1 00:00:02,240 --> 00:00:06,800 Speaker 1: This is Masters in Business with Barry Ridholts on Boomberg Radio. 2 00:00:07,080 --> 00:00:09,879 Speaker 1: This week on the podcast, I have an extra special guest. 3 00:00:10,080 --> 00:00:12,680 Speaker 1: His name is Ben Cohen, and if that name silence 4 00:00:12,680 --> 00:00:16,800 Speaker 1: slightly familiar. He is the sports reporter covering the NBA 5 00:00:17,040 --> 00:00:19,279 Speaker 1: for the Wall Street Journal and the author of a 6 00:00:19,320 --> 00:00:22,480 Speaker 1: new book, The Hot Hand, The Mystery and Science of Streaks. 7 00:00:23,040 --> 00:00:28,240 Speaker 1: If you're interested in things like statistics and analytics of sports, 8 00:00:28,760 --> 00:00:33,960 Speaker 1: how the bastball game is changing, who is driving these changes, 9 00:00:34,120 --> 00:00:38,080 Speaker 1: what is happening in the world of sports, and why 10 00:00:38,120 --> 00:00:41,880 Speaker 1: the old days of just hiring a superstar and hoping 11 00:00:41,920 --> 00:00:45,120 Speaker 1: he can drag a team over over the line is 12 00:00:45,120 --> 00:00:47,839 Speaker 1: pretty much over. I really found his book to be 13 00:00:47,920 --> 00:00:51,160 Speaker 1: quite fascinating, and I think it's something that if you're 14 00:00:51,159 --> 00:00:53,880 Speaker 1: either a math or a sports geek, you're gonna find 15 00:00:53,920 --> 00:00:58,480 Speaker 1: really intriguing. So, with no further ado, my conversation with 16 00:00:58,560 --> 00:01:04,160 Speaker 1: Ben Cohn. This is Master's in Business with Barry Ridholts 17 00:01:04,200 --> 00:01:08,600 Speaker 1: on Bloomberg Radio. My special guest this week is Ben Cohen. 18 00:01:09,000 --> 00:01:11,640 Speaker 1: He is a reporter for the Wall Street Journal, where 19 00:01:11,640 --> 00:01:15,080 Speaker 1: he was the first person to exclusively cover the NBA 20 00:01:15,240 --> 00:01:19,919 Speaker 1: nationally for the Journal. In he was named a News 21 00:01:20,000 --> 00:01:23,480 Speaker 1: Media Alliance Rising Star. He has a new book out 22 00:01:23,600 --> 00:01:27,200 Speaker 1: and it's called The Hot Hands, The Mystery and Science 23 00:01:27,280 --> 00:01:31,240 Speaker 1: of Streaks. Ben Cowen, Welcome to Bloomberg. Thank you for 24 00:01:31,280 --> 00:01:33,000 Speaker 1: having me. It's a real pleasure to be on the show. 25 00:01:33,040 --> 00:01:35,319 Speaker 1: Because so much of this book is actually based on 26 00:01:35,480 --> 00:01:37,840 Speaker 1: past episodes of your show, so it treats for me. 27 00:01:38,200 --> 00:01:40,559 Speaker 1: I have to tell I have to reveal this. I'm 28 00:01:40,600 --> 00:01:44,280 Speaker 1: reading the book on vacation in Puerto Rico, and because 29 00:01:44,319 --> 00:01:49,240 Speaker 1: I'm an information junkie, I go to the sources and acknowledgements. 30 00:01:49,240 --> 00:01:52,960 Speaker 1: At the end, nobody reads that, and lo and behold, 31 00:01:53,040 --> 00:01:55,640 Speaker 1: there's my name and masters in business because of the 32 00:01:55,680 --> 00:01:59,480 Speaker 1: Tom Gilovich um reference. But what I thought was so 33 00:01:59,560 --> 00:02:02,160 Speaker 1: hilarious this was as I'm reading the book, I'm like, 34 00:02:02,400 --> 00:02:05,840 Speaker 1: guest Guest had him, had him. It's just cracked. Oh 35 00:02:05,920 --> 00:02:08,000 Speaker 1: that's an interesting name. I should get him. It was 36 00:02:08,040 --> 00:02:11,280 Speaker 1: really fun going through all these people who I feel like, 37 00:02:11,840 --> 00:02:13,880 Speaker 1: you know, you spend ninety minutes or longer in a 38 00:02:13,960 --> 00:02:16,200 Speaker 1: room with someone, you kind of get to know them 39 00:02:16,200 --> 00:02:18,400 Speaker 1: a little bit. So let's get to know you a 40 00:02:18,440 --> 00:02:21,400 Speaker 1: little bit. You're an undergraded duke. How do you end 41 00:02:21,480 --> 00:02:24,639 Speaker 1: up at the Wall Street Journal. Bribery. Bribery is always 42 00:02:24,639 --> 00:02:26,960 Speaker 1: a good thing. Now, I I worked really hard at Duke. 43 00:02:27,000 --> 00:02:29,920 Speaker 1: I I've always known that I wanted to be a journalist, 44 00:02:29,960 --> 00:02:34,000 Speaker 1: and specifically a sports journalist. There it's a deeply uncool 45 00:02:34,080 --> 00:02:35,919 Speaker 1: thing to say, right, Like, there's some people who grow 46 00:02:36,000 --> 00:02:39,000 Speaker 1: up dreaming to be astronauts and flying to the moon. 47 00:02:39,120 --> 00:02:41,639 Speaker 1: And I wanted to like cover Rutgers for the Star 48 00:02:41,720 --> 00:02:44,280 Speaker 1: Ledger New Jersey, right. Um. So I went to Duke 49 00:02:44,400 --> 00:02:47,680 Speaker 1: like most kids who like sports in New Jersey, and 50 00:02:48,360 --> 00:02:51,280 Speaker 1: I was the sports editor of the Chronicle, which was 51 00:02:51,680 --> 00:02:54,440 Speaker 1: the student newspaper at Duke. And and and a Duke that's 52 00:02:54,440 --> 00:02:56,840 Speaker 1: a real position. It's not like most schools. It's it's 53 00:02:56,840 --> 00:02:59,440 Speaker 1: a real position. And and the paper itself is a 54 00:02:59,480 --> 00:03:02,000 Speaker 1: real newspaper. I mean it's a daily paper. I I 55 00:03:02,120 --> 00:03:05,160 Speaker 1: definitely spent more time in the newspaper office than I 56 00:03:05,160 --> 00:03:07,600 Speaker 1: did in any classroom. I mean we were working the 57 00:03:07,639 --> 00:03:10,400 Speaker 1: top editors of the paper. Their work like sixty seventy 58 00:03:10,440 --> 00:03:13,200 Speaker 1: hours a week. It's a crazy job. And so um, 59 00:03:13,240 --> 00:03:15,600 Speaker 1: when you're covering Duke basketball, you're really competing with like 60 00:03:15,680 --> 00:03:19,120 Speaker 1: everybody on the planet, right um. And so that really 61 00:03:19,120 --> 00:03:22,440 Speaker 1: gave me great grounding, and UM, I got lucky a 62 00:03:22,440 --> 00:03:24,880 Speaker 1: few times along the way with some internships and some 63 00:03:24,960 --> 00:03:28,480 Speaker 1: other opportunities, and um, when I graduated, a couple of 64 00:03:28,480 --> 00:03:32,480 Speaker 1: weeks before graduation, the journal was looking for a sports intern. 65 00:03:32,560 --> 00:03:34,840 Speaker 1: They had just started a sports page and the person 66 00:03:34,880 --> 00:03:36,960 Speaker 1: they had hired to be the intern had taken a 67 00:03:37,040 --> 00:03:40,680 Speaker 1: job elsewhere, And so literally two weeks before graduation, the 68 00:03:40,720 --> 00:03:42,960 Speaker 1: sports editor of the paper emailed me. We had talked 69 00:03:42,960 --> 00:03:45,400 Speaker 1: in the past about a potential internship, and he offered 70 00:03:45,440 --> 00:03:48,200 Speaker 1: me an internship, and I kind of kept my foot 71 00:03:48,240 --> 00:03:51,040 Speaker 1: in the door and didn't let it close them and 72 00:03:51,080 --> 00:03:53,520 Speaker 1: didn't let them close it on me. And I've sort 73 00:03:53,520 --> 00:03:57,000 Speaker 1: of been there ever since. The role you now have 74 00:03:57,880 --> 00:04:01,040 Speaker 1: is NBA reporter for the Journal. That was not a 75 00:04:01,120 --> 00:04:03,240 Speaker 1: role before you got there. It was it. We did 76 00:04:03,240 --> 00:04:06,120 Speaker 1: not really have any rules in sports before I got there. 77 00:04:06,600 --> 00:04:09,400 Speaker 1: We started a sports page around the same time that 78 00:04:09,520 --> 00:04:12,040 Speaker 1: I was hired. So two thousand nine, Murdoch buys the 79 00:04:12,080 --> 00:04:14,400 Speaker 1: paper in like oh seven, and we get that kid 80 00:04:14,440 --> 00:04:16,960 Speaker 1: Cohen and here to start a sports page. Fort Rupert 81 00:04:17,000 --> 00:04:19,440 Speaker 1: and I go way back, and uh so, for the 82 00:04:19,480 --> 00:04:21,080 Speaker 1: first few years I was at the Journal, I covered 83 00:04:21,120 --> 00:04:25,640 Speaker 1: college sports, and we didn't have a national full time 84 00:04:25,880 --> 00:04:29,239 Speaker 1: NBA reporter, And I still think one of the reasons 85 00:04:29,279 --> 00:04:31,159 Speaker 1: why I did get this job was that it was 86 00:04:31,200 --> 00:04:35,360 Speaker 1: like July and our sports editor, this brilliant guy named 87 00:04:35,400 --> 00:04:38,839 Speaker 1: Sam Walker, looked around and said, oh my god, Lebron 88 00:04:38,960 --> 00:04:40,800 Speaker 1: James is about to choose his next team, and we 89 00:04:40,839 --> 00:04:43,680 Speaker 1: don't have someone to write the story. And he sort 90 00:04:43,680 --> 00:04:45,400 Speaker 1: of pulled me into his office and said, I think 91 00:04:45,440 --> 00:04:48,520 Speaker 1: that you should cover the NBA for us. And I said, Sam, 92 00:04:48,560 --> 00:04:51,000 Speaker 1: you're just saying this because we you need someone to 93 00:04:51,040 --> 00:04:53,239 Speaker 1: write about Lebron going back to Cleveland and loan Behold, 94 00:04:53,279 --> 00:04:55,360 Speaker 1: the next day he goes back to Cleveland. I write 95 00:04:55,360 --> 00:04:57,680 Speaker 1: this story. But it turned out to be this incredible 96 00:04:57,680 --> 00:05:00,800 Speaker 1: stroke of fortune because at the time, the NBA was 97 00:05:00,839 --> 00:05:04,000 Speaker 1: about to enter this like real Golden Age. So I 98 00:05:04,360 --> 00:05:06,480 Speaker 1: still have never covered an NBA finals that the Golden 99 00:05:06,480 --> 00:05:08,800 Speaker 1: State Warriors were not playing in. So it's been five 100 00:05:08,880 --> 00:05:10,880 Speaker 1: years in a row. Perhaps this is the year. I 101 00:05:11,200 --> 00:05:13,000 Speaker 1: have a feeling that this will be the year that 102 00:05:13,040 --> 00:05:15,080 Speaker 1: the Warriors don't make the finals. So now let's talk 103 00:05:15,120 --> 00:05:18,680 Speaker 1: a little bit about how I first found you, which 104 00:05:18,880 --> 00:05:24,640 Speaker 1: was the article about Josh Miller and Adam said, Joe's 105 00:05:24,880 --> 00:05:28,599 Speaker 1: paper on the hot hand tell us what the hot 106 00:05:28,680 --> 00:05:32,120 Speaker 1: hand is. So the hot hand, there's really no singular definition, 107 00:05:32,160 --> 00:05:34,200 Speaker 1: but I like to think of it as when success 108 00:05:34,279 --> 00:05:37,640 Speaker 1: leads to more success. Now, in basketball, for example, the 109 00:05:37,680 --> 00:05:40,440 Speaker 1: hotting has always been studied through basketball, which is one 110 00:05:40,440 --> 00:05:42,520 Speaker 1: of the things I sort of found irresistible about the 111 00:05:42,520 --> 00:05:45,080 Speaker 1: whole phenomenon in basketball. It's when you make one shot 112 00:05:45,160 --> 00:05:47,200 Speaker 1: and then another shot, and then another shot, and you 113 00:05:47,240 --> 00:05:52,200 Speaker 1: feel more likely to make your next shot. He's on fire. 114 00:05:52,680 --> 00:05:56,479 Speaker 1: You're on fire, but it's not he's unconscious. But it's 115 00:05:56,480 --> 00:05:59,000 Speaker 1: really not just about basketball. I I think of this 116 00:05:59,080 --> 00:06:02,279 Speaker 1: as about human behavior. I think we are all familiar 117 00:06:02,320 --> 00:06:05,000 Speaker 1: with this feeling of the hot hand, and what I've 118 00:06:05,080 --> 00:06:07,279 Speaker 1: learned is that if we take advantage, it can really 119 00:06:07,440 --> 00:06:10,520 Speaker 1: change our lives. So this book really started with two 120 00:06:10,720 --> 00:06:15,000 Speaker 1: stories in the Wall Street Journal, in both calling it 121 00:06:15,080 --> 00:06:19,560 Speaker 1: to question this seminal classic paper about the hot hand. 122 00:06:19,640 --> 00:06:23,120 Speaker 1: One was by this team of Harvard undergraduates, so not 123 00:06:23,279 --> 00:06:26,120 Speaker 1: grad students or PhD students or professors, but kids in 124 00:06:26,160 --> 00:06:29,600 Speaker 1: their college dorm. And one was by Josh Miller and 125 00:06:29,640 --> 00:06:32,040 Speaker 1: Adam san Hero, who who did this thing where they 126 00:06:32,080 --> 00:06:35,119 Speaker 1: looked at this very old problem in a new way 127 00:06:35,200 --> 00:06:37,880 Speaker 1: and they found something that nobody had seen before. And 128 00:06:38,120 --> 00:06:40,159 Speaker 1: usually what happens, I have to say after I spend 129 00:06:40,160 --> 00:06:42,360 Speaker 1: a lot of time thinking about a story and writing 130 00:06:42,360 --> 00:06:44,400 Speaker 1: a story, is that I don't want to think about 131 00:06:44,440 --> 00:06:47,560 Speaker 1: that story anymore. I'm sick of it. The opposite really 132 00:06:47,560 --> 00:06:49,359 Speaker 1: happened here. I couldn't get the hot Hand out of 133 00:06:49,400 --> 00:06:51,000 Speaker 1: my head, and I just thought that there was something 134 00:06:51,279 --> 00:06:53,720 Speaker 1: bigger here that I wanted to explore. And that's how 135 00:06:53,839 --> 00:06:55,640 Speaker 1: you know, I end up spending three years writing a 136 00:06:55,680 --> 00:06:58,120 Speaker 1: book about it. So let's let's step back a second, 137 00:06:58,320 --> 00:07:03,839 Speaker 1: and um, Tom Gilovich is now professor Cornell. At the time, 138 00:07:03,880 --> 00:07:06,880 Speaker 1: I believe was at Stanford on the ground or Berkeley 139 00:07:06,880 --> 00:07:08,680 Speaker 1: on the ground. There were grad students. Tom Gilovich and 140 00:07:08,720 --> 00:07:12,480 Speaker 1: Bob Balone were grad students at Stanford, and a professor 141 00:07:12,600 --> 00:07:16,360 Speaker 1: Tversky the Great Amostversek was a brilliant professor there, and 142 00:07:16,680 --> 00:07:18,960 Speaker 1: they looked at the hot Hand because they thought that 143 00:07:19,000 --> 00:07:22,680 Speaker 1: it was this beautiful way to illustrate this phenomenon of 144 00:07:22,760 --> 00:07:25,800 Speaker 1: seeing patterns in randomness. And it still is right. Like 145 00:07:25,840 --> 00:07:27,680 Speaker 1: I do want to stress that, like I find that 146 00:07:27,720 --> 00:07:30,840 Speaker 1: paper hugely admirable. It's a brilliant paper, right, because it 147 00:07:30,960 --> 00:07:33,840 Speaker 1: uses this thing that we all know, this very accessible, 148 00:07:33,880 --> 00:07:37,920 Speaker 1: digestible example of a cognitive bias. Um. They end up 149 00:07:37,920 --> 00:07:43,000 Speaker 1: publishing this paper. It's in the canon of behavioral economics. Right, 150 00:07:43,040 --> 00:07:45,520 Speaker 1: it's one of the most famous papers ever written. It's 151 00:07:45,520 --> 00:07:48,760 Speaker 1: really easy to understand, like, there's nothing really obtuse about it. 152 00:07:48,760 --> 00:07:51,800 Speaker 1: It's a great paper. It really holds up um with 153 00:07:51,880 --> 00:07:56,760 Speaker 1: one small exception, sure if yeah, exactly, But Um, something 154 00:07:57,200 --> 00:07:59,680 Speaker 1: amazing happened when this paper came out, which is that 155 00:07:59,720 --> 00:08:03,320 Speaker 1: it was so unbelievable that people just simply refused to 156 00:08:03,400 --> 00:08:05,600 Speaker 1: believe it. We had all felt the hot hand and 157 00:08:05,640 --> 00:08:07,440 Speaker 1: seeing the hot hand, and now these professors were coming 158 00:08:07,440 --> 00:08:10,200 Speaker 1: along telling us there was no such thing, and that 159 00:08:10,320 --> 00:08:12,080 Speaker 1: was really hard for us to wrap our minds around, 160 00:08:12,080 --> 00:08:13,840 Speaker 1: in the same way that it's very hard for us 161 00:08:13,880 --> 00:08:16,600 Speaker 1: to wrap our minds around randomness. So I love the 162 00:08:16,640 --> 00:08:20,000 Speaker 1: image of red or back cigar unlit cigar kind of 163 00:08:20,320 --> 00:08:22,520 Speaker 1: hanging out of his mouth. I don't care what these 164 00:08:22,520 --> 00:08:24,640 Speaker 1: professors say. Of course, it's a hot hand, and there's 165 00:08:24,640 --> 00:08:26,960 Speaker 1: nothing that could have delighted professors more. Right, like this 166 00:08:27,640 --> 00:08:30,239 Speaker 1: just believing in the hot hand doesn't make it anymore true. 167 00:08:30,320 --> 00:08:33,120 Speaker 1: And Amos Tversky used to love to tell this story 168 00:08:33,679 --> 00:08:35,560 Speaker 1: when he taught the Hot hand. He would tell the 169 00:08:35,600 --> 00:08:38,200 Speaker 1: story of right hour Back because he loved the Boston Celtics, 170 00:08:38,200 --> 00:08:41,480 Speaker 1: And like, what better way to illustrate this idea that 171 00:08:41,520 --> 00:08:44,520 Speaker 1: people refused to believe than Red hour back saying that 172 00:08:44,559 --> 00:08:46,960 Speaker 1: it was all a bunch of blowney. And as much 173 00:08:47,040 --> 00:08:53,200 Speaker 1: as the conclusion maybe mathematically inaccurate, the underlying premise that 174 00:08:53,480 --> 00:08:56,400 Speaker 1: people see patterns where there are none, that we're all 175 00:08:56,440 --> 00:09:00,280 Speaker 1: subject to our cognitive biases, that still holds up. And 176 00:09:00,280 --> 00:09:03,160 Speaker 1: that's still a key part of that paper completely, uh. 177 00:09:03,160 --> 00:09:06,640 Speaker 1: And not only that, even if you do believe in 178 00:09:06,679 --> 00:09:09,080 Speaker 1: the hot hand, like I don't think it is this 179 00:09:09,640 --> 00:09:13,600 Speaker 1: exaggerated fireball of our imagination, right like you can miss 180 00:09:13,679 --> 00:09:16,640 Speaker 1: when you feel hot. And also like, there are plenty 181 00:09:16,679 --> 00:09:19,959 Speaker 1: of times when you are in an environment that does 182 00:09:20,000 --> 00:09:22,480 Speaker 1: not allow for a hot hand, and believing in the 183 00:09:22,520 --> 00:09:26,959 Speaker 1: hot hand can be disastrous, costly, it could really backfire 184 00:09:27,040 --> 00:09:29,800 Speaker 1: and burn you. And so I do think, um, that 185 00:09:29,840 --> 00:09:32,680 Speaker 1: paper is still really important and we should all read it. 186 00:09:32,720 --> 00:09:35,080 Speaker 1: I mean, part of the whole fun of This concept, 187 00:09:35,120 --> 00:09:37,480 Speaker 1: I think is figuring out what you think about it 188 00:09:37,559 --> 00:09:40,040 Speaker 1: for yourself, right, and toying around with the idea and 189 00:09:40,040 --> 00:09:42,480 Speaker 1: seeing where you land. And and as a long suffering 190 00:09:42,559 --> 00:09:45,839 Speaker 1: Knicks fan, going back to the John Stark's era, where 191 00:09:45,920 --> 00:09:49,800 Speaker 1: he would just you know, a streaky player, and whether 192 00:09:49,840 --> 00:09:52,880 Speaker 1: the shots were sinking or not, he would still reel 193 00:09:52,960 --> 00:09:55,120 Speaker 1: off seven, eight nine shots in a row. Whether they 194 00:09:55,120 --> 00:09:58,200 Speaker 1: fell or not didn't matter. He would when he felt it, 195 00:09:58,559 --> 00:10:02,640 Speaker 1: he heave did regardless of outcome. The Knicks are familiar 196 00:10:02,679 --> 00:10:05,360 Speaker 1: with streaks, They're just not the kind that Knicks fans 197 00:10:05,400 --> 00:10:09,560 Speaker 1: actually would enjoy, to say the least. So what I 198 00:10:09,600 --> 00:10:13,880 Speaker 1: found so intriguing about the original paper about the hot hand, 199 00:10:14,520 --> 00:10:20,600 Speaker 1: it was incredibly controversial. What was behind all the pushback? Well, 200 00:10:20,679 --> 00:10:23,800 Speaker 1: it defides something that we all thought to be true, right, 201 00:10:23,880 --> 00:10:26,880 Speaker 1: and we are not very good when people tell us 202 00:10:26,920 --> 00:10:31,199 Speaker 1: something we are convinced of isn't true. So my one 203 00:10:31,200 --> 00:10:35,240 Speaker 1: of my favorite examples of how easily we're fooled is 204 00:10:35,840 --> 00:10:37,720 Speaker 1: you give the example in the book, but we've all 205 00:10:37,760 --> 00:10:43,719 Speaker 1: seen this from personal life experience. A professor assigns a 206 00:10:43,840 --> 00:10:47,000 Speaker 1: class flip a coin a hundred times and write it 207 00:10:47,000 --> 00:10:49,200 Speaker 1: down and I want some of you to do it, 208 00:10:49,280 --> 00:10:53,120 Speaker 1: and some of you make it up and immediately identifies 209 00:10:53,720 --> 00:10:56,560 Speaker 1: these are real, these are fake, and the classes always 210 00:10:56,559 --> 00:10:59,400 Speaker 1: astonished by this. What does that have to do with 211 00:10:59,440 --> 00:11:03,800 Speaker 1: streaking this and our tendency to see patterns where none 212 00:11:03,800 --> 00:11:06,480 Speaker 1: are there? So this is an incredible statistician at Columbia 213 00:11:06,559 --> 00:11:10,280 Speaker 1: named Andrew Gilman who runs this very popular blog which 214 00:11:10,320 --> 00:11:14,559 Speaker 1: sounds kind of like an oxymoron, like a popular statistics 215 00:11:14,559 --> 00:11:17,000 Speaker 1: blog for a little wonky, yes, but but it's a 216 00:11:17,000 --> 00:11:20,120 Speaker 1: brilliant website. And um, you know, I talked to Andrew 217 00:11:20,080 --> 00:11:23,360 Speaker 1: Gelman about this and what he told me about how 218 00:11:23,679 --> 00:11:26,520 Speaker 1: he is able to tell his classroom to uh. He 219 00:11:26,559 --> 00:11:29,200 Speaker 1: splits his classroom into two and he tells them like, 220 00:11:29,440 --> 00:11:31,760 Speaker 1: you know, one group flip a coin, the other group, 221 00:11:31,800 --> 00:11:33,960 Speaker 1: imagine what it looks like when you flip a coin, 222 00:11:34,040 --> 00:11:37,200 Speaker 1: and then right the sequences on a chalkboard, and I 223 00:11:37,200 --> 00:11:39,120 Speaker 1: will walk in and I will be able to tell 224 00:11:39,160 --> 00:11:41,360 Speaker 1: you which one is real and which one is fake. 225 00:11:41,679 --> 00:11:44,560 Speaker 1: And so he leaves the classroom and he does essentially 226 00:11:44,600 --> 00:11:47,520 Speaker 1: this magic trick first for a statistician. Right, he comes 227 00:11:47,520 --> 00:11:50,120 Speaker 1: in and he always knows, and it's because the real 228 00:11:50,240 --> 00:11:53,000 Speaker 1: one is the one that looks fake. It has a 229 00:11:53,120 --> 00:11:55,680 Speaker 1: run of stp of heads in a row that you're 230 00:11:55,679 --> 00:11:58,800 Speaker 1: not comfortable. You'll do heads tails, heads, heads tails, but 231 00:11:58,880 --> 00:12:00,840 Speaker 1: you won't do seven heads in a row. That just 232 00:12:00,880 --> 00:12:03,680 Speaker 1: seems wrong. But we all know sometimes when you flip 233 00:12:03,720 --> 00:12:05,880 Speaker 1: a coin, you get seven tales in a row, right, 234 00:12:06,120 --> 00:12:08,400 Speaker 1: But you would never do that if you were imagining 235 00:12:08,679 --> 00:12:12,320 Speaker 1: what a string of coin flips actually looks like. And 236 00:12:12,320 --> 00:12:14,960 Speaker 1: now you've ruined that trick for him in his first class, 237 00:12:14,960 --> 00:12:17,400 Speaker 1: and well hopefully everybody at Columbia will read this book 238 00:12:17,400 --> 00:12:19,280 Speaker 1: so he will not be able to pull off that 239 00:12:19,320 --> 00:12:22,679 Speaker 1: trick anymore. Let's talk about the Miller sanjor Joe paper 240 00:12:23,360 --> 00:12:28,040 Speaker 1: on why the Hot Hands Is Real first, and I 241 00:12:28,080 --> 00:12:32,120 Speaker 1: think you may have been the first popular press to 242 00:12:32,280 --> 00:12:35,959 Speaker 1: cover that, because that's how Not only is that how 243 00:12:36,040 --> 00:12:38,280 Speaker 1: I found you, but when I was preparing for the 244 00:12:38,280 --> 00:12:42,839 Speaker 1: interview with Joshua Miller and reading all the all the coverage, 245 00:12:43,320 --> 00:12:45,040 Speaker 1: yours was the piece I found them, like, oh, this 246 00:12:45,080 --> 00:12:47,600 Speaker 1: does a really nice job on the reason I remember 247 00:12:47,640 --> 00:12:49,640 Speaker 1: this is not because I'm bragging, but because I was 248 00:12:49,760 --> 00:12:52,360 Speaker 1: terrified when that story came out. It was very nerve 249 00:12:52,440 --> 00:12:56,280 Speaker 1: racking because uh, the math had been rubber stamped by 250 00:12:56,520 --> 00:12:59,880 Speaker 1: mathematicians by Andrew Gellman himself, like the math accurate. However, 251 00:13:00,360 --> 00:13:03,760 Speaker 1: the journal is really not in the position to be 252 00:13:03,880 --> 00:13:07,600 Speaker 1: writing full stories about pre prints, right, papers that have 253 00:13:07,720 --> 00:13:11,880 Speaker 1: not been more published by like journals that you can trust. 