**How Poker Math Made Me $100K/Month Trading Prop Firms — Transcript & Summary | SozAI**
Source: https://sozai.app/transcript/poker-math-100k-month-prop-trading/

JJ Simon explains how poker math principles like expected value and bankroll management helped him earn $100K/month trading prop firms.

## Key Takeaways

- Expected value is the core concept linking poker and prop firm trading success.
- Focus on the overall decision's expected value rather than individual trades.
- Proper bankroll management and sizing using Kelly Criterion can optimize growth and reduce risk.
- Understanding break-even rates and variance is essential to sustain profitability.
- Simulations and data-driven approaches improve confidence in trading strategies.

## What the video covers

- JJ Simon learned key trading concepts such as expected value (EV) from playing poker starting with a $5 buy-in.
- Expected value is calculated by multiplying the probability of winning by the payout and subtracting costs, applicable to both poker and prop firm trading.
- He emphasizes pricing decisions based on final outcomes like pass rates and payouts rather than individual trade win rates.
- Bankroll management is crucial; poker requires conservative bankroll sizing, while prop trading can have higher edge and different sizing.
- Kelly Criterion is recommended for bankroll optimized sizing based on edge and capital.
- Break-even win rates depend on risk-reward ratios, e.g., 50% for 1:1 trades and 33% for 1:2 trades.
- Variance and probability distributions like binomial distribution help in risk management and understanding streaks.
- Simulations and backtesting multiple prop firm evaluations can estimate edge and expected returns.
- Prop firm trading often has simpler math but requires careful cost accounting including evaluation fees and resets.
- JJ Simon shares practical examples comparing poker hands and prop firm trades to illustrate these mathematical concepts.

## Chapters

1. 00:00 Introduction and Expected Value Basics
2. 01:27 Pricing Decisions and Pass Rates
3. 02:35 Comparing Poker and Prop Firm Edge
4. 03:51 Poker Example: Expected Value Calculation
5. 05:10 Break-even Rates in Trading and Poker
6. 06:24 Applying Expected Value to Prop Firm Challenges
7. 07:56 Variance and Probability in Trading
8. 09:16 Simulations and Risk Management Strategies
9. 11:00 Tracking Results and Evaluating Edge
10. 13:18 Summary and Practical Advice

Answers

## Questions about this video

What is expected value and why is it important in prop firm trading?

Expected value (EV) is the average amount you can expect to win or lose from a trade or challenge, calculated by multiplying the probability of winning by the payout and subtracting costs. It helps traders make decisions based on long-term profitability rather than individual outcomes.

How does bankroll management differ between poker and prop firm trading?

Poker typically requires very conservative bankroll sizing, often 100 times the buy-in, to manage variance. Prop firm trading can have a higher edge, allowing for different, often more aggressive sizing strategies, especially when using tools like the Kelly Criterion.

What role does variance play in trading prop firms?

Variance represents the luck or randomness in trading outcomes. Understanding variance and using probability distributions like the binomial distribution helps traders prepare for losing streaks and size their risk appropriately to avoid ruin.

## Full Transcript — Download SRT & Markdown

00:00

Speaker A

Everything I learned to make $100,000 per month, I learned playing poker. And it started at a $5 buy-in. Let me talk to you about it. So, the most important thing in poker and in prop firm trading specifically is expected value. EV,

00:14

Speaker A

short for expected value, basically is just going to be your cash received minus your cost. It can get a little bit more complicated as your cash received is obviously a percentage chance of receiving a set amount of cash. So, for

00:26

Speaker A

a basic example, if you would have a 50% chance of making $1,000, that straight up is just $500 in expected value. You just multiply those two together. Now, of course, there is a cost to attempt an upside both in poker and in proper

00:41

Speaker A

trading, which you could maybe assume is just the $100 trading evaluation. So, expected value is a pretty simple concept. And the way I trade prop firms specifically is instead of looking at my challenge is how much money I'm winning

00:52

Speaker A

and how much money I'm losing. I look at the expected value. What is my chance to win this trade multiplied by how much is my account going to be worth after this trade wins. Same thing if it loses

01:02

Speaker A

because obviously you lose about half the trades you take. So you have to price that specifically. So price the decision that you're making. Don't price your specific trade and its win rate. Do the decision like I just said, $50

01:16

Speaker A

valuation, you have a chance to pass it, right? So, if you had a one out of three chance of passing it, then maybe your expected value of that funded account would be different than if you had a one

01:27

Speaker A

out of 2% or one out of two chance of passing the evaluation. So, try to price your expected value based on the outcome, the end result, your payouts, your pass rate, not just chance of winning an individual trade. Obviously,

01:40

Speaker A

the individual trades do make up sort of a tree of outcomes until you do get the final result, but in general, the final result is the only thing that matters.

