What Are the Odds?

What are the odds your crazy play at the end of the game works? Neil deGrasse Tyson and co-hosts Gary O’Reilly and Chuck Nice investigate the use of AI and machine learning to predict and understand sports with mathematician and author Matt Ginsberg.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:01Neil deGrasse Tyson?

  Welcome to StarTalk, your place in the universe where science and pop culture collide. StarTalk begins right now.

• 0:16Neil deGrasse Tyson?

  This is StarTalk Sports Edition. I'm your host Neil deGrasse Tyson, your personal astrophysicist. And today's sports edition, we've titled, "What are the odds?" And if you're gonna start a program with that question, somewhere in there, there's gonna have to be a mathematician. So, we'll get to that in just a moment, but first let me introduce my co-host Chuck Nice, Jackie Baby.

• 0:39Chuck Nice?

  Hey Neil, what's happening?

• 0:41Neil deGrasse Tyson?

  Alright, now you pay your rent telling jokes, but so why do we have you on this?

• 0:46Chuck Nice?

  Um, actually, if I were good enough, if I were good enough to pay my rent telling jokes, I wouldn't be here Neil.

• 0:56Neil deGrasse Tyson?

  Alright, so Chuck, now we love you because you bring some levity where it's sometimes needed. But also, you're a sports enthusiast on a level that I think is uncommon among people who are not otherwise paid to have that level of knowledge, so, good to have you. But where we get our street cred, of course, is from Gary O'Reilly. Gary? Hey Neil, what's up? Alright, you're a stateside, but you were raised in the UK, played professional soccer there. And it's love talking to you about your injuries and how you recovered from them. We have whole shows on that. Yeah, there's a lot. But you come from the professional world, and there's some insight there that you could bring to this conversation.

• 1:37Neil deGrasse Tyson?

  Because what we have found is that there's a superstition can manifest itself in sports. And superstition tends to show up when people are not entirely in control of the outcome. And so, how much in control are they not? Is this even quantifiable? Should managers study this? Should players study this? And so, generally, when those kind of issues arise, you need a mathematician. And so, we found one. We found the perfect mathematician for this. And who do we have here? Dr. Matthew Ginsburg. Matthew, Matt, I think it is, if I can call you, welcome to StarTalk. Thank you, and yes, it's Matt.

• 2:21Neil deGrasse Tyson?

  It is Matt. Excellent, excellent. So you have a PhD in mathematics? I do. That's dangerous, you see?

• 2:30Neil deGrasse Tyson?

  People don't know how important math is to what they do. And then a mathematician starts walking up from and comes in the back door. And you say, uh oh, they're ready to sort of shake this up. And to tell us where we're misthinking, they're gonna straighten us out. They're gonna ruin our superstitions, they're gonna, and so you ruin people's days with your

• 2:50Speaker 02

  What I found is that, is that when you have two people who are having an argument. And you come in and you just completely settle it with mathematics, you just say, right, wrong. They always both love you. I mean, it's just, it's totally the way to make friends and.

• 3:04Neil deGrasse Tyson?

  Okay.

• 3:05Chuck Nice?

  Yeah, okay. I actually, I, I think you're wrong there, Matt.

• 3:09Neil deGrasse Tyson?

  Yeah, I think he's lying.

• 3:10Chuck Nice?

  Yeah. I think what happens is they both kind of go, that guy's a dick.

• 3:19Chuck Nice?

  They're both mad at you because they both look like idiots, uh, as everybody does, uh, next to mathematicians.

• 3:27Speaker 02

  Well, they really, they just want to have the argument. They actually don't really care about being right or they just care that they're disagreeing.

• 3:33Neil deGrasse Tyson?

  No, no, the difference is, it comes, it here's how it manifests. If you settle it with a solution that neither of them had previously embraced, then they're both wrong. And then, then, then that, that magnifies your dickitude.

• 3:51Speaker 02

  Well, so we should actually, we should get my wife in here, because she will tell you that she will be delighted at anything that you guys can do to minimize my dickitude.

• 4:03Neil deGrasse Tyson?

  Okay.

• 4:03Gary O'Reilly?

  What's surprising about this conversation is it took so long to get here.

• 4:07Chuck Nice?

  We're already, we're, no, but guess what? We're already making plans to bring him back.

• 4:18Gary O'Reilly?

  And who, who knew the word dickitude actually existed?

• 4:22Neil deGrasse Tyson?

  So, so let me ask, Ed, Ed, and by the way, this is, we have a third segment, uh, where we just sort of chew the fat and shoot the shit. Can you stay for that segment? Because there are places I want to get into your professional profile that would not be put, that would not be part of, sort of what we know we must get through. Because we want to talk about, um, what kind of statistics? Do you, where, where, where, where did you get your PhD? Where, where were?

• 4:46Speaker 02

  I got my PhD in astrophysics.

• 4:48Neil deGrasse Tyson?

  Oh.

• 4:49Speaker 02

  And it's mathematical astrophysics from Roger Penrose at Oxford.

• 4:52Neil deGrasse Tyson?

  Oh, oh, okay. Let me tell my co-authors. He just totally name dropped there.

• 4:57Chuck Nice?

  Yeah.

• 4:57Neil deGrasse Tyson?

  To, to, to, total named, Roger Penrose, who hardly anyone heard of before a month ago, when he got the Nobel Prize.

• 5:06Chuck Nice?

  Right.

• 5:07Neil deGrasse Tyson?

  That was like total, total name drop. Okay.

• 5:10Chuck Nice?

  That's a, that's a double name drop because you got the Oxford on the back of it.

• 5:14Neil deGrasse Tyson?

  You got the Oxford, you got Penrose, who's famous among all astrophysicists, and the, and the, the throwdown of the, of the Nobel Prize. But so anyhow, so then you, then you started, decided to slum it and do pure math.

• 5:28Speaker 02

  Before I went to Oxford, I was at Caltech for a year, where my supervisor was Kit Thorne, who also went on to win the Nobel Prize. And I actually think that I get credit. This is me. I'm the common link between these two scientists. For the reason they've won the Nobel Prize is because they got.

• 5:44Neil deGrasse Tyson?

  You know, it's interesting because Tom Cruise, who probably will never win an Academy Award for acting, has been in, in movies where, you know, five other Academy Awards have been given to the movie, to the other actors, to the thing. So he could say that he enabled the acting of, yeah.

