The Herd with Colin Cowherd - The Favorites - Analytics vs Expertise with Author Chris Jones

Episode Date: February 18, 2022

Host Chad Millman describes today's guest as "possibly the greatest magazine writer of his generation." He's gushing about his longtime friend and colleague Chris Jones, now the author of a new book titled The Eye Test: A Case for Human Creativity in the Age of Analytics. With co-host Simon Hunter off on a well-deserved vacation, Chad and Chris discuss the book and its argument for human inputs of experience and "embodied analysis" in an era where data has been treated as infallible. In a spirited discussion, Chad also applies the book's many lessons and anecdotes to the world of sports and sports betting. Learn more about your ad-choices at https://www.iheartpodcastnetwork.comSee omnystudio.com/listener for privacy information.

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slash RG in Colorado, Indiana, New Jersey, and Virginia, 1-888-789-7777 or visit ccpg.org slash chat in Connecticut, 1,800-2707-1-1-7 for confidential help in Michigan, 1-877-7-70-S-T-O-P in Louisiana. Call the Tennessee Red Line 1-8009-9-9 or visit 1-800-gambler.net in West Virginia. Welcome to the favorites, the podcast from the Volume Podcast Network. I am Chad Millman, Chief Content Officer of the Action Network. We have a very special guest today. You could argue that my guest today,

is the greatest magazine writer of his generation. He's written for The Atlantic. He's written for Esquire, for which he wrote multiple stories that won National Magazine Awards. The very first columnist I hired when I took over as Edron Chief of DSP in the magazine. He wrote some of the best stories we did at the magazine

in sort of the 2010s. He has written a new book that tries to undo everything that is important to me. It's called the I-Test, a case for human creativity in the age of analytics. I can't think of a writer more equipped to try to tear down the way the world is going than Mr. Chris Jones. How are you, buddy? Dude, that was the nicest introduction of all time. You've earned it. We could talk about the amazing stories you wrote for the magazine. I will say, and I've said this to you before, there's a seminal magazine piece that Wright Thompson wrote about Michael Jordan turning 50. And I think it was 2012 is when it came out,

maybe. And maybe it was 2011. I can't remember exactly. That same year, you wrote a story about a Japanese high school baseball pitcher that I just thought was better than writes Michael Jordan's story. it was like, you know, when write, like, is in a subject, he can, like, write you epic, epic stories. And this was a beautiful, amazing story that it was so inside one of the people who was harder to get inside than anyone. But there was something about the Japanese baseball story that to me, and you should explain to people what it was, it actually speaks to a lot of what your book is about, which was so clean and interesting and dramatic. in very subtle ways. I just loved it. Tell people what that was about

and then we can get into the book. I've enjoyed this conversation so far. It's been good for my ego. The story was about a young Japanese high school picture, expected to do great things. And in Japan, there's a high school tournament, Caution that happens. There's two spring and fall,

but the spring is the big one. Every district in Japan sends a team was described to me as sort of the Super Bowl plus Marty Gras plus July 4th. It's like the biggest, the country stops to watch this tournament and these kids play each other. And that picture, you know, his team kept winning. And he threw, I think it was 772 pictures in five days. And his arm fell off in the final, basically.

And his career didn't really become what it was expected to become. And it was sort of an exploration of how the Japanese approached baseball, which is a very different way than Americans. It's a lot less individualistic and what he did was sort of sacrifice. He was helping his brothers try to win this tournament. And he had no regrets, even though he lost, you know, potentially hundreds of millions of dollars. And that's just for me, it was just such a different perspective on baseball. It was a really great experience.

So thank you for your kind words about the story. But as an experience, as a selfish sort of travel and cultural experience, it was fantastic. I think about it all the time. Yeah, we really did you write on that one. You really did. Yeah. Yeah, spectacularly right. T.J. Quinn, I don't know if you remember, T.J. Quinn joined me to do the TV side of things.

And I was a little offside about it at first, but then I realized the TV side of things lived a lot better. And so even that was great. I got to move hotels. Yeah, it was fantastic. All right. So you wrote this book, The I Test, The Case for Human Creativity in the Age of Analytics. It's out now. I've read it.