01:48

Speaker A

So, try and focus a lot more on that specifically instead of individual trade win rate. You can also have a pretty accurate estimate of your edge. Like you can back test, you can pretend you have 10 prop firm evals. You could give them

02:00

Speaker A

all 3k profit target, 2k max loss. You can see how many you pass. All right.

02:05

Speaker A

Also, budget for variance. Binomial distribution should be pretty easy. There's calculators online for it. It can tell you your exact probability of passing 1, 2, 3, 4, 5 times out of 10 evals and then size your risk so you can keep

02:17

Speaker A

playing. In poker, they have super conservative bankroll requirements. So, for example, from what I've heard, if you were to play in a $5 buy-in, you would want to have a hundred times of this available. So, you'd want

02:31

Speaker A

Oh, yes. That's 500. You'd want $500 bankroll just to buy into a $5 game.

02:35

Speaker A

That's 1%. Prop firm trading, you have a lot more edge than you do playing poker. I assume at least for me I do. I was pretty good at poker. I made about $25,000 during my time in college at the casinos

02:48

Speaker A

and such. You can see some examples here. Got a nice stack of cash. But anyways, you would have much likely a higher return on your prop firm investment than on your poker investment. So your sizing would be a

03:01

Speaker A

little bit different. If you're interested in learning more, just search up Kelly Criterion. It's pretty easy to understand and you can learn specifically like bankroll optimized sizing. Um, that's what I teach in my program as well. So,

03:13

Speaker A

bankroll optimal sizing based on how much money you have and based on your edge. Next, pot odds, payout odds.

03:19

Speaker A

They're pretty similar. All right, it's the same expected value framework. Now, here's an example from poker. If you haven't played poker before, just bear with me. It's pretty fun. It's pretty interesting. But anyways, assume there's $150 in the middle. All

03:32

Speaker A

right. So, you and an opponent are playing a game for $150. All right. You have to put in $50 to make an attempt to win this just to call their bet. All right. And if you do that, you have a

03:43

Speaker A

40% chance to win. Prop firm trading is very similar. $50 a trade, 40% chance to win the trade. It's very, very similar.

03:51

Speaker A

Your expected value in the case of a poker hand, you have a 40% chance to win multiplied by how much you would win, that 150. To win that 150 in the middle, how much are we risking? 50 risking your

04:03

Speaker A

50 here. The 100 in the middle, 150 is in the middle. It's already a sunk cost.

04:06

Speaker A

You already put it in. You can't take it back out. You would have to win it back, which you have the 40% chance of winning. If you have a 40% chance of winning, that means you have a

04:15

Speaker A

60% chance to lose. You just do one minus 40%. And you multiply these outcomes together and you get an expected value of 30% or $30, sorry. So, you know, on average, every time I call the opponent's bet with my 40% chance of

04:29

Speaker A

winning, I'm going to make $30. So, you'd want to call that as many times as possible. Now, there's also a break-even rate that's really important in trading and in poker.

04:40

Speaker A

In this case, how much you put in 50 dividing by the total amount. So, in the case of trading, you would do how much do I put in? How much do I risk? Well, that would be your stop

04:54

Speaker A

loss. What is my profit target? My profit target in trading, I'll just do an example in a second to make sure it makes sense. We need parenthesis here as well. Plus the stop loss again.

05:10

Speaker A

So, risking 50, risking stop-loss, take profit 150. So, if you want to risk a 1,000 bucks and you want to go for $1,000, that's a one-to-one trade.

05:19

Speaker A

Obviously, everybody knows the break-even into that is 50%. So there you go. That's just how you calculate the break-even rates. If you're ever interested in one, if you want to do a 1 to 2, then that would be a thousand out of 2K, 1K.

05:33

Speaker A

So one out of three. That's the idea. Next, so that's important for prop trading as well. Like if you want to know the break-even rate, which you have to perform above obviously to make money. So, you should know my break-even

05:48

Speaker A

rate is a 50% win rate on my 1-to-1 or it's a 33% win rate on my 1-to-2 R trade.

