Analysing pedigrees

diomed · 15-02-2017 7:56pm

Mooooo wrote: »

Totally out of my field here but in dairy breeding genomics is really taking hold, would each foal not be genomically tested before sale, and is there an index at which those figures are judged on in terms of performance and heritable traits. Ireland has EBI, economic breeding index, for cows which has subindexes given different weightings for milk, fertility, etc. NZ has similar with different weightings called the BW, breeding worth. I dunno the data available for horses in terms of performance, accuracy etc but Is there not somethings similar for horses and if so how does it fit in with your figures?

Equinome have a gene speed test at €590 a horse.
Equinome have an Elite Performance Test at €1,450 a horse.

would each foal not be genomically tested before sale?
I don't know. Perhaps some horses are tested before sale but I do not know if the results must be revealed. They might be entered in a sale if they are tested and the results are unfavourable.

is there an index at which those figures are judged on in terms of performance and heritable traits?
Equinome have results for horses they tested. It looks like customers get results for one horse, not data for their horse and all other horses tested.
There are general statistics on the Equinome site but not with horse names.

Is there not somethings similar for horses and if so how does it fit in with your figures?
That data is valuable and I have nothing. My guess is you pay for one horse information only.

Genetic testing categorises a living foal by distance suitability and quality.
I'm trying to predict quality by analysing ancestors in a pedigree, and predicting potential quality before a foal is bred, or if already bred and unraced.

diomed · 17-02-2017 12:26pm

Further up the thread I mentioned the idea of prepotent sires, and if it might be possible to identify them.

"If a sire is “prepotent” his average should pop up above all others like a cork in water.
His influence will have boosted the rating of every pedigree in which he appears. "

I had to move the data files to my new fast PC as the number crunching task was large.
The program took each of 285,693 ancestors, found him/her in the 20,203,071 file that contained the six generation pedigree of 159,230 rated horses, and calculated an average rating and a count of the number of times the horse was in 6 gen pedigrees.
An example result is: NORTHERN DANCER1961, average 79.30, count 203,614
On the new fast PC it took eight hours for averages, and another eight house for counts.

Below is a sample of the results. When I saw them I realised Australian and Japanese horse featured prominently. Why?
Because I will only have the highest rated horses from those countries in my data gleaned from year-end international classifications, and none of the the ordinary horses from those countries.
Another "feature" of the results is many females appear only because they are the dam of famous sires. In the list below Wind In Her Hair gets in because she is the sire of Japanese horse Deep Impact.
I think the analysis will only be useful for Ireland and England horses with a good few crops / horses who have have finished their stud careers.
It is their influence in pedigrees I'm looking for, not as current sires.

This extract is DOB >= "1990" AND rate_count > 200 AND rate_avg > 85
The overall average is about 78.9

name sex rate_avg rate_count
DEHERE1991 M 92.55 201
DISTORTED HUMOR1993 M 90.19 255
DUBAI MILLENNIUM1996 M 86.88 453
DUBAWI2002 M 89.69 333
ENCOSTA DE LAGO1993 M 97.26 239
FLYING SPUR1992 M 89.07 270
FRENCH DEPUTY1992 M 97.14 213
GALILEO1998 M 87.04 1446
HELSINKI1993 F 87.38 396
OCTAGONAL1992 M 86.86 275
PULPIT1994 M 88.96 301
REDOUTE'S CHOICE1996 M 97.81 339
SHAMARDAL2002 M 87.57 385
SHANTHA'S CHOICE1992 F 97.84 350
SMART STRIKE1992 M 89.24 388
SPINNING WORLD1993 M 85.13 377
STREET CRY1998 M 86.85 342
TALE OF THE CAT1994 M 87.99 257
THUNDER GULCH1992 M 86.95 315
UNBRIDLED'S SONG1993 M 91.78 332
WIND IN HER HAIR1991 F 94.33 270
ZOMARADAH1995 F 90.01 341

rate_count >= 60000

name sex rate_avg rate_count
ALMAHMOUD1947 F 79.47 154064
BOLD RULER1954 M 79.25 73470
FAIR TRIAL1932 M 74.95 72787
GEISHA1943 F 79.02 105516
HAIL TO REASON1958 M 80.91 69518
HYPERION1930 M 77.43 174978
LADY ANGELA1944 F 79.02 134678
LALUN1952 F 78.85 64813
MAHMOUD1933 M 79.87 87270
MUMTAZ BEGUM1932 F 78.12 92140
NASRULLAH1940 M 78.34 242636
NATALMA1957 F 79.35 201694
NATIVE DANCER1950 M 79.08 246062
NEARCO1935 M 77.66 305727
NEARCTIC1954 M 79.23 192901
NOGARA1928 F 78.71 97612
NORTHERN DANCER1961 M 79.3 203614
PHAROS1920 M 79.24 111520
POLYNESIAN1942 M 78.98 117049
PRINCE ROSE1928 M 78.42 61264
PRINCEQUILLO1940 M 79.13 121707
RAISE A NATIVE1961 M 80.18 81709
RAISE YOU1946 F 80.26 68205
SOMETHINGROYAL1952 F 78.54 63531
TOM FOOL1949 M 79.19 66444
TUDOR MINSTREL1944 M 75.08 68115
TURN-TO1951 M 79.28 99468

Northern Dancer has a 79.30 average in all pedigrees.

His influence was
1st gen 113.92 (109 rated horses)
2nd gen 83.57 (6,760)
3rd gen 77.96 (40,880)
4th gen 78.84 (79,505)
5th gen 79.92 (57,181)
6th gen 80.45 (19,178)

Is the trend similar for all sires?
Why is there a gradual increase from gen 3 to gen 6?

diomed · 17-02-2017 1:10pm

The Northern Dancer example above is misleading. He was born in 1961.
His first generation horses in my data (Gen 1) are probably his expensive foals imported to Europe.
I do not have ratings for most of his foals.

This example is better. Sadler's Wells, Darshaan, and Rainbow Quest were all born in 1981.
They all became sires, and their stud careers are over.
They had similar ratings, 132, 133, 134, and actually finished 1,2,3 in a race.
The 90.00 for Rainbow Quest in Gen 5 should be ignored (only two horses).

Gen Sadler's Wells.. Darshaan....... Rainbow Quest..
0
1 88.28 87.18 84.20
2 79.80 79.31 79.24
3 78.58 77.15 79.24
4 77.99 76.95 81.30
5 77.64 75.00 90.00
6

Super sires do not produce crops much above the average.
But they, and other sires, produce some exceptional horses.

diomed · 18-02-2017 12:18am

PREPOTENT

I'm moving on from the question of do sires have an effect that lasts through generations.
I've sliced and diced the info a number of ways, and will review it in the future. A problem is the data.
The data for Ireland and UK sires will be more reliable.
The averages for USA, Japan, Australia sires will be higher as it will probably contains very few low rated.
avg1 is the average rating of the rated foals of the sires (or dams)

This is a sample for generations 0 (the sire or dam) to generation 6
(extract is count >= 1500 and dob >= 1980)

name sex avg_1to6 avg0 avg1 avg2 avg3 avg4 avg5 avg6 coun0 coun1 coun2 coun3 coun4 coun5 coun6
Alzao 1980 M 77.8 117 80.0 74.2 81.1 77.6 101.0 0.0 1 545 1074 795 141 1 0
Barathea 1990 M 75.9 129 76.9 74.8 78.6 78.0 0.0 0.0 1 601 979 153 1 0 0
Bluebird 1984 M 74.0 125 73.7 70.8 80.6 73.2 0.0 0.0 1 327 938 458 81 0 0
Cadeaux Genereux 1985 M 75.3 131 79.6 73.4 74.5 70.6 0.0 0.0 1 579 1153 465 11 0 0
Caerleon 1980 M 80.6 132 87.3 80.6 79.7 78.4 74.3 0.0 1 425 1507 1523 621 40 0
Chief's Crown 1982 M 75.3 141 85.4 75.5 75.6 70.1 49.3 0.0 1 93 1286 1315 318 3 0
Cozzene 1980 M 79.3 132 92.1 83.1 82.3 74.7 81.4 0.0 1 136 400 901 1333 39 0
Dancing Brave 1983 M 82.6 140 86.8 84.0 81.5 83.5 67.7 0.0 1 96 437 1292 549 6 0
Danehill Dancer 1993 M 79.3 118 82.7 75.9 78.6 0.0 0.0 0.0 1 887 915 18 0 0 0
Danehill 1986 M 82.0 126 91.4 82.0 79.6 79.3 0.0 0.0 1 790 7898 3131 34 0 0
Darshaan 1981 M 78.8 133 87.2 79.3 77.2 77.0 75.0 0.0 1 429 2256 2191 594 8 0
Diesis 1980 M 76.9 133 84.8 75.1 76.4 79.9 110.0 0.0 1 444 1800 1363 134 1 0
El Gran Senor 1981 M 81.4 136 89.9 76.8 82.1 81.3 0.0 0.0 1 144 395 750 288 0 0
Fairy King 1982 M 77.2 132 82.5 75.7 78.0 80.2 0.0 0.0 1 317 1536 630 25 0 0
Gone West 1984 M 80.9 129 87.8 82.6 78.8 78.4 83.0 0.0 1 252 2102 2313 324 2 0
Green Desert 1983 M 77.9 127 82.5 77.9 76.0 77.4 77.2 0.0 1 758 4702 1905 187 82 0
Groom Dancer 1984 M 74.2 128 76.6 73.7 74.6 72.1 75.4 0.0 1 268 778 612 295 8 0
Gulch 1984 M 80.4 127 81.3 80.5 79.9 83.9 0.0 0.0 1 183 764 866 34 0 0
Highest Honor 1983 M 77.5 130 85.2 77.0 73.7 84.3 0.0 0.0 1 283 1217 441 12 0 0
In The Wings 1986 M 80.3 128 82.9 79.6 79.9 82.0 0.0 0.0 1 374 1236 372 6 0 0
Indian Ridge 1985 M 74.8 123 81.0 72.9 75.1 75.0 0.0 0.0 1 564 1959 377 27 0 0
Kahyasi 1985 M 81.2 135 79.3 80.3 83.9 77.2 58.0 0.0 1 269 302 854 407 1 0
Kingmambo 1990 M 81.9 125 88.8 81.4 79.6 76.0 0.0 0.0 1 328 1928 547 1 0 0
Last Tycoon 1983 M 80.8 131 78.8 80.5 81.8 79.9 0.0 0.0 1 235 1419 1042 194 0 0
Lear Fan 1981 M 80.2 130 87.3 78.4 80.5 75.8 69.0 0.0 1 208 448 813 234 1 0
Linamix 1987 M 80.1 127 86.4 78.5 77.7 85.1 0.0 0.0 1 369 867 414 15 0 0
Lomond 1980 M 78.1 128 82.0 76.2 78.6 77.1 78.6 0.0 1 132 377 1138 383 51 0
Machiavellian 1987 M 80.3 125 85.8 78.1 82.1 91.8 0.0 0.0 1 410 2167 1188 28 0 0
Mendez 1981 M 80.0 133 81.3 85.8 78.4 77.6 85.1 0.0 1 11 385 899 416 15 0
Night Shift 1980 M 77.0 126 77.8 76.4 76.9 79.7 0.0 0.0 1 656 1187 459 141 0 0
Pivotal 1993 M 78.2 124 83.2 75.1 81.4 0.0 0.0 0.0 1 758 1248 39 0 0 0
Polar Falcon 1987 M 77.6 126 79.6 80.3 74.8 81.8 0.0 0.0 1 243 1122 1383 40 0 0
Rahy 1985 M 83.4 115 87.6 80.2 85.5 83.3 94.0 0.0 1 245 928 852 939 5 0
Rainbow Quest 1981 M 80.1 134 84.2 79.2 79.2 81.3 90.0 0.0 1 583 1798 1774 528 2 0
Red Ransom 1987 M 80.1 136 83.6 79.0 78.2 82.3 0.0 0.0 1 460 975 328 15 0 0
Royal Academy 1987 M 80.5 133 83.4 79.1 80.1 88.4 0.0 0.0 1 458 1034 422 15 0 0
Sadler's Wells 1981 M 79.8 132 88.3 79.8 78.6 78.0 77.6 0.0 1 1380 7999 7765 1470 33 0
Seeking The Gold 1985 M 85.0 135 88.3 83.6 85.3 88.8 0.0 0.0 1 175 682 952 19 0 0
Shareef Dancer 1980 M 78.4 135 75.8 74.0 78.2 84.3 80.8 0.0 1 234 618 619 576 16 0
Storm Cat 1983 M 84.9 119 92.8 85.2 83.8 84.9 71.1 0.0 1 261 2807 2659 209 16 0
Sunday Silence 1986 M 98.8 132 106.5 98.0 97.9 102.0 0.0 0.0 1 176 1687 176 1 0 0
Unfuwain 1985 M 76.6 131 81.0 76.1 74.3 83.6 0.0 0.0 1 307 810 483 25 0 0
Waajib 1983 M 75.4 121 70.6 73.7 77.4 80.6 0.0 0.0 1 127 777 638 134 0 0
Warning 1985 M 73.2 136 84.5 71.8 72.4 74.7 0.0 0.0 1 234 1587 784 103 0 0
Woodman 1983 M 78.5 126 83.9 76.8 79.1 81.6 0.0 0.0 1 326 1740 1305 148 0 0
Zafonic 1990 M 78.8 130 84.5 77.3 78.2 88.0 0.0 0.0 1 317 1104 275 1 0 0

Annie Edge 1980 F 79.4 118 99.1 83.2 76.5 77.1 0.0 0.0 1 8 604 725 184 0 0
Brocade 1981 F 76.5 121 98.3 77.7 75.2 78.7 78.0 0.0 1 10 643 1006 156 1 0
Coup De Folie 1982 F 79.9 112 106.8 83.7 78.0 81.2 89.9 0.0 1 8 598 2420 1344 33 0
Fearless Revival 1987 F 77.8 105 79.0 83.1 74.6 81.4 0.0 0.0 1 5 768 1315 39 0 0
High Hawk 1980 F 80.4 124 98.8 82.8 79.6 79.9 82.0 0.0 1 9 387 1239 372 6 0
La Papagena 1983 F 75.9 0 89.5 77.8 74.9 72.7 0.0 0.0 0 11 546 819 127 0 0
Marie D'Argonne 1981 F 77.7 121 84.6 79.7 80.4 74.8 81.8 0.0 1 7 258 1172 1383 40 0
Miesque 1984 F 81.7 133 106.9 85.4 81.4 79.5 76.0 0.0 1 8 432 2147 550 1 0
Mira Adonde 1986 F 79.3 0 99.0 82.7 75.9 75.8 0.0 0.0 0 7 913 921 20 0 0
Park Appeal 1982 F 79.6 122 105.0 82.5 77.0 74.2 78.0 0.0 1 8 775 784 88 1 0
Razyana 1981 F 81.8 69 105.7 87.9 81.9 79.6 79.3 0.0 1 9 931 7945 3138 34 0
Stufida 1981 F 77.8 0 97.5 71.8 83.1 74.6 81.4 0.0 0 2 14 779 1316 39 0
Urban Sea 1989 F 86.9 124 120.0 88.5 83.6 0.0 0.0 0.0 1 9 1013 582 0 0 0
Zaizafon 1982 F 78.8 119 110.2 81.9 77.1 78.3 88.0 0.0 1 5 640 1205 278 1 0

This is some extra info on the females listed
Annie Edge 1980 - dam of Selkirk
Brocade 1981 - dam of Barathea
Coup De Folie 1982 - dam of Exit To Nowhere, Machiavellian
Fearless Revival 1987 - dam of Pivotal
High Hawk 1980 - dam of In The Wings
La Papagena 1983 - dam of Grand Lodge
Marie D'Argonne 1981 - dam of Polar Falcon
Miesque 1984 - dam of Kingmambo, Miesque's Son
Mira Adonde 1986 - dam of Danehill Dancer
Park Appeal 1982 - dam of Cape Cross
Razyana 1981 - dam of Danehill
Stufida 1981 - 2nd dam of Pivotal
Urban Sea 1989 - dam of Galileo, Sea The Stars
Zaizafon 1982 - dam of Zafonic, Zamindar

Peintre Celebre · 18-02-2017 5:47am

Diomed I have an interest in breeding its above your normal punter but nowhere near a pro. Are there any racing books you'd recommend on the history of the breed to get into? Have read A Cenutry of Champions many Ines after struggling to get my hands on it. E mailed the author when I couldn't find one as to how I'd get one 'I'll tell you the same thing I told John Oxx and Lord Derby when they asked could I get one for them'. Like gold dust an outstanding book.

Peintre Celebre · 18-02-2017 5:50am

P s if anyone wants to hear one of the profiles of a horse I'll gladly post it. One of my favourite lines in the whole book as he describes Secretsriat '...that magical afternoon in New York'.

They rated Sea Bird the best of the previous century

diomed · 18-02-2017 10:22pm

Peintre Celebre wrote: »

Diomed I have an interest in breeding its above your normal punter but nowhere near a pro. Are there any racing books you'd recommend on the history of the breed to get into? Have read A Cenutry of Champions many Ines after struggling to get my hands on it. E mailed the author when I couldn't find one as to how I'd get one 'I'll tell you the same thing I told John Oxx and Lord Derby when they asked could I get one for them'. Like gold dust an outstanding book.

As you say many books sell out and then are not offered second-hand.
My guess is they come on the market second-hand in estate sales.
I've been lucky in that I often get fliers in the post when a new book is published.

I had about 800 books on thoroughbred horses at last count.
These have been accumulated over about twenty five years.
Perhaps one third are stud books, one third form books, and the rest biographies and pedigrees analysis books.
One thing to keep in mind is that books and pedigrees have errors.

I bought the bulk of my books from Way Books https://www.way-books.co.uk/ Newmarket, England (Greg Way).
Previously I bought from J A Allen (acquired by Hale Books in 1999 http://halebooks.com/ )
Racing Post (for Michael Church books, and Century Of Champions etc)
The Russell Meerdink Company (http://www.horseinfo.com/ good for USA authors, and Ken McLean books)
Weatherbys for new copies of the General Stud Book (£270 every four years), and Statistical Record etc

Just before Christmas I bought 32 second-hand books from Way Books, mostly biographies.
A few minutes ago I e-mailed Greg Way asking if he could supply four Italian Stud Books (£25 each, 1925-29, 1948-51, 1952-55, 1960-63).

I think a good general book on the history of the breed is Sir Charles Leicester's "Bloodstock Breeding" published in 1957 cost £30
http://halebooks.com/shop/j-a-allen/al5/bloodstock-breeding/
I think he lived in Co Meath and died in Bray.
It analysed each year's Derby and top races, a chapter for each year.
But there are many other chapters full of useful insights.
He was imo remarkable in his analysis examining many of the old wives tales about age of mares and sires, birth rank, and the usual fairy tales.
He was not afraid to roll up his sleeves and examine things in detail.
I'm not a fan of the saying "breed the best to the best and hope for the best". That saying tells you to not analyse things, just pay the stud fee.

Another for old time stuff is "The History Of The Racing Calendar and Stud-Book by C M Prior (1926).
This would not help with breeding or racing but is full of interesting trivia:
a weaver given a present of a filly in the 1700s walked 300 miles to collect her and then walked home with her
a mare ridden 300 miles in three days to win a wager
if you didn't pay when you lost a bet in a club you were put in a basket, hauled up by rope and left there
the first mention of jockeys colours in 1716 and the seventeen owners and colours
before c 1784 jockey term was originally used to mean owner but meaning changed when owners ceased to ride their horses
Pocahontas filly dob 1837 perhaps the most important horse of either sex was sold for 14 guineas, small compared with 2,500 guineas for a smart 2yo years earlier
a stud groom told to shoot a mare who was useless but shot the owner's good mare

My most useful book is The Thoroughbred Breeders Handbook by New Zealander Clive Harper published in 1997.
It is only 107 pages including appendix, bibliography, index.
It explains how to analyse pedigrees by analysing the ancestor inbreeding / linebreeding. His work follows the ideas of Harold Hampton.
My analysis earlier in this thread is very similar, although I've a few extra ideas still to analyse.
You will be lucky if you locate a copy.
In December I e-mailed Clive Harper's widow as I was told she had copies of his last book, Pattern Of Patterns in Thoroughbred Pedigrees. No reply. Clive Harper died in 2012.

diomed · 18-02-2017 11:51pm

Here is some summary data for horses, sires, dams grouped in ratings bands.

rate_band name_count name_avg_s sire_count name_avg_d dam_count
145 - 149 1 120.0 5 0.0 0
140 - 144 6 89.7 448 0.0 0
135 - 139 45 81.9 4686 92.2 58
130 - 134 167 82.4 14357 90.9 280
125 - 129 384 78.3 20786 93.3 467
120 - 124 776 74.6 13767 91.3 1389
115 - 119 1681 72.9 8656 88.5 2474
110 - 114 2200 69.5 2797 86.4 3506
105 - 109 3122 67.8 998 84.5 4656
100 - 104 3603 68.0 490 82.8 4992
095 - 099 3863 66.9 248 80.2 4844
090 - 094 4164 62.7 197 78.5 5111
085 - 089 4793 61.5 111 77.7 5352
080 - 084 5646 63.4 189 75.9 6028
075 - 079 6110 49.3 21 74.0 5781
070 - 074 6196 69.8 99 72.5 5617
065 - 069 5759 55.4 16 71.8 4884
060 - 064 5057 64.1 23 70.8 3978
055 - 059 4306 58.0 4 70.5 2838
050 - 054 3537 49.9 7 69.6 2001
045 - 049 2643 34.7 3 67.3 1169
040 - 044 1538 0 65.4 823
035 - 039 783 58.0 1 65.3 435
030 - 034 511 0 68.2 277
025 - 029 329 0 68.5 170
020 - 024 216 64.0 2 63.3 113
015 - 019 146 0 66.3 55
010 - 014 206 48.8 5 74.9 532
005 - 009 81 0 69.2 64
000 - 004 47 0 64.1 22

count 67916 67916 67916
average 78.94 123.60 85.44

average dob 1999.8 1988.5 1989.9

Comments:
These are 67,916 runners with ratings, who have sires with ratings, and dams with ratings.
Some great horses are missing e.g. Derby winner Golden Horn. His unraced dam has no rating.
Although the average sire rating is 123.60, and the average dam rating 85.44, the average foal rating is only 78.94.

