A Collection of Updates: Life, Poker, and Exciting News

And just like that, it’s October. This past year has dragged on and flown by at the same time…if that makes any sense.

I decided to try something new today. My normal writing process is as follows…I typically start by outlining some of the key topics I want to explore. Then I fill out some of the details underneath and attempt to weave it all together into a cohesive blog post. It may not be the most efficient process, but it has typically worked well for me.

However, when I started writing this post a few weeks ago, I immediately ran into some challenges getting into a steady flow.

It’s been 6 months since my last post, so when I sat down to build an outline, I realized that I have a lot to share. After a few days of false starts, here is the general list of things I came up with to write about:

Just looking above at that outline…it’s obviously a pretty disparate list of topics. I tried to plow ahead with my normal process, and I struggled to come up with transitions from one topic to the next.

After a couple of days of banging my head against the wall, I gave up on trying to cohesively tie everything together. Instead, I decided to separate each bullet point into its own separate sub-section below. Call it a collection of mini-blog posts instead of one long update. So, while I hope that you do read the whole thing, I realize it’s a long post. So if you’d like to navigate to any individual section, you can easily do so by clicking on the links in the outline. Enjoy!

An overall update of 2021

When I last posted in March, I was taking care of my own mental and physical health. And while I’ve been up to a lot over the course of the year with my family and work, I’ve tried to prioritize taking care of myself as much as possible.

Since January, I’ve developed a series of consistent habits that have included:

  • Lifting heavy weights 4x per week — I bought a squat rack, bar, and bumper plates from Rogue and carved out an area in my garage to work out. It’s one of the best investments I’ve ever made.

  • A daily stretching and meditation routine when I first wake up — I added my stretching routine in July because my muscles often felt tight, and it has increased my range of motion considerably. I still feel like I struggle somewhat with meditation. I’ve tried Headspace and currently use Calm. I’ve recently been recommended Sam Harris’ Waking Up, which I plan to try.

  • Drinking more water — I started drinking a gallon of water a day while doing a 75-Hard challenge in January. The first week was miserable, but after that, I just got used to it. When the challenge ended, I kept the habit of filling my gallon water bottle up and drinking it daily.

  • Fixing my diet and mostly eating non-processed foods — I always ate well for the most part, but I’ve tried especially hard to stick to meats, vegetables, fruits, whole grains, and good fats while cutting out junk food and sugar.

  • Taking long walks daily — Again, another addition from the 75-Hard challenge that stuck. I needed to get two 45-minute workouts per day as a part of the challenge, so I used a 3-mile walk (2 loops around my neighborhood) as one of them. I found that I really enjoyed the time outside by myself. That time feels more meditative than my morning session, to be honest. I do my best thinking on that walk and often come into the house with a few ideas to write down.

  • Spending time outside — The climate in Michigan suits me perfectly. I never wanted to go outside during summers when I lived in the DC area — it’s so hot and humid. It always felt gross to leave the house and move around. The weather is a little cooler and far less humid up here. I don’t mind the cold and enjoy playing with the kids in the snow, so winter is fun too.

  • Sleeping at least 7 hours per night — I’m not as tired during the days now and don’t have to drink coffee all day. I have my 2 cups in the morning and am good for the day.

  • Talking with a therapist regularly — I started talking with a therapist last year, and it’s just been nice to be able to dive into my own thoughts and feelings with someone. I think that I understand more about myself. I used to think someone needed to feel “broken” to go see a therapist. But now I realize how beneficial that time can be. I think everyone would benefit from regularly seeing one.

  • Drastically limiting my social media time — This is obvious, but I was doom-scrolling too much in 2020. I deleted Facebook and have limited my Twitter and Instagram time to early morning while drinking my coffee or late evening before bedtime when I’m winding down on the couch. A+ decision.

I know that these are all seemingly obvious and repeated ad nauseam by everyone on “self-optimization Twitter". But they do work. None of these things have individually been a “magic pill” to make everything perfect. And yes, they take time and effort to include in my day. But the cumulative effect of consistently prioritizing the things on the above list has drastically improved the quality of my life.

