As the football league with the highest stadium attendance globally, and broadcast in more than 200 countries, Germany’s Bundesliga is among the leaders of the world’s most popular sport. To increase fan engagement, Bundesliga is leveraging live data streams and historical data from over 10,000 games to build and train ML models in Amazon SageMaker for real-time predictions and additional insights. These models will be deployed as insights and graphics to show fans when a goal is likely to be scored, identify potential goal-scoring opportunities, and highlight how teams are positioning and controlling the field. The league is also working with AWS to deliver fans customized content and search results based on their location, favorite players, teams, and matches, and using Amazon Rekognition to analyze the largest digital football media archive in the world with more than 150,000 hours of video to easily search for historical footage.

One of the most-watched live sporting events in the US, the College Football Playoff (CFP) is an annual postseason invitational tournament to determine the NCAA Division 1 Football national champion, the highest level of college football. Using APN Partner technology from Veritone, along with use of Amazon Transcribe, Amazon Rekognition, and Amazon S3, CFP was able to develop a more advanced media archive. By implementing these technologies CFP is streamlining monetization and metadata workflows, reducing production costs, and ultimately providing their media partners with fast, easy, and comprehensive access to high-value content in near real time.

With nine million registered users who participate in daily fantasy sports contests on its innovative sports-tech and media entertainment platform, DraftKings needed to ensure it was always ready for the busiest traffic days, expanding agile adoption across the company and moving to a micro-service oriented architecture. Using New Relic for its front-end customer experience run on AWS, DraftKings quickly deploys new features, products, and engagement techniques for users across mobile and web offerings. And with real-time performance feedback from Amazon EC2 and Amazon RDS, DraftKings delivers continuous value to its users while ensuring reliability, performance, availability, and scalability.

Fanatics offers tens of thousands of authentic, officially licensed professional and college sports merchandise to fans through its online and brick and mortar stores. More than 250 million people visit the company’s 300-plus websites every year, creating a massive number of product searches and transactions that generate enormous amounts of data. Working with AWS to move its analytical data to Amazon S3, Fanatics were able to more quickly store and retrieve any amount of data, ultimately enhancing its business intelligence and analytics capabilities in a more reliable, secure, cost-effective and scalable cloud-storage environment.

With one million active paying users, FanDuel’s fantasy sports platform infrastructure has to be highly elastic to cope with significant daily traffic spikes. A startup based out of the UK, FanDuel has been running its fantasy sports service on AWS since 2012, using services like Amazon S3, Amazon EC2 with Auto Scaling and Elastic Load Balancing to ensure seamless capacity provision. FanDuel is also using Amazon RDS for Aurora due to their failover plans and Amazon DynamoDB to store post-game information such as final scores. Using AWS, FanDuel’s uptime is close to 100 percent, and thanks to Auto Scaling, they can accommodate an influx of game day traffic with ease.

FantasyDraft allows sports fans to draft teams of athletes in major sports online, paying to enter contests in which their athletes score fantasy points according to the site’s scoring rules. With peak traffic days and times focused around key sporting events and contests, website availability is vital creating a great customer experience. Using Amazon EC2 instances and Auto Scaling, FantasyDraft can automatically scale server capacity with fluctuating site traffic. Since moving to AWS, FantasyDraft has reduced operating costs due to low compute costs of EC2, increased website performance 20%, and decreased website downtime, reducing user churn and financial risk for the company.

FORMULA 1 is the highest class of automobile racing sanctioned by the FIA, with the fastest and most advanced cars. During each race, 120 sensors on each car generate 3 GB of data with more than 1,500 data points being created each second. F1 uses Amazon SageMaker to train deep-learning models with 65 years of data to provide fans with statistics, predictions, and insights into the split-second decisions made by teams and drivers streamed real-time through Amazon Kinesis. Additionally, F1 is using Computational Fluid Dynamics (CFD) run on Amazon HPC for rapid prototyping new body designs in a virtual environment for use in the 2021 season.

Golden Boy Promotions, one of boxing's most active and respected promoters, was founded in 2002 by world boxing champion Oscar De La Hoya. The company’s fragmented asset management and distribution system made up of internal hard drives and various FTP accounts couldn’t keep up with the growing volume of content and live studio shows. Working with APN Partner technology from Veritone and using Amazon S3, Rekognition, and Transcribe, Golden Boy can now share material reliably with broadcast partners for re-air and shoulder programming for promotional pieces, with the scale to auto-tag and more easily sort content and change layouts specific to each fight event.

Guinness Six Nations, an annual international six-week rugby tournament, uses AI and Machine Learning technology and predictive analytics to provide fans with new insights into the game. By measuring speed, cleanouts, steals, infringements, and time spent in the ruck Guinness Six Nations will provide a full ruck analysis. And through the analysis of pack weights, player experience, and historical data Guinness Six Nations can predict the success of a scrum—raising the bar for what rugby fans around the world expect from their sports broadcasters.

The NBA’s LA Clippers, through technology built on AWS from their official video tracking provider Second Spectrum, developed a live, augmented fan experience called Clippers CourtVision. Cameras in all 29 NBA arenas collect and store 3D spatial data including ball and player locations and movements, and then use ML and advanced analytics to generate graphic overlays ranging from live layouts of basketball plays to frame-by-frame shot probabilities, giving fans a deeper understanding and appreciation for what happens on the court.

NASCAR, the largest stock car racing organization in the US, migrated its 18-petabyte video archive containing 70 years of historical footage to AWS, and can use Amazon Rekognition to auto-tag video frames with metadata, such as driver, car, race, lap, time, and sponsors, and Amazon Transcribe to caption and time stamp every word within speech. This saves NASCAR thousands of hours of manual tagging and searching their video archives to present fans with the most iconic moments in NASCAR history. NASCAR will then use SageMaker to train deep learning models to enhance metadata and video analytics. 

