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11-09-2016, 02:21   #31
tryfix
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Originally Posted by Gringo180 View Post
Todays Leger winner Harbour Law has a real speedy pedigree. Surprised to see such a pedigree produce a stamina laden stayer at the highest level.
A DI of 1.29 isn't speedy, but I know what you mean re the dam a sprinter by Pivotal a sire who produces both sprinters and classic middle distance performers.

There's the highest level and the Highest Level. The tight finish of the Leger was between three nice group class colts rather than between 3 proper Gp 1 horses. The proper Gp 1 horse in the race crashed out leaving a Gp1 in name only behind.
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21-01-2017, 17:45   #32
 
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I'm dragging up an old thread.
For the past few months I've been doing a bit of database programming. The idea is to compare flat (not fences or hurdles) pedigrees to race results.

At this stage I have not done the comparison, but I have the basics on the pedigree side.
I have a program that analyses pedigrees. I can load any number of horses, start it, and come back later for the results.
I'll be tinkering with it a little, adding bits and pieces, putting in timing to find slow spots, and rewriting to speed things.

What gave me a boost was a poster asked me by PM to look at the Tattersalls February catalogue. It has 488 lots.
I could look at each lot on screen in my commercial pedigree program (TesioPower) and pick out the best imo.
Instead I decided to put in some extra effort to finish the database program.

It analysed the 488 Tattersalls lots in 44.53 seconds or approx 0.9 seconds a horse.
That was on my slow seven year old PC.
I bought a new PC in November and that runs things in 32% of the time of the old PC, so it will analyse a horse pedigree in under 0.3 of a second.
First it gathers the 126 ancestors in the first six generations (2,4,8,16,32,64), then analyses them.
Fwiw in a sales catalogue they print the first three generations (14 ancestors).

Plan
Add new features to the six generation analysis (group winners, Derby winners, group winner producer).
Compare the analysis to race performance.
Give up if no link found between pedigree and performance , or makes changes.
My next plan will be to analyse 7, 8, 9, 10, 11, 12 generations. This should be easy as I only have to increase the size of the ancestor database.
Of course if I go from 6 generations from 7 generations the data doubles.
A 12 generation analysis is much bigger (and slower) than a 6 generation, 8,190 horses v 126 horses, 65 times the size.

When running the program a byproduct is it gave some strange results for a few horses, many in the 1800s.
These are horses with incomplete pedigrees (some of these are half-bred non-thoroughbred).
I go back, fix the data if I can, and run it again.
The reason to test the program against so many pedigrees if to test it against complex pedigrees.

I am very interested in full siblings in pedigrees
(horses with same sire and dam e.g. sires Sadler's Wells and Fairy King are both by the sire Northern Dancer out of the dam Fairy Bridge).
And I look for 3/4, 7/8 siblings.
Examples of recent 3/4 siblings are:
Frankel; Highland Reel; Intello; Roderic O'Connor; Sir Isaac Newton; Teofilo, all by Galileo out of a Danehill dam.

Below is a summary decade by decade of full siblings in 6 generation pedigrees from 1800 to now.
It gives an indication that horses were much more closely inbred in the past, probably because you walked your sire to a local mare.
(full siblings A and B: one of horse A, and four of horse B is counted as five)
Horse populations in the early 1800s stayed in the same area (as did humans).
When trains were invented (1830s) you could travel your mare.
Motor transport (1890s) made travel even easier.
Now you can fly the mare or stallion anywhere.

In the table below you will see a spike in full siblings in pedigrees in the 1860s and 1870s.
My guess is brothers Stockwell (1849) ("the emperor of stallions") and Rataplan (1850) are heavily involved.
Galileo traces back in direct male line to Stockwell, as does almost everything else running today.
The low full sibling numbers for the 1990, 2000s, 2010s might be because many of these are low quality running horses, not breeding horses.

DecadeHorsesFull SibAverage
180?6233.8
181?401213.0
182?3118632.8
183?94824072.5
184?128536422.8
185?182688464.8
186?2374190728.0
187?3145269938.6
188?4612269885.9
189?5622244674.4
190?6543316944.8
191?7831359144.6
192?9965306733.1
193?11835328752.8
194?16631407442.4
195?25365386471.5
196?27277364061.3
197?36611829022.3
198?506201284642.5
199?698011078131.5
200?83274522670.6
201?1524962880.4
 381171 3.4
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25-01-2017, 20:30   #33
 
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This week I completed database programs that analysed 159,660 horse pedigrees, and threw out the results.
Next is trying to learn from the results if there are differences between better horses and lesser horses, and if significant.

