It makes sense to start this
piece with two quotes from German football journalist and author of a recent
book “Football Hackers”, Christoph Biermann who said, “data is part of an
ongoing evolution that changes football from a game of opinions into one of
knowledge. (Biermann 2019, pg8) The writer also makes the strong point that
“the future of football will not simply belong to those with the best data, but
those who draw the best conclusions from the information at their disposal.”
(Biermann 2019, pg8) This piece will discuss how data analytics and information
systems have impacted the world of football and the industries around it over
the last few decades. This piece will analyse how data has change football
tactics, scouting of players, player fitness and the betting industry. Who is using this data? How is it being used,
and why?
Definitions, History and
Influences
“Data analytics is the science
of analysing raw data in order to make conclusions about that information.”
(Investopedia 2019) Football, like other sports, is providing analysts with an
ever-growi
ng amount of raw data to investigate and interpret. This data along
with modern-day Information systems which is “an integrated set of components
for collecting, storing, and processing data and for providing information, knowledge,
and digital products,” (Encyclopædia Britannica 2017) have built the data
culture we see in football in 2019.
ng amount of raw data to investigate and interpret. This data along
with modern-day Information systems which is “an integrated set of components
for collecting, storing, and processing data and for providing information, knowledge,
and digital products,” (Encyclopædia Britannica 2017) have built the data
culture we see in football in 2019.
(Sandle 2018) tells us that
“the rate at which knowledge is becoming available is doubling every 12 months
and on a curve predicted to rise even faster.” See graph 1 below for a
representation of this. While not a perfect 100% increase, the increase is
stark.
Source: Chicago
Analytics Group
With this in mind, it is no
surprise of the growing need for Information systems which can quickly process
data and present it in an easy and understandable way. It is also no surprise
that information is playing a more prominent and more significant role in sport
every day. Data in sport goes back to the beginning of modern sport itself with
information like how many of the previous five games a team won. The raw data
that is transformed into information systems we see in football nowadays is a
relatively new phenomenon. Much of its influence is from American sports such
as hockey, basketball and baseball. One example of the explosion of data in
American sports in the book “The Art of Winning an Unfair Game” where the
author Michael Lewis wrote a book about how a baseball team the Oakland A’s
closed the gap between themselves and the wealthier franchises by using
analytics to find undervalued players.
The author credits the book to a simple question; “How did one of the
poorest teams in baseball, the Oakland Athletics, win so many games?”
Who are the Main Football Data
Providers and Users of Information Systems?
On stats.nba.com, users can
view and interpret players statistics such as running speeds, shots taken, the
place from where shots and passes happened, head to head records, player heat
maps, player comparison and player impact tools. American sports have for a
long time taken real-time data that may not seem like much at the time, but
when gathered consistently and over long periods can explain sports in
incredible detail. This data can then be transformed into information to be
interpreted just like any business would use information like a sales report.
We see unstructured data such as video turned into structured data, that with
the help of information systems can be presented in charts, graphs, tables and
dashboards.
Football now has many
companies offering in-depth statistics about football with the help of
information systems. Such sources include transfermarkt.com,
football-observatory.com, whoscored.com, optasports.com, smarterscout.com and
many more. All of this information is used by fans and clubs alike to gain a
better understanding of the game. It also helps them gain an advantage over the
competition on and off the pitch. See Graph 2 to see how New York based company
smarterscout have used a dashboard to breakdown the Premier League performances
of Norwich FC right-back Max Aarons. This dashboard is an example of structured
data.
One reason why statistics were
brought into American sports sooner than football a game which has often seen
to be dominated by Europe and South America, was that the data was easy to
interpret due to a straightforward reason. It had natural breaks, or at least
that was the argument for sports like American football, baseball and even the
English sport of cricket. According to (Coles 2013) football was a dynamic
sport seen as “is too fluid, too fast and too random to assess open play” to
implement such strict data collection. It was, therefore, a game impossible to
examine from an imperial standpoint.
