Using betting systems is probably the most popular form of finding selections. Also, amongst horse racing fans, the actual building of the systems is very popular.
The only problem is that most betting systems fail to make the profits that they’ve promised to deliver.
And the primary reason for this is… backfitting.
Well, that’s the name that most people use. If we were going to be completely technically perfect every betting system is backfitted by definition.
The reason for systems failing is overfitting.
So let’s start by determining exactly what overfitting is.
The Wikipedia definition is:
In statistics and machine learning, overfitting occurs when a statistical model describes random error or noise instead of the underlying relationship. Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations.
I would say that’s a pretty good definition, but let’s change it in relation to betting:
In betting, overfitting occurs when a betting system only finds profitable selections based on the sample of data used to build the system. Overfitting generally occurs when the betting system has rules created which are specific to the data set being used and not generic enough when used on unseen data.
In normal English, we are overfitting when we have rules in our betting systems that only work on the data we are building the system on. And this most often occurs when we create rules that make no logical sense regarding the conditions of the races and the runners in them or by creating too many rules.
You see fewer rules means that you are less likely to be overfitting.
The problem is that fewer rules also means you are less likely to be able to make a profit.
In order to make a profit without overfitting, we need to find the balance between rule creation and logic.
And there is one way that we can do this when we build betting systems without much difficulty.
It will increase the amount of time it takes to build the betting systems, but it also gives your systems a far greater chance of being successful when you start placing your money on the selections.
Which is what we want.
The process that I’m about to describe is a simplified version of bootstrapping.
This is a statistical process which ultimately refers to taking random samples of data throughout the development of a statistical model.
And that’s exactly what we want to do when we build betting systems.
Most betting system builders have been designed in such a way that you choose a date range and then you build your system on it.
And that’s the problem.
To be confident that your betting systems aren’t being backfitted, here’s what you want to do…
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All the best,
The Race Advisor