It is a bit tricky to read so I'll give examples
1,169 dams who were themselves rated in the band 045-049 (dam_count column) produced runners with average rating 67.3
13,767 sires who were themselves rated 120-124 (sire_count column) produced runners with average rating 74.6.
name_count is the count of runners in each rate band. 3,603 runners were rated 100-104.

You might notice large numbers of horses in the 010-014 band.
The majority of these are raced but unrated horses. They ran, but ran so badly they were not given a rating.
I gave them 10 to distinguish them from all the unraced horses (0 rating) or horses who raced abroad where no rating was available (0 rating).

A bit of extra analysis of the 17,822 dams rated 100+
dams rated 100+ mated with sires under 100 ... foal average 76.18 (49 dams)
dams rated 100+ mated with sires 100-109 ..... foal average 85.07 (179 dams)
dams rated 100+ mated with sires 110-119 ..... foal average 82.51 (1485 dams)
dams rated 100+ mated with sires 120-129 ..... foal average 84.38 (8198 dams)
dams rated 100+ mated with sires 130+ .......... foal average 88.05 (7911 dams)

Conclusion:
Breeding the best to the best will on average produce a horse above the 78.94 average, but not much above that average.

For every increase in dam rating there is (almost) always an increase in foal rating.
For every increase in sire rating there is (almost) always an increase in foal rating.
For the same rating band for sire and dam the dams appears to produce a better result
e.g. at the 120-124 band the sires produced foals average 74.6 while the dams produce foals average 91.3.
This does nor mean that similarly rated dams outperform sires.
The sires in 120-124 are mated with many much lower rated dams, rated 85.44 on average, while the 120-124 rated dams will on average be rated with sires rated 123.60 on average.

diomed · 19-02-2017 1:52pm

I keep a database of Group 1, Group 2, Group 3 race winners for Ireland, England, France, Germany, Italy, USA (Grade 1 only).
I also have the winners of these races from 1900 before they were designated "Group races".
Group races were introduced in Europe in 1971 and in the USA in 1973.
A horse who finished in the first three in the Group 1, Group 2, Group 3, Listed races can be entered in a sales catalogue in bold type ("black type").
For a few years fourth place finishers were also "black type" horses but that is now limited to fourth in Group 1 only.

I don't keep records of Listed race winners unless the race was at one time a Group 3 race or higher.
Group races can go up and down in Grade based on the quality (rating) of the horses running in them.
I don't record 2nd, 3rd, 4th place finishers. The reason is it would take too much time, and often it is only easy to find the winner.
Any volunteers to find the 2nd and 3rd place finishers (and their pedigrees) in the Group 3 Italian race Premio Carlo E Francesco Aloisi at Capannelle on 18/11/73 (strangely I have a book with this info)?

I'm not a fan of "black type". It is imo a lazy way of analysing a sales catalogue.
Just look at the page and if you see plenty of bold type it is a good horse!
I'm reading the Mark Johnston biography at the moment. I remember I was at The Curragh when his 2yo filly Millstream won the Group 3 Curragh Stakes on 09/07/94.
There were three runners so they all qualified for black type, even Sharpness In Mind who was beaten 13 lengths in 3rd.
The first two finishers were fillies, the 3rd was a gelding.
If the 3rd finisher was a filly would you know in a sale catalogue that "her" black type was as a 13 length 3rd of three runners. Not a chance.
(I also remember Mark Johnston being interviewed by the press in the ring after the race (was it that day?) in the rain. The press all had umberellas, and Mark did not. It was a lengthy interview, and he was getting wet in his expensive suit.)

Analysis to come
Over the next week I'll try to put up some stuff about black type winners (and nothing about black type placed).
Are black type winners produced by black type dams? Most people (mistakenly?) think they are.
How about the second dam and the third dam of black type winners?
You see these dams in sales catalogues backing up the sales lot.
Is there any difference between the second and third dams of black type winners and the rest of the racing population?
I'm sure I'll think of a few more questions as I work on the data.

The following table has a few major handicaps that I'll filter out (Wokingham, Lincoln)

1990 to 2015: 36,144 races, 21,113 individual Group race winners
country group_1 group_2 group_3 listed grade_1 grade_2 grade_3 handicap
IRELAND 731 612 1628 325 0 0 0 0
ENGLAND 2242 2521 4118 734 0 0 0 548
FRANCE 2322 2068 5283 393 0 0 0 0
GERMANY 647 939 1343 1 0 0 0 0
ITALY 867 553 961 698 0 0 0 21
USA 0 0 0 6 6199 335 49 0

diomed · 21-02-2017 8:16am

I posted this preliminary work on Group race winners and their dams a few minutes ago.

Some stats on Group race winners and their dams 1900 to 2015: Ireland, England, France, Germany, Italy, USA (Grade 1 only)

36,122 Group races, 21,059 individual winners

Group 1, Group 2, Group 3, Listed (a few), Grade 1, Grade 2 (a few), Grade 3 (a few), Handicaps (a few).
The "a few" comment refers to races that drifted between listed and Group 3. The same for the USA, the sample was Grade 1 only but grades in those races vary over time.
I treat races before 1971 (pattern introduction) as Group races i.e. The Epsom Derby from 1900 to 1970 is a Group 1.

I've been tidying up the data before analysis so the above may change.

dam's foals how many races? dams races runners

dam's foals won 0 group races 0 132 119 *
dam's foals won 1 group races 9525 9525 9525
dam's foals won 2 group races 3497 6994 4324
dam's foals won 3 group races 1705 5115 2454
dam's foals won 4 group races 1004 4016 1604
dam's foals won 5 group races 553 2765 967
dam's foals won 6 group races 330 1980 631
dam's foals won 7 group races 215 1505 435
dam's foals won 8 group races 137 1096 287
dam's foals won 9 group races 88 792 215
dam's foals won 10 group races 56 560 137
dam's foals won 11 group races 39 429 106
dam's foals won 12 group races 17 204 53
dam's foals won 13 group races 14 182 41
dam's foals won 14 group races 12 168 31
dam's foals won 15 group races 11 165 30
dam's foals won 16 group races 10 160 33
dam's foals won 17 group races 2 34 7
dam's foals won 18 group races 3 54 8
dam's foals won 20 group races 3 60 17
dam's foals won 21 group races 4 84 14
dam's foals won 22 group races 1 22 6
dam's foals won 23 group races 1 23 4
dam's foals won 25 group races 1 25 7
dam's foals won 32 group races 1 32 4
Totals 17229 36122 21059

* I have the names of the 119 runners but not their dams.

Which dam had four runners that won 32 Group races?
Buonamica (1943) dam Of Barbara Sirani (10 Wins); Bonnard (1 Win); Botticelli (14 Wins); Braque (7 Wins) = 32 wins,
almost all in Italy at San Siro and Capannelle, except two in England, Ascot Gold Cup, Doncaster Cup.

How many dams of Group winners 1900-2015 won a Group race ............... 1,827 (10.6%)
How many dams of Group winners 1900-2015 did not win a Group race .... 15,402 (89.4%)

(dams of the "group" winners in the first years of the 20th century obviously could not have won Group races in the 20th century but could have won "group" races in the 19th century)
(many races run today were not inaugurated until recently so dams of those winners my also have had fewer opportunities)

A count of dams of Group winners born 1970+:
won a Group race themselves .............................................871 (11.1%);
didn't win a Group race themselves ...................................6,972 (88.9% )

(it makes me wonder why sales catalogues have dams in black type)
(my guess is it is mostly placed horses in Gr 1, Gr 2, Gr 3, listed. I ignore these cheap "black types" . They are not in my analysis)

Conclusion:
Horses that win group races do not get that ability from their dam's racing ability.

diomed · 21-02-2017 10:04pm

This might seem an excessive table.
These are dams born 1970+ who have produced the winners of ten or more Group or Graded races.

The reason I'm showing the detailed list is it gives clues to the source of quality in horses.
I think it is instructive to examine the pedigrees of these dams (not the pedigree of their group winners). I think you will find clues to the source of quality.
Some dams produced Group winners to only one sire, other to many different sires, and some to similar sires (same sire line).
I could go through the pedigrees one at a time but the explanations would fill many pages. I'm listing these to indicate that good horses are not produced by chance ("breed the best to the best").

It might be

where a dam produced Group winners to only one sire then it is the pedigree of the Group winner that is important (not so much the sire and dam);
where a dam produced Group winners to many different sires then there might be something in the pedigree of that dam that is important
where the dam produced winners to similar sires that is a bit like producing winners to one sire (the pedigree of the group winner is important).