Role of Information Systems Play Off The Field
In the fast and demanding
world of football clubs need accurate knowledge quickly. Information Technology
which “helps to optimize the use of scarce resources through intelligent
information support for decision making, helps further in its implementation by
support co-ordination effort without wasteful delays.” (O Brien & Marakas
2010) Data can now be the difference in success and failure on and off the
pitch. But on the other hand according, to (Kishore, Zang, Ramesh 2004) “information
systems are only a particular type of work system that support other
organizational work systems.”
It is easy to forget that the
super clubs like Barcelona and Manchester United are much more than 11 players
who play on a Saturday. They are large businesses with revenues in the hundreds
of millions. In 2018, Real Madrid had a revenue of over €750 million. (Deloitte
2019) With this comes many responsibilities such as marketing and customer
service. “All football clubs now utilise the internet as a direct channel for
accessing their fans and providing them with the necessary information. “This
process allows fans with online capabilities to access up-to-date information
by accessing the official club website.” (Cleland 2011) This has expanded in
recent years to social media where many clubs have millions of followers on
Twitter, Facebook and Instagram. Clubs can use Information Systems to
automatically send updates to fans via email or by an app on topics such as
ticket prices, travel arrangements, and club updates. Information Systems could
also be used within clubs to set up services such as instant messaging,
management of documents, cash management and email. (Green 1999) pointed out in
his piece Football Information Services that “football clubs are more dependent
than ever on information services to market their particular brand.” (Kishore,
Zang, Ramesh 2004) backed this up further when they said that “workflow is
central to integrative business information systems.” Football clubs would find
it impossible to manage such volumes of information without Information
systems.
How Football Data Is Collected
Information Systems also make
the storing of information much more efficient and fast. For example, companies
such as Titansensors have developed a GPS tracker that measures players
performance in real time. The sensors measure data such as sprint distance,
sprint speed, muscle soreness and conditioning scores. (TitanSensor 2019)
Observe Table 3 to see all of the offered metrics. The introduction of such
technology is seen by many as the “one of the most significant advances in
football over the last decade.” (Medium 2019) The new technology has not just
increased the amount of data that coaches have but it is also reduced the time
needed to analyse the information.
Companies such as Statszone.tiki-taka.co use
their app to provide anyone willing to pay the monthly fee with in-depth stats
of football games. It is thanks to the efficiency of modern-day information
systems, real-time data collection and internet speeds that they offer their
service in real-time with minute by minute change to metrics on the app as they
change on the pitch. Information is then presented on easy to understand
dashboards. See graphs 4-6 below as an example of in-depth statistics of Dries
Mertens as Napoli beat Liverpool 2-0 in Italy on September 17th, 2019. Graph 4
presents the 24 successful and seven unsuccessful passes the Belgian made.
Graph 5 shows the five times he retrieved the ball during the game and where
the actions took place. Finally, graph six shows the crosses the player
attempted during the game. Much of the data industry is possible due to a
company known as Opta. They specialise in the collection of sports data.
According to (Opta 2019) “data is recorded, analysed and distributed using a
bespoke system that allow us to provide our data quickly, reliably and securely
to customers through a range of solutions.”
Graph 4-5. Source Stats Zone App
Graph 6. Source Stats Zone App
How It Impacts In-Game Tactics
And Coaching
JOHAN Sports are another
business who offer GPS tracker services to professional football clubs. JOHAN
Sports promise that their service will help identify when players have "an
increased risk of injury" or to "create the ideal periodization
schedule with the use of data" and "information on how to adjust
training load". When football coaches can examine the fitness of levels of
their players in real-time, this unstructured data quickly becomes structured
data leading to better decision making. Sunderland fitness coach called a
similar technology from STATsports is "quite an integral part of the whole
backroom team's work." (Wright 2016) Moreover, that "the technology
allows clubs like Sunderland to tailor their players' workloads individually
and fine-tune their training through the week" (Wright 2016) This allows
clubs to push players to their limits but also to inform players to rest when
needed to prevent injury.
As mentioned already, in-game
statistics can impact how a team plays, who starts a game, for formation is used
and so on. These are all examples of decision making. The introduction of
statistics into the world of football has been a game-changer. (Dario 2002)
argued that “advances in information technology have made it possible to
augment and improve the feedback athletes receive during training and
competition.” However, to think it is
just a recent phenomenon would be incorrect.
