In this blog post, we will explore the performance dashboard for the BeatTheBookie App’s ensemble model. This powerful predictive model combines the expertise of multiple individual models to forecast football match outcomes. By leveraging insights from the performance dashboard, we can make informed betting decisions and increase our chances of success. Let’s dive into the details of this game-changing feature.
How to identify a good model?
The ensemble model’s performance dashboard offers valuable insights. A simple 1-unit flat staking strategy is employed, placing theoretical bets when the ensemble model’s odds offer value compared to the fair Bet365 odds. By considering the average profit and number of bets, we can estimate the profitability of a model over a specific period.
The dashboard utilizes fair odds that exclude any margin, ensuring a reliable comparison. It’s important to note that a profitable model should generate a higher average profit than the bookmaker’s average margin.
With diverse filtering options, the dashboard empowers you to make well-informed decisions. By evaluating the performance history and predictive capabilities of the available models, you can optimize your betting strategy, enhancing profitability and reliability.
The following filters are available on the dashboard:
Divisions
You can assess the profitability across different divisions or a specific group of divisions. By selecting multiple divisions, the “Performance per Division” tab presents a breakdown of the profit achieved in each division, allowing you to evaluate the performance in various contexts.
Seasons
Evaluating whether the ensemble model is consistently profitable over an extended period or if its success is limited to a single season is crucial. To facilitate this analysis, the “Performance per Season” tab allows you to compare the performance across different seasons. This feature enables you to identify any seasonal patterns or fluctuations in a model’s profitability.
If you have further questions, feel free to leave a comment or contact me @Mo_Nbg.
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