To start, I feel great. I turned 40 this summer, and I think that I’m in better shape now than when I was 20. When I was in college, I skipped gym sessions regularly, viewing it as a chore. Now, I rarely miss a session, and never when I’m at home. When I do have to skip a workout due to travel, I feel sluggish and low-energy for a couple of days.

My mental clarity has improved significantly. The lifting sessions, long walks, therapy, and (I assume) meditation have all helped me to bring things back into focus. 2020 fucked with a lot of us. Finding time to sort things out in my head has helped me to put things in perspective and prioritize the things that I care about most in life — spending time with my family and my own health and happiness.

It also gave me the confidence to make a significant life decision. I recently gave my current company notice to resign. I don’t officially close out my work responsibilities until November, but the wheels are in motion to leave my job. After working in the corporate world for years, my heart just isn’t in it anymore. I was bored, unmotivated, and needed a new challenge.

I’m not ready to announce the specifics, but starting in November when I do leave my job, I will be devoting 100% of my time towards launching a new project within poker that I’ve been thinking about for the past year.

Since launching this site in January 2020, the communal response has been awesome. To be honest, I didn’t think many people would read a personal blog about data analysis and poker. To my surprise, it has reached a lot of people from all around the world. And many of you have reached out to me to discuss some of the ideas I’ve raised, ask questions about the data analysis and insights, and share some of the work that you are doing to dig into the mechanics of the game.

A consistent theme that I’ve noticed is that there are a lot of people from all around the world who are interested in exploring poker concepts through data. And I think there’s an opportunity to dig into that further.

I’ve decided to call my project Solver School, as an ode to the tool that we’re all so fond of using. I’m still figuring a lot out, but my overall mission is to teach others how to use data analysis to dive into the game tree and learn more about poker. I have the website up and running. It’s a shell at the moment, mainly there as a placeholder and to build an initial interest email list. I also have some branding and a logo designed (as demonstrated to the right), which I will be showcasing on some hoodies and t-shirts while I’m in Vegas next week (more on that below). There’s not much more to say than that I plan to launch in January 2022, and that I’m very excited to share my 20 years of data analysis expertise with the poker world.

As I have more updates in the coming weeks, I’ll share them both here and on the Solver School website. But eventually, all the work for that project will stay on that platform, keeping this site separate. So make sure you sign up for the mailing list over there so you get all the latest timing on its launch as soon as it comes out. You can also follow my new social media channels on Facebook, Instagram, and Twitter. There’s nothing there now, but more to come very soon.

Regulated online poker in Michigan

It’s nice to play online again. I know I could always play before on ACR or Ignition, but now that I’m in a regulated player pool, the overall online poker experience has been a huge improvement. As I mentioned in March, Michigan officially legalized regulated online poker in January with the launch of Poker Stars and BetMGM (Party Poker). Since I’m fortunate enough to have moved here last fall, I get to enjoy all the fun.

The games were wild, crazy, and profitable from the get-go. But over time, the ratio of recreational players to regulars went down considerably. By April, I saw my win rates decrease. I was still consistently beating NL200, but I found myself struggling in the NL500 and NL1000 games against the regular online pros. I was consistently getting punished for some lines I would take that worked fine in the live $5/$10 games I was accustomed to.

To help improve my game, I hired Brad Wilson from Chasing Poker Greatness for coaching to help me adjust from live to online cash. I also became friends with some of the Michigan regs and regularly talk through hands and strategy with them in group study sessions.

This extra work has helped me to identify leaks in my game. I worked hard on plugging them and was seeing really good results going into the summer. After a downswing in March-April, I booked my most profitable month of online cash ever in May and broke that mark in June.

My cash volume has died down considerably over the past 3 months. I never played the volume of play that I would ideally want to anyways. Throughout the first half of the year, I was lucky if I had a week where I played more than 8-10 hours. But since the start of the summer, my overall cash volume has gone down to basically zero. I’ve shifted my volume on the Michigan sites to tournaments, as I’m preparing for a 10-day trip to the WSOP. I’ve also been traveling a lot, going on vacations to see friends and family. I plan to dive back into the online cash streets in November when I’m back from Vegas.

