Frequently Asked Questions (FAQs)

We use Monte Carlo simulation to estimate the chances of you winning assuming all players are playing.

Basically, what is happening is the following. For all the unknown cards, we randomly draw a card from the cards remaining in the deck for your opponents and the shared cards. We repeat this 1000 times within a short 0.5 seconds.

Finally, we analyze and summarize the results and provide you with an estimate of your winning odds.


While we understand that there are software out there that considers opponents playing range, we do think it is very hard for a player to consider the ranges of each different opponents. Our goal is to create a calculator that players can use while playing online poker. Our design will always try to limit the number of inputs that the user will need to input into our system during their game.

Furthermore, we truly believe that adding opponents' hand ranges introduces biases into the calculations. Adding biases may create more unfavorable situation using our calculator.

No. is actually still useful.

When we assume all players are playing, this is the worst case scenario. The more players that are still playing, the less likely you will win. So, if tells you that you have 65% chance of winning, you probably have a higher chance of winning.

Basically, our estimate is conservative. It is more well-suited for people who are patient and grinding cash games.

In a nutshell, when the probability is greater than 50%, we start advising our users to start betting. Once again, this is quite conservative.

Why do we advise our users to only start betting after probability is greater than 50%?

It boils down to:

  1. Some common behaviors in cash game
  2. The worst case reward-to-risk ratio
  3. Generating a positive return in the worst case reward-to-risk ratio

In a cash game, it is very common that, if a game continues to the flop, then it usually becomes a showdown of 2 players. In terms of reward-to-risk ratio, this is the worst case. If you were 1 of the players, then it means that this worst case reward-to-risk ratio is 1-to-1. Basically, you have to risk 1 chip to gain 1 chip.

In the worst case reward-to-risk ratio of 1-to-1, you will need a winning odds of greater than 50% to generate a positive expected return. The expected return is calculated as:

  • Expected return = (Odds of winning)*(Reward return) + (100% - odds of winning)*(Loss return)

If you do the math, you will find that you will need at least 50% chance of winning to generate a positive return for the worst case reward-to-risk ratio of 1-to-1.

Please note that it will be hard to get a winning chance of above 50% prior to preflop as more players are playing. You are encouraged to try to stay in rounds where the bets are not too aggresive and you hand is equal or better than the top 10th percentile.

The max percentage of chips to bet is calculated based on Kelly citerion. Kelly citerion maximizes your return in the long run by basing on the odds of winning and the reward-to-risk ratio (i.e. pot odds). The output of Kelly citerion is how much percent of your remaining chip to bet on.

Please note that Kelly citerion optimizes the reward and not the reward-to-risk ratio. This means that your bankroll could be quite volatile in the short term.

Unfortunately, we don't believe using in tournaments would yield any good long term results. Tournaments are designed to weed out players with lower bankrolls quickly. This type of fast playing game makes less effective because is meant help you make money in the long run.

Our recommendation is to use with cash games.

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