Digital transformation, the use of Data, and AI have been transforming businesses in every industry. Sports are no exception. Football has been implementing new technology in order to guarantee succes and better engage with fans.

1. “
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C O O N E C T E D E C O N O M YR E I M A G I N I N G I N C U M B E N T S

2. D I G I T A L T R A N S F O R M A T I O N
Transforming Incumbents
Case: Sports
Moneyball: The Art of Winning an
Unfair Game (2003)
Baseball has figured out how to integrate "soft" data
with "hard“
Baseball has always been blessed with lots of hard,
statistical performance data.
Leading organizations are doing now is incorporating
the soft metrics—metrics like resilience, perseverance,
heart and chemistry

3. 3,2B Worldwide audience of the 2014 World Cup
1B Fans watched the 2014 final
98087h Total Broadcast footage of the tournament
280M World Cup fans watched online or on mobile
D I G I T A L T R A N S F O R M A T I O N
2014 FIFA World Cup in Data
2018 World Cup: “the largest production in our 24-year history” David Neal - Fox Sports VP

4. D I G I T A L T R A N S F O R M A T I O N
Brazil v. Germany Semi-Final
Twitter’s most-engaged single athletic competition ever.

5. D I G I T A L T R A N S F O R M A T I O N
German Engineering
Football reimagined. The Deutscher Fußball-Bund and SAP
H T T P S : / / W W W . S A P . C O M / P O R T U G A L / P R O D U C T S / S P O R T S - O N E . H T M L # V I D E O = E 0 7 E 4 A A 5 - C A 7 C - 0 0 1 0 - 8 2 C 7 - E D A 7 1 A F 5 1 1 F A
SAP Match Insights
The system is based around a series of key performance indicators
(KPIs): how to make the German game faster and get in front of the
goal more quickly.
Average ball possession became a critical factor with the need to
look at receiving the ball, control, passing and pass completion.
“Every training session was around that KPI - to make the game
faster,” Jungkind said.
3,4s
Average ball possession of
DE team World Cup 2010
1,1s
Average ball possession of DE vs
BZ in 2014 (7-1 Victory!)
4goals Goals suffered by DE team
18goals Goals scored by DE team

6. D I G I T A L T R A N S F O R M A T I O N
German Engineering
Visual recognition, Video and Data Points
SAP Match Insights
The system was fed by a system of eight high-definition video cameras giving a
panoramic view of the pitch and using data capture and analysis software fromAmisco.
Visual recognition algorithms were needed to identify players as FIFAforbids use of
physical tags that might otherwise be used to capture and transmit data.
Looks like an Xbox or PlayStation game and lets coaches draw lines on screen between
players to see the distance between defenders and draw concentric circles around
players to see in actual quantifiable units the space between players
5000 Data points per second

7. D I G I T A L T R A N S F O R M A T I O N
Sports Data
Case: Sports
Opta
The data company that has been
analysing football matches since
2001, recording all the
information that for years has
appeared in the small statistical
summaries that round up each
match on TV and in the papers.
H T T P S : / / V I M E O . C O M / 2 2 8 9 7 3 7 8 4

8. D I G I T A L T R A N S F O R M A T I O N
Expected Goals
Expected Goals: xG
H T T P S : / / C A R T I L A G E F R E E C A P T A I N . S B N A T I O N . C O M / 2 0 1 7 / 8 / 1 7 / 1 6 1 6 4 0 6 8 / E X P L A I N I N G - E X P E C T E D - G O A L S - S O C C E R S - N E W E S T - S T A R
x2
Lowers xG
Raises xG
C R O S S E S
T H R O U G H B A L L S
S Q U A R E B A L L S
I N S I D E 1 8 - Y A R D B O X
C O M P L E T E D D R I B B L E S
C O U N T E R A T T A C K S
C O R N E R K I C K S
B I G C H A N C E S *
*Big chances= Player should reasonably be expected to score usually in a one-on-one scenario or from very close range Opta)
3%
≥30%

9. D I G I T A L T R A N S F O R M A T I O N
Predictive statistics: Gets better with more data
Expected Goals: xG
S o u r c e : S c i s p o r t s

10. D I G I T A L T R A N S F O R M A T I O N
Predictive statistics: Gets better with more data
Expected Goals: xG
S o u r c e : S c i s p o r t s