• 6:03Speaker 02

  There you go.

• 6:04Neil deGrasse Tyson?

  There it is. Okay.

• 6:05Chuck Nice?

  Yeah.

• 6:05Speaker 02

  This is probably a dickatude.

• 6:08Chuck Nice?

  That's true.

• 6:09Gary O'Reilly?

  Yeah, I was gonna say, I'm, I'm, I'm kinda siding with your wife here.

• 6:13Neil deGrasse Tyson?

  So, so, so what, what is the, what is the knowledge you bring to assist sports people? What have you studied in your math?

• 6:22Speaker 02

  So the math really was twister theory and, and quantum mechanics and stuff like that. But since then, I spent a lot of time doing AI. And I made, I think, most of my career doing artificial intelligence and statistics and machine learning. And that's what I brought. Uh, is a knowledge of statistics and what you can predict and what you can't, and how that kind of information can help people make better decisions as they play their games.

• 6:50Chuck Nice?

  When we talk about predictive analytics, are we really just talking about a different forms of statistics? And the use of statistics?

• 6:58Speaker 02

  The, the, we're often talking about machine learning. And machine learning is really just sort of statistics on steroids.

• 7:05Chuck Nice?

  Right, yeah.

• 7:06Speaker 02

  And.

• 7:07Neil deGrasse Tyson?

  Oh wait, are steroids allowed in computing?

• 7:10Chuck Nice?

  I'm sorry, I'm gonna have to invalidate this program.

• 7:19Neil deGrasse Tyson?

  It's on steroids.

• 7:20Speaker 02

  It's a power surge. I participated a long time ago in the World Computer Bridge Championship. I wrote a computer program that played bridge. And I was at the World Computer Bridge Championship and they actually drug tested the programs.

• 7:36Neil deGrasse Tyson?

  Took a sample of blood.

• 7:37Speaker 02

  I have no idea what this means as far as steroids and so forth, but there are people worrying about this issue.

• 7:45Neil deGrasse Tyson?

  So, let me ask, if you said there's some things that you can't predict is because there's insufficient data to make a reliable prediction? Or would you, are you, did you mean to imply that there are some things that can never be predicted, no matter what?

• 8:00Speaker 02

  So, you can't, at some level, you can't actually predict anything with certainty. Right? So, we all think the sun's gonna come up tomorrow, but there are a variety of things that could cause it not to.

• 8:11Neil deGrasse Tyson?

  No, no, don't go there. No.

• 8:16Neil deGrasse Tyson?

  You say that like, yeah, there's a 50% chance the sun is not gonna rise. If I'm a betting person, we're good. So, let's, let's not worry about the philosophical limits of what could or could not happen. Let's just talk about what a certain betting person would bet on.

• 8:32Speaker 02

  So, what I'm trying to say is, all you can ever do about the outside world is quote odds. Now, if you can make that, if somebody's willing to bet me that the sun is not gonna come tomorrow, it's gonna be even odd, I'll make that bet, because the sun's coming up tomorrow. You know, 99.999 and a lot of nines. Similarly, if I want to predict that, you know, Babe Ruth pointing to a point in the stands, I'm gonna hit a homerun and it's gonna go there. It's not 100%. There's some chance that he gets to honor that prediction. And the question is, how accurately can you gauge the probabilities? And how close can you get them to 1 or 0?

• 9:10Neil deGrasse Tyson?

  Correct. And so, a 0 is certainty it won't happen, and a 1 is certainty it will happen.

• 9:15Speaker 02

  Right.

• 9:16Neil deGrasse Tyson?

  Okay, and so, of course, sports, there's a lot of betting in sports. And if you could put a shading of insight into an outcome, you could become a very wealthy man.

• 9:28Speaker 02

  Yeah, but I wouldn't have any fun.

• 9:31Neil deGrasse Tyson?

  Okay.

• 9:33Speaker 02

  Okay.

• 9:34Neil deGrasse Tyson?

  Yeah.

• 9:34Speaker 02

  Uh, I, let me just, uh, put a quick addendum to that, Matt. Um, you would, with all the money that you would get. So yes, you're right. You would not have any fun in the process. However, the results.

• 9:50Neil deGrasse Tyson?

  You have fun after.

• 9:51Speaker 02

  Afterwards, afterwards.

• 9:53Neil deGrasse Tyson?

  Alright, so what, what about curses where people have long losing streaks and they think they're cursed? And this is where superstition comes in. And it seems to me mathematicians are highly needed in those moments.

• 10:03Speaker 02

  So all we can, we can tell you that, you know, you're probably not cursed.

• 10:09Neil deGrasse Tyson?

  Okay. So there's a chance you're actually cursed. That's what you're saying.

• 10:13Speaker 02

  There's a chance of anything, right? Now, it's, imagine I give you a coin, right? And you start tossing it and it comes up heads, heads, heads, heads, heads. At some point, you will conclude that the coin is biased. The coin's not fair. And how long it takes you to admit that the coin is unfair is really a function of how confident you were initially that the coin was fair. The more confident you are the coin is fair, the longer it takes you to believe you're actually dealing with an unfair coin. Curses are the same, right? So a, a person, I think should, but we have no, there's no known mechanism by which you can be cursed. So my belief that I am cursed is, it's incredibly unlikely. But eventually the evidence would, could overwhelm it.

• 10:55Speaker 02

  Now, you know, the Red Sox not winning the World Series.

• 10:59Neil deGrasse Tyson?

  For a thousand years, they didn't win the World Series.

• 11:02Speaker 02

  Yeah, but it's just because they stung, right? It's not because they were cursed.

• 11:07Gary O'Reilly?

  Well, they sold the bandito and then they sold a lot of other players to the New York Yankees. And surprising enough, the Yankees went ahead and won a load of, won a load of World Series.

• 11:15Neil deGrasse Tyson?

  And the Red Sox had been winning.

• 11:16Speaker 02

  Yeah, because they've been good.

• 11:18Gary O'Reilly?

  Yeah, exactly.

• 11:19Neil deGrasse Tyson?

  They were quite dominant in fact.

• 11:20Speaker 02

  So I think that, now, so a curse is such an extraordinarily unlikely event. But what you asked me at the beginning is the probability is never zero or one. The probability I'm cursed is, you know, microscopic.

