Founded in 2013 as a spinoff from the University of Twente. 48 employees (34 FTE) Offices in the Netherlands, Germany and France

Transcription

1 Passion to Discover

2 Who we are Founded in 2013 as a spinoff from the University of Twente 48 employees (34 FTE) Offices in the Netherlands, Germany and France Collaboration with 31 clubs around the world Selected as one of the next European Unicorns (The European Union) Most Innovative Football Company (The HYPE Foundation) Sprout Challenger Award 2017

3 Track record in the industry Cases and clients

4 Some of our Clients

5 SciSkill The most current and reliable player ranking

6 SciSkill The basis The knowledge and intelligence of SciSports come together in a number: the SciSkill. This number represents the strength and potential of football players. The outcome of the attacking and defensive contribution of a player to the team result forms the basis of this number. The algorithm also takes into account club and competition level. The first and only index which can compare more than 90,000 footballers worldwide.

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8 SciSkill Coverage Fully automated system with a weekly update of the rankings based on played matches: 90,000 active players 244 competitions worldwide 3,698 clubs worldwide 2,000 matches each week SciSkill offers confirmation, gives new insights, provides direction, reduces risks and increases the chances of success.

9 Highest SciSkill

10 Highest Potential U21 years old

11 The online platform to compare more than 90,000 players around the world

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14 But we need more accurate data...

15 But we need more accurate data......which is why we developed BallJames

16 Knowledge to lead the game

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18 The Technology: BallJames Fully autonomous real-time 3D Data Generation System Based on Deep Learning & Computer Vision 14 camera s automatically generate voxel data from video Ultimate scalable platform Customized advanced stats for every coach This is the future FC Barcelona Exactly what we need Arsenal FC Totally Astonishing! UEFA

19 Why BallJames? Competitive data providers are: Inaccurate (due to occlusions) Slow Subjective (human operators needed) Cost inefficient Unreliable (huge differences between positions)

20 BallJames: Competitor Review

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23 Partnerships Deep Learning Development Partnership Oliver Schabenberger (COO) This is cutting edge stuff Sales partnership Emmanuele Massuocco (Co-Founder) Their sports intelligence fits perfect with our platform BallJames development Partnership Premier League Club (Head of Analytics) This can help us to make the next step

24 Edge Computing (cameras) Large amounts of data Player/Ball Detection Deep Learning Real-time Deep Learning Deployment Direct Insights Copyright SAS Institute Inc. All rights reserved.

25 Edge Analytics By 2019, at least 40% of IoT-created data will be stored, processed, analyzed and acted upon close to, or at the Edge. Source: IDC, Worldwide Internet of Things 2017 Predictions, November 2016

26 SciSports - AI At The Edge

27 Why SAS for SciSports? - Differentiators SAS focus on operationalization of the detection models Governed processes Not limited to the cloud or just one cloud Simplified end-to-end integration Integrated analytical streaming engine Supported globally (tech, language...) Copyright SAS Institute Inc. All rights reserved.

28 Advanced Streaming Analytics Multi-Phase, In-Stream Analytics Live, in-motion event analysis In-Stream Analytics Deploy models trained on historical data at rest Text Analytics Extract entities, tokenize text, classify and identify sentiment Model Supervision Control runtime model deployment Machine Learning In-stream model training and scoring In-Stream Geofencing Real time location analytics In-Stream Time Patterns Time series detection and analysis Event Processing Compute, aggregate, filter, correlate events Data Quality Business rules data quality and policy definitions Open Source Integration Deploy Python and C models Copyright SAS Institute Inc. All rights reserved.

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