Patterns And Using Them To Win

It doesn’t matter if you’re building a betting system, form reading, using trainers or some other approach. When you are looking for your betting selections you are doing one thing…

…looking for patterns.

You’re looking for patterns in historical data to estimate what is likely to happen in future data.

The better you are at separating the relevant patterns from those that aren’t then the better your predictions are going to be.

I want to talk about an approach to using patterns that you may want to investigate.

I’m going to tell you upfront that this post is designed to get you thinking about how you can use this patterning technique.

If you want to implement it then you’ll have to do some research to determine the relevant patterns for the racing you’re interested in.

But those who do will be rewarded well.

I’ve been using this approach for years to build new strategies and it’s just as effective today as it’s ever been.

Most punters who form read will go into a horse’s form to look for information that is specific to that runner.

Information that may indicate that specific runner will perform well in today’s race.

That’s all well and good, and can be very effective.

But what happens if we turn this on its head and look for more general information instead?

When we bet we need to make profits in the long-term. We are looking for value in the odds in the long-term.

What we’re doing is not looking to get it right on this race or every race. But to get it right on average more often than we get it wrong. In other words to bet on horses that on average offer value even though we may sometimes bet on individual horses that aren’t offering us value.

So why shouldn’t we be looking at the horses in a more general approach as well.

Rather than saying what has this horse done that tells us it can perform well, why don’t we say…

What are the most common traits of horses that win these types of races.

If we know what the most common traits of horses that win these types of races are, then we should be able to remove over half the runners in a race almost instantly.

This may sound simple, but it’s incredibly powerful.

And I’m going to take you through the steps to doing it right now.

  1. Finding the common traits

You need to start by investigating the common traits of the strongest runners in the race conditions you’re focusing on.

These race conditions should be ultra specific and very niche to make this process as effective as possible. However make sure that you don’t go so specific there are only a few hundred races.

In order to find the common traits don’t focus just on the winners. Also take into account the horses who came within one or two lengths of the winner, the strong performers.

You can do this by hand, but it’s easier to get a file of all the horses with a complete range of factors from your favourite ratings software or system builder.

Once you have this file you can then split it into two files, one contains the strong runners and the other contains all the other runners. Let’s call the other file the weak runners.

Now you need to find the factors that are common amongst the strong runners.

If one of your factors is Won Over Jumps In The Last 90 Days and you do a quick search on your strong runners and discover that 75% of them have at least 1 in this field then…

You have your first common trait!

But before you can put it down as a confirmed trait we need to make sure that the majority of the horses that weren’t strong runners don’t also have it as a trait.

Go to your weak runners file and look at the same information. You’re looking for there to be significantly less horses here with this trait.

If 75% of these horses also have the same trait then it isn’t common just for the strong runners.

However, if only 15% of these horses have the same trait we can conclude it is a common trait amongst the strong runners.

There will always be some weak runners that have your trait, what you should be looking for is the biggest gap possible.

2.Finding horses with common traits

Once you’ve found common traits for the strong runners in your race conditions. You then need to find the horses that have these common traits in one of the races.

Find a race that matches your race conditions and apply each common trait to all the horses one at a time. Any horses that doesn’t have a common trait remove from your list.

When you have gone through all the common traits you should have less than half the field left.

If you have more than half the field then you can safely consider this race is going to be very competitive. My recommendation would be to move onto another one in this case.

However it’s far more likely that you will just have a few runners left at the end of the race.

These are the horses that can be considered to be the best in the race and the most likely to win.

I then compare these horses with each other to determine which ones are likely to be the strongest before deciding on how to bet. Often I will be betting on all of these horses if they all look to have a chance at contending.

99% of the readers of this blog post won’t put this process into action.

But I can assure you that this approach works and will help you narrow down your fields almost instantly.

It has the added benefit that the research required to find the common traits can be done in the evenings and weekends, and once it’s done then it’s done. You don’t have to do it every morning when you find your selections.

If you do choose to implement this strategy then you’re not going to be disappointed. It’s one I use every day.

Michael Wilding

Michael started the Race Advisor in 2009 to help bettors become long-term profitable. After writing hundreds of articles I started to build software that contained my personal ratings. The Race Advisor has more factors for UK horse racing than any other site, and we pride ourselves on creating tools and strategies that are unique, and allow you to make a long-term profit without the need for tipsters. You can also check out my personal blog or my personal Instagram account.


  1. I like this approach. Probably because it is basically what an Bayesian system does, but manually.

    I have found it surprising how relatively low number of reference races produces good results, in my experience few hundred is already a good set of data. Naturally more the better. I filter by code, distance, going and winners purse. With that approach only the classiest races get low number of reference races.

    1. Thanks for the info on how you filter Panu 🙂 The smaller dataset required makes this a much faster approach to build strategies on than other more conventional approaches.

  2. This seems similiar to the Race Profiles published by Peter May. His website at is worth a visit.
    I’m considering using different profiles to calculate an overall percentage for a horse, which I can convert to odds, to see if value is on offer or not. I could then consider backing (if over valued) or laying (if under valued).
    Thanks again for a excellent article.

Back to top button