254 00:13:11,960 --> 00:13:14,960 Speaker 1: And so this paper was floating around the internet. It 255 00:13:14,960 --> 00:13:18,040 Speaker 1: had been uploaded to ssr N, and Andrew Galman had 256 00:13:18,040 --> 00:13:20,199 Speaker 1: written a blog post about it, and people were talking 257 00:13:20,240 --> 00:13:23,480 Speaker 1: about it. But like if if this paper had been 258 00:13:23,520 --> 00:13:26,559 Speaker 1: published in Econometrico, which it has been, now, it's very 259 00:13:26,559 --> 00:13:28,160 Speaker 1: easy for the Wall Street Journal to write a story 260 00:13:28,160 --> 00:13:31,679 Speaker 1: about that, right, But when it hasn't, suddenly it's it's 261 00:13:31,720 --> 00:13:35,280 Speaker 1: just these two guys, these two young American economists in 262 00:13:35,320 --> 00:13:39,360 Speaker 1: Europe and a statistician with a blog saying that it's right. 263 00:13:39,440 --> 00:13:41,480 Speaker 1: Is that enough for the Wall Street Journal to write 264 00:13:41,520 --> 00:13:44,000 Speaker 1: a story about that? It was? We decided that it was, 265 00:13:44,040 --> 00:13:45,800 Speaker 1: So let me tell you why you were right. Because 266 00:13:45,840 --> 00:13:50,680 Speaker 1: the worst case scenario is that Econometrical does the math 267 00:13:50,720 --> 00:13:54,080 Speaker 1: and says this is wrong. But at the time, not 268 00:13:54,240 --> 00:13:58,240 Speaker 1: only is this a really interesting thesis that identifies a 269 00:13:58,320 --> 00:14:03,600 Speaker 1: fundamental floor flaw in the traverse ky Gilovich paper but 270 00:14:04,160 --> 00:14:08,840 Speaker 1: it's really a whole new area of analytics for data sets. 271 00:14:08,880 --> 00:14:12,040 Speaker 1: It's not just the hot hands. These guys figured out 272 00:14:12,080 --> 00:14:16,240 Speaker 1: something really really interesting and lots of people were buzzing 273 00:14:16,240 --> 00:14:20,320 Speaker 1: about it. And it's not just a blogger, it's Andrew 274 00:14:20,360 --> 00:14:25,840 Speaker 1: Gilman of Columbia, who is a widely respected mathematician and statisticians. 275 00:14:25,960 --> 00:14:29,120 Speaker 1: Is their peer review, right, he's peer review before peer review. 276 00:14:29,280 --> 00:14:31,640 Speaker 1: So so I don't think you were that far out 277 00:14:31,680 --> 00:14:34,040 Speaker 1: on a ledge. And the worst case scenario is some 278 00:14:34,160 --> 00:14:36,680 Speaker 1: of the smartest people in math would have gotten it 279 00:14:36,720 --> 00:14:38,600 Speaker 1: wrong also, and I have to say, the funny thing 280 00:14:38,640 --> 00:14:42,440 Speaker 1: about this is that I let alone, Josh and Adam 281 00:14:42,680 --> 00:14:45,640 Speaker 1: got the same reaction that Gilovich, Valon and Tversky did, 282 00:14:45,680 --> 00:14:47,560 Speaker 1: which is, there's no way this is true. Over the 283 00:14:47,560 --> 00:14:49,480 Speaker 1: course of thirty five years, that paper, which was so 284 00:14:49,560 --> 00:14:52,520 Speaker 1: counterintuitive at the time, became conventional wizard It was was 285 00:14:52,640 --> 00:14:54,240 Speaker 1: the way we thought about the hot hand, and so 286 00:14:54,280 --> 00:14:57,360 Speaker 1: now here was this paper threatening to overturn that result 287 00:14:57,640 --> 00:15:01,040 Speaker 1: in this uh strange mathematical that takes a lot of 288 00:15:01,120 --> 00:15:03,080 Speaker 1: thinking to write about, Like there was a reason that 289 00:15:03,120 --> 00:15:06,760 Speaker 1: nobody has seen this right. This this very subtle statistical 290 00:15:06,800 --> 00:15:09,760 Speaker 1: bias that some of the world's brightest statisticians had missed 291 00:15:09,760 --> 00:15:12,520 Speaker 1: for many years. It was this bias hiding in plain sight, 292 00:15:12,840 --> 00:15:14,760 Speaker 1: and if it had been obvious, we would have seen 293 00:15:14,800 --> 00:15:17,280 Speaker 1: it many years earlier. So let's talk about that bias, 294 00:15:17,280 --> 00:15:21,000 Speaker 1: because it is very intriguing, it's very trippy. It's also intriguing. 295 00:15:21,240 --> 00:15:25,000 Speaker 1: Explain why. So Normally, if you're gonna flip a coin, 296 00:15:25,840 --> 00:15:29,640 Speaker 1: hold the gambler's fallacy aside, every flip of that coin 297 00:15:29,720 --> 00:15:32,320 Speaker 1: should be fifty fifty heads or tails. But it's not. 298 00:15:32,480 --> 00:15:35,400 Speaker 1: But but you're not just flipping a coin, you're looking 299 00:15:35,440 --> 00:15:39,480 Speaker 1: at it after the fact ex post and and saying 300 00:15:40,200 --> 00:15:42,960 Speaker 1: of the flips that followed two heads in a row, 301 00:15:43,760 --> 00:15:47,200 Speaker 1: it's not fifty fifty. Explain why, well, I will say 302 00:15:47,280 --> 00:15:49,440 Speaker 1: the one thing I've learned in thinking about this book 303 00:15:49,440 --> 00:15:51,600 Speaker 1: and writing this book and talking about this book is 304 00:15:51,640 --> 00:15:54,400 Speaker 1: that I'm not great at talking about this part of 305 00:15:54,400 --> 00:15:56,800 Speaker 1: the book. It's very it's it's hard even for me, 306 00:15:56,960 --> 00:15:59,680 Speaker 1: as like the best thing I could do is like say, 307 00:15:59,680 --> 00:16:02,640 Speaker 1: actually go back and listen to your episode with Josh Miller, 308 00:16:02,720 --> 00:16:05,560 Speaker 1: because he does a better job of explaining it than anybody. 309 00:16:05,680 --> 00:16:07,240 Speaker 1: But what I will say is that it has to 310 00:16:07,280 --> 00:16:11,080 Speaker 1: do with um, with sequences, and and and sampling without 311 00:16:11,120 --> 00:16:14,960 Speaker 1: replacement right, and and figuring out um. When you look 312 00:16:15,000 --> 00:16:17,520 Speaker 1: at a sequence of even three coin flips, if you 313 00:16:17,560 --> 00:16:20,160 Speaker 1: look at the the average chance that you will get 314 00:16:20,160 --> 00:16:23,840 Speaker 1: a heads after the heads, it's not as our brains 315 00:16:23,840 --> 00:16:27,640 Speaker 1: are conditioned to believe, it's actually lower. It's it's biased 316 00:16:27,760 --> 00:16:30,680 Speaker 1: in a negative direction. So you start with the you 317 00:16:30,720 --> 00:16:33,200 Speaker 1: flip a coin a million times, and now you have 318 00:16:33,200 --> 00:16:35,720 Speaker 1: a data set. And if you pull out all of 319 00:16:35,760 --> 00:16:38,640 Speaker 1: the heads and heads in a row, you're not just 320 00:16:38,680 --> 00:16:41,160 Speaker 1: pulling out half the heads. You're pulling out more than 321 00:16:41,600 --> 00:16:45,240 Speaker 1: half the heads relative to what's left over. So what's 322 00:16:45,320 --> 00:16:48,080 Speaker 1: left over is going to be a little tail heavy. 323 00:16:48,200 --> 00:16:50,120 Speaker 1: Is that? Is that a fair way to describe it? Yes, 324 00:16:50,160 --> 00:16:52,360 Speaker 1: And then the next obvious question is like, well, what 325 00:16:52,400 --> 00:16:54,920 Speaker 1: does that mean for the hot hand? And really what 326 00:16:54,920 --> 00:16:57,600 Speaker 1: it means is that for many years, for thirty five 327 00:16:57,720 --> 00:17:00,560 Speaker 1: years to be precise, we thought that if a fifty 328 00:17:00,640 --> 00:17:04,240 Speaker 1: percent shooter was shooting when he had the hot hand, 329 00:17:04,240 --> 00:17:06,840 Speaker 1: when he felt like he couldn't miss, that was evidence 330 00:17:06,920 --> 00:17:09,560 Speaker 1: against the hot hand. Right, there was no difference. He 331 00:17:09,640 --> 00:17:11,760 Speaker 1: wasn't any more likely to make his next shot. What 332 00:17:11,840 --> 00:17:15,600 Speaker 1: it actually was was evidence for the hot hand all along, 333 00:17:15,640 --> 00:17:18,680 Speaker 1: because when you are shooting fifty and you take out 334 00:17:19,040 --> 00:17:21,920 Speaker 1: those heads and tails and you look at what happens 335 00:17:21,960 --> 00:17:27,000 Speaker 1: heads after heads, you should be shooting lower than like 336 00:17:27,119 --> 00:17:30,840 Speaker 1: roughly right. And I believe somewhere in either your book 337 00:17:30,920 --> 00:17:34,840 Speaker 1: or the Miller paper is the advantage of the hot 338 00:17:34,920 --> 00:17:37,840 Speaker 1: hand is something like yeah, I mean if you look 339 00:17:37,880 --> 00:17:40,440 Speaker 1: at the difference, like if you look at the difference 340 00:17:40,480 --> 00:17:43,439 Speaker 1: of what we thought to what we think now or 341 00:17:43,480 --> 00:17:47,000 Speaker 1: what some people think now, it's like twelve percentage points, 342 00:17:47,000 --> 00:17:49,840 Speaker 1: and the difference is huge, like in the n b A, 343 00:17:50,320 --> 00:17:53,800 Speaker 1: the difference between in the NBA, the difference of twelve 344 00:17:53,840 --> 00:17:56,840 Speaker 1: points is the difference between Steph Curry and a league 345 00:17:56,840 --> 00:18:00,359 Speaker 1: average shooter. So so we now, you know how reason 346 00:18:00,400 --> 00:18:03,280 Speaker 1: to think that, you know, not only can we believe 347 00:18:03,280 --> 00:18:04,760 Speaker 1: in the hot hand, but it actually might be a 348 00:18:04,760 --> 00:18:08,160 Speaker 1: pretty sizeable effect. Now you know this is I think 349 00:18:08,200 --> 00:18:11,119 Speaker 1: there are reasonable people on both sides of this debate, 350 00:18:11,160 --> 00:18:13,000 Speaker 1: and that is what was so intriguing to me is 351 00:18:13,040 --> 00:18:16,000 Speaker 1: that we have very smart people, brilliant minds, who have 352 00:18:16,040 --> 00:18:18,320 Speaker 1: been thinking about this for a very long time. And 353 00:18:18,680 --> 00:18:20,720 Speaker 1: you know, you could come out to to to thinking 354 00:18:20,720 --> 00:18:23,080 Speaker 1: about this in different ways, and I think we still are, 355 00:18:23,119 --> 00:18:25,720 Speaker 1: like I think we are still trying to think about 356 00:18:25,720 --> 00:18:28,600 Speaker 1: what we should think about the hot Hand. So I 357 00:18:28,760 --> 00:18:33,320 Speaker 1: spent a lot of intellectual energy thinking gil Vitch and Seversky, 358 00:18:33,400 --> 00:18:37,400 Speaker 1: we're right. And then when Josh and Adams paper came out, 359 00:18:37,720 --> 00:18:39,879 Speaker 1: I was skeptical. And then I read as much as 360 00:18:39,920 --> 00:18:43,760 Speaker 1: I could up until the formulas, which is incomprehensible, and 361 00:18:43,800 --> 00:18:45,760 Speaker 1: then had a conversation with him and then had him 362 00:18:45,760 --> 00:18:48,720 Speaker 1: on the show, and suddenly it's like, you know what, 363 00:18:49,320 --> 00:18:53,400 Speaker 1: he convinced me, The hot hand is reel. And now 364 00:18:53,640 --> 00:18:56,840 Speaker 1: that I've spent so much mental energy on this and 365 00:18:56,880 --> 00:19:01,280 Speaker 1: I'm committed to this at this point, my cognitive dissonances. 366 00:19:01,520 --> 00:19:03,119 Speaker 1: I don't want it's crazy, and I don't want to 367 00:19:03,200 --> 00:19:05,360 Speaker 1: I don't want to flip. I can't flip again. I'm 368 00:19:05,400 --> 00:19:07,760 Speaker 1: locked in. If you could prove that it's not real, 369 00:19:08,400 --> 00:19:10,520 Speaker 1: best of luck to you. But I'm tapped out of 370 00:19:10,520 --> 00:19:12,760 Speaker 1: the debate. While imagine writing a book about it. But 371 00:19:12,760 --> 00:19:14,919 Speaker 1: but but that was actually what was so intriguing to 372 00:19:14,920 --> 00:19:16,560 Speaker 1: me about all this, because you know, at the Wall 373 00:19:16,560 --> 00:19:19,399 Speaker 1: Street Journal, what I've learned is that every great story 374 00:19:19,520 --> 00:19:23,080 Speaker 1: needs tension, right, Tension is really what makes stories. And 375 00:19:23,240 --> 00:19:26,080 Speaker 1: I just couldn't believe how much tension there was in 376 00:19:26,080 --> 00:19:28,920 Speaker 1: this fight over an idea. Right here was something that 377 00:19:28,960 --> 00:19:31,199 Speaker 1: we all thought to be true, a belief, only to 378 00:19:31,240 --> 00:19:33,439 Speaker 1: be told that it wasn't, only to be told that 379 00:19:33,480 --> 00:19:36,080 Speaker 1: actually maybe it was, and that that was just so 380 00:19:36,200 --> 00:19:39,639 Speaker 1: irresistible to me. And so the narrative itself is great. 381 00:19:39,680 --> 00:19:41,480 Speaker 1: And then what I tried to do in this book 382 00:19:41,560 --> 00:19:44,760 Speaker 1: is apply the lessons of that narrative very widely, right, 383 00:19:44,800 --> 00:19:47,200 Speaker 1: because that's why these people have been studying the hot 384 00:19:47,240 --> 00:19:49,119 Speaker 1: hand for so long. It's not because they wanted to 385 00:19:49,200 --> 00:19:50,960 Speaker 1: argue about whether or not the hot hand is real. 386 00:19:51,000 --> 00:19:55,200 Speaker 1: It's because it has these implications far beyond academia, farther 387 00:19:55,320 --> 00:19:59,040 Speaker 1: beyond basketball, right, like they sort of apply everywhere. It's 388 00:19:59,080 --> 00:20:02,439 Speaker 1: quite fascinating. So I mentioned to you I read this 389 00:20:02,440 --> 00:20:04,760 Speaker 1: book on vacation. I plowed through it in a day 390 00:20:04,760 --> 00:20:07,879 Speaker 1: and a half. I really enjoyed it. It fits in 391 00:20:08,119 --> 00:20:12,879 Speaker 1: well in the sequence of sort of related to moneyball 392 00:20:12,960 --> 00:20:16,760 Speaker 1: and related to some other things that are about sports. 393 00:20:16,920 --> 00:20:21,480 Speaker 1: The first chapter of the Undoing Project about Darryl Moore. 394 00:20:22,119 --> 00:20:25,440 Speaker 1: So I gotta ask you some questions about the book, 395 00:20:25,440 --> 00:20:28,560 Speaker 1: because there's some really really interesting things in here. Please 396 00:20:28,600 --> 00:20:30,840 Speaker 1: And also you called it wonky beach reading, which I 397 00:20:30,840 --> 00:20:32,800 Speaker 1: think is the best description of the book I've heard 398 00:20:32,800 --> 00:20:34,880 Speaker 1: so far. It really tickles me to hear that. I mean, 399 00:20:35,000 --> 00:20:36,560 Speaker 1: that's what it was to me. I was sitting on 400 00:20:36,600 --> 00:20:39,359 Speaker 1: the beach. I'm like, this is good, wonky fun and 401 00:20:39,400 --> 00:20:40,800 Speaker 1: I wanted it to be. I wanted it to be 402 00:20:40,840 --> 00:20:45,240 Speaker 1: something that like anybody could read right, like you don't exactly, 403 00:20:45,280 --> 00:20:47,080 Speaker 1: and you could read it on a beach, which which 404 00:20:47,119 --> 00:20:49,560 Speaker 1: I love reading books on the beach. So so first 405 00:20:49,640 --> 00:20:52,360 Speaker 1: question is the first of all, I like the arc 406 00:20:52,480 --> 00:20:55,320 Speaker 1: that you tell. This is told as a story throughout 407 00:20:55,400 --> 00:20:59,240 Speaker 1: time where there's this belief and then uh, an academic 408 00:20:59,280 --> 00:21:03,359 Speaker 1: research channel olenges a belief, and then subsequent research challenges 409 00:21:03,440 --> 00:21:06,639 Speaker 1: the challenge. Why in the beginning did it seem like 410 00:21:06,680 --> 00:21:09,760 Speaker 1: they were the academics on one side and everybody else 411 00:21:09,800 --> 00:21:12,600 Speaker 1: on the other, Because the academics were the only people 412 00:21:12,640 --> 00:21:15,680 Speaker 1: who were saying that everybody else was wrong, right, um, 413 00:21:15,720 --> 00:21:17,760 Speaker 1: And you know that was the beauty of their paper 414 00:21:17,920 --> 00:21:21,640 Speaker 1: was that it challenged something that is so universal. There's 415 00:21:21,680 --> 00:21:24,119 Speaker 1: this fundamental belief in the hot hand. That's in the 416 00:21:24,119 --> 00:21:27,760 Speaker 1: original paper. They pulled basketball fans and NBA players and 417 00:21:27,840 --> 00:21:30,440 Speaker 1: like something like them said, of course that there is 418 00:21:30,480 --> 00:21:32,080 Speaker 1: such a thing as the hot hand, right, like if 419 00:21:32,119 --> 00:21:35,040 Speaker 1: you had asked me. The one time in my life 420 00:21:35,040 --> 00:21:38,639 Speaker 1: that I was not completely terrible at basketball was in 421 00:21:38,720 --> 00:21:41,119 Speaker 1: high school, and I scored more points in one quarter 422 00:21:41,200 --> 00:21:43,920 Speaker 1: of one game than I had in my entire career combined. 423 00:21:43,960 --> 00:21:46,840 Speaker 1: There was something magical about that day that I still 424 00:21:46,880 --> 00:21:50,119 Speaker 1: remember now, And it would never have even crossed my 425 00:21:50,200 --> 00:21:53,560 Speaker 1: mind that this thing didn't exist, because I thought that 426 00:21:53,640 --> 00:21:56,800 Speaker 1: I knew what I felt, and not until reading you know, 427 00:21:56,960 --> 00:22:00,280 Speaker 1: hundreds of papers over the course of like four deck aids, 428 00:22:00,320 --> 00:22:03,119 Speaker 1: that I realized that, like everything I thought I knew, 429 00:22:03,240 --> 00:22:06,240 Speaker 1: might be wrong. So so let's talk about some real 430 00:22:06,320 --> 00:22:10,320 Speaker 1: specific examples from the book that are fascinating. Uh, And 431 00:22:10,400 --> 00:22:14,800 Speaker 1: let's start with Spotify and Apple iTunes. Their random shuffle 432 00:22:15,560 --> 00:22:19,040 Speaker 1: is much better when it's less random. Explain that that's right. 433 00:22:19,080 --> 00:22:22,240 Speaker 1: So a few years ago Spotify had this problem, which 434 00:22:22,280 --> 00:22:24,560 Speaker 1: is that they kept hearing from users that the shuffle 435 00:22:24,640 --> 00:22:27,760 Speaker 1: function was broken. The problem is that it wasn't actually 436 00:22:27,800 --> 00:22:31,760 Speaker 1: shuffling their music, so sometimes you would hear the same 437 00:22:31,840 --> 00:22:33,960 Speaker 1: artist twice in a row, or you would hear the 438 00:22:34,000 --> 00:22:37,200 Speaker 1: same song twice in a row sometimes, And people got 439 00:22:37,240 --> 00:22:40,240 Speaker 1: so mad about this that they accused Spotify of almost 440 00:22:40,240 --> 00:22:43,439 Speaker 1: being corrupt, of like trying to curry favor with record 441 00:22:43,520 --> 00:22:47,360 Speaker 1: labels by playing their artists more. And the very curious 442 00:22:47,400 --> 00:22:50,000 Speaker 1: thing about this is that Apple actually had the same 443 00:22:50,000 --> 00:22:53,639 Speaker 1: problem a few years before that. And there's this clip 444 00:22:53,680 --> 00:22:56,720 Speaker 1: of one of Steve Jobs's keynote speeches when he is 445 00:22:56,760 --> 00:23:01,000 Speaker 1: introducing a feature called smart Shuffle, and like, what they 446 00:23:01,040 --> 00:23:05,400 Speaker 1: had to do essentially was change the randomness algorithm. People 447 00:23:05,480 --> 00:23:07,760 Speaker 1: thought that it simply couldn't be random when it was. 448 00:23:08,119 --> 00:23:11,240 Speaker 1: The fact is, though, that pure randomness is hard to understand, 449 00:23:11,320 --> 00:23:14,760 Speaker 1: and sometimes pure randomness means you hear the same artist 450 00:23:14,840 --> 00:23:16,760 Speaker 1: twice in a row or the same song twice in row. 451 00:23:16,840 --> 00:23:19,199 Speaker 1: That's like like getting six heads in a row flipping 452 00:23:19,200 --> 00:23:20,960 Speaker 1: a coin. It's the same thing. It's actually not what 453 00:23:21,040 --> 00:23:22,879 Speaker 1: we want out of our playlist, right, And so what 454 00:23:22,920 --> 00:23:27,000 Speaker 1: Spotify did was they tweaked their code. They evenly distribute 455 00:23:27,080 --> 00:23:30,359 Speaker 1: songs and artists over the course of a playlist so 456 00:23:30,400 --> 00:23:33,320 Speaker 1: that it's random the way that we think about random. 457 00:23:33,359 --> 00:23:35,560 Speaker 1: So really, what they did was to make it feel 458 00:23:35,600 --> 00:23:38,080 Speaker 1: more random. They actually had to make it less random, 459 00:23:38,720 --> 00:23:42,240 Speaker 1: make it less technically random, but as a listener, randomness 460 00:23:42,359 --> 00:23:45,080 Speaker 1: means that after and you use the Billy Joel example, 461 00:23:45,359 --> 00:23:48,680 Speaker 1: but after a Billy Joel song, instead of hearing another 462 00:23:48,720 --> 00:23:51,560 Speaker 1: Billy Joel song, I want to hear YouTube or Push 463 00:23:51,640 --> 00:23:55,440 Speaker 1: Stars or Prefect Sprout or Elvis Costello or non revealing 464 00:23:55,480 --> 00:23:58,680 Speaker 1: Maya playlist. But you don't want to hear the same 465 00:23:58,800 --> 00:24:01,040 Speaker 1: artist twice in a row. And what the companies had 466 00:24:01,080 --> 00:24:03,360 Speaker 1: to do was wrap their minds around the way that 467 00:24:03,560 --> 00:24:06,359 Speaker 1: humans really think, right Like, there was no amount of 468 00:24:06,400 --> 00:24:09,439 Speaker 1: money or engineering talent that could solve this problem. There 469 00:24:09,480 --> 00:24:13,040 Speaker 1: was something about the way that randomness paralyzes the human 470 00:24:13,080 --> 00:24:15,919 Speaker 1: mind that the companies had to come to grips with. 471 00:24:16,000 --> 00:24:17,920 Speaker 1: And so they could have been stubborn and said, no, 472 00:24:18,000 --> 00:24:20,200 Speaker 1: of course, this is random, this is how randomness works. 