Learning Baseball Through Statistics | Stats + Stories Episode 357

Alexandre Andorra is a Senior Applied Scientist for the Miami Marlins as well a Bayesian modeler at the PyMC Labs consultancy firm that he cofounded as well as the host the podcast dedicated to Bayesian inference “Learning Bayesian Statistics” His areas of expertise include Hierarchical Models, Gaussian Processes and Causal Inference.

Episode Description

Sports analytics is a booming industry with new technologies allowing for the parsing of ever more sophisticated statistics. Analysts can now examine the height and the force of a gymnast tumbling pass, the probability of going for it on a 4th down in football, actually working out, and the arc of the best swing for a baseball player. Analytics are also used in the conditioning of athletes, particularly for all the baseball players preparing for the start of the MLB's spring training. Analytics is the focus of this episode of stats and stories with guest Alexandre Andorra.

+Full Transcript

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Rosemary Pennington
Sports Analytics is a booming industry with new technologies allowing for the parsing of ever more sophisticated statistics, analysts can now examine the height and the force of a gymnast tumbling pass, the probability of going for it on a fourth down in football, actually working out, and the arc of the best swing for a baseball player, analytics are also used in the conditioning of athletes, particularly important for all the baseball players preparing for the start of the MLB spring training. Sports analytics is the focus of this episode of stats and stories, where we explore the statistics behind the stories and the stories behind the statistics. I'm Rosemary Pennington, stats and stories is a production of the American Statistical Association in partnership with Miami University's departments of statistics and media, journalism and film. Joining me, as always, is regular panelist John Baylor, emeritus professor of statistics at Miami University. Our guest today is Alex Andorra. Andorra is a senior applied scientist for the Miami Marlins Formerly he worked as a Bayesian modeler at the PI MC labs consultancy firm. He co founded. Andor is also the host of the podcast learning Bayesian statistics. His areas of expertise include hierarchical models, Gaussian processes and causal inference. Alex, thank you so much for joining us today. Yeah,

Alexandre Andorra
thank you so much for having me. I'm super excited, and I love the show, so it's really an honor to be here and that you folks invited me.

Rosemary Pennington
Don't shine John's ego more than you need to.

John Bailer
He's talking about you, rosemary, how about the recent episodes where you have raised the game.

Rosemary Pennington
Alex, I know that you have worked as a political scientist or in political science before you moved into sports analytics. Why did you decide to make that leap? Because it seems like those are very different things.

Alexandre Andorra
Yeah, it's a it's a good question. Rosemary, I'm not surprised. Could give you, you know, the like the Manifest Destiny answer that you have with backward bias, you know, inside bias. But the truth is, is, it was in, I guess it still is extremely random. My career has been the the result of random interests, persistence and and like. And so I started, indeed, with political science. That was my, my first love in the professional area, I discovered that actually I was studying political science. I was writing a book about the geopolitics of the US. At that time, it was 2016 a very consequential election. I remember it was July, and I discovered while writing the book Nate Silver's models for 538, at the time, and and the nerd in me was awoken. I was like, and I wasn't at all it like I wasn't doing any statistics. At the time I was doing I was actually in a short term contract in the French secretary of state, so, you know, working on Foreign Affairs, basically. But I was, I saw the model, and I was like, Oh, this is awesome. I need to do that for next year's elections in France. And we had elections in 2017 also a big election, a very, even new one. And, and, yeah. So I spent the whole year, the rest of the year 2016 until until May on 12th, 2017 learning Python and learning again, Beijing, stats. So that's how I started political science. Now, hi, when did you spot? This is, like, still part of the story, but basically with time, I started to realize I was more interested in the methods than in the field of political science. More and more, I became kind of disillusioned with the field, because I felt like it was more political than scientific, and that also nobody in France was going to pay me for electoral forecasting,

and I was broke, so I didn't body.

I realized actually people would pay me for statistical methods and for statistical models, especially Bayesian models, because not a lot of people know about those and can do those. And I got very lucky, because also I started learning Python at the time, which was still kind of a niche language, only the nerds knew it. But I remember when I was telling my parents or my friends that I was learning Python, everybody. Was like, What now, if you mentioned Python to someone I don't know, a lawyer, for instance, he'll know, or she'll know what what Python is. So I was very lucky in that sense, because Python also just the popularity of Python just burst through the roof at the time. And so that's when I started integrating the pine C card F team, then we started pine C lambs in in this year, actually, I felt like it was a good time to get a new challenge, and working in a professional sports team has always been a dream for me. Since I'm a child, I've always been very into sports. I've done plenty of sports. I've been good in none of them same. So, yeah, I was like, that was very sad, because I couldn't be a pro athlete in any sports. I've tried, and now I live, actually, at the time, where I'm lucky to be able to contribute to a sports team without being an athlete. And actually, what I know how to do, and love and love to do so patient modeling and stats, I can apply that to to a sports team. And that's, that's really awesome. And so, yeah, that's how, basically, I started in the in the sports industry. That's

John Bailer
a, that's a, it's a great story. Thanks. Thanks for sharing that. I'm curious, are there things from from your study of political science that you that apply directly to thinking about analytics and sports? Yeah. I

Alexandre Andorra
mean, in a sense, a lot, because data in both realms are imperfect, you know? So Polytechnical science is way harder because this is this social data, survey data, first reason a lot. And second, it's really not reliable. Like even the best ones we have are polls. I mean, RCTs, let's say, but then we have polls, and polls are the best thing we can do, but it's really bad. And so in that sense, you know being very careful with your data and actually modeling, and just getting the data as one node in your model, and not the thing you use to actually get the results is something you develop when you model, when you do otter forecasting. And I would say, if I had to pick a second one, that would be hierarchical models, because, and that's because there is not a lot of data, but there is a lot of structure and a lot of domain knowledge, and so you have to put that into the model. And then very often, these are hierarchical layers. You can share information between the different clusters, and that's very useful, because often you don't have enough data for a given cluster, like, let's say, a state of the United States, or a county where you don't have a lot of poll but you can share what you learned from similar counties through the model. And that's extremely powerful. And it's in sports, even though, especially baseball, is extremely advanced on the on using data and using science, and you have a lot of data. This is, like, the amount of data. It's just incredible. This is like a candy shop. Like, each time I see the data, I'm just amazed by that. But it's not because you have a lot of years of data about a lot of players that you necessarily have a lot of data with each player. Because you have a lot of players who don't play a lot in the MLB or then they they play a bit, then they disappear, then they come back and and the best players they are, they are not there for, you know, like a long time either. So these, like, for each given player, don't have that many data. And that's the important thing, even though, again, baseball is an extremely rich data reach Spartan I'm not complaining at all, but something that you you get from having worked in a very data poor environment, I

Rosemary Pennington
wonder, is there some aspect of the sport that you're particularly excited to get your hands on the data of whether it's like batting or pitching, or something like is there something about the data specifically around something in baseball that is exciting, you or is it just everything? Yeah,

Alexandre Andorra
honestly, this pretty much everything, because I don't know a lot about baseball, so I'm actually learning baseball through the job. Basically, I mean, I obviously have notions about baseball, but I'm working in a pro MLP team, so you can imagine the amount of knowledge that most of my co workers have about the game, and I am nowhere near them for now, but I can learn about. Very well and fast, thanks to them. And the data is also helping me, you know, working on the models, this is really helping me understand the dynamics of the game, mainly, what, what is making a good player in some compartment that we're interested in, that's really what, what I get from from working on these models. So, yeah, I think, I think that's mainly that. You could say it's, it's the the excitement of the of the beginner, if you want,

John Bailer
that's, that's, that's a wonderful thing to possess. I think it's good to be a beginner at all points of your life. I also want

Rosemary Pennington
to point out that I also have notions of baseball that's about as well educated as I am about the sport,

John Bailer
and I played for many years, that was something that I did do. And I'm curious you sort of alluded to one of the kinds of classes of problems or questions that you might address. One was that of player evaluation is part of what what you will you might do with analytics. Are there there? What are some of the other kinds of questions that that someone that that's doing sports Analytics might be working to answer for for a professional baseball team?

Alexandre Andorra
So many,

John Bailer
pick your favorites? Yeah.

