Challenges and opportunities with a commitment to data science

alentyn Kyrylenko, Vice President of Business Development at BetInvest speaks to GI about finding the recipe for success in sports betting

If I were asked whether this business is a challenge or an opportunity, my answer would be: It is a mix of both. The ratio changes over time, mostly starting with challenges that gradually transform into fascinating opportunities. Building a successful B2B company in the gambling industry is extremely challenging, however, the opportunities this industry offers are truly exciting.

Our key competency is sports betting, one of the major challenges in sportsbook business is correct data management. Modern data streams are characterised with three v’s – volume, velocity and variety.

Firstly, we have volume, which is not surprising taking into account almost two decades of BetInvest’s operational experience. With over 25,000 events per month and up to 420 markets per game, the amount of data we provide to our clients is enormous. However, the importance of data volumes doesn’t revolve around the size of data, rather around its quality and the processing abilities.

When our data is combined with professional analytics, it produces a high quality output, therefore the number of different business-related tasks a sportsbook manager accomplishes increases. Business analytics in BetInvest deal with researching and then extracting valuable information from various sources (structured and unstructured) in order to determine best prices and define correct approaches to maximising profit of business users.

Secondly there is velocity. After data discovery and data preparation comes data delivery. Fast access to data is an integral part of the modern sportsbook offering. In-play betting is getting more and more popular among players, which automatically sets high requirements for real-time data processing and delivery. Velocity also means the clients using our platform solution enjoy real time analytics, which involves the analysis of players’ response as soon as it enters the system. New logical conclusions are created based on the combination of such responses in order to deal with possible frauds, risks and, as a result, losses for business partners. By overcoming challenges in this area we are happy to propose thelow-risk in-play betting.

Finally and most importantly there is variety, which comes in terms of different data sources and forms of information. We combine games statistics, match simulations, weather forecasts and tons of other different types of data to assess future probabilities. The sources are usually interlinked in multiple ways, creating complex mutual dependencies and data structures. The way we deal with them ultimately defines the system’s scalability, influencing the speed of data processing.

Both innovation and differentiation should play a fundamental role in the company’s strategy. In particular, we came to further strengthen our commitment to data science, paving the way towards the use of big data and machine learning in sports betting. Our bet is on machine learning. AI based technologies are taking the world by storm. It’s a science of self-learning software algorithms that learn from data and execute tasks otherwise typically performed by humans. AI is an approach that will reshape the technology as we know it. Its implementation in the world of sportsbetting is a top-level challenge. It will allow creation of personalised offerings for every player and will increase their engagement.

In terms of marketing, the modern world opens new opportunities for development. Penetration of mobile devices into mass market, such as smartphones, tablets and smart watches is reshaping customers’ behaviour and habits, changing the way they want to bet on sporting events. It leads us to the task of implementing an omni-channel approach to marketing and developing cross-platform technical solutions. It will allow companies to deliver unique proposals to the players’ fingerprints and interact with the customers wherever they go.