As the football season reaches its midway point, it’s time to take a step back and reflect on the highs and lows of my betting journey. In this blog post, I’ll share my real-life experiences, insights, and lessons learned from the first half of the season. Join me as I navigate the unpredictable world of football betting and explore the strategies that have shaped my approach.
Continue reading “Season 2023/24 – Did I create a Bet-The-Draw-Machine?”Comparing the predictive power of different xG data providers
In the realm of sports betting, predictive analytics hinges on quality data, a challenge given the cost associated with many paid services. This article delves into the world of free xG (Expected Goals) data providers used by the BeatTheBookie services, assessing their predictive power for football betting, a critical aspect for enthusiasts who seek to enhance their strategies without breaking the bank.
Continue reading “Comparing the predictive power of different xG data providers”Season 2023/24 – Comparing my Mollybet bets with my Ensemble model
Just like every season, I am excited to share my experiences with using different betting models. This year, I have been particularly focused on my ensemble model, which incorporates a diverse range of data and algorithms. Over the first three months of the season, I placed numerous bets, and now I want to take a closer look at the outcomes. I aim to share my insights and analyses regarding these bets. Let’s delve into the realm of sports betting together and explore what we can learn from these initial months.
Continue reading “Season 2023/24 – Comparing my Mollybet bets with my Ensemble model”Scraping FBRef xG data with Python
In the realm of sports analytics, FBRef has recently unveiled an essential update: the availability of Expected Goals (xG) data for previously uncovered divisions. This pragmatic addition opens doors to nuanced insights, particularly valuable in the world of sports betting. In this blog post, I pragmatically explore these developments. Using Python and adept web scraping techniques, I dissect this fresh data.
Continue reading “Scraping FBRef xG data with Python”Inside the BeatTheBookie App – Predicting football matches with an Ensemble model
Not only is it the core feature of the BeatTheBookie app, but it’s also the primary reason why I started developing the app. However, why is this the case, and how does this type of predictive model work for predicting the outcomes of football matches? Let’s delve into it.
Continue reading “Inside the BeatTheBookie App – Predicting football matches with an Ensemble model”BeatTheBookieApp – Ensemble performance
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.
Continue reading “BeatTheBookieApp – Ensemble performance”Season 2023/24 – A reconciliatory ending
The 2023/24 season has come to an end. This was the first season in which I used my ML Poisson Model and documented the betting results in multiple posts. So let’s take a look at how the overall result of the season turned out.
Continue reading “Season 2023/24 – A reconciliatory ending”BeatTheBookieApp – Ensemble predictions
The BeatTheBookie App is a web data app that provides me with predictions for my daily betting. However, there has always been something that bothered me a bit: the comparison to the odds of a bookie. Each bookie uses a different margin, making it difficult to identify value and determine the amount of value a bet offers. Fortunately, this issue is addressed with the introduction of the Ensemble predictions dashboard.
Continue reading “BeatTheBookieApp – Ensemble predictions”BeatTheBookieApp – Model performance
The BeatTheBookie App is a web-based data application that grants me access to predictions generated by various models that have proven their performance over time on my blog. However, determining which model to utilize for a specific match can be challenging. Thankfully, the model performance dashboard offers the solution to this dilemma. By exploring the dashboard, I gain valuable insights into the theoretical performance of the different models in past scenarios. This information aids me in selecting the most suitable model for each match, increasing the chances of making informed betting decisions.
Continue reading “BeatTheBookieApp – Model performance”BeatTheBookieApp – Model predictions
The BeatTheBookie App is a web data app that provides me with predictions for all models that have demonstrated their performance throughout the history of my blog. As it has already been proven, there is no single best model for all divisions. Therefore, I wanted to be able to compare predictions, as each model takes into account different aspects of past performance. The result is the model predictions dashboard.
Continue reading “BeatTheBookieApp – Model predictions”
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