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Old 08-21-2007, 08:55 AM   #31
Pell Mell
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Quote:
Originally Posted by 098poi
From "The Handicappers Condition Book" by James Quinn pg 18, "The probability of winning equals simply the percentage of winners having a characteristic divided by the percentage of starters having the characteristic."

So in your case (assuming each race you are talking about only has 1 horse with your factor) with 50 races with 8 horses in the field per race (my guess) that gives you 50 horses with your factor and 400 horses total. So 50 divided by 400 equals 12.5% of starters have that factor. If your horse wins 25% of the time then 25 divided by 12.5 equals 2 or an Impact Value of 2 which is 100% more than would be expected. ( A value of 1 would mean that the factor is not significant either way. If you had Aunt Millie randomly guess the winner by picking just names she liked she would probably have been correct between 12 and 13% of the time. A factor can produce a negative expectation also for example (from the book) 1st time starters over all lose more than would be expected from their percentage of starters.
You sound like you are on to something good but check the link to Gordon Pine's article, it goes more in depth and confuses me a bit!!!
Not quite right, I'm saying that out of the 50 races I only find an average of 2 plays.
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Old 08-21-2007, 10:39 AM   #32
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Frsh fillies/cold colts

Quote:
Originally Posted by john del riccio
I'd be interested in hearing more about the "freshened fillies" filter. I think that when a f or m goes sour, they just don't seem to get back without a break and i noticed this from the owners side first but then picked up on it from the handicapping side as well. do you see any difference with respect to age ?

john
The only age consideration involves very young two year olds. Horses raced in April or May of their 2yo year may have been breezed before their knees closed. So if one wins at first asking and then is given time off I pass.
The others are most productive in dirt races up to seven furlongs. I like at least four weeks off, some display of talent earlier in their career, and decent workouts depending on the individual trainer. Blinkers on or off is a positive.
Restricted races are the most productive but it works all the way up to stakes races. The longshot cited had three months off following a couple of races where she was assigned zero beyers. The race she won following the layoff was nw2 claiming $10k at Fairgrounds. Her maiden win was in a $20k race in New York so she passed the talent question. She was working well in the morning (note to discount if the works are limited to three furlongs) and a low profile jockey broke her on top and she wired the field.
One problem that arises is that there can be more than one in a race that has been freshened.
For confirmation of this angle review the pp's for fillies in sprint races in the form and look for that line that shows time off. You'll see some nice prices or otherwise solid efforts.
Colts usually need a race. The exception are the male offspring of Meadowlake and Phone Trick who will run fresh. Might be a conformational thing as these are frequently the boxy typed who pound away at their knees.
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Old 08-21-2007, 10:51 AM   #33
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Quote:
Originally Posted by Pell Mell
Not quite right, I'm saying that out of the 50 races I only find an average of 2 plays.
Well then,if 098poi has the formula correct,you have an Impact Value of 5000.
TTRAC
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Old 08-21-2007, 01:38 PM   #34
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Impact value is the pecentage of winners with the factor -- the percentage of ALL winners in a sample with the factor divided by the percentage of all the starters with the factor.

So, let's say you have a sample of 1000 races and you find 50 plays. Let's say you have 13 winners out of the 50. And let's say the total number of starters in the 1000 races is 8000 horses.

IV = ( %winners with factor ) / ( % starters with factor )
= (13/1000) / (50/8000)
= 0.013 / 0.00625
= 2.08

Odds don't come into it.
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Old 08-21-2007, 06:32 PM   #35
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Quote:
Originally Posted by Pell Mell
I use the Bris custom card feature and scan an average of 50 or so races per day. I look for a particular factor which takes about 10 seconds per race. Out of 50 races which would be an average of 400 or so horses I may find 2 horses with said factor. Many days there are none and some days there are 4 or 5 so I don't know the actual average but I'm guessing at 2 per day. At the end of a month there may be 40-60 plays and these average 25% or more winners at an average mutual of 10/1. So what would be the IV of my angle?
So, out of 400 horses per day, 2 have the factor you're referring to, which would be 1/2 of 1% (0.5%) of all the horses. 25% of the horses with the factor win, which means one winner every two days (on average) out of the 100 races screened over those two days. So, 1% of the winners are coming from 0.5% of the horses, which would be an impact value of 1.0/.5, or 2.00, meaning that horses with the factor are winning two times their "fair share" of the races.

