Perhaps I should have noted,in the post, that the Principal purpose of the post was to demonstrate that,as in many areas of life, a seemingly difficult problem can be solved by viewing it from a different PERSPECTIVE,much as you showed in your video .

Perhaps I misunderstood your explanation of what Whales do...I took it mean that they use their sophisticated programs to "churn"
their money through the pools with a return of +/-3%, and make their "profit" on rebates.
That would not be "winning" by my definition.It is "getting paid to play".
On that basis ,one would think that their practical limit of overall "average" participation in all pools would be limited to 30/35%. Since that threshold appears to have been reached, my thought was that "other" factors might also be relevant in determining why the odds are levelling out and diminishing. Have I made an inaccurate assumption?

While I don't completely comprehend these tables, I do get the gist of it. It's quite fascinating!
Have you given any thought to the relative effect of ;
1: steadily shrinking average field sizes,
2: slowly but steadily increasing takeout rates
3: the possibility that many players are simply getting more efficient, perhaps by using computer programs .?
These have all escalated significantly since 2010

This is a solution to the "problem" that I found 40 years ago. It's purpose is mainly to make the math and reasoning clear.

A different perspective on the "Monty Hall" problem.
After many years ,I've decided to go public with my personal and simple solution to the "Monty Hall" problem. I'm doing so here because there seems to be some interest.
It seems that others who've tried solving this problem,including mathematicians and statisticians ,did so by starting with the presumption that the " player" gets 1 and only 1 pick of the 3 doors to find the car. In fact, they get 2 picks .
If the doors are goat,goat ,car, then any randomly chosen 2 doors will find the car 2/3 times. When the game begins ,the player is asked to "select" a door .This is not a "pick" . It is a "provisional" pick and can be swapped at the game's end. The fixed odds for this "selection" are 1/3 for finding the car and 2/3 for finding a goat. At this point the host (Monty Hall) will open 1 door and reveal a goat .THIS is the players first pick. It belongs to them and is a integral part of their 2 pick set. It's not the property of the host or anyone else. The fact that it's a goat simply tells the player that the final 2 doors are not BOTH goats . This means ,of course,that there is a 100% probability of the car being behind 1 of them.
The host then asks them if they want to "switch" their "provisional" pick and own the remaining door. There is more than one way to reason this out . The simplest is to know that our "provisional" pick carried odds of 1/3 chances of being the car and that the total chance for the last 2 is 100% ,then switching must necessarily have a 2/3 chance of finding it, so they must "switch" .
Another way would be to reason that 2/3 of the possible 2pick sets contain the car which would mean that they need a 2/3 probability of finding the car (with half of the set already occupied by a goat). The fixed odds of 1/3 on the provisional pick are not enough and they must therefore switch. I'm sure anyone can see how simple this is.

@Dave Schwartz
Thanks. What you intended was pretty clear but the correction has better optics .

For easy reference; part of your posted reply.
The higher the rebate, the higher the percentage of whale money at the track.
About 34% of total win pool at tracks like MNR, CT, DED, etc.
About 10% of total win pool at tracks like SA, CD, etc.

The higher the rebate, the greater the percent of pool that shows up after the gate opens.
About 60% of total win pool at tracks like MNR, CT, DED, etc.
About 45% of total win pool at tracks like SA, CD, etc.

Using that math, for every $100 wagered "late"
$57 will be whale money at tracks like MNR, CT, DED, etc.
(34 / 60 = 56.7%)
$22 will be whale money at tracks like CD, SA, etc.
(10 / 45 = 22.2%)

CONCLUSIONS
The pools at high rebate tracks have 2.6x the percentage of whale money LATE!
($57 / $22 = 2.59)
Since that money is (effectively) in the hands of JUST FIVE BETTORS, the pool swings will be FAR MORE VOLATILE at higher rebate tracks.
(Meaning: When they agree, you can easily see 4/1 become 4/5.)

@Dave Schwartz
What percentage of that final wagering amount do you think might be "whale "money and how much is due to late betting from online ADWs & OTBs ?
Next question is about rebates. Where does the money for rebates originate? Is it money that would otherwise be given to the tracks and horsemen? We often hear that on track betting generates far more for these groups than off track betting .
I would like to revisit this thread.. It was just getting interesting and enlightening when it was derailed While the first question was well answered ,the second was not. And I have further questions as well. It could make an interesting group discussion.
I'm confident that you'll also be able to address the next question on my list, which is;
What percentage of the total pool would,in your opinion, be sufficient to cause "significant" odds drops on 3 or more horses ? Thank-you!

@Tony Kofalt
This sounds like a product that would be helpful to those of us who are "married" to the paper form. I'm utterly lost when I can't "mark up and make notes" on those PDF forms.Thanks Tony!

And sometimes it's hidden in plain sight but few people notice it...

• Yes indeed!

I'm currently trying to revive some of my old "spot plays" to see if they're still profitable.
Haven't made a "real money" bet since January 2011...

I do not ..thought perhaps you'd have an interest in creating such a method from you vast archives of stats . I started toying with such a process 20 years ago but let it slide for lack of data .

I would think it's the same process that identifies false, vulnerable or" play against" choices in the top 2 spots. It certainly wouldn't find a play in every race since ,often enough, the 1st or 2nd choices would be a "play on" type.

@Dave Schwartz

I built that engine.
It loses 4-6% per wagered dollar for me.
3d

What about an engine that identifies win candidates in the 40% of races that those top 2 lose?

@RanchWest
We can hope the collapse ends at a concentration around a few large tracks, but new fans still need to be generated. They are the fuel that makes this big engine run.

@Dave SchwartzYes, you are right but the fact that you think the smaller swings are going to allow you to use the old make-a-line-and-bet-into-it approach."
I actually don't use, nor have I ever used an odds line . Finding which contenders will likely take the most action is plenty good enough for my purposes.

@RanchWest
I'm sure you're absolutely right !
But the less money that the other 99.999% of players put in the pools and the more small,high rebate tracks that go under , the more the $80 million per week that they push through the system will inevitably and necessarily shrink.

Dave Schwartz
232
Wait...
Are you speaking of their bet size relative to:
A. Total Pool size (i.e. they're eating their own profit). Yes ,that's what I thought would limit them to some degree ..It means , effectively, that the more pools shrink the less they can bet effectively.
The "Liability threshold" is the point at which the anticipated returns are virtually guaranteed to show a significant loss.
My previous queries had more to do with odds "movement" than the odds line. I'm wondering how much of the "late" money that is not whale money effects those movements.

@RanchWest
"Liability" is the risk factor for failure.