How is Bundesliga revolutionizing viewer experience using AWS ?

Today, sports leagues are looking to learn more about players and find a competitive edge through more advanced stats.Machine learning, Artificial Intelligence and Cloud Computing are leading the next wave of technical sports innovation.

5 min readSep 22, 2020

Germany’s Bundesliga has become the first soccer league to form a partnership with Amazon Web Services to build data-driven solutions which will help generate advanced real-time statistics to integrate into live broadcasts of league matches.
Amazon’s machine learning platforms will analyze live data streams and historical data from more than 10,000 Bundesliga games to deliver insights such as predictions on when a goal is likely to be scored.

Why Amazon Web Services

AWS is currently a partner of several high-profile rights holders, including the NFL, MLB as well as Formula One and Nascar. However, this marks the company’s first entry into soccer.

The Bundesliga will use a variety of AWS AI services to achieve the next level experience on digital platforms and broadcast. From using ‘AWS Comprehend’ and ‘AWS Translate’ to generate localised Bundesliga content, to ‘AWS Personalize’ to serve the most relevant content to Bundesliga fans and applying ‘AWS Rekognition’ to make the media archive smarter. Additionally, the DFL and AWS will work together to develop custom machine learning models with ‘AWS Sagemaker’ to generate new insights around the match.

Deriving insights from a text using Amazon Comprehend

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text.The service identifies the language of the text - extracts key phrases, places, people, understands how positive or negative the text is and automatically organizes a collection of text files by topic.

Build, train, and deploy ML models using Amazon SageMaker

Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps. SageMaker Studio gives you complete access to build, train, and deploy models. You can quickly upload data, create new notebooks, train and tune models, deploy these models to production all in one place.

Automating image and video analysis using Amazon Rekognition

Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology.It helps to identify objects, people, text, scenes, and activities in images and videos.It also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases. With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs.

Creating real-time recommendations using Amazon Personalize

Amazon Personalize, a machine learning service offered by AWS enables you to improve customer engagement which can used to offer fans personalized game footage, search results based on their favourite teams, players or fixtures.

Bundesliga Match Facts powered by AWS

Average Positions: Fans will now be able to see the positioning of a team’s players on the pitch and gain insight into the team’s intended playing style. Average Positions provides new insights based on analysis performed on data captured from tracking a player’s average location on the field, which is then displayed in real-time. This statistic will help the viewer to understand if the team is setting up in an attacking or defending style, holding the midfield area or utilizing the wings.

xGoals: We can now assess the probability of a player scoring a goal when shooting from any position on the field. The goal probability is calculated in real-time for every shot to give viewers insight into the difficulty of a shot and the likelihood of a goal. To calculate the precision of xGoals, machine learning models were trained by analyzing 40,000 shots on goal.

“ These two new statistics are just the beginning of what we’ll be able to deliver for football fans as we look forward to unlocking new ways to better educate, engage, and entertain viewers around the world.” said Andy Isherwood, Vice President and Managing Director EMEA, AWS

It all starts with data

To bring Match Facts to life, several checks and processes happen before, during, and after a match. Various stakeholders are involved in data acquisition, data processing, graphics, content creation (such as TV feed editing), and live commentary. Each one of the Bundesliga soccer stadiums is equipped with up to 20 cameras for automatic optical tracking of player and ball positions. An editorial team processes additional video data and picks the ideal camera angles and scenes to broadcast.

Eventually, all the raw match data is ingested into the Bundesliga Match Facts system on AWS which are then distributed worldwide for broadcasting.
Real-time content distribution and fan engagement are especially important now, because Bundesliga matches are being played in empty stadiums, which has impacted the in-person soccer viewing experience.

Bringing code to production

The mission of AWS Data Science consultants is to accelerate customer business outcomes through the effective use of ML. For data quality evaluations and initial experimentations, we need to perform exploratory data analysis, data visualization, data transformation, and data validation. As an example, this can be done in Amazon SageMaker notebooks. The next natural step is to move the ML workloads from research to development. Deploying ML models to production requires an interdisciplinary engineering approach involving a combination of data engineering, data science, and software development.

We use two databases to store the match states: Amazon DynamoDB, a key-value database, and Amazon DocumentDB (with MongoDB compatibility), a document database. For central storage of official match data, we use Amazon Simple Storage Service (Amazon S3).

To monitor the performance of the application, we use an AWS Amplify web application. This dashboard also allows us to collect metrics to measure and evaluate the achievement of desired outcomes.

Christian Seifert, the DFL chief executive, said: “Innovation means challenging the status quo. Working closely with AWS as one of the most innovative technology companies in the world significantly enhances the investment we’ve made in innovation over the past two decades, all of which contributes to us being able to deliver a world-class football experience for our fans.”

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