The results data is 4116 rows by 40 columns = 164,640 cells.
37 of the 40 columns are features in each pedigree, 16 from duplicated stallions, 16 from duplicated mares (duplicated mares are rare).
Very few of the 37 fields from 4116 rows are filled (37x4116 = 152,292). 125.695 cells have a zero result (82.5%). Only 17.5% of cells are filled.

It is a inbreedings/linebreedings analysis of six generations counting number of duplicated horses, groups of duplicated horses, sex of offspring of duplicated horses, siblings in pedigrees and so on.
If the results are useless I will move on to other ideas.
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27-01-2017, 09:12   #34
 
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I don't know much about statistics but I think the Chi Squared test might be the way to see if my results are relevant.
I've been swotting up on it in the last few days so caution is advised.

First I split the data into three files: colts, geldings, fillies.
There are 37,057 colts and that is where I started the tests.
I split the colts into two groups 10,212 and 26,842 = 37,054 (3 missing?).

Group A are the lower rated colts, Group B the higher rated colts.
Of course the highest rated colt in group A will only be a fraction below the lowest rated colt in Group B.
In hindsight I could have picked a higher point so that the split would be closer to 50/50.

Actual FrequencyGroup AGroup BTotal
044531139415847
138761015814034
2150541165621
33179831300
458171229
532023
 102122684237054
    
    
Expected FrequencyGroup AGroup BTotal
04,367.4011,479.6015847
13,867.7410,166.2614034
21,549.144,071.865621
3358.28941.721300
463.11165.89229
56.3416.6623
 102122684237054
    
p-value0.01806328<--- chitest (actual: expected) 
    
    
Chi-Square TermsGroup AGroup B 
01.680.64 = (4453-4367.4)^2/4367.4
10.020.01 ( differences squared
21.260.48 ( to turn them positive
34.761.81 ( then divide by expected
40.410.16 
51.760.67 
    
Chi-Square13.64 <--- sum above Chi-Squared Terms values
Degrees of Freedom5 <--- (data rows -1) * (data columns -1)
Alpha0.01 <--- 1% level
Critical Value16.81 <--- critical chi-square value (x2 distribution table)
    
Decision  Reject - Group A & Group B are not different at 1% level
    
Explanation  ( If "Chi-Square" number is bigger than "Critical Value"
   ( then differences are large between the groups
   ( and not caused by chance

This is from an Excel spreadsheet.
The actual numbers are at the top.
Then there is a calculation of the "expected" numbers.
(4367.40 is 4453 x 15847/37054 and so on)
The Chi-Squared Terms are the differences squared (to turn negative differences positive).
The idea is if the difference are big then Group A and Group B are very different, and the difference is not due to chance.

The "Decision" near the end is a comment saying if Group A and Group B are similar or different.
What I want is the pedigree factor I am testing to show a difference between the groups.
I want the Group B to have more of the factor, and that difference to be so large that if is not caused by chance.
The above test "failed" to prove that there is a one in a hundred chance that Group B are better due to the factor.
But if I change the Alpha to 0.05 it changes to
"Accept - Group A and Group B are different, - significant at 5% level"
or in other words there is only a one in twenty chance that Group B has more of the factor due to chance.

Then I thought I would see what the average ratings were for the colts with this factor.
Please remember that there are 37 pedigree factors, and this is just one of the 37 factors, a factor I think might produce better colts.
The other 36 factors are not yet tested statistically.
I will try to write a database program to calculate the statistical result at 1% and 5% for colts, geldings, fillies, and for all 37 factors.
It might be worthwhile to split the data further into 10% chunks from slowest horses to fastest.
Another possible is to use the random factor to split the horses randomly so that I do not use my opinions to select groups to test.

What would happen if I calculated the average ratings of the 37,057 colts who have the factor one, twice, three times and upwards.
Almost half the colts do not have this factor in their first six generations.
The colts without this factor have an average rating of 74.36.
The higher the number of factors it appears the higher the rating.
These are the ratings of the 23 horses with 5 occurences that average 106.40
45, 65, 74, 83, 88, 90, 96, 107, 111, 112, 115, 118, 120, 121, 124, 127, 129, 131, 132, 140
I should point out that much of the data is of the best horses over the past forty years, and small numbers are unreliable.


occurrenceCountAverageDiff
015,84774.36 
114,03476.321.96
25,62179.122.80
31,30085.055.93
422989.694.64
523106.4016.71
6391.00-15.40
    
 37,057  
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05-02-2017, 20:14   #35
 
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I posted this (username amadán) on Irish Bloodstock Forums
http://www.irishbloodstock.com/phpBB...1bd7b3c&t=4342

This is an old thread so this post might be overlooked.