Alexandre Andorra
I mean, of course, like the I would say for bread and butter would be higher valuation, because that tree, in the end, what really matters for the team is being able to use the money you have as efficiently as possible in buying players is an investment. So you want to be as sure as you can be that you want to buy this player or you want to sell this one, and why? Because it depends on, you know, your objectives, how you want to build the team, how the manager also is talking with the GM and the rest of the team about that. So that, I would say, is really what I've seen being the the most important thing. If you don't have that, you don't have the foundation, and it doesn't really matter to to the rest. And it's not only in baseball, it's, it's like that in a lot of spots. I know John, you, uh, you used to coach soccer. So you know soccer is, is really the same and, and I would say it's even more important in in soccer for for different reasons. We can, we can talk about that a bit later if you want. Yeah, so there is that you need that foundation. And then there is so many data and new data sources that come in every year in baseball that really you can have a lot of fun, like the latest arrival of data. Are joint data, right? So it's like, you know, you you can track the knees, for instance, of the RV, elbows of players, and you can basically recreate their path, their movement, either on the field or even during a peach. So these, like, these really cool, I don't remember the exact name of it's like, bio stats, or something like that. You know, bio mechanics. I think it's biomechanical data. So, yeah, like, this is something some teams are, are pushing on right now, because this is the frontier. So, so if you're a biomechanistian and you like baseball, I'm pretty sure you could, you could get a job in the MLB if you wanted to. Computer Vision is also something that, that I see used more and more. Again, this is more at the frontier, but, yeah, this, I think it gives you a panel of what you can do, but basically you have so much data that, yeah, you could build a team of several like, if I had, you know, if I were given the power of building my R and D team, I would probably do something like that, like a portfolio investment strategy, basically where I would want, you know, most of my modelers to work on the on the bread and butter stuff, really nailing down the player projection and making sure we get better every year at the end. But I would also get some other modelers, maybe 20% of my portfolio that does more, you know, re secure thing more at the frontier. That takes more time, that's gonna not work a lot of the time, but it can. It can give you some really good advantage compared to the to the other teams. You're

Rosemary Pennington
listening to stats and stories, and we're talking with the Miami Marlins Alexandra. So you mentioned a moment ago soccer, and I know that you are doing research on soccer. Do you want to talk through what it is you've been working on?

Alexandre Andorra
Oh, yeah, sure. Always my pleasure to talk about soccer. I'm European, you know, so that that is really the big, the big sport over there in France also, even though French people don't really like to say it because, you know, it's not very classy, they prefer to say it's tennis or rightly. I. But look at the look at the look at the numbers, and it's just like football is by four by a factor of 10 more popular in France than rugby, which is the second sport by number of of people you know, actually playing the sport in Yeah. So basically, I started working on on a on a project that's completely open source, and we're working on a paper right now with Max go, who is a junior analyst who just finished his PhD at Boca new university in Milan in economics. And yeah. So we were curious about, how do you isolate the skills, the real skill of a player, trying to de confound it, from the skill of the team he's playing in? Because football, especially European football or soccer, is extremely unfair. It's an extremely capitalist sport, in a way, where we don't have at all the mechanisms that American sport us sports have to kind of make the leagues more equal to have a bit more suspense. European sports is very, very unequal, and the big teams are basically always the same. They don't always win, you know, but it's like 80 90% probability that PhD is going to win the league every year. For instance, in France and the rest of the continent is a bit of the same as usual. The English are a bit different, you know. But even there, the Premier League is getting more and more concentrated. And so basically, it's very important in soccer to try and and isolate the player effect. And so that's why we, we try to do in this, in this paper, we just submitted it to the to the MIT Sloan sports analytics conference for 2025 so you know, we'll see if we if we get selected, but if we get then, then we'll be in Boston, probably in March, in in basically what the player does is trying to to isolate that and trying to come up with the soccer way of computing a very cool metric that I really love in Baseball that's called War or wins above replacement, and that, that's a such a cool use of statistics to me, because this telling you what the contribution of a player is compared to a replacement level player, right? So not on an average level player, but actually a replacement level player, so a player that is ready on the bench to take the place of that player if he gets injured or if he gets traded to another team. So that's usually a much better player than an average player, because obviously, like the replacement level player in the MLB is very is really good. And so basically trying to replicate that in football, which is different because it's a much more continuous spot. So we've started isolating the problem with forwards. So center forwards, the one who strike the goals. And so, yeah, basically we did that where we have the model which can isolate the contribution of the player and then the contribution of the team the player is playing in. And so that's a that was a really cool project, very, very challenging we're fitting. The main thing is, we're using Gaussian processes in this project because I love them, and I thought it was very useful here. But basically the idea is, like, you can decompose the time series of a player carrier in at least three time components, right? You could think of a long term component, which would be the aging curve of the player. Here you could imagine, like a parabolic shape, more or less, you know, it they increase fast, and then they plateau, and then they decrease. But they decreased less fast than than they increase in. Then you could within each season of of football, you could also imagine that they have a medium, medium term time component, right where they get physically prepared, often to peak at some point in the season. In Europe, it's usually for February, March, when the biggest games happen. So usually they start slow, and then they would get better, and then they can drop, also quite a lot, because they can get injured. It can get, you know, too too intense, too many games, so stuff like that. And then you can have a third Gaussian process, which is basically your garbage can of short term variation that that is not explained by the other components. So basically, that's what we're doing in this project. And that's pretty cool, because then we can get some some cool plots that we have in in the paper where we can basically differentiate two things that we came up with, something we call the skills above replacement and the performance above replacement. So skills above replacement is. Really, if all players were playing in the same team, what would be expect them the scoring rate to be? So it's kind of what you want to know, if the playing field is leveled. So kind of who is, who is the best in in like per se, and then performance above replacement is the SAR so skill of a replacement, but taking into account the team the player is taking is playing in. And so that gives you an indication about how the team is elevating, or, on the contrary, downgrading, the performance of the player you're interested in. And so to give you some of their headline results, when we did that, interestingly, the best players, Messi, Ronaldo, Erling, Allen, all of them have you know the best. SAR, they are the best of the best, but they get an even better par So performance above replacement metric because they're also playing in teams which are just incredible. So that means the teams they were playing in were actually allowing them to score even more goals than they would have scored in an average team. I was thinking

Rosemary Pennington
of like players that I really loved watching, like Diego Floran, who played for Uruguay, and met otziel, who played for for Germany, and and Arsenal, and thinking about sort of how they, at times, can be so beautiful on the pitch and play so well, and then other times, they can look like complete garbage. And I'm just thinking about, like, the makeups of the teams when they were playing well and when they weren't playing well, just in my head, trying to think of like, oh, maybe that was a garbage national team that year, and it sort of brought down the performance of the player. So I think that's really interesting. So

John Bailer
were you restricting your data to particular leagues in certain seasons within these leagues,

Alexandre Andorra
right? So Max actually did that. He came up with a way to scrape all the data from a German website called kicker, and he managed to get all the data from four biggest leagues. So all the leagues, except for France. Obviously, we must have been on strike that day. But yeah, so basically, all the four big leagues. And I think we have almost 24 seasons for each league, wow, like that. So yeah, like, that's the data set. Is really, is really big. That's really cool data set, and we have that game by game. So it's not, you know, just one row for one season. It's game by game, which team met whom? What was the result? Who scored that? That's a really cool data set. And Max, you know, not just came up with with a way to scrap all that and save that and clean that. And so that's all in the GitHub repository for people who want to have fun with that.

John Bailer
So I'm really curious thinking about, you know, with 24 seasons of data, you know, thinking about what, who was, who was, sort of the players with these highest pa ours or equivalent values, you know, 20 years ago or 10 years ago, and how do they compare to the players with the highest values today?

Alexandre Andorra
Right? Yeah, that's a cool thing to do that we didn't do yet.

John Bailer
I'm sure there's a lot that's a really neat problem. I you know what? I think

Alexandre Andorra
that we'll get to it for sure, because that's really, that's really fun. Yeah, well, we would need for that to compute the par for each season, which is definitely doable, because we have everything in the model to do that, and we have the Gaussian processes. So what I can tell you is that, I mean, definitely messy Ronaldo, or, like, really, above and beyond, you know, shoulders above the other ones. And then you have, you have other ones that you can you're like, oh, yeah, that's normal. He's there. Alan shear for instance, for the Newcastle fans, yeah, Alan Shearer is, he's among the best ones, of course. Dio forlen. I don't think he's in there.

Rosemary Pennington
I was also thinking about too, so, oh yeah,

Alexandre Andorra
yeah. So he's not in there, but he's he didn't score a lot. He was more of a midfielder. He did score more for a midfielder, but yeah, he's not in the forwards. But yeah, there are some, like, one of my favorites, I didn't send Kevin otter way, and also Legend of PhD, of PhD, he's in there. But, yeah, you can see it's not, it's not messy level. But I was happy he was at least above replacement.

John Bailer
I see Pele. I want you to take a time machine back and get all the Pele data in this. And you know, the other thing that just immediately comes to mind for me is, if this works out, I mean, it's it immediately would generalize to other games that have that same kind of continuous flow, particularly like low scoring games with the same the context of who you're on the pitch with or the ice with. So hockey is a is a pretty natural you know, this works out in this context, I could see it generalized pretty nicely to that. Type of setting. Are there other ones that you could envision?