name dob sire sdob dam ddob sex n_grp_1 n_grp_2 n_grp_3 n_listed n_gra_1 n_gra_2 n_gra_3 n_hcap dam_of
DENON 1998 PLEASANT COLONY 1978 AVIANCE 1982 M 0 0 1 0 4 0 0 0 10
CHIMES OF FREEDOM 1987 PRIVATE ACCOUNT 1976 AVIANCE 1982 F 1 2 1 0 0 0 0 0 10
IMPERFECT CIRCLE 1988 RIVERMAN 1969 AVIANCE 1982 F 0 0 0 1 0 0 0 0 10
HEAD IN THE CLOUDS 1998 RAINBOW QUEST 1981 BALLERINA 1991 F 0 0 1 0 0 0 0 0 12
MILLENARY 1997 RAINBOW QUEST 1981 BALLERINA 1991 M 1 7 3 0 0 0 0 0 12
PROVISO 2005 DANSILI 1996 BINCHE 1999 F 0 0 2 0 4 0 0 0 10
BYWORD 2006 PEINTRE CELEBRE 1994 BINCHE 1999 M 1 2 1 0 0 0 0 0 10
ANODIN 2010 ANABAA 1992 BORN GOLD 1991 M 0 0 1 0 0 0 0 0 21
GOLDIKOVA 2005 ANABAA 1992 BORN GOLD 1991 F 11 0 1 0 3 0 0 0 21
GOLD ROUND 1997 CAERLEON 1980 BORN GOLD 1991 F 0 0 1 0 0 0 0 0 21
GALIKOVA 2008 GALILEO 1998 BORN GOLD 1991 F 1 1 1 0 0 0 0 0 21
GOLD SOUND 2002 GREEN TUNE 1991 BORN GOLD 1991 M 0 0 1 0 0 0 0 0 21
ZABAR 1988 DANCING BRAVE 1983 BROCADE 1981 M 0 1 3 0 0 0 0 0 11
BARATHEA 1990 SADLER'S WELLS 1981 BROCADE 1981 M 1 1 0 0 1 0 0 0 11
GOSSAMER 1999 SADLER'S WELLS 1981 BROCADE 1981 F 2 0 1 0 0 0 0 0 11
FREE AT LAST 1987 SHIRLEY HEIGHTS 1975 BROCADE 1981 F 0 0 0 1 0 0 0 0 11
SHERIFF'S STAR 1985 POSSE 1977 CASTLE MOON 1975 M 2 2 0 0 0 0 0 0 10
LUCKY MOON 1987 TOUCHING WOOD 1979 CASTLE MOON 1975 M 0 0 1 0 0 0 0 0 10
MOON MADNESS 1983 VITIGES 1973 CASTLE MOON 1975 M 2 2 1 0 0 0 0 0 10
KAYF TARA 1994 SADLER'S WELLS 1981 COLORSPIN 1983 M 4 4 0 0 0 0 0 0 16
OPERA HOUSE 1988 SADLER'S WELLS 1981 COLORSPIN 1983 M 4 0 2 0 0 0 0 0 16
ZEE ZEE TOP 1999 ZAFONIC 1990 COLORSPIN 1983 F 1 0 0 1 0 0 0 0 16
EXIT TO NOWHERE 1988 IRISH RIVER 1976 COUP DE FOLIE 1982 M 1 0 3 0 0 0 0 0 13
COUP DE GENIE 1991 MR PROSPECTOR 1970 COUP DE FOLIE 1982 F 2 0 2 0 0 0 0 0 13
MACHIAVELLIAN 1987 MR PROSPECTOR 1970 COUP DE FOLIE 1982 M 2 0 0 1 0 0 0 0 13
OCEAN OF WISDOM 1997 MR PROSPECTOR 1970 COUP DE FOLIE 1982 M 0 0 1 0 0 0 0 0 13
HYDRO CALIDO 1989 NUREYEV 1977 COUP DE FOLIE 1982 F 0 1 0 0 0 0 0 0 13
DIAMOND SHOAL 1979 MILL REEF 1968 CROWN TREASURE 1973 M 3 1 2 0 0 0 0 0 14
GLINT OF GOLD 1978 MILL REEF 1968 CROWN TREASURE 1973 M 6 1 1 0 0 0 0 0 14
DALGHAR 2006 ANABAA 1992 DALTAWA 1989 M 0 0 1 0 0 0 0 0 17
DALAKHANI 2000 DARSHAAN 1981 DALTAWA 1989 M 4 2 1 0 0 0 0 0 17
DAYLAMI 1994 DOYOUN 1985 DALTAWA 1989 M 6 0 1 0 2 0 0 0 17
ARAZI 1989 BLUSHING GROOM 1974 DANSEUR FABULEUX 1982 M 3 2 1 0 1 0 0 0 10
NOVERRE 1998 RAHY 1985 DANSEUR FABULEUX 1982 M 1 1 1 0 0 0 0 0 10
RUSSIAN CROSS 2005 CAPE CROSS 1994 DIEVOTCHKA 1989 M 0 1 0 0 0 0 0 0 10
ARCHANGE D'OR 2002 DANEHILL 1986 DIEVOTCHKA 1989 M 0 1 0 0 0 0 0 0 10
ESOTERIQUE 2010 DANEHILL DANCER 1993 DIEVOTCHKA 1989 F 3 0 2 0 0 0 0 0 10
RUSSIAN HOPE 1995 ROCK HOPPER 1987 DIEVOTCHKA 1989 M 0 1 2 0 0 0 0 0 10
GENEROUS 1988 CAERLEON 1980 DOFF THE DERBY 1981 M 4 0 0 0 0 0 0 0 11
WEDDING BOUQUET 1987 KINGS LAKE 1978 DOFF THE DERBY 1981 F 0 0 1 2 0 0 0 0 11
IMAGINE 1998 SADLER'S WELLS 1981 DOFF THE DERBY 1981 F 2 0 1 0 0 0 0 0 11
STRAWBERRY ROAN 1994 SADLER'S WELLS 1981 DOFF THE DERBY 1981 F 0 0 0 1 0 0 0 0 11
RUDIMENTARY 1988 NUREYEV 1977 DOUBLY SURE 1971 M 0 1 0 1 0 0 0 0 12
DIESIS 1980 SHARPEN UP 1969 DOUBLY SURE 1971 M 2 0 0 0 0 0 0 0 12
KRIS 1976 SHARPEN UP 1969 DOUBLY SURE 1971 M 1 5 2 0 0 0 0 0 12
GOLDEN SNAKE 1996 DANZIG 1977 DUBIAN 1982 M 4 0 0 0 0 0 0 0 10
SAYYEDATI 1990 SHADEED 1982 DUBIAN 1982 F 5 0 1 0 0 0 0 0 10
MY PATRIARCH 1990 BE MY GUEST 1974 EARLY RISING 1980 M 0 0 1 1 0 0 0 0 10
SILVER PATRIARCH 1994 SADDLERS' HALL 1988 EARLY RISING 1980 M 3 2 1 0 0 0 0 0 10
PAPINEAU 2000 SINGSPIEL 1992 EARLY RISING 1980 M 1 0 1 0 0 0 0 0 10
ENZELI 1995 KAHYASI 1985 EBAZIYA 1989 M 1 0 1 1 0 0 0 0 11
ESTIMATE 2009 MONSUN 1990 EBAZIYA 1989 F 1 1 2 0 0 0 0 0 11
EDABIYA 1996 RAINBOW QUEST 1981 EBAZIYA 1989 F 1 0 0 1 0 0 0 0 11
EBADIYLA 1994 SADLER'S WELLS 1981 EBAZIYA 1989 F 2 0 0 0 0 0 0 0 11
MAZZACANO 1985 ALLEGED 1974 FALL ASPEN 1976 M 0 0 1 1 0 0 0 0 16
BIANCONI 1995 DANZIG 1977 FALL ASPEN 1976 M 0 1 0 0 0 0 0 0 16
HAMAS 1989 DANZIG 1977 FALL ASPEN 1976 M 1 0 2 0 0 0 0 0 16
ELLE SEULE 1983 EXCLUSIVE NATIVE 1965 FALL ASPEN 1976 F 0 1 0 0 0 0 0 0 16
NORTHERN ASPEN 1982 NORTHERN DANCER 1961 FALL ASPEN 1976 F 0 1 0 0 1 0 0 0 16
FORT WOOD 1990 SADLER'S WELLS 1981 FALL ASPEN 1976 M 1 1 0 0 0 0 0 0 16
COLORADO DANCER 1986 SHAREEF DANCER 1980 FALL ASPEN 1976 F 0 1 1 0 0 0 0 0 16
TIMBER COUNTRY 1992 WOODMAN 1983 FALL ASPEN 1976 M 0 0 0 0 3 0 0 0 16
BIG BREAK 2010 DANSILI 1996 FAME AT LAST 1997 F 0 0 2 0 0 0 0 0 15
FAMOUS NAME 2005 DANSILI 1996 FAME AT LAST 1997 M 0 1 12 0 0 0 0 0 15
DANSE ROYALE 1990 CAERLEON 1980 FLAME OF TARA 1980 F 0 0 1 0 0 0 0 0 11
MARJU 1988 LAST TYCOON 1983 FLAME OF TARA 1980 M 1 0 1 0 0 0 0 0 11
FLAME OF ATHENS 1993 ROYAL ACADEMY 1987 FLAME OF TARA 1980 M 0 0 1 0 0 0 0 0 11
NEARCTIC FLAME 1986 SADLER'S WELLS 1981 FLAME OF TARA 1980 F 0 0 0 1 0 0 0 0 11
SALSABIL 1987 SADLER'S WELLS 1981 FLAME OF TARA 1980 F 5 0 1 0 0 0 0 0 11
BANKS HILL 1998 DANEHILL 1986 HASILI 1991 F 2 1 0 0 1 0 0 0 22
CACIQUE 2001 DANEHILL 1986 HASILI 1991 M 0 1 2 0 2 0 0 0 22
CHAMPS ELYSEES 2003 DANEHILL 1986 HASILI 1991 M 0 0 1 0 1 0 0 0 22
DANSILI 1996 DANEHILL 1986 HASILI 1991 M 0 1 2 0 0 0 0 0 22
INTERCONTINENTAL 2000 DANEHILL 1986 HASILI 1991 F 0 0 0 0 4 0 2 0 22
HEAT HAZE 1999 GREEN DESERT 1983 HASILI 1991 F 0 0 0 0 2 0 0 0 22
NASHWAN 1986 BLUSHING GROOM 1974 HEIGHT OF FASHION 1979 M 4 0 1 0 0 0 0 0 20
NAYEF 1998 GULCH 1984 HEIGHT OF FASHION 1979 M 3 0 4 0 0 0 0 0 20
SARAYIR 1994 MR PROSPECTOR 1970 HEIGHT OF FASHION 1979 F 0 0 0 1 0 0 0 0 20
WIJDAN 1991 MR PROSPECTOR 1970 HEIGHT OF FASHION 1979 F 0 0 0 2 0 0 0 0 20
ALWASMI 1984 NORTHERN DANCER 1961 HEIGHT OF FASHION 1979 M 0 0 1 0 0 0 0 0 20
UNFUWAIN 1985 NORTHERN DANCER 1961 HEIGHT OF FASHION 1979 M 0 2 2 0 0 0 0 0 20
HAWKER'S NEWS 1991 SADLER'S WELLS 1981 HIGH HAWK 1980 M 0 0 1 0 0 0 0 0 10
HUNTING HAWK 1990 SADLER'S WELLS 1981 HIGH HAWK 1980 M 0 1 0 0 0 0 0 0 10
IN THE WINGS 1986 SADLER'S WELLS 1981 HIGH HAWK 1980 M 2 0 2 0 1 0 0 0 10
MOROZOV 1999 SADLER'S WELLS 1981 HIGH HAWK 1980 M 0 1 2 0 0 0 0 0 10
SHARP CAT 1994 STORM CAT 1983 IN NEON 1982 F 0 0 0 0 7 0 0 0 10
ROYAL ANTHEM 1995 THEATRICAL 1982 IN NEON 1982 M 1 1 0 0 1 0 0 0 10
ASSERT 1979 BE MY GUEST 1974 IRISH BIRD 1970 M 4 2 0 0 0 0 0 0 10
EUROBIRD 1984 ELA-MANA-MOU 1976 IRISH BIRD 1970 F 1 1 0 0 0 0 0 0 10
BIKALA 1978 KALAMOUN 1970 IRISH BIRD 1970 M 2 0 0 0 0 0 0 0 10
DAY WALKER 2002 DR DEVIOUS 1989 ISLAND RACE 1995 M 0 0 1 0 0 0 0 0 10
SOLDIER HOLLOW 2000 IN THE WINGS 1986 ISLAND RACE 1995 M 4 1 4 0 0 0 0 0 10
FRANKEL 2008 GALILEO 1998 KIND 2001 M 10 1 1 0 0 0 0 0 18
NOBLE MISSION 2009 GALILEO 1998 KIND 2001 M 2 0 3 0 0 0 0 0 18
BULLET TRAIN 2007 SADLER'S WELLS 1981 KIND 2001 M 0 0 1 0 0 0 0 0 18
CRIMINAL TYPE 1985 ALYDAR 1975 KLEPTO 1970 M 0 0 0 0 4 0 0 0 15
ISOPACH 1977 REVIEWER 1966 KLEPTO 1970 M 1 2 3 0 0 0 0 0 15
ESTRAPADE 1980 VAGUELY NOBLE 1965 KLEPTO 1970 F 0 0 1 0 4 0 0 0 15
SHANGHAI 1989 PROCIDA 1981 KORVEYA 1982 M 1 0 0 0 0 0 0 0 14
BOSRA SHAM 1993 WOODMAN 1983 KORVEYA 1982 F 3 1 2 0 0 0 0 0 14
HECTOR PROTECTOR 1988 WOODMAN 1983 KORVEYA 1982 M 5 0 2 0 0 0 0 0 14
DYLAN THOMAS 2003 DANEHILL 1986 LAGRION 1989 M 6 1 0 0 0 0 0 0 13
QUEEN'S LOGIC 1999 GRAND LODGE 1991 LAGRION 1989 F 1 1 2 0 0 0 0 0 13
HOMECOMING QUEEN 2009 HOLY ROMAN EMPEROR 2004 LAGRION 1989 F 1 0 1 0 0 0 0 0 13
LANDO 1990 ACATENANGO 1982 LAUREA 1983 M 6 1 1 0 0 0 0 0 11
LAROCHE 1991 NEBOS 1976 LAUREA 1983 M 1 1 1 0 0 0 0 0 11
GESEDEH 1983 ELA-MANA-MOU 1976 LE MELODY 1971 F 0 0 1 0 0 0 0 0 14
ARDROSS 1976 RUN THE GANTLET 1968 LE MELODY 1971 M 3 7 3 0 0 0 0 0 14
LIRUNG 1982 CONNAUGHT 1965 LIRANGA 1973 M 2 1 5 0 0 0 0 0 12
LAGUNAS 1981 ILE DE BOURBON 1975 LIRANGA 1973 M 1 0 3 0 0 0 0 0 12
WARRSAN 1998 CAERLEON 1980 LUCAYAN PRINCESS 1983 M 4 1 1 0 0 0 0 0 17
CLOUD CASTLE 1995 IN THE WINGS 1986 LUCAYAN PRINCESS 1983 F 0 0 1 0 0 0 0 0 17
LUSO 1992 SALSE 1985 LUCAYAN PRINCESS 1983 M 4 0 4 0 0 0 0 0 17
NEEDLE GUN 1990 SURE BLADE 1983 LUCAYAN PRINCESS 1983 M 0 1 1 0 0 0 0 0 17
SOLSKJAER 2000 DANEHILL 1986 LYNDONVILLE 1988 M 0 1 0 0 0 0 0 0 13
YEATS 2001 SADLER'S WELLS 1981 LYNDONVILLE 1988 M 7 3 1 1 0 0 0 0 13
GREAT HEAVENS 2009 GALILEO 1998 MAGNIFICIENT STYLE 1993 F 1 1 0 0 0 0 0 0 12
NATHANIEL 2008 GALILEO 1998 MAGNIFICIENT STYLE 1993 M 2 1 0 0 0 0 0 0 12
PERCUSSIONIST 2001 SADLER'S WELLS 1981 MAGNIFICIENT STYLE 1993 M 0 1 1 0 0 0 0 0 12
PLAYFUL ACT 2002 SADLER'S WELLS 1981 MAGNIFICIENT STYLE 1993 F 1 2 0 0 0 0 0 0 12
ECHOES IN ETERNITY 2000 SPINNING WORLD 1993 MAGNIFICIENT STYLE 1993 F 0 2 0 0 0 0 0 0 12
GIANT'S CAUSEWAY 1997 STORM CAT 1983 MARIAH'S STORM 1991 M 6 1 1 0 0 0 0 0 10
YOU'RESOTHRILLING 2005 STORM CAT 1983 MARIAH'S STORM 1991 F 0 1 0 1 0 0 0 0 10
DANK 2009 DANSILI 1996 MASSKANA 1988 F 0 1 2 0 2 0 0 0 10
EAGLE MOUNTAIN 2004 ROCK OF GIBRALTAR 1999 MASSKANA 1988 M 0 2 1 0 0 0 0 0 10
WALLACE 1996 ROYAL ACADEMY 1987 MASSKANA 1988 M 0 0 0 1 0 0 0 0 10
SULK 1999 SELKIRK 1988 MASSKANA 1988 F 1 0 0 0 0 0 0 0 10
MINGUN 2000 A P INDY 1989 MIESQUE 1984 M 0 0 1 0 0 0 0 0 10
KINGMAMBO 1990 MR PROSPECTOR 1970 MIESQUE 1984 M 3 0 0 1 0 0 0 0 10
MIESQUE'S SON 1992 MR PROSPECTOR 1970 MIESQUE 1984 M 0 0 1 0 0 0 0 0 10
EAST OF THE MOON 1991 PRIVATE ACCOUNT 1976 MIESQUE 1984 F 3 0 0 0 0 0 0 0 10
MOON IS UP 1993 WOODMAN 1983 MIESQUE 1984 F 0 0 0 1 0 0 0 0 10
ASTRONEF 1984 BE MY GUEST 1974 MILL PRINCESS 1977 M 0 2 0 1 0 0 0 0 11
LAST TYCOON 1983 TRY MY BEST 1975 MILL PRINCESS 1977 M 2 0 3 0 1 0 0 0 11
THE PERFECT LIFE 1988 TRY MY BEST 1975 MILL PRINCESS 1977 F 0 0 2 0 0 0 0 0 11
MAXIOS 2008 MONSUN 1990 MOONLIGHT'S BOX 1996 M 2 1 2 0 0 0 0 0 11
BAGO 2001 NASHWAN 1986 MOONLIGHT'S BOX 1996 M 5 0 1 0 0 0 0 0 11
DIVINE PROPORTIONS 2002 KINGMAMBO 1990 MYTH TO REALITY 1986 F 5 1 2 0 0 0 0 0 13
WHIPPER 2001 MIESQUE'S SON 1992 MYTH TO REALITY 1986 M 3 1 0 1 0 0 0 0 13
FATIH 1980 ICECAPADE 1969 NATIVE NURSE 1970 M 0 0 0 0 1 0 0 0 10
LOVE SIGN 1977 SPANISH RIDDLE 1969 NATIVE NURSE 1970 F 0 0 0 0 7 0 0 0 10
MELODIST 1985 THE MINSTREL 1974 NATIVE NURSE 1970 F 2 0 0 0 0 0 0 0 10
ORFANO 1983 DSCHINGIS KHAN 1961 ORDINALE 1972 M 0 1 0 0 0 0 0 0 16
OROFINO 1978 DSCHINGIS KHAN 1961 ORDINALE 1972 M 3 6 1 0 0 0 0 0 16
ORDOS 1980 FRONTAL 1964 ORDINALE 1972 M 2 3 0 0 0 0 0 0 16
LOCHANGEL 1994 NIGHT SHIFT 1980 PECKITTS WELL 1982 F 1 0 0 0 0 0 0 0 11
LOCHSONG 1988 SONG 1966 PECKITTS WELL 1982 F 3 2 3 1 0 0 0 1 11
FREE EAGLE 2011 HIGH CHAPARRAL 1999 POLISHED GEM 2003 M 1 0 1 0 0 0 0 0 11
SAPPHIRE 2008 MEDICEAN 1997 POLISHED GEM 2003 F 0 1 2 0 0 0 0 0 11
CUSTOM CUT 2009 NOTNOWCATO 2002 POLISHED GEM 2003 M 0 2 4 0 0 0 0 0 11
ROSEATE TERN 1986 BLAKENEY 1966 ROSIA BAY 1977 F 1 1 1 0 0 0 0 0 10
IBN BEY 1984 MILL REEF 1968 ROSIA BAY 1977 M 4 3 0 0 0 0 0 0 10
DISTANT RELATIVE 1986 HABITAT 1966 ROYAL SISTER 1977 M 2 3 1 0 0 0 0 0 10
EZZOUD 1989 LAST TYCOON 1983 ROYAL SISTER 1977 M 3 0 1 0 0 0 0 0 10
ISLAND MAGIC 1991 INDIAN RIDGE 1985 RUM CAY 1985 M 0 0 1 0 0 0 0 0 15
PERSIAN PUNCH 1993 PERSIAN HEIGHTS 1985 RUM CAY 1985 M 0 4 10 0 0 0 0 0 15
SALVE REGINA 1999 MONSUN 1990 SACARINA 1992 F 1 1 0 0 0 0 0 0 15
SAMUM 1997 MONSUN 1990 SACARINA 1992 M 2 0 2 0 0 0 0 0 15
SCHIAPARELLI 2003 MONSUN 1990 SACARINA 1992 M 5 3 1 0 0 0 0 0 15
SAGACE 1980 LUTHIER 1965 SENECA 1973 M 3 1 3 0 0 0 0 0 12
SIMPLY GREAT 1979 MILL REEF 1968 SENECA 1973 M 0 1 0 0 0 0 0 0 12
STAR LIFT 1984 MILL REEF 1968 SENECA 1973 M 1 2 1 0 0 0 0 0 12
COMMANDER IN CHIEF 1990 DANCING BRAVE 1983 SLIGHTLY DANGEROUS 1979 M 2 0 0 0 0 0 0 0 12
YASHMAK 1994 DANZIG 1977 SLIGHTLY DANGEROUS 1979 F 0 1 0 0 1 0 0 0 12
WARNING 1985 KNOWN FACT 1977 SLIGHTLY DANGEROUS 1979 M 2 3 0 1 0 0 0 0 12
DUSHYANTOR 1993 SADLER'S WELLS 1981 SLIGHTLY DANGEROUS 1979 M 0 2 0 0 0 0 0 0 12
DOUBLE ECLIPSE 1992 ELA-MANA-MOU 1976 SOLAC 1977 M 0 1 1 2 0 0 0 0 16
DOUBLE TRIGGER 1991 ELA-MANA-MOU 1976 SOLAC 1977 M 1 3 8 0 0 0 0 0 16
TURFKONIG 1986 ANFIELD 1979 THEKLA 1980 M 2 4 3 0 0 0 0 0 10
TRYPHOSA 1992 BE MY GUEST 1974 THEKLA 1980 F 0 1 0 0 0 0 0 0 10
BARGER 1983 RIVERMAN 1969 TRILLION 1974 F 0 0 1 0 0 0 0 0 13
TRIPTYCH 1982 RIVERMAN 1969 TRILLION 1974 F 9 0 3 0 0 0 0 0 13
URBAN OCEAN 1996 BERING 1983 URBAN SEA 1989 M 0 0 1 1 0 0 0 0 20
SEA THE STARS 2006 CAPE CROSS 1994 URBAN SEA 1989 M 6 1 0 0 0 0 0 0 20
MY TYPHOON 2002 GIANT'S CAUSEWAY 1997 URBAN SEA 1989 F 0 0 0 0 2 1 0 0 20
ALL TOO BEAUTIFUL 2001 SADLER'S WELLS 1981 URBAN SEA 1989 F 0 0 1 0 0 0 0 0 20
BLACK SAM BELLAMY 1999 SADLER'S WELLS 1981 URBAN SEA 1989 M 2 0 0 0 0 0 0 0 20
GALILEO 1998 SADLER'S WELLS 1981 URBAN SEA 1989 M 3 0 1 1 0 0 0 0 20
ZENYATTA 2004 STREET CRY 1998 VERTIGINEUX 1995 F 0 0 0 0 8 0 0 0 11
BALANCE 2003 THUNDER GULCH 1992 VERTIGINEUX 1995 F 0 0 0 0 3 0 0 0 11
SIGHTSEEK 1999 DISTANT VIEW 1991 VIVIANA 1990 F 0 0 0 0 6 0 0 0 10
TATES CREEK 1998 RAHY 1985 VIVIANA 1990 F 0 0 0 0 2 1 1 0 10
WAR GAME (1) 1996 CAERLEON 1980 WALENSEE 1982 F 0 1 0 0 0 0 0 0 10
WESTERNER 1999 DANEHILL 1986 WALENSEE 1982 M 5 1 3 0 0 0 0 0 10

diomed · 21-02-2017 10:07pm

These are the above dams split into those that produced Group winners
to one sire; to different sires; to similar sires
In brackets are the dam rating, and the dam's dam rating
(? = rate not known; NR = non runner)

to one sire to many sires to similar sires
Ballerina (93; 117) Aviance (112; 106) Coup De Folie (112; NR)
Crown Treasure (?; ?) Binche (47; 103) Danseur Fabuleux (118; 124)
Doubly Sure (59; 124) Born Gold (86; ?) Dievotchka (NR; 95)
Fame At Last (98; ?) Brocade (121; 108) Doff The Derby (NR; 116)
Hasili (101; 88) Castle Moon (79; 81) Dubian (120; 118)
High Hawk (124; 112) Colorspin (118; 114) Early Rising (?; ?)
Korveya (116; ?) Daltawa (103; 116) Flame Of Tara (124; 109)
Mariah'S Storm (128; ?) Ebaziya (112; ?) Kind (108; 113)
Myth To Reality (129; ?) Fall Aspen (115; ?) Lagrion (70; ?)
Sacarina (NR; 114) Height Of Fashion (124; 129) Lyndonville (84; ?)
Solac (?; ?) In Neon (?; ?) Magnificient Style (106; ?)
Trillion (128; 116) Irish Bird (?; ?) Miesque (133; ?)
Island Race (99; 80) Mill Princess (122; ?)
Klepto (?; ?) Thekla (50; ?)
Laurea (?; 102) Vertigineux (?; 66)
Le Melody (102; 113) Walensee (126; ?)
Liranga (96; 68)
Lucayan Princess (111; 91)
Masskana (90; ?)
Moonlight's Box (NR; 119)
Native Nurse (?; NR)
Ordinale (104; 105)
Peckitts Well (96; 74)
Polished Gem (93; 121)
Rosia Bay (102; 107)
Royal Sister (?; 123)
Rum Cay (67; 124)
Seneca (128; 107)
Slightly Dangerous (116; ?)
Urban Sea (124; 101)
Viviana (?; NR)

diomed · 22-02-2017 3:41pm

In the list above you can see that the mare Castle Moon, rated 79, had three Group race winners: Moon Madness; Sheriff's Star; Lucky Moon.
I think Moon Madness, St Leger winner, was bred by Lavinia, Duchess Of Norfolk, and she was racing on a small budget. Afaik that is why she chose Vitiges, an inexpensive stallion.
You will see that she started out well, and despite success, she moved on to other stallions probably at a greater cost. Why change a winning formula?
If anyone has the time they should examine the pedigrees of these horses.

Moon Madness had:
Prince Bio (sire) duplicated in his 4th generation, producing a son and daughter.
Palestine (sire) twice in his 4th and 5th generation producing a son and daughter.
Hyperion (sire) in his 5th generation three times producing a daughter, son, and daughter.
Pharos (sire) in his 6th generation twice, producing a son and daughter.
There are a few more half siblings in his pedigree.
He was Castle Moon's best offspring.

name dob sire sdob dam ddob Rating
MOON PARADE 1982 WELSH PAGEANT 1966 CASTLE MOON 1975 73
MOON MADNESS 1983 VITIGES 1973 CASTLE MOON 1975 125
WOOD CHANTER 1984 VITIGES 1973 CASTLE MOON 1975 96
SHERIFF'S STAR 1985 POSSE 1977 CASTLE MOON 1975 123
LUCKY MOON 1987 TOUCHING WOOD 1979 CASTLE MOON 1975 110
MOON FESTIVAL 1988 BE MY GUEST 1974 CASTLE MOON 1975 79
MOON CARNIVAL 1990 BE MY GUEST 1974 CASTLE MOON 1975 94
MOON MAGIC 1992 POLISH PRECEDENT 1986 CASTLE MOON 1975 57
MOON MISCHIEF 1993 BE MY CHIEF 1987 CASTLE MOON 1975 79
MOON BLAST 1994 REPRIMAND 1985 CASTLE MOON 1975 87

diomed · 22-02-2017 7:21pm

“The Duchess owns a stud, which is managed by Dunlop, yet another strin to his bow. Most people would have found trainin 200 racehorses enough, but he likes to be involved with such things as the European Pattern Race Committee, a Jockey Club involved in research into the virus, and running the stud as well. The Duchess bought a share in a stallion called Vitiges, who turned out to be such a disaster that people wouldn’t send him the mares to submit to his embraces. He ended up being packed off to Japan, to stand at stud there.
The Duchess said “I had a mare called Castle Moon, which was quite well bred, but really rather small, and not very good either. So I put her to Vitiges – the result was Moon Madness. The mare has also given us Wood Chanter, who is a full brother to Moon Madness, and quite promising, and Sheriff’s Star, a good horse by Posse – and Posse was a failure at stud, So it is not the sire I have to thank, but the mare. She has a two-year-old in training by Mummy’s Pet called Moon Mystery, and a yearling by Touching Wood, and she is in foal again.”
Horsesweat and Tears by Simon Barnes (1988)

Mooooo · 25-02-2017 6:32pm

diomed wrote: »

Equinome have a gene speed test at €590 a horse.
Equinome have an Elite Performance Test at €1,450 a horse.

would each foal not be genomically tested before sale?
I don't know. Perhaps some horses are tested before sale but I do not know if the results must be revealed. They might be entered in a sale if they are tested and the results are unfavourable.

is there an index at which those figures are judged on in terms of performance and heritable traits?
Equinome have results for horses they tested. It looks like customers get results for one horse, not data for their horse and all other horses tested.
There are general statistics on the Equinome site but not with horse names.

Is there not somethings similar for horses and if so how does it fit in with your figures?
That data is valuable and I have nothing. My guess is you pay for one horse information only.

Genetic testing categorises a living foal by distance suitability and quality.
I'm trying to predict quality by analysing ancestors in a pedigree, and predicting potential quality before a foal is bred, or if already bred and unraced.

Labs making nice money there, 50 quid to genomically profile a calf

The Tetrarch · 11-10-2018 1:48pm

Previously I posted as diomed.

SIX GENERATION INBREEDING ANALYSIS OF RATED HORSES

In February 2017 I completed work on analyzing the inbreeding in the six generation pedigrees of 159,222 rated horses.
Inbreeding is the duplication of a horse in the pedigrees, typically a sire.
In their lifetime sire can produce thousands of foals, dam produce perhaps a dozen.
In my sample of 159,222 rated horses only 3,462 did not have inbreeding in the first six generations, 97.8% had inbreeding.

In my reading about inbreeding one author says speed is not inherited from the sire or dam, but is a product of inbreeding, typically in the 4th, 5th and 6th generations.
I am sure owners of stallions would not agree with that statement.

Inbreeding might seem simple to record. See a sire twice in a pedigree, and that is inbreeding.
It is more complex.
What should also be recorded is the sex of the offspring of that sire.
In the pedigree he could have produced two sons, a son and daughter, or two daughters.
And there are 2+4+8+16+32+64=126 ancestors in a six generation pedigree. It often happens that one, two, three, four or more sires each appear twice or more times in the six generations.

That is what I did in January and February 2017.
I wrote a database programs that analysed each of 159,222 pedigrees and recorded the output in a results file.
There were 37,057 colts, 50,335 geldings, 71,830 fillies.
There average ratings were: colts 93.79; geldings 74.45; fillies 74.43.

