How to Win Games: Find the Hidden Rules

You can find success by learning to win games, then turning life's problems into games and solving them in the same way.

About Lucky Maverick

About Jonathan Bales

I have a memory from when I was young, maybe six or seven, driving home from a Pee-Wee football game with my mom, when she turned to me and asked, “Do you want to be in the NFL when you grow up?”

I’ll never forget my response. I thought for a minute, then turned to her and said, “No. I want to run an online newsletter that helps people think differently in order to identify and extract every possible edge to maximize their probability of success.”

And so it was.

A Quick Intro to Lucky Maverick

Actually, I wanted to be a professional football player. The truth is I’m much better suited to play non-350-pound-grown-ass-man-crushing-your-skull type games and write about playing such games and build businesses centered around playing games, which is effectively what I’ve done the past decade. I have a natural penchant for the sort of characteristics that lead to enjoying to play (and win) games, many of which are the “principles” I listed in the About section of this newsletter.

(You should read more about Lucky Maverick now, if you haven’t.)

• Principle #1: See the world in terms of probabilities.

• Principle #2: Divorce process from outcome.

• Principle #3: Think about problems in expected value, which is Probability x Payoffs.

• Principle #4: Be a big fish in a small pond.

• Principle #5: Admit how little you know.

• Principle #6: Think differently than others to obtain extraordinary results.

• Principle #7: Exploit weaknesses in others’ psychology to maximize payoffs.

• Principle #8: Use a multi-faceted approach to uncovering truth.

• Principle #9: Learn mostly via trial-and-error.

• Principle #10: Be data-driven, not a data scientist.

• Principle #11: Learn by having skin in the game (and learn from those with skin in the game).

• Principle #12: Think long-term.

The thing is, you can turn almost anything in your life into a game, then implement the same principles you’d use to win at poker or backgammon or Chutes and Ladders to find success in starting a business or winning a negotiation or choosing the optimal restaurant.

And so, ultimately, Lucky Maverick is a resource for winning games, in the broadest sense, that you can use as a foundation for finding success in other areas.

If you can learn to win games, you can win at anything in life.

Thus, my hope is this blog/newsletter acts as a springboard for you to think differently and tilt the odds of success in your favor—to become a lucky maverick.

Okay, LET’S START THE NEWSLETTER!

The Gambling Olympics

When you work in the field of gambling, you meet all different kinds of people: degenerates, nerds, sickos, frauds, sharks. Some take on risk at every turn, while others try to nearly eliminate it altogether. Some are totally full of shit, and some are among the most honorable people I’ve met in my entire life.

One thing nearly all gamblers have in common, though, is what I consider a highly attractive trait: a willingness to put money (or otherwise take on downside) on their beliefs. It’s sort of weird to me how uncommon this seems to be in normal society, too. Everyone has an opinion; almost no one is willing to take on downside.

Now, I tend to stay away from what most might consider the typical “degenerate” crowd. My core group of gambling friends includes some of the top poker and daily fantasy sports players in the world, along with others willing to take on risk for their beliefs, such as entrepreneurs. As you might expect when you put a bunch of young, rich, risk-seeking bros together, this typically leads to a lot of betting.

And we bet on everything. Connect 4. Rock-paper-scissors. If the next play will be a run or pass. How long it will take Peter to eat 10 chicken nuggets. The number of strings of spaghetti on that plate over there. The number of strings of spaghetti that Adam thinks are on that plate over there.

We even created a high-stakes event called the Gambling Olympics—won by yours truly—to crown a King of the Games.

Adam Levitan @adamlevitan

Congrats to @BalesFootball for shipping the inaugural Gambling Olympics. He’s walking through the airport with this trophy, TSA ppl laughing at him.

It was a pretty sick live, two-day event with some of the top gamblers in the world—poker pros like Joe Ingram and WSOP Main Event Champion Scott Blumstein, DFS pros like Peter Jennings and Adam Levitan, renaissance men like Brandon Adams, other sports bettors, stock/cryptocurrency speculators (and even creator of Manzcoin, Peter Overzet), and, for some reason, former MLB catcher Paul Lo Duca.

Lo Duca once told me I “look like a broke-ass Vince Vaughn,” which I considered to be a great compliment given that Vince Vaughn is much taller than me, very rich and famous, and has dated many attractive women. A broke-ass Vince Vaughn honestly still seems pretty good, so thanks Paul.