In Jan/Feb 2017 I wrote programs to compare a horse six generation pedigree with rating.
To analyse deeper into a pedigree (7,8,9,10,11,12 gens) just needs the program to use a bigger ancestor database (I have those ready).
The present 6 gen ancestor database is 126 horses (2+4+8+16+32+64).

Many of these programs were written in earlier years but dusted off and completed after I finished the endless data collection at the end of 2016.
The pedigree and rating data was collected over 23 years.

I checked the program results statistically (by writing programs to do chi squared tests).
The program records 9 sire and 9 dam “factors” in each pedigree, (plus a few other extra factors) and the count of those factors in each pedigree.

The data was 159,222 horses.
These were four groups: colts; fillies; geldings; colts & geldings.
The first tests were for those four sex groups.
The second tests compared nine groups by racing quality (within the sex groups)
e.g. compare lowest group with second lowest group, all the way to comparing lowest group to highest group (9 groups is 9 x 8 /2 = 36 comparisons).

About four of the nine factors are positive (two very), a few neutral, and a couple negative. I need time to review the results files.

It should be possible to analyse pedigrees in volume and rank horses.
I recently analysed a sales catalogue of ~450 lots in about 40 seconds.
This was on my slow PC. My new PC is 3 times faster.
My new PC will be useful if I want to analyse / test more generations (7,8,9,10,11,12), or do more tests.

For increases of the count of some factors there is an increase in running rating: 0 count, 1 count, 2 count, and so on. (tested & proved statistically)
Higher rated groups of horses have more occurences of the positive factors than lower rated groups. (tested & proved statistically)
Counts go from 0 to 27, but usually up to about 7.

Average ratings increase may only be a point or so for an increase in factor occurence, but this is averaged over tens of thousands of horses.
But increasing from a count of 0 of a factor, to 1, to 2, to 3, to 4, gives a ratings increase for each jump in factor count.
(The other eight factors (or 17 factors) might affect the ratings increase.)

One of the results files is 5,184 lines.
The Chi squared test "Accepts” or "Rejects” each group comparison at 5% and 1%
i.e. a 1% Accept is the positive result has less that a 1% occurrence due to chance.

This gives an idea of the test volumes (from one test).

Occ ...Group A ....Group B
0..........4453.......11394
1..........3876.......10158
2..........1505........4116
3...........317..........983
4............58...........171
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06-02-2017, 15:07   #36
 
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I'm staying in the house today waiting for a DHL courier.

This are an extract from the results, and might be of interest. There are four sex groups and 18+ factors in each, so 72+ pieces of information.

One piece of information was picked at random (and luckily it is informative)
Average rating (factor occurence): 80.7 (0); 81.2 (1); 81.9 (2); 82.7 (3); 83.6 (4); 85.4 (5); 87.2 (6); 91.1 (7); 105.1 (8); 75.5 (9); 76.5 (10)
Average rating increase cumulatively: n/a (0); +0.5 (1); +1.2 (2); +2.0 (3); +2.9 (4); +4.7 (5); +6.5 (6); +9.4 (7); +24.4 (8); -5.2 (9); -4.2 (10)

You can see there is an increase in rating for each increase in this factor count, from 0 up to 8. Then there is a massive drop for counts 9 and 10.
One of the earlier groups has over 25,000 horses so the average is reliable, group 9 has only 4 horses and group 10 has 2 horses. Group 6 has 1,496, group 7 has 313, group 8 has 32 horses.

Some people say only one generation matters, the sire and dam. Sales catalogues show a 3 generation pedigree. I'm working with 6 generations. Is it time to look at 7, 8, 9, 10, 11, 12 generations?
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10-02-2017, 12:36   #37
 
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I have often wondered if it is possible to purchase an average mare, and breed a good horse.
The idea is to first breed a filly from the average mare, then to breed another horse that might be useful from that filly.
A test-mating is a theoretical mating on paper (or computer) of a stallion and mare.
I prepared test-matings on computer of an average horse picked at random, test-mating her with 393 stallions currently at stud in Irelend, England, France, Germany, Italy.
Using those 393 test-matings I again test-mated the first offspring with the same 393 stallions. I assumed that the results of the first test-matings were all fillies.
Of course you would not breed twice to the same sire, e.g. breed to Invincible Spirit, and breed that filly with Invincible Spirit.

