Betting probability can be explained in simple terms but if you really want to understand all the aspects of this concept you have to be willing to learn a lot of new facts. In this article we will teach you how to use the rule of multiplication in order to define the joint probability of two events. This information will help you have a better understanding of betting odds in order to be able to calculate the value of your bets more accurately.The Rule of Multiplication in Betting Probability Picture
This special rule applies in situations where we are dealing with two independent events. We consider the two events to be independent if they can occur without affecting each other’s probability. If our intention is to find the probability for both events than we need to multiply the odds with each other. For example, lets calculate the probability of seeing two heads in a row if we flip a coin twice. Given the fact that the coin is being flipped twice, both flips are happening individually so they have the same odds which are 50%. The event of seeing a head when we first flip the coin will be marked with the letter A and the event of seeing a head on the second flip will be marked with the letter B. In mathematical terms, the probability is marked with P (A and B) and its value is 0,5%x05%=0.25%. This is the probability of seeing two heads in a row if we flip a coin twice. The same formula applies when you want to see the probability for more than two independent events, no matter what their individual probabilities are.
Dependent events are the events in which the occurrence of one event affects the probability of the other events. In the betting world, dependent events are more difficult to predict. For example, lets assume that you are using a bet screening process which monitors the betting market and which has a 80% success rate at finding 5%+ value. Your monitor finds 25 bets which match your criteria. One of the 25 bets is selected for manual analysts. The bet has a 5/25=1/5=20% chances of not passing as a value after the manual analysis. The next value bet will now have a 4/24=1/6=16,675 chances of being rejected as well. The next bet now has a 5/6=83,33% chances of being a value bet. As you can see, the rule of multiplication in dependent events is generalized by conditional probability.
The general rule is used in order to find the joint probability of two events happening in a row. The mathematical formula is: P (a and B)= P (A)x P (B|A) or P (A and B)= P (B) X P (A|B). The P(B|A) is the probability of the second events happening due to the fact that the first event happened. For example, lets say that you are using the bet screening process and you are dealing with the same 25 possible bets and you want to calculate the probability of the first two bets being rejected by the manual analysis. “A” will be the event in which the first selected bet is rejected and “B” will be the event in which the second selected bet is also rejected. P (A)= 5/25 and P (B)= 4/24. The number 4 is used due to the fact that we assume that event A happened and there are only 4 bad value bets left instead of 5. Furthermore, as one bet has already been analyzed, there are only 24 bets left to consider. P (A and B) = P (A) x P (B|A) = 5/25 x 4/24 = 200/600 = 0.0333 = 3.33%. If you are dealing with more than two events the formula is slightly more complex. For example P (A and B and C) = P (A) x P (B|A) x P (C|A and B).