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LoTT is a parabola


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What game are you guys playing here? Looks interesting.

 

This is my favorite bridge topic for discussion. Where do tricks come from? How are

they generated? Which parameters are best for estimating tricks? Which parameters

are easy to use and relatively accurate for measuring tricks?

 

Power and Pattern

 

There are two independent random variables to measure tricks. They are power and pattern.

Power is the set of all parameters measuring tricks by using honors and high spot cards.

Pattern is the set of all parameters measuring tricks by using the length and shortness of suits.

 

L/W calls power Winning Points. HCP is a parameter of power which is proportional

to tricks. Both trumps and SST are subgroups of pattern. Trumps is the parameter of

pattern which is proportional to tricks.

 

Our tricks

E(tricks) = trumps + (HCP-20)/3 + SST

 

Only reliable when expected tricks is 10 or less. Other variables, not included into

this formula, come into play in high level auctions. There's nothing sacred about

this formula. This formula gives insight to the number of tricks available. It is a

tool. A guideline to assist the evaluation of tricks for the partnership. It certainly

isn't a law.

In general case the SST is a fractional displacement of the estimates by trumps and

HCP. That is the average displacement over a large number of boards. For any

specific board SST displacements are measured in integer increments.. Often

there is no displacement. Sometimes the displacement is two or more tricks.

Singletons and voids aren't worth any number of points. HCP is a subparameter

of power. Suit shortness is a subparameter of pattern. Stop adjusting the points.

HCP and suit shortness are subparameters of different independent random

variables. Valuation models should measure the tricks, not points.

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For goodness sake. Suppose, for the sake of argument, you create a perfect topographical map of anywhere, then you throw a blanket over it. The blanket will reliably do its best to fall into its contours. The same thing is true when fitting a nonlinear curve using least squares. Gauss, Smauss. The more people who use computers, the lower the average IQ of the users.
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It's kind of like NumberWang but with slightly more obscure rules. https://www.youtube....h?v=qjOZtWZ56lc
I've learnt something interesting.
FWIW the correlation coefficient is 0.58645 by my calculations.
5 significant figures?
The more people who use computers, the lower the average IQ of the users.
Reminds me of what our arithmetic teacher taught us "Every time a Scotsman crosses the border to England, the average IQ of both countries rises" :) When a PC pupil expressed his concern "Mightn't that hurt an Englishman's feelings?", the teacher reassured him "Don't worry, he won't understand it".
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5 significant figures?

I can give you more if you want. As I said upthread, this isn't a simulation; it's an exact calculation.

 

[edit] The precise value, for anyone who may be interested, is 14574888024790152694633 / 24852706986690307830040. Unless there's a mistake in my program, of course.

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I can give you more if you want. As I said upthread, this isn't a simulation; it's an exact calculation.

 

[edit] The precise value, for anyone who may be interested, is 14574888024790152694633 / 24852706986690307830040. Unless there's a mistake in my program, of course.

 

*ding* That's NumberWang!

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