COMPARING COLTS RESULTS WITH GELDINGS RESULTS

When I did the work almost two years ago the average ratings for the 37,057 colts, 93.79, were much higher than the gelding ratings, 74.45.
At the time I did not purse the matter, assuming that it might be a case where identical pedigrees, say full sibling brothers, produced horses with different abilities, and the less able runner was gelded.
I though that it was a case of the pedigree clicking, firing, sparking, due to chance, and at other times going off like a wet firework.

This morning I decided to compare the results from the colts and geldings to see if there was anything to indicate why there was a 19.34 rating difference (93.79-74.45).

areas where the 37,057 colts rated average 93.79 differ from the 50,335 geldings rated average 74.45
sire inbreeding only examined
the colts (rating avg 93.79) on average have more groups 2.811 to 2.679 (4.9%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have more siblings 0.852 to 0.624 (36.6%) than the geldings (rating avg 74.45) ... I think this is siblings produced by sires and dams
the colts (rating avg 93.79) have more male offspring 7.111 to 6.955 (2.2%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have many more female offspring 5.237 to 4.439 (18.0%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have more s_mf 0.816 to 0.754 (8.2%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have more s_mmff 0.370 to 0.323 (14.5%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have less s_mm 0.738 to 0.792 (-6.9%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have less s_mmmm 0.257 to 0.288 (-10.5%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have more s_ff 0.415 to 0.363 (14.4%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have more s_ffff 0.057 to 0.040 (43.4%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have more s_one 3.546 to 3.134 (13.2%) than the geldings (rating avg 74.45)
the colts (rating avg 93.79) have more s_sibl 0.797 to 0.568 (40.3%) than the geldings (rating avg 74.45) ... I think this is siblings produced by sires

Notes:
groups: two or more of a duplicated sire is one group; two groups would be two different sires duplicated
e.g. Rainbow Quest (1981) rated 133, has four duplicated sire groups:
Nearco, producing two sons; Blandford, producing three sons and one daughter; Phalaris, producing a son and daughter; Teddy, producing two sons and a daughter

s_mf ... a sire group producing a son (m) and daughter (f)
s_mmff ... a sire group producing more than one son (m) and daughter (f) e.g two sons and one daughter.

The most common inbreeding you see is two or more sons of a sire, typically Northern Dancer or Danzig.
I have always though this a negative in pedigrees, and the numbers support this opinion.

The differences appear small, but expressed as percentage seem larger, and the rating difference of 19.34 is large.

The Tetrarch · 17-02-2019 12:25am

For a while I have not been satisfied with the pedigree analysis results I got in Jan/Feb 2017 with the average ratings for
(1) 18 different inbreeding types in a six generation pedigree (126 ancestors 2,4,8,16,32,64)
(2) the number of occurrences of the 18 inbreeding types

Immediately whoever is reading this thread can not understand what I am saying.

(1) different inbreeding types could be:
A sire appearing twice in a six generation pedigree producing a son and daughter.
I call this s_mf (i.e. sire producing male and female).
There could be s_mf; s_mm; s_ff, and the same for dams; d_mf; d_mm; d_ff, and many other types for three or more duplicated sires, full siblings ...
(2) the number of occurrences
Example: Northern Dancer twice, Native Dancer twice; Alycidon twice, all producing one son and one daughter, would be 3 occurrences of s_mf.

This is from the Jan/Feb 2017 results.

type occ s_mf count
colts 0 93.11 15847
colts 1 93.81 14034
colts 2 94.79 5621
colts 3 96.71 1300
colts 4 96.65 229
colts 5 107.57 23
colts 6 91.00 3

You can see that for each increase in number of occurrences of s_mf there is a rating increase for those colts (on average).
The problem with these averages is: the 15,847 colts averaging 93.11 rating also have in their pedigrees many other different inbreeding duplication types from the other 17 inbreeding types
e.g. two sons of a dam duplicated twice; three sons and two daughters of a sire duplicated five times.

The 15,847 colts above averaging 93.11 also had in those 15,847 six generation pedigrees these (I'm only showing 2 of the 17 other inbreeding types below)

type occ s_mm s_ff
colts 0 5981 10401
colts 1 6800 4324
colts 2 2588 994
colts 3 450 121
colts 4 28 6
colts 5 0 1

Explanation:
2,588 colts had 0 x s_mf and 2 x s_mm
4,324 colts had 0 x s_mf and 1 x s_ff

Removing those from the average rating calculation (previously 93.11 or more accurately 93.109926) I got a revised average of 92.42 (92.434242).
(the only reason for six places of decimals is just to help with program verification).
My methodology removing the effect of the other inbreeding may not be correct.

REVISED RATINGS
This shows the original and revised for s_mf
You can see the difference that getting rid / adjusting for the other inbreeding makes.
It is more obvious how sons and daughters of a duplicated sire are better than two sons of a duplicated sire (yet to be calculated/proved).
I think revising the s_mm will show figures lower than these below.

type occ s_mm count
colts 0 93.55 16074
colts 1 93.97 15396
colts 2 93.97 4857
colts 3 93.93 688
colts 4 92.50 42

Now all I need to do is the same "rating revision" program for another 27 occurrences x 17 other inbreeding types, 27 x 17 = 459.
The average for all the 37,057 colts is 93.7780.
I'll have a think about doing a second iteration of the ratings revision.
That might further differentiate the good inbreeding from the bad (increase the ratings differences).

My plan is to produce a formula that might approximate a horse rating just from the pedigree inbreeding.
In November 2018 I rewrote the pedigree analysis program but that is unfinished.

Using runner ratings may not have been a good idea.
It might be better to use the difference between the runner rating and the rating of its dam who produced the runner.
i.e. how much did the pedigree improve the runner (or impair it).

s_mf s_mf
type occ original revised
colts 0 93.11 92.44
colts 1 93.81 93.83
colts 2 94.79 95.77
colts 3 96.71 99.62
colts 4 96.65 99.53
colts 5 107.57 121.26
colts 6 91.00 88.40

The Tetrarch · 18-02-2019 4:37pm

If you are thinking of buying a broodmare for the flat I think it is a good idea to look at the sires of the females in her pedigree.
This is imo the weakest part of many broodmares, a selection of sires in her pedigree who are rarities in the breed.
These rarities are seldom found in the pedigrees of stallions at stud, and you can not get inbreeding (and imo speed/class) without duplications (a bit like hand clapping with one hand).

Gen 1 Gen 2 Gen 3 Gen 4 Gen 5 5 Gens
ancestors 2 4 8 16 32 62
male 1 2 4 8 16 31
male -> female 0 1 2 4 8 15

my mare 1 0 0 0 4 5 9
my mare 2 0 0 1 4 8 13

The above table shows there are 62 ancestors in the first five generations of a mare's pedigree.
If you take the five generation pedigree of a sire and put it with the five generation pedigree of a mare you get the six generation pedigree of their foal (2+4+8+16+32+64 = 126 ancestors).
There are 62 ancestors in 5 generations, and 31 of those are male.
These 31 male ancestors produce 15 males, 15 females, 1 unknown sex (the foal).
I think you should buy a mare with as many of the 166 sires listed below as possible in her first 5 generations i.e. a number close to 15.

I ran off a list from my data of 166 sires born before 1990 who produced over 1,000 in two generations (i.e. grandsons and granddaughters).
The number 1,000 is an arbitrary cut-off point, but indicates sires who produced sons and daughters who went on to produce sires.

I tested the idea with my two mares.
You can see that the second mare, bought in December 2018 at Newmarket, has almost the complete set with 13/15.
She has in her first five generations daughters of Buckpasser, Damascus, Danzig, Graustark, Herbager, In Reality, Nashua, Nearctic, Northern Dancer, Prince John, Rainbow Quest, Sir Ivor, Tom Fool.
It is a bit difficult to get sires of females in the first generations (Gen 2, Gen 3) from the list of 166 sires below as they probably are not long at stud
(i.e. they were born after 1990, my cut-off point) and have not yet got 1,000+ second generation offspring).

SIRES BORN BEFORE 1990 WITH 1,000+ SECOND GENERATION OFFSPRING
A P Indy (1989) Cadeaux Genereux (1985) Fair Trial (1932) Highest Honor (1983) Mahmoud (1933) Nureyev (1977) Round Table (1954) Storm Cat (1983)
Ack Ack (1966) Caerleon (1980) Fairway (1925) His Majesty (1968) Majestic Light (1973) Persian Bold (1975) Royal Academy (1987) Sunday Silence (1986)
Ahonoora (1975) Caro (1967) Fairy King (1982) Hoist The Flag (1968) Majestic Prince (1966) Phalaris (1913) Royal Charger (1942) Surumu (1974)
Alleged (1974) Cee's Tizzy (1987) Fappiano (1977) Hold Your Peace (1969) Mill Reef (1968) Pharly (1974) Sadler's Wells (1981) Teddy (1913)
Alydar (1975) Chief's Crown (1982) Farnesio (1974) Hyperion (1930) Miswaki (1978) Pharos (1920) Seattle Slew (1974) Thatch (1970)
Alzao (1980) Chieftain (1961) Forli (1963) Icecapade (1969) Mr Prospector (1970) Pleasant Colony (1978) Secretariat (1970) Thatching (1975)
Arctic Tern (1973) Cipayo (1974) Formidable (1975) In Reality (1964) Mt Livermore (1981) Polar Falcon (1987) Seeking The Gold (1985) The Minstrel (1974)
Aureole (1950) Clever Trick (1976) Forty Niner (1985) In The Wings (1986) Mtoto (1983) Precipitation (1933) Sharpen Up (1969) Timeless Moment (1970)
Be My Guest (1974) Conquistador Cielo (1979) Gainsborough (1915) Indian Ridge (1985) Mummy's Pet (1968) Prince John (1953) Shirley Heights (1975) Tom Fool (1949)
Biscay (1965) Court Martial (1942) Gone West (1984) Irish River (1976) Nashua (1952) Princequillo (1940) Sir Gallahad (1920) Tom Rolfe (1962)
Blandford (1919) Cox's Ridge (1974) Graustark (1963) Kaoru Star (1965) Naskra (1967) Private Account (1976) Sir Gaylord (1959) Tourbillon (1928)
Blenheim (1927) Crepello (1954) Great Above (1972) Kenmare (1975) Nasrullah (1940) Rahy (1985) Sir Ivor (1965) Turn-To (1951)
Bletchingly (1970) Damascus (1964) Green Dancer (1972) Key To The Mint (1969) Native Dancer (1950) Rainbow Quest (1981) Sir Tristram (1971) Unbridled (1987)
Bluebird (1984) Danehill (1986) Green Desert (1983) Kris (1976) Nearco (1935) Raise A Native (1961) Solario (1922) Vaguely Noble (1965)
Blushing Groom (1974) Danzig (1977) Grey Dawn (1962) Kris S (1977) Nearctic (1954) Raja Baba (1968) Son-In-Law (1911) Vice Regent (1967)
Bold Bidder (1962) Darshaan (1981) Grey Sovereign (1948) Last Tycoon (1983) Never Bend (1960) Red God (1954) Southern Halo (1983) Warning (14) (1985)
Bold Lad (1964) Deputy Minister (1979) Gulch (1984) Linamix (1987) Night Shift (1980) Red Ransom (1987) Sovereign Dancer (1975) Wavering Monarch (1979)
Bold Ruler (1954) Diesis (1980) Habitat (1966) Lord Gayle (1965) Nijinsky (1967) Relaunch (1976) Sovereign Path (1956) Woodman (1983)
Buckpasser (1963) Dixieland Band (1980) Hail To Reason (1958) Luthier (1965) Niniski (1976) Ribot (1952) Star Kingdom (1946) Young Generation (1976)
Busted (1963) Djebel (1937) Halo (1969) Lyphard (1969) Northern Dancer (1961) Riverman (1969) Stop The Music (1970)
Bustino (1971) Exclusive Native (1965) Herbager (1956) Machiavellian (1987) Northfields (1968) Roberto (1969) Storm Bird (1978)

tryfix · 19-02-2019 3:15am

The great mares of the modern era not only produce multiple top-class racehorses; the very best of them will also prove adept at passing on their genes to future generations through their sire sons. Remarkably, there are three mares since pattern racing commenced that have produced five sons that have gone on to sire at least one Group 1 winner. Strange as it may sound, producing multiple Group 1 sires, while being noteworthy for the mare, may not end up being so for the breed. To construct a more meaningful ranking, our mares must have sired two or more stallion sons each responsible for at least five Group 1 winners. Influential sires are key.

The full-brothers Sadler’s Wells and the once-raced Fairy King have their dam Fairy Bridge at the top of our list. Fairy Bridge, a May foal who cost Robert Sangster only $40,000 as a yearling, went unbeaten in her only two races, both at two, earning a 115 rating from Timeform. Two other sons, Perugino and Tate Gallery, have also contributed to her tally of 91 Group 1 winners. A mere 13 Group 1 winners behind Fairy Bridge is the great Urban Sea, dam of the equally great Galileo and Sea The Stars. It’s only a matter of time–most likely sometime in 2018–that this Arc heroine takes over at the top.

The next three mares–Weekend Surprise, My Charmer and Glorious Song–all belong to eras when foal crops were much smaller. So, whilst their numbers are less impressive, their achievements are still remarkable. Weekend Surprise produced five sons that sired at least one Group 1 winner, while Glorious Song is the only mare among the group to have had three sons sire five or more winners at the top level.

http://www.thoroughbreddailynews.com/fact-of-the-week-the-king-makers/

Hope you don't mind me dropping this into your thread. The incredible influence that Urban Sea has brought to European racing in recent times makes me think that the damside is becoming more and more important in the production of top racehorses.

Coolmore's ability to deliver multiple Gr 1 winners from exceptional individual broodmares such as You'resothrilling makes a bit of a mockery of the overemphasis on the stallion input into top racehorses.

You'resothrilling's first 5 foals ( the 3 Gp1 winners Marvelous, Gleneagles, Happily and Gp1 placed Coolmore and Taj Mahal ) are all by Galileo who is himself out of the mighty pedigree influencing broodmare Urban Sea. There's no accident to the brilliant success of the offspring of these super producing blue hens in Urban Sea and You'resothrilling. Those two ladies have both had foaled 3 or more Gr1 winners, 4 in Urban Sea's case .

These two mares make any sire's record look slack in comparison to their own abilities to produce top class racehorses. You'resothrilling herself is a daughter of another super producer broodmare in Mariah's Storm, dam of the top class racehorse and top US stallion Giant's Causeway. That Storm Cat Mariah's Storm mating produced at least 4 top class producers, You'resothrilling, Pearling ( dam of Decorated Knight ), Giant's Causeway multiple Champion US sire and Freud a minor champion sire in New York State.

tryfix · 19-02-2019 3:24am

.A couple of weeks ago the manager of a TrueNicks enrolled stallion called to tell us that a hypothetical mating had generated Dosage Figures that were all zeroes – zeroes for each category in the Dosage Profile; a Dosage Index of zero; and a Center of Distribution of zero.

A check confirmed that this was not an error, and nor was it the result of an obscure pedigree. The sire in question is a son of Candy Ride out of a Deputy Minister mare, and the dam is a daughter of Henny Hughes, the sire of the magnificent Beholder, and broodmare sire of Monomoy Girl, the Champion Three-Year-Old Filly elect of 2018. What, in fact, the result indicated is that Dosage itself is beginning to disappear from modern pedigrees.

http://cs.bloodhorse.com/blogs/truenicks/archive/2018/12/10/the-disappearance-of-dosage.aspx

Not quite sure what to make of that, but I do find that in US breeding the Dosage Index results make little sense in comparison to how the Dosage Index is very useful with European bred horses.

The Tetrarch · 19-02-2019 5:27pm

Feel free to post on the thread if you like.
Many would say what I post is identical to what comes out of the back end of a horse..

Thanks for that interesting chart of dams of important sires.
One of the inbreeding groups I record in a six generation pedigree is two sons of a dam.
If a dam can produce two sons who become sires, and those sires produce enough offspring to be common in pedigrees, then you know that dam is special.

I am inclined to think Urban Sea's dam, Allegretta (1978), is another strong influence.
Her pedigree is German although trained in England by Michael Stoute, rated 101 (2yo) and 97 (3yo). Her dam won over 5f.
Timeform said “will stay 12f” but she was tailed off in the 1981 English Oaks.
I watched that race on Youtube just now and have never seen a classic field spread out as much at the finish.
Allegretta is dam of English 2000 Guineas winner King’s Best. She also bred the useful Allez Les Trois, who produced French Derby winner, Anabaa Blue.

tryfix · 21-02-2019 1:22pm

The Tetrarch wrote: »

Feel free to post on the thread if you like.
Many would say what I post is identical to what comes out of the back end of a horse..

Thanks for that interesting chart of dams of important sires.
One of the inbreeding groups I record in a six generation pedigree is two sons of a dam.
If a dam can produce two sons who become sires, and those sires produce enough offspring to be common in pedigrees, then you know that dam is special.

I am inclined to think Urban Sea's dam, Allegretta (1978), is another strong influence.
Her pedigree is German although trained in England by Michael Stoute, rated 101 (2yo) and 97 (3yo). Her dam won over 5f.
Timeform said “will stay 12f” but she was tailed off in the 1981 English Oaks.
I watched that race on Youtube just now and have never seen a classic field spread out as much at the finish.
Allegretta is dam of English 2000 Guineas winner King’s Best. She also bred the useful Allez Les Trois, who produced French Derby winner, Anabaa Blue.

Your posts are excellent, keep them flowing.

Urban Sea's German heritage is quite speedy and one that has produced bucket loads of black type producers. This may explain the ability to comfortably stretch stamina from 1m to staying distances that many of the Urban Sea line seem to possess. Interestingly ( at least I think? ) Urban Sea seems to be free of Northern Dancer influence which means that maybe the outcross she provides for the Northern Dancer line is the secret of her success as a pedigree influence.

I think that you might be interested in this article which seems to suggest that inbreeding is a bad thing. Although inbreeding to Urban Sea seems to be very successful.

This morning you may see that we have extended the computations of the Coefficient of Inbreeding and Coefficient of Relatedness to 10 generations. These coefficients were previously calculated over 8 and 6 generations respectively and were done to that generation previously due to computational restrictions, i.e, the speed of the computers and the frequency of TrueNicks requests being run had an effect on report delivery time.

We have been able to extend the computation out to 10 generations thanks to the programmers at TJCIS, and it is also where a nice balance is found between the calculations of these coefficients and pedigree completeness. As we go further back into a pedigree, the completeness of the page starts to reduce as names are either founder horses, where no ancestor is known, or names where ancestry cannot be reasonably verified. This incompleteness has an effect on the calculations for inbreeding and relatedness as they then start be underestimated, especially where the incompleteness is skewed to one side of the pedigree over another.

As a reminder, we first placed these coefficients back in 2013 - you can see the blog post for that here. The coefficient of inbreeding (COI) was introduced by Sewell Wright back in 1922 to express the expected percentage of homozygosity (closeness to being identical) arising in a given mating. It can also be viewed as the average chance that any one gene pair is homozygous due to inheritance from a common ancestor. A low inbreeding coefficient means a low level of inbreeding, at least in paper terms. The vast majority of racehorses have an inbreeding coefficient of less than 5%. Inbreeding coefficients over 5% are unusual, and over 10% are very rare.

Recently a paper by Todd and colleagues pointed to higher levels of inbreeding having a negative impact on racehorse performance. Their analysis of data from 135,572 Thoroughbred horses in Australia revealed a strong negative relationship between Wright’s inbreeding coefficient and five measures of racing performance that encompass a range of factors that contribute to exercise performance. These included two measures that are based on the assumption that more successful individuals earn more prizemoney: cumulative prizemoney earnings and prizemoney earnings per start. They also included two measures of constitutional soundness: total number of race starts and career length and accounted for consistency of performance with the measure winning strike rate. The authors suggested that the negative relationship between inbreeding and performance can be explained by a genetic load of partially deleterious alleles still being carried by the population.

The Coefficient of Relatedness (COR) answers a slightly different question. The coefficient of relatedness provides a way of objectively assessing the similarity of two pedigrees by giving a number that is a direct measure of shared ancestry. In this case, the two pedigrees that we use are the sire and dam of a hypothetical or named horse mating. This figure will vary from the COI because it is possible, indeed quite frequent that a sire or dam can be inbred themselves, thus contributors to the inbreeding of their offspring, but the level of inbreeding between the sire and dam can be low. That is, one parent can be intensely inbred while the other a relative outcross. There has been no studies on the COR and its relationship to performance.

In pushing these two metrics out to 10 generations, we have also added the Pedigree Completeness to 10 generations, as well as a count of the unique ancestors in a pedigree from the first to the 10th generation. This also sets the platform for us to implement the use of the Ancestral History Coefficient, which in the paper from Todd and colleagues above, had a positive influence on racetrack performance. With this latter metric in place, it will give us the platform to develop TrueNicks 2.0, a significantly more predictive algorithm for matings, which we have in the works to develop and launch in 2019.

http://cs.bloodhorse.com/blogs/truenicks/archive/2019/02/04/inbreeding-and-relatedness-coefficients-extended-to-10-generations.aspx

The Tetrarch · 21-02-2019 7:48pm

tryfix wrote: »

Urban Sea's German heritage is quite speedy and one that has produced bucket loads of black type producers. This may explain the ability to comfortably stretch stamina from 1m to staying distances that many of the Urban Sea line seem to possess. Interestingly ( at least I think? ) Urban Sea seems to be free of Northern Dancer influence which means that maybe the outcross she provides for the Northern Dancer line is the secret of her success as a pedigree influence.

