686. Why Is It So Hard to Find an NFL Quarterback?

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28:37To really do good science, it takes a tremendous amount of training. We talk about it being a 25-year overnight sensation. It's like we had to make sure the science was sound. That is Scott Goldman, the founder of Athletic Intelligence Quotient, or AIQ. Before that, he was a practicing psychologist. I have two PhDs, one's in clinical psychology, one's in school psychology. At the University of Arizona, Goldman became one of the first sports psychologists embedded within a Division I program. His work there caught the attention of the NCAA, which in 2013 asked Goldman to join a new task force on mental health.

29:16By then, he had been thinking about the quarterback prediction dilemma for a while. One classic example came from the 1998 NFL draft. The big debate was between Peyton Manning and Ryan Leaf. Ryan Leaf was known as being physically dominant, but he had kind of a relatively short exposure career. Peyton Manning, on the other side, had less of the physical attributes, but, you know, his dad was a legend, Archie Manning. So as I was watching the debate between these two quarterbacks, who goes one, who goes two, I said, I think we could build a better mousetrap regarding at least understanding the intelligence part.

29:54The Wunderlich test that was used for years by NFL teams was created in 1936 by a Northwestern University graduate student named Eldon Wunderlich. It was meant to help an employer assess the problem solving and reasoning abilities of prospective employees. Peyton Manning and Ryan Leaf had gotten nearly identical scores on their wonder lick. The Indianapolis Colts took Manning with the number one draft pick, and he wound up playing in four Super Bowls, winning one with the Colts and another with the Denver Broncos. When Manning retired, he was a Hall of Fame pick. Ryan Leaf, meanwhile, was drafted number two overall by the San Diego Chargers.

30:37But Leaf got hurt in his second season, and within a couple more years, he was out of the league. By then, he had earned a reputation as a bad teammate and a malcontent. How could two college quarterbacks who received nearly identical pre-draft grades have turned out so differently? And what if there was a better way to figure that out before the draft? Scott Goldman and his partner Jim Bowman set out to build a test that might help. We spent 15 years studying unsolvable puzzles, not just in sports, but we also looked at military, first responders, so firefighters, police officers, etc. So anytime like a firefighter has to kick a door down and scan looking for threats and danger as well as victims to save, that's the same as the quarterback.

31:22Goldman found that a comprehensive athletic profile consists of four domains. First domain is physical. Are you big? Are you strong? Are you fast? Bucket two is knowledge or experience, what they already know from the systems they came from. Bucket three is personality or character. And then bucket four is intelligence. And what is intelligence in a quarterback context? It's things like decision making and processing speed and visual spatial understanding. So the quarterback or the play caller calls the play in, which is some super complicated, like learning a whole nother language, like trying to understand French for me, which I can't speak French, right?

31:59Right. X blue, Z nine, sevens, blah, blah, blah, blah, et cetera, et cetera. So the first part of intelligence, right, is can he translate that? Can he recall what that play is? Some quarterbacks can do that easier than others. The ones that struggle, they have the wristband, right? So the play caller goes, hey, it's 17 on your wristband. And then the guy looks up. Oh, hey, 17. This is what we do. So after the play is called, he's got to scan and identify another intellectual property. So he's got to identify the defensive coverage. They're getting talked to in the headset. So even while they're multitasking, the headset's also kind of chirping in their ear.

32:36And so imagine like you're trying to figure out this puzzle. You've got your coach giving you advice and guidance. And all of a sudden the defense shifts. And you're like, shoot, was the instruction that was just given meant for the defense that we were both looking at or the defense that we thought was coming? The only thing I can sort of equate it to, and I have no experience at this either, but it feels a little bit like you're doing air traffic control and you're flying the plane at the same time. Yeah. Can you describe generally the attributes of a person that's really good at that? You need someone who's strong enough to make the throw.

33:10You hope for somebody who's got a sophisticated knowledge of the game. You hope that their ability to handle the pressure, the stress, and also the leadership qualities to keep everybody else on track. And then you also hope that they have intelligence. And that's where the AIQ comes in.