The average horse picked was Mary Sea (2000) by Selkirk out of Mary Astor by Groom Dancer.
She didn’t win in nine starts.
Her best Racing Post Rating was 71, and Official Rating 60.
She has four offspring in my data: Bullyseye Babe (rated 53); Elsie Bay (69); Jamaica Grande (64); Sea Tobougie (48).

I wanted to see if in two steps it was possible to produce a horse with many of the factors mentioned in my earlier post.
The test sample was 154,842 (393 x 393)+393.
The result was: 1 horse (9 count of the above mentioned factor); 2 (8 count); 75 (7 count); 754 (6); 5394 (5); 21701 (4); 45713 (3); 53685 (2); 25222 (1); 2295 (0).
You can see how difficult it is to produce a good horse (theoretically), and this mirrors the reality.

A strange outcome is it might be possible to produce a horse with an “8 count”.
One of the offspring of Mary Sea is the filly Sea Tobougie (2007) by Tobougg out of Mary Sea.
A test-mating of that combination with the current sire Zambezi Sun (fee €3k) gives an “8 count”.
Sea Tobougie was only rated RPR 47, OR 40, and failed to win in twelve starts.
In fact any brooodmare by Toubougg mated with Zambezi Sun would give a similar (not same) result.

Is it possible to take a very average filly like Sea Tobougie and breed a good horse? It seems unlikely.
But a Japanese breeder, Kihachiro Watanabe, bought Irish three-year-old filly, Saddlers Gal (RPR 52, nine starts, no wins, no places, earnings £0).
He bred from her El Condor Pasa, who was second in the Prix de l’Arc de Triomphe (8 wins, 3 seconds from 11 starts).
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10-02-2017, 12:51   #38
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Quote:
Originally Posted by diomed View Post
I have often wondered if it is possible to purchase an average mare, and breed a good horse.
The idea is to first breed a filly from the average mare, then to breed another horse that might be useful from that filly.
A test-mating is a theoretical mating on paper (or computer) of a stallion and mare.
I prepared test-matings on computer of an average horse picked at random, test-mating her with 393 stallions currently at stud in Irelend, England, France, Germany, Italy.
Using those 393 test-matings I again test-mated the first offspring with the same 393 stallions. I assumed that the results of the first test-matings were all fillies.
Of course you would not breed twice to the same sire, e.g. breed to Invincible Spirit, and breed that filly with Invincible Spirit.

The average horse picked was Mary Sea (2000) by Selkirk out of Mary Astor by Groom Dancer.
She didn’t win in nine starts.
Her best Racing Post Rating was 71, and Official Rating 60.
She has four offspring in my data: Bullyseye Babe (rated 53); Elsie Bay (69); Jamaica Grande (64); Sea Tobougie (48).

I wanted to see if in two steps it was possible to produce a horse with many of the factors mentioned in my earlier post.
The test sample was 154,842 (393 x 393)+393.
The result was: 1 horse (9 count of the above mentioned factor); 2 (8 count); 75 (7 count); 754 (6); 5394 (5); 21701 (4); 45713 (3); 53685 (2); 25222 (1); 2295 (0).
You can see how difficult it is to produce a good horse (theoretically), and this mirrors the reality.

A strange outcome is it might be possible to produce a horse with an “8 count”.
One of the offspring of Mary Sea is the filly Sea Tobougie (2007) by Tobougg out of Mary Sea.
A test-mating of that combination with the current sire Zambezi Sun (fee €3k) gives an “8 count”.
Sea Tobougie was only rated RPR 47, OR 40, and failed to win in twelve starts.
In fact any brooodmare by Toubougg mated with Zambezi Sun would give a similar (not same) result.

Is it possible to take a very average filly like Sea Tobougie and breed a good horse? It seems unlikely.
But a Japanese breeder, Kihachiro Watanabe, bought Irish three-year-old filly, Saddlers Gal (RPR 52, nine starts, no wins, no places, earnings £0).
He bred from her El Condor Pasa, who was second in the Prix de l’Arc de Triomphe (8 wins, 3 seconds from 11 starts).
It'd be interesting to do a distribution of the various combinations.

Good mare/good stallion.
Average mare/good stallion.
Good mare/average stallion.
Average mare/average stallion.

