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Bunching Theory Test: Seeking Sponsorship for Python Simulation () Bunching Theory Test: Seeking Sponsorship for Python Simulation ()

12-13-2022 , 08:52 AM
Hi,

I am seeking sponsorship to test bunching theory using a python simulation that I have developed. Bunching theory is the theory that if it gets folded around to the button, the big blind and small blind are more likely than average to have aces or kings or ax, kx. Testing this theory can provide a competitive advantage and better outcomes, and using a simulation can give peace of mind that it is not just guesswork nor a mistake in a formula.

In return for your sponsorship of $20, you will receive:
  • A copy of the Python code
  • My results proving or disproving bunching theory based on my methodology
  • A copy of my previous results

I have already simulated exact solutions and my previous results are:
  • The chances of not having any super-premium hand AA, KK, QQ, or AKs for 90 hands in a row are 22.18%
  • The chances of not having any premium hand AA, KK, QQ, AKs, or AKo for 90 hands in a row are 9.65%
  • The chances of not having any premium hand: AA, KK, QQ, AKs, AKo, AQs or JJ for 90 hands in a row are 4.79%

Your contribution will be used to help me find the time to do this simulation, which requires a significant time investment. Additionally, by receiving a copy of my results, you will gain valuable insights into the dynamics of poker and how to gain a competitive advantage.

More than one person can be a sponsor for this post and you can contribute more or less than $20. If you contribute less than $20, the project will not begin until the pool reaches $20. I will add my first contribution of $5 of my own money.


Current sponsorship amount:
$5 (from myself)
Sought in order to code this solution and scientifically test bunching theory: $20
Amount to go $15.
Bunching Theory Test: Seeking Sponsorship for Python Simulation () Quote
12-16-2022 , 12:04 PM
Quote:
Originally Posted by Robiplayer
Hi,

I am seeking sponsorship to test bunching theory using a python simulation that I have developed. Bunching theory is the theory that if it gets folded around to the button, the big blind and small blind are more likely than average to have aces or kings or ax, kx. Testing this theory can provide a competitive advantage and better outcomes, and using a simulation can give peace of mind that it is not just guesswork nor a mistake in a formula.

In return for your sponsorship of $20, you will receive:
  • A copy of the Python code
  • My results proving or disproving bunching theory based on my methodology
  • A copy of my previous results

I have already simulated exact solutions and my previous results are:
  • The chances of not having any super-premium hand AA, KK, QQ, or AKs for 90 hands in a row are 22.18%
  • The chances of not having any premium hand AA, KK, QQ, AKs, or AKo for 90 hands in a row are 9.65%
  • The chances of not having any premium hand: AA, KK, QQ, AKs, AKo, AQs or JJ for 90 hands in a row are 4.79%

Your contribution will be used to help me find the time to do this simulation, which requires a significant time investment. Additionally, by receiving a copy of my results, you will gain valuable insights into the dynamics of poker and how to gain a competitive advantage.

More than one person can be a sponsor for this post and you can contribute more or less than $20. If you contribute less than $20, the project will not begin until the pool reaches $20. I will add my first contribution of $5 of my own money.


Current sponsorship amount:
$5 (from myself)
Sought in order to code this solution and scientifically test bunching theory: $20
Amount to go $15.
Sure why not, dm me
Bunching Theory Test: Seeking Sponsorship for Python Simulation () Quote
12-16-2022 , 01:39 PM
Quote:
Originally Posted by Koshko
Sure why not, dm me
DM sent
Bunching Theory Test: Seeking Sponsorship for Python Simulation () Quote
12-20-2022 , 06:17 PM
Giving this a bump in case anyone else is interested.
Bunching Theory Test: Seeking Sponsorship for Python Simulation () Quote

      
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