33:29Goldman and Bowman built out the original AIQ database using thousands of college athletes. Today, the AIQ is used by NFL teams as well as teams in all the other major pro sports leagues in the U.S. and in many other countries. So how good is the AIQ at predicting whether an athlete will thrive? I mean, not to get too nerdy, but the place that I start with is we're the only instrument that has five published papers. And when I say published papers, I mean professors from universities took our data and they found statistically significant correlation with on-field performance. I'm looking at one.

34:08It's called Head in the Game, the Impact of Cognitive Abilities on Performance of NFL Quarterbacks. This looked at data from 42 quarterbacks who had taken your test at the NFL Scouting Combine. The authors tested whether AIQ subscales, visual spatial processing, reaction time, decision making and learning efficiency, whether they added predictive value beyond draft position alone. And the answer was basically a big fat yes. The numbers are kind of remarkable to me. So you must feel good about them. Yes. Well, it just means that we're on the right track, right? And it was QBR, quarterback rating.

34:43It was higher AIQ scores tended to make less turnovers. It was passing yards, passing TDs. time efficiency, career approximate value, career longevity. So we found pretty meaningful stuff. Can you just describe the test for me, including how it's administered? It's all done on an iPad. So what it looks like to the player is it looks like you're kind of playing a lot of games, kind of like Candy Crush or Tetris, depending on how old you are. How long does it take to take the test? 35 minutes. What is the range of scores? 100 is the mean score. And then you have a 15-point standard deviation in each direction.

35:21Anything between 90 and 104 is considered an elite athlete's normal profile. If you get 105 to 114, that's a strong score. And 115 or higher is an elite score, meaning this is something that's really a gift and makes life easier for you. And then on the flip side, 85 to 89 is an area to start to pay attention to. And 85 and lower is, hey, let's come up with a strategy that can help offset this. The one thing I don't understand, Scott, is how a non-athlete is expected to do on the AIQ. In other words, how geared is it toward intelligence within the construct of the sport? I, for instance, not a professional athlete, unfortunately.

36:07Well, I think that's just the beauty of it, right? Is there's all kinds of aspects and forms of intelligence, right? So how would you do on the AIQ? I don't know, but I'm willing to let you take it and we can find out. Can't wait. Is there anything I can do to prepare? Get some good rest. This is what I tell the players. I just say, give your best effort, work as quickly as you can without making any errors and enjoy the process. It's a challenging test, but most people do better than they think they do because science has often shown that we tend to remember the questions we got wrong more than the questions we got right.

36:43You don't have like an age-adjusted grading curve though, do you? We do not. How old are you? Damn it, 62. You're going to be a little bit outside of our optimal curve. Oh, I would think I'm a lot outside your optimal curve. Well, I was trying to be polite, but yes. And I'm sorry to say this to anyone over a certain age, but our cognitive abilities do start to decline at around age 35. What we'll do is we'll take your scores and we'll just put a little asterisk by it and know. No, no, no, no, I don't want an asterisk, but you're saying there's probably not a lot of chance that my AIQ score is going to be so good that the Pittsburgh Steelers, for instance, are going to want me to come and replace Aaron Rodgers.

37:22Well, let's see what the results are before we come to that kind of decision. And look, if it's as promising as we hope it to be, I know that there's more than just the Steelers that are looking for a good quarterback.

37:38Scott Goldman set me up to take the AIQ. So I sat down in my office with an iPad and our production assistant, Elaria. Okay, there are 10 subtests. Each is two to three minutes long. Have fun and do your best. No problem. Here we go. In a moment, you will be asked to do a number of things, like rotating shapes in your mind and making quick comparisons between numbers. I can feel my heart racing. Is that what you're supposed to do? Good luck. Thank you. Okay. Start. Shape rotations. Paired associative learning. The first pair is already there. Oh, man. No way. Object scanning. In this activity, you'll be asked to search the screen.

38:21Whoa. Route finding. Now you'll be asked to find the shortest route. Sable reaction time. Memory for shapes. Whoa. Whoa. Come on. Seriously? Number matching. Choice reaction time. Design matching. Continue to touch each box until it matches the design. Oh. Now you are going to see those. That's brutal. Continue to touch the boxes to make the designs you see. That's brutal. Each time you have finished a design, pressure begin. That's really hard. I'm going to do very poorly on this one.

