How to Make It in the NBA | Seth Stephens-Davidowitz

[00:00:07] Seth Stephens-Davidowitz, he's one of the most fascinating guys I ever interviewed. He does all this weird data analysis where he finds the secret truths about humanity from the data. Like, I remember in his first book where he was talking about how this entire country

[00:00:25] had this weird fetish that we speak about a little in this podcast coming up, but you only know about it because it shows up in the Google data. It's like no one ever talks about this. They just Google it.

[00:00:36] And so you find out all these secrets of human beings from all this weird kind of data. And Seth is the guy to find weird data. He's been doing it for years. He's written two books on it, now a third.

[00:00:50] The third book is called Who Makes the NBA? Data-driven answers to basketball's biggest questions. Plus, how I created this book in 30 days using AI, which is a fascinating part of this conversation as well. Because it's very interesting how AI is playing a role in writing.

[00:01:07] But don't think this is about basketball. This is more about an approach to data and how things we assume are often wrong. And so I'm not a basketball player. I've never, maybe I've watched one basketball game in my life, but this was a fascinating topic for me.

[00:01:25] So Seth asks questions like what percent of seven foot tall players are in the NBA? Are seven foot tall players actually good athletes? What determines how many basketball players a country produces? How genetic is basketball talent? What besides genes, do NBA playing parents pass onto their kids?

[00:01:45] What do great coaches do? So he figures out the actual data for all these things and makes the case for it. And I think Seth's going to write 100 books like this. And this was just so fascinating. Plus a fascinating conversation afterwards about how to monetize anything you love.

[00:02:05] So by the way, I did this whole podcast, including this intro while I'm totally really sick. But Jay kept calling me and saying we needed a podcast. We needed a podcast. So finally I logged in and did a podcast, but now I have to take painkillers or

[00:02:23] something and I have brain fog. So excuse that and enjoy this podcast. This isn't your average business podcast and he's not your average host. This is the James Altiger show. I'm curious if just people of the same as much as you can match of the ethnic

[00:02:57] background as possible, like not only kind of religion or ethnicity or whatever, but also like where you were born as close as possible to the exact hospital. I wonder if that contributes to this feeling of, oh, I really know this person.

[00:03:11] So like, I think it's not, it's not just knowing someone. I think like there's just an outlook. If you're like a New York area Jew, you just have a certain perspective on the world, your little wilder than probably the average person, like a little, I don't

[00:03:25] know, just there's a certain, I think way you approach life that is distinctive. And like, New York Jews are very different from Israelis, for instance. Yeah. No, even just like a Los Angeles Jew. I think it's totally different than a New York area Jew.

[00:03:39] So yeah, I think we're more, we're more honest than like a lot of other people. Like we're just like, I think that's one of the reasons I always loved your block. You just like say whatever pops into your head.

[00:03:50] I think because I'm the same way about you read my writing exactly the same way. I just say, like, I just have no filter. There's more maybe it's related. There's more neuroticism, I think, or at least outspoken neuroticism. Like maybe I don't know why that is.

[00:04:05] I would definitely agree with that. I don't know why it is, but maybe we're just getting that from TV. Maybe TV tells us that New Yorkers are neurotic Jews. So you kind of play the part? Yeah. Yeah. I don't think I do, but maybe that just happens.

[00:04:20] All right. Yeah. I could definitely see that. By the way, also, I want to talk about how you could start making more money doing what you do. Like what you do is like really valuable. You take all this data like your first book.

[00:04:34] I'm forgetting all the titles of your books. Forgive me. I have brain fog. So for listeners, I currently have COVID, but I wanted to do this podcast with Seth. If we had tried to schedule this two days ago, I would not

[00:04:47] have been able to do it, but today I'll be able to do it. But what was the title of your first book? Everything. Everybody Lies. Everybody Lies. Everybody Lies. Yeah, yeah. And you had so much interesting data and conclusions.

[00:05:00] Like I always remember that you had all this Google search data that showed people, there was one country specifically where like everybody in this country, I don't feel like calling out the country just in case they get insulted. Everyone, the men in this country, inordinately search on

[00:05:20] breastfeeding for themselves. Like it's a sexual fetish and like no other country searches. And you would never know this. Like they would never tell anyways, but they tell Google. Google is the keeper of secrets. Yeah, exactly. Yeah.

[00:05:37] It was, it was, yeah, that was the whole part of the book that just there's so much information that we'd never otherwise have from all the data is anonymous aggregate. Data on Google searches on what I'll say in India. Yeah.

[00:05:52] So breastfeeding fetish, but lots of other information as well. You know, important topics around racism and child abuse, abortion, but also like kind of everything. Well, you know, because this is sort of top of our, you know,

[00:06:04] what I forget, what was the some data you found out about racism? Oh, it was that I was just shocked by how many people make explicitly racist searches in the United States. And in parts of the country, I wouldn't have thought of it.

[00:06:16] Like it wasn't just the South. It was like a lot of parts Western Pennsylvania, Eastern Ohio, upstate New York. And then these areas just like perfectly predicted where almost perfectly predicted where Barack Obama underperformed when he was running and lots of other, you know, aspects of American society.

[00:06:34] Wow. So a secret racism that only appear appears on Google. Could political candidates use this data? Have they been using this data? Yeah, probably not as much as they should be using it. But I think they're not using it right.

[00:06:48] If you have to know, yeah, I don't know. A lot of there's there's like a real art to knowing how to use data correctly. And like, I find that most people, I always say that good data science is better than no data science.

[00:07:01] But no, but no data science is better than bad data science. And I think most data science is just bad data science. So it's kind of makes things worse. A friend of mine has a business where he has he's collected all

[00:07:14] the data on every car registration and VIN number, vehicle identification number. And also, whenever you do work on your car, I guess you have to register that. So he knows when you bought your car, what kind of car it is, how

[00:07:28] often you buy new cars and then and whether the cars would work down or not. And also in aggregate, people who have X kind of car tend to upgrade to Y kind of car. Oh yeah.

[00:07:40] So he's able to if he sees, oh, Seth usually buys a new Subaru every two years, he'll call all the Subaru car dealers who are clients and or the one in your area and give them your name and contact info and say you should call Seth.

[00:07:59] He buys a Subaru every two years, two years are up. And he's looking for this kind of upgrade probably. And it actually really improves the performance of these car dealerships. I totally believe it would. Yeah. And yeah, if you're good at predictive analytics, what that is,

[00:08:14] that's like insanely valuable. Yeah. I mean, he's selling this company for tens of millions of dollars. Just negotiating to go right now. So he's like, you're just collecting the data. And now your latest book and then you did the book that was

[00:08:30] sort of like using it for self improvement. Like if all this data could, if you had all this data, how can you do it to make yourself better? But this third book just seems like you had this crazy idea

[00:08:41] one day and it was fun and you decided to just go all out doing it. You went all out and it was basically all the data you could find about basketball and interesting things you learned from it.

[00:08:55] Like you would never think that Michael Jordan in some ways of looking at is a fairly mediocre player or LeBron James in particular was LeBron James was much more mediocre than I thought or, or Kareem Abdul-Jabbar, maybe the worst player out there.

[00:09:13] Well, no, to be clear, this is height. And I height adjusted basis. So I say that all the, you know, height is such an advantage in the NBA each inch doubles your chances and making the NBA and one in seven, seven footers reaches the NBA. But just insane.

[00:09:29] There's like no other trait that gives you like such an advantage to reach the very top of a profession, I would say. And it means that if you are seven feet tall, seven one, let alone like seven, five, you don't really have to be that good.

[00:09:43] And frequently they're not, you know, they're just tall compared to my favorite one of my favorite players, Mugsy Bogues, who was five foot three and I think is the best height adjusted player of all time. I argue in the book. Yeah, this was a pure passion project.

[00:09:58] Well, well, but it's interesting though, because height is such an advantage. You're a big point that you make is that height is such an advantage that they don't really have to be good athletes to be in the NBA. Yeah.

[00:10:09] If you look at like the average seven footer, how high they jump, how fast they run, like how well they shoot. It's the numbers are so mediocre. Like I probably shoot better than a lot of seven footers and I like barely play basketball.

[00:10:23] And then, you know, how much they jump. The I have a horrible, I could barely get my feet off the ground, but like a just an average high school athlete with some training could jump as high as an average seven footer in the NBA.

[00:10:38] And, you know, a bad high school track runner would be faster than a seven footer in the NBA. They just aren't that they don't have to be that good because they're so tall and such an advantage. Is that because like they could just basically walk

[00:10:49] around the court and all these basically midget six foot five people, they're just towering over them. And they could just they take the ball and just put it in the basket like they don't even have to jump or run or anything. Face it.

[00:11:02] I mean, yeah, some of them like Yao Ming could just kind of stand around the hoop and like dump it without jumping. He was seven foot six. But yeah, it's just such a it's a game that just plays high more than any other sport, except volleyball.

[00:11:15] Volleyball is the only other sport that uses height like like basketball does. But yeah, it's just you could block everyone's shot. You can grab all the rebounds. You can score easily. So but on the one hand, basketball's you've got

[00:11:28] to have a lot of athletic like you have to have stamina like running back and forth on the court for 60 minutes. That's like really hard work. But I think a lot of this is not that they are better athletes because they train so hard.

[00:11:43] But it's not necessarily, you know, if you practiced all the time to get your stamina up to get your vertical leap up to run faster, I think a lot of us could get approach a level of an average seven foot NBA player.

[00:11:56] But you know, we don't do that training. So they definitely are more impressive, have better stamina. But a lot of that's from training, not from natural talent, whereas all the six foot six one, six two NBA players are just off the charts, like insane, you know,

[00:12:09] insanely fast, insanely high jumpers, insanely good free throw shooting and, you know, everything can measure their incredible. So it's kind of like I'm going to say very broadly, but it's kind of like you concluded that talent in basketball is basically height, hand width.