473 00:24:20,320 --> 00:24:22,320 Speaker 1: But what they did was they gave their users what 474 00:24:22,359 --> 00:24:25,360 Speaker 1: they wanted. Right, People don't want randomness, they want variety, 475 00:24:25,480 --> 00:24:28,720 Speaker 1: and whether it's random or not is almost irrelevant. Let's 476 00:24:28,760 --> 00:24:33,480 Speaker 1: talk about the NBA Jam. The people who created that 477 00:24:33,680 --> 00:24:37,400 Speaker 1: game took advantage of the hot hand and streaks tell 478 00:24:37,480 --> 00:24:39,520 Speaker 1: us a little bit about that. So NBA Jam was 479 00:24:39,560 --> 00:24:42,960 Speaker 1: developed by this game designer named Mark Trammel. And when 480 00:24:43,000 --> 00:24:45,119 Speaker 1: Mark Trammel was a kid, there were three things that 481 00:24:45,119 --> 00:24:48,600 Speaker 1: he loved. He loved basketball, and he loved video games, 482 00:24:48,760 --> 00:24:51,000 Speaker 1: and he loved fire. He was actually a bit of 483 00:24:51,000 --> 00:24:53,800 Speaker 1: a pyromaniac, and he was able to combine these three 484 00:24:53,920 --> 00:24:57,199 Speaker 1: childhood loves into the biggest hit of his life. So 485 00:24:57,280 --> 00:24:59,640 Speaker 1: I grew up playing NBA Jam. I am right around 486 00:24:59,640 --> 00:25:01,879 Speaker 1: the same ages Steph Curry, and so I know that 487 00:25:02,240 --> 00:25:04,960 Speaker 1: NBA Jam machines were sort of ubiquitous in our childhood. 488 00:25:04,960 --> 00:25:07,920 Speaker 1: They were everywhere. And what I did not know while 489 00:25:07,920 --> 00:25:10,120 Speaker 1: we were both playing NBA Jam is that NBA Jam 490 00:25:10,240 --> 00:25:14,280 Speaker 1: was one of the most lucrative successful arcade games ever made. 491 00:25:14,320 --> 00:25:16,359 Speaker 1: In the first year of its existence, it made a 492 00:25:16,440 --> 00:25:19,359 Speaker 1: billion dollars in quarters. And this is but orders of 493 00:25:19,440 --> 00:25:23,280 Speaker 1: magnitude bigger than anything else before, ginormous to the point that, 494 00:25:23,359 --> 00:25:25,360 Speaker 1: like the people who were running the company, when they 495 00:25:25,359 --> 00:25:28,400 Speaker 1: saw the numbers in the test arcade, they just refused 496 00:25:28,400 --> 00:25:29,760 Speaker 1: to believe them. They thought this has to be a 497 00:25:29,800 --> 00:25:31,679 Speaker 1: type of like, there's no way that these kids are 498 00:25:31,680 --> 00:25:34,080 Speaker 1: playing NBA Jam so much, and yet they were. And 499 00:25:34,160 --> 00:25:36,000 Speaker 1: part of that is because it was a basketball game 500 00:25:36,040 --> 00:25:37,720 Speaker 1: and it was fun and you could do crazy things 501 00:25:37,720 --> 00:25:40,720 Speaker 1: like somersault over the basket and throw down breathtaking slam 502 00:25:40,800 --> 00:25:44,280 Speaker 1: dunks and foul anybody you wanted. But really what we 503 00:25:44,320 --> 00:25:47,520 Speaker 1: wanted to do was catch fire. So in NBA jam, 504 00:25:47,600 --> 00:25:49,320 Speaker 1: if you make a few shots in a row, you 505 00:25:49,359 --> 00:25:52,240 Speaker 1: hear the announcer for the game say he's heating up. 506 00:25:52,600 --> 00:25:54,280 Speaker 1: And then if you make your next shot, you hear 507 00:25:54,560 --> 00:25:57,040 Speaker 1: he's on fire, and the ball turns into a fireball. 508 00:25:57,080 --> 00:25:58,919 Speaker 1: And what happens when you're on fire is that you 509 00:25:59,000 --> 00:26:03,320 Speaker 1: cannot miss. And that was compelling to so many people 510 00:26:03,359 --> 00:26:06,000 Speaker 1: like it was this amazing example of Mark Trammel, the 511 00:26:06,080 --> 00:26:09,359 Speaker 1: childhood pyromaniac, still playing with fire. And to me, I 512 00:26:09,359 --> 00:26:13,320 Speaker 1: think he's sort of single handedly brainwashed this generation of 513 00:26:13,400 --> 00:26:16,760 Speaker 1: impressionable young minds into believing the concept of the hot hand. 514 00:26:16,760 --> 00:26:18,960 Speaker 1: Because when you were heating up, when you were on fire, 515 00:26:19,240 --> 00:26:23,199 Speaker 1: you can't miss. That that's really quite fascinating. Let me 516 00:26:23,240 --> 00:26:25,800 Speaker 1: go over a couple of other issues of the hot hand. 517 00:26:25,840 --> 00:26:29,600 Speaker 1: I have to ask you about Shakespeare capitalized on the Plague. 518 00:26:29,680 --> 00:26:32,840 Speaker 1: You have to explain that, well, this is oddly timely now, right, yes, 519 00:26:33,119 --> 00:26:36,760 Speaker 1: which is kind of terrifying. Um. Shakespeare was never a 520 00:26:36,800 --> 00:26:40,280 Speaker 1: metronomic writer, so scholars for a very long time were 521 00:26:40,280 --> 00:26:43,440 Speaker 1: not exactly statisticians, believe it or not. And when when 522 00:26:43,480 --> 00:26:45,760 Speaker 1: they would look at like twenty four shakespeare plays, if 523 00:26:46,080 --> 00:26:48,639 Speaker 1: he wrote them over the course of twelve years, they said, okay, 524 00:26:48,640 --> 00:26:51,199 Speaker 1: Shakespeare wrote two plays a year. In fact, that's not 525 00:26:51,280 --> 00:26:55,120 Speaker 1: remotely true. Shakespeare ran hot and cold. He wrote in streaks, 526 00:26:55,240 --> 00:26:57,959 Speaker 1: and one of the great hot streaks of his career 527 00:26:58,280 --> 00:27:01,320 Speaker 1: was when he wrote King Lear Macbeth and Anthony and 528 00:27:01,359 --> 00:27:04,560 Speaker 1: Cleopatra in this very concentrated amount of time some scholars 529 00:27:04,560 --> 00:27:07,480 Speaker 1: believe as short as two months, which is crazy, right, Um. 530 00:27:07,560 --> 00:27:10,320 Speaker 1: And the reason he was able to write those plays, 531 00:27:10,359 --> 00:27:12,639 Speaker 1: and the reason those plays were such a success, was 532 00:27:12,680 --> 00:27:15,000 Speaker 1: that it happened to be a plague gear and the 533 00:27:15,000 --> 00:27:18,200 Speaker 1: plague actually worked to his advantage in very odd ways. 534 00:27:18,240 --> 00:27:21,080 Speaker 1: But the plague was this force that shaped Shakespeare's life 535 00:27:21,080 --> 00:27:23,280 Speaker 1: from the very beginning, Like he probably should have died 536 00:27:23,320 --> 00:27:25,480 Speaker 1: when he was a kid of the plague. Um. It was. 537 00:27:25,520 --> 00:27:28,439 Speaker 1: It was just always around in London, and to me 538 00:27:28,640 --> 00:27:31,399 Speaker 1: that it spoke so neatly of the hot hand, because 539 00:27:31,600 --> 00:27:34,240 Speaker 1: the hot hand is not this random occurrence. It's this 540 00:27:34,520 --> 00:27:38,760 Speaker 1: collision of talent and circumstance and a little bit of luck. 541 00:27:38,880 --> 00:27:42,359 Speaker 1: And sometimes circumstance appears when you least expect it. Sometimes 542 00:27:42,400 --> 00:27:46,520 Speaker 1: it's the plague. So let's talk about that luck, creativity, 543 00:27:46,960 --> 00:27:50,919 Speaker 1: and circumstance collision. Some people have put forth the theory 544 00:27:51,080 --> 00:27:56,800 Speaker 1: that even human careers, you will have creativity and bunches, 545 00:27:57,359 --> 00:28:01,520 Speaker 1: and most people or many people's most productive work over 546 00:28:01,560 --> 00:28:04,600 Speaker 1: the course of their lifetime comes in a very narrow 547 00:28:05,000 --> 00:28:07,560 Speaker 1: sort of era. Explain that, and not only their most 548 00:28:07,560 --> 00:28:11,359 Speaker 1: productive work, their most memorable work. There's a statistical physicist 549 00:28:11,440 --> 00:28:14,120 Speaker 1: at Northwestern named Dash and Wang who tried to look 550 00:28:14,160 --> 00:28:17,880 Speaker 1: at this idea, like, is creativity cluster? Do our hits 551 00:28:17,920 --> 00:28:20,399 Speaker 1: come in bunches? And that's really hard to do in 552 00:28:20,440 --> 00:28:23,200 Speaker 1: a lot of industries because there's just not great data, right, 553 00:28:23,240 --> 00:28:25,760 Speaker 1: And so what he tried to do was try to 554 00:28:25,800 --> 00:28:30,520 Speaker 1: put some objective numbers to subjective issues of taste. Right, 555 00:28:30,560 --> 00:28:34,560 Speaker 1: So for movie directors, that's IMDb ratings, For scientists that's 556 00:28:34,560 --> 00:28:38,040 Speaker 1: Google scholar citations. For artists it's auction prices. Now, these 557 00:28:38,080 --> 00:28:41,760 Speaker 1: are not perfect metrics, but they're like about as good 558 00:28:41,760 --> 00:28:44,120 Speaker 1: as we could do given what we have. And what 559 00:28:44,160 --> 00:28:47,680 Speaker 1: he found was that, uh, if you tell him what 560 00:28:47,840 --> 00:28:51,200 Speaker 1: your best work is, what your highest rated movie, or 561 00:28:51,240 --> 00:28:54,040 Speaker 1: what your paper that was cited the most by other academics, 562 00:28:54,320 --> 00:28:57,080 Speaker 1: was he can find the second and third best work. 563 00:28:57,160 --> 00:29:00,520 Speaker 1: And it's because those works come to get other, like 564 00:29:00,760 --> 00:29:02,960 Speaker 1: they build on top of each other. And we have 565 00:29:03,360 --> 00:29:06,960 Speaker 1: these hot hand periods in our careers, and in those periods, 566 00:29:07,000 --> 00:29:09,200 Speaker 1: we tend to produce the work that indoors and that 567 00:29:09,280 --> 00:29:12,320 Speaker 1: other people remember. So let's talk about movies. Use the 568 00:29:12,320 --> 00:29:15,880 Speaker 1: example of Rob Briner, who has written or directed some 569 00:29:15,960 --> 00:29:20,000 Speaker 1: of my favorite films. He had a streak that was 570 00:29:20,120 --> 00:29:23,400 Speaker 1: really quite astonishing, didn't he. The first few movies he 571 00:29:23,480 --> 00:29:28,000 Speaker 1: made were Spinal Tap and The Shore Thing and Stand 572 00:29:28,040 --> 00:29:30,960 Speaker 1: By Me, and those were all successes in their own way, 573 00:29:31,000 --> 00:29:34,080 Speaker 1: whether it was critically or commercially, and it sort of 574 00:29:34,120 --> 00:29:36,880 Speaker 1: earned him the runway to make a fourth movie. Now, 575 00:29:36,920 --> 00:29:38,800 Speaker 1: all three of those movies were in movies that nobody 576 00:29:38,840 --> 00:29:42,080 Speaker 1: wanted him to make, and they were huge hits regardless. 577 00:29:42,200 --> 00:29:45,440 Speaker 1: They were these delightful contradictions. And he had this conversation 578 00:29:45,480 --> 00:29:47,880 Speaker 1: with the studio executive around this time when he's trying 579 00:29:47,880 --> 00:29:49,640 Speaker 1: to figure out what he wants to make next, and 580 00:29:49,640 --> 00:29:52,600 Speaker 1: the studio executive says, we want to do anything you 581 00:29:52,600 --> 00:29:54,960 Speaker 1: want to do, right, basically, like you're hot, we want 582 00:29:54,960 --> 00:29:57,240 Speaker 1: to be in business with you. Clart Blanche, what is 583 00:29:57,240 --> 00:29:59,360 Speaker 1: it that you want to do? And he says, you 584 00:29:59,400 --> 00:30:00,840 Speaker 1: don't want to do what I want to do and 585 00:30:00,840 --> 00:30:02,880 Speaker 1: she says, no, really, just tell us what movie do 586 00:30:02,920 --> 00:30:04,760 Speaker 1: you want to make next? And he says, no, really, 587 00:30:04,800 --> 00:30:06,479 Speaker 1: I'm telling you you're not going to want to make 588 00:30:06,520 --> 00:30:09,520 Speaker 1: this movie. And she says, just name the movie and 589 00:30:09,560 --> 00:30:11,520 Speaker 1: he says, the movie I want to make is The 590 00:30:11,600 --> 00:30:15,560 Speaker 1: Princess Bride. And she says, anything but The Princess Pride. 591 00:30:15,800 --> 00:30:18,560 Speaker 1: And that sounds crazy now, because The Princess Bride is 592 00:30:18,600 --> 00:30:20,960 Speaker 1: this cult classic and one of the most beloved movies 593 00:30:21,000 --> 00:30:23,400 Speaker 1: ever made. Right. It was written by William Goldman, who 594 00:30:23,440 --> 00:30:26,040 Speaker 1: had written Butch Cassidy, He had written All the President's Men, 595 00:30:26,120 --> 00:30:28,960 Speaker 1: like you could take his grocery lists and and win 596 00:30:29,000 --> 00:30:32,400 Speaker 1: an Academy Award, and Marathon Man all he's just he's 597 00:30:32,400 --> 00:30:34,720 Speaker 1: got like the run of and and if you've never 598 00:30:34,760 --> 00:30:38,520 Speaker 1: read m his screenwriting books, The screen Confessions of a 599 00:30:38,640 --> 00:30:42,240 Speaker 1: screenwriter or the screen trade. He's the guy who has 600 00:30:42,440 --> 00:30:45,480 Speaker 1: popularized the phrase. He's no longer with us, but he 601 00:30:45,600 --> 00:30:48,560 Speaker 1: popularized the phrase nobody knows anything, which is a good 602 00:30:48,560 --> 00:30:50,200 Speaker 1: thing to think about when you're trying to write a 603 00:30:50,240 --> 00:30:53,080 Speaker 1: book about people who think they know everything. So, following 604 00:30:53,120 --> 00:30:56,920 Speaker 1: those three movies, The Princess Bride does really well, and 605 00:30:56,960 --> 00:31:00,200 Speaker 1: then what was next, Harry Met Sally a John and 606 00:31:00,280 --> 00:31:04,320 Speaker 1: smash Um Misery and a Few Good Men. Misery was 607 00:31:04,920 --> 00:31:08,320 Speaker 1: a Stephen King book that nobody expected that to be 608 00:31:08,360 --> 00:31:11,440 Speaker 1: a great movie, absolutely, and then A Few Good Men 609 00:31:11,600 --> 00:31:14,520 Speaker 1: is just a nut. And he still continued to make 610 00:31:14,520 --> 00:31:16,800 Speaker 1: movies that are still well liked. Beyond that, he was 611 00:31:16,840 --> 00:31:19,760 Speaker 1: able to elevate his career to another level. Right, And 612 00:31:19,880 --> 00:31:21,720 Speaker 1: I have to say, like I have runned this theory 613 00:31:21,760 --> 00:31:24,920 Speaker 1: by Rob Reiner. He doesn't exactly agree. What he remembers 614 00:31:24,920 --> 00:31:27,240 Speaker 1: from this period is it was still so hard to 615 00:31:27,240 --> 00:31:29,600 Speaker 1: get The Princess Bride made. But to me, that's actually 616 00:31:29,600 --> 00:31:32,040 Speaker 1: a proof of the hot hand that was shaping everything, 617 00:31:32,120 --> 00:31:34,480 Speaker 1: because if he remembers, he was still so hard, and 618 00:31:34,520 --> 00:31:36,760 Speaker 1: it was that hard, it simply would never have been 619 00:31:36,800 --> 00:31:39,920 Speaker 1: made if he weren't hot. The Princess Bride had been 620 00:31:39,960 --> 00:31:43,240 Speaker 1: attached to a number of other producers and directors, including 621 00:31:43,280 --> 00:31:46,680 Speaker 1: some really giant names in Hollywood, and it was almost 622 00:31:46,720 --> 00:31:50,360 Speaker 1: a cursed screenplay. It just couldn't get done. It was 623 00:31:50,360 --> 00:31:53,240 Speaker 1: the great White Whale. Rollywood, I mean Trufaux tried to 624 00:31:53,240 --> 00:31:56,160 Speaker 1: make it. Norman Jewis and Robert Redford tried to direct 625 00:31:56,280 --> 00:31:58,600 Speaker 1: it and star in it, and still nobody could get 626 00:31:58,600 --> 00:32:01,000 Speaker 1: it made. Goldman like to tell this wordy that one 627 00:32:01,040 --> 00:32:03,600 Speaker 1: studio had bought the movie and was fired the next weekend, 628 00:32:03,760 --> 00:32:06,440 Speaker 1: Like nobody could get this movie made. And you could 629 00:32:06,520 --> 00:32:09,960 Speaker 1: argue that, like if Rob Ryner knew about this, maybe 630 00:32:09,960 --> 00:32:12,760 Speaker 1: he wouldn't have And even when he went to Goldman 631 00:32:12,800 --> 00:32:15,320 Speaker 1: to try to get his permission to make the Princess Pride, 632 00:32:15,360 --> 00:32:18,360 Speaker 1: he was terrified. And Bill Goleman opens the door and says, 633 00:32:18,400 --> 00:32:21,080 Speaker 1: the Princess Bride is my favorite thing I've ever written, Like, 634 00:32:21,120 --> 00:32:23,680 Speaker 1: don't screw it up. And he was able to get permission, 635 00:32:23,760 --> 00:32:26,040 Speaker 1: and he was able to make the movie, and I 636 00:32:26,040 --> 00:32:30,000 Speaker 1: think we're all luckier for it. Quite amazing. Let's talk 637 00:32:30,040 --> 00:32:34,280 Speaker 1: about how the NBA is adapting to the idea of 638 00:32:35,520 --> 00:32:39,760 Speaker 1: behavioral economics. You wrote a really interesting column about quote 639 00:32:39,800 --> 00:32:43,440 Speaker 1: the renegade executives of Houston who shook up sports management. 640 00:32:43,760 --> 00:32:46,520 Speaker 1: Tell us about those guys, well, they haven't had a 641 00:32:46,560 --> 00:32:49,520 Speaker 1: great few months since that story came out. But um, 642 00:32:49,560 --> 00:32:51,480 Speaker 1: a couple of months ago, my colleague at the Journal, 643 00:32:51,560 --> 00:32:54,560 Speaker 1: Jared Diamond, and I Jared covers baseball, I cover basketball, 644 00:32:54,840 --> 00:32:57,160 Speaker 1: We went down to Houston to have lunch with two 645 00:32:57,200 --> 00:32:59,800 Speaker 1: really smart executives there. One his name Darryl Morey, and 646 00:32:59,800 --> 00:33:02,280 Speaker 1: he the general manager of the Houston Rockets. The other 647 00:33:02,560 --> 00:33:05,200 Speaker 1: is Jeff lu Now, who was the general manager of 648 00:33:05,240 --> 00:33:07,360 Speaker 1: the Houston Astros. And we just thought it would be 649 00:33:07,360 --> 00:33:09,800 Speaker 1: fun to get them together and just talk about how 650 00:33:09,840 --> 00:33:12,040 Speaker 1: much their sports have changed. And it was fun and 651 00:33:12,120 --> 00:33:15,360 Speaker 1: it made for a really interesting story. And about a 652 00:33:15,400 --> 00:33:19,200 Speaker 1: week later, Darryl became the most interesting man in geopolitics. 653 00:33:19,200 --> 00:33:21,120 Speaker 1: He was already the most interesting man in sports, and 654 00:33:21,120 --> 00:33:23,800 Speaker 1: I love Darryl, but um, he set off this feud 655 00:33:23,840 --> 00:33:27,440 Speaker 1: between the NBA and China with this tweet supporting Hong Kong. 656 00:33:27,680 --> 00:33:29,480 Speaker 1: And back up a little bit. So he got his 657 00:33:30,000 --> 00:33:32,560 Speaker 1: graduate degree from m I T and M I T 658 00:33:32,760 --> 00:33:36,320 Speaker 1: has a really deep relationship with Hong Kong, including lots 659 00:33:36,360 --> 00:33:39,360 Speaker 1: of students. And I think they have a satellite school 660 00:33:39,360 --> 00:33:42,280 Speaker 1: there as well well. And also the NBA has this 661 00:33:42,640 --> 00:33:46,080 Speaker 1: long running financial relationship with China, right, I mean, China 662 00:33:46,360 --> 00:33:49,600 Speaker 1: is the engine that is powering the future growth of 663 00:33:49,640 --> 00:33:51,840 Speaker 1: the league. It's global growth outside of the U s 664 00:33:51,880 --> 00:33:54,880 Speaker 1: Oh yeah, it's the most important foreign market. And like 665 00:33:55,160 --> 00:33:58,120 Speaker 1: the league has always cultivated China, like over the course 666 00:33:58,160 --> 00:34:00,800 Speaker 1: of three decades or so, and like the one tweet 667 00:34:01,080 --> 00:34:03,800 Speaker 1: imperiled that relationship overnight. I mean to this day. I 668 00:34:03,800 --> 00:34:06,760 Speaker 1: mean the NBA is still not on CCTV. UM, so 669 00:34:06,840 --> 00:34:09,319 Speaker 1: a lot has changed. Um, But was it really a 670 00:34:09,360 --> 00:34:12,000 Speaker 1: two or three hundred million dollar tweet? It was a 671 00:34:12,000 --> 00:34:14,120 Speaker 1: lot of money. I mean, this the sal you know, Adam, 672 00:34:14,160 --> 00:34:17,840 Speaker 1: they canceled the Precision Games, right, they played the games, 673 00:34:17,880 --> 00:34:22,000 Speaker 1: but they weren't broadcast, right And and and NBA Commissioner 674 00:34:22,040 --> 00:34:24,120 Speaker 1: Adam Silver said that he thought the loss could be 675 00:34:24,120 --> 00:34:26,880 Speaker 1: about like four hundred million dollars. So, um, there's a 676 00:34:26,920 --> 00:34:29,040 Speaker 1: lot of money. But like you know that it was 677 00:34:29,080 --> 00:34:34,000 Speaker 1: a very fascinating issue because, um, it pitted like American 678 00:34:34,120 --> 00:34:37,680 Speaker 1: democratic norms of free speech against like trying to do 679 00:34:37,719 --> 00:34:39,879 Speaker 1: business in China. And I think this is something that 680 00:34:39,920 --> 00:34:42,080 Speaker 1: like every company is going to have to be dealing 681 00:34:42,120 --> 00:34:44,959 Speaker 1: with at some point, and um, it was just sort 682 00:34:45,000 --> 00:34:48,400 Speaker 1: of this like dry forest, And I think Darryl's tweet 683 00:34:48,440 --> 00:34:51,360 Speaker 1: turned out to be the kindling that nobody really thought 684 00:34:51,400 --> 00:34:53,600 Speaker 1: would blow everything up, but it kind of did. So 685 00:34:53,640 --> 00:34:55,799 Speaker 1: we were talking about film earlier. I think a lot 686 00:34:55,880 --> 00:34:59,560 Speaker 1: of people don't realize how much of American film is 687 00:34:59,560 --> 00:35:04,000 Speaker 1: now one did by foreign investors, including China, especially China, 688 00:35:04,120 --> 00:35:07,959 Speaker 1: And so what what happens is you end up with 689 00:35:08,920 --> 00:35:11,480 Speaker 1: the bad guy being the Russians, never the Chinese. And 690 00:35:11,520 --> 00:35:14,640 Speaker 1: that's a direct function of who's writing the check. It's 691 00:35:14,719 --> 00:35:16,360 Speaker 1: and and to me it was just it was it 692 00:35:16,440 --> 00:35:20,520 Speaker 1: was of course Darryll was involved, because Darrell is. I 693 00:35:20,560 --> 00:35:22,120 Speaker 1: love the guy. I've written about him as much as 694 00:35:22,120 --> 00:35:23,680 Speaker 1: ever written about anybody in the n b A. He's 695 00:35:23,760 --> 00:35:26,759 Speaker 1: so smart and so interesting and he's this real renaissance 696 00:35:26,800 --> 00:35:28,520 Speaker 1: man of the n b A. If you were to 697 00:35:28,560 --> 00:35:31,880 Speaker 1: ask me, like, which NBA executive would unwittingly start something 698 00:35:31,920 --> 00:35:33,759 Speaker 1: like this, like, of course it would be Daryl, because 699 00:35:33,800 --> 00:35:36,160 Speaker 1: Darrel is in the middle of everything, and he was 700 00:35:36,520 --> 00:35:39,200 Speaker 1: twice NBA Executive of the Year. I don't think he's 701 00:35:39,200 --> 00:35:41,320 Speaker 1: going to win that this year. Well he might, I 702 00:35:41,320 --> 00:35:43,719 Speaker 1: mean it, it depends. I mean it's voted on by 703 00:35:43,800 --> 00:35:46,279 Speaker 1: other executives, and I'll take the other side of that that. 704 00:35:47,160 --> 00:35:52,200 Speaker 1: I'll give you two to one odds. The interesting thing 705 00:35:52,280 --> 00:35:54,839 Speaker 1: about Daryl winning that award is that that's an award 706 00:35:54,920 --> 00:35:57,239 Speaker 1: voted on by your peers. And for a very long time, 707 00:35:57,400 --> 00:36:01,400 Speaker 1: I think there was resistance among NBA general managers to 708 00:36:01,600 --> 00:36:04,239 Speaker 1: acknowledge that Darrel is a really smart guy and he 709 00:36:04,320 --> 00:36:08,720 Speaker 1: was using statistics and analytics and information in really interesting ways. 710 00:36:08,840 --> 00:36:12,919 Speaker 1: Can't argue with success. Speaking of success, let's talk about 711 00:36:12,960 --> 00:36:16,000 Speaker 1: Steph Curry. I love the story in the book. It's 712 00:36:16,040 --> 00:36:19,399 Speaker 1: pretty good at not bad. And I understand he's taking 713 00:36:19,440 --> 00:36:21,560 Speaker 1: more shots from behind the line. So that's the thing, 714 00:36:22,080 --> 00:36:25,279 Speaker 1: the story about how he lights the Knicks up. Um, 715 00:36:25,840 --> 00:36:28,759 Speaker 1: do you remember that game? No? No, I don't, And 716 00:36:28,800 --> 00:36:31,360 Speaker 1: if I saw that game, I have suppressed the memory, 717 00:36:31,520 --> 00:36:34,640 Speaker 1: like so many other losses the Knicks have suffered over 718 00:36:34,680 --> 00:36:37,719 Speaker 1: the years. But he's a guy who's essentially on the 719 00:36:37,760 --> 00:36:40,920 Speaker 1: bench or half the time, half the game. He doesn't 720 00:36:40,920 --> 00:36:44,080 Speaker 1: have the green light to just toss up three pointers. 