Regression to the Mean

Often confused in the gambling fraternity with the law of averages is the theory of regression to the mean. Theory of regression to the mean suggests that if a player (gambler or team) performs significantly better or worse than normally expected, then in the future, he will return to the average expectation of that player (gambler or team). The difference is small, and is different from that of the law of averages, but the definition above can be misinterpreted easily.

It does not suggest that if a team is doing really well that the opposition should be backed because it is bound to return to average. This is the most common misunderstanding of the theory of regression to the mean. Even in the stockmarket, shares could drop from $10.00 to $2.50, and stockbrokers may believe, that because of the theory of regression to the mean, they will purchase the stock with the expectation that it will return to $10.00. This is entirely wrong because we do not know and cannot know the normal expectation of a team or a player, or the price of a share. However, the theory of regression to the mean does have some principles in gambling, and I will show you how to use it to correct any bankroll management errors you might have, as well as learning to think somewhat differently from the general public (which is what it takes to win long-term).

Many people like to talk about streaks in gambling. A winning steak is where there are several winning bets in a row. Obviously, streaks are very good, because nothing beats winning, and winning many bets in a row is even better! However, a punter will go wrong, when he decides to increase the bet size, because he believes that he is on a good wicket. Likewise, other punters might 'jump on board' and follow the betting of these winning punters, because they are on a winning streak. However, we find that those winning punters inevitably will lose a few bets. Then, people will jump off the band wagon and onto another. The person betting will have lost more than he won, because he increased his bet size, despite the fact that he probably won more bets than he lost.

Why is it, that if on a winning streak, one inevitably will lose a few bets in a row afterwards? The reason is told in the theory of the regression to the mean. There is a good chance that the only reason one is winning is due to luck and the only reason one loses a few bets is because one is unlucky. This is what happens in the gambling world. The fact is the person who thought he was on a good wicket in the middle of his winning streak must have thought that his tips were really good and that luck had no part of it, but when he lost, he probably cast it off as a turn in fortune.

If you want to be really successful in gambling, you have to look at the long term. I do not think I can stress this enough. Stock market and property investors look at long term gains, so why shouldn't we when gambling? When looking at streaks, we are looking at only five or more bets at a time, maybe even up to ten bets. If we checked a few of the stats, a long term gambler will constantly have 10 or so winning bets in a row, and also, will probably have 10 or more losing bets in a row. According to probability theory, this is to be expected.

However, it is interesting to note, that the professional gambler will try not to get too excited over a number of successive wins because he knows about the theory of regression to the mean. Due to this, he probably will not increase his bet size and fall into the trap, as would a lot of punters.

However, this doesn't mean that when you are doing well, your bets will start to turn sour. It doesn't mean that after a few wins, you are going to lose the next bet. Rather, the regression to the mean theory looks at the long term regression to the mean.

Suppose a gambler has been betting for about three years, and in each year, he has gained around 3% profit on his investment. In his fourth year, he is doing nothing different and betting the same way as previously, but instead, he made a 6% profit on his investment. This is a very large profit and no doubt he will be quite excited about such results. However, if we were to assume that his average yearly profit is 3%, then there is a good chance he just got lucky that year with a 6% profit, and perhaps in the future, we will see him returning 0% (no profit or loss), so as to average 3% overall. If, in his fifth year of gambling, he were to record a 2% loss, then there is a good chance that he will continue betting the way he is betting because he knows about the regression to the mean theory and he knows that in some years (or weeks/months) he will return better results than others but in the end, it will all turn out to be approximately his average.

However, we do not really know this average figure. We hypothesised above, that it was 3%, but it could be, in fact, 6%, and therefore, he was unlucky the first 3 years.

This theory can benefit the punter because there will always be times when it seems as though we can do no right and conversely, there will be times when it will seem that we can do no wrong! Just as long as the long-term average (whatever that might be) is on the positive, then this method will lead to being a successful professional punter. Never throw in the towel on bad running streaks and never increase the ante on winning streaks. If you know, that in the long term, your bets will be profitable, then be consistent in your betting and your bank balance will reflect your dependable methods of gambling.

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