Alexandre Andorra
Yeah. I mean, there are way too many things I want to do. This is the problem. But yeah, I mean, Max and I are already thinking about, you know, extending and extending that an obvious thing we can do is, is improving the model we have right now, I have several ideas. I think, I think the GPS we could try right now, we have one GP for all the players. I think I mean three GPS for all the players. I think we could actually have three GPS per player, but also sharing information between these GPS. So having a hierarchical structure in there. And also, I would like to see the model. Could do some clustering at inference time, so being able to tell you which are the elite player and the replacement level players right now, it doesn't do that. You have to do that afterwards, which is also, like, that's cool, because I think it's very good for a recruiter, for instance, a decision maker in a club, a football club to understand the model and use it, which is actually what you want, because if the model is too complicated, they are not going to use it. And this is like, well, it's money down the drain. But yeah, there is that. And of course, the all the other positions that we're interested in, right? We only did forwards for now. But the problem of football is that, is that if you, you cannot have only one war metric, you, you have to have kind of a different war metric for each position. So then, yeah, like if, even when we get to that, well, well, I think we'll go to goalkeepers, because that's going to be the, the easiest next one, and then defenders, and then the hardest is going to be midfielders, for sure, but yeah, so we're thinking about that, oh, like, I mean, if, if that's of interest to to people. And, you know, we can publish stuff, and people are interested in that, I can definitely work on that. And, you know, on the on this side, for years. That's fun. That being said. If people are, you know, interested in joining that effort, feel free to to reach out. I always love talking to motivated people. Well,

Rosemary Pennington
that's all the time we have for this episode of stats and stories. Alex, thank you so much for being here. It's great.

Alexandre Andorra
Yeah. Thank you so much, folks. I mean, I, I, I hope I didn't give you too long answers, but yeah, that was, that was a pleasure, like, really, uh, thank you for for all the work you do. And I'm really impressed by the by the setups. She's super professional. I record an episode I'm gonna feel like an imposter.

Rosemary Pennington
Stories of the partnership between the American Statistical Association and Miami University's departments of statistics and media, journalism and film. You can follow us on Spotify, Apple podcast or other places where you find podcasts. If you'd like to share your thoughts on the program, Send your email to stats and stories at Miami oh.edu and check us out at statsnd stories.net, and be sure to listen for future editions of stats and stories where we discuss the statistics behind the stories and the stories behind the statistics you.

Transcribed by https://otter.ai

Stats and Stories is a partnership between Miami University’s Departments of Statistics, and Media, Journalism and Film, and the American Statistical Association. You can follow us on Twitter, Apple podcasts, or other places you can find podcasts. If you’d like to share your thoughts on the program send your email to statsandstories@miamioh.edu or check us out at statsandstories.net, and be sure to listen for future editions of Stats and Stories, where we discuss the statistics behind the stories and the stories behind the statistics.

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Women's Endurance Statistics | Stats + Stories Episode 356

Claire McKay Bowen (she/her) is a senior fellow and leads the Data Governance and Privacy Practice Area at the Urban Institute. Her research focuses on developing technical and policy solutions to safely expand access to confidential data for advancing evidence-based policy-making. She also has an interest in improving science communication and ensuring everyone is responsibly represented in data. In 2024, she became an American Statistical Association Fellow “for her significant contributions in the field of statistical data privacy, leadership activities in support of the profession, and commitment to mentoring the next generation of statisticians and data scientists.” Further, she is a member of the Census Scientific Advisory Committee and several other data governance and data privacy committees as well as an adjunct professor at Stonehill College.

Episode Description

Are you ready to register for a 100-mile race that includes 60,000 feet of elevation gain? How about a 3000-mile race cycling across the United States in the race across America? These endurance competitions and events are amazing athletic achievements, and women are competing in these events in ever-increasing numbers. These amazing feats and the factors that have hindered and enhanced the participation of women in these endurance sports is the focus of today's stats and stories with guest Claire McKay Bowen.

• Full Transcript

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John Bailer
Are you ready to register for 100 mile running race that includes 60,000 feet of elevation game. How about a 3000 mile race cycling across the United States in the race across America? The chunnel may pass under the English Channel, but what would you think about swimming across the channel? Yeah, maybe multiple times. These endurance competitions and events are amazing athletic achievements, and women are competing in these events in ever increasing numbers. But did you know that women did not compete in any track events in the Olympics longer than 200 meters between 1928 and then 1960 or that the first women's marathon in the Olympics was in 1984 factors that have hindered and enhanced the participation of women in these endurance events is the focus of today's stats and stories. Episode. I'm John Bailer. Stats and stories is a production of Miami University's departments of statistics and media, journalism and film, as well as the American Statistical Association. Joining me is regular panelist Rosemary Pennington, chair of the department of media, journalism and film at Miami University. Our guest today is Claire McKay. Bowen. She is senior fellow and leads the statistical methods group at the Urban Institute. She is also a member of the census Scientific Advisory Committee and several other data governance and data privacy committees. An adjunct professor at Stone Hill College and a member of the significance editorial board in 2021 she was named an emerging leader in statistics by the committee of presidents of statistical societies. She is a keen participant in endurance sports, and Claire is also a returning guest to the podcast. Her recent significance article entitled significant strides women's advancement in endurance sports, provides the background for our conversation today. Claire, thank you so much for joining us today. Thank

Claire McKay Bowen
you for having me again. Well, it's great because our glutton for punishment. I think I

John Bailer
was going to ask you that. I just want to start with what inspired you to write this article?

Claire McKay Bowen
Well, if you read the first bit of the article, I was very much inspired by Jasmine Paris, who is a British ultra endurance runner, she became the first woman to finish the Barkley marathons. And so your introduction at the very beginning, talking about, are you ready to run over 100 miles with 60,000 gain fit game to be clarifying on that is, is what the Barkley marathons is, and it's considered the most brutal ultra marathon in the world, because it's unmarked. It's going through the forest and mountains of Tennessee. There's actually like these, like series of things of you get, like a specific page in a book that you have to rip out to show that you've actually hit the certain parts of the mark of the trail, because it is unmarked. So this is part of like, the brutality that is this race. And Jasmine is the first woman to finish it, and there's only think it's still like with her. It was like 20 participants who have finished that race in the history of it becoming 100 mile race, which was in 1989 so it was just incredible to follow her progress. And then she was within, just basically it was two minutes within two minutes of almost being disqualified, because you have to finish it within 60 hours. And so she finished it in the 59 like 58 minute range. So

Rosemary Pennington
in this article, you talk about how there has been this, what feels like enormous growth in women participating in endurance athletic competitions. And you talk a little bit about, sort of the importance of Title Nine, potentially for for that, can you talk us through, kind of, what, what that bit of us legislation has done for women in these sporting events?

Claire McKay Bowen
Yeah, certainly. So just to clarify for some of the people who might be interested in this article, I only focused on three aspects of what contributes to women endurance sports. There's many other factors too. But to make a nice, concise piece, it was, I've decided to focus on three, and one of them is the one that you mentioned, which is participation, like equal participation through Title Nine. And so that legislation happened. Think now it's 52 years ago, and so it allows people who go to certain schools in the United States that gets, like, certain kind of funding to have equal opportunities for for women to have in those sports and so with anything, and I believe I say this in my article, that it does take some time for for that legislation to to kick in, and for schools to be more familiar with this and to have programs start right. It doesn't happen overnight. And so you can imagine that those who are in their 30s and 40s fully benefited. Yeah. From that legislation, even though it's 52 years old. And if you look at all the major women who come out from American sports right now, in endurance, they're all in their 30s and 40s right now, hitting these and hitting these major milestones. I'm not saying this is the causation, right? We're all statistician here, but there's definitely a correlation here, and the fact that when I grew up, I'm in my 30s, and I it was never a question of whether or not we could participate in sports like, yeah, you could. You got to compete in these myriad of different activities, and it's just expected where, versus those who are now in their 50s and 60s, I talked to my colleagues, or those who are also the participant sports like, it was a very different feel when they went through school.

John Bailer
You know, I was, was fascinated by some of the different endurance events that you described as part of your as part of your article, you know, they, you know, I alluded to some of those in the introduction to the episode. Can, can you talk about some of those, those achievements ranging from the the swimmers and cyclists and and even polar runners.

Claire McKay Bowen
Oh yeah, it was really interesting because some of them I already knew beforehand, like, like, I said, I was just really inspired by Jasmine Paris's amazing Barclay marathons run. And then I started looking up into and I knew so pausing here so I already knew about Jasmine Paris's remarkable career leading up to the Barclay marathons. And I knew a couple others, like Courtney dahlwater, who is an amazing Ultra runner. And I say in my article that she won the Moab 20 240 miler, where she beat the second placer by over 10 hours. And she also did, like the Tahoe 200 miler. But the article that when, when you make these articles, they get published well before it gets published. And it was just like a month before the article was getting published that Courtney also, I think she plays second or something in the what race was this? I'm trying to think of my head. It's not the Tahoe one. It was Mount Fuji. Excuse me, Mount Fuji, and I'm looking this up now. No, she she got, she placed third overall, but she was still the overall, like winner for for women's and the second place, or just like she was barely behind the second place, or actually, it looks like 30 seconds behind the third second Placer, which is amazing, right, as a woman and the two men being her, was just not that much of a margin. So I knew about these, these individuals, but then, like, looking up more for this article, just seeing like, well, how, how have we come up from from other ones, and finding out that there was a woman, Donna, I'm not going to say her last name quite right. Your your car notion otter, endurance runner who set the record for the loggers puller run. And that just happened this year in 2024 and to say that like, well, she run 30 miles every day for 20 Antarctica like, that's that's really intense. There's a special time training you have to do for that. And then just looking up others. I I knew about the woman who ran it, who cycled across America, but I didn't know her true origins, and then looking her up and reading her her amazing career as Leah Goldstein, and it's a Canadian endurance world cyclist. So you're just seeing like all these amazing people come popping up across all the different sports, and it does create a signal that we, we as women, are dominating more and more, and it's because of certain things getting better for for us in endurance sports. When

Rosemary Pennington
I was reading this, I was actually thinking a lot about Kristen Faulkner, who won the Olympic road race this summer, and who had, you know, gone from, you know, an everyday kind of job to, like, suddenly training and then winning this race, that women, that American women, had been sort of written out of, right? And I wonder how much has like the training of female endurance athletes changed over the years that that, you know, you have this graph that shows like it's getting close their performance is getting closer to male performance, but also that we're in a situation where you can go from, you know, not being sort of in that sport to sort of being trained up to be a champion, essentially.