11. D I G I T A L T R A N S F O R M A T I O N
Predictive statistics: Gets better with more data
Expected Goals: xG
PORTUGAL WINNING THE EUROPEAN CHAMPIONSHIP:
WON ONLY 1 OUT OF 7 MATCHES WITHIN 90 MINUTES
THEIR DEFENDING WAS VERY STRUCTURED AND
SOLID
PORTUGAL WERE THE ONLY TEAM CONCEDING LESS
THAN 1 XG PER MATCH (EVEN AGAINST HUNGARY)
AND AVERAGED A MEAN XG AGAINST OF ONLY 0.56
PER MATCH.
COMBINING THIS WITH A LETHAL COUNTER ATTACK
RESULTED IN PORTUGAL WINNING THE EURO2016!
S o u r c e : S c i s p o r t s

12. D I G I T A L T R A N S F O R M A T I O N
“From watching a football match to seeing a football match” – 11Tegen11
Expected Goals: xG
S o u r c e : 1 1 T e g e n 1 1
H T T P S : / / T W I T T E R . C O M / I / S T A T U S / 1 0 1 1 3 4 9 0 9 0 7 3 3 5 6 8 0 0 2
C OMPOSITE IMAGES TH AT SH OW XG FOR BOTH SID ES IN AN Y GIVEN GAME, EAC H
EFFOR T ON GOAL MAPPED ON TO TH E PITC H ( TH E B IGGER TH E B LOB , TH E
B ETTER TH E C H A N C E )
EQU ALLY FASC IN ATIN G PA SS MA PS TH AT MAP AGGR EGATE POSITION S OF
PLAYER S ON TH E PITC H AN D TH E PASSIN G LIN KS W ITH TH EIR TEAM - MATES

13. D I G I T A L T R A N S F O R M A T I O N
Nerd Fans
Case: Sports
We will start watching (or seeing) games differently, partly as a result
of a changing audience.
Posting xG on Match of the Day will be a talking point, it will give them
something to argue about and get a rise out of fans.
The data will show you what happens over the course of a million shots
and experts can tell you why.
It will also bring a new kind of fan to the game, absolutely. This kind of
data overlaps with people who play Football Manager or fantasy
league. It’s exactly the same thing, you take information about players
and you evaluate them. If you want to be better in fantasy league then
you need data.

14. D I G I T A L T R A N S F O R M A T I O N
Field of Dreams: Data, Apps, AR
Case: Sports
SAP SPORTS ONE
THE PLATFORM IS THE EVOLUTION OF SAP MATCH INSIGHT,
USED BY THE GERMAN NATIONAL SOCCER TEAM DURING
BRAZIL 2014.
MAIN FEATURES :
TRAINING PLANNING
FITNESS
PERFORMANCE CONTROL
SCOUTING PROCESS OPTIMIZATION

15. D I G I T A L T R A N S F O R M A T I O N
Sensors for real-time data gathering
Case: Sports
This system allows users to gather players’ data
(like accelerations and ground covered), but also to
calculate correlations between other values like
team performances, average distance between
players, and movement directions.
HTTPS://WWW.YOUTUBE.COM/WATCH?TIME_CONTINUE=27&V=YSBIKA1USWK
WHEARE IS AN ITALIAN REAL-TIME ANALYSIS PLATFORM, DEVELOPED BY SPACEEXE.
The data is gathered by a GPS antenna, an accelerometer and a GNSS receiver placed in the shin guard, then sent over to a
pc or tablet for a real-time preview, and to a remote server for a more in-depth subsequent analysis.

16. D I G I T A L T R A N S F O R M A T I O N
Drones to check the grass
Case: Sports
WESII: DRONES FOR PITCH ANALYSIS
WESII’S IDEA WAS TO ANALYSE THE
SOCCER PITCH FROM A DRONE VIA MULTI-
SPECTRUM SENSORS, PROVIDING
INFORMATION ABOUT THE PITCH CONDITIONS
NOT VISIBLE TO THE NAKED EYE, LIKE
SLIPPERINESS. IT IS A KIND OF ANALYSIS
ALREADY ADOPTED IN OTHER FIELDS, LIKE
PRECISION AGRICULTURE, BUT STILL A
NOVELTY FOR SPORT.

17. D I G I T A L T R A N S F O R M A T I O N
AI for Video Analysis
Case: Sports
STATSEDGE PRO:
ARTIFICIAL INTELLIGENCE FOR VIDEO ANALYSIS
STATSEDGE IS AN INNOVATIVE PRODUCT IN
THIS FIELD: IT ALLOWS IN-DEPTH VIEWS OF
MATCHES (LIKE EXPECTED GOALS, SHOTS,
ACTION AREAS, FOULS), AND ANALYSIS OF THE
OPPONENT’S WEAKNESSES AND STRENGTHS,
PERFORMING ACCURATE TRANSITION
ANALYSIS.