38:53All right, Scott, I took your fiendishly difficult test the other day. I think I know the sections that I did really badly on and then some sections I did better on. But I don't know. You're the one that wrote the test and you scored it. So how did I do overall? I'm about 5 '11", so I need to add at least a couple inches, a bunch of pounds, and have a much stronger arm. And I need to be 40 years younger. But other than that? You're ready. Other than that, you're ready. So the first question that most players will ask is, so how did I do? Did I do good or did I do bad? What I always try to remind them is two things.

39:26There really is no good or bad. It really is just describing how you do things. My guess is as I go over this with you, you're going to go, I did know that or I knew that about me or, oh, hey, that kind of explains a little bit about what I do. And then the other thing is remember that there's no one element or piece of data that perfectly defines your capabilities. We have a section on the report, and I don't know if you're looking at it right now, but on this first page, you'll see something called positional focus. I went and I talked to coaches that I've worked with over the last 30 years in the NFL and collegiate space for every position, as well as offense coordinators, defensive coordinators, etc.

40:07And I just said, what are some of the intellectual abilities that you most value in a quarterback? So I collected all this data of what each coach is looking for for every position. My partner, Jim, he looked analytically at some of the highest performers, MVPs, Josh Allen, Lamar Jackson, Patrick Mahomes, those folks. And he looked at where they were outperforming their peer group on the AIQ. We did this independently. We came together and we had an 87 % alignment. And that's what we call the positional focus. So the most important element that we have found to be of value is something we call learning efficiency, which is the ability to kind of like download and absorb a playbook.

40:51It's the ability to recall it. That was an area that you scored in the strong range on. The other thing that I sent you all was our AI bot. We call it the AIQ+. We fed it over 297 documents of just sports-specific intelligence theory. then we added to it everything we've ever done like every development book we ever made for a professional team every player profile i asked it what style of offense is steven best suited for what's the best way to coach him and one of the things it picked up on was your strong learning efficiency so it talked about things like you're being able to run more complex playbooks that you could absorb the playbook faster than your peers the second area that you scored really well on was called spatial awareness, which is really about pocket presence.

41:40It's knowing where you are in relation to teammates, opponents. When you think about the pocket and stepping up in the pocket to avoid a last second hit, that was another area. And then the next one that was one of your highest scores was something called multiple target search. And that's the ability to scan. So it's kind of like you go high, low, you do full field scans, you look at coverage based answers. What this says is you're less likely to make errors and you're more likely to be a great game manager. So, you know, fundamentally you scored in the strong range on one, two, three, four, five, six, seven, eight, eight of the 16 abilities, which I think is pretty impressive.

42:23So first of all, plainly, I made a bad career choice. I should not be podcasting. I should Could have been a quarterback, obviously. Yeah. I mean, who knew? Let's say you got this report on this quarterback named Dubner, and you don't have a scheme that fits. What do you make of this prospect then? Do you say, okay, this guy's got talent, he's got cognitive ability in a certain direction, but he's not right for us? Here's the luxury of the role that I sit in. I'm an information provider, but I'm not a decision maker. So what I do is I try to tell the head coach and the GM I think you've got a choice.

43:00Do you love his physical talents or do you want to go let him be good for someone else if you know he can't be great for us? And sometimes they say, we still like him. We like his arm strength. We like his mobility. We like his throwing angles. We like the coach that he came from. We still like him, even though he might not be a great system fit. How can we bridge that? And that's where I'll ask the AIQ+. I'll say, hey, what's the best way to coach this guy. And that's one of the things that I asked the AIQ Plus about you. You want to know what the first thing that really popped to me that the AIQ Plus said that I loved?

43:37Yes, please. It said that you should have predefined panic answers. That doesn't sound good. No, it's actually, it's perfect sense to me based off the profile. What it's saying is if the situation goes to, I don't, sorry. No, you can say it. It's okay. If the situation goes awry, let's be sophisticated, right? If the situation goes awry, some people are really great at improvising. And your ability to download such a high volume of information, we're better off teaching you that the situation could go awry. And if and when it does, here are some predetermined solutions or scripts that you can activate.

