra data about the club that serves me for applying the case studio:

BADGE

COLOURS

- Municipal Las Gaunas

- Capacity: 15.902 STADIUM - Opened: February 28, 2002 - Field size: 104 m x 66 m

Address Avenida Moncalvillo nº 1, Puerta 3, 26008, Logroño, La Rioja

Website: http://udlogrones.com/ Social Media @UDLogrones (Twitter) / @uniondeportivalogrones (Instagram)

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Management Case Álvaro Salarich, Barcelona 2018-19.

Main Shareholder & Félix Revuelta (Grupo KILUVA) with around 93% of the shares. President

Budget 1.860.000 Euros (For more information see Appendix 2). (2018/19 season)

Despite that is a young and small club, with less than 20 administrative people working on it, the club has a structure with different departments, following top-clubs organization. Each department have just a few people working on it or even just 1, but the structure is created and prepared to grow in case of promoting to LaLiga:

• Football Department: Is the most important department in every football club and in this case is divided in two: o First Team: The maximum responsible is Juan José Guerreros (CEO and Vice-President), he has the final decision and is the only one (apart from the President) able to sign contracts, transfers, etc. He controls the economic aspect of every operation and choose a Sporting Director (since the 2018/19 season is Carlos Lasheras) that along with his team of scouts and analysts control the sportive aspect of every operation. Apart from buying, selling and renewing players, the Sporting Director is the one in charge to choose a coach and his assistants and the direct responsible of first team results. o Academy: This department is in charge of the reserve team (currently in Tercera División -4º category-) and the lower categories (U-19, U- 16 etc.). The maximum responsible is Eduardo Valdovinos and is very important a good and fluent relation between him and the first team Sporting Director, to go all in the same direction. We can say that at least all the reserve team decisions are consensual with Carlos Lasheras (and even J. J. Guerreros).

“Each Sports Director have his way of working and you also have to be aware of the resources you have. We have a work group formed by very few people and with limited resources to travel, therefore, tools such as video analysis software such as Wyscout or Instat or platforms that broadcast the games like Footters have been key to reaching many sites with a much lower cost. From here, we try to organize to control the entire 2nd B, not only the Group where we are, because in the end any player in the category can be for us and we have to keep it under control. And we would be talking about 2000 players. Nor can we lose sight of the immediately superior and inferior category, as well as offers that come to us from abroad, although in this case because of the issue of resources that we talked about, our way of acting is more than waiting for what comes to us, not of trying to anticipate and actively follow these foreign competitions, because it is unfeasible. Knowing the players and knowing their situation in the market, then it is a matter of detecting the needs of our team and among the available profiles try to find the one that best fits in different factors, but that is why it is key already to have done the work throughout the season Scouting and knowing the profiles, to be able to destinate the time during transfer windows more to the negotiations and opportunities that may arise “ - Carlos Lasheras, Sporting Director of UD Logroñés (See Appendix 4)

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Management Case Álvaro Salarich, Barcelona 2018-19.

• Match Organization Department: Is the department in charge of both the Matchday experience (so all what happens in the Stadium before, during and after it) and organizing the logistic for all the away matches, finding friendly matches to play during summer, etc. The responsible is Miguel Isasi.

• Communication Department: Is the one that works directly with the media and the own social media channels and platforms (Twitter, Instagram, YouTube, etc.). The maximum responsible is also Miguel Isasi and there is a Press Officer (María Casado) apart from him.

• Legal Department: Is a key department for different reasons and has also an importance in the football department because they write the contracts with the clauses agreed by the department and the agent of the players. The responsible is Carmelo Cárcamo.

• Marketing Department: Is in charge of negotiating the different sponsorship deals (stadium, equipment, etc.), define the marketing strategy and try to attract new members, different events, etc. The responsible is Ernesto Arpón.

• Social Department: Is the department that interact directly with the members and public in general. Also, the one that coordinates the ‘Peñas’ and serves like a kind of attention to the client. The responsible is Pablo Jiménez.

What about the currently use of Data in the club?

After interviewing club’s Vicepresident and CEO, we easily can discover how far the club is from the elite teams, but the good predisposition and interest in achieving that position in technological and Big Data terms:

“At a technological level our situation may seem precarious compared to other companies that manage budgets similar to ours, but we must not forget that here the highest % of the budget is allocated to the salary of the players, so there is not so much left to invest in R&D or in technological equipment as in other places. However, compared to teams in the category, I think we cannot complain. For a couple of seasons, we have a database with all socios of the club, to digitize the entire subscription process and be able to perform different actions. Surely that is the closest to big data at the moment. In the sports area I know that all club professionals have their own computer with the software requested for the search of players or the preparation of games, such as Wyscout or other video programs. In addition, since this season, the Sports Director with his team has begun to create a detailed database of players. Hopefully we can invest more in this aspect and help us with technology to lead the growth we want to achieve. “ - Juan José Guerreros, CEO and Vice-President of UD Logroñés (See Appendix 3)

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Management Case Álvaro Salarich, Barcelona 2018-19.

