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Sport Analytics Innovation Summit
The document summarizes discussions from a sports analytics innovation summit that took place in Boston in 2013. It covers topics around how analytics can be used in both on-field and off-field analysis to help coaches, general managers, and teams. Specific discussions included how to engage coaches with data and analytics, challenges around capturing a player's strengths from data, and ensuring analytics drive decisions and actions. Presenters discussed using data and analytics in areas like training management, injury prevention, and social media scouting.
Sport Analytics Innovation Summit
- 1. Sports Analytics Innovation Summit Winningin Sports Through Performance Analysis & Data Analytics September 12 & 13, Boston 2013
- 2. Who went? Coaches, GeneralManagers, Sports Analysts, Technologists
- 3. Key questions How doyou engage Coaches? How do you create value based on the Data?
- 4. Two tracks On FieldAnalytics Off Field Analytics
- 6. The pursuit of innovationin the English Premier League Tony Strudwick Head of Sports Science at Manchester United
- 7. The pursuit of innovationin the English Premier League Tony Strudwick Head of Sports Science at Manchester United
- 8.
- 9. Analytics may notcapture a player's main strengths or weaknesses
- 10. For example ... Oneplayers 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.
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- 12. In the last20 years, sport science has been oversubscribed yet has underdelivered.
- 13. Most coaches feelsport science brings no value to their team. The problem is perceived as the inability of data practitioners to communicate actionable metrics.
- 14. Analytics do notalways explain human psychological principles because ... Humans are not rational Humans are risk adverse Under pressure humans will fail
- 15. Analytics must drivedecisions 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 arenow well supported by analytics ... Managing training of new players Analytics & reports for chief execs
- 18. Display relevant relationships betweenthese variables: Age Group Position Ave body Mass Cumulative minutes trained
- 19. Example 49% of squadis 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 socialmedia 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 mediato search for the next Questions? Olympic team Troy Flanagan Performance Director, US Ski & Snowbaord Assn.
- 22. Using social mediato search for the next Olympic team Troy Flanagan Performance Director, US Ski & Snowbaord Assn.
- 26. Goal of programis to transfer ex-gymnasts into aerial skiing for the 2018 Olympics 3 years to reach the podium ...
- 27. The US SkiTeam created a Facebook app through create.it for finding talent
- 28. Kids submit theirbest tricks to win an invitation to tryout camp If theres not a tangible reward people won't participate
- 30. Using Visual Analyticsin Performance Analysis Questions? Kirk Goldsbery Visiting scholar at Harvard, now at ESPN
- 31. Using Visual Analyticsin Performance Analysis Kirk Goldsbery Visiting scholar at Harvard, now at ESPN
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- 33. Analytics are ReasoningArtifacts … things we use to make decisions. New Data, New Analytics, Same reasoning
- 34. Maps Maps show spatialstructure and patterns Maps provoke spatial reasoning Maps work for all sports
- 38. We’re visual creatures andwhen 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 youharness spatial science? Sports are spatial Sports are visual Analytics are not spatial or visual
- 40. Spatial Analysis Visualize patternsand quantify information Visual Analytics Translate raw game data into useful information
- 44. Example All LeBron Jamesshots 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 handlebig data As strategic devices As communicative devices
- 48. Two different approachesto visualizations Exploratory Confirmatory Depends on audience
- 49. Sensors lead to quantitativespatial 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 Risein Fitness Data Questions? Chris Glode GM, MapMyFitness
- 51. Staying Connected: The Risein Fitness Data Chris Glode GM, MapMyFitness
- 52. MapMyRun Team of 100split between Austin & Denver Connected Fitness - social, fun, simple, effective, and rewarding
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- 54. 160 million workoutslogged in 2013 Team working toward less friction in the app experience
- 55. Growth driven by Smartphones Wireless technology & reduced friction seamless data download Cloud computing Wearables… reduction in hardware costs Obesity epidemic in US
- 56. People use MapMyRunto “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 offitness data Corporate wellness Trainer driven programming, tailored to the individual based on real, recent and new fitness data. Total accountability
- 60. Opportunity via tonsof information mined on the geospatial front Example: advertising to women along certain routes, etc.
- 61. Future Woven wearables Advanced activitydetection Ubiquity of incentives to track fitness iOS7 - Support for passive all day activity tracking in background when app is inactive
- 62. Using GIS tostudy Spatio-Temporal Questions? Patterns in Sport Damien Demaj Geospatial Product Engineer at Esri
- 63. Using GIS tostudy Spatio-Temporal Patterns in Sport Damien Demaj Geospatial Product Engineer at Esri
- 64. Space and timego hand in hand in sport
- 65. Mapping a tennismatch
- 66. Example Who: Federer vMurray Data: 1706 spatial points 3D GIS & streaming video
- 71. The serve: themost important shot Speed & spin: the most important metrics Variation is key: mapping unpredictability is important
- 72. Approach 1. K Meansalgorithm - 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? VPInnovation, adidas Nelson Rodriquez MLS EVP Competition & Game Operations
- 76. Smart Soccer Qaisar Hassonjee VPInnovation, adidas Nelson Rodriquez MLS EVP Competition & Game Operations
- 77. How is technologyenabling 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 fearin the industry... but lots of copycats once something works
- 80. The adidas TeamSystem 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 clubsare now using the system - bell curve of adoption
- 86. iPad App Most peopledon’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 andwant to use the technology Tool can extend careers and improve performance Injuries are down 2% this year
- 88. Future Drop the techinto 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 TechnicalCoordinator/Tem Manager US Men’s National Team
- 90.