The World's First Independent Esports Data Marketplace for In-Game Data
Berlin, 13.09.2019 - One of the greatest challenges facing the fast-growing esports industry is the availability of reliable real time in-game data. Exclusive contracts, manual data collection, and the lack of a central interface complicate broad distribution and the development of industry standards. This is where Bayes comes in. The tech start-up, which has grown to over 20 employees in just six months since launching, has developed BEDEX—an independent marketplace to provide data consumers with reliable live data through a single interface. From the start fast live-data for ESL and Dreamhack (CS:GO) and for Riots LEC, LCS and international Lol tournaments will be available. Further expansion to include other gaming titles and organizers is already in development.
Data is a valuable asset in esports. Correctness and accuracy are unfortunately not a given, of course, as Martin Dachselt, Managing Director of Bayes, stresses. For data consumers, such as bookmakers or the media, this is a big problem—"especially in esports, which is much more agile and fast-paced than traditional sports." Data consumers want data with a high level of detail for all events and games "preferably from a single source," continues Dachselt. In addition, exclusive contracts between service providers and right holders make broad distribution and standardization difficult. For example, betting and media companies often only have access to the data of individual organizers or tournaments which severely limits coverage.
It is at this precise intersection of complexity where Bayes picks up the reins and takes a central stage in the industry with its marketplace, BEDEX. The Berlin-based start-up is in the process of finalizing distribution agreements for esports data and video streams with tournament providers.
Following the agreement, Bayes will carry out the technical integration. This includes data collection and processing as well as the creation of complex products such as real-time visualizations and probabilistic models.