While football professionals still showing a more distant position (or even less interest) with Big Data technology. Majority of them seem deeply confident in the way they have been working for ages and stay in the traditional easy stats as goals or matches played, without going deeper in the thousands of statistics that can measure through current Big Data technology:

“Yes, I have heard about Big Data. I know that for example teams like Alavés, Leganés or Betis in recent seasons are exploring this world. In our case, it is true that since we use software such as Wyscout or Instat, a series of statistics is available to us, which in some cases can be useful. To be honest, I respect all work and decision-making methods, but I need to see the player to make a decision about him. And not only see him once or 10 times on video, but get as close as possible, see him live if possible, feel how he behaves even before and after the game, talk to a coach who has had him or a former teammate to also meet to the person behind the player and ultimately talk to the player himself so that he can transmit to me that I am not mistaken. Obviously before this, in the process where interest arises, there we see if he has played games in recent seasons, the injuries he has had, in case of offensive players global data such as goals or assists, etc. “ - Carlos Lasheras, Sporting Director of UD Logroñés (See Appendix 4)

Step 2: The Proposed Solution: Differentiation through Big Data. Best Cases in the industry.

Knowing the situation, the business objective of reaching LaLiga and the club itself, it is time to define how this can be achieved. The quickest way of promoting in the recent years have been through big investments of money, which basically allow any club to sign players of upper categories (convincing them with high wages to go down one or even two categories). It has been the case of for example RCD Mallorca (with USA investors), Lorca FC (with Chinese investors) or CYD Leonesa (with Qatar investors). But in some cases, the extremely quick sportive growth has not been well based on good structures or a method. Except in the case of Mallorca -an historic club-, once both Lorca FC and CYD Leonesa have reached 2ª División, they have seen how their differentiation through pure economic power have disappeared with the rest of clubs in LaLiga -earning millions from TV- and have returned to 2ºB in the following year, with the foreign investors leaving the club (and in the case of Lorca FC loosing another category to 3º División for the economic problems derived). Also, some clubs have not reached the promotion despite the high investment and have developed high debts, extremely difficult to solve in a category with low revenues. It is the case of Real Murcia CF or RC Recreativo de Huelva, in 2ºB for years and increasing their debt season after season trying to escape, with current debts of millions of euros and in risk of bankrupt (as Salamanca CF, CD Logroñés, Club Polideportivo Ejido, etc. in the past). It is not the case of UD Logroñés with, as mentioned, a considerable big budget but not one of this kind, always ensuring the viability. So, the differentiation that can

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Management Case Álvaro Salarich, Barcelona 2018-19. add the plus to the football department to reach the objective have to came through a different path. Investing in infrastructure and in Youth Academy teams have been one of the principle lines of actuation, because that represents a permanent asset, not as the one-year wages of a player that can perform or not. And also, because growing own talented players as it is happening at the moment can both help the first team and the economy of the club through selling some of them. But in this management case I want to add another way of differentiation from the other teams in the category: the technology, and in particular: big data in football. In the Background I have explained how big data is already being collected, how clubs have developed their own data department, how they have hired people able to successfully apply and bring a concrete solution to both Sporting Directors (for signing players) and coaches (for preparing matches) and the main barriers, specially the economic one for lower division clubs. But before applying the theoretical solution and as a benchmark or way of complementing the initial part, let’s take a look to some concrete best cases in the football industry of applying the big data for taking advantage or differentiate from the competition:

➢ CD Leganés (Spain): This small club in the South of Madrid were promoted to 2º Division and LaLiga in 2014 and to 1º Division for the first time in their history in 2016. Their internal organization, infrastructure and resources were far too distance from the rest of the clubs in the category and most of the decisions in football department as signing players, investing in the 2º team, ... were taken by Asier Garitano, the first team coach that have led them to two promotions and had become a kind of general manager and more influent person in the club (and for the fans). It is said that also he took part in club decision as how they should design the future Academy. They achieved to keep a place in LaLiga avoiding relegation in seasons 2016/17 and 2017/18 and also obtain some incredible results in Cup competition as eliminating Real Madrid after winning in Santiago Bernabéu. But for the 2018/19 season, surprisingly, Asier Garitano didn’t renew his contract (and sign for Real Sociedad) and the club found themselves a bit orphan. So, for the imminent summer transfer window the club realized that did not have an optimal preparation or knowledge of different markets and opportunities, the main responsible of their signings for the last lustrum have left and despite club had been growing and hiring people, there was not a real structure and were not time enough. As a solution, club decide to externalize part of their processes and hire Driblab, the company founded by data analyst Salvador Carmona to help them in the transfers during the summer. Driblab extract between 10.000 and 12.000 data sets per match using an automatic software and the videos of the matches and has a database of stats of more than 65,000 players from 85 different competitions. They based their method in the similarity, they are able to find players with a high % of similarity to others. So, in the case of CD Leganés, once they know that the new coach will be Mauricio Pellegrino and have defined a style of play, they ask the manager for names of players that he knew or have coached before (in his previous clubs: Southampton, Alavés, Valencia, etc.) and will like to have again in the new squad. And using the Driblab method find similar players that can be sign with the limited budget of Leganés. At this moment (March 2019), CD Leganés is very close to avoid relegation for another year and most of the players signed during the summer have increased their value according to the specialized website Transfermarkt.