It's really good. Thank you. You would think it's counter to have someone like you on a podcast that is a betting podcast in which analytics are the core of what we do. And at Action Network, analytics drive our entire engine, right? We are constantly on the lookout for the number, the metrics, the edge, lots of times driven by models and algorithms, which you lay waste to in your book. And yet, I found it fascinating because it does speak to a lot of things that matter when you are trying to make decisions

and why you can't just rely on analytics, including the Super Bowl that we just saw between the Bengals and the Rans. My co-host Simon Hunter, who's a professional better, he and I in the podcast earlier this week talked about the need to have feel the eye-test elements of what the Bengals did all season and incorporating that into our numbers.

So my question for you is, why do you hate analytics so much in the people who use them? I don't. I don't. This is the thing. The book is going to get cast as like the anti-money ball, and it's not that at all. What I'm trying to say is that data is useful, models are useful, algorithms in certain situations are useful, but they're not the entire answer to many questions, particularly

in complicated situations. So they're pretty good at that, you know, I get the. use of statistics in baseball when you're deciding whether to match up a particular picture with a particular hitter. Totally understood. When things get more complicated, like when you're trying to dissect a hockey game, for instance, five guys playing together against five other guys, lots of moving parts, they can also be helpful, but maybe don't give you the entire answer. And something like sports betting, what I would argue, and by the way, I regret very deeply not having an entire chapter about gambling, which I should have done. But the idea that you can rely entirely on models, I don't see what your edge is, then unless your model just happens to be better than any other model on the planet. Or your access to numbers is better, or your understanding of numbers is better. But if you're not number one at that, then I feel like you must need some 10 or

15% that little sliver that that comes from feel or knowledge or experience or or not God. I wouldn't advocate for God. For me, it's like experience wisdom. Like what's the value of that? And so you have your model and you have, I'm assuming you plug in all sorts of numbers, but I'm assuming other people have those numbers as well. What's the difference? What's the competitive advantage of doing it exactly the same way as anybody else?

Well, you're right. I mean, your argument really is that the fallibility of the models that everybody uses. And like I said, you know, for the Super Bowl, I relied there were three experts at Action Network who we were podcasting with, who were doing a lot of shows. And there are a lot of experts at Action Network who are amazing. But three people who build ostensibly three different models coming from three. three entirely different approaches. The fallibility in the model is that there is a human element that builds the model. With any of these things, they're sort of treated as these objective, like,

hugely rational, like they were found in nature. And we build the models. So the algorithms and the models contain all the bias that the people who make them contain. So if I'm building a model and I think something is particularly important and needs to be weighted a certain way, I'm adding a human input into what is the allegedly an objective model. And that's not wrong. I mean, it's just, I think it's important for people to be aware that numbers can be used

as subjective instruments just as much as stories can or just as much as gut can. You know, it's, it's this idea that math is black or white that sort of bothers me. It's, it's not necessarily. Like statistics are used to lie all the time. I can massage numbers to make a certain case if I want to or the opposite case if I want to. And what you're describing is three different people have all the same numbers, but they approach them with different weights and measures. And again, I think that's okay.

But then if you're picking between those three models, like, how do you decide what's the right model? Then you're sort of employing these other things, I think, that I'm talking about, which is the best way I can describe, I stole this out of the New Yorker. The New Yorker, a guy named Burkhard Bilger, wrote a story about a carpenter named Mark Ellison, who was using a table. to make a curved cut. Now, if you know anything about carpentry, table saws are designed to make straight cuts. That is the purpose of a table saw.

Mark Allison, this master carpenter, was using a table saw to make this intricate curved cut. While talking to Burkhard-Bilger and an apprentice, he wasn't really paying attention to what he was doing. And Burkhard-Bilger is, like, how do you not have to focus on what you're doing? And the term that they came up with together was embodied analysis, which is almost like muscle memory, but intellectual. And that is the case that I make is that you want to be the person who has the best embodied analysis. The carpenter used the example of Roberto Clemente, how he would turn his back on a fly ball,

run to the spot where he knew the ball was coming, turn around and catch him. And that sort of deep understanding of a situation has a value. It doesn't matter that a model. might run slightly counter to your thinking there. Like the model has a worthy metric, and your experience is a worthy metric. And what I'm saying is the best decision making comes with a delicate, nuanced combination of those two things.