Claire McKay Bowen
Yeah, yeah, that was, that was amazing. Yeah, the breakaway for like, one whole kilometer. Oh, man, that was like, so, yeah, I got super excited as somebody, who does I do? It's called E racing. I do virtual bike racing through Swift. I'm on a team and, like, we all geeked out. We're like, oh my god, this happened. It was so exciting to actually see this, because it's so hard. And as somebody who's not a pro, but still does these races doing that kind of breakaway is like, really, really tough, and the fact that she did it and sustained is credible. So actually getting to your question, instead of me just geeking. I'm really excited about this. This is my other life. Rather being statistician is like, I want to be endurance athlete. I the training definitely it. We're just so much better about it. So I talk a little bit in the article, but I don't touch on everything, which is like, we're we now know that there's a difference between men and women when we train like it seems really obvious when you state that, but there isn't a lot of investment or research into it. And so we as a society have been training women to be like, Oh, we're just small men. So like, whatever we've been doing for men, we should just do the same thing for women. But there's a lot of, of course, differences, like our hormonal transitions, right? Like, it's that the fact that, like, we just have our body weights a little bit structured differently, that we need to recover differently, all these different things factor in. And so it's actually one of the reasons why, like, I actually have a coach to help me go through some of the trainings, and as a woman. And so it's really nice having somebody who's really focused on, like, what kind of nutrition do I need to have? Like, what kind of ways should I recover, or how I should train up for certain things, like having that focus is, is really nice. And it knowing that she herself is a pro athlete and knows how women should train up is, is great. So this also goes into, like, I think I talked about this article too, is there's a great book about it called roar, and it's and there's actually a podcast that goes along with it. I think it's like feisty females, and it's talks about how women hurt, like, there's a whole chapter about, like our hormones and like when we should be training, and it's very different than what people might expect, because, like, when we're closer to our cycle, for instance, we are most close, like, close to men, so you technically need to trade harder during that period of time to get certain kind of benefits, which is really interesting versus what some people might think.

Rosemary Pennington
As I was reading that I so I ran competitively in high school as a sprinter, and I had to quit my senior year because we got a new coach who was the football coach who took over our track team and started training the men and the women in the same way. And I had come back from being very ill and injured to sort of try to to run again, and he just expected us to run the exact same way. And I just I couldn't do it, because I came back sick. And I wonder, and I think about all those young female athletes you know at the middle school and the high school level, who you know, hopefully are benefiting from this changing understanding of how female athletes need to be treated to perform well. Because I know you know that was in the 90s, so it's not that long ago, but it definitely like that idea that women are not just little men kind of really resonated with me when I was reading this.

John Bailer
So, you know, you had mentioned so we've talked about a couple of the touched on a couple of the factors that you described. I mean, you talked about scientific research, representation and time were the three kind of organizing ways that you were talking about the change that has occurred in terms of society and how people are competing. I'm very interested in this. My oldest daughter ran her first marathon a few years ago, and my youngest daughter is prepping for her first marathon now. So it's neat to see this, and I'm I'm looking forward to sharing your article with them. So So can you talk a little bit about kind of you mentioned with the scientific research, the idea of of the training differences, and in reflecting that and respecting that as part of of getting people ready for endurance events. And the you talk about a little bit the representation with some of these examples that you've done, can you talk a little bit about kind of, this, this factor of time?

Claire McKay Bowen
Yeah, yeah, I think my, my, my friend's statement that I ended quoting in my article saying, like, we're seeing more women getting better at endurance sports because we have more opportunities, but because women tend to take the brunt of child care and household chores that, like, still impacts our performance negatively and on two ways. Like, one is that it just takes a ton of time to do certain events, or just to train it up, right? And I, I talk about, like, how long it took me to train up for an Iron Man, and I even qualified with the whole thing of, I'm actually in better shape than the average person. I constantly go through a cycle of, like, endurance races. And then I then take an off season, and then I reboot again, right? So I have a really strong base, and so I could do a 16 week training program to do to trade for a full Ironman. And I realize I'm saying Ironman should be said as the full distance race for the triathlon, to swim, bike and run. And training for that is just like I said, it's a lot of time. So 16 weeks is pretty short in terms of, if you're less experienced, it's also the fact like during the peak, what they call peak training, for those who don't know, it's right before you're going to take a little bit easier load right before the race. And so peak time is your most intense time. It's the longest runs or the longest swims, or the most intense, like interval training, where you just, like high impact or high high pace, or things like that. And it's usually like a three week period. And during that time, I was consistently doing like, 15 to 20 hours of workouts. So that's a lot of time to think about, like, oh, that's, that's a part time job on top of if you're working full time or have childcare duties or things like that. So so that gets into that whole, like, We need time, and if women are doing a lot of the other kind of chores or other responsibilities on top of their normal work, then that becomes very difficult for them to balance it. It's also thinking about the bandwidth too, right? It's the whole mental load of, like, I need to start this training. I need to put that effort in. And I even see that with me with who I don't have children. But sometimes I have, like, a really hard day and I need to do a workout. I'm like, gosh dang. I need to really pound through this workout. Just like, just focus on this even though I'm mentally really tired from the work day, and sometimes I have to message my coach going like I didn't push as hard as I could have for this workout just because I was mentally fatigued.

John Bailer
You're listening to stats and stories. Our guest today is Claire McKay. Bowen.

Rosemary Pennington
Claire, what got you interested in doing endurance sports in the first place?

Claire McKay Bowen
So to be honest, I was a fat kid in high school. Nobody believes me now, but I was a little overweight, and I had really low self esteem, and at some point I got asked to be the manager for the cross country team. So it was a little funny. I saw I was like, the student manager. And then at some point I was like, well, I should start running too, because then you have to sometimes, like, run from like, one point of the course to the other to to get time, or, like, cheer people on, or track all the students. And at some point, like, halfway through, I was like, well, maybe I'll just start building up. And I got it in my head that it was like, okay, everything takes a little bit of time. So I'll start running a quarter mile until I feel comfortable, and then I'll reach to, like a half mile, and then it just kept going slowly from there where I just kind of built it up. And so I actually then joined the team for the second half of the season, which was kind of crazy, and my goal was to not get last. So I never did. I do. Remember this from high school. I never got last, but one time, I did get second to last. So I wasn't super fast, right? I just was starting to run, and the team was so supportive and really nice, I got then motivated. So like, you know, I it's even though it's an individual run, it's still a team sport, because you get points for the team to rank. So I thought, well, I really need to get faster in order to help get more points for the team, because we're from a small school, so we don't have a lot of runners, and so I decided to run over the summer, I think the following year. I'm trying to remember as many years ago, but then I got I lost a ton of weight and also started running faster. So I actually got the like most improved award for the end of the season. And my coach was, like, really impressive. Like, yeah, Claire was mostly proof. She went from, I think, of like, time went from like 40 minutes to 20 something, right. So I went from being right, really, really, really slow to actually being one of the scoring members of the team for the varsity. So, like, not the fastest. I want to clarify. I was still not the fastest, but I was definitely above average at that point, and I just built off of that, because I just realized, like, I really love running, and I describe it to people as, like, my meditation, like, it's my way to just, like, clear the world and really focus on other things than like, like, stress from work or stress from life just seems to, like, melt away once I, like, start running or biking or swimming or something. It's just, it's a way to really clarify things, and it makes me feel good at the end of the day, even though sometimes I'm like, I don't want to run, I'm so tired, and then I start running, and it's like magic. So, like, there's a comic called the oatmeal I don't know if you guys, oh yes. He wrote a actual dedicated book about his love of running, because he also was overweight, and he started running. He got really into it. And he has this little comic of, like, you're sad and gloomy, and then there's this, you're running shoes on the side, and you walk up to her, and she's like, Okay, well, fine, I'll get running. And then all sudden, it's like, magic, rainbows everywhere. Like, oh, everything's better, yeah,

John Bailer
what you just said really resonated with me. I started running when I was in grad school because of stress, and it was a, I think it was, it was sort of magic, and that carried over to a faculty job, by the way, in terms of both the stress and the running, when I was reading your article, the one thing that really struck me, well, a lot of it did, but, but, but in particular, the story about the Olympics, I just did not really appreciate that there was a constraint on distance for women after, after 28 Can you talk a little bit about about what happened and then, and then how things changed again in the first in the 60s and then the 80s?