At the Gambling Olympics, we did everything from bet on sports to play beer pong. Some of the games, such as Connect 4, are what we’d refer to as “solved”—meaning there’s always a mathematically correct decision. Any time you play Connect 4, at any given point in time, every single move you could make except for one is wrong (to varying degrees). Solving Connect 4 is difficult with the number of scenarios that can play out, but if both competitors play perfect strategy, you can exactly predict every move they’ll make in every game. An extreme example of a solved game is tic-tac-toe—a game I highly recommend to any readers under the age of five.

Other games, such as rock-paper-scissors, aren’t solved. Your opponent’s anticipated strategy dictates what you should throw; if you know they throw rock 45% of the time, and split between paper and scissors the remaining 27.5% of the time, respectively, then obviously throwing paper more often is advantageous until they inevitably adjust.

In either scenario, the path toward victory is the same: know the rules, inside and out, and exploit them to your advantage. Note that, long-term, you’re best off playing games that are either theoretically unsolvable or new enough that you can solve them faster than others. In the world of games, it’s often more valuable to be first than it is even to be right.

Knowing the Rules

It might sound painfully obvious that you should know the rules of the game you’re playing, but what I really mean is this: you should be assessing how the rules can be a catalyst toward finding edges over competitors. What are the ramifications of both the stated and unstated rules, and how can you leverage that knowledge to win?

In some games, like Connect 4, the rules are clear and the possibilities are bounded. In other games, like business, the rules aren’t so clear—and in fact, many “rules” are bullshit—and the possibilities are boundless. In the latter sort of game, knowing the rules—which are real, which aren’t, how to properly exploit them without a clear rulebook, and so on—can be a difficult task.

One way to get started on the right track is to work backwards. If you’re going to win a specific game, what sorts of things need to happen? What does the path to success look like? If you put a little thought into possible end-games, you can sometimes reverse-engineer a formidable plan-of-attack by working within the rules to eliminate potential scenarios that don’t lead to favorable outcomes for you.

This is one strategy employed by the chess prodigy Josh Waitzkin—the subject of the movie Searching for Bobby Fischer—that he discussed in his book The Art of Learning, which I highly recommend. Whereas most chess players approach the game sequentially, learning their opening moves and then progressing into the mid-game, Waitzkin learned how to maximize his odds of winning by starting with end-game scenarios, often with just three pieces left on the board. In doing this, he was able to work backwards from success to cultivate more apt early- and mid-games.

Finding Your Edges

One of my favorite stories of finding an edge comes from my buddy Brandon Adams—a poker and DFS pro, former Harvard professor, game savant, and competitor in the aforementioned Gambling Olympics. BA is known for making prop bets—I’ve had a few with him myself—and he’s absolutely one of the best thinkers when it comes to creatively finding edges.

BA likes to play tennis. He’s had some sweet high-stakes matches with poker player Patrik Antonius in the past.

A few years ago, he agreed to play our friend Stephen Bass, a former professional tennis player. The terms of the bet were that BA had to win just a single game off Bass over two sets, and he was getting around +145 to do it. In non-gambler speak, BA would win $145 for every $100 he bet if he could find a way to win a single game, i.e. not lose 6-0, 6-0. Bass had to put up $145 for every $100 of BA’s money. That line increased to +200 in the lead-up to the event as the market—i.e. our degenerate friends—put more and more money on Bass, making BA a bigger underdog.

BA knew he was an underdog (a bet can still be good even if you’re expected to lose as long as you’re getting the right odds), and he formulated his strategy in a way that reflected this. In effect, BA reverse-engineered what a win might look like for him, clearly drawing a conclusion that’s true in almost all areas…

Underdogs should root for and facilitate variance.

When the thing that shouldn’t happen does happen, there’s usually what we’d call “luck” involved. Thus, BA removed the low-variance scenarios in which he might play very well and still lose, deciding to introduce as much randomness as possible into the equation. He did this in a few ways:

• He used his powerful serve as much as he could, not worrying about faults since the downside—losing the point—was the likely outcome anyway.

• He charged the net to shorten points as much as possible.

• He chose to play on top of the Cosmopolitan hotel in Vegas—a shitty court, at (small) elevation, in the heat.

• He required a start time of 11 a.m. when he knew the shadow of the building would be moving across the court.

Basically, anything BA could do to increase the odds of a “lucky” path to success, he did. Bass is a super sharp guy, too, so he played an extremely low-variance game, never really going for aggressive winners and forcing BA to beat him over and over. Bass won the match, but there’s a lot to learn from BA’s thinking.

