Statistical Betting Model
Авиасловарь. М.А.Левин. 2004.
Learn How how to use Statistics and Build Your Own Sports Betting Model in spreadsheet. Project Your Odds and Make Smarter Bets!
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Книги
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We continue the series of articles that tell us about the principles of automated forecasting. Today, it will be more about the theory — about the methods of statistical analysis. We tried to write about a relatively complex topic in simple language.
Methods of statistical analysis are based on the study of various statistical data, that is, the aggregate of any objects (situations, cases) and inherent characteristics. For sports, the objects of statistics will be individual players, sports competitions, bets. And their variable characteristics are separate qualities that can vary depending on the time or kind of the object. Investigating objects and inherent features, one can distinguish patterns that allow predicting the behavior of these objects with some accuracy in the future. Therefore, statistical methods play an important role in determining winning bets for sports events. Analysis of statistical data in sports is based on the study of tournament tables, previous results of players / teams, existing forecasts, bets, etc.
What methods of statistical analysis can be used for forecast of bets?
The simplest methods of analysis can be used even by beginners, for example, to conduct an elementary assessment of the results of previous matches. So, if team A in 90% of cases defeated team B, then it is likely that she will win it in the next match. But it is not always possible to make a working forecast without analyzing a large number of heterogeneous data.
Statistical connections in practice are much more complicated: changing just one factor in the present time sometimes entails a change in a number of other factors. In sports betting, the most commonly used methods of mathematical statistics, which are the most accurate and allow for several parameters. Usually, various services or computer programs are used for calculations. The accuracy of the mathematical analysis depends on the latitude of the sample — the more data is available for analysis (for example, the greater number of matches or bets), the more accurate the forecast will be.
In the forecasting of sports betting, the following methods of mathematical statistics are borrowed in whole or in part:
Sports Betting Statistical Models
- Correlation — the identification of the relationship between different data. Allows you to calculate the correlation coefficient — the quantitative relationship between two (and more) events / factors. If it is greater than 1, then the facts are interrelated.
- Regression — the dependence of some factors on the others is calculated as a function, with its help and forecasting is carried out.
- Dispersion — study of the significance of differences in mean values for the detection of dependencies. Simply put, the study of the influence of independent variables (data that can’t be influenced) on the dependent variable (the bet value).
- Factor — the identification of various relationships between a large number of initial data and patterns (factors) that make it possible to identify important.
- There are other methods of mathematical analysis. Mathematical statistics are quite accurate, since it operates with exact figures, although it does not take into account non-fixed, subjective indicators (for example, player fatigue after a series of matches, etc.).
Methods of mathematical statistics in practice
The algorithm for obtaining a mathematical forecast can be presented in the following simplified form: first, an analysis of the indicators that affect the team / player rating or the winning bet is selected, then they are analyzed in terms of importance and degree of influence. Based on the analysis, a mathematical model is formed, its accuracy and the presence of errors in the calculation are estimated. As a result, we can draw conclusions about the outcome of the sporting event and the success of the bets.
Football Betting Statistical Models
As examples of application of mathematical statistics in practice, the following calculations can be cited:
- A mathematical expectation is the calculation of the average probable win or loss. This probability is calculated by analyzing the same bets for similar sporting events. MO is considered according to the following formula: multiply the possible gain by its probability and subtract from the amount received the possible loss (the amount of the bet) multiplied by its probability. It is important to make bets only if the MO size exceeds the zero value.
- Predictability strategies — to determine the most favorable bet, the estimated match score obtained after analyzing the statistics is used.
- Calculation of variance — calculation of the deviation from the mathematical expectation. Dispersion can be associated with a small amount of data — the smaller the sample, the higher the probability of deviation from the true value of the math expectations. So, there is more risk of error and loss.