Sam Allardyce and Bolton
One often forgotten example is
Sam Allardyce and Bolton Wanderers. Under the often-controversial Englishman,
Bolton reached promotion to the Premier League and eventually UEFA Cup
football. The side played old fashioned football which involved kicking the
ball from one end of the field to the other. A style often frowned upon due to
its simplistic nature and lack of skill. However, for Bolton, their style was
based on detailed statistics, especially for the time. Allardyce, also known as
“Big Sam” was at the club from 1999 to 2007.
Back then Information Systems
were not what they were today but despite this Allardyce used statistics to
improve Bolton’s chances in the Premier League. (Newmann 2015) and writer
Michael Cox in his book “The Mixer” talk about how Sam’s time in the USA with
the Tampa Bay Rowdies changed his perspective on sport and the role data could
play. (Newmann 2015) By working with data collection company Prozone, Bolton
realised that if they “had to stop the opposition from scoring in at least 16
of their 38 league games to avoid relegation; if Bolton scored first they had a
70% chance of winning; set-pieces accounted for almost 33% of all goals scored;
in-swinging crosses were more effective than out-swingers; and they had an 80%
chance of avoiding defeat if they outran their opposition at speeds above 5.5m
per second.” These statistics and more were used to dictate how Bolton played.
It helped the decision makers maximise the resources they had. But marrying
their inputs such as personnel of players and coaching staff with data, the
team produced a surprisingly high level of output.
How Data Almost Made Chelsea
European Champions
(Dario 2002) Claimed that “video
technology has significantly influenced training methods”. A famous example of
this came in the 2008 Champions League Final penalty shootout between
Manchester United and Chelsea. In 2003 Basque economists Ignacio
Palacious-Huerta published his paper “Professional play Minimax” where he
tracked statistical patterns in penalty taking. Ignacio had followed the
pattern of Manchester United and passed his findings onto Chelsea. Findings
that, if not for a slip on a rainy night in Moscow, would have many Chelsea
European champions. This conclusion is game theory which “is the process of
modeling the strategic interaction between two or more players in a situation
containing set rules and outcomes. (Mcnulty 2019) Huerta’s finding revealed
that Manchester United goalkeeper Edwin Van der Saar assumed those penalty
takers would shoot across their body Meaning a right-footer would to their
right and the goalkeepers left.
Therefore, the Chelsea players should shoot to their “unnatural side” He
also learned that “Ronaldo often stops in the run-up to the ball. If he stops,
he is likely (85%) to kick to the right-hand side of the goalkeeper.”
(Kuper/Szymanski 2014). Ronaldo did stop, and as predicted went to his left,
and the goalkeeper saved it. The ability to analyse data due to the use of
Information systems and the oppurtunity to study shootouts, economist Ignacio
Palacious-Huerta almost made Chelsea European champions.
Lastly, there is the
surprising data that one of the world’s best players Lionel Messi creates more
space if he stands or jobs than if he spirts. With this knowledge, the
Argentine can conserve his energy, not be so tired in front of goal, which we
can assume increased his scoring rate. There is an argument to say that if
Lionel Messi ran more, he would be less effective at completing his main task
of scoring goals.
Football Scouting
As already mentioned,
Information Systems are “an integrated set of components for collecting,
storing, and processing data and for providing information, knowledge, and
digital products,” (Encyclopædia Britannica 2017). In 2019 with the help of
Information systems, AI, and machine learning football clubs are scouting players
from a more analytical perspective. Clubs can use this information to scout
more efficiently with the with use of easy to understand information systems
such as dashboards.
In an interview with the
Financial Times (FT), Ted Knutson, co-founder and chief executive of StatsBomb
said; “Manchester City just don’t sign bad attackers any more either; they
signed De Bruyne, Sterling, and Sané back-to-back-to-back, who were among the
very best choices [according to the data] each time.” (Burn-Murdoch 2018). Scouting
can help clubs identify players who are undervalued often due to or a lack of physical
attributes with the use of statistics.