Maybe you could run a query, get the average ratings of the offspring for each combination?

I know you've talked about buying a horse, has your data analysis narrowed down the criteria on what you'd be using to select something?
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10-02-2017, 14:57   #39
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Originally Posted by diomed View Post
I have often wondered if it is possible to purchase an average mare, and breed a good horse.
The idea is to first breed a filly from the average mare, then to breed another horse that might be useful from that filly.
A test-mating is a theoretical mating on paper (or computer) of a stallion and mare.
I prepared test-matings on computer of an average horse picked at random, test-mating her with 393 stallions
Is it possible to take a very average filly like Sea Tobougie and breed a good horse? It seems unlikely.
But a Japanese breeder, Kihachiro Watanabe, bought Irish three-year-old filly, Saddlers Gal (RPR 52, nine starts, no wins, no places, earnings £0).
He bred from her El Condor Pasa, who was second in the Prix de l’Arc de Triomphe (8 wins, 3 seconds from 11 starts).
Just on the moderateness of Saddlers Gal. The only thing moderate about her was her performance on the track, she's a blue blood through and through.

Saddlers Gal is by the mighty Sadlers Wells, out of the mare Glenveagh ( Seattle Slew x Lisadell ). Glenveagh is a half sister to Gp1 winners Fatherland ( National Stakes ) and the mighty Yeats ( multiple GP 1 winner ) both by Sadlers Wells.

Sending Glenveagh to Sadlers Wells was a matter of sending her to a Stallion that had producded 2 Gp1 winners from that nick, sending Saddlers Gal to Kingmambo was once again repeating the inbreeding to the supremely influential broodmare Special.

El Condor Pasa was a vindication of brilliant bloodlines, not the result of some random mating.

Last edited by tryfix; 10-02-2017 at 15:33.
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10-02-2017, 16:34   #40
 
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Originally Posted by Francie Barrett View Post
It'd be interesting to do a distribution of the various combinations.

Good mare/good stallion.
Average mare/good stallion.
Good mare/average stallion.
Average mare/average stallion.

Maybe you could run a query, get the average ratings of the offspring for each combination?

I know you've talked about buying a horse, has your data analysis narrowed down the criteria on what you'd be using to select something?
“Good” and “average” are not easy to define. I tend to use numbers. I produced foal averages for stallions. People would be surprised at how little the averages differ, only a few points. And of course we do not know how many foals were culled. We may just be seeing the best on the racecourse. It is a business.

A while back I grouped mares into 5 rating points bands (e.g. 1-6, 6-10, 11-15 up to 140+). The higher the dam ratings the higher the average foal rating. I confess I made errors and would have to run it again. The link between sire rating and foal rating was similar. Most sires are 120+. The dam is the weak part of the pedigree, and the dam’s dam the weakest.

The variation in foal ratings for a sire’s lifetime crop is very large, and most of the variation imo due to good/bad pedigrees instead of the dam rating. For bad pedigree I mean little in common between the horses in the sire and in the dam pedigree i.e. little or no duplications, or male duplications of a sire only. The concept of good sires, good broodmares does not make sense to me. Good horses are the product of good pedigrees that match the ancestors of sire and dam (others may disagree).

Ratings used might be suspect. They are a combination of well known ratings, the highest gained by the runner as a 3yo or older. Earlier ratings (1960s, 1960s, 1970s) seem to have been reviewed and lowered, so if you take them from old books you might get 135 for a horse, and if you see the same horse now it might be a 127. And 2yo ratings (free handicaps) were used when no 3yo+ rating found. An example here is Fairy Bridge, the dam of Sadler’s Wells. She only ran as a 2yo, was rated 124 (actually stones and pounds) in the Irish Free handicap, and retired to stud.
The USA experimental free handicap has an upper limit of 126 which might under rate those horses. The introduction of International Classifications helps even out the ratings of the major racing countries. Some countries may have been a optimistic in the past, and their ratings useful in promoting local bloodstock.

Has my analysis narrowed down my criteria?
(1) avoid numerous duplications of a sire that produces only male offspring e.g. Northern Dancer, especially if these are the only or the majority of duplications in the pedigree.*
(2) if buying to breed buy fillies with horses in their 3rd, 4th 5th generation that are full siblings of horses in the pedigrees of stallions at stud (or ¾, 7/8 siblings). These are not as common as you might think.
(3) breed the filly on paper with all sires at stud before you buy her (test-matings).

