Shot Efficiency and Passing Profile bring the total number of advanced statistics to eight, using AWS machine learning and analytics to give fans deeper insights into the game of football
Amazon Web Services (AWS), an Amazon.com, Inc. company , and the German Bundesliga, Germany’s top national football league, announced two new Bundesliga Match Facts powered by AWS that will premier as graphics during broadcasts and in the official Bundesliga app during the 2021–22 season. The first advanced stat, Shot Efficiency, compares the actual number of goals that a player or team has scored with how many goals the player or team should have scored based on the quality of their chances. The second, Passing Profile, provides deeper insights into the pass quality of a player or an entire team. Both stats will debut during Matchday 4 on September 11, 2021, featuring the faceoff between German Champion FC Bayern München and the second-place team of the previous season, RB Leipzig.
Bundesliga Match Facts help audiences better understand nuanced aspects of the game of football, such as decision making on the pitch or what goes into exceptional player performance. Bundesliga generates the Match Facts by gathering and analyzing the match feeds from live games in real time as they’re streamed into AWS. On the backend, Bundesliga uses AWS capabilities in analytics, machine learning, compute, storage, database, serverless, and media services to process and store the vast amount of data that powers these statistics, as well as to train, deploy, and scale the machine learning models used to generate predictions. Fans see the insights as graphics during broadcasts, with additional details in the official Bundesliga app. The two new Match Facts will better showcase the action on the field and give fans, coaches, players, and commentators visual support for analyzing players’ and teams’ performance.
New Bundesliga Match Facts for the 2021–22 season powered by AWS
Shot Efficiency: Football fans love to revisit and break down scoring opportunities to better celebrate or mourn key game moments. This new stat helps fans determine which players or teams best exploit their chances at scoring a goal. It compares the number of goals that a player or team has actually scored with the cumulative value from Expected Goals (xGoals)—an existing Bundesliga Match Fact—which is the number of goals the player or team should have scored based on the quality of their attempted shots. The difference between these two values is the Shot Efficiency number. If the value is negative (shown on TV by a red arrow pointing down), the player or team has scored fewer goals than would have been expected. If the value is positive (green arrow up), the player or team exceeded the expected value. For the first time, each player’s efficiency can be objectively assessed based on the overall quality of shots and the number of goals scored. For example, this advanced stat can compare two strikers who scored the same number of goals after 10 matchdays to determine which player is converting goals in challenging versus easy situations. Commentators can also use the stat, for instance, to analyze if players have a high number of goals because they are well supported by their teammates or because they exploit openings in the defense.
Passing Profile: Fans often put themselves into a player’s shoes and compare the choices they might have made in a given situation to what the player actually did. This new stat helps fans understand how players think and decide where to pass the ball. It also provides deeper insights into the pass quality and pass strength of players and teams, including which passing decisions they prioritize, such as an offensive pass, passing the ball back, or opening up play with a long ball. Before Passing Profile, the effectiveness of player passing was measured primarily by the number of passes that successfully reach a player’s target; now, with Passing Profile, it is possible to assess the quality of passes too, accounting for pass difficulty. For instance, by looking at how many opponents press the recipient and passer, how high the ball is in the air, and how many opponents were positioned between the recipient and passer, the stat calculates the pass difficulty rating. It also offers further insights into the passing behavior of a player or team by identifying the number of long and short passes, pass direction, and the type of passes a player favors.
To develop these stats, machine learning models trained on Amazon SageMaker (AWS’s service that enables data scientists and developers to build, train, and deploy machine learning models quickly) analyzed thousands of video hours of previous Bundesliga seasons. In the case of Shot Efficiency, Bundesliga trained its machine learning models on a dataset of more than 40,000 historical shots on goal, which includes features derived from player positional data, such as distance to goal, angle to goal, player speed, number of defenders in the line of a shot, and goalkeeper coverage. In the case of Passing Profile, Bundesliga analyzed video of nearly 2 million passes and used that data to construct an algorithm that computes a difficulty score for each pass at any moment, evaluating characteristics such as distance to the receiver, the number of defending players in between, and pressure on a player. Once computed, Bundesliga aggregates difficulty scores for each player and team to form a passing profile.
“Bundesliga Match Facts powered by AWS allow us to give fans more insight into the game of football, broadcasters more interesting stories to tell, and coaches and teams more data to excel at their game. Last year, the reception for Bundesliga Match Facts around the world was very positive, and we will continue to raise the bar and innovate on these analytics using machine learning to make them even better. The two new stats for this season give fans a view into player efficiency that hasn’t been achieved before, and we are still just at the beginning of our relationship with AWS. I’m excited to see how technology will continue to evolve the fan experience and the game,” said Andreas Heyden, Executive Vice President of Digital Innovations for DFL Deutsche Fußball Liga (DFL) Group.
“Teams, leagues, broadcasters, and their partners from across the sports world are using AWS to build data-driven solutions and elevate the fan experience. We’re excited to continue our work with Bundesliga to connect with their fans in a way they haven’t been able to before this collaboration,” said Klaus Buerg, General Manager for AWS Germany, Austria, and Switzerland, Amazon Web Services EMEA SARL. “Through the work we’ve accomplished with Bundesliga in creating eight Bundesliga Match Facts in a short period of time, we are giving fans a new way to appreciate player speed, field positioning, goals, passing, and shot efficiency, creating even more excitement in watching the game.”
These two new Match Facts join Speed Alert, Goal Probability, xGoals, Most Pressed Player, Attacking Zones, and Average Positions: Trends to bring the total number of insights available for Bundesliga fans to eight. Information on all of these statistics can be found at aws.amazon.com/sports/bundesliga/. Football fans also can follow all of the latest Bundesliga action on Bundesliga.com and via the official Facebook, Twitter, and Instagram channels.