18. D I G I T A L T R A N S F O R M A T I O N
Search for Similarity in Plays
Case: Sports
STATSEDGE
HOWEVER, THE TRULY INNOVATIVE FEATURE OF THIS PRODUCT IS THE POSSIBILIT Y TO SEARCH CLIPS FOR
SIMILARITY USING TRACKING DATA, THANKS TO SOPHISTICATED AI ALGOR ITHMS.
H T T P S : / / W W W . S T A T S . C O M / E D G E /

19. D I G I T A L T R A N S F O R M A T I O N
Nodes and Lines: Graphic representation of a match
Soccer is a flow sport
SOCCER IS A FLOW SPORT
PRODUCES A NETWORK VISUAL FOR EACH TEAM, COMPRISED
OF NODES — ONE CIRCLE FOR EACH PLAYER — AND LINES
CONNECTING THOSE PLAYERS. THE NODES AND LINES VARY IN
SIZE — LARGER CIRCLES INDICATE MORE INFLUENTIAL
PLAYERS, AND WIDER LINES REFLECT STRONGER CONNECTIONS
BETWEEN PLAYERS.
FLOW SPORTS, ARE MORE COMPLEX.
THINGS ARE ALWAYS IN MOTION. PLAYERS MOVE ALL OVER.
THERE ARE NO BREAKS IN PLAY WHEN THE CLOCK IS
RUNNING

20. D I G I T A L T R A N S F O R M A T I O N
Comment on CR7: “Possibly not a human” – Paddy Cosgrave
Average Footballer Rating (AFR)
“AVERAGE FOOTBALLER RATING” (AFR) FOR EACH PLAYER,
BASED ON HOW INFLUENTIAL THEY ARE IN SOCCER MATCHES .
THE AFR VALUES OF ALL PLAYERS ON A GIVEN TEAM INDICATE
THAT TEAM’S STRENGTH — ITS SUCCESS AT MAKING PASSES
THAT RESULT IN GOALS
A PLAYER WITH AN AFR GREATER THAN 70 IS PRETTY MUCH
SUPERHUMAN,” AMARAL SAYS. “AND AN AFR ABOVE 70 OVER
MANY SEASONS IS GOD-LIKE.”
LUÍS A. NUNES AMARAL
C o - D i r e c t o r , N o r t h we s t e r n I n s t i t u t e o n
C o m p l e x S y s t e m s
P r o f e s s o r o f C h e m i c a l & B i o l o g i c a l
E n g i n e e r i n g
P r o f e s s o r o f P h y s i c s & A s t r o n o m y
P r o f e s s o r o f M e d i c i n e

21. D I G I T A L T R A N S F O R M A T I O N
Amaral Lab World Cup 2018
Average Footballer Rating (AFR)
“WHEN YOU ARE ESTIMATING THE WINNER OF A WORLD CUP,
LUCK AND CHANCE PLAY A HUGE ROLE,” MUCH MORE THAN IN
THE LARGER SAMPLE SIZE OF A LONG SEASON.
WHAT AMARAL’S SYSTEM CAN DO IS DETERMINE
PROBABILITIES.
“OUR ALGORITHM TELLS US WHAT THE LIKELIHOOD OF
OUTCOMES ARE,” AMARAL SAYS. “IT’S THE DIFFERENCE, FOR
INSTANCE, BETWEEN ASKING WHAT’S THE LIKELIHOOD THAT
CERTAIN TEAMS ARE GOING TO MAKE THE PLAYOFFS, VERSUS
WINNING THE SUPER BOWL.”
THE BEST PLAYERS IN
THE WORLD AS OF MAY
2018

22. D I G I T A L T R A N S F O R M A T I O N
2018 World Cup Dream Team.
Average Footballer Rating (AFR)
WHO’S YOURS?

23. C O N C L U S I O N S
1. THE WORLD HAS CHANGED AND NEW BUSINESS
MODELS ARE CHALLENGING INCUMBENTS.
2. WE ARE IN THE MIDST OF THE 4TH INDUSTRIAL
REVOLUTION.
3. THE RULES OF ENGAGEMENT HAVE CHANGED.
4. THE POWER OF ONE.
5. THE RISE OF PROSUMERS.
6. THE ECONOMY OF FLOWS
7. THE POTENTIAL TO CREATE VALUE STEMS FROM
CONNECTIONS AND THE POWER OF THE NETWORK.
8. SOCIAL, MOBILE, REAL TIME
9. PLATFORMS ARE THE BASIS OF VALUE
10.EVERYTHING IS DIGITAL! EVEN FOOTBALL!
Conclusions