Pulse
esports
DATA.BET
betting into a science
DATA.BET's Oleksii Kulish, Lead Data Scientist, explores how Data Science is
reshaping the betting landscape, offering groundbreaking advancements and
providing a sneak peek into an exciting future of possibilities.
PREDICTIVE ANALYTICS
Over the past five years, the esports industry has achieved remarkable advancements in developing and refining mathematical models and algorithms. Data Science plays a pivotal role in this evolution, emerging as a secret weapon that unlocks new horizons for business owners. Te focus has shifted from traditional methods to gaining a strategic advantage through understanding and utilising data.
Diverse models, including regression analysis, neural networks, and deep learning, enhance the precision and relevance period of live predictions, optimising the efficiency of bet selection. As a result, more markets can remain open until the end of gaming events.
Predictive analytics stands at the forefront of innovation in the world of betting. Companies strive to be the first in posting odds and to provide the highest accuracy in forecasts and the widest range of bets. While traditional calculations in classic sports relied on statistical distributions considering team strengths and game history, modern esports demand a more complex approach. Here, conventional methods often fall short, and this is where Data Science methods and models take centre stage.
Te significance of this innovation goes beyond the accuracy of predictions. Te growing interest in betting has significantly boosted live market turnover, surpassing pre-match markets. Tanks to various models andData Science approaches, the diversity of the markets became particularly appealing, paving
P74 WIRE / PULSE / INSIGHT / REPORTS
the way for intriguing live models, which enhance decision-making and enable the industry to offer more live markets, keeping them open for extended periods.
Tis dynamic approach has resulted in a remarkable increase in the volume of bets, ranging from 5-10 times, and a higher percentage of selection, typically by 1.5-2 times. For instance, in MOBA games, these models concentrate on markets like total kills or match duration, injecting dynamism into the game and appealing to players fascinated by specific gameplay aspects.
In games like CS:GO, a diverse range of bets has surfaced, including options such as who will plant the bomb, the team's purchase strategy, or the exact score in a round. Tese additional markets heighten the excitement of the game and allow players to delve into the details of team tactics and
strategies.Data Science helps companies continuously adapt to the changing demands of the market, allowing them to stay one step ahead of competitors and meet the diverse interests of players.
Te use of machine learning models has also reduced the need for manual labor, allowing the calculation and offering of dozens of different markets in live mode without the risk of errors due to manual trading. As a result, traders have become more like operators, ensuring that everything goes according to plan rather than traditional analysts.
Tus, predictive analytics proves to be not just a powerful tool for analysis and forecasting but
Oleksii Kulish
Lead Data Scientist
DATA.BET
also a significant marketing asset. It attracts players by offering them a more comprehensive range of betting possibilities and enhances the overall profitability of companies that stay ahead in the data game.
SOPHISTICATED PLAYER BEHAVIOUR ANALYTICS
Tat is crucial not to forget that understanding and analysing user behaviour through Data Science models also becomes an integral element of success in the industry, where each player has unique preferences and gaming habits. However, analysis of customer data has a much broader application scope.
Specifically, Data Science models effectively identify fraudulent users, helping pinpoint anomalies in player behaviour and bets. Tis ensures the platform's security and maintains trust and loyalty among honest users.
Classifying players into different groups based on data analysis is another key aspect. Categorising users allows to provide a personalised approach to each group. For instance, early identification of potential VIP clients enables the offering of exclusive bonuses and attention, fostering loyalty and long-term cooperation. Tis approach gives players a sense of attention to their interests and increases the chances of making bets by about 20 per cent.
DATA PARSING AND PROTECTION Considering the speed and dynamics of esports
transforming
DATA.BET:
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