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Part V Using
Different Steepness Ratios In
Part
Four of this series, we looked at the profitability of using a $110-Inside to
$22-Inside regression. That equates to a 5:1
regression-ratio. Part One
of this series explains in detail what regression-ratios are, and how we use them. Simply
stated: Ø The steeper the regression-ratio is; the higher, earlier and more often a net-profit will be secured.
Ø
The
shallower the regression-ratio is; the less frequent and lower our net-profit will
be. The
Risk of Using Too LOW of a Regression Ratio If
we try to go cheap with our betting by not putting out a large enough initial bet (or by
flat-betting) when we have the best chance of actually capitalizing on our
Precision-Shooting abilities; then its little wonder why so many accomplished
players run into difficulty in exploiting even their most obvious skills. Ø If our bets are too low or the regressions that we use are too shallow in ratio; then we'll almost always restrain and unnecessarily retard our advantage-play earnings.
Ø
Most
players look at a lower-value/lower-ratio starting-level for their regression as a way of
reducing volatility; but in fact, it just makes it harder (or almost impossible) for them
to break through to profit on a sustainable basis.
Ø
The
lower and closer your Sevens-to-Rolls Ratio (SRR) is to random; the less time (as measured
by number of point-cycle rolls) you will have in which to capitalize on your
dice-influencing skill. Therefore you have to
bet on the fattest part of your roll-duration expectancy curve.
As
you can see on the chart above; combining a regression that is too shallow (2:1) with a
modest SRR, can result in a negative result even though you will often hit your first
paying Inside-Number bet and still be able to make the regression. What puts this SRR-7 shooter into negative
territory is the fact that he wont hit enough paying Inside-Numbers often
enough at the regressed $22-Inside mark to make the bet become net-positive. On
the other hand, you can see that if this same SRR-7 shooter simply increases (steepens)
the ISR regression-ratio to 3:1, the very same skill-set produces a modest profit.
Ø
As
your SRR-rate improves and the steepness of your regression increases; so does your return
on investment. For
example, in the chart below, a SRR-8 dice-influencer produces a profit even when employing
a shallow 2:1 regression ratio. Obviously
though, his bet-flexibility and overall income rises dramatically as his regression-ratio
increases.
It
is important to note that each SRR-level forces a different bet-reduction trigger point. While the SRR-7 shooter has to immediately regress
his large initial bet after just one hit; the SRR-8 dice-influencer can reasonably keep
them up at their initial large size for the first three point-cycle rolls before having to
steeply regress them.
Ø
As
your SRR improves over random, the higher your rate-of-return will be.
Ø
Obviously,
the more well-endowed your session bankroll is and the more comfortable you are in using
higher-ratio steeper-regression wagers; the more you will be able to take full advantage
of your dice-influencing skills.
Part
Six
of this series adds a whole new dimension to regression-based profit-making. I hope you will join me for that. Until then, Good
Luck & Good Skill at the Tables
and in Life. Sincerely, The Mad Professor
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