I am sure that some people get tired of me going on about the whales. If so, just ignore this post.
I study them because they're our major competition; the single thing that makes this game most difficult to beat.
Well, in truth, I study the IMPACT of whales.
The battle has been very one-sided. That is, every year the game gets tougher, as the efficiency in the factors becomes more even.
This post will illustrate how I came to this conclusion. Before we are finished, I will also tell you why I think this can actually work in our favor.
I have drawn races from Feb. 01 to July 15th from each of the last 2 years. 5f to 9f, fast tracks, 5+ betting interests, no FTS, and races with entries have been removed.
An example:
Let me tell you what you are looking at.
(This factor is Jim Cramer's
Projected Speed Rating. It is very much like
BRIS Prime Power.)
#1. We are concentrating on the $Net column. This is the return per $2 wager for the different ranks. (FH is actually half-the-field-plus-1 horse and does not include 1-2-3.)
#2. See how the $Nets flow downward? This is indicative of how aware the public is of this factor.
In the case of a high-level factor such as PSR or BPP, it actually means that the public is dialed into the
factors that make up these "factors." (In our software, we call these "Objects.")
#3. What we are really interested in is the ratio between the top rank and the bottom rank. We call that the "$Net Ratio."
The higher the $Net Ratio is, the more difficult it is to make money with longshots because the bigger prices are going to come from the Rear Half (RH) of the field.
In other words, the better the public is at isolating on the "hot horses," the more they will be bet down. This will effectively take some of those RH horses and cause the winners to no longer be long-priced.
#4. What we want to do at #4 is compare the 2017 $Net Ratio with the 2018 ratio.
What we see in this illustration is that the PSR factor has become more efficient. That is, the ratio has "flattened."
BTW, look at just how bad a "rear-half" horse really is.
Also, note how there is a distinct flattening of the top 3. My belief is that this is indicative of (at least philosophically) the whales doing a better job of finding "true value" in those top 3 ranks.
As they get closer to the same $Net, they have been effectively rendered useless because they make no difference in the bottom line.
Let's look at another example.
Here we are looking at a factor in our system known as "Composite Final Time." It is created from 13 different ways of looking at speed ratings, such as Last Race, Best-of-Last-2-Races, Average-of-the-Last-3-Races, Best Ever, etc.
It is safe to assume that to a large degree, these two tables illustrate just how dialed in the public is to the impact of speed ratings.
Look at the gigantic shift in efficiency in the ratio!
Understand that the normal annual shift (in major factors like these) has been something in the vicinity of 2-3%. That's kind of like saying, "The public is getting 2-3% smarter every year."
This particular jump was in the magnitude of 10%!
This is unprecedented. I check these figures almost every year and have never seen a jump like this.
By comparison, Quirin Early Speed Points have been tuned in for so long that they hardly change at all.
(As a side note, a logical question for a handicapper to ask themselves is, "What did I do this year to get 3% smarter?")
Let's do another.
Here's an older version of HDW's Projected Speed Rating. It has been around much longer, does not correlate with the tote board as much as PSR (or BPP), and, like Q ES Pts, has been dialed in for several years.
Still, it moved downward over 3%. (129-125) / 125 =3.1%.
In the next post (which will take me a couple of hours) I will address the impact on the tote board as well as a summary of this.
I contend that there is a silver lining to this. I believe the whales have created a vulnerability and I will share it with you later today.
Of course, I welcome comments.
Dave