[00:12:26] And if your dad was a basketball player also that you had talent in basketball. I don't know if that's all I concluded, but that was a big part of it. I talked about how the advantage it is to have a father

[00:12:38] as a basketball player, which frequently which shows up most strongly and that they're just incredible free throw shooters because their dads are kind of coaching them from a very young age on the proper form of shooting a ball, which which is just really valuable to learn something

[00:12:52] like that at such a young age, like sons of NBA players do. Like I wonder I wonder which things are basket like so for those listening, what's that? What's the name of the book again? I apologize. I don't remember who makes the NBA.

[00:13:06] Who makes the NBA and you go over everything about like what, you know, is it nature? Is it nurture? What are our big hands important? Is a vertical leap important? Like all of these heuristics that you would think are important. Some are some aren't.

[00:13:21] And you go over everything from the best players to the best coaches and so on. I wonder which things are basketball specific as opposed to profession specific. So so I think in all professions, if your dad was that profession or your mom, you have an advantage.

[00:13:39] So like, for instance, if you're a football player and your dad was like Archie Manning had two quarterback sons who were great quarterbacks in football. I think that was football, right? Payton, yeah, yeah. You like many. Yeah. So so and in in chess,

[00:13:55] it's not always the case that a world chess champion will be the father of a world chess champion, but often if you look at strong chess players, their dads were not as strong as them. But like like Magnus Carlson is the strongest chess player in the world.

[00:14:10] His dad is a strong master level player. So so at an early age when Magnus was just learning and when I guess your brain really, you know, forms its its strongest connections between neurons, he was learning from his dad.

[00:14:30] So his dad was able to teach him all the basic patterns that were important to master level players. And that was when Magnus was five years old. Yeah, well, I actually have a chart in the book where I calculate for all kinds of different fields,

[00:14:44] the advantage you get from having a father who was in that field. So in the NBA, if your father is in the NBA, you're 745 times more likely to make the NBA. So like that's a huge advantage. It's higher than pretty much any other sport.

[00:14:58] So football, you mentioned it's only 60x. So like 10 times lower father advantage in part because basketball is just way more genetic than football because of the height thing, which is really genetic. But then yeah, but then there are other fields like president, I calculated it's 1.4 million times advantage.

[00:15:16] I mean only based on two men, Adams and Bush, but that they because like the odds of being president for the average person are so tiny, the odds of sons of presidents have been pretty decent. It's a 1.4 times million times advantage, so way higher.

[00:15:32] And a lot of them, a lot of the fields are way higher than basketball or sports because sports, say what you will about it, it's a legitimate meritocracy. Like it basically if you're good, you're on the team. If you're not good, they cut you.

[00:15:43] Whereas something like senator, like it's not really a meritocracy. And even I have Grammy Award winner, Pulitzer Prize winner, Academy Award winner. They're all way higher than all the sports because they just network and know all the people

[00:15:57] and who really knows who's the best actor or actress anyway. It's kind of a little bit more corrupt, I think. And reality TV stars really, really high because you can just put your kid on your show. Like Hulk Hogan just had his son on the show too.

[00:16:10] So like there are a lot of fields where the nepotism plays a much bigger role, whereas in basketball or other sports, it's just genetics and then teaching them from a very engaged things like how to shoot properly. And it's interesting if you don't have the genetic luck,

[00:16:26] if you didn't win the genetic lottery like with height or hand width or we'll get the hand within a second. You do have to train more. You have to develop. There's talent and their skills. And you have to basically develop

[00:16:40] more and more skills to be a professional NBA player if you're not born with the genetic talent. Yeah, like Shaq, Phil Jackson the coach who coached Shaquille and Neil complained that if Shaq just worked hard, he would have won 10 straight MVP's. And someone told this quote to Shaq

[00:17:00] when he was on a podcast and he thinks Shaq would be extremely offended. Like how could my coach say that? Of course I worked hard. And he's just like, yeah, that's probably true. And I didn't really want to practice that hard.

[00:17:12] And you know, I was getting beat up so much in the game who I didn't want to get beat up in practice as well. He basically admitted he didn't work that hard. And he still was one of the top 10 basketball players

[00:17:21] of all time because he was seven foot two and also had other good genetic qualities. You know, he was a horrible shooter. He never seemed to care about improving his free throw shooting. It's kind of unfair, but it means true. And I had the same advantage in school.

[00:17:37] Like I was the Shaq of school, I felt. Everyone else was working really hard. And I was just like, yeah, math is pretty easy. I never really was working very hard. So, you know, I can't really attack Shaq too much for not working harder.

[00:18:06] So what's the story of Muggsy? Like he's five foot three. He must have had incredible skills. Yeah, it's insane. Like it's just we don't talk about Muggsy Bogues enough. Like he should be a legend, more of a legend. He's five foot three, 14 seasons.

[00:18:23] The NBA is starting point guard, like a good player at five foot three. It's just insane because like anybody can block your shot and grab a rebound over you. It's so nuts. You can't block anybody's shot. And yeah, he just outworked everybody, built up all his skills

[00:18:36] and was just like so much better than everybody else on everything else besides height to even to compete on that level. Like if it was one on one, Muggsy versus LeBron. LeBron is about like 6'10 or 6'11. I forget more like 6'9. But yeah.

[00:18:54] Yeah. So let's say it's one on one. Muggsy five foot three versus LeBron six nine. What would Muggsy do? Like what would his strategy be? Yeah, he tries to run around I guess LeBron. It would be tough. It would be, yeah. You can't like post up.

[00:19:12] I think LeBron every time we just post him up, back him down and then just like get really close to the basket and put it up. I don't know. But yeah, but that's the question. I guess Muggsy would have to go around and try to steal the ball.

[00:19:23] He'd have to like go around them and steal the ball every time. I think that would be the only chance he'd have. He'd have to like steal it. But so Muggsy is on a court with like, you know, 10 other LeBrons, you know, or that height and stuff.

[00:19:36] How did he survive at all? Like can't everybody just sort of push him around and like take the ball from him? Yeah. He was just so much better. He was so much faster than everybody else that he could, you know, yeah, it was a huge disadvantage,

[00:19:48] but he had the advantage of speed and everything else, you know, seeing the court better, passing it better that he was able to overcome that. It's insane. It's probably the most insane athletic accomplishment like out there to be that good at that height. It's like, it's impossible.

[00:20:01] It's like, I mean, like we haven't seen anybody else really come close to like, to that look that nobody else of five three has been in the NBA. Is he gonna be in the hall of fame? I actually gave this talk a couple of days ago

[00:20:15] to a crowd and there was a guy in the audience who is like a big time business executive who has a side passion of stats and basketball. And he's trying to convince the hall of fame to take Mugsy Bogues. So he like loved my talk.

[00:20:30] He's like, you know, because I have some data saying that on a height adjusted basis Mugsy Bogues just blows everyone away. And so, and apparently this guy has had success convincing the hall of fame to take other people as well. So we'll see.

[00:20:44] And he wants me to get on this project to try to convince the hall of fame to take Mugsy. Although I may spend time implementing your money-making business ideas instead of that. Well, you know, let's talk a little more about the book

[00:20:58] and then how you can use these ideas because like for instance, you determined that early draft picks are in fact usually better than late draft picks which is what should be expected there. And there's a way to calculate how much a player contributes to a win

[00:21:15] and early draft picks tend to be good contributors to wins on average. And you concluded that hand with is the feature most correlated out of all the features. It could be any feature like what college you went to could be IQ, it could be where you were born.

[00:21:33] But hand with is the feature most correlated with being a good draft pick because I guess you could palm the ball. But overperforming your draft picks. So yeah, so all else basically people with big wide hands have just, have historically just done way better

[00:21:53] than their draft pick suggests. And tiny hands have done terribly. Like they've just been disastrous picks because yeah, just grabbing the ball, being able to palm the ball is such an advantage in the NBA. And it seems that NBA teams for whatever reason

[00:22:07] have not fully incorporated this in their analyses of who makes a good player. You know what they don't put it. Because players talk about this. Like you talk about Kobe Bryant and Michael Jordan. Kobe Bryant wishes he had bigger hands. Yeah, I think it's just not as flashy

[00:22:22] as some of the other things like for it. Like it just doesn't seem, could it really be as important as vertical leap or just how tall you are? But it seems like it's, so it is that important that,

[00:22:32] you know, even if you say, I think teams have been like, yeah, it's probably better to have someone with big hands. But if someone's also really like a really good jumper and tall, but they just happen to have small hands,

[00:22:41] we're not gonna like not draft them because of that. Cause could that really be that big a deal? But it seems like it really is that big a deal. What's more important, bigger hands or height? I think height is overall would be the more important variable

[00:22:54] but it's just so well known. Like everyone knows a seven footers. Like, you know, yeah, like unless someone five foot eight is spectacular that everything else, you're not gonna even consider drafting them. Whereas hand size is not quite as important but it's just that there's a disconnect

[00:23:08] between how important people seem to think it is and how important it is. Whereas height, everyone kind of knows that's a big part of basketball. It seems like with your data, you could go to a team and say, listen, I can help you with next year's draft picks

[00:23:21] and they're all gonna outperform what they should be doing if they're picked at that level. Yeah, I don't know that's the most lucrative form of data analysis cause I have worked for some teams in the past. They tend to know that it's so fun to so many people

[00:23:40] that they just pay a lot less. It's like they don't, yeah. That's usually not the best way to make money if that's my goal. I don't know if that is my goal, but it is fun. I have worked with teams in the past

[00:23:54] just even based on my other books just cause they always need data people and particularly people who can think kind of outside the box cause in sports, it's very hard to, everyone's kind of doing the same thing playing around with the same data or wanting the same models.

[00:24:08] So it's really hard to have an edge unless you have some totally different outlook which say what you will about me. I do always see things very differently from pretty much everything else. So like after your first couple of books,

[00:24:19] what things have people called you up to consult about? Everything. Yeah, sports teams helping them draft. I'm trying to think things I can talk. Hedge funds, like all kinds of hedge funds were very interested in this data analysis. What kind of hedge funds they ask you?

