Explanation of Preference Scaling

Can anyone assist me with an explanation of the preference scaling for the neural ratings?

There used to be an explanation on the old website but I cannot seem to locate it here.

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Under the Neural s there is an explanation button that should have the following...

Neural factor Analysis

Racing and Sports announces a revolutionary, alternative race form assessment methodology called NEURAL FACTOR ANALYSIS.

Artificial Neural networks have been around since the 1950's, but only more recently have they been applied to solve an ever increasing number of complex real world problems dealing with such areas as medical research, law enforcement, mechanical system diagnostics and the environment.

With this as a background, Racing and Sports set about applying the neural networking to race form analysis.

Neural networking, without going deeply into it, is a tool essentially used to analyse information in a structured way by collecting numerous mathematical models to emulate actual observances.

The advantage of Neural Networks is their ability to even out distortions in input data. They are also capable of "learning" the process to which they are applied.

Neural Networks are generally good for solving problems which tend to be too complex for traditional analysis tools such as clustering algorithms, multivariate statistics, fuzzy logic etc.

In many respects, Neural Networks are very well suited to problems that humans are able to solve but other more rigid, traditional methods are not.

That's why we decided to investigate them for an application to find solutions in race form analysis.

Racing and Sports has investigated the various types of Neural Networks which would best suit this purpose and again without getting too technical opted for a variation of the supervised algorithm.

In other words, the Racing and Sports modified neural network takes the input data and supervises it through the network system to produce a set of Neural Weightings as an output.

These Neural Weightings assigned to each horse are an indication of the best (higher) to worst (lower) based on the factor input values decided upon by the user.

The input information is processed through the Neural Network by a mathematically derived "engine" which drives the system. This engine is composed by a large number of interconnected processing elements which receive and process the input algorithms.

As you know, the analysis of race form is a very complex task. A single weight rating , a la Don Scott is not the only way to solve the pre race riddle.

Traditional weight ratings are but one of these factors and instead of adding a kilo here and taking one off there for other inputs like barrier, consistency etc, the Neural Networks offer an alternative approach to form analysis by combining all the factors mathematically.

In the development of the "neural engine" the Racing and Sports computers have run at least 2.5 million simulations based around the various input algorithms.

It is these simulations the "engine" draws upon to generate the output weightings of the network.

With so much racing, the time now required by conventional form techniques would drive one insane, if every day was devoted to "doing the form" old style.

This is where the power of computers, technology and mathematics come into play.

Racing and Sports has a big investment in this "state of the art" Neural Factor Analysis and is certain that all our development in fine tuning has now delivered a form tool like no other.

At this juncture, Racing and Sports has incorporated just 12 input form factors into the Neural Network.

In our trialing period, we have been astounded by the consistency these factors have delivered.

The Neural Weightings derived have shown an excellent record in identifying the main chances.

Of course there is no "magic bullet" in form assessment. At the end of the day we are dealing with 500kg animals with emotions and feelings like the rest of us.

They do not, and never will, always conform to a mathematical formula or a single numerical figure, no matter what.

However, as a guide as to identifying who the main group of horses are likely to be, in the outcome of a race based on the input data, we believe Neural Factor Analysis will give an excellent starting point.

It will provide a "new edge" in form analysis and offer a robust framework within which to assess each runner.

Early evidence suggests this is an alternative way of producing consistent results from your form assessment.

The neural factor analysis is NOT a system.

It takes the traditional class/weight correlation algorithm, adds a new race time algorithm and then integrates the other peripheral elements like jockey, trainer, course, distance, barrier to give a final list of weightings for the main chances.

This final listing depends of course on the users preference of the algorithms (Preference Scale ) and should serve as a very helpful guide to punters desiring to "fine" a field down to the main chances for closer examination.

Explanation of Inputs for Neural Analysis

CP - Career performance assessment based on weight/class algorithms
CF - Current form measured by class/weight algorithms
TIM - Revolutionary time assessment (adjusted algorithm)
JA - Jockey ability algorithm
TA - Trainer ability algorithm
JT - Jockey/trainer combination algorithm
WT - Wet track performance algorithm
Crs - Course suitability algorithm
D - Distance suitability algorithm
$ - Prizemoney earned algorithm
BP - Barrier position (course & distance) algorithm
DLR - days since last run algorithm

The user sets the level of importance from the Preference Scale (1 to 5 or No) for each algorithm and the output weightings are listed within seconds. On the scale 1 is least impact, 5 is most significant.

The Neural factor analysis will quickly identify for you just who are the main chances in each race, the highest to the lowest based on the factor weightings.

Our computers are currently "grinding" away doing further simulations to identify other algorithms which can be included.

I invite you to come with us on this new era of highly sophisticated alternative race analysis.

I am certain our younger generation users of the site will find Neurals a welcome alternative to having to study traditional form guides and the like.

Good Punting

How ya doin?
Just a query about the Jockey Ability Algo.
I noticed at Mornington Sunday that Ben Melham (City class A grade rider) and Stephen Brown Jnr (Apprentice C grade rider) are equal @ 17 points?
Can you please explain this?


How's that for a reply ?

I am curious about the last line though, that younger punters will welcome an algorithm generated rating as an alternative to doing the form. Why younger punters ? Are they more likely to 'trust' the machine ?

I used to play with the neurals and one thing that struck me was that they returned pretty much the same sort of return that you might expect from a competent, form studying punter. (i.e. they lost about the same amount as most form studying punters) which did make me wonder why I should do the form given that the bottom line was much the same ?

Some years ago I was tipping on another forum and having a good run. I started to get private messages from punters offering to pay me for exclusive access to my tips ! For that they received the standard Tonto 'don't be a mug' reply.

I was discussing this with other tipsters on the side when one dodgy customer told me of how much money he was making by selling 'his' tips on e-Bay (which I don't believe you are allowed to do any more). He had put up a dead simple message on eBay saying all the stuff that dodgy tip sellers usually say and advertising some spectacular results. He was offering monthly, 3, 6 and 12 monthly subscriptions to his daily tipping service and he was fully subscribed.

How did he do it ? How did he manage to provide daily tips ? He was using the neurals ! He wasn't doing a shred of form study. He was simply copying the neural selections and flogging them to mugs. And he was on a winner. The tips didn't need to win. He already had the mugs money. He just kept an email list of his clients and posted them the neural selections each morning.

Typically though he was a loser. He disappeared after six weeks leaving his subscribers in the lurch. The number of dills that had forwarded him cash for a 12 monthly subscription was ridiculous. He took the money and run.

That's the brilliant thing about the neurals. It's not that they find anymore winners than you might find yourself. It's that they are free.

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