In order to develop your betting strategy, you need to build your own statistical model for the sport you want to bet. So how to develop your statistical model?
The sports betting model is a betting system that allows you to identify criteria that will help you appreciate sports events with probabilities. The main function of the statistical model is to determine the more accurate probabilities than the bookmaker’s odds. Based on the advantages of evaluating team capabilities.
The process of creating its own betting system using statistical models is a long and difficult process that involves the detailed collection of information and its converting into probability. It’s not east to beat the bookie, but those who with their strategy did it, got their reward.
Stages of constructing a statistical model
Stage 1: The purpose of the model
For example, we need to evaluate and count the matches of the Polish League teams. Not just calculate, but give more accurate probabilities than bookmakers. Only in this case will we be able to rely on profit.
Stage 2: Choosing the results to evaluate the model
The main objective of our model is to accurately assess the probabilities for a match of the Polish League. Therefore, you have to choose which betting market to choose. In our example, this is an asian handicap market.
Stage 3: Collection of information
At this stage, you have to determine which raw information you will use in your model to evaluate the teams and which will be converted into probability.
For example, will you use goals or xG model ( expected goals model ) for teams.
Football Betting System
Stage 4: Choice of a prediction model form
To determine the probability of a match result, you must use numeric formulas. For example, you use the formula of the simple theory of probability in the last 5 matches of the teams. For example, in the last 5 matches, team A: 3 wins, 1 draw, 1 loss. Team B: 1 win, 2 draws, 2 loses. The probabilities for the possible results of the match will be as follows:
- team victory A = 50%
- draw = 30%
- team victory B = 20%
You can also use the Poisson distribution to rate soccer matches, which you can read here.
This is just an example, the models can be unlimited. It all depends on how your imagination works.
Stage 5: Parameters
You need to determine which parameters to add to the model. If you are building a statistical model for evaluating football matches, you will need to determine the advantage of a home field in this league. There may be options that determine how a team plays with and without the key player, the arrival of a new trainer, injured players, and others.
Stage 6: Building Prediction Model
To develop a prediction model you can use Excel, programming languages. Tip: Use the programming language R.
Stage 7: Backtesting
Suppose that we have chosen the form of the model – the Poisson distribution. With it, you have identified the likelihood of asian handicap. Now you need to determine from the results of previous matches whether your model is more accurate than the bookmaker. If your model has given an accurate prediction in more than 50% of the matches, you can consider it as profitable. Follow the principles of the following articles to identify value bets:
Stage 8 Monitoring results
Suppose, after backtesting of your model in previous matches, you have come to the conclusion that your model is profitable. But this may not always be the case, because the bookmaker can take into their odds other factors that contribute to the profitability of your model. So, with time, change your model to warn yourself of the be in red. To do this, go back to step one and develop the model again.
Football Prediction Model
Use the Poisson distribution to build a statistical football model. This is the base you need to study for further development in professional betting.