The Power Of Ranking Ratings

What I want to share with you today is something from one of the best analytical racing minds in the US. He looks at racing in a completely unique way and his ideas have been significant in getting me to where I am with my betting today.

The chances are that, being focused on UK racing, you’ve not heard of him before. And his name is Dave Schwartz. You can check out his website here.

Now while I recommend that everyone read Dave’s work, it is developed for US racing and will need to be adjusted to work in the UK and IRE. What we want to take away are the concepts and ideas to put them to work for us in our style of racing.

The technique that you’re about to learn Dave calls Reynold Ranking. It’s a superb approach to using the ranks of horses for different factors to find the strongest runners in the field.

And yet, whilst being so powerful, it’s incredibly quick and easy to use!

First of all let me explain where this method came from…

Dave was digging into his research, as he is often found doing, and during one particular session he came across an English physicist from the 19th Century called Osborne Reynolds.

Osborne was a prominent engineer in the field of fluid dynamics. Don’t worry, you won’t need to know anything about this to use the approach.

It was 1883 when Osborne invented his number… the Reynolds Number. This number has a lot of uses, such as allowing ship designers to use small scale models to determine how they will work on the open sea.

The way the Reynolds Number works is by multiplying together the diameters of different pipes. with a number of other factors. He managed to show that when the result of these numbers reaches a “magic number” the flow of water becomes erratic.

Okay, so you’re probably wondering how this can help you with horse racing.

Well… while reading this Dave’s brain went off in a different direction with the though…

“If it’s possible to use this approach to determine when the flow of water becomes erratic, then surely we can use it to determine which horses performances are likely to be erratic!”

Let’s assume you’re trying to build a model to find selections on Handicap Chase races at Cork.

You are using four factors to try and find out what types of horses win these races. For this example I’m going to use the RnkPFP, RnkACSPCL, RnkCst10 and RnkSHorPro factors from the Racing Dossier.

The first thing we do is pull out a list of these factors for winners in at Cork in Handicap Chases with 15 runners or less. I’ve used 2013 data to do this.

Below is a sample of the data that we get:

What does this tell is?

Well, at first glance not very much because there is no single factor that can be used to reduce the number of runners.

But this is where Dave saw the opportunity.

He created Reynolds Ranks by combining every factor with the other factor, simply multiplying them together. So you would do:

RnkPFP x RnkACSPCL

RnkPFP x RnkCst10

RnkPFP x RnkSHorPro

RnkACSPCL x RnkCst10

RnkACSPCL x RnkSHorPro

RnkCst10 x RnkSHorPro

Once we’ve done that for all the winners we can look at the worst (highest) score that a winning horse has achieved.

Now we start to have a base line to look for potential selections in a race!

If we take a race from the Racing Dossier with these factors:

We can then multiply the factors together as we did above, but we now have a baseline for the worst winners in each factor.

The above table shows the result for the horses in this race for each factor multiplied together.

But now we can use our “worst winner” scores to remove any horse with a RnkPFP x RnkACSPCL of more than 110 or a RnkPFP x RnkCst10 of more than 80 etc…

That reduces the field of fifteen runners to just:

We have reduced the field by half almost instantly to find only those runners who have the profiles we know are the strongest for horses that win these types of races.

I have then added a new column called Sum, which is the sum of the scores, and the horse with the lowest score is the strongest. Which would be Gentlemen Duke.

Very quick, very simple and… very powerful.

But imagine if we had added together the totals for the winning horses when we were profiling these race conditions?

Then you would know that from the previous winners, the worst score for a single horse was 315 with nearly 75% of the winners having a score of under 200.

That means we can remove Back To Balloo and Dazzling Susie. We can also consider Nearest The Pin not to be too strong a threat.

You are now left with five possible contenders in this race with the strongest being Gentlemen Duke, Fosters Cross and Saint Gervais.

I used to use this approach on it’s own to make regular profits. Like anything, it will require a bit of practice. But once you have it mastered you will be able to profile and rank races using the Reynolds Ranking method in a matter of minutes!