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Management Case Álvaro Salarich, Barcelona 2018-19.

➢ Leicester City FC (England): In the Background were presented how Arsenal FC or West Ham United FC invest millions in football data departments, but Leicester City started doing it before and in a less expensive way, and it was key in the growth of the club from 2º division team to become a regular in Premier League and even winning the league title in the 2015/16 season. It is clear that PL’s financial environment makes it difficult for teams outside the top six to compete for the best players, so force smaller clubs to show a high level of astuteness in their player acquisition and scouting. Leicester City define the internal advantages and the ones that can offer to talented players in comparison to the big clubs: they can make older talented players feel valued, they have a greater risk tolerance in transfers (can risk signing from lower leagues), they can offer game time to young talents and they are willing to take potential short-term losses (bad results in a season) for greater long- term gains. And knowing the strategy, they define a specific way of playing and start creating an own model which take a look to the define targets in the specific stats that affect their way of play. As Rob Mackenzie (Scout and recruitment analyst) explain, “We are able to track the movement of players on and off the ball. Our recruitment team used specific indexes that detailed information about a specific statistic. This tailor our focus to players who do well in lower leagues, and the use of statistics can enable us to find players who can fit in the profiles and add to our specific team style”. The previous mentioned example of N’Golo Kanté, the French midfielder, that signed in 2015 after the data management analysts founded that was the player in Europe that most times have recovered the ball in the opposite half of the pitch during the previous season, and that was the condition that manager Claudio Ranieri had given to the club scouts (style of play). Kanté played a key role in one of the most surprising achievements in the football history with his club winning the Premier League and ended up the season signing for Chelsea for a record-fee of 36 M€ and playing in French national team. The next season was elected Best Player of the Year in PL after another league title, this time with the blues. Others as Riyad Mahrez or Jamie Vardy also arrive from smaller clubs and have given Leicester City great results in sportive and economic terms.

Obviously, the scenarios presented correspond to teams from higher categories and higher economic levels and resources, but are good examples of how to compete with more powerful clubs applying a different and big data related strategy. Let’s try to scale it to this case.

Step 3: Applying the Solution.

To apply the Big Data to the Football Department of any club and in this particular Management Case to UD Logroñés, firstly, obviously, we need the data. They are some ways to gather the data as explained in the Background part, but any of them is cost effectively enough for a club of this category and even for me as individual to develop this Case. So, we will work with the Data that the mentioned software Wyscout use in its platform. It is a enough detailed data to develop a model for the Management Case and that can be useful for the Football Department but as it is not a data gathered by us, of course we do not have a 100% security that this data do not contain any error and we do not fully personalize the parameters.

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Management Case Álvaro Salarich, Barcelona 2018-19.

Following the Best Scenarios presented, the idea is to develop an easy and quick model that help the Football Department to find a concrete player or a short list of players, as a filter that avoid them the necessity to scout thousands of players, which will be impossible with current resources. To put in practice the model let’s take a concrete problem that UD Logroñés will face during 2019’s summer transfer window: Marcos André de Souça, the forward and top-scorer of the team, will end-up his 3-year period on loan by the Brazilian club Guaratinguetá, and will be joining Real Valladolid (in 1º Division). So, UD Logroñés needs to find a forward that have the potential of reach that level, with similar characteristics and that suits the way the team play, obviously at an adequate cost.

As said, I will use Wyscout’s data to develop the Model for the Solution.

Before navigating into the different characteristics and data sets of the player profile, it is better to define our model, which will consist in 7 key parameters that our target player has to have at least pretty similar to our current player, Marcos André. To decide which should be these 7 parameters we need some football knowledge and of course take a deep look into our own team. Because we are not only looking for a forward, we are looking for a forward that suits in UD Logroñés style of play.

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Management Case Álvaro Salarich, Barcelona 2018-19.