[00:24:42] One of them was, I can talk about this once I who, but was a big investor in Google and I worked at Google for a while and then I knew their data really well. So I could understand like, I could play around with the data

[00:24:54] in ways that are really interesting to them and understand kind of trends in ways that would have been hard to pick up otherwise. And then other kind of random data questions they might have or just like, sometimes they just want a brainstorm of like,

[00:25:06] is there anything creative we can do with this weird project idea that we have or something? Like have any of them made money because of creative use of data analysis? Like for instance, look again, have satellite photos of how many cars are in a parking lot.

[00:25:22] Yeah, they definitely have. It's always hard in, to the extent I've worked in finance, which again, just as good sold, I've never had a full-time job there. You probably can relate to this. It's very easy. There's a lot of confirmation bias. It's very easy to convince yourself

[00:25:38] you did something right. It's hard to be very honest about, whether you really had an edge or whether you just got lucky. Particularly if you're not making, it's a little easier. Some of the quant funds, they're doing so many trades

[00:25:53] that the sample size does kind of even out. But a lot of, if a fund is not making that many investments, it's really hard to know whether they just got lucky or they really knew something. Even like Warren Buffett, Nassim Talib's, like it's possible Warren Buffett.

[00:26:09] There have been so many people who've tried to invest that just by pure chance, one of them is gonna have a record like Warren Buffett. And it may just be he was super lucky. We don't really know for sure. Yeah. I mean, there's some evidence

[00:26:22] that he developed skills because he's been investing literally for 80 years at this point. And so probably- But if anything is big returns where before we're earlier in his career, I think then later in his career, I think now he's struggled a little more recently.

[00:26:38] Yeah, because he's so big, it's hard to beat the market when you're as big as the market. Like you're our market yourself. So if you're the whole market, it's hard to beat the market. I think in general, it's just so hard to beat the market.

[00:26:53] Another thing I do is I give a lot of talks, like I'm kind of on the speaking circuit and I go to companies or I go to whatever, nonprofits, whatever. And then I go to a hedge fund and the questions just get like really good.

[00:27:08] And I'm like, who is this? And then someone will add me on LinkedIn. I'm like, who is this person? It's like, oh, he was the valedictorian of Princeton and triple majored in math and physics and biology or something. What kind of questions they ask it?

[00:27:21] Just you can tell when someone's at, like really knows where they're like, just like very fast, like they see the holes in my argument. I'm just like, sometimes I was caught by surprise. But I'm just like, I've given this talk a thousand times and everyone's just like, yeah,

[00:27:34] they're smiling along. And they're just like, did you think of this, this, this, this, and this? I'm like, oh my God. Can you think of a specific instance? I'm just curious. I can but I don't want to like, I don't know, it might be a little confidential maybe.

[00:27:49] So I don't know if I want to say that. The problem with data in the hedge fund world is there's a lot of data. And so with all data analysis and correctly, if I'm wrong, with all data analysis, you have this huge pool of data

[00:28:01] and then you have some tools that perhaps you've developed where you basically can ask questions to the data. So you can ask like, oh, if Microsoft is down four days in a row, what are the odds it goes up on the fifth day and is that statistically significant?

[00:28:17] And let's say you want to make a trade, you can find some statistically significant results to justify making a trade no matter what. That's the problem with a lot of this quant type of trading. That's P hacking. That's like, there is this one paper,

[00:28:36] it was written by academics that if people, they measure the mood of Twitter posts and they're like, if people are angry three days earlier then the stock market's gonna drop and they start a hedge fund based on this analysis

[00:28:50] and it blew up, it was disaster, it didn't work at all. I think that doesn't even make sense. Why should anger three days earlier? Like play out, not play out for those three days and only play out later. That's an example, you're just testing too many things

[00:29:05] and just some of them are gonna come up as statistically significant by chance. But the best data scientists are going to are gonna keep this in mind and not allow themselves to P hack or cherry pick and penalize themselves for how many things they tested.

[00:29:23] It was very, I did this for 10 years and we're almost 10 years. And I had to really make sure with everything I tested that there was, and this might be a wrong approach, but it worked for me. There has to be some common sense to it.

[00:29:38] Like it can't be, oh were people on Twitter angry three days before? Well, it would be something like, okay, Microsoft had a really bad earnings announcement and the stock was down for four days. The past 50 times that's happened, what's happened next? Or stocks in general

[00:29:55] when they have a bad earnings announcement, and then they're down four days in a row, is there something that happens? Cause then it sort of makes sense that all the week holders would panic sell after a bad earnings announcement and how long does that usually play out

[00:30:11] until it then has a rebound and is that results statistically significant? Like that, something like that had some sort of common sense to it for me and would usually work. My instinct is to agree with you except I don't know if you read the book

[00:30:24] The Man Who Solved the Market about Jim Simons and Renaissance Technology. And it basically was the exact opposite approach where they built machine learning models. It was a total black box, they had no idea why it worked. They just, and it was terrifying.

[00:30:38] They were terrified cause they're like we're just making these predictions based on no understanding of why these correlations exist. But they've been printing money for decades with this approach. Yeah, and he actually wanted to offer me a job once. We were in communication

[00:30:57] and I was all set to go for an interview that looked like a formality and then he asked me what did you do your PhD on? And I'm like, oh, I went to graduate school but I was thrown out. I didn't get the PhD.

[00:31:11] And he's like, oh, we only hire people with PhDs. We can't hire you. Interesting. That's so weird. I would think he would be less by the book. No, that was his rule, like PhD or nothing. And cause I had written a book about data analysis

[00:31:32] basically in the financial world and that's how we started talking. It was interesting, but it was like I had another strategy where Canada and the US are basically the same country. So the markets should trade the same.

[00:31:48] And so if Canada, though, went up a few days in a row and the US went down a few days in a row you could go long one and short the other. And it usually was a very, very safe strategy. Didn't make a huge amount of money,

[00:32:00] but it was extremely safe. But Canada is also correlated with Australia like these other ex-British empire economies. And but then you have to look, Australia is correlated with some Asian economies. So you always have to see, you know, all of the correlations and how they're working together.

[00:32:21] And there was interesting data there that gave me a good system for a couple years. I mean, yeah, most of these winning strategies work as you said for a couple of years. They just work for a period of time and then the market figures it out.

[00:32:35] Yeah, the arbitrage always goes away on all these things, but the arbitrage can't go away with basketball. People just have to grow bigger or have bigger hands or have more dads who were in basketball. What are some other features that surprised you that the data uncovered?

[00:32:53] Well, this one is kind of a little subtle, but when you're tested to be an NBA player, you have a standing jump, like you don't get a running head start and then you have a running head start jump. And it turns out that undervalued players in the draft,

[00:33:07] like you want to draft players who have a much better standing jump than the running head start. Because I think a big problem that NBA teams have is they get too attracted to shiny qualities. So someone could just like jump with a running head start

[00:33:20] like really, really high. It's like, oh my God, that's so impressive. But a lot of the game of basketball, you don't really get a running head start. You're just kind of in place or half a step. So those players have been consistently undervalued, whereas the great leap,

[00:33:34] the people who need a running head start to leap are like, they tend to underperform their draft pick. And another one's really interesting is if someone's really ranked highly in high school and then they fall in the draft, you should just draft them anyway.

[00:33:49] It's like if someone was like in high school, everyone's like, yeah, this player is like, I can't miss. He's the 10th best player in the country. And then all of a sudden he plays in college for a couple of years and everyone decides,

[00:33:58] ah, maybe he's not that good. He's still probably that good. So it's kind of like, you should go with your first instinct. There's that phenomenon in basketball too where these players who are huge, big time recruits in high school and then they fall to the second round

[00:34:11] or whatever, tend to be really good, like really good best. Why do they not do good in college? It could be just random thing. Yeah, we don't know for sure. Maybe it was just a bad system could be, that could be the reason

[00:34:23] that was just a bad fit or something. And they don't do as well as people were expecting and everyone's like, oh, well maybe they suck. Well no, they still are as good as everyone originally thought. One interesting thing you had was that

[00:34:35] people who didn't go to college tend to be better NBA players than people who went to college. And you think that college gives you four years of intense training, like forget about the education part, just four years of intense coaching, that would help.

[00:34:49] But where do the non-college players, are they just like going straight from high school or what's their story? Yes, well it used to be they go straight from high school. It's not allowed anymore because they banned straight from high school

[00:34:59] but when they were going straight from high school, there was this huge inefficiency that they were just massively undervalued. It's kind of similar to the Teal Fellowship, right? Where he gets all these people who are the most talented people in the world to just skip college

[00:35:12] and they're just massively more successful. I think, yeah, maybe it's like also inside information. If you're willing to go straight to the NBA instead of go to college, you're probably better than people realize because you maybe know more about yourself than even they know.

[00:35:28] That could be part of it. But for years that was like a massive inefficiency. Just take players who weren't going to college. And so I'm trying to think there were some other pieces of it. What was the deal with coaches?

[00:35:41] So do you think there is such a thing as a good coach? And your point in there that was a good coach is someone who encourages, who has the ability to get players to pass more frequently between each other. But does that result on more wins? Yeah, like 100%.

[00:35:59] I'm convinced that coaches are really important. There are a lot of statisticians who have looked at it in very different ways and they're all like NBA coaches are really important. The thing about the NBA is there's an incentive problem where basically players get rewarded

[00:36:14] for just scoring a lot of points. They get paid more and they get more fans. So players have an incentive to just take a ton of shots, particularly shots through the end of the game. If you have a chance of being a hero, that's so valuable.

[00:36:27] And if you missed a shot, everyone just forgets. But that's bad for the team because it would be better if they passed for a better percentage shot. So the great coaches are able to get players to kind of overcome their incentives

[00:36:39] and pass the ball more than they naturally want to, which is, yeah, that's I think the secret of coaching in the NBA and why it's just insanely valuable. Like the great coaches, I think, add about as much to a team as a great player.

[00:36:52] Yeah, you mentioned one coach who made the players dying together more frequently and just spend more time together so they would bond more instead of having their own little islands for themselves. Yeah, it's funny because like you think, that was Greg Popovich, the Spurs

[00:37:06] who's kind of a legendarily good coach. And you think that like, what does a great coach do? You'd imagine them like just diagramming plays all the time and just like really being in their own head and being basketball geniuses.