721 00:36:44,520 --> 00:36:46,839 Speaker 1: What happened in that one game with the Knicks. Yeah, 722 00:36:46,880 --> 00:36:49,560 Speaker 1: the through line of Steph Curry's career until a certain 723 00:36:49,600 --> 00:36:52,239 Speaker 1: point of his life was that nobody really thought that 724 00:36:52,320 --> 00:36:54,360 Speaker 1: he could be as good as we now know him 725 00:36:54,400 --> 00:36:57,720 Speaker 1: to be. Um. He was lightly recruited out of high school. 726 00:36:57,840 --> 00:37:01,200 Speaker 1: He went to tiny Davidson College. Even after coming out 727 00:37:01,200 --> 00:37:04,239 Speaker 1: of Davidson, where he had this incredible, unforgettable run in 728 00:37:04,239 --> 00:37:07,120 Speaker 1: the n c A Tournament in two thousand eight. You know, 729 00:37:07,200 --> 00:37:08,960 Speaker 1: he was the seventh pick in the NBA Draft. There 730 00:37:08,960 --> 00:37:12,120 Speaker 1: were lots of questions about whether someone who was as 731 00:37:12,160 --> 00:37:14,719 Speaker 1: small as him and shot three pointers as much as 732 00:37:14,800 --> 00:37:17,840 Speaker 1: him could really be like a force in the NBA. 733 00:37:18,120 --> 00:37:20,600 Speaker 1: And those questions kind of lingered until this one night 734 00:37:20,840 --> 00:37:24,160 Speaker 1: in February. Let me interrupt you before we get into 735 00:37:24,200 --> 00:37:27,920 Speaker 1: that night. So, as a Knicks fan, watching Jordan and 736 00:37:27,920 --> 00:37:32,680 Speaker 1: the Bulls dismantled him. Season after season, the Bulls always 737 00:37:32,760 --> 00:37:37,680 Speaker 1: had Um somebody Steve kerr Hodges, somebody who was an 738 00:37:37,719 --> 00:37:41,840 Speaker 1: assassin from behind the three point line, and it forced 739 00:37:42,440 --> 00:37:44,680 Speaker 1: the floor to be spread, so they couldn't if you're 740 00:37:44,719 --> 00:37:47,440 Speaker 1: gonna collapse on Michael Jordan's He's going to find the 741 00:37:47,520 --> 00:37:50,120 Speaker 1: open man and it might be a three pointer. So 742 00:37:50,400 --> 00:37:53,719 Speaker 1: I think twice about it. That was a very specific 743 00:37:53,840 --> 00:37:59,240 Speaker 1: tactical decision. Now tell us what happened with Uh Curry 744 00:37:59,719 --> 00:38:02,120 Speaker 1: and the next that night, so so Steve Kerry with 745 00:38:02,120 --> 00:38:04,720 Speaker 1: the three point shooter around Michael Jordan's. What if Michael 746 00:38:04,760 --> 00:38:07,400 Speaker 1: Jordan's were the three point shooter right? That's sort of 747 00:38:07,400 --> 00:38:10,319 Speaker 1: the question that has become prevalent in the NBA over 748 00:38:10,360 --> 00:38:14,080 Speaker 1: the last few years. This was a night that nobody 749 00:38:14,120 --> 00:38:17,640 Speaker 1: thought would be Steph Curry's breakthrough, his coming out party. 750 00:38:18,000 --> 00:38:20,680 Speaker 1: The night before the Golden State Warriors had played in Indiana, 751 00:38:20,719 --> 00:38:23,040 Speaker 1: they had gotten into a fight. Steph Curry was actually 752 00:38:23,040 --> 00:38:25,040 Speaker 1: involved in the fight, and if you watch the clip now, 753 00:38:25,040 --> 00:38:27,719 Speaker 1: it's kind of amazing because he charges this guy named 754 00:38:27,800 --> 00:38:31,440 Speaker 1: Roy Hibbert seven ft two and ways two of Steph 755 00:38:31,440 --> 00:38:34,239 Speaker 1: Curry's right, and what happened is exactly what you might 756 00:38:34,239 --> 00:38:36,640 Speaker 1: think happened, which is Ray Hibbert just sort of brushed 757 00:38:36,719 --> 00:38:40,760 Speaker 1: him aside. For his entire life, Steph Curry's great disadvantage 758 00:38:40,800 --> 00:38:43,480 Speaker 1: was had been his size, right, but for this one night, 759 00:38:43,520 --> 00:38:45,880 Speaker 1: it was his improbable advantage. He was too small to 760 00:38:45,920 --> 00:38:48,480 Speaker 1: do any real damage in a fight of NBA players, 761 00:38:48,520 --> 00:38:50,880 Speaker 1: So they fled to New York that night, so no 762 00:38:51,000 --> 00:38:53,799 Speaker 1: suspension for him. He's not suspended. Other players on his 763 00:38:53,840 --> 00:38:56,800 Speaker 1: team are. However, Steph Curry is fined thirty five thousand 764 00:38:56,840 --> 00:38:59,560 Speaker 1: dollars and nobody has ever been so fortunate to lose 765 00:38:59,600 --> 00:39:02,799 Speaker 1: so much money. The Warriors get to New York and 766 00:39:03,040 --> 00:39:05,399 Speaker 1: they just don't have their full team right they they're 767 00:39:05,480 --> 00:39:07,839 Speaker 1: there are only a certain number of guys who can play. Now, 768 00:39:07,920 --> 00:39:10,360 Speaker 1: something else happens before they get to Madison Square Garden, 769 00:39:10,360 --> 00:39:14,160 Speaker 1: which is very funny in retrospect. Steph Curry during Warriors 770 00:39:14,239 --> 00:39:17,880 Speaker 1: road games always takes the second of three buses from 771 00:39:17,920 --> 00:39:19,800 Speaker 1: the team hotel to the arena. There are three buses. 772 00:39:19,840 --> 00:39:23,680 Speaker 1: Steps always on the side of superstition or timing, so like, 773 00:39:23,920 --> 00:39:25,640 Speaker 1: he wants to be at the arena a certain time 774 00:39:25,640 --> 00:39:27,200 Speaker 1: and he wants to warm up at a certain time 775 00:39:27,239 --> 00:39:29,239 Speaker 1: and getting there on the first bus is too early, 776 00:39:29,280 --> 00:39:32,279 Speaker 1: and the third bus is probably too late. This day, 777 00:39:32,440 --> 00:39:35,200 Speaker 1: for some reason he can't remember, he misses the second bus, 778 00:39:35,400 --> 00:39:38,040 Speaker 1: takes the third bus. What happens when the third bus 779 00:39:38,080 --> 00:39:40,520 Speaker 1: leads the team hotel gets pulled over by New York 780 00:39:40,560 --> 00:39:42,640 Speaker 1: City cops on the way to Madison Square Garden. So 781 00:39:42,680 --> 00:39:47,560 Speaker 1: now he's missed his normal bus, his now bus, He's 782 00:39:47,600 --> 00:39:50,839 Speaker 1: missed his normal bus. His third bus gets pulled over 783 00:39:50,880 --> 00:39:53,239 Speaker 1: on the way to the garden. He's rushed, he's late, 784 00:39:53,719 --> 00:39:56,040 Speaker 1: he's gotten into a fight the night before, He's down 785 00:39:56,080 --> 00:39:58,920 Speaker 1: thirty dollars. And what happens at night is that he 786 00:39:59,040 --> 00:40:02,279 Speaker 1: has the single greatest shooting night of his career. He 787 00:40:02,360 --> 00:40:04,840 Speaker 1: scores fifty four points, plays all forty eight minutes, He 788 00:40:04,840 --> 00:40:06,680 Speaker 1: doesn't come out of the game. He makes eleven of 789 00:40:06,680 --> 00:40:09,000 Speaker 1: his thirteen three pointers. Nobody in the history of the NBA, 790 00:40:09,200 --> 00:40:11,640 Speaker 1: let alone him, had ever taken so many threes and 791 00:40:11,719 --> 00:40:13,879 Speaker 1: made so many of them in the same game. And 792 00:40:14,480 --> 00:40:17,600 Speaker 1: this was really an epiphany for Steph Curry and for 793 00:40:17,640 --> 00:40:20,640 Speaker 1: the Warriors generally, and actually for the whole NBA, because 794 00:40:20,960 --> 00:40:23,080 Speaker 1: what they were able to do after that night is 795 00:40:23,160 --> 00:40:27,160 Speaker 1: build a team around Steph Curry's remarkable ability to shoot 796 00:40:27,200 --> 00:40:30,840 Speaker 1: a basketball, and he's only gotten better behind the behind 797 00:40:30,840 --> 00:40:34,560 Speaker 1: the line. Before that game, he averaged like eighteen points 798 00:40:34,640 --> 00:40:37,760 Speaker 1: and took five threes a game. Since then, he averages 799 00:40:37,760 --> 00:40:40,000 Speaker 1: twenty six points and he takes ten threes. He's won 800 00:40:40,040 --> 00:40:42,920 Speaker 1: two m vps, the Warriors have won three championships, and 801 00:40:42,960 --> 00:40:46,120 Speaker 1: the most remarkable thing about all of this, um is 802 00:40:46,120 --> 00:40:48,719 Speaker 1: that it took the NBA so long to figure this out. 803 00:40:48,760 --> 00:40:50,960 Speaker 1: Like three is worth more than two. It's in the 804 00:40:51,000 --> 00:40:53,759 Speaker 1: name of the shot, right, It's it's not just a 805 00:40:53,760 --> 00:40:56,600 Speaker 1: little it's worth one and a half times a regular shot. 806 00:40:56,840 --> 00:40:58,880 Speaker 1: But it's not one and a half times as difficult, 807 00:40:59,239 --> 00:41:01,640 Speaker 1: or is it. There is a huge incentive to shooting 808 00:41:01,680 --> 00:41:04,160 Speaker 1: three pointers. Now it is more difficult, but not if 809 00:41:04,160 --> 00:41:07,680 Speaker 1: you're Steph Curry, right. Steph Curry is a shooter from three, 810 00:41:07,800 --> 00:41:10,120 Speaker 1: and the name of the game now is shoot as 811 00:41:10,120 --> 00:41:12,919 Speaker 1: many three pointers as possible. And the game was sort 812 00:41:12,920 --> 00:41:15,600 Speaker 1: of going there anyway. But whether or not the Warriors 813 00:41:15,640 --> 00:41:18,120 Speaker 1: would have built around Steph Curry, I'm not sure they 814 00:41:18,160 --> 00:41:20,200 Speaker 1: would have. Without this game, we're going to have to 815 00:41:20,239 --> 00:41:22,799 Speaker 1: move the three point line. We might, you know, I 816 00:41:22,840 --> 00:41:25,040 Speaker 1: think that there there is talk about like a potential 817 00:41:25,080 --> 00:41:28,919 Speaker 1: four point line. Um, there's talk about the three point line. 818 00:41:28,960 --> 00:41:31,640 Speaker 1: But we're getting to a point now where about ten 819 00:41:31,719 --> 00:41:34,359 Speaker 1: years ago, the number of three pointers in the NBA 820 00:41:34,400 --> 00:41:38,040 Speaker 1: game accounted for about of shots. Now we're at about 821 00:41:38,040 --> 00:41:40,560 Speaker 1: thirty five percent of shots. The number of threes per 822 00:41:40,600 --> 00:41:43,360 Speaker 1: game has doubled over the course of fifteen years. I 823 00:41:43,480 --> 00:41:45,440 Speaker 1: was at the m I. T. S. Slowan sports analytics 824 00:41:45,440 --> 00:41:49,120 Speaker 1: conference recently and asked someone with a team, like, what 825 00:41:49,280 --> 00:41:51,560 Speaker 1: is the upper limit here? Like when when do you 826 00:41:51,560 --> 00:41:55,440 Speaker 1: get to returns? Well, the Houston Rockets are taking their 827 00:41:55,440 --> 00:41:58,520 Speaker 1: shots now, so like for a single team, how high 828 00:41:58,560 --> 00:42:02,319 Speaker 1: could you get? And this person, really smart, wonky analytical 829 00:42:02,480 --> 00:42:05,680 Speaker 1: mathematical says that he has studied the numbers and he 830 00:42:05,719 --> 00:42:09,359 Speaker 1: thinks that it's the team shots as three. So like 831 00:42:09,760 --> 00:42:12,520 Speaker 1: by those standards, where nowhere even close to the end 832 00:42:12,520 --> 00:42:14,239 Speaker 1: of this, I'm trying to think of how you would 833 00:42:14,239 --> 00:42:18,120 Speaker 1: move the lineback with without Unless you make the line, 834 00:42:18,239 --> 00:42:20,760 Speaker 1: you give up the corner shot, which is the best 835 00:42:20,840 --> 00:42:23,479 Speaker 1: location shot. The corner three pointers the most efficient shot 836 00:42:23,600 --> 00:42:26,279 Speaker 1: in the closest and it's the most it's still worth 837 00:42:26,280 --> 00:42:28,399 Speaker 1: three points, right, I mean, there are some funky things 838 00:42:28,440 --> 00:42:30,080 Speaker 1: that you could do, Like you could make an arc. 839 00:42:30,280 --> 00:42:31,920 Speaker 1: You could make an arc. You could you could add 840 00:42:31,960 --> 00:42:33,839 Speaker 1: a four point line but move the three point line 841 00:42:33,880 --> 00:42:37,279 Speaker 1: in so that you actually make every shot worth the 842 00:42:37,320 --> 00:42:39,360 Speaker 1: same amount of points. Right now, there is this huge 843 00:42:40,040 --> 00:42:44,160 Speaker 1: incentive against shooting mid range shots because there worth two 844 00:42:44,160 --> 00:42:46,920 Speaker 1: points and you generally at the same rate as three pointers, right, 845 00:42:47,360 --> 00:42:51,040 Speaker 1: no sense, How could you sort of um incentivize people 846 00:42:51,040 --> 00:42:53,680 Speaker 1: to take those shots? Is that you change the value 847 00:42:53,680 --> 00:42:55,160 Speaker 1: of them? Now, I think there are people in the 848 00:42:55,239 --> 00:42:58,080 Speaker 1: NBA who are encouraged that even though teams are shooting 849 00:42:58,120 --> 00:43:00,239 Speaker 1: a whole bunch of threes now and all the good 850 00:43:00,280 --> 00:43:03,280 Speaker 1: teams are shooting threes, there's not really a homogeneous style 851 00:43:03,320 --> 00:43:05,800 Speaker 1: of play. They're getting those three pointers in different ways, 852 00:43:05,840 --> 00:43:09,520 Speaker 1: so there is some variety, um, but the end result 853 00:43:09,600 --> 00:43:10,960 Speaker 1: is the same. Like the name of the game now 854 00:43:11,120 --> 00:43:13,120 Speaker 1: is how many three pointers can you take? And how 855 00:43:13,120 --> 00:43:16,000 Speaker 1: many of them can you make? So let's talk about 856 00:43:16,040 --> 00:43:19,920 Speaker 1: somebody that you've you wrote about after Kobe Bryant's passing, 857 00:43:20,040 --> 00:43:24,520 Speaker 1: but I'm familiar with from Michael Lewis's book The Undoing Project, 858 00:43:24,920 --> 00:43:28,080 Speaker 1: and that's Shane Batty. He's a guy that would be 859 00:43:28,120 --> 00:43:33,760 Speaker 1: assigned to cover the best score on the other team, 860 00:43:33,880 --> 00:43:37,000 Speaker 1: and if you look at his stats, that really nothing. 861 00:43:38,080 --> 00:43:40,080 Speaker 1: What does a guy like Shane Batty a mean to 862 00:43:40,880 --> 00:43:43,600 Speaker 1: the new version? And of course he was on the 863 00:43:43,600 --> 00:43:47,520 Speaker 1: Houston Rockets under Darryl Moury, But what does the player 864 00:43:47,600 --> 00:43:52,120 Speaker 1: like that mean to the new version of Basketball's equivalent? 865 00:43:52,120 --> 00:43:56,640 Speaker 1: Of money ball, just about everything. Really. To me, the 866 00:43:56,640 --> 00:43:59,480 Speaker 1: beauty of Shane Battier is that, um, he was someone 867 00:43:59,640 --> 00:44:03,040 Speaker 1: who the NBA did not value properly because he did 868 00:44:03,080 --> 00:44:05,200 Speaker 1: not have great stats. Right, He didn't score a lot 869 00:44:05,200 --> 00:44:06,640 Speaker 1: of points, he didn't grab a lot of rebounds, he 870 00:44:06,680 --> 00:44:09,760 Speaker 1: didn't shodow a lot of assists. But when he played, 871 00:44:09,880 --> 00:44:12,040 Speaker 1: his team was better when he was on the floor, right. 872 00:44:12,160 --> 00:44:15,680 Speaker 1: And there was no relationship that embodied this better than 873 00:44:16,280 --> 00:44:18,880 Speaker 1: Shane Battier when he tried to guard Kobe Bryant. And 874 00:44:18,920 --> 00:44:21,880 Speaker 1: so I talked to Shane after, you know, the tragic 875 00:44:21,920 --> 00:44:24,480 Speaker 1: death of Kobe Bryant a few weeks ago, because I 876 00:44:24,480 --> 00:44:27,560 Speaker 1: wanted to know, like, what did he remember from those 877 00:44:27,600 --> 00:44:29,640 Speaker 1: games when they played each other? And you know what 878 00:44:29,719 --> 00:44:32,080 Speaker 1: he What Shane says is that when they played, he 879 00:44:32,120 --> 00:44:35,600 Speaker 1: always felt like he was Captain Ahab and Kobe Bryant 880 00:44:35,600 --> 00:44:37,759 Speaker 1: was his Moby Dick and he was always chasing him, 881 00:44:37,880 --> 00:44:40,320 Speaker 1: and they had this strange cat and mouse game where 882 00:44:40,719 --> 00:44:42,640 Speaker 1: it was not only physical, it was not only on 883 00:44:42,680 --> 00:44:46,160 Speaker 1: the court, it was psychological. Shane Battier knew that like 884 00:44:46,239 --> 00:44:48,360 Speaker 1: trying to trash talk Kobe was the worst thing that 885 00:44:48,400 --> 00:44:51,080 Speaker 1: you could do because it would get him. So he 886 00:44:51,239 --> 00:44:54,799 Speaker 1: would like purposefully be modest when he walked on the 887 00:44:54,800 --> 00:44:57,320 Speaker 1: court with Kobe. He would like basically say, like I 888 00:44:57,320 --> 00:44:58,880 Speaker 1: don't even belong on the same court as you man, 889 00:44:58,960 --> 00:45:01,440 Speaker 1: Like I'm this unathletic plots like you're gonna kill me tonight. 890 00:45:01,960 --> 00:45:05,680 Speaker 1: What Kobe knew was exactly what Shane Battier was doing. So, 891 00:45:05,760 --> 00:45:07,759 Speaker 1: like Kobe wrote in his book, like yeah, I knew 892 00:45:07,760 --> 00:45:09,880 Speaker 1: Shane was like being modest because he thought that that 893 00:45:09,880 --> 00:45:12,200 Speaker 1: wouldn't fire me up. And so they were going back 894 00:45:12,239 --> 00:45:14,280 Speaker 1: and forth, and they were so deep into each other's 895 00:45:14,280 --> 00:45:18,240 Speaker 1: minds and so their matchups were just these classic matchups. 896 00:45:18,280 --> 00:45:20,919 Speaker 1: I mean what Shane says that nobody challenged him more 897 00:45:20,920 --> 00:45:23,480 Speaker 1: than Kobe. He was like the pinnacle of challenge in 898 00:45:23,520 --> 00:45:26,520 Speaker 1: his profession. The great thing about their relationship, the thing 899 00:45:26,560 --> 00:45:28,960 Speaker 1: that I loved was that they had no relationship. They 900 00:45:29,000 --> 00:45:31,799 Speaker 1: never talked outside the arena. There was nobody who each 901 00:45:31,840 --> 00:45:34,280 Speaker 1: of them respected more in terms of offense and defense, 902 00:45:34,400 --> 00:45:36,560 Speaker 1: and yet it was all on the basketball court, like 903 00:45:36,680 --> 00:45:38,680 Speaker 1: they never got a chance to like have that beer 904 00:45:38,680 --> 00:45:41,719 Speaker 1: and just reminisce about all of these incredible matchups that 905 00:45:41,760 --> 00:45:45,279 Speaker 1: they had. So the plus and minus measurement is is 906 00:45:45,320 --> 00:45:48,040 Speaker 1: your team scoring more points when you're on the court 907 00:45:48,160 --> 00:45:50,960 Speaker 1: and as the other team scoring less points, what is 908 00:45:51,000 --> 00:45:55,760 Speaker 1: your contribution? Daddy A turned Kobe Bryant into a negative 909 00:45:55,760 --> 00:45:58,560 Speaker 1: for the Lakers, sometimes right and sometimes so um so 910 00:45:58,640 --> 00:46:01,120 Speaker 1: plus minus is estab that like over the course of 911 00:46:01,120 --> 00:46:04,160 Speaker 1: one game, maybe a little bit noisy, sometimes like sometimes 912 00:46:04,200 --> 00:46:06,400 Speaker 1: it's not sometimes exactly shows a lot, but of the 913 00:46:06,400 --> 00:46:08,520 Speaker 1: course of a season and over the course of a career, 914 00:46:08,800 --> 00:46:11,239 Speaker 1: it's like hugely informative and so like for the last 915 00:46:11,280 --> 00:46:12,960 Speaker 1: few years, who has had the best plus minus in 916 00:46:13,000 --> 00:46:15,720 Speaker 1: the NBA. It's Steph Curry and that sort of shows 917 00:46:15,800 --> 00:46:20,200 Speaker 1: his impact on the game quite quite interesting. So one 918 00:46:20,239 --> 00:46:22,640 Speaker 1: of the person I have to ask about the number 919 00:46:22,640 --> 00:46:27,640 Speaker 1: one draft last years Zion Williamson. How was he turning out? 920 00:46:27,719 --> 00:46:31,000 Speaker 1: He was supposed to have a huge impact on the 921 00:46:31,120 --> 00:46:33,880 Speaker 1: n b A he got hurt uh in the beginning 922 00:46:33,880 --> 00:46:37,200 Speaker 1: of the season and now he's back. Is this guy 923 00:46:37,280 --> 00:46:40,440 Speaker 1: gonna be worthy of a number one pick? Or is 924 00:46:40,480 --> 00:46:44,600 Speaker 1: it another topic that goes bust? He's fantastic, he uh. 925 00:46:44,640 --> 00:46:47,160 Speaker 1: There There are not many rookies in the NBA who 926 00:46:47,239 --> 00:46:50,120 Speaker 1: changed the fortunes of their team immediately, Like you could 927 00:46:50,120 --> 00:46:52,000 Speaker 1: probably list them on one hand over the course of 928 00:46:52,000 --> 00:46:55,520 Speaker 1: the last few decades. Lebron James of course, um, maybe 929 00:46:55,600 --> 00:46:59,040 Speaker 1: Kevin Durant, maybe Anthony Davis. Was Zion Williamson has done 930 00:46:59,360 --> 00:47:01,520 Speaker 1: after missing the first few months of his rookie season 931 00:47:01,560 --> 00:47:04,640 Speaker 1: with an injury, is that he's turned New Orleans Pelicans 932 00:47:04,680 --> 00:47:07,880 Speaker 1: into like a real player. So like if you look 933 00:47:07,920 --> 00:47:10,600 Speaker 1: at the numbers, even the plus minus numbers, when he's 934 00:47:10,640 --> 00:47:14,200 Speaker 1: on the court, they're destroying other teams and so destroying. Yeah, 935 00:47:14,320 --> 00:47:17,840 Speaker 1: like they are, Uh, they're going to be excellent building 936 00:47:17,840 --> 00:47:20,239 Speaker 1: around him over the next few years. And so, um, 937 00:47:20,280 --> 00:47:22,200 Speaker 1: he sort of lost some of his momentum because he 938 00:47:22,200 --> 00:47:24,279 Speaker 1: didn't play for a few months and everybody sort of 939 00:47:24,280 --> 00:47:26,799 Speaker 1: forgot about him. And yet we see him now and 940 00:47:26,840 --> 00:47:29,840 Speaker 1: it's like you are like you're seeing a superstar in 941 00:47:29,880 --> 00:47:32,200 Speaker 1: the making. Like there, he's gonna lose weight, his body's 942 00:47:32,200 --> 00:47:33,919 Speaker 1: going to change, he's going to learn how to play 943 00:47:33,920 --> 00:47:35,799 Speaker 1: the game. Like you watch him on defense. He doesn't 944 00:47:35,800 --> 00:47:37,440 Speaker 1: know what he's doing yet. Right, he's a rookie. He's 945 00:47:37,480 --> 00:47:40,080 Speaker 1: nineteen years quick, and he can jump, and he has 946 00:47:40,120 --> 00:47:43,520 Speaker 1: brilliant vision, he can pass. He everyone knew that he 947 00:47:43,600 --> 00:47:46,719 Speaker 1: was this incredible dunker, but like, his game is so 948 00:47:46,800 --> 00:47:50,000 Speaker 1: well rounded, he is like going to be a sublime basketball. 