05:54

Speaker A

So, now you know I have to do better than that to make money and then you can make sure your strategy actually does that. Anyways, the break-even on that poker would be a 25% equity, but you have 40%. So, when you have a higher

06:05

Speaker A

chance than the break-even, you're going to be making money. Now, prop firms are even more simple. I think they'd be more simple. At least for me, they are.

06:13

Speaker A

Assume you have a 30% chance of receiving 300. These numbers are vastly different for everybody. They're vastly different on different firms. This is just an example so you can sort of see how I apply these numbers and then try

06:24

Speaker A

to do it yourself for your specific numbers. So maybe you have a 30% chance of getting a $300 payout. Same thing, expected value calculation. Multiply the probability of the upside by how much the upside is and then you subtract your

06:39

Speaker A

fee. All right. The reason why we're not subtracting a probability times a fee is because we already paid that fee. So, it's basically a 100% chance that we had to pay the eval fee. If that makes sense. In this case, we are receiving

06:53

Speaker A

plus $40 in expected value. So, you'd want to take as many of these challenges as possible if it cost 50 and your average 30% chance of a $300 payout. You want to play this game as many times as

07:05

Speaker A

possible. The break-even on this one. So you can also do break-even on trades and you can do break-even on this. So this one should be pretty simple, right? Like if you buy a challenge for 50 bucks, one

07:17

Speaker A

out of six needs to convert to a payout, right? Because 50 times 6 is 300. So you bought six, one gets a payout. That's break-even. And you could just do 50 divided by 300 to give you 16%.

07:30

Speaker A

So, your cost should also technically include the activation fee, every eval that you purchase, every reset that you do, but that's sort of built in. Just figured I'd add that. And if you want to get really specific and you like

07:42

Speaker A

simulating things, might as well.

07:56

Speaker A

talk about variance. We learned about expected value, which is just how much our stuff is worth. Now, we need to talk about variance, which is basically luck, probability, your chance of winning.

08:05

Speaker A

Well, it's not your chance of winning. It's like how likely are you to be winning more than you should versus losing more than you should in a luck based manner. Just like flipping a coin, you're going to flip a coin 100 times.

08:15

Speaker A

You expect to get 50, but you might get like 48. That's just variance. They're just different outcomes essentially.

08:22

Speaker A

Now, some examples. 30% chance of a payout right? Finding your chance of a failure is very easy. It's 1 minus probability of winning. Winning means success, I guess.

08:36

Speaker A

So if this is 30%. Then you know that your probability of not winning is 70%. They just have to add up to one like 100%. So you 30% lose. Wait now 30% win, 70% lose in this example. So what's the probability of

08:51

Speaker A

losing 10 in a row, right, of that same exact one? our example where we start for 50 and we have a 30% chance at three 300. This same example chance of losing exponent to the power of 10 and then you get 2.8%.

09:09

Speaker A

So you can have positive EV, right? Like we can expect to make money on this bet because this number here was that 90.

09:16

Speaker A

Yeah, that should be 90. We're almost expecting to double our money every time we buy this. But you could still lose 10 in a row 3% of the time.

09:25

Speaker A

So, make sure you understand winning strateging. Make sure you have Make sure you understand that winning strategies can possibly have incredibly bad losing streaks to where you don't abandon the strategy, but you also need to know if it's just a bad strategy. So, make sure

09:42

Speaker A

there is lots of testing. Also, if this number ever becomes below 0.5%. then I would probably start to consider that maybe something's wrong.

09:56

Speaker A

All right, 1% chance that is still statistically likely enough for me to be like, "All right, maybe something's up, but I'm going to keep doing it." When this cuts in half to 0.5%, then I'm like, "All right, something something's

10:06

Speaker A

something's gone wrong. I'm going to I'm going to check make sure everything's as it should be." Now, of course, there's noise.

10:13

Speaker A

What this means is it's sort of like a bell curve. You would expect 30% of your accounts to get a payout, but it could fall over here at like 19%.

10:24

Speaker A

It could also go up to like 41%. And there's a specific probability that it falls in here. Maybe it's 95%.

10:31

Speaker A

Meaning 5% of the time you'll have a 41% or higher payout rate. And you can use this formula for that.

10:40

Speaker A

These are just some examples of 20 attempts. your chance of falling outside of any given bounds. Basically, the more attempts you have, the more likely you are to come back in here towards the 30%. Which is why this is taller, if

10:55

Speaker A

that makes sense. So, higher chance to get closer to 30 the more attempts you take. Um, basically, same thing with a 100 coin example. You flip a coin 100 times. No, that's a bad example. We'll do 10 times. You flip a coin 10 times.