In the average comparation with the opponents in last season we can easily appreciate that UD Logroñés is a team that tend to have more possession and more passes than rival (so number of passes and the accuracy of them are important for any player in the team). Then, looking in detail to attacking data sets (as we are looking for a forward, we are not much interested in defensive data) we can see that despite the positional attack are predominant, UD Logroñés don’t hesitate to run if they are spaces (so the forward has to have these characteristic). While, for example, number of crosses and aerial duels is lower than the average, so we can not worry at all for theses parameters.

Now we can go to the player profile and start selecting the 7 parameters that we consider more important given the characteristics of the team, and that will be define our model. These parameters will be the following: - Scored Goals (average / 90’): we need a striker that score goals, obviously. - Expected Goals: which is a technical calculation that tells us a lot of the quality of his shots, taking less into a count de number of opportunities he has.

- Nº of Passes & % Accurate Passes: Due to our combinative style of play we are interested in strikers that actively participate in the creation of opportunities, not only finishing them.

-Nº of Dribbles & % of Successful Dribbles: An important characteristic in majority of offensive players in every team. It’s good that if the team cannot create an opportunity by combination, he can create one on his own, especially in teams with high possession rates (as UD Logroñés) that will face more defensive oppositions that difficult passing.

- Progressive Runs: As seen in team’s data set, UD Logroñés is a team that despite is not usually vertical, doesn’t hesitate to run if rival let them. So, the striker has to be prepared and used to do this kind of runs to allow the team to be flexible to this scenario. 23

Management Case Álvaro Salarich, Barcelona 2018-19.

Applying the data of the 7 parameters into an Excel sheet and applying a desviation % (5% for the most important parameters and 10% for the rest of the parameters)

we have the minimum results that our target forward have to show in the different parameters. This is our Similarity Model.

Now it is time to go to the advanced search and start selecting the filters for it. Apart from the 7 parameters of our model (with their appropriate deviation), we have to consider obviously the position (center forward) are other important filters as the age (we want a young player so we will choose under-25), their market value (we cannot pay more than around 100.000€) and the number of matches played last year (we don’t want a player without confidence or in bad shape).

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Management Case Álvaro Salarich, Barcelona 2018-19.

In Wyscout database are as much as 333.991 players, but after applying our Similarity Model we have found only 6 players with similar characteristics to Marcos André for what UD Logroñés ask to his forwards, and at the appropriate price and age. Now it’s time for the Sporting Director to analyze these profiles and decide which one prefers, instead of taking hours analyzing hundreds of players.

It is important to repeat that they are not exactly equal players (which is impossible), but they are players that have some concrete characteristics or aspects (the ones that the team consider more important for his style of play) very similar. In fact, if we choose one of the list of 6 and we look to the graph that Wyscout do for the players in comparison with Marcos André we can see many differences:

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Management Case Álvaro Salarich, Barcelona 2018-19.

But if we do the comparison graph with only the important characteristics, the ones in our Similarity Model, we can easily see that they are closer in that key aspects:

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Management Case Álvaro Salarich, Barcelona 2018-19.

Step 4: Club’s Feedback.

Once the Solution has been fully put in practice and some interesting results seems to have been appeared that can be useful for an immediate application or at a least a method and a new way of a working have been presented and understand by the current Football professional in the club, it is time to know his perspective about the experiment. Starting with an overall validation:

“I have to tell you that I was pleasantly surprised above all for its agility, for the speed in which we were able to apply the small model and make a filtering, which among many players would have been impossible, forcing us to reduce the sample where to look, or it would have taken us weeks. In addition, you as a worker in this world of football, show that you know how to apply it in a very practical and concrete way. I would sum it up in this: agility and precision. “ - Carlos Lasheras, Sporting Director of UD Logroñés (See Appendix 4)

Now we need to discover if it will end up here or can be a real option for future applications in the club. Will him use it again?

“Yes, why not. In addition, you have applied it using software such as Wyscout that I already use regularly and that has this function at our disposal but that I had never stopped to analyze or try to understand or look for a utility. Now knowing about it, it can be another option to consider when looking for a player. I always say that the more help we have, the better, because our work is very difficult and it would be absurd not to take advantage of it. I would be unable to get in front of a computer and end up making a decision without seeing the player, even the numbers and the other programs tell me that it is the good one. And like me, I think today the majority. As a complement, as long as it is that agile and concrete (and in our case without extra cost when coming integrated in a software that we already have) it can be a good option. “

And last but not least, it is a good moment to ask a football professional about, in his opinion, the main limitations and barriers of this technology:

“As a main limitation I would say that there is a section where numbers will never be able to enter and that is the mental section, the human component of the player. How he is in his day to day, how he reacts to different situations or stimuli positive or negative. The players are normal people and most of the week they spend training, living together, ... The match is only 2 hours a week, where they have to arrive with the correct moral and physical and mental activation, but we cannot analyze only what happens in those 2 hours. Then at a purely football level, I think that the range of statistics offered is already extremely extensive, they measure things that I would not have thought of ever measuring. Although, there is always something left to perfect and with time it will be done.”