• 11:33Speaker 02

  But eventually, I might eventually be convinced that I that I was cursed. I don't think, you know, for a baseball team to be cursed, I believe you would need more than a lifetime's worth of evidence. The Red Sox didn't even come close.

• 11:44Gary O'Reilly?

  Right. Do you not get a herd mentality where all of a sudden that so many people buy into it that they cannot remove that thought from their mind and therefore it kind of self prophesizes?

• 11:57Speaker 02

  I don't think so. So I've actually, I've looked at.

• 12:00Neil deGrasse Tyson?

  Wait, just wait, Gary, you're talking about a case where that's how voodoo voodoo might work, right? Where you're so convinced you're going to fail that throws off your name and then you fail and then you credit the voodoo, blame the voodoo for that.

• 12:13Gary O'Reilly?

  Because you have to find, you have to find a fool guy. Therefore, it's the curse.

• 12:18Neil deGrasse Tyson?

  So that would mean performing at very high level athletics, you know, that 90% of the game is half mental. That's what you're saying there.

• 12:27Speaker 02

  Absolutely.

• 12:28Gary O'Reilly?

  A lot of it is.

• 12:28Speaker 02

  That's what I tried to look at. So I played tennis in high school. I was awful. And.

• 12:34Neil deGrasse Tyson?

  So you took up astrophysics. I'm glad. Okay.

• 12:37Speaker 02

  Yeah, I know. And I think part of the reason I became convinced that I was terrible and that made me worse. But I think when you're talking about professional athletes, if they do that to themselves, they're not professional athletes. They just can't, they're competing against people who don't.

• 12:50Neil deGrasse Tyson?

  If they're susceptible. Good.

• 12:52Speaker 02

  One of the things I did when I was working with the Oregon Ducks volleyball team is I had a bunch of statistics and just out of curiosity.

• 12:59Neil deGrasse Tyson?

  You live, you live in Oregon. You're in Eugene, Oregon.

• 13:02Speaker 02

  I do. I live in Eugene, Oregon. I've worked with the Ducks a bunch. I was working with the volleyball team and they gave me statistics on on every play. And I said, okay, let's look at individual players who play poorly for the first half of a match. Dude, is there any correlation between they're playing poorly the first half of a match and they're playing poorly the second half of a match? In other words, have they gotten in their own heads and decided they're having a bad night? And the answer was no. There was no such correlation. The kids are.

• 13:34Speaker 02

  As near to machines as the coach can make them.

• 13:36Neil deGrasse Tyson?

  Wow.

• 13:37Speaker 02

  They play badly on one point, they shake it off, they play well the next.

• 13:41Neil deGrasse Tyson?

  And let me just add, and just to, to, just to, to, to blow some smoke in your direction. The, you have to know that that was the right question to ask. Right? That's a brilliant question and a simple question that I bet most people don't think of. Because what you're saying is if you, if you're starting to have a bad game. And then it, does it affect you mentally? Cause you already know what they are physically. You know what they're capable of. And you, you ask the right question and not enough people in the world think about the value of the right question asked at the right time.

• 14:12Speaker 02

  So, and thank you. I think that one of the things that I have learned, so a lot of what I've done has involved large amounts of data. And what you do is you want to take the data that you get from whatever source. And you're looking for patterns and the patterns, you're looking for surprises. Because when you find a pattern, it's a surprise. Might be a curse, might be lack of curse. But you're looking, you learn to look for patterns in data. That's what machine learning is about. That's what statistics is about, is what data science is about. And when I got all this volleyball data, I just started doing everything I could think of. I asked a bunch of questions that were, that were less interesting. But you know, this one, thank you for saying it was a good question. But it's something that the data was able to advise me on.

• 14:57Speaker 02

  And you know, so I've done, I did the same thing with basketball. So I, I got every basketball play for a year. And I started looking to see, is there anything that predicts whether a player is going to perform well or poorly in any particular game? And the answer turned out to be yes. And it was basically the number of minutes he had played previously. And basketball has a very long memory. It turns out that, that playing a lot early in the season, you carry that burden with you for the whole rest of the season.

• 15:27Neil deGrasse Tyson?

  But is it, does it help you or hurt you if you played a lot?

• 15:30Speaker 02

  It hurts, it hurts.

• 15:30Chuck Nice?

  It hurts you, yeah.

• 15:31Speaker 02

  It hurts.

• 15:32Chuck Nice?

  And it, yeah, it's, it's season fatigue, yeah. As a matter of fact, last year, before the whole, you know, COVID, so not this past season that they played, but the season before, there was a big argument about certain players.

• 15:47Neil deGrasse Tyson?

  Wait, wait, Chuck, if you want to go before, it's just B C, before COVID, that's all.

• 15:51Chuck Nice?

  Oh, yeah, B C.

• 15:52Gary O'Reilly?

  There you go.

• 15:54Chuck Nice?

  But there was a big controversy about, um, allowing players to kind of take a break during the season, sit out games that weren't as crucial, to allow their bodies to, uh, refresh and re-energize in some way. And, uh, it just became a huge, huge thing, and the idea is...

• 16:15Neil deGrasse Tyson?

  Damn it, I'm paying eighty dollars for a ticket, I want to see Shaq play.

• 16:18Chuck Nice?

  That's it, and that's basically where the controversy is.

• 16:22Gary O'Reilly?

  There you go.

• 16:22Chuck Nice?

  And the other controversy was...

• 16:23Neil deGrasse Tyson?

  Because I'm paying his salary.

• 16:25Chuck Nice?

  Right, the other controversy is, hey, we never did it like this before. You know, the guys at the ba, the guys before, who came before us are tougher. They're, those guys grounded out for the whole season. What makes you so soft that you gotta take a break? But it's really based...

• 16:41Gary O'Reilly?

  Chuck, do you want me to go through my injury list? Because this, this is another hour. Now, the guys in my era did exactly that. And we have injuries that last for days if we start at one end and go to the other. We didn't have guys like Matt, who would sit down, and now you find in elite sport, we, we call asset management. I gotta pull you out for two games so as I can have you for the next two months. Because if I play you in those next two games, you're out for those two months because you're burnt, your muscles aren't in a good condition, and so there's a difference.

• 17:10Chuck Nice?

