LowWater
06-24-2010, 07:18 PM
I'm trying to find the right way to ask a question.
I know a winning player who suffered through a 35 buy-in downswing. As I understand it a losing player cannot have a downswing; for them a downswing is an indirect measure of time. As long as it was a given that 95% of the time his downswing would be under 35 buy-ins, what other conclusions can be drawn?
Suppose his win-rate inclusive of this downswing was 5BB/100 over 20K Hands. With these four parameters of Bayesian statistics, what other conclusions can we draw?
1. Worst downswing: 35 buy-ins
2. win-rate = 5BB/100
3. power (N) = 20,000 hands
4. CI (confidence interval), downswing = 95%
What if we wanted to increase our insurance to say that 99% of the time, my friend's worst downswing would be less than or equal to 35 buy-ins? What further parameters do I need to know?
I know a winning player who suffered through a 35 buy-in downswing. As I understand it a losing player cannot have a downswing; for them a downswing is an indirect measure of time. As long as it was a given that 95% of the time his downswing would be under 35 buy-ins, what other conclusions can be drawn?
Suppose his win-rate inclusive of this downswing was 5BB/100 over 20K Hands. With these four parameters of Bayesian statistics, what other conclusions can we draw?
1. Worst downswing: 35 buy-ins
2. win-rate = 5BB/100
3. power (N) = 20,000 hands
4. CI (confidence interval), downswing = 95%
What if we wanted to increase our insurance to say that 99% of the time, my friend's worst downswing would be less than or equal to 35 buy-ins? What further parameters do I need to know?