Claire McKay Bowen
That's that's a great comment about the whole Olympics. Like I. Didn't know either, until I started writing this article too. Actually, I mean, I knew about the famous incident with Catherine, who's the first woman to finish the Boston Marathon. I mean, that went all over, pretty viral, about how a woman pretended to be a man to run this race, and in the viral picture of the race director, trying to pull the bib off of her and her boyfriend trying to defend her. They're like now, let her run. So this just goes back to back. So pausing here, so going back into the early 1900s all the way through the 1980s by the time women are part of the Olympic sports, it was just still the idea that women are small and delicate. So you see some things you can, like, look this up on like YouTube, or some other videos of like, what was the exercise equipment for women? It was these really ridiculous machines, but that was all what people thought was the way to have women work out. Like, there was, like, this belt that went around your waist, and it would just like, go back and forth and just like, massage your waist. And that was a workout for women to help, like, thin out their waistline. And the idea that, like, well, if you work out your what was it, your uterus would fall out your you would start growing more hair and just become more manly if you worked out more. And so these kind of ideas really permeated society, about like how women would perform, and it didn't help that in one of the Olympic races. So this is alluding to what you were saying, John, was that during one of the, I think it was the 800 meter race. So the women passed out from the heat of that race, and then the Olympics were like, Nope, we can't have women run that far like that. That's, that's too much. It's, they're too delicate. They can't do this. And you can imagine it's because we just didn't train women properly, right? And it's obvious that when you look at women like Courtney dahlwater, who's blowing men out of the water, that's definitely not the case.

Rosemary Pennington
I wonder, given the work that you have done and what you've looked at for this, you know that again, that to go back to that graph, you have this graph of these. You know, world, what is it? World Record marathon times, where towards the end, the men and women's times are getting closer together, and then you've got these examples of women who are beating men or coming in very close to men. I just sort of wonder, what do you sort of see as kind of the next, the next thing we should be watching out for when it comes to women athletes and endurance sports like what is, what is the next headline? You imagine the next five to 10 years?

Claire McKay Bowen
Oh, that's a that's a great question. I mean, you say I'm doing research. This is all for fun. I'm not. I want to preface to, like my readers, that I'm not a sports medicine right, scientist or endurance coach or anything. It's just something I really enjoy doing, and I've been doing for a while, and I part of these groups that follow these things because we enjoy it. So I'm going to preface that, but in the next five to 10 years, I very much vision women just getting like, as fast as men in certain sports. I think there is definitely like, there is definitely a difference, and that's why I say that women aren't small men, right? So there's going to be some things that men are going to be better at than women, in terms of, just like the physiology of things, which I know that's not what people want to hear, but this is why women are better at endurance sports. We're seeing that in the, I think in its in the future is that we're going to consistently see men, like men, dominating in some sports, and women dominating in others, like these endurance ones, because women actually are better physiologically. To take this. I mean, that's why the only woman to swim the English Channel four times, like back and forth, like the only person is a woman. The fact that Coney dawater is just blowing out all these other men, or jasmine Paris also is like, coming up, she did another kind of race where she beat a lot of men too. It's this is what we're going to be seeing more and more. And so certain sports are just going to be predominated by by women versus men, and vice versa, and some other aspects. So

John Bailer
when you're working on this, this article, what, what was the most surprising thing that you learned in in, you know, doing the background and writing this

Claire McKay Bowen
Well, other than the Olympic part, because I actually didn't know that the that women weren't allowed to I knew they were allowed to run, but I didn't realize it was so soon as soon As in. I thought we as women could start racing in Star Olympics force earlier than 1982 or whatever it was like. I was just really surprised about that. The other surprising thing was the the fact that we had to do these larger studies to be saying, Hey, we. Be obviously time is a factor, or obviously getting sponsorship is a factor or better nutrition, right? These are some things that seems pretty obvious, and it's definitely obvious to me too, but at some point you have to actually be a scientist and be like, Okay, we're gonna actually survey people. We're actually gonna analyze these things. And it wasn't I thought these things happen much sooner, but it hasn't. So like the Asics one for that big survey they did that didn't happen until 2023 and looking into the challenges and barriers for women in sports, or the fact that some of this research on like whether or not it's okay for women to work out while they're pregnant, right? There's, there's still a stigma about that, even though more and more research is showing that it's actually really good for women to work out while pregnant and post pregnancy with moderation, and, of course, having certain other tests done with your doctor and checking but that was why I thought it was amazing. Like one of my friends, she she ran a six minute or like, sub six minute mile the week that she gave birth, that she incredible, yeah, she also Boston called like she's just one of those people that just just makes you feel terrible, and like, I did a half marathon with her while she was pregnant. At that point, she was 30 something plus weeks pregnant. She beat me. She beat me like 10 minutes so she was the first place here in our age because we're in the same age group, and I got second place. So I felt like, well, if I'm gonna be beaten, it would be by my Asia. But then at the same time, she was 30 plus weeks pregnant, so I was like, I don't know how, how great that makes me feel about being beaten by her, but she's, she's an amazing athlete, and she's also, like, working full time with a different career, and then doing this on the side, and just just killing it. So I think it's so incredible. And she did all while she was pregnant, and then post pregnancy, she went back to do the corona which is the World Championship for for the full distance triathlon, and she got to bring her daughter with her. And it was very, very like nice to see that post on on social media about her and her family going out and her daughters watching her race.

John Bailer
Well, well, Claire, I'm afraid that's all the time we have for this episode of stats and stories. Thank you so much for joining us today. Thank you for having me. Stats and stories is a partnership between Miami University's departments of statistics and media, journalism and film and the American Statistical Association, you can listen to us on Spotify, SoundCloud, Apple podcasts, or other places where you find podcasts and follow us on social media if you'd like to share your thoughts on the program, Send your email to stats and stories@miamioh.edu or check us out at stats and stories.net and Be sure to listen for future editions of stats and stories where we discuss the statistics behind the stories and the stories behind the statistics you.

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Name, Image, and Statistics | Stats + Stories Episode 353

Emily Giambalvo is a sports reporter focusing on data-driven projects with the enterprise and investigations team. She covered University of Maryland football and men’s basketball from 2018 to 2023, and she has contributed to The Post’s coverage of the Olympics, gymnastics and national college sports. Emily grew up in South Carolina and graduated from the University of Georgia.

Episode Description

For decades, college athletes could not make any money from their sports identities. In 2021 the NCAA passed an interim name image and likeness policy which now grants athletes control over those indentities. They can now be paid for autographs, personal appearances, and endorsements. The economic impact of the NCAA name image and likeness changes are the focus of this episode of Stats+Stories with gues Emily Giambalvo.

• Full Transcript

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Coming Soon

Throwing the Red Flag | Stats + Stories Episode 344

Dr. Mike Orkin is a Professor of Statistics Emeritus at California State University, where he was a professor and chair of the statistics department for many years before becoming a consultant and a nationally known authority on probability and gambling games. Since then he has appeared in numerous forms of media ranging from CBS Evening News, NBC’s Dateline, a Google Tech Talk series as well as authored serval books.

Check out the full article at Significance.

Episode Description

A long pass down the sideline is caught in bounds. Or was it? The referees ruled it a catch, but the opposing team was unconvinced. In the NFL there's a way to challenge a referee call that comes with a potential risk which is the focus of this weeks episode of Stats+Stories.

+Full Transcript

John Bailer
A long pass down the sidelines during a football game is caught in bounds, well, or was bobbled and incomplete, the referees ruled it a catch, but the coach of the opposing team was not convinced. In the National Football League, there is an option for a coach to challenge a referee's call. This challenge comes at a potential cost. Our guest today has a strategy to help a coach decide about challenging a referee's decision. I'm John Bailer. I'm joined by Rosemary Pennington, chair of the department of media, journalism and film. Stats and Stories is a production of Miami University's departments of statistics and media, journalism and film, as well as the American Statistical Association. Our guest today is Dr. Mike Orkin. Orkin is a professor of statistics emeritus at California State University, where he was a professor and chair of the statistics department for many years before becoming a consultant and a nationally known authority on probability and gambling games. He is the author of a number of books, including the recently published The Story of Chance: What's luck got to do with it? Our focus today will be on his Significance magazine article, to challenge or not to challenge? Well, that is the question, thank you so much for joining us today, Mike, it's so nice to have you back as a guest.

Mike Orkin
And I'm very happy to be back here as a guest.

John Bailer
So can you start with a description of how the red flag challenge works in the National Football League?