It's not a black or white way of thinking. And I used to be, you know this about me. I used to be a very black and white thinker. Like, this is right and this is wrong. This is universal and this is not. The world doesn't work like that. And for me, there's an advantage to being really smart and good about football's a great example.

Like those models, did they incorporate anything about stress? Like the Super Bowl is a different game. So any game analysis that you've done, like, did you look at which guys are going to perform under pressure or not? That, to me, is an element that you need to think about. But did the models think about that? I don't know. Well, a couple of things on that. One, you would say you were a black and white thinker.

I would just say you were judgy. Judgy, very judgy, yeah. Two, I think what you're talking about is the best model ends up becoming a combination of learned experience and data, right? It's like, and you wrote about this in the book, it's more than trust your gut. It's really maybe trust your eyes, right? obviously the eye test if if if you are if if you know what you're talking about lots of opinions are not valid they are dumb and my gut would be useless in a lot of situations because I don't have any knowledge you know to to back up my my feeling what I'm saying is if you have that

experience if you have watched a thousand football games and if you've bet on a thousand football games that has value that knowledge has value and I think we're we sort of live in a time when that human element is sort of dismissed as bad almost like it's dismissed as irrational or subjective there's all these words that we use to describe that sort of that little eggs that humans bring to things i'm saying i'm saying that has some worth it's it's and especially in the situation like you're talking about where everyone's got the same numbers like what's going to separate what there's no business book i could write where i go you know the best thing you can do is follow the crowd. Just do what everyone else is doing. That's the right

thing. You would think that was insane. But that's the argument that we have about analytics all the time, that it's the one right tool and it will always find the right answer. It's nonsense. Missing football? Well, you can still turn every Thursday into payday with NBA on TNT on Fanduil Sportsbook. It doesn't matter. If you win or lose, Fandul is giving all customers $10 back every Thursday in site credit. Just bet $10 or more on a same game parlay on any NBA on TNT game. Same game parlay is let you combine the moneyline points by player props and more all into one wager. I like same game parley bets because there are so many NBA markets to bet.

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that. Learn how it belonging begins with us.org. Brought to you by the ad council. You know, it's interesting. I mentioned the Bengals Ram Super Bowl. That's a big football game that happens here in the United States. I know the great cup is Mike. Yeah.

So it's like the gray cup, but smaller, I guess. It's a little bit. It's a little bit. like a combination of sort of the Gray Cup and the World Junior's finals in high. Okay. And maybe a bit of the tournament of hearts curling, I'm assuming. Exactly. Right. Right. Okay. All right. Yeah. The thing, there were so many people who were betting the Rams. The Rams got the preponderance of money. There were a lot of professional betters who liked the Rams. The Rams were open his three and a half point favorites. It went up to four. It got up to four and a half and five in some places. and everyone was saying the reason like the Rams is because the Bengals wins were fluky.

And there were too many numbers that were sort of violating their principles and what their models said. And in every matchup, the Rams win head to head. And there were a lot of us, myself included Simon Hunter, who's professional better, Chris Raybon, Sean Croner, a lot of action network experts who watch these games and thought, sure. But if it's a fluke that happens 20 out of 21 times over the course of a season, it's not a fluke.

It's how they play. And if the Bengals only lost three games by more than three points, there's something happening within the context of those games that is immeasurable in the overall stats, they have to account for some way. And I think that's a lot of what you're arguing. Yeah, it's where watching the game matters. Like, stats can give you, if you, there's a, the other football, soccer, Liverpool were built largely by two people who approached the game very differently.

One, they have a physicist named Dr. Ian Graham, who literally does not watch the game. He strictly uses stats. He maintains this database of 100,000 players. He thinks that watching film or watching the game itself biases him. He doesn't want that. He's as pure an analytical approach as you can get. But you mirror that or you marry that with Juergen Klopp, who's the manager, who has this, he played the game.