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Management Case Álvaro Salarich, Barcelona 2018-19.

Summary of the Process.

And to sum up the process, it is time to do a short list of some advantages that this applied Big Data through Wyscout can give to a club like UD Logroñés, not only the ones seen in this process for the Football Department, also to other levels of the club just applying it in the same way:

ADVANTAGE TO WHOM HOW

Increase the number of Scouts / Using software in which thousands players that can be followed Football of players are available, not only or signed. Department the ones in the league.

Football Giving him more data to change / Improve the Decision Making Department complement his decision will help him reduce the margin of error.

Using existing software will not Reduce costs. Club’s have an extra cost and may reduce

economy some unnecessary ones.

Comparing to others and using Know better his weak points. Players objective data can help them know

where to improve.

Extra information about own team and players or Coaches Using the same parameters opposition ones. available.

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Management Case Álvaro Salarich, Barcelona 2018-19.

FINAL CONCLUSIONS

In 2019 Big Data in football is an extensive practice for many different top clubs around the world. What some years ago was seen as a risky investment or some strange technology is nowadays a day to day resource for many football professionals, thanks to its big range of applications, from measuring the physical performance to the match preparation and analysis of the coaches and analysts. One of these applications, and probably the one that still more controversial or less accepted, is the one put in practice in this Management Case: the use of Big Data in the process of scouting, filtering and signing a player. Despite this, in this Management Case we have seen a very concrete application of Big Data for filtering players applied with the Sporting Director of UD Logroñés, a club in 2ºB Division in Spain with the clear objective of getting promoted to LaLiga in order to continue growing and achieving their business objectives, but a bit desperate after 10 years failing to success in this objective. We have contributed to show that Big Data can bring some differentiation to the way they traditionally work, helping the Football Department increase the number of players that can be under scope at the time that they can save time and economic resources, while giving also more information to support or take decisions. Knowing clearly the profile of the club, their problem and their available resources, and looking for a very concrete and applied solution, we have reached a kind of agreement with club’s Director of Football, in which he has left some prejudices about Big Data and has shown a good predisposition to use the solution as a complement, as a new tool, while don’t affect or drastically change his traditional way of working. Just this reluctant to change attitude is one of the keys, in my opinion, of what is needed to be solved for a total integration of Big Data in Football, apart from the mentioned limitations of the technology: as the economic capacity to arrive to lower leagues or the difficulties to measure some unmeasurable aspects as mental ones. Despite this, I truly believe that in an upcoming future Big Data will reach all the clubs, independently their division or resources, once can fully overpass this barriers: “be cheap, be simple to use and make clubs feel that it is a necessity - and not a luxury - to have it”. As Carlos told me in his feedback interview after applying the solution. “Remember when the clubs started signing goalkeeper coaches, rival analysts, ... They only were extended to all levels when those 3 keys were given. And with Big Data it won’t be different”. But, to sum up, I feel that seems far more feasible to find Big Data as a tool, than as a total substitution of scouts and its processes.

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Management Case Álvaro Salarich, Barcelona 2018-19.

APPENDIX

1. Television Rights in Spanish LaLiga (Season 2017-2018):

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Management Case Álvaro Salarich, Barcelona 2018-19.

2. UD Logroñés official budget for 2018-2019 season:

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Management Case Álvaro Salarich, Barcelona 2018-19.

3. Interview with Juan José Guerreros, CEO and Vice-President of UD Logroñés.

As said, apart from being the CEO and Vice-President of the club, he is the maximum responsible of the Football Department, and the only (apart from the President) able to sign contracts, transfers, etc. He controls the economic aspect of every operation and choose a Sporting Director (since the 2018/19 season is Carlos Lasheras).

• Llevas en el club prácticamente desde su fundación hace casi 10 años, pero ¿cómo ha evolucionado el club desde que te convertiste en el máximo responsable de las decisiones del día a día en junio 2015?

El club está siguiendo un proceso de crecimiento. Es un proceso largo y quizá desde fuera a veces no se aprecia o puede parecer muy lento, pero tenemos unos recursos limitados por la categoría en la que estamos y tenemos muy claro que no podemos cometer errores del pasado: gastar más de lo que ingresamos y endeudar el club. El club crece día a día, cada año hay más profesionales trabajando, estructuras más completas y más recursos a todos los niveles, pero es difícil hacer equilibrios entre invertir en el club a la vez que has de invertir en jugadores competitivos para lograr los objetivos deportivos.

• Pero el objetivo sigue siendo el mismo: el ascenso a LaLiga. ¿Podrías explicar brevemente la importancia a nivel empresarial de lograrlo?