  There's a higher probability that you're going to receive an injury.

• 17:13Speaker 02

  One of the things that I found, and it was interesting, so it's not just, you know, sit Steph Curry. It's, at what point, so, you know, there's three minutes left in the game, you're up six. Is that enough that you should sit him down? And give him six more minutes of rest today, so that he's played better tomorrow or the next day? And the interesting thing is, if you have all the numbers, this becomes a purely quantitative question. You know, if I sit him down for the rest of this game, my chances of winning this game go down a tiny bit. I've probably won it because we're up six with three minutes left. But my chances of winning... The day after tomorrow go up and the game after that they go up.

• 17:54Speaker 02

  So you end up with this incredibly quantitative question and I actually crunched it all.

• 17:59Neil deGrasse Tyson?

  So, okay, so let's come back to that. We got to take a break now, but when we come back, we're going to talk about number crunching and exactly as you're describing, Matt, and I'm going to ask you the question, if it's all just a matter of numbers, who needs coaches? When StarTalk Sports Edition continues.

• 18:40Neil deGrasse Tyson?

  We're back. StarTalk Sports Edition. We're doing this by the numbers. What are the odds? What does that even mean? And we got a mathematician, Matt. Matt, love having you here. Just because I think everyone should have their own personal mathematician in our speech. You just reach for them when you need one. And that's just, I love, love having you.

• 19:05Speaker 02

  The guys in the bar who are having a fight, they don't want their own person.

• 19:08Neil deGrasse Tyson?

  They don't want their own mathematician. I want our own mathematician, Matt Ginsberg. So we left off with you describing the decision to sit a high value player if you're leading because you don't need them to win the game and that could help you win tomorrow's game or the next game. And see, these are decisions not, according to you, not left to the judgment of the coach, but these are with fast computing and AI thinking about it, you can make these decisions in an instant. So presumably that's not just for basketball, for other sports as well?

• 19:44Speaker 02

  So, um, yes, you can, I mean, you can help all over. You help in different ways. You know, so I worked with the Ducks football team on whether they should punt or go for it on fourth down. I worked with the volleyball team on when they should call timeouts. I also did some, you know, so I worked with the volleyball team. This was not so successful. We set up a system where there were two high-definition cameras and they would watch the volleyball. And the, the girls on the team had, had uh, smartwatches on their arms under a shooting sleeve. And if the serve was going to be out, we would make the smartwatches buzz and we could tell before the serve got there. That was not successful. Um, the N C double found out about it. They told us we were bad people and made us stop.

• 20:27Chuck Nice?

  But is it, is it illegal?

• 20:29Speaker 02

  They actually said it was illegal.

• 20:31Neil deGrasse Tyson?

  Well, they didn't know it should be illegal until they saw that you were doing it, right? Isn't it?

• 20:36Speaker 02

  Well, they said it was illegal and we said, why? It doesn't break any of the rules. And they said, we don't actually know which rule it breaks, but we are telling you that it does break the rules and you have to stop.

• 20:46Neil deGrasse Tyson?

  Yeah. So what they should have said is not that it breaks rules, but that it's cheating. And so, so uh, did you, did it calculate based on a ballistic trajectory and not an aerodynamic trajectory?

• 20:57Speaker 02

  So, um.

• 20:58Neil deGrasse Tyson?

  So you would get it wrong if the ball has a spin on it?

• 21:01Speaker 02

  One of the things I did obviously is look to see whether the ballistic trajectory got the right.

• 21:08Neil deGrasse Tyson?

  Obviously.

• 21:10Speaker 02

  Of course. Well, you have to, you've got to test what you're doing. You can't just make stuff up and then expect it to work. So, and the answer was, I was able to accurately predict whether a volleyball serve was going to be in or out. So that was, that was just, it worked. But, but cheating, they can't just say you're cheating, right?

• 21:27Chuck Nice?

  Yeah, I was gonna say, how does that change, how would that change the game? Is it?

• 21:31Neil deGrasse Tyson?

  No, you decide whether you're going to return it or not. Serves can be deadly. And if they're out, you'd rather not have to try to return it. This is very simple.

• 21:38Chuck Nice?

  Yeah, but you would have, oh, I see what you're saying. So it happened in that, in that such short period of time that if you're wearing the watch and it buzzes, just do nothing.

• 21:48Neil deGrasse Tyson?

  That's brilliant.

• 21:49Speaker 02

  I would be buzzing, I would be buzzing their watches pretty much as the ball crossed over the net.

• 21:54Chuck Nice?

  Okay. Cause that, that, that's what I was trying to figure out is how, how, how much in real time and how, what, so your reaction time is part of this too?

• 22:04Speaker 02

  Well, I didn't do anything. Like, the computer was, it was all a computer.

• 22:08Neil deGrasse Tyson?

  Chuck, he programs AI. He doesn't, he doesn't have to do a damn thing.

• 22:12Chuck Nice?

  He's not even here right now.

• 22:16Neil deGrasse Tyson?

  It's his avatar, you know.

• 22:17Chuck Nice?

  There you go. I got.

• 22:19Neil deGrasse Tyson?

  Wait, wait. So, so what is the future of coaches if you can make key decisions such as that by AI? What do you need a coach for?

• 22:27Speaker 02

  So, I think this is not just about coaches, right? So, we have AI entities making more and more decisions for us. And I think the thing that you, that you have to realize is we solve problems totally differently than machines do. So, you know, when a person plays chess, they look at a handful of chess positions. When Deep Blue plays chess, they look at, it looks at billions. When we solve problems by pattern recognition, they solve problems by searching. The net result is that we are good at one kind of thing and computers are good at a different kind of thing. So, the question about balancing somebody's energy, how many minutes should they sit out this game and next game?

• 23:09Speaker 02

  Machines are good at that. We're lousy. Machines should do that. Questions about motivating the players to practice harder, to not get drunk before games. Whatever it is that coaches are doing that is very much a personal interaction, adding value, adding experience, adding, you know, pattern recognition kinds of things, we're going to keep doing that. That's what.

• 23:34Neil deGrasse Tyson?

  No, no, no. Wait, wait, wait, wait. No, you, no, because what happens is I, I was out all night and I was drinking and I come in and AI tests my blood. And it says, "Your alcohol is 2% blood." I got that joke from a movie some years ago.

