### Author Topic: Horse  (Read 297 times)

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#### Sputnik

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##### Horse
« on: December 02, 2017, 02:39:37 PM »

Testing binomial probability equal even money on Horse betting ... first place winner ...

Odds around 3.0

W & LW has 50% chance to win
LL has 50% chance to win

V-ODDS 3.81 W
V-ODDS 3.63 W

V-ODDS 3.29 L
V-ODDS 3.77 L

V-ODDS 3.75 L
V-ODDS 3.62 L

V-ODDS 3.15 L
V-ODDS 3.24 W

V-ODDS 3.15 W

V-ODDS 3.57 L
V-ODDS 3.34 W

V-ODDS 3.06 W

V-ODDS 3.97 L
V-ODDS 3.73 L

V-ODDS 3.88 W

And i also test higher odds around 6.0 with binomial calculation

V-ODDS 6.18 L
V-ODDS 6.76 L
V-ODDS 6.54 W

V-ODDS 6.30 L
V-ODDS 6.00 L
V-ODDS 6.75 L
V-ODDS 6.07 W

V-ODDS 6.91 L
V-ODDS 6.98 L
V-ODDS 6.55 W

This is pretty amazing :-)
« Last Edit: December 02, 2017, 02:42:57 PM by Sputnik »

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#### Sputnik

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##### Re: Horse
« Reply #1 on: December 04, 2017, 08:06:57 AM »

The people opinion and money rule what kind of odds to expect and you can not trust them.
I took a pretty common favorit odds and look at the output using STDS to measuring the accuracy.
The odds range is between 2.0 and 2.99 and i find 3.80 STDS sequence in during four weeks.
That is 3 win and 22 loses ... pretty cool to measuring the horse market that way and see how wrong the public eye is when they estimate a horse with relativ low odds.

Cheers

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#### thomasleor

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##### Re: Horse
« Reply #2 on: December 04, 2017, 08:57:06 AM »
For those of you who do not know what he is talking about, here is a good link to teach yourselves Binomial Probability Distribution.

http://stattrek.com/probability-distributions/binomial.aspx

It is pretty simple math and you can easily (unless you do not use Mathematica software) put in the formula in your excel for future instantenous use.

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#### Reyth

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##### Re: Horse
« Reply #3 on: December 05, 2017, 12:50:57 AM »
Quote
Cumulative Binomial Probability

A cumulative binomial probability refers to the probability that the binomial random variable falls within a specified range (e.g., is greater than or equal to a stated lower limit and less than or equal to a stated upper limit).

For example, we might be interested in the cumulative binomial probability of obtaining 45 or fewer heads in 100 tosses of a coin (see Example 1 below). This would be the sum of all these individual binomial probabilities.

Pure gold!  Thanks Thomas!!

Heretofore I have solved problems like this by resorting to "bean counting" which is not always a practical solution...
« Last Edit: December 05, 2017, 12:54:11 AM by Reyth »