He has an instinctual understanding of soccer. He has a fluid sort of slashing style. He's brought sort of this speed metal approach to the game, this really human. element to it and both of those things combined allowed them to win their first title in 30 years one or the other i don't think would have done it yurgan needed that sort of sober second thought that the analytics gave them the analytical might needed that little what you're talking about well if the numbers if the numbers on the bangles seemed like flukes and yet there was you know what you said 20 out of 23 did like then it's not a fluke at some point it becomes not an accident

is how they play. And that you only get, I think, from sort of watching the games. Like statistics can be indicative, but they don't tell the whole sort of. Possession is another great stat in soccer that is used all the time. But there's such a thing as useless possession. Like when you're just passing it around in midfield is not particularly constructive. Fruitful possession is a very valuable thing. But that requires some watching of the game to go, oh, they're actually dangerous.

It's not useless possession. and it's dangerous possession. And that's what I'm talking about, is that sort of, what you're talking about is exactly right. And as it turns out, what was it, 2320, right? So the Bengals, if you bet the Bengals, it was the right call. I bet the Bengals. You bet the Bengals.

Lies, damn lies and statistics is what I keep thinking about whenever you're talking about, sort of how statistics can be used to manipulate things. Also, you mentioned Liverpool. You'll be glad to know that I was in L.A. last week on my flight out and on my flight back, uh, the two books I was reading were the I test by Chris Jones and lyrics by a famous Liverpoolian named Paul McCartney.

And I spent more time reading the I test by Chris Jones than lyrics by Paul McCartney. Um, even though, even though I do take issue with something in the book. So, uh, you talk about, because I like debate, by the way.

I know. This is what the, this is the whole point. It's the whole point. You talk about my, Michael Lewis and Moneyball and sort of the impact that Moneyball has had on this sort of concept, right? And for me, like, this, what Michael Lewis did is the epicenter of our business. Action Network doesn't exist if Michael Lewis isn't writing about Moneyball.

If he's not capturing how people are thinking opportunistically about being fans of sports, if the internet doesn't exist, if there's not a democratization of data. If there's not a perfect storm of all these things, then all of a sudden, gambling doesn't become as widespread. It doesn't become as accessible. It doesn't become something that ultimately is legalized, you know, in many, many states and continues to be legalized in more states. You write about the movie. I think the scene that you hate the most in the movie is my favorite scene, which is when.

Oh, God. Yeah. When Brad Pitt is sitting around with his scouts and they're all saying, we've got to, you know, they're talking about he's got a good looking girlfriend. I love his swing. He's a five to a player. And Brad Pitt is saying, no, we don't have to replace Jason Giambi. We have to replace this number of hits, this number of runs, this number of times a guy gets on base.

And let's do that any way we can. That's how I think about building a team. And you hated that part of the movie. I hated how the scouts were portrayed. They were portrayed as like bumbling idiots. deaf, they all had hearing aids. They were all gray-haired. They were combative.

Who's Fabio? Like, just they were portrayed as complete morons, which is what the analytics movement has done to, like, institutional knowledge. Like, if you, if you dare say analytics, but you immediately become a moron. You're a Luddite, you're a heathen, you believe in fairies.

Like, it's an extremely negative, like I've been attacked. for what I think by analytics people. And it's aggressive. It's like, and I'm the scouts, those scouts found Roberto Clemente. Those scouts found Derek Peter. Those scouts found

all the great baseball players that we all grew up loving. That's not an accident. They weren't lucky. They knew something about baseball. Was their knowledge infallible? No. Analytics taught us some really important things. Like, clot-hitting.

Like, I, I, I agree that clutch hitting doesn't exist. I agree that the sacrifice bunt is kind of dumb. You shouldn't do it. Those are things that analytics taught us. But all that knowledge, all the stuff that those guys knew in their bones has a value. So to make them seem like absolute morons, I thought was like an injustice. So some very smart people.

And we could use more smart people. I just don't understand why you would ever limit your perspective to the point where it's like, Well, I know you've seen the game for 40 years. I don't care what you think. That's ridiculous to me. That's like, and we have this, this, there's this strain of anti-expertyise that's kind of crapped in the society that's really damaging. It gets me like, I'm getting worked up.