According to the (Independent
2016), Leicester City Football Club asked their “analytics team to look for
metrics such as most interceptions, tackles and forward passes per 90 minutes
across Europe’s top leagues.” They quickly discover little known 5ft 6ins
N’Gole Kanté. Leicester found a player that would not just perform well in a
league winning side, but also make them a profit. Leicester sold the player one
year later for £32 million, making a £26.4 million profit. He has since gone on
to win the PFA Premier League player of the year. (BBC 2017) He (Kanté) was
discovered due to scouts looking at the statistics and not the appearance of
the diminutive Frenchman. At 5ft 6ins, his type of build was often overlooked
in the past. Raw statistics is only numbers on a screen, but this, coupled with
information systems and IT, these statistics such as video, can be turned into
valuable information. The processing and storing capabilities of the software
behind companies such as wyscout has changed football scouting forever. Perhaps
other industries and not just other sports can use similar methods to improve their
HR and recruitment departments. This hope may be challenging to do with GDPR
within the European Union, but football has proven that the technology is
there.
VAR & Goal Line Technology
Goal-line technology (GLT) has
been an instant hit in football. A technology similar to that in tennis and
cricket is an excellent example of information systems processing data. The
results of GLT need to be extremely quick and accurate. According to (FIFA
2018), the “technology adopts seven high-speed cameras per goal and “the images
are sent to a computer and analysed in real-time.” As soon as the ball crosses
the line, a signal will be sent to the referee’s watch, letting them know it is
a goal. This fact is an example of information systems providing real-time
information that is instantly solving a problem.
Video Assistant Referee (VAR)
has been less successful. However, is
none the less a form of data collection and information systems. If a referee
is unsure about a critical decision in a game, he can ask or be advised to use
VAR. Many fans have complained that the system is not quick enough. This piece
of information is perhaps an example of where information systems need to be
improved to collect and provide data quicker for customers. According to
Premier League referee VAR “has made four mistakes so far during the Premier
League season. (Sky Sports 2019)
Impact on Betting:
There seems to be a lack of
research into this topic. But there is no doubt that football fans nowadays are
a lot more educated about the sport than they were in the past. This is
somewhat thanks to TV punditry and the rise of subscription television, but it
is mainly down to the football data analysis that has grown from the small
group of football statistic blogs. and betting
companies have long had the advantage of asymmetry information. The (American
Economic Review 2003) suggest this is when “buyers and sellers commonly process
difficult, and not identical information.” This means that a seller of a
service may have a much better understanding of a product than a buyer. With
the increase of data, this gap has decreased. Betting companies benefit from
having more knowledge. They will have to find new ways to stay ahead. Which
will likely lead to an even greater need for information and increased
sophistication of information systems and data analytics. 2015 saw the
introduction of UK betting company where users can buy stocks called “features”
in football players. On the platform, users are essentially betting on the
future performance of a player rather than betting on individual results. If
the Index is to go mainstream, it will further complicate sports betting and
the world of football as a whole. (Football Index 2019) The index uses
information systems and cloud computing to gather information in real time.
This information includes headlines from UK newspapers to calculate media
dividends for customers. Match day information to inform match day dividends
with their live ranking system. See
graph 8 and 9 below.
Graph 8: Source Football
Index. Accessed on October 11th at 11.22 am
Graph 9: Source Football Index. Accessed on October 12th
at 2.07 pm
Conclusions:
The world is seeing rapid
growth in date and the football industry is no different. To be successful in
the future football clubs like any other business will be rewarded for taking
this data and turning it into useful information. The role of Information
systems will be likely to continue to grow. Information System operators will
need to continue to improve their system’s ability to collect, store and
process data. These systems will continue to create information, knowledge and
wisdom from these data inputs. IS will likely integrate itself further into
football scouting, the transfer market, football tactics and the betting
industry.
Reference List:
Academic Articles:
The American Economic Review
(2003) Behavioural
Macroeconomics and Macroeconomic Behaviour https://www-jstor-org.ucc.idm.oclc.org/stable/3083349?pq-origsite=summon&seq=1#metadata_info_tab_contents
(Ignacio Palacious-Huerta
2003) “Professional play Minimax”
Dario, L., 2002. Advances in
the application of information technology to sport performance.