I think that you might be interested in this article which seems to suggest that inbreeding is a bad thing. Although inbreeding to Urban Sea seems to be very successful.

It might be that ancestors in the dam side of urban Sea are important to the breed in IRE & GB now.
I know Galtee More (1894) (twice) and Ard Patrick (1899) (six times) feature in the pedigree of Allegretta (1978), both out the mare Morganette.
Those two sires, good racers, absent from IRE & GB pedigrees for about eight generations might be the influence.
Ard Patrick won the English Derby, with Sceptre 4th.
Sceptre had earlier won the 1000 Guineas, 2000 Guineas, English Oaks.
The following year Ard Patrick beat Sceptre and that year's Derby winner Rock Sand in the Eclipse Stakes.
Galtee More won the English Triple Crown in 1897.
Morganette also produced Irish Derby winner Blairfinde.

The pedigree expert Les Brinsfield died in 2018.
He pointed out that when the mare La Troienne (1926-1954) went from France to the USA almost every horse she produced over there was successful - 14 named foals, 12 raced, 10 winners, 5 five stakes winners, 2 Hall of Fame inductees.
Brinsfield though the reason was La Troienne had a daughter, Young Giantess, of the first English Derby winner, Diomed in her pedigree.
Diomed was an unsuccessful sire in England, but when he went to the USA at 21 years of age, he was outstanding.
When many horses are successful later pedigrees become saturated with sons of that sire as everyone wants to cash in by standing sons of the successful sire.
Diomed left only sire sons in the USA. What was lacking in the ancestors in USA pedigrees from about 1870 onwards was daughters of Diomed.
Brinsfield mentioned that Young Giantess, a daughter of Diomed, was many times in La Troienne's pedigree, as well as another (unnamed) daughter of Diomed.
My version of TesioPoewer allows you list the ancestors of a horse to 12 generations. When I did that for La Troienne Young Giantess was there 57 times and the unnamed Diomed daughter 8 times.
My guess is if I ran deeper analysis (i.e. took the four grandparents of La Troienne) and did a search of each of them the number for Young Giantess would be much higher than 57.

On the question of inbreeding being good / inbreeding being bad, a poster on thoroughbredvillage.com.au ridiculed inbreeding and said DNA tests have proved errors in records therefore analysis is futile.
A few weeks later her was telling us that inbreeding to Herod was good, and linking to the research.
When researchers breed a good horse people will take notice, or they tell people how to breed a good horse ("hurlers on the ditch").

The Tetrarch · 26-02-2019 4:42pm

I wrote programs In Jan/Feb 2017 to analyse the inbreeding in the six generations pedigrees (2+4+8+16+32+64 = 126 ancestors) in 159,222 horses (37.057 colts; 50,335 geldings; 71,830 fillies).

At that time the results were promising.
There were 18 inbreeding types identified, 9 sire inbreeding duplication types, and 9 dam inbreeding types.
Examples of three groups (inbreeding types) are a sire duplicated twice (1) producing two sons, (2) producing a son and daughter, (3) producing two daughters).
Of course most pedigrees had only one or two inbreeding types, the most common being two sons of a duplicated sire back in the fourth and/or fifth generations.

The above is only one of six pieces of analysis, one done (above), five to do.
By "done" I mean reassessed. I have the Jan/Feb 2017 average ratings for the other five.
Done: sire inbreeding in colts
Not done: dam inbreeding in colts; sire inbreeding in geldings; dam inbreeding in geldings; sire inbreeding in fillies; dam inbreeding in fillies.

Why did I concentrate on sire inbreeding in colts?
In my data the colts were rated 93.78 average; geldings 74.45; fillies about the same as geldings.
It made more sense to concentrate on the horses with ratings about 20 points above the breed average.
And sire inbreeding is more common than dam inbreeding, as sires produce hundreds or thousands of offspring in a lifetime, broodmares perhaps a dozen.

I truncated the data in the above graph, removing ratings averages where the number of colts with an inbreeding type was 40 or less.
In one graph line the data is 93.5 (34,992 colts); 99.3 (2,021 colts); 95.2 (43 colts) (beside the text box [Value "X" Axis Major Gridlines]) and not shown 41.1 (1 colt).
The 95.2 dip in the graph line is misleading as it is only 43 colts.

Since the initial analysis two years ago I knew it could be improved.
In the last few weeks I wrote programs to improve the ratings.
The problem was the average for many inbreeding types did not vary far from the average for all 37,057 colts (93.778).
Almost every pedigree will have a few different inbreeding types, and the task was to as far as possible know how much each type contributes.

Think of it like 37,057 bags of licquorice allsorts, with a number on each bag giving the bag an attractiveness rating.
But the bags were not precisely filled by machines, with a fixed number of each sweet type - black and white rectangular pieces, yellow and white rectangles, white cylinders wrapped in licquorice, circular yellow pieces with a liquorice centre, and the nice round light blue ones with small balls on them (and pink ones).
Imagine the bags were filled by hand and the count of each type of licquorice sweet in each bag differs greatly.
You can count the black and white rectangles and get the average rating on the bags with 1 b&w rectangle, 2 b&w rectangles, 3 b&w rectangles and so on.
But that average ignores the other sweets in the bag, and they are raising or lowering the average.

What I did in the last few weeks was, for example, take all the pedigrees with one occurrence of a sire duplicated (i.e. twice in pedigree) producing two sons.
It was 16,074 of the 37,057 colts.
Then I counted the duplications of the other 17 inbreeding types (9 sire types, 9 dam types) in those 16,074 pedigrees.
I remove the influence of the other 17 inbreeding types.
The program to reassess the rating for each inbreeding type is 1700 lines, very repetitive.
Then it was simple to copy the program, make a small adjustment, and run it for the next inbreeding type, and so on.

GRAPH
The bottom axis should start at 0 and go to 7 (not 1 to 8 as shown).
The average of 93.778 was graphed, a straight line, but a white line does not show up well on a white background.
Where a graph line suddenly stops e.g. purple line 103.3 at count 4 (actually 3), that is because there were no high occurrences of that inbreeding type.

You want your colt to have the inbreeding types "light blue line"; "royal blue line", "cyan line"; "purple line".
You do not want your colt to have inbreeding types "yellow line" or the line that goes off the page on the right at 94.5 for 7 occurrences.
Where the graph lines are concentrated in the bottom left corner is where the high numbers of colts are i.e. the low sire inbreeding counts.
You want your colt to have a high occurrence count of the best types of inbreeding. A low count of these will not improve the colt above the herd.

A general rule is you want opposite sexes in an inbreeding.
If you have a sire duplicated you do not want two sons of that sire.
The same for a duplicated dam. You do not want two daughters from her.
Better to have a son and daughter of a duplicated sire or two daughters.

The problem for breeders is they already have the mare.
The sires available at stud may not give the inbreeding matches required.
Look for a mare that matches the sires now at stud.

Counts for all nine sire inbreeding types in colts:
187,925 (0, zero); 75,251 (1); 35,127 (2); 11,723 (3); 10,046 (4); 4,154 (5); 4,000 (6); 1,925 (7); 1,510(8); 788 (9).
You can see that a count of 0 or 1 of an inbreeding type is very common (shown on the graph as 1 and 2), and of course average colts are very common.

The Tetrarch · 28-02-2019 4:53pm

The Tetrarch wrote: »

The above is only one of six pieces of analysis, one done (above), five to do.
By "done" I mean reassessed. I have the Jan/Feb 2017 average ratings for the other five.
Done: sire inbreeding in colts
Not done: dam inbreeding in colts; sire inbreeding in geldings; dam inbreeding in geldings; sire inbreeding in fillies; dam inbreeding in fillies.

Now all six done.
Nothing obvious from the results, but I only glanced at them.
It is difficult to assess dam inbreeding for one reason.
There is seldom more than one dam inbreeding group, with only 9.4% of the 159,222 having dam inbreeding in six generations.
Pedigrees with female (dam) duplications: (0) 90.6%; (1) 5.6%; (2) 2.9%; (3+) 0.9%.
This is the occurrences of dam inbreeding groups in colts + geldings + fillies = 159,222 horses.
occ Perc
0 90.6%
1 5.6%
2 2.9%
3 0.4%
4+ 0.5%

"everything is learned by comparison"
At best in the 159,222 horses you are comparing large numbers with 0 occurrence (144,250) against those with 1 occurrence (8,928), 2 occurrences (4,618); 3 occurrences (583).
... there is not enough contrast.

However, with 9 dam inbreeding types, and colts, geldings, fillies = 9 x 3 = 27
... in 24 of 27 cases having 1 dam inbreeding group gave increased average ratings over 0 dam inbreeding group.
... in 8 of 15 groups (not 27 due to small count groups bypassed) those with 2 dam inbreeding groups had higher average ratings again over those with 1 inbreeding group.
... 5 of the 7 with 2 inbreeding groups who were not higher than 1 inbreeding group were still higher that the 0 inbreeding groups.

Comparing the colts (avg rating 93.8) to the geldings and fillies (avg rating ~ 74.5 each) might show something other than mentioned in a post above.

The Tetrarch · 28-02-2019 4:56pm

I enjoy looking at the USA stats in my old paperback copy of The Original 2008 Thoroughbred Times Racing Almanac (highly recommended and cheap second-hand).

Have a guess (facts USA 1930-2006)
Most foals by a broodmare: Betsy Ross (b. 1939)

23 foals

Most wins by broodmare's offspring (all her offspring): Slow and Easy (1922)

15 foals, 14 starters, 11 winners, 182 wins

Most winners by a broodmare: Dear Guinevere (1977)

19 foals, 17 winners

Most starts by broodmare's offspring (all her offspring): Our Patty (1933)

17 foals, 15 starters, 15 winners, 1,275 starts

Oldest broodmare to produce a named foal: Mercian Queen (1929)

age produced last foal 34

Oldest broodmare to produce a winner: Miss Jubilee (1951)

age foaled last winner 31

Oldest broodmare to produce a stakes winner: Fantasy Miss (1975)

age foaled last stakes winner 26 (Fanteria)

Champions who produced champions
Inside Information (1991) produced Smuggler (2002)
Flanders (1992) produced Surfside (1997)
Glorious Song (1976) produced Singspiel (1992)
Relaxing (1976) produced Easy Goer (1986)
Affectionately (1960) produced Personality (1967)
High Voltage (1952) produced Impressive (1963)
Misty Morn (1952) produced Bold Lad (1962)
Two Lea (1946) produced Tim Tam (1955)
Now What (1937) produced Next Move (1947)
Jacola ( 1935) produced Phalanx (1944)
Myrtlewood (1932) produced Duranza (1941)

They have many champions each year in the USA.
The "producers" included champions:
2yo female; 3yo female; older female; sprinter; handicap female

The "offspring" champions were:
2yo male; 3yo male; 2yo female; 3yo female; turf male; sprinter

From 1930 to 2006 11 champions produced champions.
77 years with about 10 champions a year ~770 champions
It is surprising how few champions the champions fillies produce.

The Tetrarch · 04-03-2019 2:24pm

The mare bought in December 2017 at the Arqana sale, Deauville, was covered on 28th February. She failed to get in foal 2018.
The mare bought at Tattersalls sale, Newmarket, in December 2018 is due to foal in about ten days time. All well she will travel to a stallion in Normandy in April.

The Tetrarch · 11-12-2019 3:31pm

This is a list of English Derby winners from 1945 to 2016, and a few earlier important Derby winners.
It shows (in my data) the number of offspring they produced (prog1),
the number of offspring those offspring produced (prog2: grandchildren),
and the number the grandchildren produced (prog3: great-grandchildren).
Sires born after around 1990 would have few great-grandchildren by 2019, those born after 2010 would have few progeny at this stage.
Up to around 1970 many stallion owners restricted their stallions to 40 mares a year.

A few sires had short stud careers: Troy; Golden Fleece; Shergar
Many sires were exported to Japan (High-Rise; Commander-In-Chief; Lammtarra; Oath), Australia (Quest For Fame),
USA (Nijinsky; Secreto), and would be under-represented in my data.

English Derby winners
name (dob)_____________prog1___prog2___prog3
Blenheim (1927)____________243___1292___4549
Hyperion (1930)____________370___3528___13015
Mahmoud (1933)___________238___1162___4300
Dante (1942)_______________128___603___2319
Airborne (1943)_____________33___56___132
Pearl Diver (1944)__________42___68___170
My Love (1945)_____________41___56___81
Nimbus (1946)______________132___341___771
Galcador (1947)____________38___29___34
Arctic Prince (1948)_________91___341___911
Tulyar (1949)______________92___361___1378
Pinza (1950)_______________90___202___356
Never Say Die (1951)_______191___996___2637
Phil Drake (1952)__________38___50___147
Lavandin (1953)____________38___70___150
Crepello (1954)____________252___1227___4638
Hard Ridden (1955)_________52___149___258
Parthia (1956)_____________80___156___281
St Paddy (1957)____________164___702___1583
Psidium (1958)_____________35___59___89
Larkspur (1959)____________25___47___77
Relko (1960)_______________186___749___1976
Santa Claus (1961)_________45___151___359
Sea-Bird (1962)____________102___807___3214
Charlottown (1963)_________61___148___337
Royal Palace (1964)________72___146___155
Sir Ivor (1965)____________714___2299___13161
Blakeney (1966)____________254___854___1651
Nijinsky (1967)____________847___9441___21934
Mill Reef (1968)___________252___2999___8841
Roberto (1969)_____________311___5259___11486
Morston (1970)_____________68___153___274
Snow Knight (1971)_________17___38___82
Grundy (1972)______________103___332___421
Empery (1973)______________51___119___415
The Minstrel (1974)________459___1613___3948
Shirley Heights (1975)_____463___2866___6854
Troy (1976)________________70___348___1162
Henbit (1977)______________82___126___111
Shergar (1978)_____________24___76___71
Golden Fleece (1979)_______31___88___96
Teenoso (1980)_____________86___110___94
Secreto (1981)_____________345___365___965
Slip Anchor (1982)_________299___470___367
Shahrastani (1983)_________113___197___190
Reference Point (1984)_____89___151___118
Kahyasi (1985)_____________335___441___1488
Nashwan (1986)_____________417___907___542
Quest For Fame (1987)______185___327___125
Generous (1988)____________297___459___344
Dr Devious (1989)__________190___198___32
Commander In Chief (1990)__37___37___3
Erhaab (1991)______________59___24___0
Lammtarra (1992)___________43___67___45
Shaamit (1993)_____________30___32___3
Benny The Dip (1994)_______50___28___1
High-Rise (1995)___________2___0___0
Oath (1996)________________4___1___0
Sinndar (1997)_____________326___198___3
Galileo (1998)_____________1461___2187___88
High Chaparral (1999)______643___149___2
Kris Kin (2000)____________26___2___0
North Light (2001)_________33___1___0
Motivator (2002)___________242___25___0
Sir Percy (2003)___________227___5___0
Authorized (2004)__________277___8___0
New Approach (2005)________378___44___0
Sea The Stars (2006)_______303___15___0
Workforce (2007)___________4___0___0
Pour Moi (2008)____________75___0___0
Camelot (2009)_____________65___0___0
Ruler Of The World (2010)__4___0___0
Australia (2011)___________23___0___0
Golden Horn (2012)_________1___0___0
Harzand (2013)_____________0___0___0
Wings Of Eagles (2014)_____0___0___0
Masar (2015)_______________0___0___0
Anthony Van Dyck (2016)____0___0___0

Top sires:
You can see that in a few generations their offspring dominate the breed.

name (dob)______________prog1___prog2___prog3
Nasrullah (1940)___________281___3747___20654
Bold Ruler (1954)__________290___5207___20713
Nearctic (1954)____________162___1848___23562
Hail To Reason (1958)______191___3123___15547
Nothern Dancer (1961)_____519___19163___95224
Raise A Native (1961)_______791___4340___36396
Nijinsky (1967)_____________847___9441___21934
Mr Prospector (1970)_______831___22105___54298
Blushing Groom (1974)______341___7843___15644
Danzig (1977)______________733___17219___33030
Storm Bird (1978)__________637___4265___18120

Before buying a mare for breeding it would imo be a good idea to check the sires in her pedigree, paying attention to the sires of females in her pedigree, and especially her dam line.
If the sires there have produced few prog1, prog2, prog3 (see Reference Point above) then that sire may not be passing quality to its foals.
And if you want to have inbreeding duplications of famous sires in a foal pedigree then a mare with sires in her pedigree with few offspring is not attractive.

The Tetrarch · 31-12-2019 1:44pm

Northern Dancer prog1 prog2 prog3 Totals Ratio
progeny of sire 519
grandchildren of sire 19,163
great-grandchildren of sire 95,225
. ======== ======== ======== ======== ========
Northern Dancer - colts 231
Northern Dancer - geldings 0
Northern Dancer - fillies 288
.
Northern Dancer - colts/colts 4,004
Northern Dancer - colts/geldings 2,115 17,677
Northern Dancer - colts/fillies 11,558
. 11.9
Northern Dancer - fillies/colts 379
Northern Dancer - fillies/geldings 118 1,486
Northern Dancer - fillies/fillies 989
.
Northern Dancer - colts/colts/colts 9,908
Northern Dancer - colts/colts/geldings 14,190
Northern Dancer - colts/colts/fillies 37,453
Northern Dancer - colts/fillies/colts 5,025 88,967
Northern Dancer - colts/fillies/geldings 5,839
Northern Dancer - colts/fillies/fillies 16,552
. 14.2
Northern Dancer - fillies/colts/colts 582
Northern Dancer - fillies/colts/geldings 597
Northern Dancer - fillies/colts/fillies 2,499
Northern Dancer - fillies/fillies/colts 540 6,258
Northern Dancer - fillies/fillies/geldings 434
Northern Dancer - fillies/fillies/fillies 1,606
.
519 19,163 95,225

Northern Dancer was possibly the most influential sire of the 20th century.
I look at many six generation pedigrees on screen (2+4+8+16+32+64 = 126 ancestors).
Northern Dancer (b 1961) is in almost every six generation pedigree.
He if often duplicated in pedigrees, the majority of times as the sire of sons in the pedigree.
I even had to widen a count field from one digit to two digits as a pedigree had twelve sons of Northern Dancer in six generations (out of 63 sires!).

The average thoroughbred generation is about eleven years.
Northern Dancer was born in 1961, 58 years ago.
He should feature, on average, in the 5th generation of horses born in 2019, and in earlier generations from his first crop in 1966 onwards.

I decided to analyse in detail the basic numbers of offspring of Northern Dancer (519 progeny, 19,193 grand-children, 95,225 great-grandchildren) in my data in more detail.
If you split the numbers into colts, geldings, fillies you see that Northern Dancer's 95,225 grand-children are predominately the produce of his stallion sons, 88,967 horses (93%).
He has 14.2 times more great-grandchildren decended from sons than from daughters (88,967/6,258 = 14.2).
This reflects the 1970s importations of sons on Northern Dancer into Europe, and the re-exportation of many of those sons back to north America as sires.

The great horse St Simon (b 1881) was so successful as a sire there was a rush to buy his sons. Over 100 of his sons found places at stud. And the sire line of St Simon died out.

You might point out that there is an imbalance in the numbers.
Surely Northern Dancer colts should have produced equal numbers of colts and fillies?
I have 4,004 colts (male); 2,115 geldings (male); 11,558 fillies (female) ... 6,119 males, 11,558 females, not 50%/50% but 34.6%/65.4%.
Than shows about 5,500+ males disappeared, probably because they were unsuitable for training. And many fillies were not retained.
These numbers are what is in my data, and are not the full crops.

A bit of trivia: the analysis of 28,868 sires and 266,750 dams born from 1900 onwards to produce the above information for each takes 29 minutes on my slower PC.

Is this "information" of any practical use?
It is backward looking. It looks at the horses produced by sires and dams who lived decades ago.
The data might be useful if you want to look at the breeding performance of sires and dams in the 3rd, 4th, 5th generation of a pedigree.
You want sires and dams who produced many children, grand-children, great-grandchildren (sorry about the use of "children").
You want to avoid sires and dams who failed at stud i.e. were bad producers / unpopular.
If you are looking at a sales catalogue you will see the black type of the dams on the dam line, and also the black type of the relations of those dams.
But you will have little idea of how many progeny trace back to the 5th dam, 4th dam on the dam line, or the same for the dam line of the sire of the lot on offer.