44:21I think you could be kind of like a Brock Purdy. I did ask the AAPQ Plus out of curiosity how to compare you to Patrick Mahomes and Josh Allen. And? It said that they were better able to handle the chaos and the unpredictable, and you had some real strengths in the ability to manage a game. Just generally speaking, intelligence is one of the greater predictors of success. People with high levels of intelligence, they have the ability to discard a calcified way of doing something. When things go awry, your ability to improvise is very much based off of intelligence. So sports, firefighters, police department, and currently AIQ is being used by many of these types of professions.

45:03Military, special forces, airline pilots. There are other aspects of intelligence that we do not measure that might have to do more with, say, analytics or math or language. But for us, what we've talked about was high pressure, chaotic, constantly mutating puzzles. Let's say my AIQ score came in and I'm a current prospect in the draft. Which teams would benefit from a quarterback like me? Ooh, I think there's a lot. I would go more with the play caller than the team because that's the thing you really want to align is the play caller and the quarterback. So play callers that I think are amazing that you would fit wonderfully with.

45:44And again, assuming everything below the neck is of an elite superior level, I think you'd be great in Minnesota with Kevin O 'Connell. Unbelievable, brilliant mind, brilliant play caller. You know, I look pretty good in purple. I didn't know we were adding that as one of the variables of consideration. How do you feel about colder states versus warmer states? Minnesota, first of all, they're in a dome, so I'm not going to worry. And also like the downtown in Minneapolis, they have those skyways that are heated and I'm okay with that. All right. So we'll put in a word with the Vikings for you to potentially be an undrafted free agent.

46:18What's the youngest player you've tested with AIQ? 16. What if someone came to you and said, I've got a 12-year-old quarterback or maybe I run an academy where I've got 100 12-year-old quarterbacks. And I really believe in what you're doing, Scott. I think it's meaningful and the data show that it's predictive, right? that people who do better on their AIQ do better in football, and it's more predictive than a lot of the more traditional yardsticks. And even though I understand that AIQ is measuring who they are, I also wonder if we could use it a little bit the other way around to coach them up cognitively while they're young.

46:56What do you think of that idea? That's what we created it for, was not to be a predictive model, but to be a descriptive tool. I've never met a player that loves to get mother effed. And I've never met a coach that really loves to do that. But the frustration between the player and the coach happens because there's some kind of disconnect. And if you look at the way that we designed the AIQ reports and the AIQ Plus to talk, it's very much a descriptive element. We are describing what the player can do and how the player processes the game where it was like, okay, so this is what we would do with this guy.

47:33This is how we would get them, you know, to really handle the rigors and the pressures of the game.

47:43We will be right back with the final act in our story about how to pick an NFL quarterback. I'm Stephen Dubner. This is Freakonomics Radio. As always, thanks for listening.

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48:33Freakonomics Radio is sponsored by PNC Bank. Boring. Great word. Bad rep. Yet time and time again here at Freakonomics, we find that when something culture-changing happens, boring things like calculations and careful planning are usually behind it. Which begs the question, why not apply it to other aspects of life? Like banking, for example. Well, PNC Bank did since its inception, proving time and again that the best banking strategy isn't the exciting type, but the steady, reliable, definitely not YOLO type. PNC Bank, brilliantly boring since 1865. Brilliantly boring since 1865 is a registered mark of the PNC Financial Services Group, Inc.

49:13PNC Bank, National Association, member FDIC.

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50:30When a seemingly intractable problem meets a potentially disruptive technology, Silicon Valley usually isn't very far behind. In this case, Silicon Valley by way of Ireland. I'm Stephen Smith. I'm the CEO and founder at Kipman Labs. Smith was a strength and conditioning coach for an Irish pro rugby team before he moved into data science. His firm now works with all kinds of sports organizations, including teams, leagues, and governing bodies across more than two dozen countries. So what is Kitman exactly? Kitman Labs is an athlete intelligence platform. We help sports organizations capture, manage, and derive insight from data across the full athlete lifecycle.

