The Dosage Index approach basically selects Chef-de-Race sires based on general tendency analysis and provides an interpretation according to their presence within the pedigree. That system does not evaluate the influence of mares. Here, on the other hand, although the data pool is naturally much more limited, the score is produced for every sire and mare through a completely mathematical evaluation. As a result, the foal being evaluated is considered as a blend of all of its ancestors. What still needs to be improved — and what I am currently working on — is increasing the number of representative races and the diversity of regions included in the dataset.
Honestly, I think the method being used is effective. Of course, a large portion of Swing Easy’s speed score comes from Indian Ridge, but Swing Easy himself is also directly contributing the genetics that made Indian Ridge fast in the first place. If the study had been conducted the way you suggested, it would have focused solely on the influence of sires and broodmare sires.
What I am aiming for here is an algorithm that, when any pedigree is entered for analysis, can generate speed and stamina scores by drawing data from all pedigree elements. To achieve this, I carried out a study in which I expanded the algorithm’s dataset by increasing the representative race count for each criterion to eight, while also incorporating races from different regions.
@archiebreland Hello, the full list consists of 29 stallions due to the article image format (5:2). In the coming period, I will also share more comprehensive lists based on crops or sire lines, using updated statistics.
@cob1ll Hello, these values are calculated using correction factors based on the countries where the stallion’s progeny have raced.
CB: Corrected Black-Type Winners/Runners
CE: Corrected Earnings/Runners