• 23:49Speaker 02

  I know, I know a couple of those players.

• 23:51Neil deGrasse Tyson?

  And so then AI says, "My data shows that your performance will be diminished by this amount." And so they will know exactly how much your performance would be diminished.

• 24:02Speaker 02

  But that's not the problem.

• 24:03Neil deGrasse Tyson?

  That's not, I don't need a coach for that, when, when you can know the chemistry of that phenomenon.

• 24:08Speaker 02

  You don't need a coach to tell you that your drunk player shouldn't be playing. You need a coach to convince the player not to get drunk the night before a game.

• 24:19Chuck Nice?

  Uh, but didn't Joe Hamitz get drunk the night before the Super Bowl and still win the Super Bowl? I mean.

• 24:25Neil deGrasse Tyson?

  Did he? How do you know that? Did, what, did you tan on his?

• 24:31Chuck Nice?

  I was wearing the pantyhose.

• 24:33Neil deGrasse Tyson?

  So let me ask, for those who are not 100 years old, he did a TV commercial advertising pantyhose. After, I think he shaved his legs, did he? I don't know. Anyhow. Anyway, let's move on, Matt. So, so, so Matt, baseball is famous for how much statistics plays in the decisions of coaches. On the level where they shift an entire infield of players to one side because of the statistics of how the batter hits the ball. Do other sports lend themselves to this level of analysis?

• 25:05Speaker 02

  Yes.

• 25:06Neil deGrasse Tyson?

  Yeah.

• 25:06Speaker 02

  Short answer. Basketball is right on baseball seals. So I know a bunch of people involved in the basketball world, and they are incredibly committed to exploiting statistical information the same way the baseball guys do. The other sports are behind. So I've been looking at football and talking to football people, and they know that they're not taking advantage of data as much as some of these other guys are.

• 25:32Neil deGrasse Tyson?

  And as you began just a moment ago, the biggest decision play is do you kick or do you go for fourth down? I mean, fourth and short, do you kick or do you go for it? And that's, you know, everyone, that's, everyone debates that the day after, all right? If it didn't go the way people wanted, how does, how does data help that?

• 25:52Speaker 02

  That is, you just do it. You just figure it out. And I did work for the Oregon Ducks. And I actually made a deal with them that I would figure out what they should do on fourth down and I would get four season tickets. I worked.

• 26:05Neil deGrasse Tyson?

  Good deal.

• 26:06Speaker 02

  And I told them, every week I would go to them with this giant book of what to do in every possible fourth down situation. And I would give it to the coach and I said the same thing. I said, look, here's the deal. Just stop punting between the 35 yard lines. You'll be fine. And the Oregon Ducks stopped punting between the 35 yard lines and they, they had an amazing year. In part because not punting between 35 yard lines in college football is just right. I did then go to him the next year and ask him if he wanted to do it again and he said no. And I said, what? And he said, I know not to punt between the 35 yard lines. I'm going to keep my tickets. And he's and he sent me on my way. So they are starting to make the decision this way,

• 26:49Speaker 02

  but not terribly effectively yet. I mean, you can do so much more than fourth and however, fourth and whatever.

• 26:56Neil deGrasse Tyson?

  So what so what you're saying is your your your your advice to him was consistent with his life experience and therefore it had no value to him?

• 27:03Speaker 02

  No, no, no. He he, when I started working with him, he never punted. He always punted between 35 yard lines. Everybody punted. So the first time he followed my advice, he was playing Utah, was fourth and five from midfield, and he decided to go for it. Because I had been telling him to do this forever. Utah was so surprised they had to waste a timeout. Because they had put their punt return team on the field and he put his normal offense on. So they had to blow a timeout and then he got it. And he thought, well, that's pretty cool. And he did it again. And he learned, he just started doing better. And if you watch college football now, you will see that between the 35 yard lines, they go for it a lot. And this is starting to trickle into the NFL also.

• 27:48Chuck Nice?

  And and and what is the fourth between the 35 yard lines? Is there a qualifier? Because fourth and 15 on a penalty between the 35 yard line is a lot different than fourth and two between the 35 yard line.

• 28:02Speaker 02

  The actual answer is there is essentially no qualifier. I don't I didn't run it out to fourth and 47, but but 15, I think 15 may have been around the breakpoint, but you really just go for it. And the reason is

• 28:17Neil deGrasse Tyson?

  Because some percentage of plays gets you 15 yards, right?

• 28:20Speaker 02

  Sometimes you make it, but mostly punting does not help you. Because college punters aren't that good. They're going to punt it in the end zone. So instead of having it at midfield, they have it at their own 20. And it's not really that much better.

• 28:33Chuck Nice?

  It's not that much. And also too, um. College returns are a lot, advance a lot further because in the pros, if you look at the pros, when they punt, those dudes are right there and most times that player, that player is going down. Occasionally, you'll see a breakaway, you might see somebody get 20 or 30 yards on a return, which is far more routine in college than it is in the pros.

• 29:02Gary O'Reilly?

  That's why they're called special teams, Chuck.

• 29:04Speaker 02

  Now, the other thing I told him is you should always go for it on fourth and one. On your own nine, go for it on fourth and one. And the numbers just say it's better because every now and then you're going to get it and then you get a new life. Punting from your own nine, you're screwed. You were screwed on your nine, you're still screwed because the other team is going to have the ball on your own, you know, on your 40 and you're still dead.

• 29:25Chuck Nice?

  One yard line, yeah.

• 29:26Speaker 02

  And the coach actually told me, he said, stop telling me about this. I can't go for it on fourth and one from my own nine because if I'm wrong, they're going to fire me. I don't care if it's right. Stop talking to me about it. I'm just not interested. So I stopped talking about it. But so, so coaches are acting, coaches have a lot more to balance than simple quantitative decisions, right? They have to balance the press and the fans and people's moods and stuff that I don't know anything about because I'm just a numbers guy.

• 29:58Gary O'Reilly?

  So you're telling me the facts don't care, right? So when the coach, yeah, the, the coach is just riddled with emotions and he's going to get fired if dot, dot, dot. What happens when you slide the dossier across the desk and say, this is factual? How much pushback? And, and is it never going to happen? Or do you get like the embrace the coach eventually gives you? Or is it always an up?