[00:37:17] And it seems like a big part of his secret is just the social aspects of the game. Basically getting the players to like each other enough that they're willing to sacrifice some of their own monetary rewards for the good of the team.

[00:37:37] What made you wanna do this book? The thing we have to talk about is I wrote this book in 30 days using AI tools. So I became obsessed with AI. I am completely obsessed with AI. I'm just like, this is changing everything.

[00:38:03] And I started playing around with these tools, this tool code interpreter from chat GVT where you just like, it just does all your data analysis for you. It's so insane. It's like the most insane product I've ever seen in my life.

[00:38:16] Do you feed at the data or does it not feed at data? No, you feed at the data and then you just talk to it and it does everything you ask. It runs all the code, it creates your charts, your graphs, your new data sets, everything you want,

[00:38:27] it just does it. It's so insane. It was like the most mind-blowing thing I've ever seen. So what data do you feed it and you feed it in the format of like Excel? A CSV, yeah. You just feed it like these are all the basketball players.

[00:38:38] Yeah, this is their, all the physical, their physical stats, their college stats, their pro stats, where they're from. And then like, yeah, anything you just talk to it, you're like, you know, add a variable of what continent they're from and it just knows every country,

[00:38:53] what continent that's in. So it'll make France, Europe and China, Asia and Canada, North America or whatever. And it's just like so insane. So basically things that used to take me four months, now took me about four hours. So I'm just like, wow,

[00:39:09] if I could do things that quick, then I could write a book really, really fast. I tried to calculate how fast I could write a book and I concluded I could write like a good book in 30 days, which everyone told me was totally insane.

[00:39:21] I wouldn't be able to do it, but that kind of like, that was fun too. Cause it was like, oh, you know, people don't think I can do this. Well, I'm going to show them that I can write a good book in 30 days. So that was motivation.

[00:39:31] And then I'm obsessed with basketball. So I'm like, well, might as well write about basketball cause it's such a passion of mine. So it was a combination of, it was mostly due to AI that I just wanted to like play around with these tools.

[00:39:44] And it's great cause the AI, it's not like it wrote the book, right? It was like an assistant. It basically allowed you to crunch the data a hundred times faster or 700 times faster than you normally could. Well, and then all the art.

[00:39:58] So I've never had art in anything I've done because I like, you asked me to draw- It takes a long time. It's not just takes a long time. I have zero talent. Like you said, draw a horse. Like I couldn't draw anything

[00:40:09] like that at all resemble the horse. But now I have like art that I think is people have been telling me like, wow Seth, your art is so beautiful. And I'm like, you know, if I didn't do any of that I just told mid-journey or Dalí,

[00:40:21] like make, you know, make a, I have a section on genetics. So I'm like, you know, be fun for that. Make a piece of DNA like playing basketball. And then like they have a piece of DNA playing basketball. I was like, all these things.

[00:40:32] I'm like, wow, you know, that's super cool. And like it kind of, it's kind of fun cause like one of them, like I think there is a creative artistic person inside me. Absolutely. Yeah, but I can't express it because I have no talent like to draw.

[00:40:50] But then like I can express it now cause Dalí or mid-journey could just draw my ideas. Like, oh DNA playing basketball or you know, whatever idea I have. I mean, when chat GPT first came out I did a little experiment. I wanted to see if in an afternoon

[00:41:05] I could have it write a book. So I wanted to learn more about like neuroscience. So I just started with like random prompts like what makes someone smarter in terms of neuroscience. And then it would mention all these neurochemicals. And then I would say like, okay, well,

[00:41:22] what foods contain or boost these neurochemicals? And it would list some foods and then I'd say, okay, come up with five recipes that use all of these foods. And it would come up with these recipes and format them just like in a cookbook.

[00:41:35] And yeah, you can have pictures of the food. And it's, I think it's a real great thing where the hype equals the reality. Like AI actually is immediately improving the efficiency of the entire economy for millions and millions of people right now. Yeah, I totally agree.

[00:41:56] I mean, like even you just see the uses so if you go to mid-journey, like if you use mid-journey it's on discord. That's the art product. You give it a prompt. Like, I have one, I wanted to talk about,

[00:42:12] I have this theory that the best potential basketball player is probably working as a rice farmer in India right now. Cause like what's the chances that the best basketball player LeBron James or something happens to be born in the United States?

[00:42:23] Like it's more likely that there's someone out in India like United States, the tiny part of the populations that just never grew enough because of bad nutrition and never developed their skills. So I'm like, it'd be fun to draw LeBron James as a rice farmer in India.

[00:42:38] So I just tell mid-journey like draw right LeBron James as a rice farmer in India. It looks exactly like LeBron James as a rice farmer in India, it's wild. But then when you're on mid-journey you see what everyone else is asking for.

[00:42:50] And it's just like, yeah, like one of the big use cases is coloring books, for example. People are like, I'm making a coloring book, make like an elephant coloring, coloring or whatever. And it's so, it's perfect. Like there's no use for a human

[00:43:06] to create a coloring book anymore. Like obviously you just do AI mid-journey or Dolly and you have your own coloring book. I mean that you could do in like a day if you come up with a coloring book or something.

[00:43:20] So yeah, it's like, yeah, I totally agree with you. The hype and the weird thing is AI right now is the worst it's ever gonna be. So it's only gonna get better from here. Like this is the worst version of AI. It's only gonna go improve.

[00:43:36] And it's still a ready revolutionary. So like how much better is it gonna get? I wonder if there's a plateau though. Like I wonder if there's the huge leap and then now improvements may be significant but it might not be as noticeable.

[00:43:49] Like when you buy a MacBook Air now as opposed to two years ago it's much better than the MacBook Air two years ago but you can't really tell. Like it's not like it used to be 10, 15 years ago. There might be a plateau

[00:44:02] but like I think the end game is just like an infinitely smart person who can, an infinitely smart machine who could do everything like in no time. So like I think we eventually will get there. So it might be like the curve if it's been growing exponentially

[00:44:19] it may like stop and then go like start growing exponentially again in 10 or 15 years. I don't know how it's gonna play out but I think the end game as long as it doesn't kill us all is just like a perfect intelligence.

[00:44:33] Well, what other data things can you feed it? What else have you played around with? Well, I mean the last 30 days I've been working nonstop on my book because I was trying to write a book in 30 days which is not easy.

[00:44:46] Wait, did you have a publisher publish it in 30 days or did you sell it? No, no, no, I couldn't, I sell published. I couldn't convince any publisher to take this project. Take this project. But now you realize now you've discovered the joys of self publishing

[00:45:01] so now you can write your next 50 books. It's so much fun. It's also like, I just kind of like I don't know if you can relate to this I just liked the challenge of like being outside the system. It's like more fun.

[00:45:14] It's like you feel like you're a rebel a little bit and it's like usually I hate self promotion but I've been really enjoying self promotion for this book cause it feels like I'm a little bit breaking the rules and like trying to convince people

[00:45:25] to have me on their show even though I'm not like an official Harper Collins author anymore. I'm just like a self published author is really fun. My best selling books are self published about 50, so I have over 20 books about 50% are mainstream published like Harper Collins and so on

[00:45:43] and 50% are self published. My best selling books by far are self published and it's because you can market it better because it's like it's still fresh in your head. You probably, you don't have to wait a year and a half

[00:45:55] after you wrote it for it to be published like you just wrote it and now it's published. So you could still talk, you have the energy to talk about it and you can also play around with pricing. You could do deals with email lists

[00:46:07] and marketing to like you could market it yourself. You I can't market my Harper Collins books. Like I can't pay for ads on Amazon because they only accept the ads from the publisher. So whereas self published books you can. I totally agree with you.

[00:46:22] And for whatever reason, it's just been really, really fun. It feels like, again, I hate self promoting. I've always hated marketing. It's always felt like gimmicky or whatever but the challenge of this has been like I've just been leaning into it. Someone told me the book was,

[00:46:35] they couldn't get a paperback copy of my book. And I'm like, I'm sure that was just like an error of Amazon or whatever. But I'm like, it'll be really fun to make this seem like my book isn't so such high demand that it sold out everywhere.

[00:46:50] So I started like blasting out on all the social channels that, the book is sold out due to high demand or whatever. I've just been having so much fun. Like that's like a classic marketing trick, right? Yeah. So like which I've never done before.

[00:47:01] I've always found it gimmicky. But for some reason, I think the self publishing has just unleashed the gorilla market. Well, because it's more of your baby. It's more my baby, yeah. Yeah. That yeah, it's more my baby. And I feel like I'm not responsible to anybody.

[00:47:15] Like if there, nobody's watching me to be like, you're not allowed to say that or whatever. It's just like, it's all me. And I just love that. So here's a data thing. Like, and a friend of mine did this data analysis in 2014

[00:47:28] about mainstream published books versus self published books. But first off, he did it in 2014. So that's nine years ago. I don't know if the data is different. Second, or maybe it was like 2016. Second, I don't know if you ever saw the TV show,

[00:47:41] Silo, it's Hugh Howie did this. So he wrote the book, whoa, which became the TV series, excellent TV series, Silo. But he, his analysis years ago concluded that on average self published books have a higher ranking than mainstream published books.

[00:47:58] And on average, he had some other conclusions that were you would think would be the reverse, but he concluded that self publishing was better. I'm forgetting all the data now. It might be. That said, can you actually get like rich, rich for books?

[00:48:13] It seems, I guess you can really. Let's take mainstream published books. Let's say you get a huge advance. All right. I don't know. What's a huge advance these days? Like, okay, a million dollars, a few people still get and so on.

[00:48:30] I had a good advance on my last mainstream published book, but the advance has spread out over many years. So it doesn't really feel like it has that big of an impact to your income in any one year. And then the agent takes out 20%

[00:48:45] and then the IRS takes out about 50 to 60%. And so, and then you get these payments like once every year and a half or you know, you get three or four payments. It just doesn't feel like you're making any money on a mainstream published book

[00:48:58] even if you have a huge advance. I know you're not getting rich from a mainstream published book. I'm saying can you get rich from a self public? I mean, I guess you can. Like, you know, you can get rich from books.

