The reason is that when I look at a subset of races - such as horses that actually were within 1 length at the 1st call, I found that the important factors are far different than when looks at the totality of all horses.
That's a mouthful. Sorry.
Another way to say it through an example and with a few breaths in the sentence...
We know that the best jockeys win the most races because we can see it in the statistics for jockey standings.
However, if we looked at only (say) horses that were within one length a furlong from the wire...
... we'd probably find that "Jockey Win Pct" was not the big factor it is in the overall stats.
It was the idea of "subset studies" that drove me to develop the 1-2-3.
IMHO, that is where the edge is to be found.
I should do a video on what I've come to call "Segments and Subsets."
While I do not do it graphically as they do, this video provides some insight into the value of breaking data down into segments.
Ayasdi's English Premiere League 2:31.
If you are not a soccer fan (as I am not), perhaps you'd make more sense of their
13 Positions of Basketball video 14:39.
There is a longer, better version of the
13 Positions of Basketball video 33:15.
Dave
