I decided to build up a numerical model to simulate and determine the risk of losing all the money (and have an idea on some other points as you will see below) when following a fixed stake policy. I have to confess, however, that my secret desire was (is!?) to find a mathematical reason to support a progressive staking strategy (to no success up to now, however).

Basis of the work were:

1. Flat stakes during the simulation, meaning that the number of units staked per bet are kept constant for each simulation;

2. Each simulation consisted of 10,000 runs of a set of 2,000 bets each run (Why 2,000? Because I assumed a serious punter should be on ca. 5-7 bets per day, as an average, making up app. 2,000 bets a year);

    

3. Simulations were done considering two variables:

1. stake size (1%,2%,3%,4%,5%,7%,10%,15% and 20% of the initial bank and kept constant unitwise for the simulation);

2. strike rate (50% thru 60% with a 1% interval) in order to check how findings vary with the punter ability to predict correct results;

3. Note: I used a constant odd of 1.90. I used this because this is an odd that can be achieved in almost any football match (asian handicap), or basketball, american football (spread betting),etc. Please note that the model can also use different odds (say e.g. 30% of 1.50, 40% of 1.70 and 30% of 1.90 odds) if we deem necessary. Results and conclusions being presented today, however, are applicable for 1.90 odds.

Calculated outcomes of the model for each simulation (set of 10,000 runs of 2,000 bets each run) are:

1. Probability of losing all the money sometime during the 2,000 bets (season);

2. Percentage of time when the punter current bank is lower than the maximum bank already achieved in the past bets ( this is an wonderful insight to give us some soul comfort when we realize that on one given day, our bank is, say, 88% of the maximum bank we had achieved in the past, during the same season). For your information, I can guarantee that most of the punters should be below the maximum achieved bank more than 95% of the time (most likely even more than 95%);

3. Average estimated final bank (when not losing all the money);

4. Average estimated maximum bank (sometime during the 2,000 bets) also when not losing all the money.

Main findings are:

1. For the losing all the bank probability please check the below table;

2. Average final bank figure, does not significantly (as expected) differ from the hand-calculator easily calculated ones;

3. Small details (such a 1% higher strike rate) make a lot of difference. Therefore, it pays off to devote some (much?) time and effort to gather info, data, etc. on betting events. Each 0.1% you can increase in your strike rate is worth of it.

Now, take a look at the table below and tell me where you are (or should be).

I will be back with more on this subject soon.

Abraços.