[00:49:07] J.K. Rowling is a billionaire or whatever. But I'm saying like, from my experience, that's a good experience. Yeah, from my experience, like everything I've done creatively, even when I thought I was making a lot of money because I had just been a grad student

[00:49:21] and I'm like by my standards compared to my $30,000 stipend, this is a lot of money. When a business call, like a hedge fund called me up and they wanted to help like me to work for them. I'm like, oh, that's another league compared to a creative pursuit.

[00:49:35] But I don't know, maybe I'm, I mean, it's also obviously a power law. So like, yeah, I don't know. Yeah, you're right. Like so, so John Grisham, J.K. Rowling, they're definitely outliers. And self publishing is hard, but I just think, look, let's put it this way.

[00:49:50] I think you're more likely to make some money from a self published book than a mainstream published book. No, I agree some money, but it's even hard. Like who makes the MBA? Like, although I've been lying and claiming that it's like,

[00:50:02] you know, nobody can get in the bookstore because it's so much demand. You know, refreshing the royalties on like Amazon. And it's not that much, you know, I'm getting five bucks. But you could do deals though. Like when I had my book, Choose Yourself come out,

[00:50:19] some guy called me and said, hey, I have this huge email list. This guy had like a million people on his email list. If right a few extra chapters and make it hard cover cause at the time Amazon was doing paperback

[00:50:31] and Kindle and audio book, but not hard cover, make it hard cover, write a few more chapters. It's just for people on my list. And include like your stock predictions. And I will sell 20,000 copies of this for $20 in two weeks and split it with you. And he did.

[00:50:52] And he did. He sent me a check literally for $200,000 two weeks later. Wow, okay. Yeah, so that is- And at that time that was the most I had ever made from books. A book. And that was because I did this deal.

[00:51:06] Like you can do deals that publishers can't do. Interesting. Another thing with books, I feel like, so I love books. So if someone like, anytime I see like, you know, someone tweets, hey, this book was good. I just order it. It's 15 bucks. It's like, what do I care?

[00:51:25] You know, 15 bucks, whatever. I'm like, I love books. I'll learn something. I'll learn a few things. Like, I buy a ton of books, but I feel like the average person just doesn't like books that like, I mean, another thing I'm seeing like, I'll tweet, I'll tweet.

[00:51:39] I had one tweet when I was promoting my book before it came out. It got 1.1 million views. And then like five people bought my book off of that tweet. Like, which is a terrible rate. So what am I doing wrong there? Like, is that-

[00:51:55] Well, because your people aren't going from Twitter to Amazon, but what they will do is they'll go from Twitter to Substack. So you could do a thread. Here are five things about the MBA you definitely did not know. And then you have a new,

[00:52:14] you reply to that tweet and you have the five things in each new reply. And then at the end, you say, if you like this thread, I thought it was interesting. I have a lot more information like this. Subscribe to my newsletter on Substack

[00:52:27] and you link to that. And then you have, then you're bringing your audience onto your own platform and let it instead of- You're getting to know your audience. So I need a Substack. I need a Substack first.

[00:52:37] Yeah, like you need a way to get to know your audience. Like right now they're just these amorphous Twitter followers who love your stuff, but you just don't know anything about them. So you need to kind of build a community and you can do that along the newsletter.

[00:52:50] No, sometimes I'll also see like, you see the Twitter statistics, like a lot of people just like click on your profile when something goes viral. They're like, who is this person? They probably just followed me like five years ago and they totally forgot who I was.

[00:53:03] And I would tweet going viral. So they're like, oh. Or someone shared it. So they, so their friends shared it, but they don't follow you whether they follow their friend who shared it. But if you could get people onto your newsletter,

[00:53:13] then you could communicate directly to them through a newsletter and a higher percentage of newsletter readers will buy your book than Twitter followers. Twitter followers, you're lucky if you're gonna get, you know, one-tenth of 1% to do anything. But they will go from digital thing to digital thing.

[00:53:31] Like if you have a free newsletter, they'll subscribe to that. So like, so yeah, so, cause you said you're gonna offer me tips to make more money. So like, do you think doubling down on like creative stuff? Cause I feel like I should, I love doing it.

[00:53:46] I did this one month project just cause I'm like, this, I'm not like I'm gonna get rich off an MBA book. I'm just like, I saved a lot of money. I don't really need to think about money for a bit for a while.

[00:53:57] I'm just gonna like have fun for a month and fool around with MBA data. And like, you know, it was pure joy. It was like the month of my life, the highlight of my life I'd say up to this point. That's great.

[00:54:08] But yeah, but I'm kind of like, I think the creative thing is kind of like a, I don't know, from what I found, like I said, anytime like a business reaches out to me, I'm like, that's where they really have the money

[00:54:19] and the creative stuff is hard, but I don't know. Don't separate out creativity from business. Like you're a real creative data analyst. Like you find things like people in India have fetishes about breastfeeding. Yeah, I've been that one. I've never been able to monetize.

[00:54:34] Maybe I should be like, yeah, there should be like some breastfeeding porn company especially in India. No, but what I'm saying is look at my friend who has this car data and like he told me, if you have a Subaru, I'll the first question I'll ask you is,

[00:54:49] what's the name of your pet? Like everybody who has a Subaru has a pet. So he has like all this data about people, like he's obsessed with cars. He's always data about people based on their cars. So you know how to analyze data

[00:55:01] and you're very creative at it. Like this is like an art form too. As you said, there's bad data analysis and there's good data analysis. There's some types of data analysis that will make money and some that won't. So maybe finding things out about porn

[00:55:15] might not make money, but there are areas and stock market might be too crowded to make money. But there are areas like again, my friend's doing it with car dealerships. By the way, he's only doing it with new car dealerships.

[00:55:30] He's not even doing it with used car dealerships. Like new car dealerships was enough. So this is like this brand new field. It's not a brand new field, but it is a brand new field now because of AI making things so much faster and easier

[00:55:41] that there's kind of this wide open field where you could find creative stuff that is potential to make money. For instance, insurance, there's a lot of statistics in insurance, but I bet you it's not really using the latest sophisticated data analysis techniques

[00:55:59] or even selling insurance also could be related to that. I know, but just like thinking that makes me wanna like shoot myself in the face with a shotgun like insurance markets. Like another problem I have is I just, if I'm not interested in something,

[00:56:14] it's very hard for me to do it. I know the feeling. Yeah. And like I've always, I've always my entire career, like I do something completely impractical and then I'm like, this isn't working. So I major in philosophy. It's like the least practical. I was in Stanford,

[00:56:30] the hardest Silicon Valley ever was studying computer science. My friend in my dorm was like the eighth employee of Facebook and I was like reading Nietzsche books. Like it was insane. Like there were four kids in the class. Like it was not,

[00:56:42] did you get angry at the tech kids who then got rich? No, no, no, no. I'm not gonna admit. Yeah, probably. Yeah, probably. But so then I'm like, okay, well this is not going anywhere. Like I've, again, I'm having this, I loved it.

[00:56:57] I was smoking a ton of pot. Like I was just like really enjoying my life, but I'm like you can't just read Nietzsche the rest of your life. It's like after you sign practical and then I got an economics PhD. Like the total,

[00:57:10] from zero practicality to like 100 practicality and like I was all on the path. I was writing papers on like the equivalent of insurance markets. And I'm like, I'm like, and the professors were like, you're, you know, liked me.

[00:57:23] I was on the path towards like a good academic job, a safe academic job. And then I found Google Trends data and like breastfeeding porn. And I'm just like, I gotta look at this. Like I just stopped completely all the practicality and I'm just like,

[00:57:37] and then I like, so I always like, I'm always on the verge of practicality and then it's like philosophy, porn, NBA analysis. Yeah. So what do you make James? I find your analysis of these situations interesting. You know, I have the same problem, right? Like so in 2001, 2002,

[00:57:55] when the dot com boom was busted, a lot of my friends who were in the tech business in New York, they all picked up and moved to Silicon Valley. And literally they all became billionaires. They're all billionaires now. And I could have done that too,

[00:58:12] but I didn't want to do it because I wanted to write a novel. I wanted to write books. I wanted to, I mean, I built other companies. I sold them. I did okay. I was a hedge fund manager for a while, but I always asked myself,

[00:58:26] what if I had just, it's a better life anyway in California. It's better weather. It's everybody I knew moved there. What if I had just done that and focused on money just a little bit more? Maybe I'd have like a billion dollars, but then I wouldn't have done,

[00:58:41] I mean, I did stand up comedy for six or seven years. I've written all these books. I have some degree of notoriety. I have this podcast, which I love doing. So you only have one life. So... Yeah. And I kind of feel like

[00:58:56] if I spent 30 days just doing what I love, like that's even hard for a billionaire to do, right? To like find a passion project like that that they're so obsessed with that like who cares at that point? If you're... I would say their passion projects

[00:59:12] are things that like Elon Musk is doing his passion project. He wants to go to Mars. He figured out from the ground up how rockets work and he put it all together and made billions of dollars at it. Like he has a passion for that.

[00:59:25] So I do think a lot of billionaires are passionate about business-y things. Well, yeah. That's like winning the lottery if your passion also has to be like connects with a get rich thing. So like when I was in high school, I was obsessed with fantasy sports.

[00:59:43] Like I've just always been obsessed with sports. Who makes the NBA book? And like my dad is like, I was like number like, I was like winning all these national competitions and fantasy sports, even though I was like, everyone else was like a grown person

[00:59:56] and I was just like a little kid. And my dad's like, this is very impressive. Like it's great there. So passionate about it. But like can't you just devote all this time and energy to the stock market? Well, he gave you bad advice. Did he? Yeah, because okay.

[01:00:12] My podcast I've had on as a guest a couple of times, Matt Barry who he was a Hollywood screenwriter. He wrote like one of the crocodile Dundee movies. He's written a whole bunch of things. He was making a great living out there and he hated it.