949 00:47:50,080 --> 00:47:52,880 Speaker 1: So so let's violate one of Darryl Morey's rules and 950 00:47:52,920 --> 00:47:57,520 Speaker 1: compare him to somebody else. Who is Zion more like? 951 00:47:57,800 --> 00:47:59,600 Speaker 1: Is he Gianni or is he going to be more 952 00:47:59,640 --> 00:48:05,040 Speaker 1: like a little Bron? It's interesting? Uh, and you wrote 953 00:48:05,040 --> 00:48:08,759 Speaker 1: to column Giannice is now hitting from the outside, which 954 00:48:08,760 --> 00:48:11,200 Speaker 1: makes him even more dangerous of a player. So he's 955 00:48:11,239 --> 00:48:16,279 Speaker 1: probably been compared more to Lebron. I'm pronouncing his name wrong. 956 00:48:16,800 --> 00:48:19,719 Speaker 1: Is he going to be more liking Honest or Lebron? Well, 957 00:48:19,760 --> 00:48:22,520 Speaker 1: he's always been compared with Lebron because their body types 958 00:48:22,520 --> 00:48:24,680 Speaker 1: are kind of similar. Lebron's a little bigger, though, isn't it. 959 00:48:24,800 --> 00:48:28,279 Speaker 1: Oh yeah, what? But but like cooler, bigger, thick, Oh 960 00:48:28,320 --> 00:48:30,919 Speaker 1: my god, he's like girthy. Right. The thing I think 961 00:48:31,000 --> 00:48:33,640 Speaker 1: that makes him like Janice is that they're closer to 962 00:48:33,680 --> 00:48:37,000 Speaker 1: the same age and they belong to similar generations. So 963 00:48:37,320 --> 00:48:39,440 Speaker 1: the amazing thing about Jannice this year is that he's 964 00:48:39,480 --> 00:48:41,680 Speaker 1: probably going to win the MVP Award for the second 965 00:48:41,719 --> 00:48:44,200 Speaker 1: year in a row, and he's averaging about thirty minutes 966 00:48:44,239 --> 00:48:46,279 Speaker 1: per game. There forty eight minutes in an NBA game, 967 00:48:46,400 --> 00:48:48,120 Speaker 1: which means that he's only playing thirty minutes and he's 968 00:48:48,120 --> 00:48:50,040 Speaker 1: putting up stats that he's going to win the m 969 00:48:50,080 --> 00:48:54,480 Speaker 1: v p UH. In his first few years, Lebron played 970 00:48:54,520 --> 00:48:58,080 Speaker 1: like forty two minutes. And I think what makes Zion 971 00:48:58,160 --> 00:49:00,759 Speaker 1: more like Janice than Lebron is that his minutes are 972 00:49:00,800 --> 00:49:03,200 Speaker 1: always going to be monitored for his career, because of 973 00:49:03,239 --> 00:49:04,960 Speaker 1: his body type, because of his age, because of the 974 00:49:05,000 --> 00:49:07,239 Speaker 1: way the NBA has played today, He's gonna play like 975 00:49:07,320 --> 00:49:09,680 Speaker 1: thirty two thirty three minutes, and that means that, like 976 00:49:09,719 --> 00:49:13,280 Speaker 1: in the playoffs, hopefully he will be fresher, so fresher. 977 00:49:13,400 --> 00:49:15,560 Speaker 1: You also want to maintain the A c L as 978 00:49:15,600 --> 00:49:18,480 Speaker 1: a problem, maintain the Achilles. Like when you look at 979 00:49:18,480 --> 00:49:21,280 Speaker 1: the injuries that people in the NBA tend to get, 980 00:49:21,719 --> 00:49:24,319 Speaker 1: they seem to come in different waves. Is the game 981 00:49:24,440 --> 00:49:28,800 Speaker 1: changes there overuse injuries. We're not used to seven footers 982 00:49:28,880 --> 00:49:31,239 Speaker 1: jumping out and trying to guard three pointers and having 983 00:49:31,239 --> 00:49:33,360 Speaker 1: to be as mobile as you do now. So um, 984 00:49:33,400 --> 00:49:35,160 Speaker 1: I think we're still learning a lot about that. Like 985 00:49:35,200 --> 00:49:38,040 Speaker 1: I think even the smartest teams know that they don't 986 00:49:38,080 --> 00:49:41,000 Speaker 1: know all that much about injuries and injury prevention and 987 00:49:41,040 --> 00:49:44,160 Speaker 1: like wearables and biometrics like this in some ways is 988 00:49:44,200 --> 00:49:46,319 Speaker 1: the next frontier of all of this stuff. So who 989 00:49:46,320 --> 00:49:49,640 Speaker 1: do you think is the most interesting person in the league? 990 00:49:49,760 --> 00:49:53,000 Speaker 1: And I'm gonna ask you that for players and for 991 00:49:53,160 --> 00:49:57,520 Speaker 1: coaches or executives. Interesting in what sense? In any sense 992 00:49:57,560 --> 00:50:01,120 Speaker 1: you choose Interesting in terms of their impact on the game, 993 00:50:01,600 --> 00:50:04,800 Speaker 1: interesting in their potential. Well, you know, the real answer 994 00:50:04,800 --> 00:50:06,640 Speaker 1: is Steph Curry because I just love watching him. I 995 00:50:06,680 --> 00:50:09,080 Speaker 1: still find him just thrilling to watch. But but I 996 00:50:09,120 --> 00:50:12,040 Speaker 1: actually the most interesting guys in the league are the 997 00:50:12,080 --> 00:50:15,800 Speaker 1: ones who were misvalued for some reason, and the evolution 998 00:50:15,800 --> 00:50:19,640 Speaker 1: of the game um has changed their value in the 999 00:50:19,719 --> 00:50:22,239 Speaker 1: league and the premium that teams put on them, and 1000 00:50:22,280 --> 00:50:24,799 Speaker 1: so that tends to be like three point shooters and 1001 00:50:24,840 --> 00:50:27,200 Speaker 1: so not the step Curry types, almost like the like 1002 00:50:27,239 --> 00:50:29,160 Speaker 1: the Steve Kerr player types. So I've written a lot 1003 00:50:29,200 --> 00:50:31,480 Speaker 1: about these guys. I've written about Duncan Robinson with the 1004 00:50:31,520 --> 00:50:34,120 Speaker 1: Miami Heat, who went to a small high school in 1005 00:50:34,120 --> 00:50:37,239 Speaker 1: New Hampshire. He went to Exeter Academy. He went to 1006 00:50:37,280 --> 00:50:40,360 Speaker 1: Williams College D three Williams College in the nest Gag 1007 00:50:40,560 --> 00:50:44,120 Speaker 1: transferred to Michigan when undrafted, played in the G League, 1008 00:50:44,320 --> 00:50:46,920 Speaker 1: and now is the single best three point shooter in 1009 00:50:46,960 --> 00:50:50,040 Speaker 1: the NBA. And it's a guy who, like, you know, 1010 00:50:50,840 --> 00:50:54,480 Speaker 1: basically the whole sport changed and he adapted, and suddenly 1011 00:50:54,560 --> 00:50:57,920 Speaker 1: he becomes this really valuable player. Did he adapt? Did 1012 00:50:57,920 --> 00:51:01,160 Speaker 1: the sports change to exactly what he was? The sport 1013 00:51:01,239 --> 00:51:04,799 Speaker 1: evolved into his favor right, and so um, you know, 1014 00:51:04,920 --> 00:51:08,040 Speaker 1: it's it's his story is really a fairy tale, right. 1015 00:51:08,080 --> 00:51:10,440 Speaker 1: But to me, what made it so interesting was that 1016 00:51:10,920 --> 00:51:13,160 Speaker 1: it's a case study in economics, right, and how we 1017 00:51:13,200 --> 00:51:16,120 Speaker 1: think about how we value players. Not too long ago, 1018 00:51:16,280 --> 00:51:19,399 Speaker 1: Duncan Robinson was not valued all that highly. Now like 1019 00:51:19,520 --> 00:51:22,360 Speaker 1: every team needs to Duncan Robinson. And that's the same 1020 00:51:22,400 --> 00:51:25,600 Speaker 1: sort of um progression that took place in the NFL 1021 00:51:26,160 --> 00:51:29,080 Speaker 1: with that Michael Lewis wrote about with the blind Side, 1022 00:51:29,400 --> 00:51:31,920 Speaker 1: where there was an off tackle that was never an 1023 00:51:31,960 --> 00:51:36,760 Speaker 1: important UM role and then suddenly protecting the quarterback becomes 1024 00:51:36,800 --> 00:51:40,000 Speaker 1: so much more important following some rule changes and some 1025 00:51:40,280 --> 00:51:43,440 Speaker 1: just generally the way the game changed, same sort of thing. 1026 00:51:43,520 --> 00:51:46,799 Speaker 1: Suddenly what was you know, a league minimum salary role 1027 00:51:46,880 --> 00:51:50,040 Speaker 1: becomes a three four or five million dollar role. He 1028 00:51:50,200 --> 00:51:54,200 Speaker 1: got really lucky that this evolved right into his sweet spot. 1029 00:51:54,280 --> 00:51:56,279 Speaker 1: So so that's a player well, and the team's got 1030 00:51:56,360 --> 00:51:58,520 Speaker 1: lucky too, because the only way to win in professional 1031 00:51:58,520 --> 00:52:01,359 Speaker 1: sports now is to find the nf agiencies in the market, right, 1032 00:52:01,520 --> 00:52:04,960 Speaker 1: Sometimes that's the valuable role players. If if there's a 1033 00:52:05,200 --> 00:52:08,080 Speaker 1: um cap, if there's a salary correct, and you know, 1034 00:52:08,239 --> 00:52:11,520 Speaker 1: the greatest inefficiency are the superstars, right because in an 1035 00:52:11,520 --> 00:52:13,759 Speaker 1: open market, Lebron James is worth a whole lot more 1036 00:52:13,800 --> 00:52:16,640 Speaker 1: money than he's paid right now, right because his salary 1037 00:52:16,800 --> 00:52:19,200 Speaker 1: is capped. Of course, Like that's why you want superstars 1038 00:52:19,280 --> 00:52:21,839 Speaker 1: is because like you know, you don't you can't throw 1039 00:52:21,960 --> 00:52:24,239 Speaker 1: enough money at them. It doesn't matter Lebron James makes 1040 00:52:24,239 --> 00:52:26,960 Speaker 1: what thirty five million dollars a year, he's really a bargain, 1041 00:52:27,160 --> 00:52:29,520 Speaker 1: right because relative to what it means to the l 1042 00:52:29,560 --> 00:52:33,319 Speaker 1: A Lakers revenues no like relative to when you are 1043 00:52:33,360 --> 00:52:35,920 Speaker 1: building a team in the NBA, because there are a 1044 00:52:35,960 --> 00:52:37,839 Speaker 1: lot of other players who make thirty five million dollars 1045 00:52:37,880 --> 00:52:39,359 Speaker 1: a year because it's the most that you can pay, 1046 00:52:39,800 --> 00:52:42,319 Speaker 1: Like in an open market, what a team would give 1047 00:52:42,400 --> 00:52:44,719 Speaker 1: Lebron seventy five million dollars a hundred million dollars right, 1048 00:52:44,719 --> 00:52:46,760 Speaker 1: even if it were an open market in a cap 1049 00:52:46,800 --> 00:52:49,440 Speaker 1: system where the team had a salary cap but the 1050 00:52:49,480 --> 00:52:51,680 Speaker 1: players didn't and you could offer them whatever you want. 1051 00:52:51,680 --> 00:52:53,040 Speaker 1: You can make a case that, like, if there were 1052 00:52:53,080 --> 00:52:55,280 Speaker 1: a hundred million dollars salary cap, you should give Lebron 1053 00:52:55,360 --> 00:52:58,560 Speaker 1: ninety million dollars, right and just filling in with everybody else, 1054 00:52:58,880 --> 00:53:00,879 Speaker 1: and so like million dollars up stars are the great 1055 00:53:00,880 --> 00:53:03,880 Speaker 1: inefficiency and and that's what basketball teams believe. But there 1056 00:53:03,880 --> 00:53:05,839 Speaker 1: are other ways to find value. And it's to find 1057 00:53:05,920 --> 00:53:07,920 Speaker 1: value on the margins. It's to get those guys like 1058 00:53:08,040 --> 00:53:10,520 Speaker 1: Duncan Robinson and Shane Daddier, like guys who are not 1059 00:53:10,680 --> 00:53:13,440 Speaker 1: valued the way the markets suggests they should be. So 1060 00:53:13,520 --> 00:53:17,440 Speaker 1: there was another reference in the book that cracked me up. Um, 1061 00:53:17,600 --> 00:53:21,320 Speaker 1: George Steinbrenner and the Harlem Globe Trotters changed the NBA. 1062 00:53:22,360 --> 00:53:24,520 Speaker 1: You're gonna have to explain that because listeners are going 1063 00:53:24,560 --> 00:53:26,839 Speaker 1: to think they misheard that. It has to do with 1064 00:53:26,880 --> 00:53:29,719 Speaker 1: the formation of the three point line, Like the three 1065 00:53:29,719 --> 00:53:32,120 Speaker 1: point line did not always exist in basketball. It seems 1066 00:53:32,160 --> 00:53:34,960 Speaker 1: so fundamental to how the game is played today. But 1067 00:53:35,160 --> 00:53:40,000 Speaker 1: somebody dropped somebody dropped a line on the court, this 1068 00:53:40,160 --> 00:53:43,239 Speaker 1: little strip of tape and decided shots from inside will 1069 00:53:43,280 --> 00:53:45,520 Speaker 1: be worth two points and shots from outside will be 1070 00:53:45,560 --> 00:53:48,600 Speaker 1: worth three points. And I misremembered this when I had 1071 00:53:48,640 --> 00:53:51,840 Speaker 1: my conversation with Daryl Maury. I thought it was in 1072 00:53:52,000 --> 00:53:55,680 Speaker 1: college first, but it wasn't. It started in the NBA first. 1073 00:53:55,840 --> 00:53:58,200 Speaker 1: It actually started in a basketball league called the American 1074 00:53:58,200 --> 00:54:02,040 Speaker 1: Basketball League, which predated the America Basketball Association, which then 1075 00:54:02,120 --> 00:54:04,239 Speaker 1: merged with the m b A, and so in the 1076 00:54:04,280 --> 00:54:07,400 Speaker 1: a b L in the nineteen sixties, this short lived 1077 00:54:07,600 --> 00:54:10,480 Speaker 1: Doomed Basketball League that was run by the founder of 1078 00:54:10,480 --> 00:54:13,200 Speaker 1: the Harlem Globe Trotters. They were the first to experiment 1079 00:54:13,239 --> 00:54:16,399 Speaker 1: with the three point line in a professional league. And 1080 00:54:16,520 --> 00:54:18,640 Speaker 1: there were eight teams in this league. And who was 1081 00:54:18,680 --> 00:54:21,120 Speaker 1: one of the owners of this doomed Basketball league but 1082 00:54:21,120 --> 00:54:23,960 Speaker 1: George Steinbrenner before he bought the New York Yankees. And 1083 00:54:24,000 --> 00:54:26,360 Speaker 1: which team did he own? He owned the Cleveland Pipers, 1084 00:54:26,680 --> 00:54:29,640 Speaker 1: And there was this discussion in one of their meetings. 1085 00:54:29,640 --> 00:54:31,680 Speaker 1: A couple of weeks ago, I went down and found 1086 00:54:31,719 --> 00:54:34,120 Speaker 1: these papers in this archive at the University of Texas 1087 00:54:34,200 --> 00:54:36,480 Speaker 1: that sort of showed how this league was formed, and 1088 00:54:36,520 --> 00:54:38,200 Speaker 1: the guy who started the league was this guy named 1089 00:54:38,239 --> 00:54:41,440 Speaker 1: Abe Sapperstein, who was this visionary marketing whiz behind the 1090 00:54:41,440 --> 00:54:44,160 Speaker 1: Harlem Globe Trotters. He also started the A B L 1091 00:54:44,600 --> 00:54:47,399 Speaker 1: and uh he had so much power that one day 1092 00:54:47,480 --> 00:54:49,759 Speaker 1: he missed one of their meetings where all of the 1093 00:54:49,760 --> 00:54:53,160 Speaker 1: owners came to be and Uh. They decided that they 1094 00:54:53,160 --> 00:54:55,320 Speaker 1: would try to strike back at some of his power 1095 00:54:55,640 --> 00:54:58,760 Speaker 1: by eliminating the three point line. So they took a vote, 1096 00:54:58,960 --> 00:55:01,359 Speaker 1: do we think like we should have a three point line? 1097 00:55:01,560 --> 00:55:03,400 Speaker 1: And if we do, like, where should it be? Should 1098 00:55:03,440 --> 00:55:05,719 Speaker 1: it be at twenty three ft? Should it be at 1099 00:55:05,800 --> 00:55:08,560 Speaker 1: twenty ft? Like? Where exactly? And they decided to move 1100 00:55:08,560 --> 00:55:11,200 Speaker 1: the three point line in, so three ft they move 1101 00:55:11,239 --> 00:55:13,719 Speaker 1: it in. They have this vote. Steinbrunner votes against it. 1102 00:55:13,760 --> 00:55:15,759 Speaker 1: He says keep it where Sapristein wants it to be. 1103 00:55:16,000 --> 00:55:19,120 Speaker 1: But it passes by a fourth three margin. Sapperstein comes 1104 00:55:19,120 --> 00:55:21,960 Speaker 1: back to the next meeting just completely ignores what happened 1105 00:55:22,000 --> 00:55:25,000 Speaker 1: in his absence and set the line at three ft 1106 00:55:25,239 --> 00:55:27,200 Speaker 1: nine inches away from the center of the basket. And 1107 00:55:27,239 --> 00:55:29,840 Speaker 1: where is the three point line in the NBA today? 1108 00:55:29,520 --> 00:55:31,640 Speaker 1: Twenty three ft and nine inches away from the basket. 1109 00:55:31,719 --> 00:55:34,359 Speaker 1: It's exactly where A sa Perstein decided it should be 1110 00:55:34,640 --> 00:55:37,680 Speaker 1: sixty years ago. That that that's quite fascinating. You would 1111 00:55:37,719 --> 00:55:41,919 Speaker 1: never guess that Stone Brenner has impacted not just Major 1112 00:55:42,000 --> 00:55:46,239 Speaker 1: League Baseball, but the NBA as well. There was a 1113 00:55:46,280 --> 00:55:51,000 Speaker 1: stat in your book that I found completely and totally insane, 1114 00:55:51,040 --> 00:55:53,000 Speaker 1: and I have to ask you about this, which one 1115 00:55:53,440 --> 00:55:57,520 Speaker 1: the Warriors have outscored their opponents by more than four 1116 00:55:57,600 --> 00:56:01,640 Speaker 1: thousand points in curries minutes, in other words, when Steph 1117 00:56:01,640 --> 00:56:04,520 Speaker 1: Curry is on the floor over the past five years. 1118 00:56:04,920 --> 00:56:09,200 Speaker 1: Talking about plus minus that has generated an advantage for 1119 00:56:09,239 --> 00:56:13,799 Speaker 1: the Golden State Warriors of plus four thousand points. That 1120 00:56:14,080 --> 00:56:18,000 Speaker 1: can't possibly be right. That's just are you questioning my math? 1121 00:56:18,120 --> 00:56:21,600 Speaker 1: Absolutely insane, It is insane. And the most insane thing 1122 00:56:21,600 --> 00:56:23,839 Speaker 1: about it is that I believe they are being outscored 1123 00:56:23,880 --> 00:56:25,600 Speaker 1: by the other team when Steph Curry is not on 1124 00:56:25,640 --> 00:56:28,360 Speaker 1: the court, right, So they're negative when he's not on 1125 00:56:28,400 --> 00:56:30,880 Speaker 1: the court. There their plus four thousand when he's on 1126 00:56:30,920 --> 00:56:33,080 Speaker 1: the court, and the other team beats them when he's 1127 00:56:33,080 --> 00:56:35,080 Speaker 1: off the court. And so that just shows it shows 1128 00:56:35,120 --> 00:56:38,640 Speaker 1: like this incredible force that Steph Curry has become so 1129 00:56:38,760 --> 00:56:43,040 Speaker 1: his plus minus has to be just crazy. If that's 1130 00:56:43,080 --> 00:56:46,320 Speaker 1: the case. Yeah, and that it's it speaks to um 1131 00:56:46,719 --> 00:56:48,960 Speaker 1: why it was so brilliant to build a team around him, 1132 00:56:49,000 --> 00:56:51,240 Speaker 1: Like nobody thought that you could or that you should, 1133 00:56:51,320 --> 00:56:54,479 Speaker 1: and the Warriors have proved everybody wrong. So so let's 1134 00:56:54,480 --> 00:56:56,880 Speaker 1: talk about some you mentioned going down to Texas and 1135 00:56:56,920 --> 00:57:00,120 Speaker 1: doing some research. Who was the most interesting post and 1136 00:57:00,200 --> 00:57:03,160 Speaker 1: you spoke to when you were recently researching this? And 1137 00:57:03,200 --> 00:57:06,240 Speaker 1: by interesting, I mean who is the most surprising person 1138 00:57:06,760 --> 00:57:09,640 Speaker 1: that you came away from the conversation with m I 1139 00:57:09,719 --> 00:57:12,360 Speaker 1: really didn't expect that. I talked to a lot of 1140 00:57:12,360 --> 00:57:14,440 Speaker 1: interesting people. I talked to Steph Curry. I talked to 1141 00:57:14,640 --> 00:57:18,240 Speaker 1: Eugene Fama, I talked to David booth Um, Tom Gilovich, 1142 00:57:18,360 --> 00:57:20,680 Speaker 1: these all of these So I haven't had stuff Curry on. 1143 00:57:20,760 --> 00:57:22,800 Speaker 1: But that's my that's my list right there. That's your 1144 00:57:22,800 --> 00:57:26,360 Speaker 1: bucket list. One bucket list that's checked off staff is 1145 00:57:26,360 --> 00:57:28,880 Speaker 1: on the bucket list. I have to say, one of 1146 00:57:28,920 --> 00:57:30,840 Speaker 1: the most interesting people I talked to is a guy 1147 00:57:30,920 --> 00:57:32,960 Speaker 1: named Nick Hagan, who I don't think you've had on 1148 00:57:32,960 --> 00:57:35,400 Speaker 1: this show. I have not. Nick Hagan is a fifth 1149 00:57:35,400 --> 00:57:38,720 Speaker 1: generation sugar Beet farmer on the border of Minnesota and 1150 00:57:38,720 --> 00:57:40,680 Speaker 1: North Dakota, and I took a trip out to his 1151 00:57:40,760 --> 00:57:44,400 Speaker 1: farm because um I wanted to know, like, do farmers 1152 00:57:44,440 --> 00:57:46,400 Speaker 1: believe in the hot hand? Like this is one of 1153 00:57:46,440 --> 00:57:49,760 Speaker 1: the reasons why this is one of the reasons why 1154 00:57:49,800 --> 00:57:51,960 Speaker 1: people have studied the hot hand, is because it applies 1155 00:57:52,000 --> 00:57:54,480 Speaker 1: to all these different industries. And so um I went 1156 00:57:54,480 --> 00:57:58,080 Speaker 1: out there during wheat harvest. And Nick is this fascinating 1157 00:57:58,120 --> 00:58:01,040 Speaker 1: guy because his family has been in the farming business 1158 00:58:01,160 --> 00:58:04,320 Speaker 1: for five generations, right going back to his great great 1159 00:58:04,360 --> 00:58:07,640 Speaker 1: grandfather in the middle of the d and yet he 1160 00:58:07,720 --> 00:58:10,040 Speaker 1: didn't think that he would enter the family business. He 1161 00:58:10,160 --> 00:58:13,280 Speaker 1: was a trombonist. He came to Juilliard to play music 1162 00:58:13,520 --> 00:58:15,720 Speaker 1: before he finally decided, actually, I do want to go 1163 00:58:15,760 --> 00:58:18,160 Speaker 1: back into the family business and moved back to this farm. 1164 00:58:18,280 --> 00:58:21,840 Speaker 1: And what he told me was like music and farming 1165 00:58:21,880 --> 00:58:24,320 Speaker 1: and basketball couldn't be any more different. Like music is 1166 00:58:24,360 --> 00:58:27,400 Speaker 1: more like basketball than it is like farming. So in 1167 00:58:27,920 --> 00:58:30,840 Speaker 1: basketball the court is always the same, right, like you 1168 00:58:30,920 --> 00:58:34,320 Speaker 1: know the parameters, and farming it's always moving. So like 1169 00:58:34,520 --> 00:58:37,160 Speaker 1: if the basketball court is a rectangle, farming is like 1170 00:58:37,200 --> 00:58:38,680 Speaker 1: one day it could be a rhombus, and the next 1171 00:58:38,760 --> 00:58:40,360 Speaker 1: day it could be a trapezoid, and the next day 1172 00:58:40,360 --> 00:58:41,920 Speaker 1: it could be a triangle. Is that a function of 1173 00:58:42,000 --> 00:58:45,800 Speaker 1: whether the market for the crops? Everything you do not 1174 00:58:45,960 --> 00:58:48,440 Speaker 1: have control. And so what he has learned is that 1175 00:58:48,760 --> 00:58:51,760 Speaker 1: basketball is about playing offense, right, farming is about playing 1176 00:58:51,800 --> 00:58:54,439 Speaker 1: defense and trying to play the long game. And keep 1177 00:58:54,480 --> 00:58:57,440 Speaker 1: in mind like all of these lessons that you've learned 1178 00:58:57,480 --> 00:59:00,560 Speaker 1: for all of these years. So like he doesn't chase patterns. 