Working with Brad Wilson

As I mentioned above, I started working with Brad Wilson. I had listened to a few of his podcasts previously, and his approach to poker resonated with me. Brad did not take a Pio-centric approach, which was important to me. I booked a 4-pack of sessions, and I’ve been working with him ever since. Working with Brad has greatly influenced the way in which I think about the game.

No Pio in my coaching sessions was seriously a priority for me. I wanted to push my boundaries into different study areas. I can tend to stay in the solver world too long, so challenging my brain to look at the game through a different lens is an area I wanted to explore. What I didn’t realize when going in was how data-heavy Brad is in his strategy creation — he’s just going at it from a different angle than I am.

Brad has analyzed millions of hands of actual gameplay and derived quantifiably-profitable strategies targeted at specific player profiles. He has a great knack for quantifying what’s important and using that to drive decisions. Working with him has helped me to be able to better simplify thought processes and translate them into heuristics that I can utilize in-game.

Brad recently invited me to appear as a guest on his Chasing Poker Greatness podcast. You can listen to it here.

I highly recommend anyone else reach out to Brad if you’re looking for coaching or to check out any of his awesome products. He’s one of the good guys in the poker industry. He does great work and is actively trying to make the industry and game a better place. 

PLaying in the Live Streets

It’s been nice to play online. But at the end of the day, I’m a live player at heart. I was cruising along in that arena until the pandemic hit. My last live session before the pandemic was in February 2020. After that point, I didn’t play a single hand of poker until I was vaccinated earlier this year. After I finally got the shot in March/April, I immediately jumped back into playing live. I’m about 30 minutes from the Detroit casinos and have made it there for a handful of sessions over the summer.

It’s great to reside a reasonable distance from live poker, but I do miss the DC poker scene. It’s easy to not realize how good the action is in the area until you’re no longer there. There was almost always a $5/$10 game running at MGM National Harbor. On weekends, a $10/$25 (or higher) game would also routinely get off the ground. Maryland Live is the other major local option and consistently ran $5/$10 on weekends. As such, there was never a shortage of decent games that I could play at any given time.

I’ll start by saying that Detroit doesn’t have a bad scene at all. There are plenty of places I could live within the country where I’d be stuck with no live poker or $1/$2 as my only options. Within the Detroit casinos, there are always at least several $2/$5 games running. The games are relatively decent and there’s a really good PLO scene with a lot of action that is tempting me to dedicate study time in that space.

However, the $5/$10 game only runs at MGM Grand and it appears to be inconsistent as to whether it gets off the ground. I live 35 minutes away from the casino, so there are times I make the drive and can’t play higher than $2/$5. MGM also lets people straddle from any position, which I really don’t like. In my opinion, this type of straddle ruins the flow of the game when someone comes in and straddles every hand. It’s also a terrible experience for the person to that player’s left who has to now act first every hand.

So while I do make it into Detroit from time to time, I don’t make it to the casinos nearly as often as I did in DC. Sometimes, it’s just easier to fire up a few tables on Poker Stars and play for a few hours on there.

I did take a 5-day Vegas trip to play right after I was vaccinated in May and got a ton of volume while I was out there. It was actually a pretty wild trip. I arrived in Vegas on a Wednesday — mask mandates and plexiglass was in full force. On Thursday, the CDC announced that it removed the mask mandate. By Friday, all the plexiglass was down at most casinos, and nobody was wearing masks anymore. It felt as if the pandemic just ended overnight.

It was awesome to be back in Vegas after an 18-month hiatus. I saw a bunch of friends, played a lot of poker, and finally felt normal again. As soon as I got home, I started planning my trip back. I’ve teased it enough, but that next trip happens to be…

Tournament poker and preparing for the wSOP

…my first World Series of Poker!! I post this today, October 15, and hop on a plane this afternoon to spend the next 10 days at the WSOP. I plan to kickoff my series tomorrow in Flight 1B of the $1500 Monster Stack.

