An overview of the Sports Analytics Innovation Summit held in Boston, September 2013

1. Sports Analytics
Innovation Summit
Winning in Sports Through Performance
Analysis & Data Analytics
September 12 & 13, Boston 2013

2. Who went?
Coaches, General Managers, Sports Analysts, Technologists

3. Key questions
How do you engage Coaches?
How do you create value based on the Data?

4. Two tracks
On Field Analytics
Off Field Analytics

6. The pursuit of
innovation in the English
Premier League
Tony Strudwick
Head of Sports Science at Manchester United

7. The pursuit of
innovation in the English
Premier League
Tony Strudwick
Head of Sports Science at Manchester United

8. Psychology of Sport

9. Analytics may not capture a
player's main strengths or
weaknesses

10. For example ...
One players greatest skill may be
to motivate other players.
If players are not physically or
mentally ready to perform then
data is a waste of time.

11. Other Problems ...

12. In the last 20 years, sport science
has been oversubscribed yet has
underdelivered.

13. Most coaches feel sport science
brings no value to their team.
The problem is perceived as the inability of
data practitioners to communicate
actionable metrics.

14. Analytics do not always explain human
psychological principles because ...
Humans are not rational
Humans are risk adverse
Under pressure humans will fail

15. Analytics must drive decisions
and actions or else they're
worthless.
Need more graphical representations, not
excel spreadsheets
Emphasis on real time apps, real time data
& analysis, real time decisions
Catapult Team Tracking System

17. Decisions that are now well
supported by analytics ...
Managing training of new players
Analytics & reports for chief execs

18. Display relevant relationships
between these variables:
Age Group
Position
Ave body Mass
Cumulative minutes trained

19. Example
49% of squad is 29+ years old
Higher number of injuries coming from
this group
During November, December, January
intensity training goes down, injury
goes up

20. Goals of social media to
analysis
Using
search for the next
Olympic team
Remain injury free
Increase player availability and individual
performance
Troy Flanagan
Maintain high performance over 45 games
Performance Director, US Ski & Snowbaord Assn.
per season, 4 games per week

21. Using social media to
search for the next
Questions?
Olympic team
Troy Flanagan
Performance Director, US Ski & Snowbaord Assn.

22. Using social media to
search for the next
Olympic team
Troy Flanagan
Performance Director, US Ski & Snowbaord Assn.

26. Goal of program is to transfer ex-gymnasts
into aerial skiing for the 2018 Olympics
3 years to reach the podium ...

27. The US Ski Team created a Facebook app
through create.it for finding talent

28. Kids submit their best tricks to win an
invitation to tryout camp
If theres not a tangible reward people
won't participate

30. Using Visual Analytics in
Performance Analysis
Questions?
Kirk Goldsbery
Visiting scholar at Harvard, now at ESPN

31. Using Visual Analytics in
Performance Analysis
Kirk Goldsbery
Visiting scholar at Harvard, now at ESPN

32. What are Analytics?

33. Analytics are Reasoning Artifacts …
things we use to make decisions.
New Data, New Analytics, Same reasoning

34. Maps
Maps show spatial structure and patterns
Maps provoke spatial reasoning
Maps work for all sports

38. We’re visual creatures
and when we see something attractive we want to
consume it
It takes time
to make something that people want to consume.
If you were to ask Faulkner how he writes …
he doesn't just write, he considers how to frame the
story first

39. How do you harness spatial science?
Sports are spatial
Sports are visual
Analytics are not spatial or visual

40. Spatial Analysis
Visualize patterns and quantify information
Visual Analytics
Translate raw game data into useful information

44. Example
All LeBron James shots for the last 5 seasons
Spatial map of shooting patterns
Good for engaging the athlete
Good for finding players that are similar or different

