Ah... I was referring to unique permutations.

Have I made an inaccurate assumption? — William Zayonce

You'll have to be the judge of that, but I would say "no."

Not +/- 3% but rather precisely -3.5% has been the target.
This allows an ROI of +7.5% to +9%.
The model calls for the bankroll to be churned 125x per year.

Limited to 30/35% depends upon the track takeout & rebate.

Odds levelling out: They do not "level out." They skew towards the efficient -3.5% for them, which equates to almost pure takeout rates for us.

3: the possibility that many players are simply getting more efficient, perhaps by using computer programs .? — William Zayonce

This is the real challenge.

4 people out of a 1000 win.
6 out of 6 whales win.

There's the math.

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%) — William Zayonce

Well, it was WRONG.
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 MNR, CT, DED, etc.
(10 / 45 = 22.2%)

Fixed MY typo in the original and your repost.

Well, if it's working, keep doing it.

There's also the horses that match what you know works and nobody has it. — RanchWest

Nobody has it for the same reason.

I built such a product years ago: Vulnerable Favorites.

I would think it's the same process that identifies false, vulnerable or" play against" choices in the top 2 spots. — William Zayonce

I'd completely agree.

Do you have such a process yourself?

If so, how effective is it?

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

How do you identify just those race?

Finding which contenders will likely take the most action is plenty good enough for my purposes. — William Zayonce

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

Wait...
Are you speaking of their bet size relative to:
A. Total Pool size (i.e. they're eating their own profit)
or
B. Their total bankroll (i.e. optimum bet theory)

Of course they have A covered.
That is basic tote math.

"Liability" is the risk factor for failure. — William Zayonce

Sorry, that does match anything I am aware of.

Can you lay that out for me?

Thanks for your time Dave . After crunching, and understanding your numbers you've given me my answer. Clearly the track rebate is critical when choosing which one to play. Picking a high rebate track will mean bucking huge off swings by the 56.7% of whale generated "late" money. While at SA they only influence the odds to the tune of 22.2% of the "late" money. — William Zayonce

Methinks you are right but for the wrong reason.

Yes, 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.

@RanchWest is right about that approach being dead.
It's as dead as a doornail.

So, what do you do?
Ranch and I have had some conversations and I think he's close.

It's found in anti-handicapping.
Loosely speaking, it's found in predicting who the whales are and aren't going to bet.

They don't view their liability as the other money in the pool. Their liability is something weird happening. — RanchWest

I don't understand that.

I'm wondering how they calculate their bet sizing when they don't know the final pool totals . I would have thought that they'd have a "liability threshold" , a % of the total pool, beyond which they would be at severe risk. Perhaps my assumption that their bet sizes were predicated upon the dollar amounts already in the pools. — William Zayonce

Here's what they have:

• Excellent global How-They-Bet models
• An almost 2-decade history of tote data.

My newest release of HSH includes a much-improved How-They-Bet engine, that will make a huge difference for HSH users if they choose to use it.

What we don't have is that 2nd part: a tote model.

What the whales DON'T HAVE is a good handle on how the OTHER WHALES are going to bet.

I have that.

Maybe I misunderstood your question.

But the point is that the whales bet ZERO money early enough for it to be viewed on the toteboard while you could still make a bet.
___________________
Without explaining the math - which is a bit rigorous - here are a few key points.

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 SA, CD, 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.)

Hope this helps.

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 ? — William Zayonce

None of it.

All the whale money shows up AFTER the gate is open.

Just like yours and mine.

I agree with what you've written.

Value today is a challenge, that's for sure.

Most people confuse Price with Value anyway.

My Dog, I hope I'm not getting dyslexia! — Tom

LOL