Mike Orkin
Yeah. So for some situations, for some types of plays, the coach of either team has the right to challenge the result of the play as called by the refs, and if they think the ref is wrong, they can, for instance, the example you just gave is the perfect example, because that's one of the situations you can challenge, and that is the receivers running down the field, the quarterback throws him a pass, he goes out of bounds, he appears to have caught up, looking on the TV monitors. It looks like he may have bobbled the ball, and so that would be an incomplete pass. The refs on the field call it complete. So it's up to the coach of the defensive team if he wants to or not, to throw the red flag on the field, which is the challenge flag, and to challenge the referee's call and say, Hey, wait a minute, that's an incomplete pass. So if this is a crucial situation, as it was in a couple of the examples I gave in the article, in particular, for one example that you were just sort of referring to, namely, the receiver on the team who has the ball, catches the ball and looks like it seems to bobble it as he's going out of bounds. If that's in a crucial situation, then the coach on the defensive team can throw the challenge. Now you're only allowed a limited number of these challenges. And if you're wrong, you lose a time out, and they keep changing the rules on how many challenges you're allowed. So starting now, starting in the 2024 season, you're allowed two challenges, but if you get either of those right, then you're allowed a third challenge sometime in the game. So the coach doesn't want to just start tossing the flag and discriminately, because if he does and is wrong, he's going to lose a time out, and he's going to lose the challenge opportunity, another challenge opportunity. So the coach has to be somewhat knowledgeable. You can see the instant replay on the screens in the stadium, and, of course, the coach has a staff up in the booth looking at the TV instant replays. Then you only get a few seconds to decide whether to throw that challenge slack?

Rosemary Pennington
I would say this is a relatively new thing in American football. What sense do we have of how often coaches are doing this, and are they doing it in particular kinds of situations? Are they more likely to do it in the playoffs versus a regular season game?

Mike Orkin
Well, it's been around for a little while. It's been around various types of instant replay have been around for at least 20 years, instant replay in general, so there are certain times in the game, like the last two minutes of the game or of the half, they will do an instant replay of any key plays like making a touchless score, or things like that, or a turnover. And to answer your question, roughly 50% of instant replay reviews have been overturned, not that it's not only coaches challenges. That's also just the general instant replay reviews that the refs have to do at certain times of the game. But that's a pretty high percentage, yeah. And the reason, of course, is you can't see that in situations that are difficult. You can't see exactly what happened with fumbles, is another one. And so the instant replay really helps to be able to see on TV exactly, or on your screen, on your video screen, exactly what happened.

John Bailer
I was gonna say it sounds like there's, there's sort of different value placed on the importance of timeouts there. Also, you're gonna tell us a little bit about using craps as a model for thinking about this. But there's also another model about kind of what, what weight do you place on the value of, you know, what's the benefit of winning versus the cost of losing a timeout, right?

Mike Orkin
rWhich is sort of part of my model, yeah. And that's exactly right. And in fact, Shanahan was quoted in my article about that very thing, and then he has made that comment many times, a similar comment, so you have to, that's exactly right. That's sort of the key to understanding this. You have to weigh the value of a time out and compare it to the value of a successful challenge. And then, of course, there's also the fact that you only get two challenges in the game, or maybe three, if you're successful in the first on one of the first two. So that's another factor.

Rosemary Pennington
So you mentioned your model, and your model tries to help coaches figure out should they throw the flag or not? It was based on craps. I enjoy blackjack and poker. I do not really understand craps all that well, so I wonder why craps as this model for helping coaches sort this out.

Mike Orkin
Okay, so it isn't really craps, per se. It's the type of game that craps is, namely you either win or you lose, and you win with a clearly defined probability. Just count combinations on rolling a pair of dice when you make one of many craps bets, and then when you win, you get a certain payoff odds. So for instance, in the particular craps bet that I used in the article, if you bet that seven will come up, if you roll a pair of dice and seven comes up, you win, and you get paid four to one, which means for every dollar you bet, you get $4 and then the chance of winning is 1/6, because if you roll a pair of dice, there's six ways out of 36 that a seven will come up. So those are the two factors that are involved when you have to decide if you want to think about it probabilistically, whether it's a good bet for simple bets like that. So now you mentioned poker and blackjack, which are more complicated, because in poker, you play against the other players, not against the casino, and so things like bluffing can apply. And in blackjack, you have what are called dependent events, because when you deal cards out of a deck, once a certain card is dealt, then the deck composition changes. And so there are strategies where you sort of count, what's called card counting, where you can have good strategies. But in the situation that I'm talking about, it's more like a craps game, because the coach has to make a quick decision, and he has to weigh the payoffs against the winning payoff against the loss. And there has to be some idea of a probability involved. So now this is not something where you can just count combinations like you can when you roll a paradise. So this is what we could call maybe a subjective probability, or the probability of an expert that the coach has to figure out with his staff, two numbers. I think that most coaches can do that, and probably would like that kind of structure. But even so, if the coach can think of two numbers, the probability of a successful challenge, and there's data that I mentioned a few minutes ago to help with that. And then, what is the payoff? Odds? How much is it worth, or what's the value of a successful challenge to the coach?

John Bailer
So, you know, continuing that idea of sort of this, this payoff, and the value, you talk about expected value as part of the story here, when you're setting this up, this model for the coaches, and you know, you're the expectation, the expected value being negative is one of the reasons why I don't frequent most, you know, casinos in gaming, that doesn't attract me. So can you talk a little about what expected value means in the context of the craps games that are being played, and then how you then use that as a place to step off towards thinking about the decision about the red flag?

Mike Orkin
Right? So when you're playing craps, we're playing any casino game, there's this notion of expected value, which is really just how much you win on the average or lose. And then. Winnings is a loss in repeated play, so in craps, for example. And if you do this over and over with where the games are in, your bets are independent of each other, then the law of averages will give us a nice, cozy end result if you do it a lot of times. So that's not that it's much harder in blackjack and a little different in poker, but in craps, if you bet on seven, the example I used, and you win, you win $4 with probability 1/6. And that means that, roughly speaking, or put another way, in the long run, you'll win. If you bet $1 you'll win $4 about 1/6 of the time, and then you'll lose the other five, six of the time, install on the average. So if you win $4 one six of the time and lose $1 5/6 of the time, you'll end up on the average, losing $1 with probability overall, out of every six plays, you lose $1 on average. So that means your expected value, or your average per dollar bet, is minus one six or 17 cents. Now that, as John pointed out, is not a particularly wholesome environment. But some people, they think they're going to be lucky, or they'll bet, thinking they have some strategy, which they don't. And craps, it's a popular game. It's a group activity, lots of people standing around cheering, whatever. But it's a long run losing proposition. There's no way you can win a game of chance like that in the long run. And the way to measure that is with expected value.

John Bailer
You're listening to Stats and Stories. Our guest today is Mike Orkin, who's now going to tell us about how this expected value from craps translates into thinking about the red flag decision for a coach.

Mike Orkin
The expected value for just betting on seven and craps, is not good. It's negative. So we don't, I don't tell the coach to do something like that, because that's a losing strategy on the average. So what I thought about was, how can you make craps? And people sometimes cheats using loaded dice to come into a casino and try to win craps, because the probability of whatever they're betting on, let's say the probability of a seven gets higher because they have trick dice. Now that's not a very good idea, because if they get caught, they'll be in serious trouble, but you can think about it mathematically. What probability for these loaded dice do you need to make the game a to have a positive expected value? And it turns out that's pretty easy. Namely, instead of the probability being 1/6 it has to be 1/5 for you to win that bet. In order to break even on that bed in the long run. So the way to think of it is four times 1/5 minus one times four fifths. You can see that that equals zero. That's your expected value for a bet on seven using these loaded dice, where the probability of getting a seven is higher than it is ordinarily. But then that got me to thinking that it's very easy to balance off the payoffs and the probabilities, and if you put that together, you can see very quickly when it's a good bet. So when you're going to throw the challenge flag, the coach has a few seconds, and all he or someone on the staff needs to do is give them two numbers, and those two numbers can be quickly weighed. In fact, I have a little table in my article to see if it's a good bet, namely, if it has positive expected value. This is not exactly like a positive expected value in crafts, of course, because we're not in a casino. You can't count combinations. These are just subjective or expert opinions of the coach and the staff.

Rosemary Pennington
Have you shopped this around to the NFL?

Mike Orkin
No, I haven't yet. I just, I'm planning to send it around a little bit. That's a good question. One of the reasons that I thought of shopping it around is that some coaches for teams that I root for, like the 49ers, living out in the San Francisco area, make foolish decisions, and namely, really conservative decisions on when to throw the challenge flag. And I think someone like Kyle Shanahan, the coach of the Niners, who has a very smart staff could very easily use a strategy like this. Just think of two numbers. In fact, one of those numbers is backed by data, namely, what's a chance, in general, of a challenge flagging, of an instant replay being overturned? Causing a play to be overturned, but so they could just think, well, let's see. Like this, the example I give in the article, the Eagles. This is the champion NFL champ, NFC Championship game in 2023, the Eagles. They have fourth down there in the 49ers territory. Jalen Hurts, the quarterback on the Eagles, throws a pass, and if that pass is not complete, it'll now be the Niners ball, and they'll get out of a serious problem, namely, their opponent is ready, is getting ready to score. And so this is a high value immediately, the coach can tell if it's high value here, when it's fourth down and you have a challenge overturned, it's the other team's ball. So anyway, it's very clear that in this particular case, there was a high value that a coach would assign to this play getting overturned, which would overwhelm the possible loss of a timeout. And then there's the probability of success. But the TV replay, even, as even Shanahan, clearly shows that the receiver is bobbling the ball.