Last edited by Overlay; 08-21-2007 at 06:35 PM.
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Old 08-21-2007, 06:42 PM   #36
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Quote:
Originally Posted by Pell Mell
Not quite right, I'm saying that out of the 50 races I only find an average of 2 plays.
Your initial post said at the end of the month you have 40-60 plays. That is where I got the 50 from. You only look at your plays. What percentage would win as their "fair share" relative to those that actually won. Forget about how many races aren't plays. It doesnt matter if only 1 in 500 races has a play, after 50 plays you should get the results I said.
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Old 08-21-2007, 07:05 PM   #37
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I see said the blind man. Thanks
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Old 08-21-2007, 08:08 PM   #38
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GameTheory,

Quote:
IV = ( %winners with factor ) / ( % starters with factor )
IMHO, a better formula is:

Wins / ExpectedWins

where:
Wins=actual wins

ExpectedWins= the sum of 1/field for each horse in the sample.


Dave
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Old 01-28-2018, 11:53 PM   #39
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Going for a record here, bumping a thread over ten years since last post.

This was an interesting read. I wonder if peopleís thinking has changed at all in the intervening time period.

A guy called Roger Biggs (not the train robber!) here in Australia was/is big into the IVís, wrote a few self published books about them. Personally, I think they have limitations. I think for your standard form factors like last start finish pos etc the market already has it all accounted for.
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Old 01-31-2018, 07:30 PM   #40
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Quote:
Originally Posted by Gamblor View Post
Going for a record here, bumping a thread over ten years since last post.

This was an interesting read. I wonder if peopleís thinking has changed at all in the intervening time period.

A guy called Roger Biggs (not the train robber!) here in Australia was/is big into the IVís, wrote a few self published books about them. Personally, I think they have limitations. I think for your standard form factors like last start finish pos etc the market already has it all accounted for.
As you say, the market may very well have those factors accounted for from the standpoint of not overlooking them or omitting them, but (to me) the usefulness of the IV's is that they allow you to determine not just if the factors have been taken into account, but also whether, in the process of being taken into account, they have been undervalued or overvalued (especially in combination) by the public.
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Old 01-31-2018, 10:45 PM   #41
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Originally Posted by Tom View Post
I always look for subsets - say you have a general stat about last out winners. Within, that is likely a subset of those who are profitable and another that is not. (There are).
Good bump.

That's the direction I am heading.

I try to find an attribute, rating etc...that's close to break even as a group.

Then from within that group, I look for subset I can weed out or uprade. The remainder will do better.
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Old 01-31-2018, 11:28 PM   #42
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When I was using a data base system, one thing I always tracked was how well these factors were doing as a whole group, how the were doing in the last 4 weeks. When the recent performance went below how a factor did as a whole, I would start to give that factor a higher rating. If the recent performance was higher than the factor did as a whole, I would lower that factors rating.

As an example, I looked at wire to wire wins on turf. I will just use round numbers here. Over a 5 yr period your data base tells you that 30% of all turf sprints are won wire to wire. But in the last 4 weeks they have been winning 25% of the turf sprints. Time to use this a little heavier, because it will go back up to the 30%.
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Old 02-01-2018, 04:50 PM   #43
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Originally Posted by jay68802 View Post
When I was using a data base system, one thing I always tracked was how well these factors were doing as a whole group, how the were doing in the last 4 weeks. When the recent performance went below how a factor did as a whole, I would start to give that factor a higher rating. If the recent performance was higher than the factor did as a whole, I would lower that factors rating.

As an example, I looked at wire to wire wins on turf. I will just use round numbers here. Over a 5 yr period your data base tells you that 30% of all turf sprints are won wire to wire. But in the last 4 weeks they have been winning 25% of the turf sprints. Time to use this a little heavier, because it will go back up to the 30%.
On that logic I assume youíre buying up bitcoin right now.
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Old 02-01-2018, 04:56 PM   #44
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Not bitcoin, but real estate in Sydney, NE.
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Old 02-02-2018, 11:17 PM   #45
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The way you look at layoffs, and value them, must have changed dramatically since this thread was started all those years ago. Layoffs were always negative. They definitely must be viewed differently today.
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