[01:00:25] He hated it. He had the same expression. I felt like I was going to shoot myself in the face. And he loved fantasy sports. So he quit all the Hollywood stuff and he got divorced. Like his whole life changed.

[01:00:39] He lived in a, he moved out of his fancy Hollywood house, I guess, and moved into a small apartment. He started writing articles for a blog about fantasy sports for $100 an article. And because he was a good writer, cause he'd been a professional writer,

[01:00:54] his writing started getting noticed and there's a lot of fantasy sports fans out there. So he created his own site and it got bigger and bigger. He sold it to ESPN and now he's the anchor for fantasy sports on ESPN.

[01:01:07] Like when I walk in the street with him, everyone says, oh, thanks for those picks. I won my league last Sunday or whatever. Like he's famous guy, ESPN, made money, makes a great living, and all from fantasy sports because he single-mindedly

[01:01:23] pursued the profession and figured out how to make money off of it. He built this platform and then he sold it and... Yeah, but that's another danger in picking a career, right? Is there's all this selection bias. So the ones who tried that and didn't get anywhere

[01:01:37] are gonna be on your podcast. Yeah, that's true. That's true. So you don't know... Yeah, I don't know what the odds are. What percent of people have quit a lucrative job to follow their passion? Like it turned into anything. Well, one thing we know for sure

[01:01:51] is that the percentage of people who do that is higher now than it was 30 years ago because of the internet. So like my listeners know I'm obsessed with chess right now and one of the things that really intrigued me back in 2020

[01:02:06] when we were all kind of locked in for COVID in 2020 and 2021 is that chess players who weren't necessarily the best players in the world. In fact, some of them are not very good at all started using YouTube and Twitch to analyze games or stream their games live

[01:02:23] while they were playing the games. And this became a thing. And so some of these people have like hundreds of thousands or even millions of followers and are making millions a month on chess an activity that never made anyone money ever

[01:02:36] in history but now is making even bad players a living and not just a few, but like quite a few. And it actually is not as big now as it was in 2021 when we were all locked in. But so that kind of amazed me that

[01:02:50] because of all these tools available to us and getting more and more available to us you could basically do anything and there's probably some way to make a living at it. Well, I just think the question is the odds. So even chess, what percent of chess people

[01:03:05] with Twitch are making a good living on it? It's probably pretty tiny. I think it's hard to say because there's selection bias but there's also if you weren't succeeding like how fast did you give up? So a lot of the people who just stuck with it

[01:03:19] who started maybe their Twitch streams in 2016 and had 50 followers and 60 then 80 and they stuck with it. And then the pandemic came and the TV show, The Queen's Gambit came out and then suddenly it spiked and they spent years developing their personalities on Twitch and YouTube and so on.

[01:03:36] So they got a huge fan base. Basically all of the people who stuck with it succeeded. We just don't know how many people kind of gave up before their magic time or maybe they gave up because they didn't have a good personality or they didn't enjoy it

[01:03:51] for whatever reason. So it's hard to say but I do think the odds are much higher now than they've ever been before that you could take anything. For instance, if you did a newsletter about quirky data stuff and you did this once a week or once a month

[01:04:10] you would quickly get 100,000 readers and you could monetize that. You could have ads in your newsletter and it would make you a living for the rest of your life. I know plenty of people- Well, newslet, substackers some of them are killing it right now. That is like-

[01:04:22] Yeah, and that's just persistence, consistency and having good information and you have the good information. Try to think not just for basketball but for like any field like the data, the quirky data of the week and just put it out there

[01:04:40] and I bet you you'd get like quite- I know one guy, Joseph Pompleano who has a newsletter called- They are following on Twitter yeah. They are following on Twitter. He has a newsletter called Huddle Up and he combines, he was an ex Morgan Stanley Bond trader.

[01:04:57] He combines business with sports. So he talks about basically the business of sports and all these quirky things that I never knew about like how much people who perform in the Super Bowl get paid and just what does the Mavericks getting sold mean for the basketball industry?

[01:05:16] Like, alright, how do they value the Mavericks and all or different salaries? I don't know. He's been on a bunch of times. I've read a bunch of the newsletter. I don't even like sports but I love reading about data in sports and business in sports.

[01:05:31] And so it's these weird intersections that are doing really well on Substack and you can make a lot of money on Substack even with like really offbeat newsletters. Like that's something I would definitely consider. Yeah, no, I think also just my work ethic tends to be very inconsistent

[01:05:51] in that I'm either all in or like I'm lying on a beach for like two months or I've never been someone who's like, you know grind it out day in, day out, week in, week out. And I think, you know, if you're, if you're a newsletter person,

[01:06:04] like the great thing about writing these books and like my weird consulting stuff and speaking is you just kind of like do it when you do it and then, and then, you know the rest of the time you kind of just goof around. It's really hard.

[01:06:18] Like I have a hard time with that. Like I said, I've been on this quest where I'm trying to get as good a chest as I was when I was younger. And it's very hard because the whole, I stopped playing for 25 years

[01:06:31] and the whole world, the whole chess world's different. And so I've been doing my own data analysis like how often does someone my age get back to that level that they once were? It's, it's, you could count it on one hand out of. Always it.

[01:06:46] Yeah, out of millions of players. So it's very, very hard. Like I was talking to one friend of mine who did a study on this and it's literally like less than five people. And, but also there's now, there's things I look at like,

[01:07:03] okay, what are the most successful opening moves? Like very few people have looked at this before. Like what can I play in the beginning of the game? It's called the opening that leads to the highest percentage of wins. And it's funny how few books or players

[01:07:20] really mentioned this. And, but there's answers to all these questions. I read a book about AI chess and how it's taught people things about the game that we didn't know. Like I think you'll probably know more by like moving the pawn all the way from the end,

[01:07:33] like up a lot is a very successful move or something. Yeah, you read the book, Game Changers by Matthew Sousa. Yeah, yeah, yeah. That was good. Yeah, that was good. Magnus Carlson specifically took that book and took those games at the computer plane

[01:07:46] and he really, really studied them and it has noticeably improved his game. Like he uses a lot of the computer strategies and he, I mean, it's very hard to improve when you're already the best player in the world. And he's been the best player in the world

[01:07:59] for about 15 years or more, but he's steadily kept improving because of studying the computer. And the computer really had like unusual strategies that it had sort of, I guess perfected and it's worthwhile for humans to study them. I had Gary Kasparov on the podcast

[01:08:20] and before the podcast we're talking and I asked Gary Kasparov, hey, I read this great book Game Changers about computer chess. And I said, did you read it? And he said, read it. I wrote the forward to it. You didn't read the whole thing.

[01:08:33] So he's got that, the Russian Jew style of. Blunt. Yes. But yeah, I do believe that if you're really passionately interested in something, there's a way to make money at it. And I just see it in so many different fields. You're right, there is selection bias,

[01:08:52] but I'm kind of an example of where I've been able to, most things I've done, I've been able to turn into something that was worthwhile. And now the other question is, at what point do you start thinking about monetization? Cause I've also heard like,

[01:09:06] if you think too quickly about monetization, like then you don't allow your creativity and your curiosity to really drive you, but you can't like never think about it, right? Yeah, like I was writing my kind of personal development style of blog posts

[01:09:20] for about five or six years before I even thought about monetizing it. And I think, yeah, it's a good point that the quicker you monetize something, probably the less money you'll make from it. So you kind of have to let it, because it's sort of like

[01:09:36] you create this enormous goodwill with your audience when you're doing something for love and they can see it and there's no friction for them to see your stuff because they don't have to pay. And so you build this enormous goodwill

[01:09:50] and after a certain amount of time, they want to pay you. They want you to benefit from all this good work you're doing. And I'm not saying this in a cynical way. They legitimately, generously want you to do well because you're providing so much value for them.

[01:10:04] And so they almost feel bad if you don't ask for money at some point. So it's sort of like you'll know the right point to monetize. And I've had a couple of those points depending on what industry I've been, because I've also diversified industries,

[01:10:17] which might be a bad thing because I've been a jack of all trades master of none, but maybe a little bit of a master in some areas. But that was actually another question. This is actually related to your basketball data. I noticed for the seven footers,

[01:10:35] a lot of them didn't start playing the game until they were older, whereas probably the six footers played it from the age of six years old on. And I wonder if, you know, in every field, what the ages are where it's too late, given your set of characteristics,

[01:10:56] at what year is it too late for you to start doing something? And, you know, some professions is older than others. I think it's a really good question. I think it's an unknown question. You probably know the book, Range David Epstein. Yeah. Like everybody loves that book. Yeah.

[01:11:09] Because it kind of says that, you know, it's good to sample things and take a while to specialize. He starts with sports. He says, you know, Roger Federer, we think of Tiger Woods who started playing golf when he was two years old.

[01:11:21] And like that's the way to master sport. But Roger Federer played a whole bunch of sports until he turned to tennis. I think as a teenager, and he actually, that's actually an advantage in some ways in a lot of sports. And like even some seven foot players

[01:11:32] like Nicolid Jokic, he played water polo as a kid. And you see the way he plays basketball is like a water polo player. He's just like always looking around, pass this way, pass that way, pass that way. And it's like a really unique,

[01:11:46] he's kind of has a unique style that turns out to be really effective that he might not have developed if he played basketball too quickly. So they're probably something that, but I'm sure it just depends so much on the particular skills that are required.

[01:11:58] The skills that are required to like learning a language. We know that the earlier you try like the better chance you're gonna have. Like you wanna really start, if you have a kid, you want them to be bilingual, you know, raise them as bilinguals,

[01:12:11] teach them both languages when they're kids. Cause it's gonna be way harder when you're 20 or 30 or let alone 60 to pick up a language. Whereas some other skills like, you know, yeah, like your business skill I think you could probably learn pretty late. Like, you know,

[01:12:26] I'll almost the later the better. Yeah. And I talked about in my last book that the most successful entrepreneurs tend to be 45 years old, which surprises people. Everyone thinks it's like 18 year olds like Zuckerberg. But that's just a selection effect where the best potential entrepreneurs

[01:12:40] like start really quickly, like Zuckerberg and Gates and Jobs. But you know, on average, it's good to like find your time and learn your craft and learn your field and learn your industry and then start your business, you know, your 40s, your 50s, your 60s.