Sin ninguna duda. Nuestro objetivo es ascender a Segunda División porque las implicaciones a todos los niveles son vitales. Estamos en una categoría que es deficitaria, que para estar arriba necesitas inyecciones externas de particulares y pese a eso nada te asegura salir de allí. Entrar en LaLiga te permite, con la correcta gestión de los recursos, hacer al club autosostenible a la vez que el crecimiento paulatino, que te explicaba anteriormente, se podría acelerar de forma drástica. Un club como el nuestro crece más en 1 temporada en el fútbol profesional que en 10 años aquí en 2ºB donde apenas se pueden destinar recursos. También se te abren oportunidades de negocio, como lograr la concesión del estadio, construir una Ciudad Deportiva o crear una marca que se pueda expandir internacionalmente a través de la tv, el poder de la marca LaLiga o el fichaje de jugadores de una determinada nacionalidad.

• A nivel tecnológico, ¿cuál es la situación actual y cómo está creciendo el club en ese aspecto? ¿Qué rol comienza a jugar el big data en los diferentes departamentos?

A nivel tecnológico nuestra situación puede parecer precaria en comparación con otras empresas que manejan presupuestos parecidos al nuestro, pero no hay que olvidar que aquí el mayor % del presupuesto se destina al salario de los futbolistas, no hay tanto espacio para invertir en I+D o en equipamiento tecnológico como en otros sitios. Pese a ello, en comparación con equipos de la categoría, creo que no podemos quejarnos. Desde hace un par de temporada tenemos una base de datos

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Management Case Álvaro Salarich, Barcelona 2018-19.

con todos los socios para digitalizar todo el proceso de los abonos y poder realizar diferentes acciones. Seguramente eso sea lo más cercano al big data por el momento. En el área deportiva me consta que todos los profesionales del club tienen su propio ordenador con los softwares solicitados para la búsqueda de jugadores o la preparación de partidos, como Wyscout u otros programas de vídeo. Además, desde esta temporada, el Director Deportivo junto a su equipo de trabajo ha comenzado a crear una base de datos detallada de jugadores. Ojalá podamos invertir más en este aspecto y ayudarnos de la tecnología para liderar el crecimiento que queremos realizar.

• ¿Qué impide a un club de 2ºB apostar más decididamente por el big data? ¿Es todo cuestión económica o también hay cierta desinformación o miedo al cambio?

En nuestro caso el motivo principal es económico. Aunque también es cierto que otros factores pueden afectar. Como decía anteriormente, hay que hacer equilibrios con la inversión en salarios de futbolistas, que al final es lo que los aficionados piden y lo que nos da de comer día a día con sus resultados. Hasta hace poco en esta categoría todo el dinero se ha destinado a los jugadores, pero poco a poco hemos ido introduciendo gastos en otros aspectos que nos van a hacer crecer a medio/largo plazo, intentando no perder la competitividad deportiva a corto plazo. Sobre el tema de la desinformación, es cierto que en el fútbol hay muchos profesionales que llevan muchas décadas trabajando de determinada manera y pueden sentirse más extraños con algunas practicas o incluso amenazados de alguna forma, pero como en toda integración tecnológica, es un proceso gradual y actualmente ya todos los futbolistas, entrenadores o profesionales que empiezan por otras vías, están trabajando con tecnología.

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Management Case Álvaro Salarich, Barcelona 2018-19.

4. Interviews with Carlos Lasheras, Sporting Director of UD Logroñés.

He was chosen by the CEO to lead the Football Department since June 2018, and along with his team of scouts and analysts control the sportive aspect of every operation. Apart from buying, selling and renewing players, the Sporting Director is the one in charge to choose a coach and his assistants and the direct responsible of first team results.

Part I (Before applying the Solution)

• De forma breve, ¿cómo funciona el proceso de seguimiento y fichaje de un jugador?

Cada Director Deportivo tendrá su forma de trabajar y también tienes que ser consciente de los recursos que tienes. Nosotros tenemos un grupo de trabajo formado por muy poca gente y con recursos limitados para viajar, por tanto, herramientas como los software de vídeoanálisis como Wyscout o Instat o plataformas que emitan los partidos como Footters han sido claves para poder llegar a muchos sitios con un coste mucho menor. A partir de aquí, intentamos organizar para controlar toda la 2ªB, no solo el Grupo donde estamos, porque al final cualquier jugador de la categoría puede ser para nosotros y hemos de tenerlo controlado. Y ya estaríamos hablando de unos 2000 jugadores. Tampoco podemos perder de vista la categoría inmediatamente superior y la inferior, así como ofrecimientos que nos llegan desde el extranjero, aunque en este caso por el tema de recursos que hablábamos nuestra forma de actuar es más de esperar a lo que nos llega, que no de intentar anticiparnos y seguir activamente esas competiciones extranjeras, porque es inviable. Conociendo los jugadores y sabiendo de su situación en el mercado, es cuestión de detectar las necesidades de nuestro equipo y entre los perfiles disponibles intentar encontrar el que mejor encaje en diferentes factores, pero por eso es clave ya haber hecho durante toda la temporada el trabajo de Scouting y de conocer los perfiles, para poder destinar las ventanas de traspasos más a las negociaciones y oportunidades que puedan surgir, sin perder tiempo en ponerse a recuperar partidos antiguos de ese jugador.