* I started to record the sire lines for each of the 393 stallions now at stud, and the sire line of the dams of those 393 stallions. After 22 stallions I stopped to do other work. 17 of those 22 stallions were Northern Dancer sire line, and 12 of their dams were Northern Dancer sire line (9 had both). Careful pedigree planning is needed to avoid this.

The example I gave of El Condor Pasa should be examined. His dam Saddlers Gal has the full siblings Special and Lisadell (both By Forli out of Thong) in her pedigree 3 x 2, too close to make her a good runner, but this close inbreeding often makes the mare a good producer. The Japanese breeder knew what he was doing. He bred her to the sire Kingmambo, who also has Special in his pedigree.

The next work is to go beyond the basic 6 generation analysis and prepare something that goes deeper into the pedigree, isolating the features that top males have and top females have (identified visually on screen). The analysis so far was a ready reckoner.
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10-02-2017, 20:33   #41
 
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Saddlers Gal sold for 22,000 guineas as a yearling in 1990, the lowest price for a Sadler's Wells yearling that year. Then she ran nine times with a best placing 5th of 6. I can't find her sales price but I think she might have been entered in a Tattersalls mare sale without selling. My guess is she sold to her Japanese owner for a lot less than her original sale price.
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11-02-2017, 05:31   #42
 
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Just got knocked out of a tournament on PokerStars (5:20 am). Time for a cup of coffee and a donut.

Found this on the internet a few minutes ago

Takashi Watanabe's interest in horseracing is driven by his knowledge of pedigrees which resulted in his breeding of El Condor Pasa, the newest Japanese star to shine in Europe. The owner of a trucking and transportation company in Tokyo, Watanabe was introduced to the sport by his father.
In 1992, he commissioned an agent to attend the Tattersalls December Sales to purchase the mare Saddlers Gal-a daughter of Sadlers Wells-who had failed to win in nine starts in Ireland.
The mare was withdrawn from the catalogue, but he was so determined to secure her that the representative, Morio Sakurai, was ordered to track her down.
''Mr Watanabe asked me to find her,'' said Sakurai. ''I located her on a farm in Ireland and he told me to buy her.''
The subsequent mating between Saddlers Gal and the top French miler Kingmambo was to produce El Condor Pasa, who Watanabe named after a Simon and Garfunkel hit.
The colt was placed with Yo****aka Ninomiya and last year became the first three-year-old to win the Japan Cup, doing so by two and a half lengths-the widest margin ever.
Ninomiya, a trainer since 1990, has a team of just 10 horses.
Approaching 50 years of age, he had previously served as assistant to renowned horseman Teruo Hashimoto for 12 years.
But he has also gained valuable experience for El Condor Pasa's current international programme during spells with Sir Michael Stoute in Newmarket and with US trainer Bruce Headley in California.

* Yo****aka (Yosh1taka)
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11-02-2017, 20:05   #43
 
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I analyse a number of things in pedigrees, including duplications.
This is an example of a six generation pedigree with duplicated horses in colour.
Some of the analysis factors I mention would be what you see here.

Modern pedigree are much less inbred, often with three or four highlighted horses. Here over twenty are highlighted.
The Tetrarch, foaled in Co Kildare, raced in England and was unbeaten.
Note that there is nothing duplicated in the first three generations. Sales catalogues show three generations.
A picture is worth a thousand words.


Last edited by diomed; 29-03-2017 at 13:47.
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11-02-2017, 20:17   #44
 
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This is the pedigree of Mary Sea, the average filly I chose for the test-mating experiment mentioned in previous posts.
Note the few connections between the pedigrees of her sire Selkirk and dam Mary Astor.


Last edited by diomed; 29-03-2017 at 13:47.
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11-02-2017, 20:34   #45
 
Join Date: Jun 2013
Posts: 4,674
My plan now is to mix it up a bit and work on the ideas in my ideas file.

I've always thought that the lower down in a pedigree the weaker the pedigree.
For example, in the above pedigree of Mary Sea (rated (71) the dam line of Mary Astor (86), Djallybrook (105), Hollybrook (rating not found), La Vagabonde (non runner) was not too weak. This area is often a lot weaker than the rest of the pedigree, full of minor sires.

I'm going to find out if possible the average rating of all the 126 positions (2+4+8+16+32+64) in the six generation pedigrees in my files. I'm not sure what good that is, but if I redo it for different ratings bands e.g. (0-20, 20-40, 60-80, 80-100, 100-120, 120+) there might be a lesson.
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