• 30:22Speaker 02

  It varies enormously, right? It's a, it's a personal thing. I mean, so I've worked with people who have a huge not invented here syndrome. You can tell them any idea and they will tell you, yeah, I already thought of that. Doesn't matter if they have or not.

• 30:35Neil deGrasse Tyson?

  Yeah, yeah.

• 30:36Speaker 02

  You can, dealing with football coaches, a football coach may say, if I go for it on my own nine and fourth and one and I'm wrong, I get fired and he's right.

• 30:44Neil deGrasse Tyson?

  Yeah.

• 30:45Speaker 02

  Because it's his job to know what gets him fired. Then you can't, you know, he said, stop trying to talk to me about this.

• 30:51Neil deGrasse Tyson?

  Yeah, but in baseball, if you make a statistical decision, you're not going to get fired because everyone knows the power of those statistics and then in the long run, you're gonna win and and you have one hundred and sixty two fricking games. And because it's a marathon, not a sprint. Now, maybe football, each game has, is a little more critical. Let me, how, what about the hail Mary pass? Is that, is that a statistical thing?

• 31:14Speaker 02

  I don't know. I, I actually um just looked at this and I can tell you that it looks like you, it works about two percent of the time. But it's riskless. Right? Because

• 31:24Neil deGrasse Tyson?

  Yeah.

• 31:25Speaker 02

  you are, you have the ball at midfield, there's six seconds left in the game, you're down by four. If you don't throw a hail Mary pass, you are guaranteed to lose. If you do throw a hail Mary pass, you have a two percent chance of winning. I'll take two percent over zero percent any day. So it's not, it's not the kind of decision, what people get upset with is you go for it on fourth and one and statistically it's right, but it was wrong spectacularly today.

• 31:50Neil deGrasse Tyson?

  Okay, okay. So the, the, the alternative to hail Mary pass is a quarterback run with twelve consecutive laterals. That's, that's the alternative to that. And have you thought much about that? That's, that's a lot of ball handling, which always carries a risk.

• 32:07Speaker 02

  I, no, so you have to understand, I can't think about that. Because I don't think about football, I think about numbers. And there are no, there is no data on people trying this multiple lateral play. So

• 32:20Neil deGrasse Tyson?

  Yeah, there would be, you could say, what fraction of laterals are fumbled? Right? Because it's another ball handle, right? And, and so there's got to be some access into that play.

• 32:30Speaker 02

  Problem is that every lateral has to be backwards.

• 32:33Neil deGrasse Tyson?

  Yeah.

• 32:34Speaker 02

  So. Eventually you may run out of field, but the real problem is you're not moving the ball forward as you're laterling. Occasionally you do see somebody, you know, there's a kickoff return at the end of a game and people start laterling around. It never works. I've never seen it work. I have seen Hail Marys work.

• 32:52Chuck Nice?

  Yeah, and then there's also the trick play, like, which is a variation of a lateral, where, and it normally only happens on kickoffs, where the returner will receive the ball, and then, because you can forward pass as long as the ball is not going forward, so he throws the ball across the field to another player, which looks like a forward pass, but because it's going in back, it's going backwards, it's considered a lateral, and then that player is free from obstruction.

• 33:31Neil deGrasse Tyson?

  He's wide open.

• 33:32Chuck Nice?

  He's wide open, and he's got a big, long field of, and if he's fast enough, he can actually avoid being tackled, so, yeah.

• 33:40Neil deGrasse Tyson?

  We gotta take a quick break. When we come back, Matt, I want to get into sort of what made you who you are. If I can spend a couple of minutes doing that, and still connected to the theme.

• 33:52Chuck Nice?

  What mad scientist puts you together, Matt?

• 33:57Neil deGrasse Tyson?

  In what basement were you invented? All right, we'll take a quick break. This is StarTalk Sports Edition by The Numbers when we return.

• 34:28Neil deGrasse Tyson?

  We're back. StarTalk.

• 34:31Neil deGrasse Tyson?

  Sports edition. What are the odds? And we've got mathematician Matthew Ginnenberg. So Matt, you briefly mentioned that, and you just said off the cuff, oh, Hail Mary passes work 2% of the time. And, you know, I don't, I don't have to run numbers to know that it doesn't happen often. But when you say 2%, you probably mean exactly 2%. So how did you, how do you actually get that number?

• 34:58Speaker 02

  So for that number, which your team actually asked me about, I looked at all the football data I have. So I have every NFL play since 1999. And the question is, which are the Hail Marys? So I said, okay, you got to be down more than a field goal, but a touchdown can tie it. So you got to be down four to eight points. You have to be at least 30 yards away from the end zone. So you have to have at least 30 yards to go. It has to be the end of the game, which I defined as either less than 20 seconds left to play, or less than a minute left to play, and it's fourth down. So you're desperate. And then I looked at all the plays that were like that, and how many of them were actually

• 35:37Speaker 02

  recorded as being a deep pass, which is part of the data I have. There were 187 plays in desperate situations like that, that were recorded as deep passes. And of those 187 plays, four were touchdowns. So I can then tell you

• 35:53Neil deGrasse Tyson?

  That's your 2%?

• 35:55Speaker 02

  2.1% of Hail Marys work.

• 35:58Neil deGrasse Tyson?

  Wow. Wow. Yeah. But as you say, 2.1% over nothing. I have all this data. I just did a bunch of queries. Yeah, it's 2% over, over 0%, right? I mean, if you don't do it, you, you know, you're not. That's, okay. So in this third segment, which we've, we're still trying to find a good name for it. But until we do, we're just calling it shoot the shit. So, so what, I got a question for you, Matt. Um, if I remember correctly, was it Deep Blue? Yes. Or whichever IBM computer beat the world's best Go champion. That was a Google computer called- Google, sorry, Google. That's right, Google. What was the name of that computer?

• 36:41Neil deGrasse Tyson?

  I think it was AlphaGo is I think what they called it. Yeah, okay, AlphaGo. And I remember chatting with some Google people and apparently you can do one of two things if you have machine learning, deep machine learning AI, you can say, alright, let's study every single game ever played, which is you can do with chess because every important game is recorded, right? And have it learn moves that worked and didn't work, and it could have the sum of all human knowledge and thereby beat practically any human who plays it. That makes sense. But then, in the follow-on Google program, it didn't do that. It said, what is the goal of the game? Oh, it's to demarcate territories and to prevent, is that the goal?