My voice is about to crack. You know, you see it with the COVID debates. Oh, well, don't trust the experts because I have access to a computer. Well, they had access to 40 years of knowledge. Like, let's rely on that maybe a little bit. It's just, that's why I didn't like that scene. It just treated them like morons. They're not morons.

They just weren't right about everything, but neither is analytics. It's like, I don't get why we're arguing one has to be right and the other has to be wrong. They can both be right. And they're especially right when they work together to find the best answer. So a couple of years, last, was it last summer? I don't remember, it was right. No, it was the summer of 20 when the pandemic was sort of in full swing. I wrote a bunch of stories, like this series of stories for action now.

network that really traced the modern movement of sports betting. It started with this guy Charles McNeil who invented the point spread. He was a mathematician and a trader in Chicago in the 1930s. And then went to the development of sort of more analytically driven models. And a guy named Roxy Roxburgh, who by the way was a son of Vancouver and was running a sports book in sort of some of the Wild West oil trading offices in Vancouver in the early 70s, kind of got run out of town. Okay. And he moved to Vegas and was betting and sort of developed this concept that he could be

a bookmaker to everybody because he was better at running the numbers. And so people started buying his numbers on a consultancy basis. So he was the bookmaker who was feeding the stardust and he was feeding books in Reno and all that kind of stuff. And then ended with a guy who was 25 years old and a genius, math genius who studied, you know, computer science at USC and got into Bitcoin and, you know, made millions of dollars betting on sports and then moved to Costa Rica and is now moving markets, right? And I spoke to Michael Lewis about it. And I asked him like, and you comment about this. is it better that people can relinquish responsibility for their decisions because they've got a model?

And you have a line. I've become a professional hedger. Welcome to my kingdom of doubt. That's why we make the models. So we don't have doubt. And so we can say we have a handrail on the roller coaster to hold on to. I guess your argument. Michael Lewis was like, no, it's great we have these. I'm okay with people really, relinquishing responsibility. The models do the work. You would disagree. Well, I would say the models give us an illusion of certainty that we find comforting, but it actually doesn't really exist.

And we saw that with COVID all the time. Because the models predicted certain outcomes. You interfere with the process in various ways, positively or negatively, those outcomes change. Like the models, you know, I go back to, And this was in Moneyball, too. Like you go to a 98% chance, you go, well, that's going to happen.

98%. But two out of, or one out of 50, that happens not infrequently. That's one out of 50. How many times in poker that the one card you don't want comes on the river? It happens. And so we have this like, the models give us some, I don't know what you want to call it,

but it's like this, this idea that life is less chaotic than it really is. And I get the appeal. of that. Like we want to feel like we're in control. Like we want to feel like we're masters of our own faiths. I don't believe in not planning. Like I plan. I also don't believe in ignoring data, not anti-science. But the idea that if this outcome seems likely, then it's going to happen is really dangerous. Because then you don't prepare for the other thing. This is Trump winning the election. you know, like major consequential things happen all the time where we think, well, that's not likely. And it's unlikely things happen.

And so that certainty is like, it's a false sense of security that, again, I get we want the comfort because life seems really chaotic and difficult sometimes. But it's not real. And I think it gives you, it lulls you into the sense that things are going to go the way you think they're going to go. And my life has taught me that sometimes you get punched in the mouth. And then what really happened, then you decide who you are. Like those are the moments when, and the idea of abdicating responsibility in numbers. I mean, why do we want anyone to advocate responsibility? It seems hugely unethical.

Well, I don't know. The machine told me to do it. How mental would that make you if someone said, if you went to the bank and you said, well, there's this problem. And they were going, well, the machine decided that was right. It would make you insane. You'd like tell the machine that is wrong. You know, it's a, so I, this is, this is a larger debate about the, the path we're on as a society. And if it's good or bad to be so removed from each other, I, and I think it's ultimately bad.