Green, R. (1999),
"Football information services: fanzines, “Match of the Day” and the
modem", Aslib Proceedings, Vol. 51 No. 1, pp. 20-29.
(Kishore, Zang, Ramesh 2004)
Enterprise integration using the agent paradigm: foundations of
multi-agent-based integrative business information systems Journal of Sports
Sciences Accessed Sep 18th 2019
Books:
Christoph Biermann (2019) The
Science and Art of a Data Revolution (English Version)
Kuper/Szymanski (2014 Edition)
Soccernomics, pg 158-159.
(O Brien & Marakas (2010) Management
Information Systems https://www.dias.ac.in/download/2015/dtr8/102-112%20Pages%20of%20DTR%208th%20issue.pdf
Michael Cox (2017) The Mixer
Journals:
Sage: Jamie Cleland (2011) The
Media And Football Supporters: A Changing Relationship.
Websites:
BBC (2017) PFA Player of the Year
Accessed Sep 21st 2019 https://www.bbc.com/sport/football/39686272
Coles (2013) Rise
of Data Analysis in Football Accessed Sep 21st
2019 http://outsideoftheboot.com/2013/06/26/rise-of-data-analysis-in-football/
Deloitte (2019) Bullseye
Football Money League Accessed
16/Sep/2019 https://www2.deloitte.com/uk/en/pages/sports-business-group/articles/deloitte-football-money-league.html
Financial Times (2018) How
Data Analysis Helps Football Clubs make better decisions.
Accessed 16/Sep/2019 https://www.ft.com/content/84aa8b5e-c1a9-11e8-84cd-9e601db069b8
FIFA 2018: About
Goal-Line Technology Sep 19th
2019 https://football-technology.fifa.com/en/media-tiles/about-goal-line-technology/
FIFA 2018 Video
Assistant Referees Sep 19th
2019 https://football-technology.fifa.com/en/media-tiles/video-assistant-referee-var/
Football Index (2019) About
Page Sep 19th
2019 https://www.footballindex.co.uk/stockmarket/policies/About_Us
John Burn-Murdoch (2018) How
data analysis helps football clubs make better signings https://www.ft.com/content/84aa8b5e-c1a9-11e8-84cd-9e601db069b8
(McNulty 2019) The
Basics Of Game Theory https://www.investopedia.com/articles/financial-theory/08/game-theory-basics.asp
Medium (2019) GPS
Tracking in Football Accessed
Sep 20th 2019 https://medium.com/@kitradar/gps-tracking-in-football-with-stephane-smith-of-titan-sensor-275e65d946a0
Newman 2015: In
praise of Sam Allardyce Accessed
Sep 19th 2019 https://www.theguardian.com/football/these-football-times/2015/mar/04/praise-sam-allardyce-manager-bolton-wanderers-premier-league
Opta:
https://www.optasports.com/about/the-opta-difference/ Accessed 16/Sep/2019
(Sandle 2018) Knowledge
Doubles Almost Every Day Sep 16th
2019 http://www.digitaljournal.com/tech-and-science/science/op-ed-knowledge-doubles-almost-every-day-and-it-s-set-to-increase/article/537543
Sky Sports (2019) Premier
League referee chief Mike Riley admits four mistakes this season Sep 19th 2019 https://www.skysports.com/football/news/11095/11807734/var-premier-league-referee-chief-mike-riley-admits-four-mistakes-this-season
http://statszone.tiki-taka.co
Wright (2016) STATSports: The
training technology used by Arsenal, Man City, Barcelona and more Sep 17th 2019 https://www.skysports.com/football/news/11095/10502787/statsports-the-training-technology-used-by-arsenal-man-city-barcelona-and-more
Bibliography:
Anderson: How a
World Cup Star Was Discovered Using Data—and What It Means for Recruiters Date
Accessed Sep 21st 2019
BBC (2019) Manchester City and tactical
fouls - what do the stats say? Date
Accessed September 16th 2019
Darlington FC (2019) Quakers
Using GPS To Assess Players' Fitness. Date Accessed September 18th
2019
Michael Lewis (2003) The Art
of Winning an Unfair Game. Date Accessed September 18th 2019
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