John Bailer
You know, it's interesting. I was thinking about this value discussion, and I looked at your table, you had it as value versus probability of when, and you know you, like you said, there is data on kind of how likely these types of calls are, have been overturned, but boy, the the context in which these calls would be made, you know, if I'm down to, well, if I don't have any timeouts left, I can't even call, I can't even throw the flag, right, you know. But if I'm sitting with three timeouts, it's going to be pretty easy to think about throwing it without, you know, I might be willing to say, Okay, I'm sitting on two if I'm wrong here. So the context is in the time of the game and where it occurs, you know, kind of all right, this incomplete pass call that was being made at the 50 yard line, and I'm gonna hit the punt. Otherwise, that might be different than if you're about the score. So there's sort of all these, these flavors of when things happened. So I imagine, you know, trying to think about doing this very quickly. You know, you say you only have seconds to make this decision, because they're going to hustle back to the line and try to get the next play off, you know, before, right?

Mike Orkin
Yeah, well, yeah, so that's right. So it's not easy, but these coaches in the NFL have to make these kinds of split decisions all the time, quick decisions, all the time, split second decisions, and they have a staff backing them up. There's a team of people sitting up high in the stands with TV monitors in front of them so they can see instantly what happened. So yes, it's very difficult, but to be an NFL Coach, you have the support and the knowledge to be able to do that sort of thing. And I think most coaches wouldn't have, once they sort of got fluent with it, wouldn't have much trouble estimating a probability of getting an overturned, a challenge overturned, and also of assigning a value, which is how much it's worth to the coach, when you compare where the loss part of it is all the things you just mentioned, John.

Rosemary Pennington
Yeah, as we've been talking, I've been thinking about all these other moments during a football game when a coach is gonna have to make a tough decision, do we go for it on fourth down? Detroit yesterday just pulled off this really amazing trick play, right and got a touchdown. And it seems like there are a lot of coaches who are doing increasingly riskier things on the field compared to even just 10 years ago. And I wonder just sort of how something like this might work out for someone, or whether there's another kind of formula to help coaches sort of navigate the Should we go out on fourth down feels like maybe it's closer than Should we do a flea flicker or something? Right?

Mike Orkin
So in general, some of these other situations that you mentioned might be more complicated than whether to toss the challenge flag, but yeah, the coaches have to make all these now. Nowadays, for some reason, you're right. They seem to see more trick plays, more going for it on fourth down, and this going forward on fourth down has actually been studied by using data, and their quantitative results about that have been surprising to the NFL that that they should go for it on fourth down more often.

Rosemary Pennington
This, your paper, will lead to that for challenge flags.

Mike Orkin
Well, actually, I try to just, I like to try to quantify things, and sort of what I do, and I thought it would be, it's quantifying this by just having two numbers that the coach has to and the staff have to think of is something they do. And I hope that Kyle Shanahan uses something like this. I don't care about the others. Andy Reid. I mean, I root for the chiefs. Andy Reid does that. He does, yeah, he's, well, he's more liberal than Kyle Shanahan. Anyway, in fact, in the article, I'll give an example of where he threw the challenge flag, and he didn't get it. Wasn't successful, but he still was sort of using these basic ideas, even if he didn't quantify it with two numbers. So he does that. He's more liberal. Let's put it that way. So go ahead.

John Bailer
I was now sort of picturing, you know, this whole red flag, and in review, has come about because of technology. You know, this has been something that, right, that's a change in the rules, and the change of play as a contact is a consequence of having this novel technology. And I'm just sort of imagining now, you know, if you're going to take your time machine into the future, Mike, you know, and thinking about technology, is there going to come a time when there'll be no need to have a red flag challenge, because it'll immediately be processed, you know, there'll be some kind of predictive model behind the scenes that will say, No, no, that's not. Was that not successful? Yes, that was. I mean, I've just sort of imagined that why will not, not the technology go to this, go to this next level?

Mike Orkin
Well, yeah, that's then. There's talk of that. That's not just a statistician's dream, but it's there. They're actually, they have plenty of technical people who work for the NFL. And there's, as you say, there have been advanced, huge advances, in technology. I mean, the next thing they're going to be saying is, oh, we're going to use AI to make this decision, which is really just a catchphrase for, you know, software and, and, but new software that does stuff like that. So, yeah, I think, I think that there will be a slow shift, or maybe not so slow, to making this decision more often by the NFL itself, with using technology. There's talk of doing that, of course, in baseball too, and they're starting to do things like that, like the sports in the strike zone. Well, it sort of depends on the umpire, and there are certainly ways to use technology to help with that.

John Bailer
Well, I'm afraid that's all the time we have for this episode of Stats and Stories. Mike, thank you so much for joining us today, for being here.

Mike Orkin
My pleasure, anytime.

John Bailer
Stats and Stories is a partnership between Miami University’s Departments of Statistics, and Media, Journalism and Film, and the American Statistical Association. You can follow us on Twitter, Apple podcasts, or other places you can find podcasts. If you’d like to share your thoughts on the program send your email to statsandstories@miamioh.edu or check us out at statsandstories.net, and be sure to listen for future editions of Stats and Stories, where we discuss the statistics behind the stories and the stories behind the statistics.

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Covering the Olympics | Stats + Stories Episode 343

Bo Li, is an associate professor in Sport Leadership and Management department. He teaches sport administration, sport marketing and sport public relations. His research has been mainly focused on sport digital media and branding. He has previously co-edited the book Sport and the Pandemic: Perspectives on Covid-19’s Impact on the Sport Industry, Sport Administration, and Governance and Administration of Global Sport Business. His research interests lie in the intersection of digital media, mass media, branding, and consumer behaviors. Specifically, my scholarship aims to advance our understanding of how various forms of media are used to connect with customers at different levels. He has authored over 40 peer-reviewed academic manuscripts. His works have been published in leading academic journals including Sport Management Review, Communication & Sport, Journal of Media, Culture, and Society, International Journal of Sport Marketing and Sponsorship, International Journal of Sport Communication, Sport Marketing Quarterly, International Journal of Sport Finance and Journal of Sport Media. (9/18/2024)

Episode Description

Paris hosted the most recent Olympic and Paralympic games. But, before these fade into memories what did you think of the coverage of the games? That’s what our guest Dr. Bo Li is talking about today and how these types of sports mega events are covered.

+Full Transcript

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John Bailer
Paris hosted the 2024 Summer Olympics and Paralympics games this year. Before these fade into memory, what was your reaction to the coverage of the games? Having Snoop Dogg as a commentator added a fun element to these games. But what does that mean for the branding of the games in sports? How did that impact audiences? This Stats and Stories episode will be a conversation about decisions by journalists covering major sporting events such as the Olympics, more and about how branding and sports digital media is evolving. I'm John Bailer. I'm joined by Rosemary Pennington, chair of the department of media, journalism and film. Stats and Stories is a production of Miami University's departments of statistics and media, journalism and film, as well as the American Statistical Association. Our guest today is Dr. Bo Li. Li is an associate professor in the Sports Leadership and Management Department at Miami University. He teaches sports administration, sports marketing and sports public relations. His research has been mainly focused on sports, digital media and branding, positioned at the intersection of digital media, mass media branding and consumer research. But prior to starting his career as a teacher and researcher, Li was a journalist who covered two Olympics, three World Men's World Cups, one Women's World Cup and three International World Swimming Championships. Wow, Bo. Thank you so much for being here today.

Bo Li
Thank you so much for having me, such an honor.

John Bailer
Well, can you tell us a little bit about how you got involved in sports journalism?

Bo Li
Yeah, definitely. You know, when I was a kid, being a sports journalist had always been my dream. So after I graduated from college, I went to Australia to study for my master degree. So after I finished my master's degree, I went back to China, and happened to be in 2007 so it's like when the 2008 Olympic Games was, so I always want to, like, cover the Olympic Games. They say, Oh, okay, I need to find a job in sports media. So I apply for multiple different jobs. And then I got into Tencent, which is the largest Internet in China at that time. So I had the honor to, you know, cover my first ever Olympic Games, which happened to be in Beijing, where the city I was living at that time. So it's kind of cool, like, cover major events like the Olympics.

Rosemary Pennington
What was it like for that to be your first foray into sports reporting and to have to, like, juggle so many different sports and so much data that comes with the reporting on those events?

Bo Li
Yeah, that's a very good question. It's like the current Olympic Games, and is very challenging compared to any other sports events that I covered before, because the Olympic Games are 16 days long. You've got so many different sports happening every single day. So before going to the Olympic Games, you do need to spend tons of time to prepare your work. So you have to understand, you know, a lot of sports that you're familiar with, a lot of sports. You possibly only watch it a few times in your life. So you do have to prepare a lot of this information before going to the game. So every single game, because each media only has limited numbers of media potentials, so they want you to cover as many things as possible, so right before the first day's event. So we need to have the meeting. So if, like, three of us have the media potential, we have spread the word. We say, hey, tomorrow, you know, I'm gonna cover swimming, because Michael Phelps will be swimming tomorrow, so we're likely to have some very good results for this athlete. So we will need to spread the word, and then we have to travel between different venues every single day, so you have to get that ready. So before that, we actually spent tons of time getting all this data to understand who'll be likely to have a really great performance tomorrow and what particular event. So what time do we have to be there? So everything has been calculated and made sure that we won't miss anything major. So that was very exciting. But also have to say this, 16 days, you usually get up very early because, like, shooting competitions are usually scheduled, like starting at six o'clock in the morning. So you basically have to go to the shooting venue at 5:30 in the morning. And to cover that, you know when this finishes, and then you tend to go to a different venue. It's just a lot of work, definitely, when you cover the Olympic Games.