I don't know, brother. There are days I'd love to abdicate responsibility completely. People love it. That's, that's why, that's why, because you can say, well, the model told me to do it. And I obeyed the math and the math told me, I get the idea that you wanted outside of yourself. But it's like, it's, it's, I don't know, it's not right. You can tell yourself whatever lie you want to tell yourself. But I mean, look at the game last night.

Like that game, if we really want to break it down, you analyzed the hell out of it in advance. Other people did as well. That game really came down to two officiating calls. Like that element exists. So you can plan all you want. Can you plan for officials suddenly deciding to not make a call that was pretty egregious? And then to make a call that seemed soft.

Like those are the, that's the, that's that game. And it's like, so everything you put into it came down on that. That's hard to think about it that way because you want to think, oh, no, I knew what I was doing. And I bet the bangles because I did some smart analysis. And you did. But ultimately, the score line was dictated a lot by two calls that were pretty random. You're 100% right. That's also something that we talked about on our podcast earlier in the week is that at the end of the day, the officials had a much bigger impact on

this game than they should have. But listen, I actually love everything you're sort of advocating for in the book. I think for anyone who listens to this podcast, which tends to be people who are looking for answers, looking for ways to mitigate risk, looking for models and predictions that help them find a 3% edge instead of being in 50%, but being in 53%. One of the best sort of moments in the book for me, and this is what I want you to answer before we get out of here, is you talked about how the best time for people to shine is during life storms, right? The idea that extreme moments are when people are going to outshine the machines because of their imagination. Give me an example that you can think of from the sports world when that's

been true. Oh, gosh, sports. So in the book, I talk about, you know, weather, literally climate, because the models that we use to forecast weather are less and less good at predicting extreme weather, because the models have never seen it before. So like the data mining or, you know, is basically relies on the future behaving something like the past. And in climate, it doesn't. The same thing happened, you know, there was wildfires in California and iPhones weren't capturing how red the skies were. And people thought it was like this tech conspiracy to make it seem less bad than it actually was. And it's just because the algorithm that operates your camera just didn't understand what it was seeing. And it was like, well, those skies can't be that red. I'm going to correct it.

You know, because it wasn't looking at a volcano. It was trained to know that volcanoes are red, but skies generally aren't that red. And so it was fixing a problem that was in fact reality. I'm trying to come up with a good sports example where it's like where the past did not behave. Well, look, you had one in the book. It might not be about imagination and pressure. But the whole Barry Zito experience, I thought, was a great reflection of lack of imagination of what could happen. No.

You know, not a necessarily. I was trying to come up with a positive point. one. Barry Zito was a negative one. Yeah, because statistically, Barry Zito seemed like a lock. When the Giants signed him, you know, he was,

I know wins and losses are sort of fraught, but he was 93 and 11 when the A scored more than three runs. He'd never had an injury. He projected to be better than All of Fame pictures in almost every category, if you'll follow the stats. And what, this was one of the times,

when I really started thinking about what I believe in, because I would have these arguments with people about Barry Zeta, who I knew as a human being, that spent a lot of time with him. And I think he was damaged by the contract itself. When he signed with the Giants record contract, and I think Barry, who was a pretty sensitive soul, just took on too much weight,

and it screwed up how he picked, because the way he pitched, he talked about being an instrument that the universe played, You just let it flow through you, you know, that flow state. You don't think about what you're doing. He talked about being consciously, you know, working in your subconscious, consciously working in your subconscious, like flipping a switch and just turning everything off.

And the contract made it impossible for him to do that because now there's all this outside influence and pressure. And analytics guys were like, well, no, there's more foul territory in Oakland than San Francisco. So he didn't get those foul ball outs. I'm like, that's not, that can't be. the whole answer to why Barry Zito fell off a cliff as soon as he moved over to the Giants. Like, foul territory at home is one small factor. And it's just the idea that the contract might damage him never entered the conversation. And never entered the conversation from the Giants' perspective.

It never entered Barry's thinking until it happened. His agent's thinking, of course, he wants the biggest contract. But like when Barry found out about the contract, he was out with a friend having sushi and sashimi, and he choked. Scott Boris, text him the numbers. and he choked on his fish. And I'm like, that matters. That matters. And so I think when you're signing, that's a great example.

