![]() |
#1
|
|||
|
|||
![]()
If you're not familiar with Kelly Criterion calculations, read this before continuing:
http://en.wikipedia.org/wiki/Kelly_criterion It seems like something very much like this could be a very useful tool to MTT players/backers. Having an analytic way to calculate how much of your own action you want to sell in a big tournament or how much of other players action you want to buy would be awesome. The problem is that the Kelly Criterion math I've seen assumes you get paid X : 1 on your bet and win Y% of the time. How can I adapt this to the much more complicated payoff distribution of an MTT? |
#2
|
|||
|
|||
![]()
There are a few chapters in The Mathematics of Poker that deal with these types of issues, but do not directly answer your specific question. I think that they provide enough insight from which to conclude that your question is probably impossible to answer, due to the variety of buy-ins and payout structures. Additionally, even if we played in the same tournament over and over again, the assumptions about the likelihood of various outcomes for a given player that would be required in the model would be so speculative as to render the end product meaningless IMO.
|
#3
|
|||
|
|||
![]()
meh. You can still get an average ROI and standard deviation (both factoring in the staking deal) for the players results which should come close enough for a KC calculation. The answer? A boatload of buyins for anything approaching even a 1 standard deviation confidence in not dropping your player before he hits a bit enough cash to turn positive.
Small stakes for a lot of frequent tourney players is probably going to be far more satisfactory than just backing a couple of horses in large buyins. |
![]() |
|
|