1179 00:59:00,600 --> 00:59:02,240 Speaker 1: He doesn't believe in the hot hand, even though he 1180 00:59:02,280 --> 00:59:04,160 Speaker 1: does believe in the hot and he doesn't behave as 1181 00:59:04,160 --> 00:59:06,680 Speaker 1: if he believes in the hot hand. Um, what he 1182 00:59:06,760 --> 00:59:10,440 Speaker 1: does is he trusts principles instead of chasing patterns. And 1183 00:59:10,840 --> 00:59:13,320 Speaker 1: to me, like, you know, I could talk to academics 1184 00:59:13,320 --> 00:59:15,760 Speaker 1: like I've been in NBA locker rooms, I've never been 1185 00:59:15,880 --> 00:59:18,080 Speaker 1: on a sugar beet farm before. And that was one 1186 00:59:18,120 --> 00:59:20,000 Speaker 1: of like the most thrilling parts of this book for me. 1187 00:59:20,640 --> 00:59:23,920 Speaker 1: So last question before we get to our favorite questions. 1188 00:59:24,760 --> 00:59:29,080 Speaker 1: You're simultaneously writing a book and working for the journal 1189 00:59:29,120 --> 00:59:32,720 Speaker 1: full time writing a column. Lots of folks have said 1190 00:59:32,800 --> 00:59:36,040 Speaker 1: that's impossible to do. You have to take time off. 1191 00:59:36,360 --> 00:59:39,040 Speaker 1: How are you able to balance both of those. It's 1192 00:59:39,080 --> 00:59:43,280 Speaker 1: not easy to write a book while you're also writing 1193 00:59:43,320 --> 00:59:48,280 Speaker 1: columns that are, if not on the same topics, certainly 1194 00:59:48,320 --> 00:59:51,280 Speaker 1: similar topics to what you're covering in the book. A 1195 00:59:51,320 --> 00:59:55,800 Speaker 1: lot of early mornings and long weekends and not taking vacation. 1196 00:59:56,000 --> 00:59:58,720 Speaker 1: And I realized not too long ago that I haven't 1197 00:59:58,720 --> 01:00:00,880 Speaker 1: watched much television over the course of the last two 1198 01:00:00,960 --> 01:00:04,240 Speaker 1: or third Yeah, and so, um so there was that 1199 01:00:04,520 --> 01:00:06,320 Speaker 1: I gave myself a lot of time to write the book. 1200 01:00:06,320 --> 01:00:08,479 Speaker 1: It was like eighteen months from start to finish of 1201 01:00:08,480 --> 01:00:10,680 Speaker 1: of writing. Um So, it was just sort of trying 1202 01:00:10,680 --> 01:00:13,280 Speaker 1: to find time whenever I could. But I have to say, 1203 01:00:13,320 --> 01:00:15,320 Speaker 1: like I think that writing a book made me better 1204 01:00:15,440 --> 01:00:17,720 Speaker 1: at writing stories for the wallstre Journal. It was sort 1205 01:00:17,720 --> 01:00:19,920 Speaker 1: of like cross training in a sentence, like it just 1206 01:00:19,960 --> 01:00:22,080 Speaker 1: accessed a different part of my brain that was fun 1207 01:00:22,120 --> 01:00:24,200 Speaker 1: to play with that I never really get to exercise 1208 01:00:24,240 --> 01:00:27,400 Speaker 1: all that much. Quite interesting. I have to tell you, 1209 01:00:27,520 --> 01:00:31,200 Speaker 1: I approached this book in with great trepidation for a 1210 01:00:31,240 --> 01:00:36,760 Speaker 1: couple of reasons. First, I had already had Kanaman and 1211 01:00:36,920 --> 01:00:40,680 Speaker 1: Gilovich and Miller and whole run of people on and second, 1212 01:00:41,240 --> 01:00:45,640 Speaker 1: I really enjoyed the story you wrote about um Adam 1213 01:00:45,680 --> 01:00:49,400 Speaker 1: and Josh about their paper, and I'm like, oh, I 1214 01:00:49,440 --> 01:00:51,480 Speaker 1: hope this book doesn't suck, because every now and then 1215 01:00:51,520 --> 01:00:54,000 Speaker 1: I'll start a book and I'm like, yeah, I can't 1216 01:00:54,040 --> 01:00:57,480 Speaker 1: finish this. But I really liked it, and I plowed 1217 01:00:57,480 --> 01:01:00,960 Speaker 1: through it, and you did a really nice job taking 1218 01:01:00,960 --> 01:01:06,600 Speaker 1: what's essentially this narrow, wonky academic theory and turned it 1219 01:01:06,600 --> 01:01:11,840 Speaker 1: into a compelling two pages worth of a discussion. It's 1220 01:01:11,840 --> 01:01:14,480 Speaker 1: a great narrative. Well, thank you, thank you for overcoming 1221 01:01:14,480 --> 01:01:17,720 Speaker 1: your trepidation, and I'm glad that it didn't suck. Um, 1222 01:01:17,760 --> 01:01:20,760 Speaker 1: it really didn't suck it. First of all, I did 1223 01:01:20,800 --> 01:01:23,960 Speaker 1: say it's it's good wonky beach Rena because because it was. 1224 01:01:24,040 --> 01:01:27,920 Speaker 1: I'm like, it's interesting enough, and it's told in a 1225 01:01:28,840 --> 01:01:33,480 Speaker 1: sort of the inherent tention. Um, I think the tension 1226 01:01:33,520 --> 01:01:35,920 Speaker 1: resolves itself towards the ends. Well, it's funny. I think 1227 01:01:35,920 --> 01:01:37,840 Speaker 1: writing for the wall Stree Journal actually gives me good 1228 01:01:37,920 --> 01:01:40,640 Speaker 1: training for this, because when I write about sports for 1229 01:01:40,680 --> 01:01:43,200 Speaker 1: the journal, I write for people who know everything about 1230 01:01:43,200 --> 01:01:45,680 Speaker 1: sports and nothing about which is not easy to do. Yeah, 1231 01:01:45,720 --> 01:01:47,160 Speaker 1: and so you have to thread that needle. And that's 1232 01:01:47,200 --> 01:01:48,680 Speaker 1: what I wanted to do with this book. I wanted 1233 01:01:48,720 --> 01:01:51,400 Speaker 1: it to be entertaining to people who knew the saga 1234 01:01:51,440 --> 01:01:53,439 Speaker 1: of the hot hand, and also people who don't even 1235 01:01:53,440 --> 01:01:56,040 Speaker 1: know what the hot hand is. UM, And so that 1236 01:01:56,080 --> 01:01:58,520 Speaker 1: meant like trying to reach as broad of an audience 1237 01:01:58,600 --> 01:02:02,040 Speaker 1: as possible without alien aiding that core audience. And if 1238 01:02:02,080 --> 01:02:05,560 Speaker 1: you describe the hothhand simply as streaks, everybody understands what 1239 01:02:05,600 --> 01:02:09,080 Speaker 1: a streak is. It's not it's not that difficult to grasp. 1240 01:02:09,120 --> 01:02:11,280 Speaker 1: But I thought you did a nice book. And I'll 1241 01:02:11,320 --> 01:02:14,360 Speaker 1: repeat on the air what I what I told you earlier. 1242 01:02:14,680 --> 01:02:19,040 Speaker 1: So you know, I always sift through the sources just 1243 01:02:19,120 --> 01:02:22,440 Speaker 1: to see um who they used. And I don't know 1244 01:02:22,440 --> 01:02:24,760 Speaker 1: a lot of people read the acknowledgements, but it's another 1245 01:02:25,160 --> 01:02:27,200 Speaker 1: version of the sources. Well, the best part of the book. 1246 01:02:27,240 --> 01:02:29,439 Speaker 1: You should read the dast that's the secret of any book. 1247 01:02:29,640 --> 01:02:32,480 Speaker 1: And I was shocked to actually find that you mentioned 1248 01:02:32,720 --> 01:02:36,400 Speaker 1: the Masters in Business episode with Gilovich, and that set 1249 01:02:36,440 --> 01:02:39,959 Speaker 1: me back looking through the book. And I just went through, 1250 01:02:40,560 --> 01:02:45,920 Speaker 1: go down the list. They'll are konom and Miller. Um. 1251 01:02:46,000 --> 01:02:47,800 Speaker 1: I think I'm a few years into like a PhD 1252 01:02:47,800 --> 01:02:50,000 Speaker 1: in business from listening to this podcast. Because like, the 1253 01:02:50,000 --> 01:02:51,920 Speaker 1: beautiful thing is that not only have you had all 1254 01:02:51,960 --> 01:02:54,880 Speaker 1: of these luminaries come in here and be really open, 1255 01:02:55,040 --> 01:02:58,240 Speaker 1: but there are transcripts right like you can read these 1256 01:02:58,360 --> 01:03:01,320 Speaker 1: interviews as if their essays almost their biographies of these 1257 01:03:01,360 --> 01:03:04,440 Speaker 1: really brilliant minds. What what's the only problem with the 1258 01:03:04,480 --> 01:03:07,480 Speaker 1: transcripts is we we don't clean them up. They just 1259 01:03:07,520 --> 01:03:10,560 Speaker 1: get cut and paste uff like that. And very often 1260 01:03:10,640 --> 01:03:16,320 Speaker 1: what sounds normal in a spoken sentence reads terribly And 1261 01:03:16,840 --> 01:03:18,680 Speaker 1: but there are some people who speak in paragraphs, and 1262 01:03:18,680 --> 01:03:20,680 Speaker 1: those people just blow my mind because I don't know 1263 01:03:20,720 --> 01:03:23,240 Speaker 1: how they do that. I had a buddy in grad 1264 01:03:23,280 --> 01:03:27,120 Speaker 1: school who would write when we would have UM some 1265 01:03:27,120 --> 01:03:30,800 Speaker 1: some final exams were essays and some were multiple choice. 1266 01:03:31,280 --> 01:03:34,400 Speaker 1: And his first draft of an essay is better than 1267 01:03:34,440 --> 01:03:38,320 Speaker 1: everybody else's third draft. His the way he thought and 1268 01:03:38,560 --> 01:03:43,000 Speaker 1: constructed something was shout out to Jeff um was so 1269 01:03:44,120 --> 01:03:50,000 Speaker 1: just beautifully done. But just like, listen, the fact is 1270 01:03:50,520 --> 01:03:54,240 Speaker 1: that every draft makes a column better, and you don't 1271 01:03:54,240 --> 01:03:57,720 Speaker 1: have an infinite amount of time to do draft nine seven. 1272 01:03:58,280 --> 01:04:01,280 Speaker 1: It's all right, here's the research, cheers, the rough outline, 1273 01:04:01,560 --> 01:04:04,760 Speaker 1: here's the first pass. Now I'm going back and changing 1274 01:04:04,800 --> 01:04:06,560 Speaker 1: the structure and adding more stuff. And now I'm on 1275 01:04:06,600 --> 01:04:09,280 Speaker 1: the second pass and then usually there's a third or 1276 01:04:09,320 --> 01:04:12,960 Speaker 1: a fourth pass after that. But that's it. You don't 1277 01:04:13,000 --> 01:04:14,920 Speaker 1: have time to do. And I know if you do 1278 01:04:15,040 --> 01:04:19,160 Speaker 1: five more, it just gets that much better, tighter's faster, smarter. 1279 01:04:19,640 --> 01:04:23,160 Speaker 1: But who you You can't do a month for a 1280 01:04:23,200 --> 01:04:29,360 Speaker 1: weekly column. It's a weekly and so that's really the challenge. UM. 1281 01:04:29,400 --> 01:04:32,840 Speaker 1: And and I found that that sort of thing really, uh, 1282 01:04:33,040 --> 01:04:37,960 Speaker 1: really kind of interesting. So if you could speak fluidly 1283 01:04:38,400 --> 01:04:41,200 Speaker 1: the way we write, that would be a great thing. 1284 01:04:41,800 --> 01:04:44,760 Speaker 1: I have a pet theory which Barbara Taverski told me 1285 01:04:45,000 --> 01:04:47,440 Speaker 1: isn't true, or at least she says there's no data 1286 01:04:47,480 --> 01:04:50,000 Speaker 1: that supports it. Maybe it's true, maybe it's not. I 1287 01:04:50,040 --> 01:04:54,160 Speaker 1: think the part of your brain responsible for writing is different, 1288 01:04:54,480 --> 01:04:58,920 Speaker 1: perhaps adjacent to the part of your brain responsible for speaking. 1289 01:04:59,680 --> 01:05:01,840 Speaker 1: I mean, I will say that I think Barbara Tverski 1290 01:05:01,920 --> 01:05:03,920 Speaker 1: knows more about the brain than I know about anything, 1291 01:05:03,960 --> 01:05:07,440 Speaker 1: so I trust her judgment on that. But I do think, um, 1292 01:05:07,480 --> 01:05:10,920 Speaker 1: there is just something about like sometimes I will just 1293 01:05:10,960 --> 01:05:13,760 Speaker 1: sort of dictate things and go back to them later. 1294 01:05:13,840 --> 01:05:16,440 Speaker 1: And what I've learned actually is that, UM, sometimes the 1295 01:05:16,480 --> 01:05:18,240 Speaker 1: easiest way for me to write a story. I can 1296 01:05:18,280 --> 01:05:21,680 Speaker 1: be staring at a screen all day long writing and 1297 01:05:21,840 --> 01:05:24,560 Speaker 1: if I look at that document on my phone on 1298 01:05:24,600 --> 01:05:28,320 Speaker 1: the subway leaving work, it looks totally different and something clicks. 1299 01:05:28,320 --> 01:05:30,760 Speaker 1: It's sort of like that thing where you stare across 1300 01:05:30,760 --> 01:05:33,000 Speaker 1: word for like fifteen minutes and you can't get a 1301 01:05:33,000 --> 01:05:34,919 Speaker 1: few boxes, and you come back to it a few 1302 01:05:34,920 --> 01:05:36,959 Speaker 1: hours later and it's just staring you right in the face, 1303 01:05:37,040 --> 01:05:39,880 Speaker 1: and like you're like, how did I not see this already? 1304 01:05:39,960 --> 01:05:42,840 Speaker 1: Have you ever seen the word jumbles where there's a 1305 01:05:42,880 --> 01:05:46,640 Speaker 1: reset button and it just changes the order of the letters. 1306 01:05:46,680 --> 01:05:49,480 Speaker 1: So so that's on on a phone or on a computer. 1307 01:05:49,600 --> 01:05:51,520 Speaker 1: I have friends who, when they're writing stories, will just 1308 01:05:51,600 --> 01:05:54,040 Speaker 1: change the font of the story as they're writing because 1309 01:05:54,040 --> 01:05:55,880 Speaker 1: it makes them look at it in a completely different 1310 01:05:56,000 --> 01:05:58,240 Speaker 1: So I don't know if you've so you go through 1311 01:05:58,280 --> 01:06:00,680 Speaker 1: an editor when you publish. When I publish ship Bloomberg, 1312 01:06:00,720 --> 01:06:02,960 Speaker 1: I have an editor who does that. When I throw 1313 01:06:03,040 --> 01:06:06,520 Speaker 1: something up on the blog, I'm just completely blind to 1314 01:06:06,560 --> 01:06:09,760 Speaker 1: my own typos, So sometimes I'll ask someone else to 1315 01:06:09,800 --> 01:06:12,440 Speaker 1: give it a quick through and catch some things that 1316 01:06:12,480 --> 01:06:15,800 Speaker 1: I miss. But the technique that's other people have talked 1317 01:06:15,840 --> 01:06:18,720 Speaker 1: about is take what you've written, cut and pasted into 1318 01:06:18,760 --> 01:06:22,520 Speaker 1: a different word document or whatever you're document were, you know, 1319 01:06:22,720 --> 01:06:27,160 Speaker 1: word processor of choices and change the size and the 1320 01:06:27,240 --> 01:06:30,000 Speaker 1: choice of funds, and now you're looking at it with 1321 01:06:30,080 --> 01:06:33,400 Speaker 1: fresh eyes. You're not on different lines, yes, and it's 1322 01:06:33,440 --> 01:06:36,480 Speaker 1: just order. It just changes your ability to see typos 1323 01:06:36,560 --> 01:06:40,080 Speaker 1: and spelling and grammar issues that you completely missed the 1324 01:06:40,120 --> 01:06:42,840 Speaker 1: first time. What some editors that the journal have taught me, like, 1325 01:06:42,880 --> 01:06:45,360 Speaker 1: we fact checked all of our own stories, right, we 1326 01:06:45,400 --> 01:06:47,800 Speaker 1: don't have magazine fact checkers, but you have your own 1327 01:06:47,840 --> 01:06:51,000 Speaker 1: bias there. Well. Sometimes what we do is if I 1328 01:06:51,040 --> 01:06:52,880 Speaker 1: have looked at a story a lot, I will fact 1329 01:06:52,960 --> 01:06:55,320 Speaker 1: check from the bottom up. And so when you just 1330 01:06:55,400 --> 01:06:57,360 Speaker 1: read the story in a different way and you're checking 1331 01:06:57,400 --> 01:06:59,880 Speaker 1: things off as you go, your eyes don't glide over 1332 01:07:00,040 --> 01:07:02,200 Speaker 1: things in the order in which you know they're coming right, 1333 01:07:02,280 --> 01:07:06,720 Speaker 1: because it's flipped completely the opposite way that that's really interesting. 1334 01:07:06,800 --> 01:07:09,120 Speaker 1: So eighteen months in the writing is that? Is that 1335 01:07:09,160 --> 01:07:11,320 Speaker 1: how long you're working on this for the draft? Yeah? 1336 01:07:11,360 --> 01:07:13,400 Speaker 1: I mean what about the research part? Oh yeah, I 1337 01:07:13,440 --> 01:07:16,080 Speaker 1: worked on the proposal for a long time before that, 1338 01:07:16,160 --> 01:07:19,240 Speaker 1: and the research part I hired a research assistant who 1339 01:07:19,600 --> 01:07:22,960 Speaker 1: downloaded every paper ever written about the hot hand and 1340 01:07:23,080 --> 01:07:25,600 Speaker 1: sifted through them and like summarized all of them, so 1341 01:07:25,640 --> 01:07:28,280 Speaker 1: you didn't actually read every page. I read the summaries 1342 01:07:28,280 --> 01:07:30,000 Speaker 1: of all of them, but I read all the major ones. 1343 01:07:30,040 --> 01:07:32,280 Speaker 1: So I have I have in my apartment to like 1344 01:07:32,760 --> 01:07:37,320 Speaker 1: five page binders with double sided printing of like every 1345 01:07:37,480 --> 01:07:40,800 Speaker 1: scholarly paper ever written about the hot hand, because I 1346 01:07:40,840 --> 01:07:43,240 Speaker 1: wanted to like be really fluent in the literature and 1347 01:07:43,320 --> 01:07:47,920 Speaker 1: not miss anything. So when when you talk about first 1348 01:07:47,960 --> 01:07:49,880 Speaker 1: we believe this, and then we believe that, now we 1349 01:07:49,920 --> 01:07:52,360 Speaker 1: believe this, is it really more of sort of a 1350 01:07:52,440 --> 01:07:55,600 Speaker 1: pendulum swing. It goes from one extreme, then it goes 1351 01:07:55,640 --> 01:07:57,120 Speaker 1: to the other, and then when it comes back, it 1352 01:07:57,160 --> 01:07:59,560 Speaker 1: doesn't quite come back as far, and maybe it settles, 1353 01:07:59,560 --> 01:08:04,600 Speaker 1: and eventually we come up with some understanding and neither. 1354 01:08:05,040 --> 01:08:08,200 Speaker 1: So the initial paper clearly we see patterns where there 1355 01:08:08,240 --> 01:08:11,080 Speaker 1: are none, even if the math is wrong about the basketball. 