Since this is my first WSOP, this is all uncharted waters for me. I’m fairly new to tournaments in-general — it wasn’t until January 2020 when I decided to start learning how to play MTTs. My plan at that point was to debut at last year’s WSOP, which we all know how that turned out. Before 2020, I had played in 2 live tournaments and a small handful of online ones in my life. Like I said, I’m a cash game player at heart.

I still don’t have a ton of experience — I’ve only played 5 more live tournaments in the past 2 years and about 1000 online ones. But I have been studying the format, and I think I’m getting better. I’ve had some good runs in some online events, highlighted by a 4th place finish in the Michigan SCOOP Main Event in May for $15K, a win in an ACR $88 Mega Stack for $9K, a 3rd place in a Sunday $60K Guaranteed for $6K, and a few wins in some daily online tourneys.

Here is the short-list of tournaments that I’m targeting for my 8 full days there:

My final schedule will almost certainly not include all of these. Since these are mostly multi-day events, making it past Day 1, in any event, will cause the next day to shift. I also may decide after a few grueling days that I need to take a day off. But my tournament play will be a subset of the list above. I’m sure I’ll also sprinkle some cash sessions throughout the week.

I’ve worked hard over the past couple of months to prepare for this, and I feel really good going in. I worked with Matt Hunt in some coaching sessions, grinded the WSOP-focused Home School training series by Solve for Why, and devoted as much volume as I can to tournament poker online.

I obviously have plenty to continue learning in tournaments, as evidenced by the fact that I am often in new and confusing situations. As with most cash players when moving into tournaments, I do a great job accumulating chips when super deep, but struggle when trying to navigate 20-30 big blind stacks.

But I’m getting better. I’m excited. I’m motivated. I’m focused. I’m ready to play some poker. Why can’t I put a run together and go deep in one?

Comparisons

I actually do want to write about poker in this post. Well, I suppose it’s more of a data analysis method, but I’ll obviously use a poker example to demonstrate it. And that is the method of comparison.

There are many sophisticated ways to analyze data. Comparison is not one of them. In fact, it’s a simple concept to understand, because we do it every day in our lives. When buying something, we compare different product features and prices of various options. When dating, we compare the compatibility we feel with someone to how we have connected to someone else, such as in a former relationship. When playing a game, we compare our performance to a competitor or a previous high score (that’s an example of a benchmark).

To back it up a bit, I’ll define the methodology. The comparison involves looking at two or more data points to evaluate against each other or a defined benchmark (usually an aggregate descriptor, such as the average). We typically use it to evaluate points side-by-side to understand differences, rank several items in a category, list key segments against one another, identify patterns or outliers in data, and in many other ways.

Back in March, Berkey invited me to lead the S4Y Mastermind about studying poker using solvers. In that session, I walked through the way in which I frame part of my solver-related study. Without talking about the concept specifically, I spent much of the 2-hour course (and subsequent 1-hour Q&A session) demonstrating the concepts of using comparisons of solver data to infer insights and derive strategies.

As I have been prepping for the WSOP, I have been working with Floptimal to familiarize myself with ranges at various stack sizes. In my opinion, Floptimal’s tool facilitates comparison analyses as well as any commercial poker product I’ve seen to date. I understand the challenges involved in presenting a lot of complex data in a simple-to-consume format. Floptimal’s UI for doing this is just outstanding, allowing for easy comparison of different data points and the ability to pivot to multiple dimensions. I highly recommend as an excellent study tool for preflop ranges.

When comparison is used well, it’s an effective way to make data analysis more accessible to all. As a result, when helping individuals start utilizing data-driven tactics to get better at poker, I often point to comparison as an initial methodology. By starting with a data point and comparing it to one or more reference points, we ask the question “in relation to what? The insights when compared to an anchor point can often drive home some important ideas.