I’ve implemented a similar variance-seeking strategy in daily fantasy sports. You’d think winning a fantasy sports league would be mostly about predicting player performance, and of course that matters, but depending how you approach it, spending time projecting the outcomes of games isn’t necessarily the most important component of becoming a winning DFS player.

When I first started playing DFS, I focused basically 100% of my time on picking the best players. It just seemed obvious at the time that if you want to win a fantasy football contest, the most important part would be an extensive knowledge of football.

But DFS is a game—one that’s zero-sum in which you’re competing with others (mostly) trying to do the same thing as you—and I eventually realized my edge wouldn’t be in out-projecting others. Maybe I could find a small edge by spending hours upon hours researching matchups, but I didn’t think it was worth a ton of my time. There were a bunch of reasons for that, the most important of which was that everyone else was spending all their time doing the same thing.

In games, it’s not what you know. It’s what you know that others don’t.

The important thing I learned from my early time in DFS is that you need to cater your strategy toward your odds of winning. If you’re an underdog, that means taking on randomness, and even putting yourself in a position to benefit from it. In DFS tournaments in which you’re competing against lots of other players, everyone is an underdog. The type of lineup you create in a head-to-head game—in which you could easily be a large favorite to win the contest—should usually look dramatically different from the lineup you create in a tournament.

When finding your edges, it’s imperative to know your baseline odds of success. The most important components of that are the number of people (or businesses, or whatever) with whom you’re competing and your relative probability of victory compared to your competitors.

For example, if you’re bowling in a tournament against a bunch of equally skilled bowlers, you should take on variance to widen the range of outcomes for your round; if you need to score 240 to win, consistently scoring 210 won’t really help you. That could mean maximizing the odds of rolling strikes, even at the cost of a lower overall score if you miss. On the flip side, if you’re bowling against your friends and you’re clearly the best in the group, you should be taking on little risk to ensure victory.

If you’re saying to yourself, “But man, I’d really just like to have fun when bowling with my friends,” then just forget about ever having success in life because you’re a natural-born loser. If you’re not willing to do anything and everything to crush your friends’ spirits until they’re completely demoralized and questioning if they should even be friends with you, then you’re just not management material, Gary.

But really, the goal of a competition is to win. The fun of the game comes in finding small edges to maximize the chances of winning. One very useful way to do that is to work backwards, envisioning what success looks like and then eliminating as many potential paths that don’t lead to it as possible.

Finding Hidden Rules (Where I Ramble About Rock-Paper-Scissors)

One event in the Gambling Olympics was a rock-paper-scissors tournament consisting of head-to-head, best-of-21 battles. I don’t use the term ‘battle’ lightly; this was all-out war as far as I was concerned.

Coming into the Gambling Olympics, odds were posted for each event. I don’t mean like some guys we knew created theoretical odds; I mean an actual bookmaker posted odds on which anyone could bet.

Jonathan Bales @BalesFootball

This is pretty awesome. MyBookie.ag posted odds on the Gambling Olympics. Yes, you can go bet on each event (under Special Wagers). The current favorites are @CSURAM88 (+450), @The_Oddsmaker (+500), me (+500), @adamlevitan (+550), and @badams78 (+600).

While I had the second-best odds to win the entire event, I was the favorite in rock-paper-scissors. Did this result exclusively from me talking non-stop on Twitter about how I played daily against a solver (very fun by the way) to become a giant in the R-P-S streets? Maybe, maybe not…who’s to say?

Long story short, I finished in the top half of the field in 11 of 12 events—rock-paper-scissors being the only one I missed. Some might call me not finishing well in rock-paper-scissors “bad luck,” but I try to be as honest with myself as possible and realize it was VERY bad luck. I mean jfc some of these guys can’t even tell the difference between exploitative and game-theory-optimal throwing styles lol CAN YOU IMAGINE???

Anyway, how much did you spend on this newsletter? Nothing? You’re about to get your money’s worth right now because I’m going to tell you how to win in rock-paper-scissors every* time.

*roughly 55% of the time against even the shittiest of opponents

Okay, so the first thing to note is what people do after you have the same throw, i.e. you both throw rock, for example. Now I’m clearly not going to give you the entire arsenal here—you’re going to have to pick up my next book, How to Parlay a Small Edge in Rock-Paper-Scissors Into Losing All Your Friends, out next fall—but just note that many people will do the same sort of thing after a “tie.” There are many other edges to be found in rock-paper-scissors, depending on your style of opponent, but that’s one of the larger advantages. Another is to call out what you’re going to throw (sometimes lying and sometimes not).

