Goal! In this competition, you’ll detect football (soccer) passes—including throw-ins and crosses—and challenges in original Bundesliga matches. You’ll develop a computer vision model that can automatically classify these events in long video recordings.
Your work will help scale the data collection process. Automatic event annotation could enable event data from currently unexplored competitions, like youth or semi-professional leagues or even training sessions.
What does it take to go pro in football (soccer)? From a young age, hopeful talents devote time, money, and training to the sport. Yet, while the next superstar is guaranteed to start off in youth or semi-professional leagues, these leagues often have the fewest resources to invest. This includes resources for the collection of event data which helps generate insights into the performance of the teams and players.
Currently, event data is mostly collected manually by human operators, who gather data in several steps and through numerous personnel involved. This manual process has room for innovation as in its current shape and form it involves a lot of resources and multiple iterations/quality checks. As a result, event data collection is usually reserved for professional competitions only.
Based in Frankfurt, the Deutsche Fußball Liga (DFL) manages Germany’s professional football (soccer) leagues: Bundesliga and Bundesliga 2. DFL partners with the operator of one of the largest sports databases in the world, Sportec Solutions. They’re responsible for the leagues’ sports data and sports technology activities. In addition, Sportec Solutions provides services to global sports entities and media companies.
Automatic event detection could provide event data faster and with greater depth. Having access to a broader range of competitions, match conditions and data scouts would be able to ensure no talented player is overlooked.
Awards:-
- 1st Place – $ 12,000
- 2nd Place – $ 8,000
- 3rd Place – $ 5,000
Deadline:- 06-10-2022