• 37:25Neil deGrasse Tyson?

  Well, let me play myself and do what I think I need to do to win. And let me play a billion games against myself. Doing that, that program beat the previous program that had beaten all previous Go players. And then it exploded.

• 37:47Neil deGrasse Tyson?

  And then a tear in the space-time continuum opened up. So my question is, man, at what point are you gonna say, my best data are all of the games ever played, rather than my best data are the games that could be played that I can think up and have never been played and thereby I'm gonna make a giant leap for the sport? Like the first person to bunt, that must have been a crazy, like, what is that? Oh, something had to invent that, right? I remember, uh, it was Fosbury, it was a Fosbury- Yeah, Fosbury Flop. Yeah. 1968 Olympics, Mexico City. He does something brand new. So just to be clear, because I've noticed that people know that that's a better way to jump over the bar,

• 38:31Neil deGrasse Tyson?

  but they don't always know why, but give me like 30 seconds to explain that. So if you watch old high jumpers, um, they would go forward over the bar and you can only really bend at your waist. Your legs can't bend-

• 38:49Neil deGrasse Tyson?

  In the opposite direction than they do. So your legs have to clear the bar straight. Whereas if you go backwards over the bar, your back can curl, you can curl backwards at your waist, and your legs can dangle. So you can make a a a hemicycle, a semicircle, and curl yourself around the bar, taking your center of mass below the bar, even though your body goes above the bar. So you can jump higher than ever before by actually jumping lower than ever before in a world record um setting jump. So, because when you're curling, your center of mass is no longer in your body. It's outside of your body, and you didn't actually have to jump as high. So you could say that was cheating, but they they left it in. And now everybody jumps that way.

• 39:34Neil deGrasse Tyson?

  So I just had to slip that in, because I I've noticed that not everyone knows that, even some athletes. So continue, Matt. Sorry, I interrupted.

• 39:41Speaker 02

  So what I do, what people working machine learning generally do is they, and I said this before, you look for patterns in data. The more data you have, the more likely it is that the patterns you detect are real, the more likely, the easier it becomes to find the pattern. So you want as much data as you possibly can have. And there obviously is a is a choice. You either can use naturally occurring data, data from chess games, or you can use synthetic data you generated by playing yourself, for example. And there's a trade off. The naturally occurring data is, at some level, gonna be better. It's hard to imagine computer simulations of football games being of much value, for example. But you do have the opportunity to generate more data

• 40:26Speaker 02

  by by playing yourself, by using other computers. At this point, computers are way better at chess than we are. So the way you, the data you want, you want to look at the data from Stockfish, which is the best non-machine learning based program. From my perspective, you just want to do what works. I don't care where the data comes from, as long as what I learn from it is actually valid.

• 40:47Neil deGrasse Tyson?

  Yeah, but it's more fun if your program invents a new football play that no one thought of.

• 40:53Speaker 02

  Yeah.

• 40:53Neil deGrasse Tyson?

  Because it because it didn't want to base itself on games that were played before.

• 40:59Chuck Nice?

  Wow.

• 41:00Neil deGrasse Tyson?

  I want to see innovation because that's, you know, and I guess that's what trick plays are, but.

• 41:06Chuck Nice?

  Yes, but, but, and, and is that true creativity? Or is, and is that what we're doing as human beings? Looking around and seeing, uh, looking for misdirection, looking for ways to make your opponent, uh, think something that's not happening. Uh, that's how we come up with new plays and that is also a part of pattern recognition. As a matter of fact, in football, they call it disguising the defense and all that kind of stuff.

• 41:34Neil deGrasse Tyson?

  Yeah, and, and, and not only that, the, the very final play in the movie Major League was basically a trick play. And that's baseball, right? What happens is the batter points to the outfield. Okay. And so, so that's, you know, that's, he's showing some gonads there, right? Points like he's going to hit. And then instead he turns around and bunts. And so the third baseman has to come running in because they were playing in deep. There was a whole construct.

• 42:02Speaker 02

  Let me, let me give you, let me actually try and answer this.

• 42:08Chuck Nice?

  Okay.

• 42:09Neil deGrasse Tyson?

  No, we'd rather just argue at you.

• 42:10Speaker 02

  I, I know. I'm going to actually ask you the question back. When I worked for the Ducks, I actually did invent a new play. And I described the play as an optional self-safety. So there are situations in football where you actually want to score a safety on yourself and then take the kickoff from the 20 and so forth and so on. And I created a, another kind of play, which was you go back for a pass, throw a pass. If your pass is basically guaranteed because the guy is just wide open, throw the pass. Otherwise, step out the back of the end zone and do a safety on yourself. New play, nobody had ever thought of before.

• 42:49Speaker 02

  So possibility one is that the Ducks win a crucial game because I gave them this new play. Possibility two is the Ducks win a crucial game because I got them to stop punting between the 35 yard lines. For me, possibility two is just as much fun. That's the question you originally asked. Is just as much fun as possibility one? Because I did it. I know I did it. I don't have to go and pick up a girl in a bar by telling her I invented this, the passing self-safety.

• 43:22Chuck Nice?

  By the way, that wouldn't work.

• 43:24Speaker 02

  Okay, good.

• 43:27Neil deGrasse Tyson?

  Work in the nerd bar.

• 43:28Chuck Nice?

  Hang on Chuck.

• 43:29Neil deGrasse Tyson?

  Works every time.

• 43:30Chuck Nice?

  If you've said that, you've tried it.

• 43:33Neil deGrasse Tyson?

  No, no, it works in the nerd bar. Otherwise, go on.

• 43:36Speaker 02

  I know, when I watch a football game, when I watch a college football game and I see somebody punt not between the 35 yard line, I smile from ear to ear because I did that. It's just as good as if I invented this play that people run from time to time. It's just as much fun. What I did was just as impactful. And whether it was something that that sort of looks really splashy, like pointing to the outfield and then bunting, or whether it's something that's just grinding it out by doing the numbers and figuring out what to do on fourth down. Impact is impact, winning is winning.

• 44:09Neil deGrasse Tyson?

  All right, so then why don't, why don't batters who are statistically predicted to hit 80% of their line drives to the left side of the infield, why don't they just punch one to the right side? And or save that for when they really need it? And was it an ego that they're fighting? Yeah, I'll get through them even though they're putting their best stuff on me.

