Machine learning and Artificial Intelligence is widely used in time series analysis & forecasting. With help of several historical data & computing power, ML & AI models sometimes will produce very useful insight & guidance to horse racing odds for today betting decisions.
When using machine learning and artificial intelligence models for horse racing we rightly require a little way to access how successful they are. Horse race betting will be different in predicting the face recognition or cancer diagnosis as these applications are about the accuracy of the predictions. With horse racing betting, accuracy has an important part to play, however, it is not a complete picture.
The less accurate model can be more profitable & for this reason, we focus more on the profit. The common profit measurements will be variable stake profit and flat stake profit. The variable staking profit means we will place the stake set for winning £1 as per the odds. The flat stake profit means placing £1 on each selection, like top-rated in ratings Thus, for instance, 2/1 shot will have a bet of 50p on it. Obviously, in both the examples stake will be whatever you would like it to be.
Challenges: Support betting with the online models
Just like other AI-backed services, companies providing live betting will benefit from the online models that generate predictions and help to determine the live odds in sports betting and races. The online models need several input features that will make accurate predictions, which include low latency access of features, which are computed from the historical data. These kinds of features are very complex to compute in an online application themselves as well as are not possible to reuse in case they’re embedded in the applications. Nonetheless, the classic classification models aren’t suited for the betting strategies, so one has to use the custom loss feature in his network to attain better profitability.
Once you implement the feature computation in the online application, then you need to make sure consistency of an online feature implementation with feature implementation that is used to produce the train or test data for this model (training data pipeline). Many different ML and AI learning approaches are applied to horse racing like Artificial Neural Networks & Naïve Bayes Classifiers.
ANN Horse Racing Predictions
The Artificial Neural Network is trained on the input data. For horse racing, input data is the large corpus of the race results. But, the tricky part is to determine which metrics you must include in an input training data like win % on X number of horse races, jockey, trainer, gender, going, and more. We’re constantly refining these metrics used in the system with different sets of metrics that are used for the flat racing, steeplechase, and hurdles (we have seen a huge difference in the performance of the metrics between the racecourses – this might be because of issues with the source data).
When input data is prepared the artificial neural network will be trained. This neural network is generally initialized with the input node representing every metric and output node as finish position refactored like 0 for the last and 100 for the first. It is one example of supervised learning as the right output is known while compiling input data. This network is well-trained by presenting input data and making incremental changes to the configuration of a network till output matches its target very closely. The neural network is well-suited to the task since it will handle an inevitable freak result, which appears in input data.
Final Words
Machine Learning and Artificial Intelligence have impacted everything across us as well as have gone through many criticisms too. But, over the past many years, this new technology has delivered most of the promises in different industries such as finance, healthcare, and more. With artificial intelligence starting to impact the sports betting industry, it’s promising the legal and accessible way to bet through these Sportsbooks that is the billion-dollar industry allowing the players to bet right from their phones or laptops safely. With this scenario available to you, soon artificial intelligence can close this gap that comes between gambling & investing.