1356 01:08:11,320 --> 01:08:14,400 Speaker 1: And then the pushback, Hey, but the math is wrong 1357 01:08:14,720 --> 01:08:17,160 Speaker 1: doesn't mean the underlying thesis is wrong. But there is 1358 01:08:17,200 --> 01:08:20,639 Speaker 1: a hot hand, um, And then it kind of comes back, well, 1359 01:08:20,680 --> 01:08:23,040 Speaker 1: there's a hot hand, but we weren't looking at how 1360 01:08:23,040 --> 01:08:25,759 Speaker 1: difficult the shot was. We weren't looking at the defense 1361 01:08:25,800 --> 01:08:28,600 Speaker 1: of intensity, and that changes the number. And then a 1362 01:08:28,600 --> 01:08:30,680 Speaker 1: few years later, oh, now we have the ability to 1363 01:08:30,760 --> 01:08:34,000 Speaker 1: look at that and the pendulum swinging because of forces 1364 01:08:34,040 --> 01:08:37,680 Speaker 1: beyond our control. So the first meaning technology or the 1365 01:08:37,760 --> 01:08:39,759 Speaker 1: data that we have right, I mean, the first paper 1366 01:08:39,840 --> 01:08:43,400 Speaker 1: was written using the best data that was available back then, 1367 01:08:43,560 --> 01:08:46,240 Speaker 1: which was terrible. Statis looks primitive now, but at the 1368 01:08:46,280 --> 01:08:48,400 Speaker 1: time it was cutting edge. Like the reason they were 1369 01:08:48,439 --> 01:08:50,880 Speaker 1: able to write this paper that the Philadelphia has seventy 1370 01:08:50,920 --> 01:08:54,040 Speaker 1: sixers had a statistician. He was the only person who 1371 01:08:54,120 --> 01:08:57,519 Speaker 1: took note of the chronology of shots, so he knew 1372 01:08:57,640 --> 01:08:59,840 Speaker 1: like what you would do after you made a shot, 1373 01:09:00,080 --> 01:09:02,240 Speaker 1: or you made two shots or three shots. Nobody else 1374 01:09:02,280 --> 01:09:04,160 Speaker 1: was doing at the time. That seems crazy now because 1375 01:09:04,200 --> 01:09:06,120 Speaker 1: we know everything there is to know about any given 1376 01:09:06,120 --> 01:09:08,000 Speaker 1: shot in the NBA, right and we can look back 1377 01:09:08,080 --> 01:09:10,960 Speaker 1: many years and figure out anything we might want to know. 1378 01:09:11,080 --> 01:09:13,320 Speaker 1: But that wasn't available back then. The data that we 1379 01:09:13,360 --> 01:09:16,360 Speaker 1: have now was not available to the researchers in like 1380 01:09:16,400 --> 01:09:19,519 Speaker 1: their nerdiest wonkiest, wildest dreams or else they would have 1381 01:09:19,560 --> 01:09:22,200 Speaker 1: used it because they did so the seventy sixers had 1382 01:09:22,200 --> 01:09:24,680 Speaker 1: a statistician and no other team did. Was that was 1383 01:09:24,720 --> 01:09:26,800 Speaker 1: that close to dr J? What? Why? You know? I 1384 01:09:26,840 --> 01:09:29,280 Speaker 1: don't know. I think this guy named Harvey Pollock was 1385 01:09:29,360 --> 01:09:32,639 Speaker 1: just sort of, uh, you know, one of his own. 1386 01:09:32,800 --> 01:09:35,559 Speaker 1: He was like a man before his time, and he 1387 01:09:35,600 --> 01:09:38,000 Speaker 1: was nicknamed superstat like everybody knew. He was like the 1388 01:09:38,080 --> 01:09:42,040 Speaker 1: towering figure in analytics before analytics was like this buzzword 1389 01:09:42,200 --> 01:09:45,639 Speaker 1: in sports, and yet it took decades to catch on. 1390 01:09:46,200 --> 01:09:49,360 Speaker 1: That's right, quite quite shocking. So I could keep you 1391 01:09:49,640 --> 01:09:51,439 Speaker 1: all day, but I know I have to get to 1392 01:09:51,520 --> 01:09:54,599 Speaker 1: some of my favorite questions before we let you go. 1393 01:09:55,320 --> 01:09:57,719 Speaker 1: And I'm not going to ask you what you're streaming 1394 01:09:57,720 --> 01:10:00,160 Speaker 1: you're listening, because I know you're not watching t V 1395 01:10:00,760 --> 01:10:02,840 Speaker 1: and I know some of the podcasts you've listened to. 1396 01:10:03,320 --> 01:10:05,639 Speaker 1: So instead, can I even ask you what your first 1397 01:10:05,680 --> 01:10:09,160 Speaker 1: car was? Did you ever own a car? I drove 1398 01:10:09,400 --> 01:10:12,280 Speaker 1: a nineties seven four Runner in high school and college 1399 01:10:12,320 --> 01:10:14,800 Speaker 1: that used to be my dad's solid Toyota Truit. But 1400 01:10:14,840 --> 01:10:16,639 Speaker 1: I know nothing to kills. I'm not a car guy. 1401 01:10:16,760 --> 01:10:20,759 Speaker 1: I absolutely no interests generational is it I like driving cars? 1402 01:10:20,800 --> 01:10:22,519 Speaker 1: Like I like I like when I'm on the road, 1403 01:10:22,600 --> 01:10:24,960 Speaker 1: like renting a car and I take Zip cars. I 1404 01:10:25,040 --> 01:10:28,519 Speaker 1: just I have no interest in like old Porsches or 1405 01:10:28,520 --> 01:10:31,840 Speaker 1: Ferraris or anything. And in the first couple of years 1406 01:10:31,840 --> 01:10:34,920 Speaker 1: of doing this, I started asking that question as a 1407 01:10:34,920 --> 01:10:37,200 Speaker 1: as a would you have for breakfast? What was your 1408 01:10:37,200 --> 01:10:39,760 Speaker 1: first car? Just to do a voice check, And then 1409 01:10:40,000 --> 01:10:43,519 Speaker 1: the answers became so interesting that I started weaving into 1410 01:10:43,600 --> 01:10:49,120 Speaker 1: these questions. And then as I interview younger people, they're like, 1411 01:10:49,360 --> 01:10:51,559 Speaker 1: why would I ever need a car? Between Zip car 1412 01:10:51,560 --> 01:10:53,320 Speaker 1: and Uber? Who needs that in a car? Tell you 1413 01:10:53,320 --> 01:10:57,760 Speaker 1: what I'm streaming? Go ahead, big Taylor Swift fan? Oh really? Um, 1414 01:10:57,800 --> 01:11:02,479 Speaker 1: have you seen the Netflix documentary How Is How? Is That? 1415 01:11:02,640 --> 01:11:05,200 Speaker 1: Pretty great? Oh? Really? Yeah, it's in my list. I 1416 01:11:05,240 --> 01:11:07,639 Speaker 1: haven't gotten to it. There is a scene in there 1417 01:11:07,680 --> 01:11:09,080 Speaker 1: and you will know what scene it is when you 1418 01:11:09,120 --> 01:11:11,200 Speaker 1: see it. That's like really arresting. It's like one of 1419 01:11:11,240 --> 01:11:13,360 Speaker 1: the best things you'll see on TV all year. Okay, 1420 01:11:13,520 --> 01:11:16,240 Speaker 1: I will definitely, I will definitely check that out. What 1421 01:11:16,400 --> 01:11:18,479 Speaker 1: is so? Now? I'm gonna ask you what else are 1422 01:11:18,479 --> 01:11:23,120 Speaker 1: you listening to and watching on on on streaming services? 1423 01:11:24,120 --> 01:11:27,760 Speaker 1: My streaming services? Um, my choices are strange. I I 1424 01:11:27,880 --> 01:11:31,719 Speaker 1: fall asleep every night watching Netflix on my phone. Usually 1425 01:11:31,760 --> 01:11:33,920 Speaker 1: what I do when I travel, I do that with 1426 01:11:33,960 --> 01:11:37,200 Speaker 1: the iPad, do you So? Now I put in. My 1427 01:11:37,240 --> 01:11:39,160 Speaker 1: wife is sleeping next to me, and I have like 1428 01:11:39,200 --> 01:11:42,920 Speaker 1: an air pod in and I fall asleep, and um, 1429 01:11:42,960 --> 01:11:45,960 Speaker 1: the show I've been watching over and over is this old, 1430 01:11:46,160 --> 01:11:49,679 Speaker 1: not old, but old ish um show called Gilmore Girls, 1431 01:11:49,960 --> 01:11:52,439 Speaker 1: which I can't believe you said that. Why, I'm gonna 1432 01:11:52,479 --> 01:11:55,960 Speaker 1: out myself you're a Gilmar Girls. So last summer, so 1433 01:11:56,120 --> 01:11:59,000 Speaker 1: my my wife and her sister have a house out 1434 01:11:59,000 --> 01:12:01,800 Speaker 1: in the Hampton, saying it from their parents, and um, 1435 01:12:02,800 --> 01:12:05,280 Speaker 1: there's always an argument about what were if we're out there, 1436 01:12:05,280 --> 01:12:09,920 Speaker 1: what we're gonna watch? And my my problem with them 1437 01:12:10,120 --> 01:12:13,120 Speaker 1: is that we'll argue over something I'll give into them 1438 01:12:13,240 --> 01:12:15,599 Speaker 1: and then they'll fall asleep. And I'm watching something of theirs. 1439 01:12:16,040 --> 01:12:18,080 Speaker 1: And one day we were prepping to go out and 1440 01:12:18,120 --> 01:12:22,519 Speaker 1: I'm flipping through Netflix and I'm just Gilmer Girls. What's this? 1441 01:12:22,720 --> 01:12:25,519 Speaker 1: And my sister in law says, I love that show. 1442 01:12:25,960 --> 01:12:29,960 Speaker 1: She goes in fact, that's the show that had Melissa 1443 01:12:30,000 --> 01:12:32,960 Speaker 1: McCarthy in it before anyone knew who she was. So 1444 01:12:33,040 --> 01:12:37,200 Speaker 1: we start watching an episode and two seasons through it. 1445 01:12:37,560 --> 01:12:40,040 Speaker 1: I still have like a dozen seasons to go. The 1446 01:12:40,040 --> 01:12:42,120 Speaker 1: beautiful thing about that show is that it gives you 1447 01:12:42,240 --> 01:12:44,320 Speaker 1: material to fall asleep to whenever you want. So it 1448 01:12:44,320 --> 01:12:46,040 Speaker 1: doesn't seem like a good show to fall asleep too, 1449 01:12:46,040 --> 01:12:49,160 Speaker 1: because it's very fast paced. It's very like orkan Ash 1450 01:12:49,280 --> 01:12:52,240 Speaker 1: a little bit. The dialogue is very like that snappy 1451 01:12:52,400 --> 01:12:54,439 Speaker 1: and it moves along quickly, and you would think, like, 1452 01:12:54,520 --> 01:12:56,800 Speaker 1: you don't want those voices in your ear before you 1453 01:12:56,800 --> 01:12:59,040 Speaker 1: fall asleep. But what I found is that it just 1454 01:12:59,080 --> 01:13:01,160 Speaker 1: sort of I've seen them so many times that like 1455 01:13:01,520 --> 01:13:03,880 Speaker 1: they're sort of background noise, and by the time I 1456 01:13:03,920 --> 01:13:06,400 Speaker 1: get to the end of the series, it's been so 1457 01:13:06,439 --> 01:13:08,599 Speaker 1: long since I saw the pilot and the first season 1458 01:13:08,640 --> 01:13:10,280 Speaker 1: that I just go back to it and started again. 1459 01:13:10,560 --> 01:13:14,880 Speaker 1: So so I do that with two shows, one to 1460 01:13:15,000 --> 01:13:18,520 Speaker 1: watch and one to fall asleep with. I think Seinfeld's 1461 01:13:18,520 --> 01:13:22,080 Speaker 1: Comedians and Cars getting Coffee. I have that to just 1462 01:13:22,200 --> 01:13:24,040 Speaker 1: roll over to the next show. But they're too short, 1463 01:13:24,160 --> 01:13:26,720 Speaker 1: is the problem. But you can't watch him every day. 1464 01:13:26,920 --> 01:13:29,160 Speaker 1: You have to, Like that's a little bit. You watch 1465 01:13:29,240 --> 01:13:31,200 Speaker 1: one or two a week, and you go through the 1466 01:13:31,240 --> 01:13:33,839 Speaker 1: whole series, and by the time you finish the whole series. 1467 01:13:34,320 --> 01:13:36,720 Speaker 1: A new season comes out right, and when that's done, 1468 01:13:36,760 --> 01:13:39,000 Speaker 1: you could start over. But the other show that you 1469 01:13:39,040 --> 01:13:42,080 Speaker 1: can have two shows to full sleep to one is 1470 01:13:42,120 --> 01:13:45,679 Speaker 1: The Big Bang, which I've seen a million times. Another guest, 1471 01:13:46,479 --> 01:13:51,439 Speaker 1: former writer, producer of the show. And and then second 1472 01:13:51,720 --> 01:13:55,120 Speaker 1: and I find this hilarious. My wife finds this annoying. 1473 01:13:55,680 --> 01:13:58,200 Speaker 1: There is a show on the Sci Fi Channel called 1474 01:13:58,720 --> 01:14:01,240 Speaker 1: How the Universe Works that'll put you right this so 1475 01:14:01,240 --> 01:14:04,760 Speaker 1: so I'm but those shows work on two levels. If 1476 01:14:04,800 --> 01:14:10,080 Speaker 1: you're watching them while you're awake in a well lit room, 1477 01:14:10,120 --> 01:14:15,000 Speaker 1: it really is a very accessible way to reach some 1478 01:14:15,160 --> 01:14:19,680 Speaker 1: really interesting, cutting edge astrophysics things that are changing. That 1479 01:14:20,120 --> 01:14:23,479 Speaker 1: like all sorts of fascinating discoveries that you just never 1480 01:14:23,520 --> 01:14:25,400 Speaker 1: will see in the New York Times of Wall Street. Jenneral, 1481 01:14:25,520 --> 01:14:30,519 Speaker 1: it's way out there, both literally and physically. But second 1482 01:14:30,680 --> 01:14:34,640 Speaker 1: you put that in a darkened room. The uh the 1483 01:14:34,720 --> 01:14:38,080 Speaker 1: guy who does the voice overs, he's got it's just 1484 01:14:38,840 --> 01:14:42,880 Speaker 1: so horrific. His voice is so deep and soothing. It's 1485 01:14:42,880 --> 01:14:47,040 Speaker 1: almost the real TV equivalent of ambient recommend This is 1486 01:14:47,520 --> 01:14:52,120 Speaker 1: food shows from other countries that are subtitled so they're slow. 1487 01:14:52,200 --> 01:14:54,880 Speaker 1: There's classical music like Chef's Table France will crunch it 1488 01:14:55,040 --> 01:14:57,080 Speaker 1: right out like that. One season will last you like 1489 01:14:57,080 --> 01:14:59,720 Speaker 1: a year of falling. So my I always have this 1490 01:14:59,840 --> 01:15:04,640 Speaker 1: to agreement with my wife. She watches shows like UM 1491 01:15:05,120 --> 01:15:08,360 Speaker 1: Love It, or Listed or or Property Brothers. They engage 1492 01:15:08,360 --> 01:15:12,800 Speaker 1: your that's anytime there's an inherent tension and a conclusion, 1493 01:15:13,960 --> 01:15:16,080 Speaker 1: your brain wants to stay away till the end. So 1494 01:15:16,520 --> 01:15:20,600 Speaker 1: to me, deep space. What is more relaxing than a 1495 01:15:20,800 --> 01:15:25,160 Speaker 1: dark and screen and just the universe. It's just it's 1496 01:15:25,160 --> 01:15:27,040 Speaker 1: like sleeping under the stars. But what's your take on 1497 01:15:27,040 --> 01:15:30,760 Speaker 1: Gilmore Girls? Pretty great, right, It's really well written. I 1498 01:15:30,880 --> 01:15:34,719 Speaker 1: really like the characters. I haven't gotten as deep into 1499 01:15:34,760 --> 01:15:38,400 Speaker 1: the show as you have. Um, So it's you know, 1500 01:15:39,240 --> 01:15:41,559 Speaker 1: as as you watch the show progress, there are there 1501 01:15:41,560 --> 01:15:46,000 Speaker 1: are always the opportunity to go the wrong way and 1502 01:15:46,040 --> 01:15:50,200 Speaker 1: derail a show. And I'll cause a little controversy right now. 1503 01:15:50,640 --> 01:15:54,679 Speaker 1: So I've watched all of the marvelous Mismaysel from the beginning. 1504 01:15:54,720 --> 01:16:00,759 Speaker 1: It's wonderful, except except when you watch the initial season. 1505 01:16:00,800 --> 01:16:04,960 Speaker 1: The initial season is essentially what is it like for 1506 01:16:05,000 --> 01:16:09,479 Speaker 1: a housewife in the late fifties early sixties to break 1507 01:16:09,520 --> 01:16:13,439 Speaker 1: into stand up comedy in an era of very repressed speech. 1508 01:16:14,320 --> 01:16:18,720 Speaker 1: That's a fascinating topic. And unfortunately the show has been 1509 01:16:19,040 --> 01:16:23,920 Speaker 1: too successful because it kind of abandoned that theme and 1510 01:16:24,040 --> 01:16:26,400 Speaker 1: it's I don't care about going to the Cat Skills 1511 01:16:26,400 --> 01:16:28,320 Speaker 1: in the summer, even though I spent summers there as 1512 01:16:28,360 --> 01:16:30,880 Speaker 1: a kid. I don't like there was a whole run 1513 01:16:30,960 --> 01:16:34,559 Speaker 1: of the the in Laws moving to Queen's and that 1514 01:16:34,560 --> 01:16:40,200 Speaker 1: that whole thing was just the the the B storylines. Um. 1515 01:16:40,240 --> 01:16:42,679 Speaker 1: And you could take a show like Seinfeld that would 1516 01:16:42,680 --> 01:16:45,880 Speaker 1: have four equal storylines and have them all go off 1517 01:16:46,280 --> 01:16:48,960 Speaker 1: and they would interweave and all reach a conclusion at 1518 01:16:49,000 --> 01:16:53,400 Speaker 1: the end. I found the B storyline invested in. Like 1519 01:16:53,800 --> 01:16:57,759 Speaker 1: Midge's husband, I don't care about him. Shows feel similar 1520 01:16:57,800 --> 01:17:00,920 Speaker 1: to you Mazel and Gilmore Girls. There are elements that 1521 01:17:00,960 --> 01:17:03,280 Speaker 1: are very similar. Sure well they're written by the same person. 1522 01:17:03,360 --> 01:17:06,960 Speaker 1: That would that would make sense that you know I've noticed. Um. 1523 01:17:07,000 --> 01:17:10,799 Speaker 1: There was a British show I used to love called Coupling, 1524 01:17:11,240 --> 01:17:14,960 Speaker 1: which is basically Friends with some teeth. Like Friends was 1525 01:17:15,040 --> 01:17:19,800 Speaker 1: a milk toast lazy no, I mean, I mean with 1526 01:17:19,880 --> 01:17:22,599 Speaker 1: a bite. But I don't know if that's really true 1527 01:17:22,640 --> 01:17:25,759 Speaker 1: about the British dentistry anymore. But it was a serbic 1528 01:17:25,800 --> 01:17:28,320 Speaker 1: and nasty and funny, and it was written by guy 1529 01:17:28,360 --> 01:17:30,880 Speaker 1: whose last name is Moffett, who later goes on to 1530 01:17:30,920 --> 01:17:32,640 Speaker 1: write a bunch of Doctor Who and a bunch of 1531 01:17:32,680 --> 01:17:36,519 Speaker 1: other stuff. And it's amazing how smart a writer, how 1532 01:17:36,960 --> 01:17:40,160 Speaker 1: entertaining a writer. But I think I kind of knew 1533 01:17:40,200 --> 01:17:42,960 Speaker 1: that some of the people associated with gilmal Girls were 1534 01:17:43,000 --> 01:17:47,439 Speaker 1: also associated with with Miss maysl. What what's so interesting 1535 01:17:47,479 --> 01:17:52,400 Speaker 1: about the show is Melissa McCarthy's character is just so 1536 01:17:53,080 --> 01:17:55,640 Speaker 1: like you see the glimmers, Because I came to the 1537 01:17:55,680 --> 01:17:59,760 Speaker 1: show after she' earlyer already was a giant star and 1538 01:18:00,040 --> 01:18:03,559 Speaker 1: you could see glimmers. But even back then, like, oh, 1539 01:18:03,600 --> 01:18:07,360 Speaker 1: she's gonna be hindsight biased, She's going to be fantastic. 1540 01:18:08,520 --> 01:18:10,240 Speaker 1: Is it worth watching the rest of the show? Am 1541 01:18:10,280 --> 01:18:12,200 Speaker 1: I going to be? Not only do you get to 1542 01:18:12,240 --> 01:18:14,040 Speaker 1: watch the whole thing, you get to see Rory go 1543 01:18:14,080 --> 01:18:16,479 Speaker 1: to college and come out of college. But you know, 1544 01:18:16,560 --> 01:18:20,439 Speaker 1: Netflix did a revival I saw, so I haven't seen it, 1545 01:18:20,479 --> 01:18:22,640 Speaker 1: but I read about those four episodes there about an 1546 01:18:22,640 --> 01:18:24,000 Speaker 1: hour and a half each, and so you can kind 1547 01:18:24,000 --> 01:18:25,640 Speaker 1: of catch up with them about it. Is it worth it? 1548 01:18:25,680 --> 01:18:28,800 Speaker 1: Because the every it's good. As an arrested development fan, 1549 01:18:29,240 --> 01:18:32,040 Speaker 1: I was warned off of the Netflix version. It will 1550 01:18:32,400 --> 01:18:36,000 Speaker 1: it will satisfy an itch. Okay, alright, that works. Wow, 1551 01:18:36,040 --> 01:18:38,559 Speaker 1: that was a long answer to that long Gilmore girls thought. 1552 01:18:38,560 --> 01:18:41,080 Speaker 1: And you thought asking about streaming would be boring, Well, 1553 01:18:41,160 --> 01:18:43,800 Speaker 1: you told me you weren't watching anything, So that's that's 1554 01:18:43,800 --> 01:18:46,040 Speaker 1: why I was watching old things I watched. There you go, 1555 01:18:46,120 --> 01:18:49,160 Speaker 1: so you're not there's nothing you're watching currently. I Once 1556 01:18:49,200 --> 01:18:50,720 Speaker 1: I was done with the book, I I caught up 1557 01:18:50,720 --> 01:18:53,360 Speaker 1: on Succession in like a weekend and loved right. Um, 1558 01:18:53,720 --> 01:18:56,960 Speaker 1: so I watched the first two episodes. I don't matter. 1559 01:18:57,200 --> 01:18:59,599 Speaker 1: I don't like any of the characters and I can't. 1560 01:18:59,680 --> 01:19:03,160 Speaker 1: I can't and you know there's nobody I relate to. 1561 01:19:03,240 --> 01:19:04,800 Speaker 1: And it's like, wait, if I don't like any of 1562 01:19:04,800 --> 01:19:07,400 Speaker 1: these characters, if I'm not invested in any of them, 1563 01:19:07,400 --> 01:19:08,720 Speaker 1: if they can all get hit by a bus, that 1564 01:19:08,760 --> 01:19:11,439 Speaker 1: I don't care, why am I watching this? I want 1565 01:19:11,439 --> 01:19:14,400 Speaker 1: to feel And I know some people have said, well, 1566 01:19:14,439 --> 01:19:18,880 Speaker 1: I feel the same way about Seinfeld. There was a lovable, 1567 01:19:19,120 --> 01:19:22,120 Speaker 1: obnoxious nous about them. It's not and the same thing 1568 01:19:22,160 --> 01:19:26,960 Speaker 1: with Curb your enthusiasm. Right aside from all the cringe worthiness, 1569 01:19:27,000 --> 01:19:30,679 Speaker 1: there's a certain appeal to the characters, and everybody wishes 1570 01:19:31,080 --> 01:19:33,959 Speaker 1: everybody has a bit of Larry David. Well, well you wish, 1571 01:19:34,200 --> 01:19:37,559 Speaker 1: so Larry David is nothing like Larry David. Larry that 1572 01:19:37,720 --> 01:19:40,960 Speaker 1: is his kid right blown up, And we all wish 1573 01:19:41,000 --> 01:19:44,920 Speaker 1: there are times when we could give voice, like I 1574 01:19:45,080 --> 01:19:47,479 Speaker 1: come into the city on the seven, all right, go 1575 01:19:47,560 --> 01:19:48,760 Speaker 1: from the true because I don't want to go to 1576 01:19:48,800 --> 01:19:51,360 Speaker 1: Penn Station, so I'll come in that way. And I 1577 01:19:51,400 --> 01:19:55,320 Speaker 1: am still after years and years and years, astonished that 1578 01:19:56,040 --> 01:19:59,840 Speaker 1: this is literally the busiest subway stop in all of 1579 01:20:00,360 --> 01:20:03,439 Speaker 1: the New York City subway system and people haven't figured 1580 01:20:03,439 --> 01:20:05,160 Speaker 1: out to get the hell out of the way of 1581 01:20:05,240 --> 01:20:08,960 Speaker 1: the door. Really are you just paying? So? And I 1582 01:20:09,439 --> 01:20:14,040 Speaker 1: wanna There was a great um Seth Myers before the 1583 01:20:14,080 --> 01:20:16,840 Speaker 1: new season came out where they have Larry David on 1584 01:20:17,280 --> 01:20:20,639 Speaker 1: and basically set Larry David loose on all the writers 1585 01:20:20,920 --> 01:20:23,640 Speaker 1: to be Larry David and throughout the day. So one 1586 01:20:23,680 --> 01:20:27,120 Speaker 1: of the writers invites people to his home for dinner 1587 01:20:27,120 --> 01:20:30,040 Speaker 1: and Larry, no, no, you have to work with these people. 1588 01:20:30,120 --> 01:20:32,400 Speaker 1: They don't want to waste their Thursday night having dinner, 1589 01:20:32,800 --> 01:20:36,240 Speaker 1: and it's just great to have Larry David there as 1590 01:20:36,280 --> 01:20:39,880 Speaker 1: a foil for your deepest dark secrets. I have that 1591 01:20:40,080 --> 01:20:43,280 Speaker 1: sort of running internal narrative constantly. The best thing that 1592 01:20:43,320 --> 01:20:46,600 Speaker 1: I've streamed recently probably is that, UM, I am a 1593 01:20:46,680 --> 01:20:49,559 Speaker 1: huge John Laney dork, and UM, I just think he's 1594 01:20:49,560 --> 01:20:53,240 Speaker 1: a genius. So many there's so many like I I 1595 01:20:53,479 --> 01:20:56,400 Speaker 1: watched his talk show appearances because they're hilarious. The funniest 1596 01:20:56,439 --> 01:20:59,840 Speaker 1: thing on the internet is, Uh, he did and in 1597 01:21:00,000 --> 01:21:03,360 Speaker 1: review at the Street Why with Nick roll in their 1598 01:21:03,400 --> 01:21:05,800 Speaker 1: oh hello characters with and they're right, they are old 1599 01:21:05,920 --> 01:21:08,360 Speaker 1: old colleagues from way back when, and it's an interview 1600 01:21:08,360 --> 01:21:11,320 Speaker 1: with John Oliver and it's about ninety minutes. Um, John 1601 01:21:11,320 --> 01:21:13,600 Speaker 1: Oliver interviews them, they take Q and a's and I 1602 01:21:13,680 --> 01:21:18,360 Speaker 1: cannot describe how just outrageously funny this thing is. It 1603 01:21:18,439 --> 01:21:20,920 Speaker 1: is like it's it's I think he is the funniest 1604 01:21:20,920 --> 01:21:22,519 Speaker 1: stand up on the planet. It's funnier than any of 1605 01:21:22,600 --> 01:21:25,080 Speaker 1: his stand ups because the way that he can embody 1606 01:21:25,160 --> 01:21:28,439 Speaker 1: these characters is it's it's incredible. I would watch it 1607 01:21:28,520 --> 01:21:30,839 Speaker 1: like I have watched it so many times, and I 1608 01:21:30,920 --> 01:21:33,160 Speaker 1: like happily watch it any time it comes out, all right, 1609 01:21:33,240 --> 01:21:35,120 Speaker 1: So I'm gonna put that on my list. Let me 1610 01:21:35,240 --> 01:21:37,280 Speaker 1: let me run through some of my favorite questions that 1611 01:21:37,439 --> 01:21:41,479 Speaker 1: otherwise uh people will yell email me and and complain. 