11:09

Speaker A

Maybe you get four and six. Maybe you get three and seven. Right? If you flip a coin a thousand times, your chance of getting 300 and 700 is zero. Like that's never going to happen because it's 50/50. Maybe getting

11:24

Speaker A

495 and 505 is very likely. Well, not very likely, but it's it's pretty likely, right? It's not going to be exactly 500 500. Uh but 3 and 7 converting to this, that's basically impossible over the long run. It might

11:37

Speaker A

even be impossible. Uh, so make sure you're aware of that as well because your rate could fall into this bottom 5% luck and then if it ever becomes bottom 5% luck, then something's probably wrong.

11:50

Speaker A

Here are some examples of what I used to do for poker. I went to Texas Card House in apparently April of 2025 and I track a bunch of different stuff.

12:00

Speaker A

Track the buyin, track the cash out. So this is my eval fee, the poker buyin.

12:04

Speaker A

Basically, this is the payout, the cash out. Track the start, track the end. Oh my. Track the duration. Track the hourly, the ROI, the type of game you're playing, where you're playing it. Lots of things come into effect that could

12:18

Speaker A

impact how much money you're making. Usually, just like the type of player. Um, but in general, same thing with trading. Lots of stuff is going to impact maybe what instrument you're trading, your risk-to-reward, your win rate, obviously, your psychology. As

12:29

Speaker A

much stuff as you can document, the better. Maybe which prof you're trading on, which proper plan you're buying.

12:35

Speaker A

Because if you're given two rule sets and they're they're pretty different, right? Like maybe one account's 20% consistency. Maybe an account's 100% consistency, but it's got a 2K payout cap. This one's maybe it's got a 5k payout cap. The same strategy is going

12:50

Speaker A

to perform extremely different on these two. And one of them it must perform better on. So make sure you simulate and just choose the one that it works better on. All right. GTO that is called game theory optimal and that is technically

13:04

Speaker A

the best way that there is to play poker. There are a few different ways to make it more optimal slightly just what are called exploits. Basically GTO is how a computer would play poker is the most optimal way on ma from a

13:18

Speaker A

mathematical POV like a human is not going to beat it essentially because it is playing the most optimal way possible. Now, if someone is playing really bad at poker, meaning they don't fold ever, so player X has never folded,

13:34

Speaker A

right? They're going to call every bet that you make, that means you should never bluff, right? If they're going to call every bet, never bluff.

13:42

Speaker A

And always bet. Always bet when you have a good hand and never bluff if your opponent always calls. That's an exploit. In a spot where a computer might decide to bluff because you have a really bad hand, we know that looks like this dude's

13:58

Speaker A

calling every bet, so maybe I'm not going to bluff. Now, so there are, of course, exploits that use evidence about their opponents. Now, prop trading is a slightly different problem. Okay, there is still an optimal way to approach it

14:13

Speaker A

because you are given a rule set. It is a complete information game, which is amazing and I think it's why I've made so much money doing it. Just because there is complete information, you can optimize the rules, right? You're given

14:25

Speaker A

a rule set, there's a bunch of different ways to trade in that rule set, but one of those ways must be the best way. So, if you can find that way, then you can make $100,000 a month. Uh, no income

14:36

Speaker A

claims on YouTube, but I've been able to make $100,000 a month just by finding the best way to fit in that rule set.

14:42

Speaker A

Now, a little bit about how I've been able to do that is basically just simulations. Okay, I assume with a 1R trade, a 2R, a 3R, I know my win rate for these. I know my strategies win rate

14:56

Speaker A

for these. I've tested it over a year of like actual trading and then eight years of back testing. I even know my win rate for a 0.5R if I ever wanted to try that.

15:04

Speaker A

So, I know my win rate. Okay? And your account starts at a certain state, zero.

15:09

Speaker A

From there, you win or you lose a trade. On the top side, you have a probability of winning. You also have a probability of losing. Now, your account's going to be at a different state if you win versus if you lose, right? It's going to

15:22

Speaker A

be worth a different amount if you lose money versus make money, of course. So, in a specific rule set, you can see how much is my account worth if it's at $51,000 or if it's at $50,800, right? So, if you win $800 bucks or if

15:42

Speaker A

you win $1,000, it's obviously going to be worth a different amount. Maybe this one's worth 700. Maybe this one's worth 900 right?