51:13Everything from recruitment and development through to performance optimization, welfare, and even the operations of major leagues themselves. And why the name Kitman? It doesn't really translate to the US very well, but in Ireland, the Kitman or equipment manager almost is always the lifeblood of the organization. They do the hundreds and thousands of tiny things that nobody sees, but without them, the entire organization falls apart. We had a Kitman called Johnny O 'Hagan, this grouchy old guy who had just been there for about 30, 40 years. If a cleat popped off, of course he had the exact one ready for them.

51:52The jerseys were set up, the water was set up, the fruit was set up, the whistles were there. He got sick at one point in time, ended up in hospital. And the entire organization nearly fell apart. He just did the thousands of unseen jobs that nobody really appreciated. And I loved that concept. And for the company and what I wanted us to do, I wanted us to be the lifeblood and power behind great decisions in an organization, but not the person that's picking up the trophy, taking the accolades, doing the interviews. I wanted us to be behind the scenes, you know, the hidden jail within the organizations.

52:24The reason we are talking to Smith is because we heard about a model that Kipman has built, a model that uses, here, I'll read you a little bit, a model using AI trained on more than 15 years of NCAA performance and NFL combined data to identify the statistical profiles most associated with NFL success. So does this mean that Kipman can predict which college quarterbacks will become great pro quarterbacks? So the role of the model is not necessarily to be predictive. We don't have a crystal ball. The problems that we're solving are really complex. The role is to reduce uncertainty. So the model draws on a very broad set of inputs, physical and physiological data, training history, match performance metrics, biographical factors, and increasingly psychological behavioral indicators.

53:09And then we're looking at, of all of those characteristics, which are most indicative of long-term success? And then we're going back and sweeping the data, looking for the next factor in line, and the next, and the next, and the next. And we're building that breadcrumb trail behind it. And then what we're doing is trying to see, okay, who fits that profile? The Kipman model found that the top quarterback in this year's draft class, with an AI success prediction of 51%, was, not surprisingly, the number one overall pick. The strongest quarterback signal was Fernando Mendoza. Undefeated season produced exactly the kind of statistical fingerprint that the model rewards most highly.

53:48In the old days, statistical fingerprint was mostly about physical skills, size, speed, arm strength, etc. And now? What the data increasingly points to is the importance of processing speed. How quickly a quarterback reads a defense, how they go through the progressions and makes decisions on their pressure. There's also growing interest in resilience metrics, how a player responds to adversity, but within a game across the season. And frankly, coachability, right? The rate at which a player absorbs and applies new information, how quickly they're developing. They are some of the most predictive long-term variables that we see today.

54:21Do you have a relationship at all with the NFL or with NFL clubs? The relationships that we have with some of our larger leagues and sporting bodies are highly confidential. I can't actually speak directly about them. I'm going to take that as a probably. Yes, we operate in professional football. You also operate in the other professional football, what we call soccer, the English Premier League, MLS in the US. Tell me about that. The core and backbone of what they're trying to do is to produce better players. So in the Premier League, they have a thing called the EPPP, which is the Elite Player Performance Plan.

54:57And essentially, that is a set of rules and regulations for how you develop talent. So from the age of U9 all the way through the first teams, they have a set of standards and regulations for everything from tactical development, technical development, physical development, and even like medical care, resilience, robustness, and even some aspects of education. Our platform is designed to help them to collect all of the relevant data in each of those different strands and or operationalize the workflows for specific users. So for example, if I'm a coach within an academy setting in somewhere like Chelsea Football Club, I'm the U9 coach.

55:34I come in and I build out my session plan. What athletes are involved in each one of those drills? How long are we going to spend on that? And then what's the physical load or toll that that's going to take on our players? Then the fitness staff members are coming in and they're pulling in all of the data from, let's say, wearable technology. If they're using performance tracking data to objectify some of the tactical and technical pieces of information, that's coming in. if there was an injury in that practice session, the medics would come in and log the injury within the system. And then the next day, as the athletes are recovering, they may be collecting recovery indexes from them or things like how's their neural system, how have they slept, how are they moving.

