The Martingale System
The Martingale system is a popular betting system, which is usually applied to roulette but can also be successfully applied to any game which offers a probability payout which is approximately 50/50 such as the outcome of a coin toss or the pass line in craps.
The system is one of the simplest betting strategies in that the gambler doubles his stake after every loss, so with the first winning bet he or she will win back the sum of their losses and make a small profit. For example the player first bets $2 and loses, then $4 then $8 and then wins on the next bet of $16, he or she will collect $32 which covers their losses of $30 and will have made $2 profit.
Whilst mathematically, the system is relatively sound, it does has several disadvantages when applied to real life play. The most obvious one is that with the stake doubling each time, then the player needs to have a reasonably big bank roll in order to cover the stakes. It is not impossible for 10 losing bets in a row to come up and if the player started with a $5 stake, then the 10th bet would be $2560 which is beyond the scope and limit of most players.
Perhaps the main reason why the Martingale does not work in practice however are the table limits which are in place in almost every casino. Even if you were to find a casino who would let you place unlimited bets, eventually you would find that the odds approached house edge anyhow.
An experiment was carried out comparing the Martingale system with flat betting and the results showed there was very little difference in the two. However the Martingale system requires a large bankroll and high table limits.
Many so called “betting systems” advertised on the internet are little more than a trumped up version of the Martingale system. Whilst on paper some of these systems do look appealing, in actual real world betting, they are pretty useless. There has never been a betting system which can prove consistent profit s over one billion hands which is a relevant number of hands for true statistical analysis.
