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Optimizing Tables

simonchad25s
simonchad25
edited July 2018 in APT Questions

Hi APT,

I practice on here from time to time but am growing really frustrated with your tools. Let me share an example of my frustration. I recently created a table (KGB's Dungeon) and it was a 5/10 game with all playable hands, and the player mix was OVER aggressive. I found that selecting OVER aggressive wasn't helping me in terms of what I was trying to improve at. So, I moved the table aggression down to AVERAGE for table. I played nearly 25 hands and each time I opened the pot I got 3B nearly 90% of the time and flat called 10% of time when the other players didn't fold. That is completely ridiculous and whatever input function you guys created into your model is completely off. Please find me a game when the opener gets 3B 90% of the time and it's an "Average" table. Also, in these same games the Big Blind folds WAY TOO often. In most games, especially 9 handed the Big blind can call an opener with nearly 50% of all starting hands. What this means is the Big Blind should be folding only 1 out of every 2 times, but this is CLEARLY not the case here. The big blind folds so much. Thank you.

Comments

  • AllenBlay
    AllenBlay
    Hi, if you look around this forum you are going to see a bunch of threads with people posting about how the bots are not aggressive enough and don't three bet enough even on aggressive mode, and threads talking about how the bots defend the blind too much against raises. Bottom line is that the impression of the bots is driven very much by the distribution of cards in a small sample and everyone seems to get a different opinion on them. I'm not somewhere where I can look at your hands right now, but I expect that if I look at them what I will find is that either the three bets were justified in the sample of hands or the bots figured out that you fold too much to three bets and they are trying to punish you for folding too much - they learn fairly quickly.

    I'm definitely not saying the bots are perfect - they aren't and they aren't designed to be perfect. But I think with the aggressive setting they are as aggressive as I'm used to seeing.
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