56:11So what we're trying to do is basically build a 360 degree view of what are we doing to the athletes? What are the load and stimulus we're placing on them? And then how are they responding? So U9, we should say, this is a concept that Americans will largely be unfamiliar with. That's under nine years old, correct? Absolutely. So these are kids. What you're describing now is capturing data of the athletes that are already in your building, essentially. Talk about data that you use to analyze for recruitment and predicting. Let's say you're an NFL team that's looking at potential draftees from college.

56:46Typical models for scouting or recruitment. If we use the NFL as an example, they are looking at your college stats from that year, who is the best quarterback, who are the best running backs, who are the best receivers, et cetera. They look at key attributes that are important for each of those positions. What we're trying to do is slightly different in that the time horizon we're looking at is much longer. So with regards to like the EPPP, what we're trying to do is look at what do players that make it and play once in the Premier League look like? What do players that play a hundred times? What do players that play 10 seasons?

57:15And when you invest in these types of league-wide initiatives that span this type of time horizon, you can really start to basically reverse engineer. What did that person look like? In today's landscape, the Premier League are the highest producing league from a professional talent basis than any other league in the world. And they have the benefit of now being able to look back on players like Bukayo Saka or Cole Palmer, and they can basically follow them back to when they're U9. And when we look at the NFL today, we don't have that luxury. That's because you don't have these future NFL players from the time they were eight or nine and all the data on them.

57:50Is that why? Yeah, number one, I think we need a connected pathway. Since I've moved to America, I've realized, well, there is somewhat of a disconnect between the professional game, the collegiate game, and the youth game. Chelsea's academy are recruiting at the age of eight. Major League Soccer have now made a huge investment in both Next Pro, their semi-professional league, and then Next, which is their elite development. League. And they're getting all the way down to U13 right now. That's a tradition in soccer that we don't have in American football. Let's assume that that tradition doesn't start in American football.

58:21In other words, let's assume that the Pittsburgh Steelers and Green Bay Packers and Dallas Cowboys aren't starting youth academies where children are starting from the age of seven, eight, nine. What can you do to establish a firmer pathway like the one you're describing for the NFL? Well, you look at a partnership model. I know that that's more complicated in the world of the NFL because high school football has its own situation. Collegiate football is a powerhouse. But I think there's an opportunity to create some level of partnerships. And ultimately, this will benefit players and it will benefit the game and it will benefit fans.

58:55I mean, listen, when you look at predictive modeling or you're thinking about scouting recruitment, you're thinking about performance optimization. we've seen these superstar athletes that come through but then going from being a superstar in college to being a superstar in the NFL it can crush people if they don't have the mental resilience and the tools to be able to deal with that we've often seen players that have come through who weren't in the first round weren't in the second round sometimes weren't even a third round draft pick become like the player like look at Brock Purdy people would laugh at you when it was a draft year if they had suggested that you would put Brock Purdy as a first round draft pick But like form has shown.

59:31So in your view, if you could gather as much data as is possible on Brock Purdy's life and career, physical, strategic, behavioral, cognitive, et cetera, and go back as far as you could, what do you suspect that you'd find in the data that was essentially overlooked by 31 teams? I think you'd see a lot more consistency than you sometimes see in other players. If we have the data and the inputs about what makes success, what drives success, how we create success, we can replicate that. We can scale that. I see that Kitman Labs also does some work with the U.S. military, more than$4 million in defense contracts over the past several years.

1:00:11Tell me about that. It was kind of an area that we stumbled into, quite honestly. We've been very heads down in the world of sport, but they've reached out to us and asked us, we come in and look at a particular body of work for them. We're trying to recruit, just like we are in sports. We think about that as a really simple thing in the US. Well, you go, you sign up and you recruit it. No, that's not really exactly what's happening. What it takes to be a fighter pilot is completely different to what it takes to be a pararescue jumper. It's very different to being a Marine or very different to being a SEAL.