Through its Next Gen Stats (NGS) program built on AWS using machine learning technology, the NFL offers advanced stats that highlight the scale, speed, and complexity of the game. Ultra-wideband receivers track the players and ball movement down to the inch using RFID tags, capturing and storing over 3TB of data each game leveraging Amazon EC2, S3, and EMR. Real-time data is combined with traditional box score data to calculate hundreds of metrics and output predictions and insights delivered through graphics to fans online, onscreen, in stadium, and in second screen experiences, and as APIs to teams, analytics companies, broadcasters, and commentators. 

Founded in 2006 in the UK as Pro Football Focus and now majority owned by former NFL pro Cris Collinsworth, PFF’s team of over 500 analyzes pro and college football using sophisticated mathematics and analytics models. PFF began implementing machine learning solutions with Amazon S3 and AWS ElastiCache to manage scale, having migrated its entire technology and cloud stack to AWS in July 2019. PFF will use AWS compute, storage, database, serverless, analytics and machine learning services to improve operational efficiency, innovate at a faster pace and drive deeper meaning from game statistical data. AWS will enable PFF to uncover never-before-seen metrics that will change the way that teams, fans, and the media experience football.

Considered one of the most tech progressive and data-driven teams in the NFL, the Seattle Seahawks are moving the vast majority of their infrastructure to AWS, leveraging compute, storage, database, analytics, and ML services to drive deep analysis of their players and competitors’ data, improve operational efficiencies, and speed innovation. A data lake on Amazon S3 will combine the team’s 40-plus years of stats with NFL data, player tracking, GPS movement, player health and wellness data, and scouting information for deeper visibility and greater insights enabling coaches to make better matchups and real-time adjustments that will lead to more successful drives and touchdowns.

University of Illinois, Urbana Champaign (UIUC) collaborated with the Amazon Machine Learning (ML) Solutions Lab to help UIUC football coaches prepare for games more efficiently and improve their odds of winning. The team combined UIUC’s deep expertise in college football and coaching with AWS’s machine learning to create a state-of-the-art ML model that predicts the result of any football play. In addition, UIUC coaches now have auto-generated visual game planning sheets based on key features recommended by the ML model. This saves the coaches’ time when preparing for a game, and gives them more insights on their performance and strategies.

Second Spectrum is the Official Optical Tracking and Analytics Provider of sports leagues such as the National Basketball Association (NBA) and the English Premier League. Second Spectrum uses AWS to help sports leagues and their media partners deliver analytics, visualizations, and easily searchable video clips to enhance the fan experience and provide teams with deeper competitive insights. Second Spectrum uses AWS Elemental to minimize latency in its streaming services while offering fans a high-quality viewing experience, and AWS Elemental MediaStore, a storage service optimized for media, to allow television producers and sports commentators to quickly access key moments from sports events.

Swimming is Australia’s most successful Olympic sport and one of the most popular activities in the country with more than 4.5 million people participating annually. Participation in swimming is a fundamental component of Australia’s iconic culture however it relies on government funding and global competition is fierce. Working with AWS, the team has used machine learning models to optimize relay formations, to give the best chance of winning medals at key competitions. AWS is proud to play a role in engaging, supporting and developing the next generation of recreational and elite Australian swimmers. Through this partnership, AWS hopes to support Swimming Australia to increase the sport’s profile and level of media coverage, grow national participation rates and contribute to improved performance outcomes of the Australian national swim team.

For Sportradar, the global provider of sports and intelligence for the betting and media industries providing data coverage from more than 200,000 events annually, advances in computer vision are an opportunity to expand the depth of sports data offered to customers and reduce the costs of data collection through automation. Sportradar is investing in computer vision research both through internal development and external partnerships to build computer vision data collection capabilities with an initial focus on tennis, soccer and snooker. Working with the Amazon ML Solutions Lab, Sportradar is exploring the application of state-of-the-art deep learning models for automated match event detection in soccer, moving beyond player and ball localisation to understanding the intent of the play in terms of what is happening in the game. To bring this technology into production as it matures, Sportradar is leveraging AWS services including Amazon SageMaker, EKS, MSK, FSx and Amazon’s broad range of GPU and CPU compute instances for its computer vision processing pipeline. This infrastructure allows Sportradar's researchers to test and validate computer vision models at scale and bring models from the lab to production with minimal effort while delivering the low latency, reliability and scalability needed for live sports betting use cases.

Using AWS, INEOS TEAM UK can process thousands of design simulations for its America’s Cup boat in one week versus in more than a month using an on-premises environment. The team is using an HPC environment running on Amazon EC2 Spot Instances to help design its boat for the competition. For the hull, whose design needed hundreds of compute cores for every simulation, the team used Amazon EC2 C5 instances in addition to the latest Amazon EC2 C5n Nitro-powered instances with Elastic Fabric Adapter (EFA) network interfaces. To ensure fast disk performance for the thousands of simulations completed each week, the team also used Amazon FSx for Lustre to provide a fast, scalable, and secure high-performance file system based on Amazon Simple Storage Service (Amazon S3).

Pulselive is digital partner to some of the biggest sports leagues and events, from the Premier League to the Cricket World Cup. The Sony subsidiary is helping create fan experiences that increase engagement through new and impactful ways. Pulselive uses Amazon Personalize to enable its customers to create highly personalized recommendations for their online sports media content. Working with the Amazon Prototyping team, Pulselive created a new recommendation engine, increasing video consumption by 20%. By leveraging AWS, Pulselive was able to quickly conduct A/B tests, create a simple proof of concept with minimal disruption, and experiment, keeping the barrier to entry low - both technically and financially.