Here is a small summary of 2,180 dams born in 1961, the same year as Northern Dancer (the year 1961 is irrelevant, just taken at random).
1,723 dams born in 1961 had less than 10 great-grandchildren; 396 dams had 10 to 99; 50 dams had 100 to 999; 11 dams had 1,000+ great-grandchildren.
It is obvious that the 11 dams who produced the greatest number, 1,000+, produced these through sons or grandsons that were sires.
Can you name these dams born in 1961 who produced 1,000+ great-grandchildren? Thought not.
Can you name the 292 dams born in the 20th century who produced 1,000+ great-grandchildren?
These questions show how difficult it is to read a sales catalogue pedigree page trusting your memory to identify important horses.

What I will do in the next year is use this progeny data, and mark the ancestors of mares on offer at the 2019 breeding stock sales with the progeny counts.
It should be possible to do this in a few minutes.

In the next few posts below I will put up some sire and mare numbers.

Chinese proverb "Everything is learned by comparison."

The Tetrarch · 31-12-2019 2:06pm

Dams born in 1961 who produced the most descendants

dam prog1 prog2 prog3 p2_x1c p2_x1f p3_x1c p3_x1f p2_xc_2_xf p3_xc_2_xf
Bubbling Beauty (1961) 7 286 1501 269 17 1433 68 15.82 21.07
Camenae (1961) 6 327 1928 312 15 1055 873 20.80 1.21
Ciboulette (1961) 10 969 2548 920 49 1899 649 18.78 2.93
Iskra (1961) 6 253 1284 235 18 1242 42 13.06 29.57
Isolt (1961) 6 462 3568 451 11 3549 19 41.00 186.79
Luquillo (1961) 8 64 1241 44 20 88 1153 2.20 0.08
Our Martha (1961) 4 652 1392 646 6 1381 11 107.67 125.55
Picture Palace (1961) 9 280 1016 264 16 978 38 16.50 25.74
Rocchetta (1961) 6 500 4749 490 10 4730 19 49.00 248.95
Tsarina (1961) 1 818 1024 818 0 1024 0 0.00 0.00
Windmill Girl (1961) 6 346 1062 337 9 1023 39 37.44 26.23

Bubbling Beauty: dam of sire Arctic Tern, who was sire of Bering and Glacial Storm.
Camenae: dam of sires Camden Town and High Top (sire of Top Ville), second dam of Old Vic.
Ciboulette: dam of sires Barachois and Night Shift (sire of Azamour; Deportivo; Dyhim Diamond; Nicolotte, second dam of sires D'Accord; L'Enjoleur; Medaille D'Or; Snaadee.

I'll leave it at that. Guess the others. That is only one year, 1961.

The Tetrarch · 31-12-2019 2:17pm

Sires since 1900 with 6,000+ great-grandchildren
Near the end of the list sires are still adding prog3 numbers e.g. Galileo, son of Sadler's Wells is active.

sire sdob prog1 prog2 prog3 p2_x1c p2_x1f p3_x1c p3_x1f p2_xc_2_xf p3_xc_2_xf
Phalaris (1913) 1913 143 1,283 6,206 1,064 219 5,225 981 4.86 5.33
Teddy (1913) 1913 174 1,347 6,150 992 355 4,395 1,755 2.79 2.50
Gainsborough (1915) 1915 165 1,281 6,991 1,021 260 5,676 1,315 3.93 4.32
Pharos (1920) 1920 107 1,454 6,665 1,268 186 5,690 975 6.82 5.84
Hyperion (1930) 1930 370 3,531 13,020 2,782 749 9,183 3,837 3.71 2.39
Nearco (1935) 1935 318 2,795 14,487 2,221 574 10,896 3,591 3.87 3.03
Nasrullah (1940) 1940 281 3,747 20,654 3,191 556 17,839 2,815 5.74 6.34
Princequillo (1940) 1940 235 1,673 10,081 1,117 556 5,326 4,755 2.01 1.12
Native Dancer (1950) 1950 190 2,160 10,194 1,778 382 7,390 2,804 4.65 2.64
Turn-To (1951) 1951 162 1,346 9,488 1,032 314 8,412 1,076 3.29 7.82
Ribot (1952) 1952 242 3,148 9,842 2,722 426 7,528 2,314 6.39 3.25
Bold Ruler (1954) 1954 290 5,207 20,712 4,410 797 17,195 3,517 5.53 4.89
Nearctic (1954) 1954 162 1,848 23,562 1,516 332 22,748 814 4.57 27.95
Red God (1954) 1954 184 1,280 9,748 918 362 8,902 846 2.54 10.52
Round Table (1954) 1954 241 2,030 8,550 1,337 693 4,085 4,465 1.93 0.91
Herbager (1956) 1956 197 1,767 6,561 1,326 441 2,809 3,752 3.01 0.75
Hail To Reason (1958) 1958 191 3,123 15,547 2,638 485 13,880 1,667 5.44 8.33
Sir Gaylord (1959) 1959 237 2,368 10,260 1,747 621 8,220 2,040 2.81 4.03
Never Bend (1960) 1960 201 2,398 10,902 1,874 524 7,721 3,181 3.58 2.43
Northern Dancer (1961) 1961 519 19,163 95,225 17,677 1,486 88,967 6,258 11.90 14.22
Raise A Native (1961) 1961 790 4,340 36,398 3,110 1,230 31,947 4,451 2.53 7.18
Buckpasser (1963) 1963 213 1,808 14,353 1,029 779 2,822 11,531 1.32 0.24
Damascus (1964) 1964 641 3,266 10,879 2,303 963 6,471 4,408 2.39 1.47
In Reality (1964) 1964 474 3,020 7,356 2,386 634 4,361 2,995 3.76 1.46
Sir Ivor (1965) 1965 713 2,299 13,163 1,132 1,167 4,446 8,717 0.97 0.51
Habitat (1966) 1966 419 2,850 10,608 1,360 1,490 2,226 8,382 0.91 0.27
Caro (1967) 1967 272 3,960 8,190 3,292 668 4,084 4,106 4.93 0.99
Nijinsky (1967) 1967 847 9,441 21,934 7,779 1,662 14,346 7,588 4.68 1.89
Vice Regent (1967) 1967 552 2,566 8,646 1,822 744 6,089 2,557 2.45 2.38
Hoist The Flag (1968) 1968 162 2,496 7,345 2,019 477 3,404 3,941 4.23 0.86
Mill Reef (1968) 1968 252 2,999 8,841 2,212 787 5,828 3,013 2.81 1.93
Halo (1969) 1969 613 5,002 9,904 4,135 867 5,942 3,962 4.77 1.50
Lyphard (1969) 1969 763 6,502 11,854 5,008 1,494 7,056 4,798 3.35 1.47
Riverman (1969) 1969 514 2,907 7,172 1,629 1,278 3,316 3,856 1.27 0.86
Roberto (1969) 1969 311 5,259 11,484 4,396 863 8,925 2,559 5.09 3.49
Sharpen Up (1969) 1969 489 4,729 10,858 3,968 761 7,529 3,329 5.21 2.26
Mr Prospector (1970) 1970 831 22,107 54,305 19,892 2,215 43,197 11,108 8.98 3.89
Secretariat (1970) 1970 565 2,327 9,929 905 1,422 1,567 8,362 0.64 0.19
Blushing Groom (1974) 1974 341 7,843 15,644 6,820 1,023 11,620 4,024 6.67 2.89
Seattle Slew (1974) 1974 588 5,049 12,740 3,650 1,399 7,879 4,861 2.61 1.62
Ahonoora (1975) 1975 234 2,326 6,918 1,795 531 3,514 3,404 3.38 1.03
Shirley Heights (1975) 1975 463 2,866 6,853 1,559 1,307 4,295 2,558 1.19 1.68
Danzig (1977) 1977 733 17,221 33,034 15,759 1,462 30,726 2,308 10.78 13.31
Nureyev (1977) 1977 561 9,262 13,104 7,834 1,428 7,453 5,651 5.49 1.32
Storm Bird (1978) 1978 637 4,265 18,122 3,407 858 14,529 3,593 3.97 4.04
Sadler's Wells (1981) 1981 1,727 13,626 14,187 10,256 3,370 9,919 4,268 3.04 2.32
Danehill (1986) 1986 1,348 13,861 7,967 11,633 2,228 6,024 1,943 5.22 3.10

Notice in the right hand column the very low numbers for Herbager; Buckpasser; Sir Ivor; Habitat; Secretariat,
and to a lesser extent Round Table; Caro; Hoist The Flag; Riverman.

These failed to establish sire lines and are known through their daughters.

The Tetrarch · 02-01-2020 1:42pm

I am starting the new year recording my horse books in a database: title, author, author name, publisher, index, pages, year, cover, weight_gms, category, count.
(author is full name; author name is surname; index - number of index pages; cover - hardback/paperback; weight in grams; category - biography (trainer; jockey; breeder), betting, horse career, racing history and so on)
A few years back I counted over 900 books.
This is the first 100 books: weight 82.26 kg; pages 28,089

Title / Author / Year
100 Greatest Races / Nicholas Godfrey / 2005
A Bloody Good Winner / Dave Nevison / 2008
A Century Of Champions / John Randall & Tony Morris / 1999
Alex Bird, The Life And Secrets Of A Professional Punter / Alex Bird / 1985
American Classic Pedigrees 1914-2002 / Avelyn Hunter / 2003
Baffert, Dirt Road To The Derby / Bob Baffert / 1999
Bart, My Life / J B Cummings / 2009
Captain Mac-Hell, James Machell 1837-1902 / Richard Onslow / 1999
Champion Charlie, The Authorised Biography Of Charlie Swan / Mochael Clower / 1997
Derby Double, The Unique Story Of Racehorse Trainer Arthur Budgett / Bill Curling / 1977
Emperors Of The Turf, Twelve Months In The International Flat Racing Industry / Jamie Reid / 1989
Favourite Racehorses / Timeform / 1997
Following The Horses / Finbarr Slattery / 1996
Fred Archer, A Complete Story / John Welcome / 1990
Gentleman George?, The Contradictory Life Of George Duffield / George Duffield, Michael Tanner / 2002
Handy All The Way, A Trainer's Life / Peter Walwyn / 2000
Henry Cecil, Trainer Of Genius / Brough Scott / 2013
History Of Galway Races / Francis P M Hyland / 2008
Horsesweat And Tears / Simon Barnes / 1988
Horsetrader, Robert Sangster And The Rise And Fall Of The Sport Of Kings / Peter Robinson, Nick Robinson / 1993
Irish Flat Racing Records / John And Bob Kelly / 1997
It's Tougher At The Bottom / Jack Berry / 1991
Jenny Pitman, The Autobiography / Jenny Pitman / 1998
John Porter Of Kingsclere, An Autobiography / John Porter / 1919
Just My Story / Stephen Donoghue / 1922
Kings Of The Turf, Ireland's Top Racehorse Trainers / Michael Clower / 2007
Legacy Of Lexington / Kathleen H Kirsan / 2014
Lester, The Autobiography Of Lester Piggott / Lester Piggott / 1995
Lester, The Official Biography / Dick Francis / 1986
Lester's Derbys / Lester Piggott/Sean Magee / 2004
Making The Running, A Racing Life / Ian Balding / 2004
Mark Johnston, The Authorised Biography / Nick Townsend / 2006
Martin Moloney, A Legend In His Lifetime / Guy St John Williams / 2001
Martin Pipe, The Champion Trainer's Story / Martin Pipe, Richard Pitman / 1992
Men And Horses I Have Known / George Lambton / 1924
Mick Kinane, Big Race King / Michael Clower / 1996
My Racing Life / Tommy Weston / 1952
Northern Dancer, The Legend And The Legacy / Muriel Lennox / 1995
Nothing To Hide / Edward Hide, Mike Cattermole / 1989
On The Level / Henry Cecil / 1983
Pat On The Back. The Story Of Pat Eddery / Claude Duval / 1976
Prix de l'Arc de Triomphe 1949-1964 / Arthur Fitzgerald / 1982
Racing Maxims & Methods Of "Pittsburg Phil" / Edward W Cole /
Richard Hughes, A Weight Off My Mind, My Autobiography / Richard Hughes / 2012
Richard Ulbrich's Peerage Of Racehorses / Richard Ulbrich / 1994
Royal Ascot / Richard Onslow / 1990
Running Racing, The Jockey Club Years Since 1750 / John Tyrrel / 1997
Sam Darling's Reminiscences / Sam Darling / 1914
Scu, The Autobiography Of A Champion / Peter Scudamore / 1993
See How They Ran / Richard Ulbrich / 1981
Sire Lines Updated Edition / Abram S Hewitt / 2006
Stable Rat, Life In The Racing Stables / Philip Welsh / 1979
Tesio, Master Of Matings / Ken Mclean / 1984
The Breedon Book Of Horse Racing Records / Edward Ableson & John Tyrrel / 1993
The Captain, A Biography Of Captain Sir Cecil Boyd-Rochfort Royal Trainer / Bill Curling / 1970
The Daily Telegraph Chronicle Of Horse Racing / Norman Barrett / 1995
The Derby, The Offical Book Of The World's Greatest Race / Alastair Burnett/Tim Neligan / 1993
The Guinness Book Of Flat Racing / Gerry Cranham/Christipher Poole / 1990
The Guv'Nor, A Biography Of Noel Murless / Tim Fitzgeorge-Parker / 1980
The Guv'Nor, A Biography Of Noel Murless / Tim Fitzgeorge-Parker / 1980
The History Of The Derby Stakes / Roger Mortimer / 1973
The Irish Derby 1866-1979 / Guy St John Williams/Francis Hyland / 1980
The Irish Derby, Celebrating The 150th Running Of Ireland's
Greatest Race / Sean Magee / 2015
The Jockey Club / Roger Mortimer / 1958
The Master, A Personal Portrait Of Bart Cummings / Les Carlyon / 2011
The Melbourne Cup, Complete History And Statistics / Maurice Cavanough/Meurig Davies / 1971
The Sweeney Guide To The Irish Turf 1501-2001 / Tony & Annie Sweeney / 2002
The Thoroughbred Broodmare Book / Clive Harper / 2003
The Truth At Last / Charles Hawtrey / 1924
The Twenty Greatest Irish Trained Champions Of Flat Racing / Colm Long / 2005
The Wayward Lad, The Autobiography Of Graham Bradley / Graham Bradley / 2000
The Winning Look / Nick Mordin / 1994
Thoroughbred Pedigrees Simplified / Miles Napier / 1998
Thoroughbred Stallions / Tony Morris / 1990
Thoroughbreed Breeding Notes And Comments / Mordaunt Milner / 1987
Turform Annual 1988 - 2007 (20 years) / Turform / 1988
Upgrading Thoroughbreed Families / Jack Glengarry / 1995
Vincent O'Brien, The Man And The Legend / Raymond Smith / 1997
Willie Carson, Up Front, A Racing Biography / Willie Carson, Brough Scott / 1993
Winner All Right, 100 Years Of Irish Racing & Breeding / Guy St John Williams / 1999
Yankie Doodle Dandy, The Life And Times Of Tod Sloan / John Dizikes / 2000

The Tetrarch · 16-01-2020 4:57pm

The Tetrarch wrote: »

I am starting the new year recording my horse books in a database: title, author, author name, publisher, index, pages, year, cover, weight_gms, category, count.
A few years back I counted over 900 books.
This is the first 100 books: weight 82.26 kg; pages 28,089

I must have miscounted the books previously, or included general books.

Horse books:
count: 913 (vol 1, vol 2 of a book counted as two books)
weight 935.88 kg
average 1.025 kg
pages 634,541
average 695 pages

heaviest weight: 7.858 kgs (337 pages) Notable English and Irish Thoroughbreds (publ. 1983) by Mary Mountier and Tony Morris
other heavyweights: 4.124 kgs (556 pages) Thoroughbred Racing Stock (p 1960) by Lady Wentworth
3.780 kgs (1,042 pages) The Bloodstock Breeders' Review 1972

lightest weight: 0.035 kgs (47 pages) Make Your Betting Pay by Tony Stafford
other lightweights: 0.066 kg (64 pages) Counterpain, reflections of life as a bookie's cashier by Trixie
0.066 kg (48 pages) A glossary of french bloodstock terminology by Mary-Louise Kearney
The most important book of all 913 books is a lightweight: 0.137 kg (56 pages) The First Scientific Principles of Thoroughbred Breeding, Part 2, The Origin of Speed (p 1956) by Harold Hampton

most pages: 2,703 pages - The American Stud Book XXVII part 2. part 1 (2,188) + part 2 (2,703) = 4,891 pages
fewest pages: 40 pages - The Owner by Peter Curling (sketches/art)

There is a stack of books on the living room floor about five wide by four deep, waist high.
These are to be coded and put on shelves in groups e.g. biographies; betting; racehorses.
The fear is finding a box of books or a cupboard of books I missed.

The Tetrarch · 29-03-2020 5:24pm

This is a thread I started when my username was diomed.

In Jan/Feb 2017 I wrote pedigree inbreeding analysis programs and compared the rating of 159,222 horses to the inbreeding in those horses.
The inbreeding was split into 18 different types of inbreeding.
Examples of three different inbreeding types are: two sons of a duplicated sire; son and daughter of a duplicated sire; two daughters of a duplicated sire.
I found that different inbreeding types gave different results / different influence on the foal.

It was always my intention to revisit the work and re-write the programs.
There were a few small errors in the earlier version.
Other reasons for a re-write were improved (expanded) analysis, and to increase the pedigree analysed for each horse from six generations (126 ancestors: 2+4+8+16+32+64).

During the present coronavirus lock-in I have worked on the basics.
I expanded the pedigree from 6 generations (126 ancestors) to 10 generations (2,046 ancestors), 16 times the number of ancestors.
I have no idea if bigger is better.
At this stage all I have done is write a program to fill a file with 2,046 ancestors of a horse, and mark and number the duplication groups (01dup; 02dup; 03dup ) in those 10 generations (and the horses behind the duplications i.e parents, grandparents and so on).

An example is the sire Galileo (b 1998).
I always thought his pedigree was boring and it was difficult to explain where he got his quality.
If you look at Galileo's six generation pedigree you see only two duplication groups: Native Dancer (m) 4x5 daughter and son produced; Nasrullah (m) 6x6,6 two sons and one daughter produced.
This looks like a very average inbreeding pedigree.
Of course you can say he was by multiple times champion sire Sadler's Wells out of the Arc winner Urban Sea and that explains his quality.

What I found when the program ran over the 2,046 ancestor in the first 10 generations of Galileo's pedigree is 58 inbreeding duplication groups.
At this stage I have only run the program over a handful of other horses and the usual result is about 36 to 40 duplication groups.
I do not know if the large number of inbreeding groups in Galileo's pedigree is rare, or if it is significant.
I will now go back and add features to the basic duplication group identification: support horses (i.e. sire and dams that are parents of the duplicated horses); full sibling identification; comparing the duplication groups to each other to see if they have horses in common.

The Tetrarch · 29-03-2020 9:26pm

Part of the analysing inbreeding theory is that if a sire is duplicated in a pedigree two or more times it must be through a son and daughter or two daughters if you want a good horse. If Northern Dancer is twice in a pedigree (must be in the sire side and the dam side) I want to see a son of his and a daughter of his (or two daughters).
However, in modern pedigrees duplication groups with only sons of a duplicated sire are very, very common.
In my opinion that produces slow horses.

I found this remarkable.
For the last hour I have gone through the 58 duplication groups in Galileo's ten generation pedigree, 50 duplicated sire groups and 8 duplicated mare groups.
56 of the 58 duplicated sire groups are represented by offspring of both sexes or by daughters only.
Two groups had sons only of the duplicated sire: the 28th group, Dark Ronald (1905) had 9 sons; the 57th group, Bend Or (1877) had three sons.
21 duplication groups produced daughters only.
You will notice that there were 27 duplication groups in the pedigree before you get to the Dark Ronald group which is in the 8th generation (2 horses); 9th gen (3 horses); 10th gen (4 horses).

The above analysis was done by hand. I would prefer to write a program to do the counts automatically, and to test many other horses in a batch.

The Tetrarch · 14-05-2020 1:38pm

I am rearranging the directories on my PC and found this 2016 analysis of horse names. Perhaps I posted it on the forum at the time.
It shows the words most commonly used (not the full name).