1612 01:21:41,920 --> 01:21:45,280 Speaker 1: So who your early mentors, What journalists influenced the way 1613 01:21:45,320 --> 01:21:48,320 Speaker 1: you approach covering sports? There were a lot before I 1614 01:21:48,360 --> 01:21:50,040 Speaker 1: got to the Wall Street Journal, But there was one 1615 01:21:50,120 --> 01:21:52,280 Speaker 1: guy at the Wall Street Journal named Sam Walker, who 1616 01:21:52,320 --> 01:21:54,920 Speaker 1: was the founding sports editor of the journal, who is 1617 01:21:54,960 --> 01:21:58,719 Speaker 1: this brilliant and insane and insanely brilliant and brilliantly insane 1618 01:21:58,840 --> 01:22:02,360 Speaker 1: person who sort of set the bar really really high. 1619 01:22:02,479 --> 01:22:04,879 Speaker 1: And so when I was an intern, when I freelanced 1620 01:22:04,880 --> 01:22:06,280 Speaker 1: for the paper for a while, even when I was 1621 01:22:06,320 --> 01:22:07,880 Speaker 1: a staff writer, it felt like every time you got 1622 01:22:07,920 --> 01:22:10,160 Speaker 1: a story into the paper, you were like pole vault 1623 01:22:10,160 --> 01:22:12,360 Speaker 1: thing basically, like you were trying to get above a 1624 01:22:12,400 --> 01:22:15,040 Speaker 1: certain point. And um, I think that's why we used 1625 01:22:15,080 --> 01:22:17,200 Speaker 1: to hear a lot of the journal like we didn't 1626 01:22:17,240 --> 01:22:19,639 Speaker 1: know that you covered sports because we didn't. But now 1627 01:22:19,840 --> 01:22:21,639 Speaker 1: I think people understand that we try to do something 1628 01:22:21,680 --> 01:22:23,760 Speaker 1: a little bit different, and that's because of Sam. I 1629 01:22:23,800 --> 01:22:26,160 Speaker 1: think he sort of taught me what a good story 1630 01:22:26,360 --> 01:22:28,559 Speaker 1: was and like to not be precious with my own 1631 01:22:28,600 --> 01:22:31,599 Speaker 1: writing and to just like let other people make it better. 1632 01:22:31,680 --> 01:22:35,240 Speaker 1: So Sam hired me and had this huge influence on 1633 01:22:35,280 --> 01:22:37,880 Speaker 1: my life. Let's talk about books. What are some of 1634 01:22:37,920 --> 01:22:39,840 Speaker 1: your favorite books? What do you like to read when 1635 01:22:39,840 --> 01:22:42,680 Speaker 1: you're not writing books? Yeah, I mean it's I'm a 1636 01:22:42,680 --> 01:22:44,680 Speaker 1: sucker for the Michael Lewis books. I like, I think 1637 01:22:44,720 --> 01:22:47,680 Speaker 1: money Ball Is is still brilliant and um, when I 1638 01:22:47,720 --> 01:22:51,000 Speaker 1: went to visit Nick Hagan on the farm, we were 1639 01:22:51,000 --> 01:22:54,240 Speaker 1: talking as we boarded, like his weak combine. I asked 1640 01:22:54,320 --> 01:22:56,479 Speaker 1: him sometimes I write to classical music, and I asked him, 1641 01:22:56,479 --> 01:22:58,280 Speaker 1: like who should I be listening to? Like who who 1642 01:22:58,360 --> 01:23:00,960 Speaker 1: is your favorite composer since you was at Juilliard and 1643 01:23:01,000 --> 01:23:04,080 Speaker 1: he played trombone and he said, um, you know, I 1644 01:23:04,120 --> 01:23:06,840 Speaker 1: know this is going to sound silly, but like the 1645 01:23:06,880 --> 01:23:09,200 Speaker 1: best guy is Mozart and he's like and I know, 1646 01:23:09,400 --> 01:23:12,479 Speaker 1: like you know, other people know Mozart, but like I 1647 01:23:12,560 --> 01:23:15,519 Speaker 1: know Mozart and like I appreciate him. And I sort 1648 01:23:15,520 --> 01:23:17,559 Speaker 1: of feel the same way about Michael Lewis, like everybody 1649 01:23:17,600 --> 01:23:20,639 Speaker 1: loves his books, but like, you know, as someone who 1650 01:23:20,760 --> 01:23:23,519 Speaker 1: has tried to write a book along the same lines, 1651 01:23:23,600 --> 01:23:26,400 Speaker 1: like the stories that he finds like on a sentence level, 1652 01:23:26,479 --> 01:23:28,960 Speaker 1: like everything about them they're they're just brilliant, like they 1653 01:23:29,000 --> 01:23:31,680 Speaker 1: just they hold up. And whenever I feel stuck, I 1654 01:23:31,760 --> 01:23:34,240 Speaker 1: might sometimes go back and and read some just a 1655 01:23:34,240 --> 01:23:36,720 Speaker 1: few pages from his books because like that voice, like 1656 01:23:36,840 --> 01:23:39,559 Speaker 1: it just gets in your head and it's I love it. 1657 01:23:39,600 --> 01:23:42,680 Speaker 1: I I anxiously await all so money will get you 1658 01:23:42,720 --> 01:23:45,280 Speaker 1: wanna mention another one of his or and then other 1659 01:23:45,320 --> 01:23:48,439 Speaker 1: books you you like, well, I mean The blind Side, 1660 01:23:48,520 --> 01:23:51,320 Speaker 1: the Undoing Project. Um, now I don't know, I I 1661 01:23:51,640 --> 01:23:54,120 Speaker 1: M I read these types of books. I mean part 1662 01:23:54,120 --> 01:23:56,559 Speaker 1: of this book is like it is like using a 1663 01:23:56,640 --> 01:23:59,880 Speaker 1: social stych. It is like using an idea from so 1664 01:24:00,080 --> 01:24:02,519 Speaker 1: psychology to explore the world. And there are a lot 1665 01:24:02,520 --> 01:24:04,639 Speaker 1: of books along those lines. And I think I read 1666 01:24:04,680 --> 01:24:07,800 Speaker 1: them at an impressionable age. They really like they really 1667 01:24:07,800 --> 01:24:10,599 Speaker 1: became popular when I was like in middle school, high school, 1668 01:24:10,640 --> 01:24:13,000 Speaker 1: and like they were just sort of intoxicating to me. 1669 01:24:13,080 --> 01:24:14,680 Speaker 1: And so um, there are a lot of books like that, 1670 01:24:14,760 --> 01:24:16,760 Speaker 1: I mean novels too, Like you know, I loved the 1671 01:24:16,760 --> 01:24:19,400 Speaker 1: Salary Rooney book Normal People when it came out, like 1672 01:24:19,400 --> 01:24:21,439 Speaker 1: like everybody else in New York City, it seems. And 1673 01:24:21,479 --> 01:24:24,040 Speaker 1: but but those that you know Moneyball and like the 1674 01:24:24,080 --> 01:24:26,320 Speaker 1: Michael Lewis Cannon, that's that's that's what really does it 1675 01:24:26,360 --> 01:24:28,800 Speaker 1: for me. Tell us about a time you failed and 1676 01:24:28,840 --> 01:24:31,640 Speaker 1: what you learned from the experience. It was, Well, I 1677 01:24:31,840 --> 01:24:33,759 Speaker 1: feel like I fail every time I write a story because, 1678 01:24:34,080 --> 01:24:36,360 Speaker 1: like you know, you're writing a newspaper story that's a 1679 01:24:36,360 --> 01:24:39,040 Speaker 1: thousand words words, like you've talked to a lot of people, 1680 01:24:39,160 --> 01:24:41,040 Speaker 1: you know, all this nuance that you can't possibly pack 1681 01:24:41,120 --> 01:24:43,400 Speaker 1: into the story. And so, like you know, every time 1682 01:24:43,400 --> 01:24:46,639 Speaker 1: the story comes out, like I, I feel like it's 1683 01:24:46,680 --> 01:24:48,960 Speaker 1: not good enough, right. But but one time I really failed. 1684 01:24:48,960 --> 01:24:51,240 Speaker 1: It was actually not too long ago. Um. I wrote 1685 01:24:51,760 --> 01:24:53,920 Speaker 1: one of my like bajillion stories about the Golden State 1686 01:24:53,920 --> 01:24:56,280 Speaker 1: Warriors last year, and it was right before the finals, 1687 01:24:56,680 --> 01:24:59,080 Speaker 1: and you know, I needed something new to say about 1688 01:24:59,080 --> 01:25:00,800 Speaker 1: this team that I've been I about for five or 1689 01:25:00,840 --> 01:25:03,439 Speaker 1: six years. Um And we have a daily newspaper, and like, 1690 01:25:03,479 --> 01:25:05,280 Speaker 1: you know, give me a break. Not every story is perfect. 1691 01:25:05,320 --> 01:25:09,040 Speaker 1: And um, I was trying to express this thought that 1692 01:25:09,080 --> 01:25:11,360 Speaker 1: I had that the Golden State Warriors were the Golden 1693 01:25:11,360 --> 01:25:15,479 Speaker 1: State Warriors because there were like five Um, really valuable 1694 01:25:15,479 --> 01:25:17,200 Speaker 1: players on that team, and you take out any one 1695 01:25:17,280 --> 01:25:18,800 Speaker 1: of them and the whole thing falls apart. It's a 1696 01:25:18,800 --> 01:25:21,479 Speaker 1: bit like a Jenga tower, right. Um. And the way 1697 01:25:21,520 --> 01:25:23,920 Speaker 1: I phreeze this in the story was like, the Warriors 1698 01:25:24,000 --> 01:25:28,360 Speaker 1: are this dynasty because of Steph Curry, Clay Thompson, Kevin Durant, 1699 01:25:28,720 --> 01:25:33,040 Speaker 1: Draymond Green, and Andrea Gudala. And the end was italicized 1700 01:25:33,120 --> 01:25:34,760 Speaker 1: right because it was meant to say that, like, if 1701 01:25:34,760 --> 01:25:37,000 Speaker 1: you take out any one of their contributions, they're not 1702 01:25:37,120 --> 01:25:39,599 Speaker 1: the Warriors. That's not always the case with basketball teams. 1703 01:25:39,600 --> 01:25:41,439 Speaker 1: Like basketball teams were built around one or two guys. 1704 01:25:41,600 --> 01:25:45,040 Speaker 1: The ninety s Bulls are the Bulls. With Jordan's you 1705 01:25:45,040 --> 01:25:46,840 Speaker 1: could sort of substitute a lot of other guys, right, 1706 01:25:46,960 --> 01:25:50,479 Speaker 1: can't do that with the Warriors. Um. The problem was that, Um, 1707 01:25:50,520 --> 01:25:54,000 Speaker 1: I forgot that like on Twitter and on social media, 1708 01:25:54,160 --> 01:25:58,519 Speaker 1: you can't italicize words, right, and so UM when this 1709 01:25:58,560 --> 01:26:01,559 Speaker 1: stuff ran on social media, when I wrote tweets that 1710 01:26:01,640 --> 01:26:05,240 Speaker 1: we could share from like you know, wha, Um, it 1711 01:26:05,520 --> 01:26:07,760 Speaker 1: appears as like the Golden State Warriors are good because 1712 01:26:07,800 --> 01:26:11,479 Speaker 1: of Steph Curry, Clay Thompson, Kevin Durantraymond Grand and Andrea Guadala. 1713 01:26:11,680 --> 01:26:14,559 Speaker 1: And this turned into one day last year, like the 1714 01:26:14,720 --> 01:26:17,880 Speaker 1: entire internet dunking on the Wall Street Journal because it 1715 01:26:17,960 --> 01:26:21,439 Speaker 1: read like the Beatles are good because of Paul, George, 1716 01:26:21,640 --> 01:26:24,679 Speaker 1: John and Ringo. You know, like it that's a fair statement. Yeah, 1717 01:26:24,680 --> 01:26:27,439 Speaker 1: but it just sure it's Paul and John. But you 1718 01:26:27,479 --> 01:26:30,240 Speaker 1: know they're not the Beatles necessarily without George and Ringo. 1719 01:26:30,280 --> 01:26:32,719 Speaker 1: But it made for it. It looked like this very 1720 01:26:32,760 --> 01:26:35,760 Speaker 1: silly sentiment, and I just felt terrible. I felt like, 1721 01:26:35,800 --> 01:26:37,960 Speaker 1: when you have the entire internet like making fun of 1722 01:26:38,000 --> 01:26:41,280 Speaker 1: you for a day, you're just like god right, um 1723 01:26:41,479 --> 01:26:43,800 Speaker 1: and so um. What it taught me was like you 1724 01:26:43,880 --> 01:26:45,599 Speaker 1: kind of have to be careful and like every word 1725 01:26:45,640 --> 01:26:48,599 Speaker 1: actually matters. And also that like people forget about things 1726 01:26:48,640 --> 01:26:51,599 Speaker 1: on Twitter after a few hours, life is really short, 1727 01:26:51,800 --> 01:26:56,559 Speaker 1: future reference and well capitalize the equivalent in stars. Yes, 1728 01:26:56,880 --> 01:26:58,800 Speaker 1: that would make you to know a couple of months ago. Alright, Well, 1729 01:26:58,880 --> 01:27:02,200 Speaker 1: I'll share my other uh secret Twitter secret with you later. 1730 01:27:02,240 --> 01:27:04,960 Speaker 1: You'll you'll appreciate this. Um, what do you do for fun? 1731 01:27:05,000 --> 01:27:07,240 Speaker 1: What do you do when you're not banging out columns 1732 01:27:07,240 --> 01:27:09,919 Speaker 1: for the journal? Well? I can't watch sports because sports 1733 01:27:10,080 --> 01:27:12,719 Speaker 1: is work, right, and my brand is always working. Um. 1734 01:27:12,760 --> 01:27:14,280 Speaker 1: I just wrote a book in my spare time, so 1735 01:27:14,320 --> 01:27:17,040 Speaker 1: I don't know all that much about fun. But one thing, 1736 01:27:17,280 --> 01:27:20,519 Speaker 1: one thing that I love lately is that, um, um, 1737 01:27:20,560 --> 01:27:23,439 Speaker 1: this is gonna sound silly, but um there's this YouTube 1738 01:27:23,520 --> 01:27:25,680 Speaker 1: channel from Bone Appetite and I don't know if you're 1739 01:27:25,680 --> 01:27:27,639 Speaker 1: familiar with it, and I'm not a great home cook, 1740 01:27:27,720 --> 01:27:32,479 Speaker 1: but um this these videos are like so magical and 1741 01:27:32,520 --> 01:27:37,240 Speaker 1: I'm reeling and like, um, there there are the editors 1742 01:27:37,640 --> 01:27:41,040 Speaker 1: in the test kitchen and the recipe developers. Um, they're 1743 01:27:41,120 --> 01:27:43,400 Speaker 1: just really charming and like you sort of fall in 1744 01:27:43,400 --> 01:27:47,519 Speaker 1: love with that. I'm a new episodes like almost every day, 1745 01:27:47,600 --> 01:27:49,599 Speaker 1: and my wife and I they're like fifteen minutes, will 1746 01:27:49,640 --> 01:27:52,000 Speaker 1: just put it on and like it really like soothes 1747 01:27:52,040 --> 01:27:54,679 Speaker 1: me before I go to sleep. Okay, So I'm gonna 1748 01:27:54,720 --> 01:27:58,439 Speaker 1: give you marriage advice that I wish someone had given 1749 01:27:58,479 --> 01:28:01,760 Speaker 1: me many decades ago. My wife and I both like 1750 01:28:01,880 --> 01:28:05,640 Speaker 1: to cook, and it's only fairly recently that we started 1751 01:28:05,760 --> 01:28:10,479 Speaker 1: on a Sunday night pulling a cookbook out and making 1752 01:28:10,520 --> 01:28:13,839 Speaker 1: a recipe from scratch and not just like a simple 1753 01:28:14,200 --> 01:28:16,960 Speaker 1: you know, boil water throw pasta, like a full blown 1754 01:28:17,120 --> 01:28:21,559 Speaker 1: Bobby Flay recipe. And we've developed over just a couple 1755 01:28:21,560 --> 01:28:24,400 Speaker 1: of years a few favorite things. We have a dinner party. 1756 01:28:24,439 --> 01:28:27,360 Speaker 1: We know exactly what we're gonna make, and I you're married, 1757 01:28:27,360 --> 01:28:30,320 Speaker 1: how long now? Like three years? Okay, had we been 1758 01:28:30,360 --> 01:28:35,200 Speaker 1: doing this twenty five years ago, we would be fantastic chefs. 1759 01:28:35,520 --> 01:28:37,960 Speaker 1: We don't do it over the summer because that's always barbecue. 1760 01:28:38,760 --> 01:28:44,080 Speaker 1: But through especially from like the late fall to early spring, 1761 01:28:44,120 --> 01:28:46,559 Speaker 1: was it a new recipe every time? Just about just 1762 01:28:46,760 --> 01:28:48,439 Speaker 1: every now and then we'll go back to something and 1763 01:28:49,960 --> 01:28:52,680 Speaker 1: so right, and very often it's like, wow, that's a 1764 01:28:52,680 --> 01:28:55,559 Speaker 1: lot of work, and this isn't that good. Most of 1765 01:28:55,560 --> 01:28:57,920 Speaker 1: the time it's this was really good. And every now 1766 01:28:57,920 --> 01:29:01,240 Speaker 1: and then it's like, oh my goodness, your favorite. Um. 1767 01:29:01,280 --> 01:29:04,360 Speaker 1: I have to say, I love the Bobby Flay cookbook. Uh. 1768 01:29:04,400 --> 01:29:07,400 Speaker 1: And we have like a whole shelf of a dozen 1769 01:29:07,880 --> 01:29:11,040 Speaker 1: different cookbooks. There are a handful of people that try 1770 01:29:11,080 --> 01:29:16,320 Speaker 1: and work on on basics and I'm I'm embarrassed. Um 1771 01:29:16,400 --> 01:29:18,840 Speaker 1: what is her name? She has a restaurant I really 1772 01:29:18,880 --> 01:29:22,200 Speaker 1: like out in Hampton's called the Canal Cafe. There's something 1773 01:29:22,240 --> 01:29:28,280 Speaker 1: Gourmam drown a blanket. Had I prepped for this question. Um, absolutely, 1774 01:29:28,360 --> 01:29:31,479 Speaker 1: But but play with that and see if that does 1775 01:29:31,520 --> 01:29:36,080 Speaker 1: anything for you, Because we've just had a fun it's actually, um, 1776 01:29:36,120 --> 01:29:38,080 Speaker 1: not only useful, but like fun, it makes you actually 1777 01:29:38,120 --> 01:29:39,880 Speaker 1: want to do it right and you start to look 1778 01:29:39,920 --> 01:29:42,160 Speaker 1: forward to because usually Sunday night as I'm prepping for 1779 01:29:42,240 --> 01:29:45,320 Speaker 1: the beginning of work. Now you go shopping sometime over 1780 01:29:45,360 --> 01:29:47,960 Speaker 1: the weekend and then you do this and of course 1781 01:29:48,000 --> 01:29:51,160 Speaker 1: you have a bottle of wine open um, and sometimes 1782 01:29:51,200 --> 01:29:53,160 Speaker 1: you're drinking a bit throughout. It doesn't have to be 1783 01:29:53,200 --> 01:29:56,080 Speaker 1: Sunday nights. It just worked out for us. But it's 1784 01:29:56,120 --> 01:29:59,960 Speaker 1: a lot of fun. Um. And our final two questions, Uh, 1785 01:30:00,040 --> 01:30:02,080 Speaker 1: what sort of advice would you give a college grad 1786 01:30:02,120 --> 01:30:06,679 Speaker 1: who was interested in any of the sports or journalism? Um, 1787 01:30:06,720 --> 01:30:11,000 Speaker 1: to take advantage of their place in the world. So 1788 01:30:11,240 --> 01:30:14,000 Speaker 1: sometimes when the journal has interns, I always tell them this, 1789 01:30:14,120 --> 01:30:17,960 Speaker 1: that what they know, what their world is is actually 1790 01:30:18,400 --> 01:30:21,280 Speaker 1: very different from the world of the people like running 1791 01:30:21,360 --> 01:30:23,840 Speaker 1: the Wall Street Journal. So like just by virtue of 1792 01:30:23,880 --> 01:30:26,960 Speaker 1: being twenty one years old, you are on TikTok, right, 1793 01:30:27,000 --> 01:30:29,240 Speaker 1: and you talk to other twenty one year olds, and 1794 01:30:29,280 --> 01:30:33,040 Speaker 1: you know what, like this very interesting um subset of 1795 01:30:33,080 --> 01:30:35,720 Speaker 1: people are interested in and so like you almost think 1796 01:30:35,800 --> 01:30:39,320 Speaker 1: of your world as like this subculture to mine, like 1797 01:30:39,439 --> 01:30:42,439 Speaker 1: you are an anthropologist, and so by the very first 1798 01:30:42,439 --> 01:30:44,560 Speaker 1: frontage story I wrote for the Wall Street Journal was 1799 01:30:44,600 --> 01:30:46,479 Speaker 1: a few months after I graduated from college, and it 1800 01:30:46,520 --> 01:30:49,639 Speaker 1: was about this dance craze known as the Dougie, which 1801 01:30:49,760 --> 01:30:52,160 Speaker 1: you might remember this song like you know, teach Me 1802 01:30:52,160 --> 01:30:54,960 Speaker 1: how to Dougie, and everybody in sports was doing it. 1803 01:30:55,000 --> 01:30:56,760 Speaker 1: Was this was this an ahead kind of wise, it 1804 01:30:56,800 --> 01:30:59,160 Speaker 1: was an ahead and so um, and I tell them specifically, 1805 01:30:59,200 --> 01:31:01,040 Speaker 1: like you know, the ahead does not have to be 1806 01:31:01,080 --> 01:31:03,760 Speaker 1: about like you know, birding or something or something that, 1807 01:31:03,800 --> 01:31:07,040 Speaker 1: like you think, like it can just be something funny 1808 01:31:07,080 --> 01:31:09,479 Speaker 1: about something in your life. And so like, you know, 1809 01:31:09,520 --> 01:31:11,400 Speaker 1: the people running the Wall Street Journal did not know 1810 01:31:11,479 --> 01:31:13,080 Speaker 1: what the duck you was. But I was twenty one. 1811 01:31:13,120 --> 01:31:14,519 Speaker 1: Of course I knew what the duck you was, right, 1812 01:31:14,560 --> 01:31:17,160 Speaker 1: And like you can take advantage of that, Like what 1813 01:31:17,240 --> 01:31:21,040 Speaker 1: you know is actually pretty interesting, huh, quite quite interesting? 1814 01:31:21,680 --> 01:31:24,200 Speaker 1: And what is it about the world of sports that 1815 01:31:24,240 --> 01:31:26,880 Speaker 1: you know today that you wish you knew? No, normally 1816 01:31:26,880 --> 01:31:29,800 Speaker 1: I would say years ago, but a couple of years 1817 01:31:29,840 --> 01:31:33,360 Speaker 1: ago when you got started in in your career. Um 1818 01:31:33,400 --> 01:31:37,520 Speaker 1: that I should have taken a single course in economics 1819 01:31:37,640 --> 01:31:40,680 Speaker 1: or psychology or statistics or computer science when I was 1820 01:31:40,680 --> 01:31:44,520 Speaker 1: in college. I graduated from school and like immediately recognized 1821 01:31:44,560 --> 01:31:47,599 Speaker 1: that what I wanted to do, I really needed more of, 1822 01:31:47,640 --> 01:31:50,880 Speaker 1: like a quantitative background that I don't think I have 1823 01:31:51,080 --> 01:31:52,760 Speaker 1: to this day. And I wish I knew how to 1824 01:31:53,120 --> 01:31:54,800 Speaker 1: write code, and I wish I knew how to like 1825 01:31:55,080 --> 01:32:01,080 Speaker 1: really understand um statistics because it has become like essential 1826 01:32:01,280 --> 01:32:03,639 Speaker 1: in sports now and really writing about sports, like writing 1827 01:32:03,640 --> 01:32:07,320 Speaker 1: about sports fluently and finding interesting stories, like you can 1828 01:32:07,320 --> 01:32:10,360 Speaker 1: really use numbers and then try to build stories around them, 1829 01:32:10,360 --> 01:32:12,840 Speaker 1: which is something I hope I did in this book. Well, 1830 01:32:13,040 --> 01:32:15,439 Speaker 1: quite fascinating. I really enjoyed the book. Thank you, Ben 1831 01:32:15,479 --> 01:32:18,120 Speaker 1: for being so generous with your time. We have been 1832 01:32:18,160 --> 01:32:21,760 Speaker 1: speaking with Ben Cohen. He is the NBA reporter for 1833 01:32:21,840 --> 01:32:24,360 Speaker 1: The Wall Street Journal and author of the new book 1834 01:32:24,800 --> 01:32:28,439 Speaker 1: The Hot Hands, The Mystery and Science of Streaks. If 1835 01:32:28,479 --> 01:32:30,920 Speaker 1: you enjoy this conversation well, be sure to look Up 1836 01:32:30,920 --> 01:32:33,760 Speaker 1: an Inch or Down an Inch on Apple iTunes, where 1837 01:32:33,800 --> 01:32:36,599 Speaker 1: you can see any of the previous three hundred plus 1838 01:32:36,640 --> 01:32:40,720 Speaker 1: conversations we've had over the past five plus years. We 1839 01:32:40,920 --> 01:32:44,840 Speaker 1: love your comments, feedback, and suggestions. Be sure and give 1840 01:32:44,960 --> 01:32:49,360 Speaker 1: us a review on Apple iTunes. Check out my weekly 1841 01:32:49,439 --> 01:32:52,759 Speaker 1: column on Bloomberg dot com. Sign up from my daily 1842 01:32:52,800 --> 01:32:56,599 Speaker 1: reads on Ridholtz dot com. I would be remiss if 1843 01:32:56,600 --> 01:32:58,720 Speaker 1: I did not thank the Crack staff who helps put 1844 01:32:58,760 --> 01:33:04,160 Speaker 1: these conversations together each week. Nick Falco is my recording engineer. 1845 01:33:04,920 --> 01:33:09,519 Speaker 1: Sam Shivraj is my booker. Slash producer. Michael Batnick is 1846 01:33:09,520 --> 01:33:13,360 Speaker 1: our head of research. I'm Barry Retults. You've been listening 1847 01:33:13,360 --> 01:33:16,000 Speaker 1: to Master's Business on Bloomberg Radio