• ¿Interviene algún factor numérico más allá del económico en los procesos o se basa todo en opiniones subjetivas?

Respeto todos los métodos de trabajo y de toma de decisiones, pero yo necesito ver al jugador para tomar una decisión sobre él. Y ya no solo verlo una o 10 veces por vídeo, sino acercarme lo máximo posible, verle en directo si es posible, palpar cómo se comporta incluso antes y después del partido, hablar con algún entrenador que le haya tenido o algún excompañero para conocer también a la persona que hay detrás del jugador y en última instancia hablar con el propio jugador para que me acabe de transmitir que no me estoy equivocando. Evidentemente antes de todo esto, en el proceso donde surge el interés, allí lógicamente pues miramos si ha jugado partidos en las últimas temporadas, las lesiones que ha tenido, en caso de jugadores ofensivos datos globales como goles o asistencias, pero el jugador es mucho más que todo ello.

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Management Case Álvaro Salarich, Barcelona 2018-19.

• ¿Conoces el big data (estadística avanzada) y en particular sus aplicaciones al mundo del fútbol, o más concretamente, a la captación de jugadores?

Sí, he oído hablar sobre ello. Sé que por ejemplo equipos como el Alavés, el Leganés o el Betis en las últimas temporadas están explorando este mundo. En nuestro caso es cierto que desde que utilizamos los softwares que comentaba antes (Wyscout o Instat) se nos pone a nuestra disposición una serie de estadísticas que en algunas ocasiones puede ser útil.

• ¿Conoces algún compañero de profesión que esté actualmente tomando decisiones basadas en el big data? ¿Crees que puede ser una práctica habitual próximamente?

De los que te comentaba anteriormente, conozco la realidad de como lo están aplicando en el Alavés y allí lo que han hecho ha sido crear un Departamento paralelo. El Big Data no está integrado como tal en la Dirección Deportiva o en la preparación de partidos, pero sí que desde ese Departamento se sugieren jugadores encontrados gracias a la aplicación de esto a la Dirección Deportiva, como un complemento, como si fuera un ojeador extra. Luego la Dirección Deportiva lo estudia y lo valora, para tomar una decisión. Supongo que se extenderá más o menos en función de los resultados que se obtengan, como todo, pero a mí personalmente mientras sea una ayuda, no me parece mal. Lo que no podemos es volvernos locos.

Part II (After applying the Solution)

• ¿Cómo valorarías de forma general la solución aplicada?

Ya sabes que soy una persona muy sincera, pero te he de decir que me ha sorprendido gratamente sobre todo por su agilidad, por la velocidad en la que hemos podido aplicar el pequeño modelo y hacer un filtrado, que entre tantos jugadores nos hubiera sido imposible, obligándonos a reducir la muestra donde buscar, o nos hubiera llevado semanas. Además, tú como trabajador de este mercado creo que has sabido como aplicarlo de una forma muy práctica y concreta, sin intentar vender la moto o aspirar a un imposible. Lo resumiría en esto: agilidad y precisión.

• ¿Crees que puede tener cabida a la hora de buscar jugadores en los próximos mercados? ¿Estarías dispuesto a utilizarla?

Sí, porque no. Además, lo has aplicado utilizando un software como Wyscout que ya utilizo habitualmente y que tiene esta función a nuestra disposición pero que nunca me había parado a analizar o a intentar entender o buscar una utilidad. Ahora sabiendo de ello o sabiendo que tú la dominas, puede ser una opción más a tener en cuenta a la hora de buscar un jugador. Yo siempre digo que cuantas más ayudas tengamos, mejor, porque nuestro trabajo es dificilísimo y sería absurdo no aprovecharlo.

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Management Case Álvaro Salarich, Barcelona 2018-19.

• ¿Crees que el big data puede sustituir a las opiniones subjetivas o su límite en este contexto está en ser un acompañamiento a la hora de tomar las decisiones?

No sé si puede o no, porque no domino lo suficiente para afirmarte con rotundidad si el Big Data está capacitado para sustituirnos de alguna forma, pero sí que te digo que yo sería incapaz de ponerme delante de un ordenador y acabar tomando una decisión sin haber visto al jugador por mucho que los números y los demás programas me digan que es el bueno. Y como yo, creo que a día de hoy la mayoría. Lo que hablábamos antes, como complemento, siempre que sea así de ágil y concreto (y en nuestro caso sin coste extra al venir integrado en un software que ya contratamos) puede ser una buena opción, pero yo dejar de ver fútbol y ponerme a hacer números todo el día para tomar decisiones, no lo veo. Me cuesta creer que al final sean las máquinas las que terminen fichando. O decidiendo a quien fichar, porque imagino que la negociación sí que la seguirán haciendo los humanos, bueno, quién sabe (risas).

