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2023 GRAND SLAM

PRESENTATION 

INTRODUCTION

SMT’s 35 years of experience in live sports’ television production, in-venue presentation, fan engagement, promotion, digital presentation, and league management has led SMT to understand that there is a seemingly universal question that constantly faces all sports federations:

 

“Are there opportunities to increase our revenue generating potential through the adoption of new  

 technologies that increase the monetization value and market reach of our data and video assets?”

 

SMT has been asked to present our thoughts on how the four Grand Slams might answer this question.

SMT's 5-STEP PREMISE

Grand Slams, singularly and collectively, can increase their revenue generating potential by:

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1. Adopting a Common Data Platform Infrastructure;
2. Maintaining Grand Slam ownership of all data in and out of the infrastructure;
3. Centrally controlling all data distribution and data licensing from the infrastructure;
4. Constantly curating and cultivating the input and output systems of the data platform; and
5. Strategically selecting new technologies for incorporation into the data platform.

SMT's 5-STEP PREMISE

Defines a path, a methodology, and a recipe that Grand Slams can follow: 

1. To monetize existing data, video, and assets more effectively;

i.e., Make the Existing Revenue Pie Bigger and Tastier

2. To create new data, new video, and new assets and thus new opportunities for monetization.

i.e., Make New Revenue Pies

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STEP 1: Select A Common Data Platform Infrastructure 

Three Functionally Independent Layers: well-defined interfaces, modular, and future proof

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Level 2 = All Systems that present, consume, deliver, or use Grand Slam Data, e.g.

  • In-Venue Displays: Ribbon Boards, ​Kiosks

  • Broadcast Platforms: 2-D & 3-D Graphics, Virtual Ads

  • Analytics Platforms: Coaching, Training, Medical Player Apps, Officiating

  • Digital Platforms: Mobile & Web Apps, Digital Twin, Officiating - TLC

  • Virtual Insertions: Ads, Erase & Replace, Geography & Demographic Targets

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Level 1 = Central System to Ingest, Store, Time-synchronize, and Collate all Grand Slam Data

  • Creates A/I Secondary Data and Analytics

  • Event Marker Creation and Insertion into Timelines

  • Point by Point Predictive Outcome Probabilities

  • Outputs and Supports Multiple use-case APIs (live real-time, smoothed, etc.)

 

Level 0 = All Systems that Create Primary Data or Video

  • Scoring and Statistical Systems

  • Ball Bounce Location (TLC) & Ball Speed Tracking

  • Broadcast Camera Video, Multiple Camera POV’s

  • Environmental Tracking (weather, temperature, wind, etc.)

  • Clock and Time Tracking    

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STEP 2: Each Grand Slam Owns all Data Generated at its Event

Regardless of vendor patents, etc. each Grand Slam maintains sole ownership of their event’s data.

STEP 3: Each Grand Slam Administrates Who Gets API Distribution

Each Grand Slam controls their own Data Licensing and Data Delivery:​

a. To Third Party Grand Slam Partners but with new Reporting of User Registration Obligations ​​

​(Traditionally these are Fixed Fee Licenses with Guaranteed Revenue)

​b. Direct to Consumers with Consumer Behavioral Feedback and Modeling 

​(Opportunity for Grand Slam to Monetize with Targeted Ads & Custom Content)

STEP 4: Constantly Curate and Cultivate the Input and Output Systems

Scoring and Stats; Tracking (Ball, Player, Racket); Camera (Video & Data); Tracking, Clock and Time Tracking, Multiple Camera POV’s Odds Maker Data Feed Ingest

 

 Broadcast Platforms, Analytics Platforms, Digital Platforms, In-Venue Platforms,     Officiating Assistance Systems (TLC, Let Calling, VAR), OTT Platforms, Betting   Platforms, Predictive Analytics Platforms, Odds Maker Data Feeds

Input Systems: 

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Output Systems: 

STEP 5: Strategically Select New Technologies for Adoption

New Meta Data Technology Systems for Consideration

a. Ball Attribute Systems (spin, contact compression, 3-D trajectory)

b. Player & Racket Tracking (Skeletal, Limb, Joint & Racket Tracking, Biometrics)

c. Lidar 3-D Court and Facility Modeling

d. A/I Foreground Background Separators for all Camera POV’s

e. A/I Analytics Systems – Empirical and Predictive

f. A/I Autocreation of Highlights and Clips for Social Media Distribution

g. Direct to Consumer Systems - Consumer Behavior and Attributes Targeting Systems

EXAMPLES: MAKING THE REVENUE PIE BIGGER

  • Auto Instant Replay of A/I Fonted Video Highlight Clips for Distribution

  • Online Second Screens, Viewer POV Choice, Subscription Data Analytics, Hyperlinks

  • Increase Eyes on Screens – Increase Engagement – Increase Documentable Fan Interactivity

  • Creation of New Ad Inventory Opportunities - Live, Replay, Post, and Social Media

EXAMPLES: MAKING NEW REVENUE PIES

  • Creation of the Digital Twin of Every Match, (Multiple Uses & Puts Grand Slams in the Meta Verse)

  • Creation of Coaches Analytics and Replay Access Technology and Player Performance Portal

  • Creation of Erase and Replace Ad Inventory for Broadcast and Direct to Consumer Content

  • Geo-Targeted and Demographic-Targeted Virtual Ads & Activations

  • Fan Engagement: Custom Content, In-App Purchases, Targeted Ads, Attributes, Preferences, Grand Slam Fantasy Games and Leagues

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