Miss (3,088); Lady (3,064); La (2,440); The (1,839); Royal (1,379); My (1,030); Blue (996); Golden (990); Red (954); Sweet (839); Princess (828); Little (741); Silver (701); Queen (649); Star (619); High (612); Bold (596); Mr (563); Le (550); Rose (520); Gold (518); Fair (505); Prince (505); King (503); Belle (501); St (484); Our (476); Flying (474); Sea (467); Black (465); Lucky (447); First (443); All (441); El (440); Double (415); Sir (415); Dancing (404); A (394); Irish (390); Grand (385); No (384); Just (370); Lord (368); Love (368); Desert (367); Good (366); Northern (362); Big (361); Green (350); New (349); Magic (348); Wild (348); In (342); Gay (340); Top (338); Great (337); Regal (336); Secret (332); Mrs (330); Young (330); Indian (329); Night (311); Dark (310); Grey (306); Noble (303); Dance (302); Happy (300); Al (298); River (297); White (295); Sun (291); Mary (290); Super (285); One (280); Diamond (258); On (258); French (255); Native (255); Mister (252); Summer (252); Pretty (245); Dream (241); Fairy (241); Perfect (241); Go (240); Time (240); Bright (239); King's (234); Old (233); Spring (229); Be (223); Merry (222); War (221); Last (218); So (218); Master (216); Persian (215); Best (213); Classic (212); Queen's (211); Sharp (211); Sister (211); Snow (210); Rock (209); Captain (207); Light (206); Hot (202); Storm (202); I (201); Arctic (199); Roman (198); Crystal (196); Bella (192); Maid (192); Sunny (192); Midnight (185); Madame (184); She's (184); Sky (184); Full (183); Dame (182); Fast (181); Silent (181); Special (181); Cool (175); Free (175); Moon (173); Quick (172); Santa (172); Saint (170); Beau (169); Two (169); True (168); North (163); Three (163); Fine (161); Russian (161); Never (160); I'm (159); Smart (156); Brown (155); Key (154); Marie (153); Another (152); Cape (152); Petite (150); Forest (148); Pearl (148); Brave (147); Final (146); Lovely (146); Ma (146); Eastern (145); Pink (145); Spanish (145); Take (145); Highland (144); Princesse (144); Proud (144); Reine (144); Western (144); Celtic (143); Ocean (143); Always (141); Countess (141); Fleur (141); Island (141); Honey (140); Anna (138); Don't (138); Oh (138); Air (137); Bay (137); Fleet (137); Run (137); Majestic (136); Mountain (136); San (133); American (132); Don (132); Lake (132); It's (131); Rainbow (131); Musical (130); What (130); General (129); Call (128); Ice (128); May (128); Tudor (128); Morning (127); Swift (127); Bonnie (126); Maria (126); Fly (125); Court (124); Real (124); Southern (124); Misty (123); Private (122); Stormy (122); Pure (121); Silk (121); Come (119); Donna (119); Song (119); Fire (118); Victory (118); Angel (116); Out (116); Right (116); Welsh (116); Raise (115); Sally (114); Water (114); City (113); Divine (113); Imperial (113); Baby (112); Dawn (112); Madam (111); Well (111); Art (110); Evening (110); West (110); Crimson (109); More (109); Precious (109); Winter (108); Count (107); Crown (107); Hidden (107); Penny (106); Rare (106); Cherry (105); Mount (105); Peace (105); De (104); Major (104); Amber (103); Fancy (103); Flower (103); Tiger (102); Clear (101); Dubai (101); Easy (101); Spirit (101); Greek (100); Mighty (100); Not (100); Orange (100); Scarlet (99); Triple (99); Gallant (98); Gentle (98); Second (98); Heavenly (97); Long (97); Solar (97); Sovereign (97); Up (97); Charming (96); Elusive (96); Emerald (96); For (96); Iron (96); Jack (96); Make (96); Mystic (96); Country (95); Play (95); Polar (95); Port (95); Quiet (95); Battle (94); Hard (94); Polly (94); Simply (94); Better (93); Hello (93); John (93); Music (93); T (93); Beautiful (92); Hasty (92); Home (91); Only (91); April (90); Deep (90); Early (90); Lost (90); Polish (90); Touch (90); Wise (90); Agnes (89); Chief (89); Dear (89); Nice (89); Some (89); Fantastic (88); Mon (88); To (88); Very (88); Aunt (87); Game (87); Hill (87); Ruby (87); Four (86); Magical (86); Winning (86); Kiss (85); Castle (84); Champagne (84); Jet (84); Paris (84); Power (84); Rosa (84); Etoile (83); Forever (83); Her (83); Jane (83); Keep (83); Lily (83); Far (82); Premier (82); Singing (82); Sound (82); Stella (82); Turn (82); Yellow (82); Daring (81); Distant (81); Rich (81); Shy (81); Social (81); Born (80); Duchess (80); Moonlight (80); Sans (80); South (80); Street (80); Arabian (79); Blushing (79); Elegant (79); Kings (79); Prairie (79); Supreme (79); African (78); Duke (78); Legal (78); Man (78); Pride (78); Prime (78); Purple (78); With (78); Helen (77); Hurricane (77); Lucy (77); Nordic (77); Shining (77); Beauty (76); By (76); Delta (76); Luna (76); Rain (76); Rio (76); Sis (76); Back (75); Coral (75); Hi (75); Seattle (75); Straight (75); Tropical (75); Autumn (74); Candy (74); Sparkling (74); Speedy (74); Sugar (74); Eternal (73); Let's (73); Party (73); Seven (73); Twilight (73); Via (73); Annie (72); Flaming (72); Hail (72); Scottish (72); Shadow (72); She (72); Val (72); Jungle (71); Liberty (71); Mi (71); Mlle (71); Pleasant (71); Ring (71); Romantic (71); Running (71); Speed (71); Sunset (71); Wood (71); Blazing (70); Bonne (70); Five (70); Ivory (70); Mill (70); Son (70); Strong (70); Tea (70) and on and on.

The above are 24.2% of all words used in horse names in my data.
Total 345,527 words, of which 134,425 are unique.

Looking through the words a few used only once are:
Accelerating; Accelerator; Accidental; Achieved; Addict; Adjusted; Aeroplane; Aesthetic …….
Angel was used 116 time; Angle was used 0 times.

With Miss (3,088) and Lady (3,064) the most used what about their male equivalents? Mister was (252) and Lord was (368), about one tenth as common.

The Tetrarch · 29-06-2020 2:01pm

In post 86 above I mentioned analysis of Galileo's pedigree.
His ten generation pedigree is almost exclusively desirable inbreeding, with almost no negatives.
I checked a few famous sire failures. Their pedigrees had negatives.
This test was only on a handful of horses, top runners also sire failures.

Old pedigree program
In Jan/Feb 2017 I wrote a database program that analyses inbreeding in the first six generations of pedigrees (2+4+8+16+32+64 = 126 ancestors).
The inbreeding results were compared to the ratings of 159,000 horses (horse by horse).
I found there was a strong relationship between certain types of inbreeding and higher ratings. The reverse was true. A few inbreeding types gave lower ratings.
A son and daughter of a duplicated sire (i.e. a sire twice or more in a pedigree and on both sides) was much better than two sons of a duplicated sire (the most common inbreeding).

The inbreeding types are many:
Duplicated sire: son & daughter; two sons; two daughters
Duplicated dam: son & daughter; two sons; two daughters
Other duplications are offspring of full siblings (horses with the same parents). These can be full sibling brothers (e.g. Sadler's Wells and Fairy King; Kris and Diesis); or full sibling sisters; or a full sibling brother and sister (e.g. Hector Protector and Bosra Sham) and they can produce son and daughter, two sons, two daughters.
There can also be 7/8 siblings or 3/4 siblings (e.g. two horses by Galileo out of Danehill mares), and their offspring.
Another complication is an inbreeding group can be more than two sires (or two dams). A sire duplicated 3, 4, 5 or more times is common.

New program
For about three months I have been writing a new pedigree analysis program.
There were a few programming errors in the Jan/Feb 2017 program, and the analysis it generated was too simple.
This time I went for a bigger pedigree for each horse, 10 generations (2,046 ancestors), or 16 times as many ancestors.
I was not too concerned about analysing the 9th and 10th generations but extending the analysis beyond six generation was informative.
What I found in Galileo was two horses in his first six generations on the sire side became part of a duplication group when I took in the 7th and 8th generations on the dam side.
There is no rule that everything is known from the sire and dam (many hold this view); or from a three generation pedigree (sales catalogue); or from four generations (Dosage Index calculation).

Work done:
Duplication groups identified (can be up to 70 groups in 10 generations).
Full Siblings identified.
Support horses identified (parents or grandparents of duplicated horses outside the duplication groups)
7/8, 3/4 and other near siblings identified (15/16; 5/8).

Work to do:
Comparison of duplication groups to each other (are they related?)
Marking of 7/8, 3/4 siblings.
The program for these two is done and running but not built into the main program.
This morning a program is comparing 146,000 horses (146,000 vs 146,000) and this program will be built into the main program. If there are 40 duplication groups it will compare 40 vs 40.

Personal computers
2008 PC: stopped working in May 2020, and has been brought back to life.
It is with the IT repair person. He is building another PC that will become my reliable PC for old software.
2006 PC: I am using this to write the new program. It is three times faster than the 2008 PC.
2020 PC: This has nothing on it, and I use it for browsing boards.ie, racingpost.com and other internet sites.

My plan is to use two or three PCs at once to run the new program.
My old program analysed 51 pedigrees a second on the 2016 PC. The new program analyses 2 pedigrees a second on the 2016 PC.
I timed the new program section by section as I wrote it looking for small time savings.
An example of a saving is the comparison of 146,000 horses (list 1) vs 146,000 horses (list 2) (the same horses).
If you compare A (list 1) v B (list 2) you do not need to compare B (list 1) v A (list 2).
As far as possible I do the work before I run the analysis ("here is one I prepared earlier").
Instead of looking up the sire and dam of a horse (2 horses) the new program looks up the parents, grandparents, great-grandparents (14 horses).

What use is a program that analyses pedigrees?
If a program can analyse one pedigree it can analyse many pedigrees.
I think the main benefit is analysing breeding stock.
There are breeding stock sales in IRE, GB, FR in Nov/Dec each year.
If you have the pedigrees of all the mares at those sales (about 3,000) you can prepare test-mating of those mares with every stallion in IRE, GB, FR, and pick the best stallion/mare combination.
While you are at it you can also analyse the pedigree of the foal the mare is carrying (almost all mares sold are pregnant), and her breeding potential (if a filly).

The Tetrarch · 11-07-2020 12:32pm

The Tetrarch wrote: »

Work to do:
Comparison of duplication groups to each other (are they related?)
Marking of 7/8, 3/4 siblings.
The program for these two is done and running but not built into the main program.

Since that post I spent time speeding up the program.
The above two pieces are not in the main program yet.
They may be slow. It might be best to leave them out of the main program, but could be used later to reanalyse small samples of good horses.

Program speed analysing one horse is about 0.561 seconds each horse on a fast PC.
My old 2017 program took about 0.020 seconds each horse but analysed a lot less pedigree.
The program uses a load file that can contain an unlimited number of horses.
The program loads one horse, analyses it, puts the result in a results file, then loads the second horse and repeats.
In the past few weeks I learned new programming tricks, but the reality is I learned stuff I should have known and used earlier.
The slow part of the program below, dup_all, can be adjusted.
At present it finds as many duplicate groups as possible in 10 generations.
The most I found is about 65, but I can quickly change the program to find e.g. the first 35 groups and analyse those only, and that will increase speed.

Program names and seconds taken for one horse
start 0.561seconds (all the programs below together)
… prgs 0.546s (is a summary prg that runs the programs below)
...… all 0.063s … (generates a 10 generation, 2,047 ancestor pedigree)
...… dup_all 0.327s ... (identifies the duplications groups in the 2,047 ancestors, up to 70 groups)
...… supp 0.016s … (identifies non-duplication group horses who are parents or grandparents (i.e. support, of duplication group horses)
…... sibl 0.015s … (identifies full-siblings)
...… grade_groups 0.110s … (counts the dupl groups, identifies their offspring sex, categorises the groups)
...… group_analysis_all 0.015s … (groups by size and type e.g. mmf.mff is a six horse dupl group with two sons (m), one daughter (f) sire side, and one son, two daughters dam side)
...… results_calc 0.000s … (counts each group, puts the info into a one line result for each horse)

The Tetrarch · 19-07-2020 4:46pm

The Tetrarch wrote: »

Work to do:
Comparison of duplication groups to each other (are they related?)
Marking of 7/8, 3/4 siblings.
The program for these two is done and running but not built into the main program.

The Tetrarch wrote: »

Since that post I spent time speeding up the program.
The above two pieces are not in the main program yet.
They may be slow. It might be best to leave them out of the main program, but could be used later to reanalyse small samples of good horses.

These last two pieces are finished, and are in one program.
The running time for that program is 0.031s each horse.

This is a bit of a cheat.
The main program takes about 0.6s a horse.
To do this final analysis for each horse would take another 60 seconds each horse i.e. increase the analysis time per horse from 0.6s to 60.6s.
Instead of running the analysis for each horse (about 60 seconds) I identified the horses in history that are likely to be in almost all pedigrees.
It was 1,840 horses (from c 1900 to 2020).
The analysis was 1840 x 1840 / 2 = 1,692,800 "horses" and a separate program took 11h 34m to do this.
That analysis is in a results file that is looked up by the final version of the program. A lookup that takes 0.031s is better than about 60s if done live.
If I find horses not in the 1,840 I will add them and add their analysis to the results file. In time almost all important ancestors will be covered.

The next step is to run the total program with a big load file of thousands of horses, and a big results file to take the output.
This might throw up a few issues but hopefully nothing much.
The work has taken almost five months.

The Tetrarch · 25-07-2020 8:50pm

Tonight I finished the pedigree analysis program, but these things have a habit of never finishing.

The results file has 75 numbers on one line for each horse.
The next step is running the program with a large load file of a few thousand horses.
Often programs stop for a simple reason such as one results field being too narrow.
In Jan/Feb 2017 I compared the previous pedigree analysis program results to horse ratings, and that is where this is heading.

The Tetrarch · 03-08-2020 12:10pm

The Tetrarch wrote: »

In Jan/Feb 2017 I compared the previous pedigree analysis program results to horse ratings, and that is where this is heading.

The early comparisons of the inbreeding counts to ratings are disappointing.

The inbreeding counts are from generation 1 to generation 10
i.e. an inbreeding in the 4th generation of both the sire and dam (4x4) and an inbreeding in the 10th generation (or any other generation) were both counted as one.
Obviously an inbreeding group in the 4th generation should have more influence on the foal (and on a rating) than an inbreeding group in the 10th generation.
My analysis in Jan/Feb 2017 was on six generation pedigrees, where the majority of inbreeding was in the 4th, 5th, 6th generations, and I did not feel it necessary to give weights to different generations.
That 2017 program proved that ratings varied with the type of inbreeding and the inbreeding counts.

H E Keylock in The Mating of Thoroughbred Horses (1942, 95 pages) suggested that the influence of ancestors on a foal is 1/2+1/4+1/8+1/16+1/32+1/64+1/128 ... , a series that approaches 1, with the two parents contributing 50%, the four grandparents 25%, the eight great-grandparents 12.5% and so on. This would have a parent four times more influential than a grandparent (50%/2 v 25%/4).

Other books prefer 0.7 i.e. two duplicated horses in the 4th generation (2x1) are about as influential as three in the 5th generation (3x.7).

Keylock quotes J B Robertson who agreed that the above formula (Galton's law) was true as a general statement (late ancestors have greater influence than distant ones), but is/could be untrue where characteristics are transmitted independently and show no tendency to blend (an example is coat colour).

My next programming step is to copy all the work to new directories, and make changes there.
I will keep the work done year to date as the extraction of inbreeding groups is sound.

One feature I added since 2017 was a change to the analysis of a sire duplication group that produce a son and daughter (s_mf = sire producing a male and female).
I split s_mf into s_mf and s_fm.
The first is a sire producing a son in the sire pedigree of the foal, and a daughter in the dam side.
The second is a sire producing a daughter in the sire pedigree of the foal, and a son in the dam side.
Early numbers indicate that s_mf produces a higher rating than s_fm (but that is on small data).
The reason might be that s_mf is a duplication from the sire side of the pedigree of a major sire (his son) on the sire line or broodmare sire of a top sire, with a daughter of that sire in the dam of the foal.
s_fm could be duplication from the sire side of the pedigree of a minor sire (his daughter) on a dam line of the sire or on the dam line of the broodmare sire, or on the dam line, with a son of that minor sire in the dam of the foal.

It would be nice if, instead of a "son and daughter of an unnamed sire", I could gather the names of the duplicated sires.
I notice that only a small number of sires occur frequently as duplications in pedigrees.

Time for a proverb and a quote:
"Everything is learned by comparison."
"I did not progress until I learned to reflect."

The Tetrarch · 27-08-2020 12:40pm

Since my last post three weeks ago I have been working on tidying data.
The ratings file with 159,000+ horses needed to be reviewed.

From Jan/Feb 2017 until now, August 2020, the names in my pedigree database have changed a little
e.g. the sire Warning (1985) had a name change to Warning (14) because I entered another horse into the pedigree database, also Warning (1985).
You can not have two horses with the same name.
These were changed to Warning (14) [by Known Fact out of Slightly Dangerous] and Warning (2) [by Albaro out of Chilton Blue].
The numbers in brackets (14) and (2) are the Bruce Lowe family numbers, useful in differentiating when the name and year of birth are identical.
These name changes in the pedigree database, perhaps 3% of the 159,000 rated horses, had to be updated in the ratings database.

...........................................................................................................

Back to the new pedigree analysis program and how to fix the poor results.

In the original Jan/Feb 2017 pedigree program I did not differentiate between inbreeding duplications in different generations.
For example, an inbreeding group of a son and daughter of a duplicated sire, the sire in the 4th and 5th generations, 4x5, would be counted as 1.
The same for an inbreeding group of a son and daughter of a duplicated sire, the sire in the 6th and 6th generations, 6x6, would be counted as 1.
Obviously, the closer inbreeding 4x5 probably has more influence on the foal than the more distant 6x6.

With almost all the inbreeding in the original Jan/Feb 2017 six generation pedigree program in the 4th, 5th, 6th generations the question of giving greater weight to inbreeding in the 4th generation over that in the 5th and 6th generations was ignored. The results were still informative.

But with the unfinished 2020 ten generation pedigree program it is obvious that inbreeding in the 4th generation and inbreeding in the 10th generation should have vastly different influences.
In my first results a few weeks ago I ignored this, giving every generation equal value i.e. a weight of 1.0 (see below)**

Using my test case of Galileo (1998) I am experimenting.
Galileo has 58 inbreeding groups in his first 10 generations. These have 199 duplicated horses.
4th gen (1); 5th gen (3); 6th gen (6); 7th gen (22); 8th gen (34); 9th gen (56); 10th gen (77) = 199

I know many do not agree with inbreeding analysis. 100% of the horse DNA is in the horse.
Others say you need look no further than the sire and dam.
I think you must agree that the DNA in the horse is also in the sire and dam. We do not know what DNA the horse received.
The same for the grandparents. The DNA in the horse is also found in the grandparents.
And the same for the great-grandparents, and earlier generations.
The DNA in the horse came from ancestors. It did not come from elsewhere.

Giving different weights to inbreeding in different generations for Galileo:

Weight given / generation / percentage in that generation
Weight 1.0**: 4th (0.5%); 5th (1.5%); 6th (3.0%); 7th (11.1%); 8th (17.1%); 9th (28.1%); 10th (38.7%)
This was what was applied to Galileo's pedigree weeks ago.
You can see far too much influence was assumed for the earlier generations (8th, 9th, 10th).

Weight 0.3**: 4th (28.6%); 5th (25.7%); 6th (15.4%); 7th (17.0%); 8th (7.9%); 9th (3.9%); 10th (1.6%)
Weight .05**: 4th (8.5%); 5th (12.7%); 6th (12.7%); 7th (23.2%); 8th (18.0%); 9th (14.8%); 10th (10.2%)
Weight 0.7**: 4th (2.5%); 5th (5.2%); 6th (7.3%); 7th (18.8%); 8th (20.3%); 9th (23.4%); 10th (22.5%)
Weight 2.0**: 4th (0.0%); 5th (0.1%); 6th (0.3%); 7th (2.4%); 8th (7.3%); 9th (24.0%); 10th (66.0%)

Weight 0.3 - with the 4th generation given a value of 1.0, the 5th generation gets 0.3, the 6th generation 0.09. This gives far too much weight to the closer generations.
In this case, the one duplicated horse in the 4th generation is given a value of 28.6%. 77 duplicated horses in the 10th generation get 1.6% for all of them. Nonsense.
Weight 0.5 - this is the weighting I will use for the moment.
It assumes influence is halved each generation i.e. a grandparent has twice the influence of a great-grandparent.
Weight 0.7 - this is the weighting recommended in a pedigree analysis book I like. I think it gives too much influence to earlier (8th, 9th, 10th) generations.
Weight 2.0 - this gives a nonsense valuation, with two thirds of the influence in Galileo's pedigree attributed to the duplications in the 10th generation of his pedigree. I did this calculation to show that a Weight under 1.0 must be correct.

There have been many theories about thoroughbred pedigrees.
My stance is to let the numbers tell me what analysis works.

From "The Mating of Thoroughbred Horses" (1942) by H E Keylock
"The following conclusions are arrived at with regards to the inheritance of characteristics
1. Good performers on the race course cannot be selected by their conformation or other visible characteristics.
2. Varying characteristics do not follow the female or male line of descent, but follow an unpredictable course.
3. Neither the sire nor the dam can convey any characteristics to their progeny and the progeny inherits all the characteristics from its four grandparents.
4. Some animals usually pass on the necessary winning characteristics and some animals usually do not pass on these characteristics.
If they do pass them on then these characteristics are not inherited from ancestors in the 1st, 3rd, 5th, and 7th generations, but from ancestors in the 2nd, 4th, 6th and 8th generations."