15:48

Speaker A

And you would have a specific probability of winning this trade. You'd also have a probability of winning this trade.

15:54

Speaker A

They'd probably be different probabilities since you have a different profit target and maybe you keep the risk-to-reward a little bit different. Maybe you trade a plus or minus 800, plus or -,000. In that case, it would probably be the same

16:05

Speaker A

just because it's a 1 hour trade. But I know if I trade a 1 hour trade, I'm going to win it at x% of the time. And I know I want to win $1,000 on my one trade because my account's going to be

16:15

Speaker A

worth 900 versus this one up here being worth 700. Of course, you do have to model the losing side as well. just do one minus probability of winning to get your probability of losing and that should be the same from there. But in general, I

16:29

Speaker A

want to know the probability I win multiply by how much my account's going to be worth if I win. Now, why don't you just go for an infinitely large win?

16:37

Speaker A

Because your probability of losing goes up a lot. So, whatever you gain by trying to win more, in this case, going for an extra 200 bucks, you'd also lose an extra 200 bucks, right? Because your risk is now a,000 instead of 800 on that

16:50

Speaker A

trade. So whatever you would gain in the potential account state after you could also lose on the downside by risking more basically you do I mean you do do that technically also for expected value since it's worth a different amount and you have maybe a

17:06

Speaker A

different probability of winning versus probability of losing you should also instead of maybe instead of doing this if it's if it's not something you're able to solve for maybe instead do the simulations I was talking about earlier simulate It's four

17:21

Speaker A

different prop firms, all with different rules. One of them has to work best for you. And then just choose and use the firm that worked the best for you.

17:30

Speaker A

There's technically no need to do all these calculations. I mean, it's not really going to do anything bad. You just won't be performing optimally. You might still make money, which is great. But just if you can't do it, just use the best firm

17:43

Speaker A

for your specific strategy. You don't have to optimize your strategy or the specific account state model. All you have to do is just make sure you're using the best firm for your strategy.

17:53

Speaker A

It could definitely be optimized. If you're not using this formula though, you're not optimizing it for sure.

17:58

Speaker A

That's just guaranteed because this is like the statistically best way to perform in a given rule set. No hate, just straight up math. But at least choose the best firm for your strategy and your performance overall. So you

18:12

Speaker A

could use your win rate, you could use your risk-to-reward. Make sure you know all these values though. And make sure you have at least 200 trades to validate that. Five trades. That's not going to be enough sample size like we talked

18:22

Speaker A

about earlier. Here's a picture. Ignore this guy. Here's a picture of GTO Wizard. It was on my Apple Pro. What is that called? Apple Vision Pro. I think the VR headset thing. Anyways, that's why it's blurry. But these are a bunch

18:36

Speaker A

of poker hands, right? This should be 13 by 13. Is there 13? Yeah, there's 13.

18:40

Speaker A

What am I saying? 13 by 13. And you can have any specific one of these hands.

18:47

Speaker A

And based on the cards that are in the middle with this hand, I would raise by 2.5, 2.5x, that sort of thing. Same. So, same thing with poker. You got three cards in the middle, you got two cards

18:58

Speaker A

in your hand. There is an optimal decision based on that because you're given a bunch of rules. Same thing in prop track. Here is me trading while using GTO Wizard to train poker on my Apple Vision Pro. Now, in poker, when

19:13

Speaker A

you're making money, the next thing you should do is multi-table, right? So, if I'm playing $20 buyins, I have two options from here, right? I could do 10 games of a $20 buyin at the same time, online poker, so I have like 10 tabs

19:27

Speaker A

open. Or I could do one game of a $200 buyin. All right, they're the same risk, right? Like I put 200 bucks at risk either way. One of these though might be more effective than the other.

19:40

Speaker A

Personally for me, it was playing this one for two reasons. First, your expected value in these games might be higher. The larger the buyin, the better the player, so you usually have less edge. For me, that was the case. I never

19:53

Speaker A

really went above 510 because I felt like I wasn't studying enough to have an edge there. Also, your variance. If you have a $200 buyin that you're doing once versus 10 sets of 20, vastly different variance, right? Imagine we're going to

20:08

Speaker A

double. Imagine we play our poker until we lose it all or until we double it.