I said when you're signing a player, like, will this contract change how he plays? Will it add pressure to him or will it make him rise to greatness? And that the numbers won't help you there. That's when you come down to talking to someone and go, what kind of person is this? Is he going to rise to the occasion or is he going to choke? And that's, you know, a super interesting debate. that I think you can't really answer with a spreadsheet. That comes down on being in a room with somebody

or watching how they play or watching them in moments of stress. And that's, that for me is that like that 3% you're talking about. And of course, retroactively, you can go, of course Barry Zito was going to fall off a cliff. Of course that contract was going to screw with his head. I mean, but we didn't see it at the time. And that's, yeah, that is a good example of a negative.

I'm trying to come up with a positive one where, where, you know, like, Bryson DeCambo and golf is really interesting to me because he's playing in a different way and they keep trying to tweak the game to mess with him. And it's like they don't want what he's doing. And that sort of give and take, like can he survive golf, screwing with him is sort of a really interesting thing for me to watch. Because he's pure analytics, basically.

Yeah, you write about this in the book. Like he is going to completely re-enacted. imagine, and we've talked about this in action, Jason Sobel has written about it really well, like completely reimagine how he's going to swing the club and what is important to him, which is basically hit the ball as far as you fucking can. Yeah, he's changed what matters. It's not your score. It's your ball speed, it's your swing speed.

And golf doesn't like it. And so, you know, there's an interesting thing happening with Bryson right now where golf, the golfers themselves voted to ban green reading books like the books that had these beautiful laser red maps of every green they played and they were perfectly legal bryson used them all the time to figure out lines because bryson was good at bryson has a literal chart that he consults this is the this is the distance this is the slope this is the blind this is how hard i hit it and he knows you know he can control how hard he hits it but the line reading was a big advantage to him. It helped them. And they took it away. And they took it away. It's like a pretty purposeful rebuke

of how he plays the game. Like, yeah, they took it away from everybody, but it's really going to mess with Bryson. Like I think this year is going to be really interesting to watch it because, you know, he built this system that now no longer can be used. And that's life. That's life.

This is, Bryson is also, in a way, the argument against pure analytics because I can always mess with the system a little bit. And then what now? And that's, I guess, the book. The book is basically, how do you succeed when you get asked, what now? And for me, the answer isn't always numbers. Sometimes you just got to be an awesome person.

That's a lovely sentiment to end it on, Chris. I hope the book is hopeful. It is hopeful. It's totally hopeful. The book is full of amazing people. People should read it. It's a great book because there is like not even in sports, right? You mentioned in polling, in COVID, in the way the economy is being discussed, in sports,

that really is the reason we want to be here and the thing that we want to escape from the COVID and the economy and the politics and the environment, all of which are sort of discussed in the book. Like, this helps us find clarity when we're looking for new ways to be fans. And for that reason alone, I would say, everyone, go by the eye test, a case for human creativity, emphasis on the creativity in an age of analytics by multiple national magazine award winner, Chris Jones. Thank you, Chad. That's lovely to hear your voice.

And thank you for your earlier patronage in my career, no matter to love. Whatever, man. You don't even mention it in the book. It's like kind of weird. It did. It did matter. It helped a lot of my thinking. It helped a lot of my thinking. Travel safe, buddy. I'll talk to you. Okay. Thanks. See you. All right. I want to thank Chris Jones, brilliant writer, wrote an amazing book called The Eye Test. Also, I want to remind everybody, I talked a little bit about this in the podcast on Monday,

the Super Bowl review. Simon and I have gotten a lot of questions about how we'll handle the show now that NFL season is over. Don't worry. We will still be here. Tuesday and Thursday. We'll cover everything that matters in the NFL offseason, the combine, the draft, free agency, all of it. It is a huge, huge part of what we're going to continue to do. We'll also cover NFL betting 101 educational stuff. We'll talk about how Simon uses game tape, how he builds his models. We finally have time for all that stuff. Honestly, the podcast got so big, so fast. We were always in the midst of covering games and talking about games and people have a ton of questions so we want to get to those. But the gambling season is never over. That's why we're

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