[01:12:55] So that's an area where it's definitely, I think people think, I guess a lot of people missed opportunities cause they thought it was too late in business. Like they're like, you know, they had an idea but they're like 55, they were having a family that a mortgage,

[01:13:10] they're like, well, I'm not going to all of a sudden become an entrepreneur. And I think the data clearly shows that's a mistake. A 60 year old has like a higher chance of succeeding than a 20 year old, three times higher chance of succeeding than a 20 year old.

[01:13:23] Like six year old still has a great shot of creating a successful business. So I think that's an area where my guess is a lot of people are missing out by thinking it's too late. Yeah. I think you're right. Because also a look,

[01:13:36] a 20 year old still doesn't know how to manage risk. And like 90% of entrepreneurship is how you manage risk. And this is, you know, most companies fail because people don't manage all their risks properly. And they don't know how to test things and be cautious and so on.

[01:13:52] But you know, for you, like you love data analysis. Now your third book on quirky, weird, fun, exciting data. And is it monetizable? Probably like again, there's this example from cars. There's tons of examples from every industry. But just specifically what you do like the quirky stuff,

[01:14:15] I would try to see if on a regular basis, you could come up with something interesting every week. And it doesn't have to be the most interesting thing because for every newsletter writer, some letters are good, some letters are bad.

[01:14:30] You know, not every issue is going to be, oh my God, this is the one that's going to go viral. You can't predict virality. But I would, you know, like we have a political season coming up. There's certainly lots of data about politics and so on.

[01:14:45] I mean, who's that guy, 538.com, Nate, whatever? Yeah, he made a whole career out of like quirky data on politics. But I'm curious if like over the next week or so you could come up with another quirky thing that you get the data on

[01:15:01] and you feed it into Code Interpreter and you get excited about it. Yeah, I think Code Interpreter could make it like really less painful for me too. Cause also I like data analysis but I've always kind of hated coding. Like coding has never been fun to me.

[01:15:16] Like that's like boring and like debugging and that's all I'm doing. But now I don't have to do any of that cause like Code Interpreter just does it. So now it's just really coming up with the questions. And getting the data.

[01:15:26] Like where do you get your data from? Well, another reason I did the MBAs are just so much data available. Like just cause there's so many nerds collecting data on this. So there's all kinds of data sets like Kagle, prediction contests have data sets

[01:15:39] and basketball reference is this huge site by basketball nerds that they just have tons of information on every player that was really useful like all kinds of play. Yeah, so it's harder. What if every team, like every game you bet on a team

[01:15:55] where on average they have higher larger hand widths. Like I wonder if that would be a good betting strategy. You'd have to figure out, you'd have to take into account the odds I guess. Yeah, my guess is not cause I think

[01:16:08] like by the time an individual game happens like we know that's a good player. Like we know so Kami Leonard was a player with enormous hands and he outreformed his draft pick but we knew he was a good player by the time

[01:16:20] you know a certain number of games into the season. So maybe it would work like the very beginning of the season but I think eventually it would kind of be incorporated into the odds. But you never know because sometimes there's an arbitrage

[01:16:31] where the home team, you know the home team more people bet on the home team in that town and so the line sort of adjusts. I don't know anything really about betting but you know sometimes there's an arbitrage because people are excited about a certain team.

[01:16:46] But what if they play a team where for whatever reason this team on average their hands are so much bigger than the team that everyone thinks is gonna win and people aren't aware of this arbitrage you mean there might be opportunities like that.

[01:16:59] It would definitely be an entertaining way to make money. I would say I think a general betting on sports could be very lucrative if you, didn't you have someone on your show who's made killing betting on sports? Billy Waters and then I think there was another guy too

[01:17:15] recently, I forget. I know one guy Billy Waters made a lot of money on sports and he's still making a lot of money on sports doing something like this and maybe we had someone else recently. But just even, I don't even care about the betting

[01:17:30] like just asking the question like do the teams with larger hand whiffs win? More than the team yet? Yeah no I could have a newsletter where I just asked like a quirky question that only I would think to ask like all the time.

[01:17:41] Yeah, because that's where you're really, you're a creative guy and creativity is not just about like painting paintings or writing poetry, it's these questions and data. So that's why your books like no one, why didn't know whenever write a book about using data analysis for self improvement?

[01:18:00] Like that was a great book. Thank you. What was the title of that one again? Don't Trust Your Guy. Don't Trust Your Guy yeah. And so yeah just stuff like that like even the stuff like it's in that book there's so many things that people say on Twitter

[01:18:14] like oh if you take vitamin D you're never gonna get a cold. Like every day on Twitter people are constantly making presumptions and saying things. Well you could actually test the data on all of these things, write a newsletter that everyone, you know what's going viral already

[01:18:30] because somebody will say something on Twitter and it'll go viral and you could just say oh well no that's wrong because here's the data and then boom that will go viral piggybacking on the first thing. Yeah I also think just like newsletters it's like let's say you're charging

[01:18:44] like a hundred bucks a year. Like I have a pretty big network. Like I start with like my mom would definitely subscribe and my dad would subscribe, my brother, my sister, I have like 28 cousins. Like I start doing the math just from there.

[01:19:00] I'm like at what point do I just people who love me I feel like I have a lot of friends. I'm like I'm like I just get start there then I have my base then I expand outward to fans. I don't know. Here's what you should do.

[01:19:14] Start it free and get 10,000 free readers and then convert to premium. So some of the newsletters some are still free like half are free and half are premium and you have to pay like I don't know 19 a month or $9 a month for the premium

[01:19:31] and 10% roughly 10 to 20% will convert from free to premium and that's the math. So just get 10,000 subscribers then you'll have 1,000 that'll pay you 10 bucks a month so that's 10,000 a month and to get to 10,000 free subscribers is you have to have good quality stuff

[01:19:50] but it's not like with your material it'll get that fairly quickly. Yeah, yeah I guess just the consistency is something I've always rebelled against. I don't like having like pressure to do something every week or whatever. Like I like my two months like my little sabbaticals

[01:20:12] like I bet if I told you, Seth I want you to come on this podcast every Wednesday and tell me some new quirky things. I'd shoot myself. Yeah probably every Tuesday night you would be like yelling at your girlfriend and getting all this stuff.

[01:20:25] No, I'm like I wanna go to the Caribbean for three weeks or something like I don't have kids right now so I'm like I really can just I think just I don't have to think I also for a long time have avoided

[01:20:36] like all things that pinned me down in any sort of way. So I think on all dimensions of life and I think this is another way it's just would feel like it's pinning me down. It's limiting my freedom. I've always been after freedom. So here's what you do.

[01:20:51] Don't do a newsletter every week. Do first collect like first let's say two weeks from now you have an inspiration for a newsletter. Okay, just do it in secret. Then three weeks later you have one and then suddenly when you have like 20

[01:21:06] newsletters done and you haven't released to sing one now you can start releasing every week no you could be consistent because all the work's done. You know, do you know where I meet safety? Oh yeah, we convinced me to do a newsletter

[01:21:19] in 2011 he convinced me to do a newsletter. Rami and I lived in the I think we were roommates for like a semester junior year randomly assigned. Oh wow. I'll give you a great Rami story. I think we're roommates maybe dormates yeah I think was roommates

[01:21:34] and then we are he announces he's going to teach everyone personal finance so he starts plastering around the whole dorm like Rami's safety is personal finance class and I'm just like Rami you don't know anything about personal finance like what the hell are you talking about?

[01:21:53] Nobody's going to show up to your stupid class on personal finance like you're not a professor you know people have been studying this for 30 years whatever then he puts on his class I think two people showed up I think one of them had a big crush on him

[01:22:08] and I felt so bad like this poor guy has no sense of like what's what the world wants from him he's making a fool of himself like what a loser and we didn't really talk for a while and I just like I'm in my PhD program

[01:22:20] I like just wake up one day I look up like I see Rami somewhere I'm like I look him up and he's like the world's great personal finance crew and it just got a Netflix show Oh it gets bigger and bigger and then he's the number one show

[01:22:32] and Netflix and this and that and I'm just like if I have kids I'm telling them the Rami Siti story that's how you start you got to plaster it you got to have that hootspa before you know fake it till you make it

[01:22:46] you got to put go around put put all the stuff on the world don't care that your roommates going to think you're an idiot you know you're a loser you're pathetic you don't know what you're talking about he just he had pure confidence hustle hootspa from day one

[01:23:00] and then it's but everybody starts nobody starts like you know everyone knows everyone's super impressed by you and like now it's easy for him but yeah you're totally right by the way like that's why degrees and experience it's not like experience is not necessary but it's overvalued

[01:23:23] you got hootspa is the most important oh yeah value like I had a friend I just want to tell you this story I had a friend who he was rejected he wanted to be a professor of computer science at Cornell University he was rejected

[01:23:36] he had a PhD in physics they didn't want him to teach computer science so he did the same thing Ramit did he started putting up signs in Cornell's computer science department at 7 p.m. Thursday night I'm going to teach this thing about computer science

[01:23:50] and he was a good very talented teacher more and more people started showing up for a class now he's a tenured professor at McGill like for computer science and he taught at Cornell for many years well yeah no but the reason I brought Ramit is he

[01:24:04] he apparently now is living a life where it's all automated a lot of it's automated he can just go on vacation for like two months and his team or whatever just does all the posts and he has the post in waiting and kind of what you're suggesting

[01:24:19] and then so he can live this free life that seems appealing while still having a massive audience and everything yeah think about it like let's say for a year you decided to just explore whatever you wanted and you would just format it into a newsletter

[01:24:34] or even get a virtual assistant to format it into a newsletter when you had enough interesting things and let's say on average every two weeks you came up with something well after you have 26 things after ten years you have 260 so like at some point