• 44:29Speaker 02

  I, you have to ask a baseball player. I have played a bit and your natural swing is going to go a particular way and messing with it is at your own peril.

• 44:37Neil deGrasse Tyson?

  I got you.

• 44:38Chuck Nice?

  Right, right. So can I ask you, let's look at football and basketball because they are not as statistically driven as baseball. Is there one thing in each sport, barring the fourth and one situation that, you know, you hear announcers talking about? Is there one thing in each sport that you would say, this is what they're all not doing, that if they did, they would find a greater success?

• 45:12Speaker 02

  So basketball, basketball really is very statistical these days and I don't understand basketball nearly as well as I understand the other games, so I'm going to leave basketball out of it. Football, yes. So there is one incredibly easy thing that people don't do in football and they're crazy. And that is you score a touchdown and you have to decide whether to kick the extra point or go for two. It turns out that your expected number of points scored is pretty much the same. You're about 50/50 to make it if you go for two. So, all you're doing, when you decide to go for two, instead of picking an extra point, is you're adding sort of noise. You're adding uncertainty. And that means, and this is incredibly simple and they should just-

• 45:54Neil deGrasse Tyson?

  But I have to, I have to butt in, because you said something that I don't know if it's completely clear to others. So, when he says your expected results are the same, what he's saying is, if it's a 50% chance you're going to score two points, then half the time you score it, the other half you don't. On average, you scored one extra point.

• 46:13Speaker 02

  Correct.

• 46:13Neil deGrasse Tyson?

  Which is the same as the guaranteed one extra point.

• 46:16Speaker 02

  Right.

• 46:16Neil deGrasse Tyson?

  That was the traditional add-on. So I think I said that correctly, right?

• 46:20Speaker 02

  Yes.

• 46:20Neil deGrasse Tyson?

  Okay.

• 46:21Speaker 02

  Yes. So you can either have a very straightforward one point. You know it's going to be one. It's not going to be zero, it's not going to be two, it's just going to be one. Or you can have like a noisy one point, where it's half the time it's zero and half the time it's two. So the question you should be asking is, do I want noise in the football score? And the answer is, if you're playing a team that's better than you, you do. Because the way you're going to win this game is by getting a little bit lucky. And you want to give the gods of luck as much chance as possible to help you. You want to increase what's called the standard deviation in the score. You can't move the average, but you can make it noisier.

• 47:02Neil deGrasse Tyson?

  And you want to climb out to the wings of that distribution, where you could have actually a chance of winning that game.

• 47:08Speaker 02

  Exactly.

• 47:09Neil deGrasse Tyson?

  As the underdog.

• 47:09Speaker 02

  Yes. So every underdog in football that scores a touchdown should go for two. And it's obvious, and it's simple, and I have no idea why they don't do it. They don't think about the problem this way.

• 47:20Neil deGrasse Tyson?

  Apparently it's not obvious to people who don't have a PhD in mathematics, with the degree that they earned from a Nobel Prize-winning brilliant-

• 47:25Speaker 02

  No, they just need-

• 47:27Neil deGrasse Tyson?

  Well, we got to, we got to, we got to actually land this plane. But to take us out, Matt, just tell me, what was Factor Man? What is that book? You wrote a book in 2018.

• 47:36Speaker 02

  I did. It is, I have spent a lot of my professional career working on a particular technical problem. And if you solve it, you can solve all the other problems, literally. And it's a book about a guy who does. And

• 47:51Neil deGrasse Tyson?

  So it's a novel?

• 47:52Speaker 02

  It's a novel.

• 47:52Neil deGrasse Tyson?

  Oh, cool, cool.

• 47:53Speaker 02

  It's a thriller. It's a thriller.

• 47:55Neil deGrasse Tyson?

  A thriller, a mathematical thriller. Two words you've never seen in the same sentence.

• 48:00Speaker 02

  I've often talked to my friends about, you know, if you solve this problem, it is actually a race between whether you take over the world or the government kills you. And, and and this guy who solves this problem is in this race. He knows he's in this race. He doesn't really want to

• 48:14Neil deGrasse Tyson?

  I'm watching that when it comes out on Netflix because they'll surely buy the story.

• 48:19Speaker 02

  Anyway, that's what, that's what Facturant's about.

• 48:21Neil deGrasse Tyson?

  Oh, excellent, excellent. I'll look for that. And, uh, and greatest name ever for a computer program, Dr. Phil with a F I L L. Tell me about that.

• 48:30Speaker 02

  Dr. Phil is, uh, I don't remember who suggested the name. I actually, it's a program that solves crossword puzzles. And Neil, you and I have both created crossword puzzles.

• 48:41Neil deGrasse Tyson?

  I co-created the crossword puzzles for the New York Times.

• 48:43Speaker 02

  I am, I am awful at crossword puzzles. When I have a puzzle in the New York Times, it takes about a year from the time you submit it till the time it comes out. I can't do my own puzzles when they're finally published. So I wrote this program that's really good at solving crossword puzzles. It's sort of my revenge on all the people who are so, so much better than I am. I needed a name and, uh, I asked the community of crossword puzzle constructors for a name. And one guy suggested Deep Clue.

• 49:09Neil deGrasse Tyson?

  Nice, good one.

• 49:10Speaker 02

  That was good. And somebody else suggested Dr. Phil, which I thought was a tiny bit better. So that's how Dr.

• 49:16Neil deGrasse Tyson?

  Very cool. So, so in other words, never wrong a geek because whatever they're not good at, they'll create a robot that is

• 49:25Neil deGrasse Tyson?

  take over the world.

• 49:28Speaker 02

  Yeah.

• 49:28Neil deGrasse Tyson?

  But man, man, we gotta, we gotta call it quits there. But thank you for being on StarTalk. Sports, I'm delighted to hear how you've contributed to this. And this is surely not the end of that story. There is much more, um, infusion that math will have not only in sports, but the rest of our lives. And I, I think overall, the more, the better. And we look forward to this. So thanks for being on StarTalk. Chuck, Gary. Always a pleasure. Thank you. Always a pleasure. We're here. I'm Neil deGrasse Tyson, your personal astrophysicist, as always, bidding you to keep looking up.