With many edges, you can often eliminate one potential throw from your opponent such that you’re highly likely to tie or win your next toss. In situations in which you think you are at an advantage, you should usually start the next throw as quickly as possible so as to not let your opponent think. Now, you might do this all the time anyway, but I do not. No, sometimes I take an inordinate amount of time to think about what I’d like to throw when I don’t see a clear path to victory, contemplating every relevant factor and picking through the percentages until hey, why won’t anyone play rock-paper-scissors with me anymore!?

If you can, you should use the time (or lack thereof) between throws to your advantage. Being in control of the amount of time your opponent can think is a pretty big edge.

In the Gambling Olympics, one of my opponents—poker player Joe Ingram—figured this out in his match against me. Joey is well-versed in the sport of finding edges, having been one of the top Pot-Limit Omaha card players in the world using an extreme approach to learning that I’ll talk about another time. And his approach to our rock-paper-scissors match was also…extreme.

Joey knew I liked to control the tempo of the rock-paper-scissors matches, and he also knew I had been in the lab grinding the numbers on optimal throws. So after every toss, Joey would act like a fucking maniac, jumping around and screaming in my face, especially after he won.

Sean Koerner @The_Oddsmaker

@MattFtheOracle @MattBrownM2 @paulloduca16 @BlackjackFletch @badams78 @PeteManzinelli @jphanned @SBlum2711 @BalesFootball @adamlevitan @CSURAM88 @Joeingram1

On the surface, it appeared as though Joey was trying to get into my head, which I admit…he didn’t at all because I’m a stone-cold assassin. But the real game that Joey was playing was buying time. In taking upwards of 30 seconds to a minute—and sometimes more—between throws, it meant that each throw was effectively independent of the others. There was no rhythm. No real correlation between throws. And no edge for me, the favorite. I mean, we played a best-of-21 match that I lost 11-10, and it probably lasted 15 minutes.

The point here isn’t that me and my friends are complete psychopaths who jack each other off when we increase our win probability by five percentage points in a meaningless game—although that does sound nice. It’s that to find edges in zero-sum games, you have to understand the game within the game, identifying “hidden” rules that aren’t explicitly stated.

In rock-paper-scissors, one of the major “hidden” edges is controlling the tempo based on your confidence in the win probability of your next throw. In the game of wealth creation, which is governed by less defined rules than in traditional games, most of the edges are hidden.

Sports, Payoffs, and More Hidden Rules

When you think of a game like daily fantasy sports—competitions to field a team of athletes who score the most fantasy points based on their real, in-game performances—you’d imagine the most important component in being successful would be knowing sports inside and out to predict the most likely outcomes.

And uh, yeah, duh, if you could perfectly predict on-field events, you’d never lose in DFS or sports betting. But obviously, you can’t perfectly predict them; while there might be a philosophical debate about whether or not things are determined, practically speaking, there’s a range of outcomes in each game and the job of anyone speculating on sports is to try to accurately forecast those probabilities.

Like I mentioned, the biggest advancement I made in my career as a DFS player—the single largest leap I took when trying to compete for big money against some of the best fantasy sports players in the world—was realizing that the real game wasn’t solely about projecting sports, and really not even mostly about that.

The primary reason for this is the fact that DFS is a game-theory-driven, zero-sum contest of competing minds—not a contest solely about making the most accurate on-field predictions. Your goal as a DFS player isn’t necessarily to build a lineup capable of scoring as many points as possible, but rather one that’s most likely to score more points than your opponents’ lineups. These tasks might sound similar, but there’s a fundamental difference in that your real goal—what you’re solving for in terms of EV—is to maximize lineup win probability, not fantasy points.

This was my big realization—and one of the “hidden” rules of DFS.

Think about the difference here. If you’re solving for projected points, then all you should be concerned about is predicting on-field performance. That’s it. If you know sports better and can build better models and can figure out which inputs best predict performance, your lineups will score more points. If you’re solving for win probability against other lineups, though, you need to be concerned with your opponents’ strategies.