[01:24:50] there's enough where you could be consistent with a newsletter without really giving you too much stress so like that happened that happens that still happens for me because I wrote every day for like 20 years so and a lot of things I wouldn't publish some things I would publish

[01:25:06] but then people would forget it so it's possible to just reuse stuff or rewrite stuff all the time because I have thousands and thousands of articles that I have ready to go well yeah and I can also just use stuff for my books

[01:25:18] a lot of people want to have read them and then yeah like right because like you want 100,000 subscribers on sub-stack okay probably 100,000 people didn't buy your book I mean maybe they did but you know you're gonna hit a new 100,000 anyway and of the 100,000 to read your book

[01:25:34] they're gonna forget anyway you know most people forget 95% of what they've read so and you could update things so it doesn't have to be the same you could give provide a little bit more insight on each thing so you already have like a ton of material

[01:25:49] so or you could just you know you could slice the material in a different way so you know you have like an enormous you already put a lot of work into this data analysis and you have this very quirky style and this very creative style and data analysis

[01:26:07] I would form something around that like it's just a fact I love that stuff so I would subscribe to your newsletter so that's why I want you to do one and then you could come up with this podcast we'll talk about all the things about your newsletter yeah

[01:26:21] yeah yeah no it's definitely I've been thinking a lot of things I think I emailed you about a podcast I'm like I I feel like I should be doing more things I kind of just got I also just like when I get in a situation where things

[01:26:34] like I got in a situation a couple of my books did well and a combination of consulting and speaking and like some of the book stuff I was just like making a good living and just like really like able to take a lot of vacation and stuff

[01:26:47] and I was really kind of phoning it in a bit and now I'm like well maybe I should work harder or do more stuff we'll see yeah or again try to try to do more of the stuff you enjoy and then and there's there's so many different ways

[01:27:01] to monetize things now like I mentioned about chess with Twitch or we had on this couple that they're obsessed with dinosaurs and now they make a living from a YouTube channel about dinosaurs or we had on someone recently who really is good at buying small businesses

[01:27:17] so she made a newsletter and courses about buying small businesses and she's killing it so well I think actually one newsletter post I'd like to write is analyzing this very question because when you say this like my data analysis brain is is skeptical

[01:27:34] in the sense that I just think you're getting such a selected sample of like the people who succeed in this are the only ones you're seeing and I just have no idea what the numbers are of someone who goes all in

[01:27:44] and I would be very interested in seeing that I believe you're right but but two and there's no way to really know maybe there is a way to know and that would be great to find out but two things have happened though one is the platforms

[01:27:59] by which you can monetize knowledge has increased so it used to be just let's say books and three television stations so there were six publishers and three television stations and that was the only way to monetize something and it may be infomercials also and that was it

[01:28:19] and this was as recently as like the 90s or the OOs now there's like a hundred different platforms and ways to monetize things so that number has increased and then I just see from the inside like in the chess world people I knew who were not good players

[01:28:36] but for years had like good decent YouTube channels and they just loved it now they're actually like making a living and they will for the rest of their lives because they have the right number of subscribers and I just saw that happen internally

[01:28:49] and so I know people who tried and failed but they also didn't really try hard enough so again I don't know what trying and failing means sometimes you try and you're not that good at it and you don't enjoy it so you don't and you don't like

[01:29:02] having a small audience for a while so you give up so it's hard to say it's hard to really get data on that but I saw how that industry grew from the ground up I do agree with you that you know persistence goes a long way

[01:29:15] if you go out you know people I know who are painters and they you know they were broke until they're like late 30s like making no money but kept at it kept at it kept at it kept at it then they get their big break it's a combination

[01:29:30] you got to just keep putting work into the world to allow your break you know allow the break to happen and then once you get that break you got to just like capitalize on it like crazy yeah and I think if you're willing to do that

[01:29:42] the odds are probably are pretty good even on something a seemingly long shot as like uh paint like a painter I think there are some things where it's just like the odds are just too far against you like being an actor actress in Hollywood or something like that

[01:29:57] but I think like you could be really persistent and you know keep going for it and do everything right and I just think the odds are just so low that yeah I think that's right but you know also you have to be able to withstand backlash so when

[01:30:12] whenever you monetize something some people are gonna hate you for it some people who loved you quote unquote are now gonna hate you no matter what as soon as you turn on every switch to make money or any switch to make money

[01:30:23] some people will hate that you did that like if you take if you didn't have ads on your podcast and now you have ads there will be a a group of people who will hate you because now you have ads if you never were charging for something

[01:30:36] and now you're charging for something there's a group of people who will hate you and say you sold out and you feel really bad that these people hate you because you thought they loved you but you confused their love for real love and I'm just

[01:30:48] I'm more talking to myself that I was always very disappointed at the people who would be disappointed in me whenever I charged for something and I felt guilty about it but over time you deal with it I just think in general like as a creative person

[01:31:05] you have to be really you have to like almost lean into to the haters you got to kind of get off on on the haters yeah which it comes like I remember like my first book came out and you know everyone loved it everyone's like this great

[01:31:18] great great second book like yeah again some people are expecting it to be like my first book then they're just like you know I got attacked and initially I was like I don't know how I'm gonna deal with a bad review

[01:31:28] but then like you just kind of lean into it and you're like it's kind of funny that they like what they attack you for too and you're just like you start laughing it off and then like that kind of energizes you

[01:31:38] and you're like well now I don't care because I can handle like someone like one person just said that I'm like the most self-absorbed person they've ever seen or something and I'm like yeah I can to be fair I am probably pretty cool I am

[01:31:51] I can be a pretty self-absorbed so they did kind of nail me so I'm like I just always kind of funny like that they thought that and like particularly when you get someone like a bad review from someone who's like very like by the book and like

[01:32:06] you know plays by the rules and more like you know presentable and official and stuff and they like hammer you then I kind of get off on that like you know I feel like it's kind of cool that I don't really care about that that's a good attribute

[01:32:17] like yeah I used to think I didn't care but you know I've been doing this you know I've been writing or doing things for the public or either podcast or going on TV or writing since about 2002 maybe even a little earlier so 20 over 20 years

[01:32:33] and every time there's a backlash it gets more and more heightened so at first it's just one person wrote me and said oh you know you ugly Jew what's up like I would get offended that was like in 2003 then that stopped offending me but then it just gets

[01:32:54] the hate the trolls or haters keep upping the ante every few years and at some point they find your buttons and it does get a little painful yeah well it's just interesting what your button is so like you know if someone says like

[01:33:09] my teeth are yellow or yeah you're ugly or whatever I'm just like yeah okay fine like I'll care like it doesn't really bother me but like if they have like if they say like he's a pretty good data analyst or something like that

[01:33:24] that would just like drive me insane like that pretty good yeah no I somebody told me I don't know that it's true that I think it was like Chevy Chase punched like Steve Martin in the face or something there again it's huge fight and someone said what happened

[01:33:39] and it was that Chevy Chase had uh Steve Martin said to Chevy Chase that he's a pretty good comedian yeah like you're pretty good you're you're a pretty good comedian and like if he had said you're the worst comedian I've ever heard

[01:33:52] you'd be like oh he's just in a bad mood or he's just jealous or whatever but like pretty good is like fuck he like looked at me closely and concluded that I was pretty good and that that kind of like uh

[01:34:03] can uh I think I can relate to that like if that would I think that was a lot more than someone really attacked me I think that was on the set of SNL when that happened wasn't yeah I'm not sure if it was Steve Martin

[01:34:13] it might have been Bill Murray I'm not sure yeah it might have been yeah but I forget like all all those guys had big personalities but uh yeah similarly I got a review on one of my books it was one out of five stars

[01:34:26] and they're like this is the most unintentionally like hilarious book of the year and like it reads like a set like a parody of a Ted talk or something and like that didn't bother me at all if it was like three stars or four stars

[01:34:39] like that would have really driven me three stars are the worst yeah like yeah it's pretty good you know not quite at the level of an Adam Grant or like this or that but like the worst book I've ever read I'm just like yeah that's kind of fun

[01:34:50] like that didn't bother me at all it'd be interesting to study what makes the Adam Grants of the world because I feel like there are some writers who have this very sort of narrative but academic style that do get blessed by the media and become larger than life

[01:35:07] when okay I love Adam Grant's stuff he's been on this podcast a billion times but I'm just curious like Adam Grant Malcolm Gladwell some other people all their stuff's good but just there's also a lot of good stuff out there that never gets noticed

[01:35:24] I'm just curious what makes the difference is it the academic credentials I think Adam I think Adam well Malcolm Gladwell doesn't have that academic credentials I think Adam Adam Grant has a combination of a real talent I think his storytelling is great

[01:35:37] and I think he's really really hard working like he is you talk about the consistency that I struggle with like he's tweeting and he has a new thing every day so consistent it's hard to keep that up though like I did that for 20 years

[01:35:53] and I just can't do it anymore I'm too old yeah yeah I think he has he's got a real talent I think he's just got incredible work ethic and discipline and consistency and then yeah there is something probably like he is presentable to the world

[01:36:09] in some way that people like or something I think that's what you're getting at like yeah that he's blessed like that people are happy for him to be like the next Malcolm Gladwell or something in a way that some other people wouldn't get that same blessing yeah

[01:36:26] it's interesting see lots of interesting data out there so so Seth I always love talking to you I'm actually experiencing severe COVID related pain at the moment and so I think I have to go unfortunately but come on seriously come on the podcast anytime you find out

[01:36:45] any interesting data at all no pressure no stress we don't even have to schedule you could just call us up and you come on the next day and uh happy to have you on anytime and always interesting stuff and meanwhile what's it why NBA players get picked

[01:37:05] is that what who make no who makes the NBA oh who makes the NBA yeah it was such a fun read because I like I like having these questions answered and and you don't you don't realize you like having them answered until you read what the questions are

[01:37:21] like let me actually was your list of well I'm going to read the list of questions in the when I do the intro that you mentioned in your intro but great book once again and and and thanks again for coming on the podcast always fun James

[01:37:36] thanks for having me thanks Seth