04-23-2002, 05:44 PM
I created a simulation in VB to get some insight into some questions that I had and thought I would share the results. If anyone has any comments on how I could make this more useful it would be greatly appreciated.
I basically programmed a full ring game with 1.00/2.00 bets, complete with blinds(.50/1.00), moving button, rake, and different AI in each spot. I forgot to add the tip. Here is the setup.
Preflop
Players 1 and 7 are intelligent players, taking into account cards and position according to one of Abdul’s writings
Players 9 and 10 are fish and always see the flop
I set all other players up with a strange algorithm that I have seen on low stakes online poker a lot. They love all pocket pairs, and like flushes(two suited cards), and like two cards bigger than ten. (Will always raise loved cards, and will call with liked cards)
PostFlop – All pretty much play the same. Fishes will call one bet, top-pair/better players will bet, and four-flush/str8’s will call.
Turn – One fish will call a bet regardless. All other players will follow the same post-flop criteria.
River – Top pair or better bets, everyone else stays at this point (I should probably change this).
Results: I first wanted to look at the standard deviation of players 1 and 7(who I consider to be the best players). Here is how they fared
Player 1 :
Total over 2000 hands - +420.5 units (A big bet is 2.00) (10.51 units/50 hands)
Standard Deviation for each 50 hands : 28.70 units
Biggest 50-hand win – 71.7 units
Biggest 50-hand loss – 43.2 units
Standard Deviation for each 100 hands : 35.67
Biggest 100-hand win – 77.3
Biggest 100-hand loss- 43.1
Low point -43.1 units
High Point +420.5 units
Player 7:
Total over 2000 hands - -24units (A big bet is 2.00) (-.6 units/50 hands)
Standard Deviation for each 50 hands : 24.9 units
Biggest 50-hand win – 60.9 units
Biggest 50-hand loss – 47.8 units
Standard Deviation for each 100 hands : 24.62
Biggest 100-hand win – 54.7
Biggest 100-hand loss- -35.2
Low Point -91.7 units
High Point +16.7 units
Average Players Results After 2000 hands
2 +.5 Units
3 +359.7 Units
4 –128.1 Units
5 –37.6 Units
6 +223.8 Units
7
8 –14.1 Units
Could this be a result of position? This is very odd to me.
Fishes
9 –1612.3 Units
10 –2007.6 Units
Rake 2819.2 Units
Net/Gain Loss after 7,000 hands
1 +1296.7 units
7 +732.4 units
2 +588.8 units
3 +501.3 units
4 +437.3 units
5 +633.6 units
6 +1072.2 units
8 –597.9 units
9 –5365.3 units
10 –9111.9 units
Rake 9812.8 units
Findings: The standard deviation findings were somewhat interesting, but this is more of a testament to game selection than anything else. Amazing how much two fishes can pay off. I was also amazed out how well, depending on position, the standard strategy worked.
I also took some comfort in seeing that a player with a clear advantage was actually breaking even (losing 12 big bets)after 2000 hands(between 45 and 70 hours)
Any comments would be greatly appreciated.
Thanks much,
-Jim
I basically programmed a full ring game with 1.00/2.00 bets, complete with blinds(.50/1.00), moving button, rake, and different AI in each spot. I forgot to add the tip. Here is the setup.
Preflop
Players 1 and 7 are intelligent players, taking into account cards and position according to one of Abdul’s writings
Players 9 and 10 are fish and always see the flop
I set all other players up with a strange algorithm that I have seen on low stakes online poker a lot. They love all pocket pairs, and like flushes(two suited cards), and like two cards bigger than ten. (Will always raise loved cards, and will call with liked cards)
PostFlop – All pretty much play the same. Fishes will call one bet, top-pair/better players will bet, and four-flush/str8’s will call.
Turn – One fish will call a bet regardless. All other players will follow the same post-flop criteria.
River – Top pair or better bets, everyone else stays at this point (I should probably change this).
Results: I first wanted to look at the standard deviation of players 1 and 7(who I consider to be the best players). Here is how they fared
Player 1 :
Total over 2000 hands - +420.5 units (A big bet is 2.00) (10.51 units/50 hands)
Standard Deviation for each 50 hands : 28.70 units
Biggest 50-hand win – 71.7 units
Biggest 50-hand loss – 43.2 units
Standard Deviation for each 100 hands : 35.67
Biggest 100-hand win – 77.3
Biggest 100-hand loss- 43.1
Low point -43.1 units
High Point +420.5 units
Player 7:
Total over 2000 hands - -24units (A big bet is 2.00) (-.6 units/50 hands)
Standard Deviation for each 50 hands : 24.9 units
Biggest 50-hand win – 60.9 units
Biggest 50-hand loss – 47.8 units
Standard Deviation for each 100 hands : 24.62
Biggest 100-hand win – 54.7
Biggest 100-hand loss- -35.2
Low Point -91.7 units
High Point +16.7 units
Average Players Results After 2000 hands
2 +.5 Units
3 +359.7 Units
4 –128.1 Units
5 –37.6 Units
6 +223.8 Units
7
8 –14.1 Units
Could this be a result of position? This is very odd to me.
Fishes
9 –1612.3 Units
10 –2007.6 Units
Rake 2819.2 Units
Net/Gain Loss after 7,000 hands
1 +1296.7 units
7 +732.4 units
2 +588.8 units
3 +501.3 units
4 +437.3 units
5 +633.6 units
6 +1072.2 units
8 –597.9 units
9 –5365.3 units
10 –9111.9 units
Rake 9812.8 units
Findings: The standard deviation findings were somewhat interesting, but this is more of a testament to game selection than anything else. Amazing how much two fishes can pay off. I was also amazed out how well, depending on position, the standard strategy worked.
I also took some comfort in seeing that a player with a clear advantage was actually breaking even (losing 12 big bets)after 2000 hands(between 45 and 70 hours)
Any comments would be greatly appreciated.
Thanks much,
-Jim