﻿ Monte Carlo - Gambling Strategy Simulation | Simulate Betting System to get bets expected, real and generated values

# Monte Carlo

The Monte Carlo simulation method can be used here.

## 1. Description

The Monte Carlo simulation method is very useful for testing the results of the bets and for verifying if our model of analysis and estimation of the probability of winning, is a good one, according to the reality and, used in the long term, it produces profit. The method also allows us to find out if the previous results were influenced by luck and to see how the random factor can influence the future results.

We can find 100 bets of odds 2.00 and probability 60% but if of the 100 bets we win only 45, then it means that our model of analyzing and detecting the value bets is not really correct and needs to be improved.

If we have a well set up analysis model, then we can use Monte Carlo simulation to also check already decided bets. In order for the information obtained with the Monte Carlo simulation method to be as accurate as possible, it is necessary to carry out a number of simulations as large as possible on as many bets as possible, otherwise the information obtained may be influenced by luck (the random factor).

The majority of professional bettors are basing on Value Bets and many use this simulation method to test whether the bets found actually had the expected value.

In order to be able to add bets to the Monte Carlo simulation method, it is necessary to know the odds caught of the bets (the one offered by the bookmakers) and their estimated odds (the one corresponding to the calculated probability of winning). The name of the bets is optional but indicated to be able to recognize the bets.

The addition of bets is shown in the following image:

It should be stated that bets can be added to the Monte Carlo simulation method and at the Kelly and Value Bets strategies, where we have to know the odds caught and the probability of winning instead of the estimated odds, the latter being calculated automatically.

## 3. Monte Carlo verification

Monte Carlo verification contains information about:

• The expected profit which is the average of the values of the bets added to the Monte Carlo simulation method.
• The real profit obtained from establishing the results of the bets. If the result of a bet is not set in the betting list of the Monte Carlo simulation method, then its result will be considered as being annulled (N) - which is similar to an unspecified result because it is not taken into account when calculating the real profit, its added value being 0.
• The profit generated by the Monte Carlo simulations performed and which is compared with the other values.

If a consistent number of simulations is made or if the number of bets added to the Monte Carlo system is large enough, then the profit generated by the MC simulation will be approximately equal to the expected one. The value generated following MC simulation is useful when we want to see possible fluctuations, because for example, at a small number of added bets, even if their estimated (expected) value is a good one, we can have bad luck and obtain a real profit below the one expected, but in the long run, at a consistent number of bets, the situation to actually be ok. For example, if we have 20 bets added and we set at the number of simulations to make a single simulation, then we will be able to see different possible fluctuations of the real profit obtained in a single simulation, as in the real case.

The Monte Carlo verification is presented in the following image:

## 4. Betting list

The betting list contains all the bets added at the Monte Carlo simulation method and some information about them, such as: name, odds caught, estimated odds, bet value, result and date when the bet was added. Of these, the result of the bets can be modified through click on its surface.

The list of bets is shown in the following image:

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