### Regression - Going & Distance

The UK Horse Racing model is based around mathematical regressional analysis and some of the figures from the analysis seem to be very important. Two of these are the Going and the Distance regression figures.

This is an attempt to statistically identify favoured race conditions. Note that 5 runs are required before a regression figure is calculated.

There are two figures in the format:

**g/d**

The first is the going regression and the second is the distance regression.

Basically, if a horse likes the going or distance, or the Model suspects that he may like the going or distance, then the regression figure is positive. Conversely if the horse is considered to have a problem with the going or distance then the regression figure will be negative.

The figures for each horse are shown as two numbers seperated by a forward slash. The first number is the going regression and the second is the distance regression.

The numbers become interesting when they are 1.0 or greater or -1.0 or less. A large number is +3.0 upwards or -3.0 downwards and then the horse does become interesting for various reasons. We tend not to consider anything which is around the sero mark as significant.

A positive value of 1 means that on average the horses runs 1l pounds better on today's going or distance than the mean rating. In general, this calculation generally understates the true picture as there are many other factors that confuse the regression.

One good strong indicator which I know a few follow with success if there is a horse with both regression values at 1.0 or greater and the total of the pair is 4.0 or more. That, then, becomes a very strong indicator that this horse is going to travel very well.

One good indicator is if the ground is heavy and there is a strong positive going regression and even more so if one of the other columns such as Lst or WinF is showing a strong positive too. On extreme ground and distances these regression values are even more important.

Some people have noted that it may not be wise to lay a horse which has the only positive regression figures in the race.

We find that the distance regression is a much more powerful indicator than the going regression. It is always worth having a close look at horses that seem to like today's distance, particularly if the horse has been recently trying out different trips.

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