Sommersemester 2020 - Studentisches Start-up Projekt
In professional ball sports, teams, athletes and sports fans receive interesting and helpful information and statistics regarding the game. No matter if football, tennis, golf, etc., at the end of a match you always get lots of data and statistics about the respective match. In football, for instance, this could be the pass rate, the duel rate, the number of goal shots, and much more. The data provided can refer to the entire team, but also individual players. However, this is not available for amateur clubs so far. Hence, our vision is to make sports game analysis affordable for everyone.
Amateur clubs face great challenges when analyzing their own football games to improve their players’ performances. So far, there exists no tool tailored to their needs, as the solutions by current providers are not affordable and almost exclusively targeting the professional market. Therefore, our goal is to provide a 100% digital game analysis program tailored to the needs of amateur clubs.
We approached the project with the lean start-up method, where we constantly used build-measure-learn techniques. This approach consists of iterative hypothesis testing cycles with the aim to come up with an MVP. We therefore conducted qualitative interviews with more than 100 amateur football clubs to receive key-insights about their problems and current experiences with analyzing their football games, their needs, and their willingness to pay. Additionally, we talked to experts in the industry. We interviewed experts related to football, as well as experts in the technical areas. Beyond that, we developed two prototypes to illustrate our product to our potential customers. Firstly, we created a ‘dummy’ in order to demonstrate how our product would create value to them. Secondly, we designed a landing page to provide amateur clubs more information about the product.
We found out that most of the amateur clubs face great challenges in analyzing their games, as they still have to do this manually. In fact, this is very time consuming and includes a high rate of mistakes. Additionally, we identified that many amateur clubs often have limited budgets to afford such a product. Based on these insights, we developed a business model that is perfectly tailored to amateur clubs. As about 50% of amateur clubs already film their games themselves, we decided to keep this task with them. So the only thing they need to do is to upload the video into our program after the game as a first step. As a second step, the data will be automatically processed through our technology and all the statistics will be prepared. As a result, amateur clubs visually receive their statistics through our fully automated analysis program. We will offer our easy to use solution to amateur clubs for a monthly subscription fee of 160€. All in all, our team got a proof of concept over the semester in this course. We plan to develop our 100% digital solution by using artificial intelligence, visual computing and data analytics. In case an amateur football game is filmed via smartphone or video camera, our technology is developed to recognize all the passes, shots, fouls, etc. and to visually prepare the data for the subscribers. Due to our limited technical capabilities, we had to overcome the obstacle to find a technical expert, who can develop such a technically sophisticated product. Luckily, we finally found two experts in June 2020 and they are currently working on the first “real” prototype of our product.
Dilay Türe (TU)
Alexander Jerabek (WU)
Adnan Dzanovic (WU)
Sebastian Felber (WU)
Alexander Rifaat (WU)
Thomas Pannermayr M.Sc.
Alexander Staub M.Sc.