1:00:38So how we recruit for those and the types of characteristics that are needed is the same thing as, Well, the characteristics to be a quarterback versus a running back versus a receiver versus a lineman, all of those are different. Once they have them in, they care about development. So how do we give them the right characteristics? How do we develop all of these things to put them in the right position, just like we do in sport? And then when we have them at the other end of a training pipeline and they're ready for work, how do we keep them healthy? How do we keep them performing well? They're the same underlying principles.

1:01:05So whether you're playing football, whether you're playing rugby, whether you're playing tennis, whether you're running around in a training environment to be an airman, We care about measuring the load. We care about understanding what you're doing. We care about understanding how you're responding to that. And that's about people, not about sport.

1:01:22I learned a lot today from Stephen Smith, Scott Goldman, Dan Hatman, and Kurt Warner. And I'm guessing you did too. But still, there are some big questions. Like, will NFL teams finally learn to identify which college quarterbacks will become good pro quarterbacks? It's one thing to over-invest in a college superstar who turns out to be a bust in the NFL. But what about the other scenario? The Kurt Warner scenario, where a quarterback who turns out to be world-class was passed over by every team in the league. As it turns out, history may be repeating itself within the Warner family. Kurt's son EJ is also a quarterback.

1:02:05He just finished his college career, and he too went undrafted. Here's Kurt. EJ, he played at a little smaller school. He didn't play at an SEC school or a Big Ten school. Fresno State was where he finished up. He has done it really well for a long time. But there are some things that he doesn't stack up with what's prototypical. You said as a player, you could understand that and process it. What about as the father of a player, though? It's got to be hard. It is hard. And I think the thing that's hard for me with EJ is because I know what he does really well. And I've watched it. And he was in some situations in college, very much like me.

1:02:50I've watched him play in so many different scenarios. And I understand that he's not the most physically gifted player to play. But these mental things that I'm talking about, I think he's very rare at those things. Do you think he's going to get a chance? He's only 22 years old. I do believe that he's better than some of the guys that are out there, and I do believe he's going to get a chance. EJ is better than me coming out of college, and it's not even close. But I do believe he is an NFL quarterback and could have a long career in the NFL if given a shot. EJ Warner did have tryouts with two NFL teams, the Kansas City Chiefs and the Denver Broncos, but he didn't make either roster.

1:03:32We will keep an eye on him and let you know if there's any news. In the meantime, my big thanks to Kurt Warner, as well as Smith, Goldman and Hatman. Let us know what you think about this episode. Our email is radio at Freakonomics dot com. Coming up next time on the show, prediction markets have been around for a long time, but they've suddenly become famous because they will let you place a bet on just about anything. So is that all they're good for? Kalshi is the most accurate way to predict the future. We'll hear from the CEO of Calci, as well as the economist who pioneered the prediction market idea 40 years ago.

1:04:12When we do head-to-head pairwise comparisons of betting markets and some other institution at the same time, same topic, similar resources, the markets just do about as well or substantially better in terms of accuracy and similar cost. That's just a remarkable fact. And we'll hear from a regulator about prediction market risks. What I think is the cost and a very real serious cost is trust in the markets. That's coming up next time in the first of a two-part series on prediction markets. Until then, take care of yourself. And if you can, someone else too. Freakonomics Radio is produced by Renbud Radio.

1:04:50You can find our entire archive on any podcast app. It's also at freakonomics.com where we publish transcripts and show notes. We will be sure to post my AIQ scores there if you want to take a look. And a special thanks to listener Peter Wynn, who suggested this episode on the quarterback prediction problem. This episode was produced by Pete Madden and edited by Ellen Frankman. It was mixed by Jake Loomis with help from Jeremy Johnston. The Freakonomics Radio Network staff also includes Dalvin Abouaji, Eleanor Osborne, Elsa Hernandez, Gabriel Roth, Alaria Montanacourt, and Tao Jacobs. Our theme song is Mr.

1:05:26Fortune by the Hitchhikers, and our composer is Luis Guerra. Thanks again for listening. Should I leave my phone on in case the Vikings or Jaguars or Bears call? I think Lloyd from Dumb and Dumber said it best. You're saying there's a chance. I'm saying there's a chance. That's right.

1:05:51The Freakonomics Radio Network, the hidden side of everything.

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