Building Your Own Sports Betting Model
First off, let’s start by defining what a sports betting model is. A sports betting model is a system which is able to identify unbiased reference points. This can then allow you to determine the probability for all outcomes in a particular match or game. Ultimately, the model will be able to highlight good betting opportunities, by assessing and analysing a team or player’s true ability significantly more accurately than any bookmaker. This all sounds great, however, it must be stated here that building a sports betting model can be a rather difficult and time-consuming process. Furthermore, you have to follow numerous instructions and orders when creating your own model, which can complicate the already tedious process. On the flipside, once you have successfully created a functional betting model, it will most likely show you profitable betting opportunities that the general bettors simply wouldn’t be able to consider.
There are five main steps to building a betting model:
Specifying the aim or goal of your betting model
This might seem like a straightforward and unnecessary step, but many sports bettors miss the point their betting model is trying to accomplish. Without a specific aim, you could be overwhelmed with numbers and lose focus of your overall goals. Although you could say that you could collect the data first, to see if there are any patterns, this will still need to be tested against several hypotheses, each with a different aim. Therefore, starting with a specific aim, is strongly recommended.
In betting the most common goal is to produce accurate probabilities of a team winning. This is a notably different object than achieving the highest prediction accuracy.
The next step is short and simple. All you have to do is decide upon a numerical form by selecting a quantifiable metric.
Common metrics include; accuracy, cross entropy, F1-score, mean squared error, and mean average error. However, these measure different things, so be careful with how you interpret them.
Collecting, grouping, and modifying data
All sports betting models require data to integrate into the algorithm. There are two ways of collecting data. One involves the painstaking process of gathering the appropriate data by yourself, the other involves using published data online. Luckily for bettors keen on building their own models, there is endless amounts of data available online. Once you have the data, there are several queries that need to be taken care of. For instance, if we are looking at CS:GO matches at a certain event, should you consider all the previous matches or just the matches from the last tournament? This is where you can exercise your judgement, and make adjustments, determined by what your aim is.
Choosing the form of the model
This is where the mathematical part comes into play. Given that there are just so many models to choose from or create, our recommendation here is not to overcomplicate.
Logistic Regression is a good starting point for modelling the outcome of sports games, where there are two teams, one winner, and no draws. Logistic Regression can be generalized to Multinomial Logistic Regression in the case where there can be a draw, or when there are more than two outcomes (horse racing). These linear classifiers have very simple implementations in sklearn (python), R and even Excel.
Dealing with assumptions
Each model will have a number of assumptions, and you should be aware of their strengths and limitations. You may forget to do this, but it’s an absolutely vital step. For example, a significant factor behind the financial crisis in 2007-2008 was the misuse of derivatives caused by a misunderstanding of assumptions in contracts.
Building the model
This step finally gets to actually building the sports betting model. There are various tools and resources to help you, including online calculators, Excel, Python and R programming. You don’t have to be a programming or a mathematical genius to build a sports betting model.
Testing the model
It’s crucial that you regularly test the accuracy and efficiency of your sports betting model to understand how sensitive it is to the results. In any case, the results of the model may lead you to reconsider and attend to any of the previous steps. The key question as it always is in sports betting is to assess whether or not the model is making a profit.
Monitoring the results
Assuming that a solid model has been built and tested, it needs to be maintained and updated as time progresses. This loops us right back to the start – defining future aims.
Applying the knowledge from here
Understanding the steps involved here is important when learning to build a sports betting model. However, quantitative modelling isn’t solely focused on building a model and applying. There are a number of processes (not necessarily in the order stated) which should be completed. Following this process won’t guarantee a profitable model. but it will ensure you are considering things that are needed to build a sports betting model. Make sure you follow our blogs and learn the ways to make yourself a better bettor.