20:12

Speaker A

That's kind of like a standard thing that I used to do. I don't know if that's good, but we could go to zero or we could go to 400, right? Maybe assume we have a 50. You know what? We're going

20:21

Speaker A

to do 60% chance. So, the math is easy. Maybe we have a 60% chance of doubling, which is really good EV. Multiply those two together. That's 240 bucks of EV and then zero. So, your 200 becomes 240 on

20:31

Speaker A

average. Now, for these though, 60%, what's the chance that you lose 10 in a row? 0.4 4 to the^ of 10. I don't know what that is. It's probably like less than 1%. So you have a 60% 40% chance of

20:43

Speaker A

walking away a loser here and maybe a lot less chance of walking away a loser here. That's the goal with multi-tabling and to get lower lower what's the word for that? Worse opponents. I'm just going to say worse

20:56

Speaker A

opponents. Anyways, now profit trading is a little different though. All right. I wanted to to model some more variance for you.

21:06

Speaker A

So, you could add more props. You could trade more accounts, right? There's lots of stuff that you can do. Oh, damn.

21:14

Speaker A

Anyways, lots of stuff you can do. Personally, if I was to choose between risking 2,000 on one account or 200 on 10 accounts. In the poker example, I choose this one, right? Less risk. On the prop, though, I

21:29

Speaker A

think I'm going to choose this one now. The reason why is we're still risking the same amount of money effectively, but like I said, there's different rule sets. The most common evaluation rule set is a $3,000 profit target and a

21:43

Speaker A

$2,000 max loss limit. All right? So, if your profit target is 200 bucks, imagine how many trades that's going to take. You're just going to go up and down. You might not even hit this within a year. You got to win 15 more than you

21:56

Speaker A

lose. It's going to take you forever. So personally I would do more risk on one account. Same risk overall but more on one account to get to where you want to be faster. Lastly, bankroll management.

22:07

Speaker A

That is how you win at poker in the long run. Same thing with prop firms. Okay. I would prefer your risk of ruin to be less than 0.5%. Just like that statistic we talked about earlier. And you can

22:19

Speaker A

calculate that for yourself. Use the thing at the start of the video. Also in the description, click on my free playbook that goes into my strategy. It goes into my approach a lot more and it's completely free. So, click the link

22:30

Speaker A

below. It should say my free playbook. Just download that. You can learn a lot more. You can have some more examples as well. Anyways, assume you have the $50 total cost per your eval. A,000 bucks buys you 20 obviously.

22:42

Speaker A

Then, if you have $2,000 of max loss and you only risk 100 bucks per trade, it's going to take you 20 times to lose it, right? So, understand also that trailing draw exists. that's going to keep turning up as you make money. So, with

22:58

Speaker A

this specifically and with this specifically, you should be able to model your exact risk of ruin, your exact expected value so that you know if I start with $1,000, I have X% chance of turning it into Y dollars and I have Z%

23:11

Speaker A

chance of losing it all. Very important things that you should know before you start.

23:17

Speaker A

Last thing to end it off, tracking. I tracked religiously my poker results. You can see here just different casinos, the different stakes that I played, the different buyins that I played with, how much money I made. You saw the one

23:31

Speaker A

earlier that went more into depth, but each one of these had that more in-depth analysis. I did it forever. Here's January.

23:37

Speaker A

Here's April. And it goes on more and more. Obviously, I just picked two pictures for you. But also had a horrible downtrend.

23:45

Speaker A

1260 loss, 700 loss. But then 2150 win, 700 loss, 600 loss. but then here a really good streak. So, it's important that you know, am I just getting lucky here or am I actually generating positive expected value? And hopefully

23:58

Speaker A

the statistic that I talked about today gave you a lot more in-depth detail about how to do that on a prop firm. And I hope you learned a lot more about how I or proof that I played poker because

24:07

Speaker A

some people think I didn't, which is weird. proof and examples of how poker got me into all of the correct mindsets, psychology, risk management, variance understanding, expected value understanding, all that sort of stuff that is very very related to poker and

24:22

Speaker A

psychology. I don't know if I mentioned that. I should have mentioned that in this video. Whoops. It's very similar.

24:27

Speaker A

It's it's very similar. And I think my poker psychology is why I got so good at trading psychology with just one huge trading mistake that you've probably heard about before. In general, that is how I started with $5 poker buyins, ran

24:39

Speaker A

up to $25,000 in bankroll, got into trading, and now I'm doing $100,000 a month in profit trading through this approach that was mostly molded by poker. Thank you for watching and I'll see you in the next

Topics: poker math expected value prop firm trading bankroll management Kelly Criterion risk management break-even rate variance trading strategy JJ Simon

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