I agree with point 1. and 2.
H E Keylock suggested that influence in pedigrees by generation is (1/2)+(1/4)+(1/8)+(1/16)+(1/32)+(1/64) .....
That gives each parent 1/4 influence, each grandparent 1/16 influence, each great-grandparent 1/64 influence (Weight 0.25).

tryfix · 27-08-2020 8:12pm

The Tetrarch wrote: »

Since my last post three weeks ago I have been working on tidying data.
The ratings file with 159,000+ horses needed to be reviewed.

From Jan/Feb 2017 until now, August 2020, the names in my pedigree database have changed a little
e.g. the sire Warning (1985) had a name change to Warning (14) because I entered another horse into the pedigree database, also Warning (1985).
You can not have two horses with the same name.
These were changed to Warning (14) [by Known Fact out of Slightly Dangerous] and Warning (2) [by Albaro out of Chilton Blue].
The numbers in brackets (14) and (2) are the Bruce Lowe family numbers, useful in differentiating when the name and year of birth are identical.
These name changes in the pedigree database, perhaps 3% of the 159,000 rated horses, had to be updated in the ratings database.

...........................................................................................................

Back to the new pedigree analysis program and how to fix the poor results.

In the original Jan/Feb 2017 pedigree program I did not differentiate between inbreeding duplications in different generations.
For example, an inbreeding group of a son and daughter of a duplicated sire, the sire in the 4th and 5th generations, 4x5, would be counted as 1.
The same for an inbreeding group of a son and daughter of a duplicated sire, the sire in the 6th and 6th generations, 6x6, would be counted as 1.
Obviously, the closer inbreeding 4x5 probably has more influence on the foal than the more distant 6x6.

With almost all the inbreeding in the original Jan/Feb 2017 six generation pedigree program in the 4th, 5th, 6th generations the question of giving greater weight to inbreeding in the 4th generation over that in the 5th and 6th generations was ignored. The results were still informative.

But with the unfinished 2020 ten generation pedigree program it is obvious that inbreeding in the 4th generation and inbreeding in the 10th generation should have vastly different influences.
In my first results a few weeks ago I ignored this, giving every generation equal value i.e. a weight of 1.0 (see below)**

Using my test case of Galileo (1998) I am experimenting.
Galileo has 58 inbreeding groups in his first 10 generations. These have 199 duplicated horses.
4th gen (1); 5th gen (3); 6th gen (6); 7th gen (22); 8th gen (34); 9th gen (56); 10th gen (77) = 199

I know many do not agree with inbreeding analysis. 100% of the horse DNA is in the horse.
Others say you need look no further than the sire and dam.
I think you must agree that the DNA in the horse is also in the sire and dam. We do not know what DNA the horse received.
The same for the grandparents. The DNA in the horse is also found in the grandparents.
And the same for the great-grandparents, and earlier generations.
The DNA in the horse came from ancestors. It did not come from elsewhere.

Giving different weights to inbreeding in different generations for Galileo:

Weight given / generation / percentage in that generation
Weight 1.0**: 4th (0.5%); 5th (1.5%); 6th (3.0%); 7th (11.1%); 8th (17.1%); 9th (28.1%); 10th (38.7%)
This was what was applied to Galileo's pedigree weeks ago.
You can see far too much influence was assumed for the earlier generations (8th, 9th, 10th).

Weight 0.3**: 4th (28.6%); 5th (25.7%); 6th (15.4%); 7th (17.0%); 8th (7.9%); 9th (3.9%); 10th (1.6%)
Weight .05**: 4th (8.5%); 5th (12.7%); 6th (12.7%); 7th (23.2%); 8th (18.0%); 9th (14.8%); 10th (10.2%)
Weight 0.7**: 4th (2.5%); 5th (5.2%); 6th (7.3%); 7th (18.8%); 8th (20.3%); 9th (23.4%); 10th (22.5%)
Weight 2.0**: 4th (0.0%); 5th (0.1%); 6th (0.3%); 7th (2.4%); 8th (7.3%); 9th (24.0%); 10th (66.0%)

Weight 0.3 - with the 4th generation given a value of 1.0, the 5th generation gets 0.3, the 6th generation 0.09. This gives far too much weight to the closer generations.
In this case, the one duplicated horse in the 4th generation is given a value of 28.6%. 77 duplicated horses in the 10th generation get 1.6% for all of them. Nonsense.
Weight 0.5 - this is the weighting I will use for the moment.
It assumes influence is halved each generation i.e. a grandparent has twice the influence of a great-grandparent.
Weight 0.7 - this is the weighting recommended in a pedigree analysis book I like. I think it gives too much influence to earlier (8th, 9th, 10th) generations.
Weight 2.0 - this gives a nonsense valuation, with two thirds of the influence in Galileo's pedigree attributed to the duplications in the 10th generation of his pedigree. I did this calculation to show that a Weight under 1.0 must be correct.

There have been many theories about thoroughbred pedigrees.
My stance is to let the numbers tell me what analysis works.

From "The Mating of Thoroughbred Horses" (1942) by H E Keylock
"The following conclusions are arrived at with regards to the inheritance of characteristics
1. Good performers on the race course cannot be selected by their conformation or other visible characteristics.
2. Varying characteristics do not follow the female or male line of descent, but follow an unpredictable course.
3. Neither the sire nor the dam can convey any characteristics to their progeny and the progeny inherits all the characteristics from its four grandparents.
4. Some animals usually pass on the necessary winning characteristics and some animals usually do not pass on these characteristics.
If they do pass them on then these characteristics are not inherited from ancestors in the 1st, 3rd, 5th, and 7th generations, but from ancestors in the 2nd, 4th, 6th and 8th generations."

I agree with point 1. and 2.
H E Keylock suggested that influence in pedigrees by generation is (1/2)+(1/4)+(1/8)+(1/16)+(1/32)+(1/64) .....
That gives each parent 1/4 influence, each grandparent 1/16 influence, each great-grandparent 1/64 influence (Weight 0.25).

I'm interested in the lack of inbreeding in the first few generations of Galileo's pedigree.

In the first 5 generations the only inbreeding is via Native Dancer in his 4th and 5th generations. Galileo's half brother Sea The Stars ( Cape Cross) has no inbreeding in the first 5 generations at all. His dam Urban Sea has no inbreeding until back in the 5th generation where she has loads, Nasrullah twice on her Sire side, Alchemist twice on her dam side and Prince Rose once on each side.

If you take the view that repetition proves something, ye can look at the Galileo x You'resothrilling cross that has produced a steady stream of G1 winners and G1 placed horse. Northern Dancer appears in the 3rd ( Sire) and 4th ( dam) generations as well as Hail To Reason on both sides in the 5th generation of that perfect niche cross.

How do you apportion inbreeding influence as it dilutes through the generations? Edit I see.

The Tetrarch · 28-08-2020 4:13pm

tryfix wrote: »

I'm interested in the lack of inbreeding in the first few generations of Galileo's pedigree.

A few minutes ago I did a quick analysis of Sea The Stars. There are similarities with Galileo.
They are from the same dam, but different sires.
I am interested in how the two sires, Cape Cross and Sadler's Wells, match with Urban Sea. The matching will be different.

Sea The Stars has 55 duplication groups (224 horses) in 10 generations. Galileo has 58 groups (199 horses).
The similarity is that few of the early inbreeding groups of either i.e. those close to the horse, have the usual two sons (or more) of a duplicated sire found in the majority of modern pedigrees.

Sea The Stars:.......... f.m; m.mf; f.f; f.f; m.m; m.f; ff.f; mmf.f; f.m; mmmff.m; mfff.fff; f.ff; m.f; mmmmmmmmmmmmmmff.m. (bold are from duplicated dams)
Galileo:.................... f.m; mm.f; mf.ff; mf.m; mf.ff; m.f; mmmf.m; f.m; f.f; f.f; mff.mfff; f.mmf; f.f

I took two colts rated 25 and 14 at random.
Random Colt 1: ........... m.m; m.mf; f.f; m.m; m.fff; m.m; f.f; m.m; f.mfff; m.mmmmmmmmmmfffff; m.mmfff
Random Colt 2: ........... f.f; m.mm; f.m; m.mm; f.f; f.ff; f.mmmm; m.mmmmmf; f.mff; f.f; ff.f; m.mmmmmmmmm; f.mmmfffff

The thing I expect and notice is the lack of duplicated sons of sires close up in Sea the Stars and Galileo.
In the poor horses there are (1) m.m x 4 (2) m.mm x 2 close up.

The Tetrarch · 02-09-2020 9:53am

The yearling sales are starting, and will be run over the next few weeks.
I downloaded Excel files from Tattersalls and Goffs, and am working on extending the pedigrees of 2,969 yearlings to six generations.
I will probably finish the pedigree extensions today.

My plan is to analyse those yearlings with
(1) the pedigree program I wrote in Jan/Feb 2017
(2) the pedigree program (unfinished) I have been writing since March 2020.

(1) will probably be done today.
(2) will be done in the next few months.

I will rank the yearlings by ability based on the pedigree analysis.
The yearlings will run over the next few years, and I will use their ratings and earnings to compare my analysis with the results.

Harold Hampton analysed yearling sales catalogues in New Zealand in the mid-1950s, writing out 1,400 six generation pedigrees by hand, and analysing them.
Hampton's results were good, identifying most of the quality runners. He used his failures to refine his analysis.

The Tetrarch · 18-09-2020 2:54pm

This morning I got out a book on statistics and tried to get a bit of sense out of my ratings file.
I copied into Excel 69,215 horses that have a rating, and also have a sire rating, and a dam rating.

Average runner rating: 77.10 (median 76.00); Average sire rating: 122.54 (median 126.00); Average dam rating: 83.42 (median 84.00)
The correlation coefficients are: Runner with dam 0.271; Runner with sire 0.131
The correlation coefficient is a number from +1 to -1. +1 would be a perfect relationship between two numbers. As one number increases the other number increases. -1 one number decreases as the other increases.

You might think sending a dam rated 83 to a sire rated 122 would give a runner rated possibly (83+122)/2 = 102. That does not happen.
What might surprise people is that the runner average of 77 is well below their dam average of 83.

Surely the top sires do better than that? I had a look.

Sire ..................rated runners ..........runner average ........ dam average
Sadler's Wells.............888........................ 89.34.................100.91
Rainbow Quest...........403........................ 84.76 ................100.55
Darshaan..................264 ........................88.62 ..................94.78
Danehill....................424 ........................91.81...................91.72
Barathea...................397.........................76.92..................87.74
Cadeaux Genereux.....435.........................80.93..................88.09
Cape Cross................502.........................81.79..................87.38

On a larger group of 159,232 rated horses the average rating is 78.95.
One standard deviation of that group is 23.64, and 65.67% of horses are within+/- 1 SD (from 55.31 to 102.59).

One conclusion is that commonly regarded good sires are not exceptional.
They get highly rated mares to star their careers at stud.
Afterwards they attract quality mares through a combination of high fees, and selectivity by the sire owner accepting only quality mares.

How many runners were rated better than their dam in the 69,215 sample?
Better 26,594 or 38.4%; better by 10+ ratings points 24.8%; better by 20+ rating points 14.80%; better by 30+ rating points 8.28%

How many runners were rated better than their sire in the 69,215 sample?
Only 67,871 sires were rated, probably because the missing ratings were from sires who ran in the USA or Australia.
613 runners (0.90%) were rated better than their sire.

The Tetrarch · 28-09-2020 11:14am

About half an hour ago I started the first real run of my new pedigree analysis program.
It took seven months in 2020 to get this far.
Often a program runs for a while and stops when it hits an problem. Then a fix is made, and the process starts again.
Fingers crossed. It is still running.

A big difficulty is trying to reduce a 10 generation pedigree to one number (or a few numbers) to indicate the quality of the pedigree.
The load file is 159,208 horses with ratings.
The program picks a horse, analyses its pedigree, gives the horse numbers, and outputs those into a 159,208 horses results file. Then it steps down to the next horse and repeats.
At about 0.5 seconds each horse, it will take 22.1 hours to run.
It is running on my 2016 PC, but in 2020 I bought two more PCs that should be a lot faster.
I plan to split the load file in three and run the program on three PCs at the same time.
If I compare all the 3,000+ mares on offer at the breeding stock sales in IRE, GB, FR in Nov/Dec against 500+ stallions that gives about 1,500,000 "foals" those mares could produce.
To analyse 1.5 million test-mating foals would take 278 hours (11.5 days) on the 2016 PC.
I will probably use a cut down version of the program to pre-analyse the large numbers, and then run the full program on the best from the pre-analysis.

It will soon be time to get out the statistics books, and write a program to produce a statistics file from the results file.
If the results are not good, it will be back to reassessing and probably dismantling parts of the program.

The Tetrarch · 02-10-2020 12:27pm

My new inbreeding analysis program is running.
The first time I ran it if stopped 23 times when it hit an incomplete pedigree.
Most of those incomplete pedigree were for horses born between 1900 and 1910
It was not surprising that preparing ten generation pedigree for those found a few gaps.
Ten generations back from 1910 is around 1801 (10 x 10.9 years = 109 years).
I would prefer that the program stops when it hits a snag. I can check the problem.

I used my own number for each generation: 16 for the horse (unused); 8 for each parent; 4 for each grandparent; 2 for great-grandparents, and so on.

Using the last horse analysed, ZYZXX (2003) as an example
(Yes, that is a real horse name (AUS) 35 starts, 4 wins)

Buckpasser is the first* sire duplicated in his pedigree, one in the 4th generation, once in the 5th generation.
*I use the date of birth of the duplicate sire to determine which is first (01dup group).
Buckpasser (1963) is group 01dup and Northern Dancer (1961) is 02dup, even though the Northern dancer duplications are closer to the foal/runner.
There is an obscure (but necessary) reason for doing this.

01dup Buckpasser 4x5 ... values 1.0000+0.5000 = 1.5000
02dup Northern Dancer 3x4 ... values 2.0000+1.0000 = 3.0000
03dup Native Dancer 5x5.6 ... values 0.50+0.50+.025 = 1.2500
04dup Alibhai 5x7 ... values 0.500+.0125 = 0.625
05dup War Admiral 7x8.8.9 ... values 0.125+.0625+0.625+0.03125

All the 10 generation inbreeding of ZYZXX totals 11.984375

.................................................................................................................

Review
At this stage it is difficult to separate the wood from the trees.
What inbreeding is important? What inbreeding is a negative?

Galileo (1998) has a total inbreeding of 11.828125 (the summation of 58 duplication groups)
Zyzxx (2003) has a total inbreeding of 11.984375 (the summation of 46 duplication groups)
Can we conclude from this that inbreeding is not a guide to class?
If we look at the type of inbreeding closely we can see differences.

Galileo (1998) has inbreeding groups that produce a son(s) and daughter(s) (mf) of 5.656250
Zyzxx (2003) has inbreeding groups that produce a son(s) and daughter(s) (mf) of 3.187500

Galileo (1998) has inbreeding groups that produce only sons (mm) of 0.343750
Zyzxx (2003) has inbreeding groups that produce that produce only sons (mm) of 3.812500

Galileo (1998) has inbreeding groups that produce only daughters (ff) of 1.796875
Zyzxx (2003) has inbreeding groups that produce that produce only daughters (ff) of 3.062500

Galileo (1998) has inbreeding groups that have extra sons 1.750000, and groups that have extra daughters 2.281250
Zyzxx (2003) has inbreeding groups that have extra sons 0.968750, and groups that have extra daughters 0.953125
(an extra daughter would be a duplicated sire, e.g. Hyperion, that appears three times in the pedigree (a group).
That group is one son and two daughters (mxmf)- an male/female duplication group (one son; one daughter) and with one extra daughter.

..................................................................................................................

The most inbred horse the program found was Akazie (GER) (1938) (f).
Akazie gets a 16.000000 from the program.
Her sire Alchimist is by Herold out of Aversion (by Nuage out of Antwort)
Her dam Artischocke is by Herold out of Arachne (by Nuage out of Antwort)
Herold's dam Hornisse is by the sire Ard Patrick.
Antwort is by the sire Ard Patrick.

Another way of stating this pedigree is that the fourgrandparents of the sire are the same as the four grandparents of the dam.

..................................................................................................................

I am thinking of changing my valuation system to Wright's Coefficient
https://en.wikipedia.org/wiki/Coefficient_of_relationship

The Tetrarch · 02-10-2020 12:43pm

High numbers my program (and Wright's Coefficient) calculate from close inbreeding in the 1st, 2nd, 3rd generations are not desireable.

In Thoroughbred Breeding, Notes and Comments (1987) by Mordaunt Milner page 103
"Dr Q P Campbell, lecturing at the Animal and dairy research Institute in Bloemfontein, stated that 'Generally speaking, performance in a horse starts to deteriorate when inbreeding exceeds 3-8%*'. Dr Campbell suggests that for performance to be affected it would require an inbreeding as close as two free generations**. If it requires inbreeding as close as that to produce an adverse effect, it is logical that inbreeding should be as close as that before it can be beneficial."

* does he mean > 3% ?
** two free generations is 3x3 or 1/32 (or 3.125%) Wright's Coefficient

The Tetrarch · 25-10-2020 10:23am

Wright's Coefficient

For example, is there is a 5x5 inbreeding to Nureyev as in the example below the calculation is
100 x (1/2 ^((5-1)+(5-1)+1))% ....
100 x (0.5 to the power of 9)% ....
100 x 0.001953125% ....
0.1953%

This is the calculation for the planned mating (and hopefully a foal) of my 3yo filly Ahlam with a stallion in 2021

Stallion*-Ahlam
Inbreedings are
1) Sadler's Wells 4x6 = 1/512 x 100 = 0.20%
2) Fairy King 4x6 = 1/512 x 100 = 0.20% (I am treating Sadler's Wells and Fairy King as the same horse as they are full siblings / have the same parents)
3) Nureyev 5x5 = 1/512 x 100 = 0.20% (5x5 is the same strength as 4x6)
4) Millieme 4x5 = 1/256 x 100 = 0.39% (I am treating Millieme and Shirley Heights as the same horse as they are full siblings / have the same parents)
5) Shirley Heights 6x5 = 1/1024 x 100 = 0.10%

These total up to 1.07%
(0.20+0.20+0.20+0.39+0.10=1.07%)

Taffeeite

1) Rainbow Quest 4x4 = 1/128 x 100 = 0.78%
2) Danzig 4x5 = 1/256 x 100 = 0.39%
3) Ribot 6x6 = 1/2048 x 100 = 0.05%
4) Flower Bowl 6x6 = 1/2048 x 100 = 0.05%
5) Buckpasser 6x6 = 1/2048 x 100 = 0.05%
6) Sir Ivor 6x6 = 1/2048 x 100 = 0.05%
7) Best In Show 6x6 = 1/2048 x 100 = 0.05%
8) Northern Dancer 6x5 = 1/1024 x 100 = 0.10%
9) Northern Dancer 6x5 = 1/1024 x 100 = 0.10%

These total up to 1.61%

Note: Taaffeite has Northern Dancer twice in her 6th generation on the sire side, and once in the 5th generation of her dam.
These are calculated as two inbreedings, 6x5 + 6x5. (8) and (9)

It is suggested that inbreeding is slightly greater than the above figures if you then compare inbreeding groups e.g. compare Buckpasser to Sir Ivor. I ignored that.

Inbreeding calculation
1x1 = 50% [1/2]
1x2, 2x2 = 25% [1/4]
2x2 = 12.5% [1/8]
2x3, 3x2 = 6.25% [1/16]
3x3, 2x4, 4x2 = 3.125% [1/32]
3x4, 4x3 = 1.5625% [1/64]
4x4, 2x6, 6x2= 0.78125% [1/128]
4x5, 5x4. 3x6, 6x3 = 0.390625% [1/256]
5x5, 4x6, 6x4 = 0.1953125% [1/512]
5x6, 6x5 = 0.09765625% [1/1024]
6x6 = 0.048828125% [1/2048]

Any inbreeding that adds up to the same number has the same percentage
e.g. 6x6, 5x7, 7x5, 4x6, 8x4 all give the same 0.048828125%

You can see that if your horse contains one 3x3 inbreeding that is 3.125%, and you are into the territory that is not recommended i.e. 3% inbreeding or more.
If there is another inbreeding to the 3x3 you add that to the 3.125% from the 3x3.

Enable, recently retired, is 3x2 Sadler's Wells and 6x6 Nasrullah: 6.25%+0.05% = 6.30%.
I mentioned before that close inbreeding like this occasionally works if the horse (in this case a filly) is the opposite sex to the close inbreeding (Sadler's Wells, a male). In this case that is true.
Another is Fatherland (1990) (a colt, rated 115). He is inbred 3x1 to the full sibling sisters Special and Lisadell (both by Forli out of Thong), a 12.5% inbreeding. The sex of the inbreeding, females.
(you could say the inbreeding here is two inbreedings, 4x2 to Forli (m), and 4x2 to Thong (f).)
Interesting to me, is that the two males in the Enable inbreeding are on the sire line of her sire, and on the sire line of her dam.
In Fatherland the female inbreeding is on his two dam lines, the dam line of his sire, and the dam line of his dam.