47. Visualizations can handle big data
As strategic devices
As communicative devices

48. Two different approaches to visualizations
Exploratory
Confirmatory
Depends on audience

49. Sensors
lead to quantitative spatial research questions
However, provoking spatial reasoning may lead to
more questions than it answers
Find a question to try to answer and attack it

50. Staying Connected:
The Rise in Fitness Data
Questions?
Chris Glode
GM, MapMyFitness

51. Staying Connected:
The Rise in Fitness Data
Chris Glode
GM, MapMyFitness

52. MapMyRun
Team of 100 split between Austin & Denver
Connected Fitness - social, fun, simple, effective,
and rewarding

53. Users
40% Aspirational
45% Recreational
15% Fanatical

54. 160 million workouts logged in 2013
Team working toward less friction in the
app experience

55. Growth driven by
Smart phones
Wireless technology & reduced friction seamless data download
Cloud computing
Wearables… reduction in hardware costs
Obesity epidemic in US

56. People use MapMyRun to “outsource
their willpower”
Friends in the system keep other users
more active via notifications

57. Techniques for engagement:
Games: people keep coming back for competition
Games are considered a “jedi mind trick” by
MapMyRun, effectively manipulating users to return
Route art: motivated users who were otherwise
uninterested in social

59. Practical applications of fitness data
Corporate wellness
Trainer driven programming, tailored to the individual
based on real, recent and new fitness data. Total
accountability

60. Opportunity via tons of information mined
on the geospatial front
Example: advertising to women along
certain routes, etc.

61. Future
Woven wearables
Advanced activity detection
Ubiquity of incentives to track fitness
iOS7 - Support for passive all day activity tracking in
background when app is inactive

62. Using GIS to study
Spatio-Temporal
Questions?
Patterns in Sport
Damien Demaj
Geospatial Product Engineer at Esri

63. Using GIS to study
Spatio-Temporal
Patterns in Sport
Damien Demaj
Geospatial Product Engineer at Esri

64. Space and time go hand in hand in sport

65. Mapping a tennis match

66. Example
Who: Federer v Murray
Data: 1706 spatial points
3D GIS & streaming video

71. The serve: the most important shot
Speed & spin: the most important metrics
Variation is key: mapping unpredictability is
important

72. Approach
1. K Means algorithm - looks for natural clusters in the
data, balls that are close in space but also have a
similar attribute
2. Create euclidean lines & calculate large mean distance
3. Tag the most important points in the match
4. Add a feature overlay – Pseudo Realism – putting
players back in their environment

75. Smart Soccer
Qaisar Hassonjee
Questions?
VP Innovation, adidas
Nelson Rodriquez
MLS EVP Competition & Game Operations

76. Smart Soccer
Qaisar Hassonjee
VP Innovation, adidas
Nelson Rodriquez
MLS EVP Competition & Game Operations

77. How is technology enabling
sports analytics?

78. Wearables
Multifunctions, always connected, smart/
aware devices that measure me
Enabled by advances in sensor
technology, algorithms, data science
Everyone from startups to established
brands are developing tools
What are you looking for? What kind of
sensors to develop, ease of use

79. Lots of fear in the industry... but lots of
copycats once something works

80. The adidas Team System
Open platform… more sensors over time can be
added to the platform
Measures Heart rate, Speed, Distance, Location,
Acceleration
100 shirts
30 pods
4 ipads

81. 19 MLS clubs are now using the
system - bell curve of adoption

86. iPad App
Most people don’t look at all 20-30 parameters,
just the top 2-3
How is the information actionable?
How is pre-season trianing improving the fitness of
my athletes?

87. Results
Athletes appreciate and want to use the technology
Tool can extend careers and improve performance
Injuries are down 2% this year

88. Future
Drop the tech into the academy programs & build a
national data set of kids & analytics using the system
Commercial opportunities, super fan stuff, fantasy
teams, etc.

89. USA Volleyball
Questions?
Anton Willert
Technical Coordinator/Tem Manager
US Men’s National Team

90. Thanks for visualizing