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Case Study

Democratizing AI for Sports Betting

How we used deep learning to build a football prediction and betting tip platform.

Challenge

Regular sports bettors got into a very disadvantageous position recently: they stand “bare hands” against giant bookmakers who have the resources, expertise and technology to leverage the latest advances of AI and big data analysis. We believe it’s an unfair advantage.

Solution

We have built a football prediction and betting tip platform powered by deep learning. Unlike most betting tips websites, our approach is data-driven and rooted in well-founded research. The platform provides users with odds monitoring and actionable betting tips based on a personalized betting strategy. Performance is transparently tracked for all recommendations.

The platform is currently under beta testing for invited users.

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System Architecture

Approach

First, we trained a deep neural network to predict football match outcomes of five European leagues. In order to minimize potential biases, we leveraged the natural fluctuation of the model’s accuracy across the training epochs and ran 100 Monte Carlo simulations for each league. Each league’s model was only trained on the data from the other four leagues. In an easy-to-use SaaS interface, we present the users with tips of maximum expected value and recommend a mathematically optimal stake according to user’s individual risk profile. Performance of the model is constantly evaluated.

Betting online

Results

9.6%

average yearly return

4.9%

median yearly return

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