• ¿En qué consideras que puede mejorar o desarrollarse el big data para ser más completo o para llegar a todos los clubes (Teniendo en cuenta que lo mostrado en esta práctica no es el Big Data más desarrollado del mercado, ni de cerca, sino lo más accesible que tenemos a nuestra disposición)?

Seguramente hay un apartado donde los números no vayan a poder entrar nunca y ese es el apartado mental, el componente humano del jugador, como es en su día a día, como reacciona ante diferentes situaciones o estímulos positivos o negativos. Los jugadores son personas y la mayor parte de la semana la pasan entrenando, conviviendo y siendo personas normales. El partido solo son 2 horas a la semana, donde han de llegar con la correcta moral y activación física y mental, pero no podemos analizar solo lo que ocurre en esas 2 horas, el ideal sería saberlo todo sobre ellos antes de ficharlos. Luego a nivel puramente futbolístico, creo que el abanico de estadísticas que ofrece Wyscout (o más incluso si tenemos en cuenta otros softwares que he podido leer como Mediacoach) es ya extremadamente extenso, miden cosas que no se me hubiera ocurrido medir nunca. Aunque estoy seguro que algún experto en estadísticas todavía echará en falta algún parámetro que a mí se me escapa. Siempre queda algo por perfeccionar y con el tiempo seguro que se irá haciendo. Y sobre lo de llegar a todos los clubes, las claves son las de siempre: que sea barato, sencillo de utilizar y que los clubes sientan que es una necesidad -y no un lujo- tenerlo. Así se crea el mercado. Recuerdo cuando los clubes empezaron a fichar entrenadores de porteros, analistas de rivales, … Solo se extendió a todos los niveles cuando se dieron esas 3 claves.

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Management Case Álvaro Salarich, Barcelona 2018-19.

Bibliography

1 ”Prediction by the Numbers” by Daniel McCabe (NOVA Productions for WHGB Educational Foundation in 2018)

2 “Moneyball: The Art of Winning an Unfair Game” by Michael Lewis (2003)

3 “Managing Football. An International Perspective” by Sean Hamil & Simon Chadwick

4 http://business-technology.co.uk/2014/03/what-a-player-how-big-data-gives-premier-league- football-clubs-an-edge/

5 https://fivethirtyeight.com/features/bayern-munichs-head-of-analytics-tells-us-how-pep- guardiola-has-embraced-stats/

6 https://www.theguardian.com/football/2014/oct/17/arsenal-place-trust-arsene-wenger-army- statdna-data-analysts

7 https://www.abc.es/contentfactory/post/eslaliga/laliga-apuesta-por-la-tecnologia-para-hacerse- mas-competitiva/

8 https://www.elconfidencial.com/deportes/futbol/2011-02-10/la-lfp-y-mediapro-crean- mediacoach-un-analizador-de-juego-en-tiempo-real_525500/

9 https://datafloq.com/read/how-big-data-is-changing-the-world-of-football/1796

10 https://blogs.deusto.es/bigdata/el-futbol-y-big-data-parte-i/

11 Podcast: http://www.ecosdelbalon.com/2017/11/podcast-futbol-entrevista-estadistica- avanzada-salvador-carmona/

12 http://www.lavanguardia.com/deportes/futbol/20160208/302001343093/modric-benitez-real- madrid-granada.html

13 Scout7 podcast: http://directory.libsyn.com/episode/index/id/6074174 14 https://statsbomb.com/ 15 https://www.theguardian.com/football/2017/mar/30/expected-goals-big-football-data-leicester- city-norwich

16 http://www.thepfsa.co.uk/single-post/2017/01/12/Why-Football-Remains-The-Most- Unpredictable-Game---Even-For-The-Experts

17 https://www.marcadorint.com/portadas/salvador-carmona-analisis-datos-futuro-ha-pasado-la- nba-la-nfl-futbol-no-iba-una-excepcion/

18 https://www.elconfidencial.com/tecnologia/2018-10-27/algoritmos-software-real-madrid-barsa- big-data_1636678/

19 https://driblab.com/es/2018/09/07/el-cd-leganes-agradece-a-driblab-sus-servicios/

20 https://business.linkedin.com/talent-solutions/blog/talent-analytics/2018/world-cup-star- recruited-using-data

21 https://pathfinder4.com/quantifying-the-beautiful-game-how-analytics-and-big-data-is-helping- to-shape-football/

Own investigation and sources.

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