Horse Racing Forum - PaceAdvantage.Com - Horse Racing Message Board

Go Back   Horse Racing Forum - PaceAdvantage.Com - Horse Racing Message Board > Thoroughbred Horse Racing Discussion > General Handicapping Discussion


Reply
 
Thread Tools Rate Thread
Old 08-29-2008, 01:32 PM   #1
podonne
Eliminator
 
Join Date: Dec 2005
Location: Chicago, IL
Posts: 332
'Significant' Impact Value

For those of you who use impact value analysis, is there a certain level that you would consider 'significant' enough to use in a system.

I understand IVs to mean that 1.0 shows that the value has no impact, i.e. the distribution if winners in the sample roughly equals the distribution of runners. So I wonder how far above or below 1.0 the impact value would have to go to show a significant effect.

Or, if anyone is reluctant to go on record with an exact figure, a method for determining it would be appreciated. I don't think the standard statistical methods are applicable.
__________________
Whenever I read something I think about horse racing... Is that an addiction?
podonne is offline   Reply With Quote Reply
Old 08-29-2008, 02:02 PM   #2
Overlay
 
Overlay's Avatar
 
Join Date: Mar 2003
Location: Oklahoma City, Oklahoma
Posts: 7,700
Quirin detailed the procedures he used for determining a statistically significant deviation from the number of expected winners (either positive or negative) in Appendix A (pages 293-300) of Winning at the Races. I believe that the standard he used was any value that fell above 2.5 (for positive factors) or below -2.5 (for negative factors) for the equation:

(Actual Number of Winners (NW) - Expected Number of Winners (EW)) divided by the square root of (EW (1 - EW/Number of Horses (NH)).

I once asked Mike Nunamaker whether he had applied similar tests to the findings that he came up with in Modern Impact Values. He said that he had not, but that the large sample size upon which his findings were based performed the same function and provided the same assurance as the statistical testing that Quirin conducted on his smaller sample sizes.

I'm not sure that you can draw a hard-and-fast correlation between the results of those tests, and any particular level of impact value. I would say that the tests are the determinative factor. A particular handicapping variable may have a relatively high or low impact value, yet still not fall outside of that -2.5 to +2.5 spread.

Last edited by Overlay; 08-29-2008 at 02:06 PM.
Overlay is offline   Reply With Quote Reply
Old 08-30-2008, 02:06 PM   #3
robert99
Guest
 
Posts: n/a
The application issue may be that you are likely to be using multiple IVs for horses in any one race. The errors of taking say the cube root of three IVs multiplied together are more significant than any error for one IV but very difficult to quantify race by race.
If you are using multiple IVs, then using any not greater than say 1.20 (or 0.8 on negative side) do not add too much when you then take the roots of the multiples.
  Reply With Quote Reply
Old 08-30-2008, 04:22 PM   #4
Overlay
 
Overlay's Avatar
 
Join Date: Mar 2003
Location: Oklahoma City, Oklahoma
Posts: 7,700
Quote:
Originally Posted by podonne
For those of you who use impact value analysis, is there a certain level that you would consider 'significant' enough to use in a system.

I understand IVs to mean that 1.0 shows that the value has no impact, i.e. the distribution if winners in the sample roughly equals the distribution of runners. So I wonder how far above or below 1.0 the impact value would have to go to show a significant effect.

Or, if anyone is reluctant to go on record with an exact figure, a method for determining it would be appreciated. I don't think the standard statistical methods are applicable.
To expand on my previous comment, the objectives that I try to achieve in selecting and using impact values are:

(1) to the greatest extent possible, choosing factors that qualify as independent variables/significant values (if they are single-point factors); or that have independent/significant values at the top and (preferably)/or bottom of their impact-value ranges, and that have a smooth progression of impact values from top to bottom (if they are a ranking-type factor);

(2) avoiding redundancy of variables within the major handicapping categories (speed, pace, condition, class, etc), or dependent relationships among the categories, that would distort the accuracy of blending them together;

(3) if deciding between two ranking factors that measure the same handicapping element, preferring the one with the greatest range or spread from top to bottom; and

(4) when dealing with single-point factors, concentrating on significantly positive variables rather than significantly negative ones, since the positive variables have demonstrated their ability to favorably influence the horse's winning chances, regardless of what negative aspects the horse may have contained in its record.
Overlay is offline   Reply With Quote Reply
Old 08-31-2008, 03:24 AM   #5
ranchwest
Registered User
 
Join Date: Oct 2001
Location: near Lone Star Park
Posts: 3,908
I'd rather know 1,000 positive indicators and have a general notion of how strong each was than to have 3 positive indicators that I knew to be exactly a very strong indicator but with no knowledge of the stratification of those indicators.

Many people try to look at data in an arbitrarily exact way. Most data is very stratified. Do you look at the totals or do you break it out by each combination of field size, number of horses in the race matching the criteria, type of race, age of the horses, distance, surface, track or circuit (including the quality of racing there), etc., etc., etc.

What about negatives? What is a "showstopper"? What is the relationship between showstoppers and positive factors?

What about combinations of positive factors? Are there ever combinations of positive factors that are negative?

The truth of the matter is that computers aren't really telling us much when we examine isolated factors such as horses carrying over 114 pounds. Many people who do not use computers assume that computers are incapable of making determinations beyond such a simple level. Generally, computer handicapping is probably still in its infancy, but has already come a long way from 20 years ago.
__________________
Ranch West
Equine Performance Analyst
ranchwest is offline   Reply With Quote Reply
Reply




Thread Tools
Rate This Thread
Rate This Thread:

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off

Forum Jump

» Advertisement
» Current Polls
How do you prefer your Coffee !?
Cream and Sugar - 28.57%
30 Votes
Cream only - 20.00%
21 Votes
Black - 41.90%
44 Votes
Decaf - 9.52%
10 Votes
Espresso - 12.38%
13 Votes
Starbucks etc... - 9.52%
10 Votes
Other - 23.81%
25 Votes
Total Votes: 105
This poll is closed.
Powered by vBadvanced CMPS v3.2.3

All times are GMT -4. The time now is 09:08 PM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2020, vBulletin Solutions, Inc.
Copyright 1999 - 2020 -- PaceAdvantage.Com -- All Rights Reserved -- Best Viewed in a modern browser @ 1280x720 Resolution Or Higher
We are a participant in the Amazon Services LLC Associates Program, an affiliate advertising program
designed to provide a means for us to earn fees by linking to Amazon.com and affiliated sites.