Expected Value = Probability * Payoffs

In the early days of DFS, everyone was focused on probability, or accuracy. How can I better figure out what will happen in these games? And yes, of course, that matters a lot. But even then, and especially now, you’re competing with absolutely everyone trying to do the same thing. I realized I wasn’t going to really be able to find the biggest edge in this area because:

1)     The “usable edge”—how much focusing on player projections would help me—was limited since everyone was concentrating there; theoretically, if everyone could create perfect projections, you’d have a factor that would be of the utmost importance without producing any substantial edge over opponents.

and

2)     People inherently care more about the frequency of positive outcomes than truly maximizing overall EV; that is, people mostly care about how often they are right or how often they win (the probabilities) and not what they win when they are right (the payoffs).

This line of thinking resulted in players focusing almost exclusively on predicting what would happen during the games and ignoring or at least significantly overlooking the importance of the payoffs—how easily the lineup could win or come close—if their players performed as expected. In DFS, the ownership of the players—how many other lineups utilize them—dictates the payoffs. Everyone asks the question “Is this player going to do well in this game?” but so many overlook the just-as-vital question “How much will it help me win more money if he performs as I expect?” And it turns out that in DFS, just as in life, much of the EV is in trading in a little safety to dramatically improve the payoffs.

My friend and fellow DFS player Drew Dinkmeyer once told me there’s a saying in finance, “What do you win if you win?” If you can get 2-to-1 odds on the flip of a coin, it’s easy to see why payoffs matter, but because it’s less straightforward in real life, so many people don’t place enough energy into assessing the upside of decisions.

Don’t do the equivalent of over-scrutinizing a coin’s properties to figure out if heads might come up 50.1% of the time and ignore what you win if it does. Life isn’t a coin flip, but it’s more random than most think, which ironically is what allows for the biggest edge. Many of the best hidden rules are found in areas where people are most significantly underestimating the luck factor.

Thus, when searching for hidden rules to find an edge, try to identify areas in which people are focused on accuracy or probability or the most likely outcome, and not the payoffs. And there are many such situations. Many times, this will be the result of them “solving” for the wrong thing, i.e. projected points vs. lineup win probability. In the business realm, you might see it in the form of solving for tomorrow’s revenue instead of customer loyalty (and much greater long-term revenue). Usually, the answer in this world—whether the question is “how do I make the best product?” or “how can I get a raise?”—is to make something or become someone indispensable.

Indispensability comes from predicting how things might play out in the future and ways that the work you do now can offer higher and higher future leverage. Leverage is attained by having something others want but can’t find elsewhere, and you can often acquire that “exclusivity” by uncovering areas where people are focused on maximizing short-term results (or overreacting to short-term variance) and not concerned enough about long-term win probability.

The Nature of Hidden Rules

Writer Kurt Vonnegut once said, “If you want to break the rules of grammar, first learn the rules of grammar,” which I always thought was a useful metaphor for many things in life, but it’s especially apt when we’re talking about games and approaching life as a game.

If you want to break the rules, you first must be a master of the rules. If you work in internet marketing, you can’t really exploit others’ inefficiencies in YouTube advertising, for example, until you know everything there is to know about buying ads on YouTube. The first step on your journey to becoming a master of any game is to know the rules, inside and out. You can’t just skip the basics, and there’s really no way to jump ahead without putting in the time. Not until then can you properly identify and take advantage of hidden rules.

The hidden rules of any game can be discovered by thinking outside-the-box, working backwards from success and considering what sorts of decisions tend to lead there or theoretically increase EV and win/success probability. You can find many small edges by better exploiting the rules than your opponents, and you can find very large edges by properly identifying hidden rules, which effectively allow you to decrease competition by playing an entirely different game than others.

It’s worth pointing out here that an almost necessary consequence of playing games through the lens of hidden rules is that your approach will be contrarian, viewed as unorthodox and, very often, foolish by the majority of your peers. And guess what? Sometimes, your methods will be foolish. That’s a pill you’re going to have to swallow.

My buddy Jay Raynor was one of the best DFS players and didn’t even know the difference between a quarterback and a cornerback. He also was one of the first people to recognize the value of correlations in daily fantasy baseball, creating lineups that “stacked” a bunch of players from the same team to improve the lineups’ upside. He knew next to nothing about baseball, but discovered one incredibly profitable hidden rule others were overlooking just by approaching the game in a fresh way. He tried other strategies that didn’t work, but it didn’t matter; initially laughed at, Jay became one of the top DFS tournament players in the world.