The challenge with comparison is that it’s better used as a visual methodology. Or said better, it’s much easier to compare things when visualizing the differences and/or similarities of two or more items as opposed to simply looking at raw data points. As a result, we often have to categorize, organize, and/or translate the data into a visualization to get it in a format where we can make good comparisons. I’ll demonstrate with an example.

I created a simple aggregate report to analyze a flop scenario, focusing on a single-raised, UTG vs BB pot in a 6-max, 100BB cash game. I ran an aggregate report for 25 flops within PioSolver. I put the output into a table and gave it some minimal formatting to make it somewhat readable, but have otherwise done no manipulation to the data. Based on the chart below, how easy do you think it would be to derive some insights?

Unformatted PioSolver aggregate report output of 30 files for UTG vs BB single-raised pot formation in 6-max, 100 BB game.

Unformatted PioSolver aggregate report output of 30 files for UTG vs BB single-raised pot formation in 6-max, 100 BB game.

Pretty hard, right? It’s difficult to sort through and understand anything about the data set. I think most people’s eyes gloss over when they see a sea of raw data like this, mine included! But with a little bit of simple visualization work, we should be able to turn this table into a way in which we can utilize comparison to learn some new findings.

For instance, we could quickly sort a column by a metric that we may want to use as a baseline value from which to start the comparisons. We can also average all boards to set a benchmark that all other points can be compared to. That baseline value will give us an idea of the entire formation across all 25 boards, giving us a better idea as to how “good” or “bad” different boards are for our range in relation to the whole group.

Here’s that same chart from above with a bit of cleansing:

Formatted PioSolver aggregate report output of 30 files for UTG vs BB single-raised pot formation in 6-max, 100 BB game.

Formatted PioSolver aggregate report output of 30 files for UTG vs BB single-raised pot formation in 6-max, 100 BB game.

I didn’t do much, but that little bit has helped us compare some data points.

  • First, I sorted by the IP EV. I was always taught to start with the most impactful metric (or KPI in the business world), and I can’t think of a more important one in poker than expectation value. I’m assuming that we’re examining from the UTG perspective, although we can (and should!) certainly conduct this analysis for defensive positions.

  • I added some conditional formatting to a second set of data points — in this case our strategic action frequencies (bet 2/3 pot, bet 1/3 pot, and check). These three metrics will always add up to 100%, so it’s beneficial to group them together for analysis. I switched the column orders from the first table and added data bars to quickly identify the relative percentage to one another.

  • I included gradient shading on the three main success metrics that Pio outputs — EV, Equity, and EQR. For each column the average value is white with the above average values shaded green and the below average values shaded red. Since the table is sorted by EV, that column will have a continuous green to red flow. But the other two metrics don’t look as similar. Usually the three correlate somewhat with one another. Where they don’t can be an interesting point to investigate further and try to figure out why.

  • I also added data bars on the Global % metric. This represents how frequently we get to this game node. In this case, it’s also the measure of how frequent the BB checks. In most cases, the BB checks almost all of its range. But there are some instances with lower values, meaning the BB presumably donks a higher frequency. Insights like this are important to understand when doing this analysis, because it assumes something about an opponent’s strategy.

  • I created an average row as a benchmark to compare data points against. Now technically, I would have to do a bit more math to give a true “average” of these boards since they appear at different frequencies relative to one another (they’re also only a subset of flops in the game), but for the purpose of this demonstration, this pure average is fine.

  • Finally, I dropped all number significance to 1 decimal point. We don’t need to get more granular than that in this view. The extra precision isn’t helping anything. It just adds unnecessary complexity.

And these changes have helped! We can quickly look at the various boards and start to compare them to one another much more effectively. But I’m going to introduce one more addition that I think can help power this even more.

Comparisons are extremely valuable when paired with segmentation or attributes to call out insights. I’ve added a column that includes the flop texture for each board:

Formatted PioSolver aggregate report output of 30 files for UTG vs BB single-raised pot formation in 6-max, 100 BB game.

Formatted PioSolver aggregate report output of 30 files for UTG vs BB single-raised pot formation in 6-max, 100 BB game.

