This exact science is able to demonstrate how profitable to bet on a particular event, and how likely it is that the game will end with a certain result. Many bettors regularly lose their money simply because they do not use math in sports betting.
Mathematics in betting
In order to estimate the chances of the team you are betting on to win, you need to understand probability theory. The odds provided by a bookmaker’s office will help with this. As a rule, they correspond to reality, i.e. reflect the real balance of power. However, there are situations where bookmakers deliberately under or overestimate the odds to get more profit.
To calculate the probability that a certain event will happen, you need to divide one by the odds that the bookmaker has assigned to that event. Probability (%) = 1/Off.
Here is an example. Suppose the bookmaker gives odds 2.05 to win the first team in a soccer match (K1), 3.8 to win the second team (K2) and 3.6 to draw. Using the above formula we calculate that K1 will win with a 49% probability, and K2 with a 26% chance. The probability of an even score is 28%. Having added up these figures, we get 103%, though it should be 100%, as there can be no fourth outcome of the meeting. The extra 3% is the margin, or the profit of the bookmaker’s office.
Margin percentage depends on several factors. For example, the margin at different bookmakers can vary between 1-10%. Also takes into account the popularity of the event – during the World Cup, the margin at some bookmakers can be below 1%.
Mathematics in soccer betting
Continuing the topic of soccer, we will look at the impact of mathematics on the success of betting on this sport. As already noted, the actual probability that a certain event will happen may be different from what we are offered by bookmakers, i.e., their odds. It is important to consider when choosing an event on which to bet. Therefore, it is necessary to be able to estimate the probabilities of events independently, making an accurate and detailed analysis.
Here is another example. Bookmaker odds for the Spanish La Liga soccer teams Leganes and Betis are 1.65 to win, 6.3 to win and 3.8 to draw. After analyzing all the factors and looking at the results of previous meetings between these teams, we conclude that the probability of winning for Leganes is 45%, and for Betis – 30%, a draw – 25%. Now we need to calculate the value of each bet:
- Laganes win: 1.65×0.45-1=-0.2575;
- Betis win: 6.3х0.3-1=0,89;
- Draw: 3.8×0.25-1=-0.05.
From this calculation we can see that the odds for a Betis victory by the bookmaker were overestimated, and therefore the value of this bet is high. Thus, betting on such events, of course, you will lose more often, but due to the high valuation, more rare cases of victories will compensate for losses.
Mathematics in betting on soccer is also needed in order to wisely manage your money allocated for betting. Even the most experienced players in bookmakers who use effective strategies can not be immune from the fact that their bets will not play. Because of the presence of variance – a deviation from the expected result, it is necessary to have a financial cushion. It will allow you to wait out a series of failures.
How to calculate the size of the bank, which the bettor must have to play safely?
To do so, several factors need to be taken into consideration: the size of the bets, the system used, the odds, the type of bets, etc. For example, when betting on winning one event, and using a fixed amount of betting for this purpose, it is necessary to have a sum that allows you to make at least 20 such bets. Or, in other words, you need to bet no more than 5% of your bank.
Mathematics in soccer betting helps to calculate the probability that a certain event will happen based on your own analysis. For this purpose, the Monte Carlo method is often used, the meaning of which is to get a lot of results based on the data obtained.
For example, in the soccer World Cup, there are 3 national teams that are fighting for first place. To use the Monte Carlo method, you must analyze as much raw data as possible: the teams’ level of play, their lineups, motivation, the skill of the individual players, etc. Let’s assume that the level of play of the national teams, can be expressed by numbers: 1, 2, 3. In other words, the first team plays at the highest level, and the third team is not as strong. In the same way, all the other factors are evaluated, then they are generated, and from this data we find out the real chances of each national team winning.