Knowing rules inside and out is paramount to success, but finding and exploiting the hidden rules a prerequisite for greatness. To get there, work backwards from success (however you define it), think about problems differently by questioning everything, accept you’ll often be very wrong, and consider which implicit questions people are asking or solving for that just aren’t the right questions to be asking.

The hope is that in approaching games/life in a different way, you can limit your losses when wrong, but achieve monumentally asymmetrical benefits when you’re right since you’re the only one or among the only ones to have identified the rare and lucrative hidden rule.

The Important Points

• Know the rules, inside and out, and exploit them to your advantage.

• One way to get started on the right track is to work backwards. If you’re going to win a specific game, what sorts of things need to happen? What does the path to success look like?If you put a little thought into possible end-games, you can sometimes reverse-engineer a formidable plan-of-attack by working within the rules to eliminate potential scenarios that don’t lead to favorable outcomes for you.

• In games, it’s not what you know. It’s what you know that others don’t.

• You need to cater your strategy toward your odds of winning. If you’re an underdog, that means taking on randomness, and even putting yourself in a position to benefit from it.

• When finding your edges, it’s imperative to know your baseline odds of success. The most important components of that are the number of people (or businesses, or whatever) with whom you’re competing and your relative probability of victory compared to your competitors.

• In rock-paper-scissors, one of the major “hidden” edges is controlling the tempo based on your confidence in the win probability of your next throw. In the game of wealth creation, which is governed by less defined rules than in traditional games, most of the edges are hidden.

• People inherently care more about the frequency of positive outcomes than truly maximizing overall EV; that is, people mostly care about how often they are right or how often they win (the probabilities) and not what they win when they are right (the payoffs).

• Many of the best hidden rules are found in areas where people are most significantly underestimating the luck factor.

• Indispensability comes from predicting how things might play out in the future and ways that the work you do now can offer higher and higher future leverage. Leverage is attained by having something others want but can’t find elsewhere, and you can often acquire that “exclusivity” by uncovering areas where people are focused on maximizing short-term results (or overreacting to short-term variance) and not concerned enough about long-term win probability.

• Writer Kurt Vonnegut once said, “If you want to break the rules of grammar, first learn the rules of grammar.” If you want to break the rules, you first must be a master of the rules. Not until then can you properly identify and take advantage of the hidden rules.

• The hidden rules of any game can be discovered by thinking outside-the-box, working backwards from success and considering what sorts of decisions tend to lead there or theoretically increase EV and win/success probability.

• An almost necessary consequence of playing games through the lens of hidden rules is that your approach will be contrarian, viewed as unorthodox and, very often, foolish by the majority of your peers.

• Consider which implicit questions people are asking or solving for that just aren’t the right questions to be asking.

• The hope is that in approaching games/life in a different way, you can limit your losses when wrong, but achieve monumentally asymmetrical benefits when you’re right since you’re the only one or among the only ones to have identified the rare and lucrative hidden rule.

Quick Hitters

• Take a look at Nat Eliason’s blog. Really great content that’s similar to Lucky Maverick.

• Check out the Universe in a Nutshell app. It’s a pretty cool visualization if you like space and the universe and quantum mechanics and stuff.

• This is a good week to send the first Lucky Maverick email as I got lucky myself with a $70,000 cash on DraftKings on Sunday. DFS is not what it used to be in terms of an edge, but it’s still nice to be in a position to get lucky sometimes.

• I’ve gotten very interested in alternative investments lately—things like trading cards, handbags, art (and even digital art), and so on. Altan Insights is a great starting point.

• I’ve mentioned it before, but this series on Chinese businessmen is worth reading.

• I spoke with Andy McCullough of The Athletic about my pushup bet and Mike McDonald’s sick free-throw bet (paywall).

Final Notes on Lucky Maverick

• This thing is over 5,000 words. That won’t happen very often. I plan to tinker with the format of this newsletter, mixing in long-form content like this with quick-hitters, bullet points of what I’m reading or working on, maybe some podcasts, and so on. I’m open to suggestions.

• As you noticed, I put the most important points in bold and listed them at the end, which I plan to do in any semi-long posts for those short on time (or, more likely, those who just don’t want to read through my shitty joke attempts).

• The newsletter structure will change, and I hope that the quality of the content does, too. Lucky Maverick will always be evolving. If things don’t look significantly different every six months or so—and for the better—then I’m doing something wrong.

• I’d like feedback! Tell me what you like and what you don’t. Like a true contrarian, I probably won’t listen to you, but maybe, who knows?