Just adding that one bit of segmentation can start to help demonstrate some insights. Notice how there are more Rainbow boards towards the top of the chart and Two-Tone boards towards the bottom. We can start seeing some interesting patterns in the data. Translating findings terms that we can understand and apply at the table, like board textures, is the way in which we can start connecting the dots between theory and execution.

There are so many different routes you can go with data analysis when you start layering in segmentation using attributes. Data can be powerful when grouped effectively. The magic point of study and strategy development is when you can identify those groupings that will be easily identifiable and memorable when you’re in-game at the table.

But once you do get that magic point, the analysis can go into a ton of directions from there. Think of all the possible segments you can explore:

  • Paired, unpaired, and trips boards

  • Rainbow, two-tone, and monotone boards

  • A-high, K-high, Q-high, etc. boards

  • Specific descriptors of boards (e.g. Ace-wheel-wheel, KQ-low, middling connecting boards, etc.)

There are a lot of different ways to categorize things, and all can potentially yield interesting insights. The point is to identify those segments that will yield interesting insights AND are accessible in your memory to be able to translate into heuristics that you can implement at the table. It’s a delicate balancing act and will certainly require a lot of trial-and-error, but this is how anyone can start digging into the data to analyze poker with the goal of developing in-game strategies.

Update to my spreadsheet

floptimal.PNG

I’ve been thinking about the comparison note above for a few weeks now. Using Floptimal on a regular basis will do that to you, repeating that methodology over and over. But through that repetition, I developed an idea to incorporate additional comparison views into my own flop analysis workbook that I think is a decent improvement.

There’s a methodology of comparison analysis that Floptimal facilitates really well that is an outstanding way to learn. I don’t know what the actual term for it is, so I’m just going to call it a pivot.

The image to the right has a few awesome examples of it. Let’s suppose I’m starting by studying my 50 BB BTN open ranges. I can enter the parameter options on the left and study the grid in the center of the image.

With many analysis tools and other resources, the study ends there. At this point after internalizing the range, you might move on to look at CO open ranges or BB defense ranges or an entirely different spot.

But Floptimal lets you pivot your focus into a different dimension. We can now click on a hand — in the example, I selected JTs. By doing that, we can look at the second graph on the top right. Now, our focus is not the 50 BB button open, but instead JTs and how that hand plays at every position and stack size.

The pivot lets you shift your perspective momentarily and look at the data from another perspective. I find that these shifts are incredibly valuable, especially when studying a game as complex as poker.

As I was using Floptimal, I had a bit of an epiphany about a gap in my own workbook and decided to add a couple views to create a solution. All the data within the my workbook starts at the formation-level and lets the user drill down from there. In other words, I required the end user to choose a formation first (e.g. UTG vs BTN, single raised pot). All of the the underlying metrics supported analysis within that top-level context.

While you could analyze the data within all formations in a myriad of ways, you previously did not have the ability to analyze data across formations very easily — that exercise would have been quite tedious. As a result, I decided to build two additional tabs to solve the issue.

Both views are identical in interface to the existing Formation analysis tab. However, they provide additional levels of segmentation, opening up the possibility for much deeper analysis across formations. The first view presents the data for a chosen board heuristic (e.g. monotone, A-wheel-wheel, paired rainbow, etc.). The second view presents the data for a chosen individual board. Both let you pivot from an individual heuristic or board to look at the equilibrium frequencies across all formations.

I’ve created a brief video that demonstrates the functionality below. If you’re interested in purchasing this workbook, you can find it at my product store.

conclusion

As I mentioned above, there’s a lot going on. I’m not sure how frequently I’m going to be posting here, but I can guarantee there will be another post within the next couple months to formally announce my launch plans for Solver School. Please follow me on on Instagram and Twitter, or sign up for my email list to get the heads up when that post does go live.

If you have any questions, comments, or want to discuss anything, please feel free to reach out to me on any of those channels or email me here. Thanks for reading.

-Lukich

Writing, Announcements, MediaMichael LukichSolver Work, Reflections, Products, PodcastsComment