John Bailer
It sounds like this mad combination of statistics and logistics, yeah. So, I'm sort of picturing you kind of pouring through the schedule for each day, right, and trying to imagine what's going to be the kind of stories that's going to have the biggest hook, yeah? So what are some of the things that might lead you to say, Oh, this is definitely where I need to be tomorrow.

Bo Li
So there are a lot of different things. And one thing is the top athletes. Everyone wants to target the top athletes like the 2008 Olympic Games. Like people want to know whether Michael Phelps can become the first ever swimmer to win eight gold medals. So every single day, what we're doing at that time was just, you know, going to the swimming pool to see whether Michael Phelps could continue winning the medals. And also, because Michael has tons of schedule, so at least usually, every time when they finish competition, they just talk to me there right away. So Michael Phelps is different at that time, so they have a press conference for him when the whole competition is over. So maybe he'll win three races that night. So you're not going to talk to him during the race, but you only get a chance to talk to him when the race is over, then he has his own press conferences. So this, obviously, top athletes are important, and also we want to see people who break the world records at the Olympic stages, right? So that's something we've been really focusing on, because that really triggers people's interest. People want to know, you know, who's actually the best athlete? Why are they the best? Because they set the new record, or what record that was the, you know, best accomplishment by any human being in that sport. So that really triggered people's interest, and also made our story become very appealing.

Rosemary Pennington
So in the Olympics, you might be covering, shooting, one hour. You might go to dressage. You might maybe do indoor cycling, maybe it's track, maybe it's gymnastics, all of these various sports have their own sets of data, right, that are important to understand the sport. How do you prepare to tell a story of, say, dressage, in a way that you know you can explain what these stats mean and how they're being judged to an audience? What I'm assuming, you are not going to be an expert on dressage.

Bo Li
Yeah, it's difficult. Is like for us, we only know certain sports. We only participate in certain sports, so we're not going to be understanding every sport very, very well, but having this statistic with you that makes you really understand the sports better, and also can help you develop a very good relationship with athletes. So for instance, when a competition is over, go to the mix zone, where the media is all getting together. Try to touch all these different athletes. The Olympic Games is like you go swimming with possibly 300-400 reporters all waiting at the mix zone. You know, when athletes finish that competition, they're gonna walk across the mix zone and try to talk to everyone. So there's no way they're able to talk to everyone, because that time is very limited. So they only talk to someone they believe they trust. How you are able to develop this relationship is if you ask them a very good question. So what would be a good question is you ask them and say, Hey, Michael, you just won a men's 200 meter butterfly in the last 50 you swim like this time. You know this is much faster than the previous. What's the strategy behind this? So when you ask questions like that, the swimmer will say, Well, this guy knows swimming, so I want to talk to him a little bit more, because he know my sport, he's not like random person who just assigned a job to come here to ask me some random question that has nothing to do with my sports, so they want to talk a little bit more about it. So I think they make us more professional, and then also help you develop a trust relationship between you and athletes. Athletes would prefer talking to you over other journalists which can help us to write better stories.

John Bailer
I hadn't really thought about this, sort of having this insight about the details about performance as being one of the ways of developing credibility, and also this connection with the athletes.

Bo Li
Yeah, you also find out there are many, like loyal fans, like they care about statistics, right? They're very sensitive about the time, right? You talk about this time, they know if there's a good time or not a good time. And so I think that is very important, because when you try to target audiences, you're going to target different audiences. Some audiences only care about the beautiful story behind the successful athletes, but a lot of them care about, you know, the statistics behind this performance, and they can let you know, you know, whether this athlete is very successful or not, you know. So a lot of time you do have to try to incorporate those statistics in order to target those readers.

John Bailer
So how do you weave in, kind of these statistical aspects of this incredible performance in the last 50 meters of a race, or other characteristics that you think is going to help bring in an audience?

Bo Li
Yeah, definitely. I’ll give an example, in 2012, when I covered the London Olympic Games. So the swimming competition was really dramatic at that time. So there was a Chinese swimmer. Yes, she won at 16 years old. She competed in the women's 400m, so she set the world record. So everyone said, oh, that's a great performance, because that's a record, right? Not just because she set the world record, her last 50 was even faster than Ryan Lodis 400m men's race. So that really shows how fast she swims. So when you're able to show that data to the readers and audience and they say, Oh, she's just incredible. That's an incredible performance for athletes. So that can really justify and enhance that accomplishment the athlete delivers and the competition.

Rosemary Pennington
Is there a particular story that came out of either the Beijing or London Olympics that you are particularly proud of reporting or how you wrote about it or shared it?

Bo Li
Yeah, there are definitely a lot of things we are really proud of, like, because I was covering the Olympics for Chinese media. So obviously the Chinese audience really cares about, you know, who's going to be the first athlete to win the gunmetals? So in China, they really care about first, you know, you win the first ever gold medal in the event, I'll win the first ever gold medal for the Chinese team. So that was a very important moment for Chinese athletes. So usually they have a schedule. We had a schedule like, Okay, who is going to win the first gold for China? This, this sport could be in diving, could be in shooting, it could be in some of the sports. So I went to the 2012 Olympic Games. So that was a shooting event, an event that was the first ever gold medal to be delivered. So I happened to be there in that event, and a Chinese athlete when they got a medal. So that was very big news in China at that time. And also the IOC President, Jack Logger, was also there in that event, because he had to deliver the medal to the winner. So, because the shooting venues are very small, when the venue was finished, everyone tried to, you know, talk to the IOC President. I was just very lucky. I got outside of the shooting venue and he would just like, in front of me. I was, oh, they couldn't find better. And then I was there, like, three or four reporters with their people were like, should I talk to him or not? I didn't even think about it. I just put my microphone there and say, Hey, President Jack, how do you think about a performance? What do you think about the Olympic Games? You know? What do you think about the opening ceremony last night? And, you know? So that we will be able to get first hand information, able to talk to these high profile officials and athletes, so that would make our story become very appealing, and people happy about that.

John Bailer
So in your coverage, were you doing video coverage, audio coverage, print coverage, I mean, sort of, the whole package?

Bo Li
Yeah. Like you can see the chain of the media has been changing the last few years, like, because I work for our website. So the website, at the very beginning, emphasizes more about writing articles, just a Latin newspaper, you know, taking photos, right? Like newspapers, but later and started to care more about video, right? I guess, because, you know, people just want to watch something, athletes talk, or something that really, can really help. People can just get, help us get more readerships, more clips on the website. So we have to do a lot of different things. So nowadays, particularly when you see sports journalism being changed, like journalists in the past may only ask you, okay, you just go there to write a story. So when we cover a tennis event, for instance, like if you work for a newspaper, right, you only need to be in the venue for three hours and then finish a story and submit it, right? But I think there was 2013 when we covered, you know, French opens. I've seen a lot of reports for the New York Times. They're gonna sit there for the entire day, because they're not just writing a story for the newspaper, but also writing for a website as well. So they have to sit there all day, maybe have to write, you know, six or seven stories. And so I think that really changed the expectation for audiences. Right, nowadays with social media becoming so popular, a lot of journalists try to develop that brand on social media, so you're not just using that platform to break news, to share your personal opinion, so people also want you to share your content. A lot of content might not be available on their media platform, but social media provides them with the platform where they can disseminate more information. So yeah, because they can only have, like, one hour interviews done with athletes, maybe only 30 minutes will be broadcasted. Also good question that you don't want to waste it and you possibly want to share it on your social media to target a certain audience.

John Bailer
So you've covered the Olympics and World Cups, yeah, and other kinds of events. What are the big differences when you think about covering the Olympics, which are very concentrated in space as well as time, and the World Cup, which has just seemingly years of qualifying and then, and then a very full month of competitions. What are some of the differences?

Bo Li
Very, very different. The World Cup is more relaxing.

Rosemary Pennington
Okay, because it's not relaxing to watch.

Bo Li
World Cup play, because World Cup matches have been hosted in multiple different cities, so you have a chance to travel, so you only cover one game, right? So you're gonna cover one game and pregame press conferences and when the game's finished, the second day you travel to a different city. So you got a chance to travel to many different cities, meet a lot of different people, and you have a very easy schedule, because you only need to work for four or five hours that day, but the Olympic Games is a very, totally different story, 16 days in a row. You basically don't expect yourself to have any break, right? Because I feel like when we watch the Olympic Games, there are a lot of exciting moments, but when your reporter is covering the game, you cannot really digest this exciting moment, just like athletes, like when they win the medal or it was, like, hard for them to really digest the moment of accomplishment. It only takes them, like, two days, three days or four days. Just realize, you know how great the performance was. The same when you cover the games, because, like, you cover swimming, these are five medals being delivered today, right? So all of great performance, you just have no time to really, you know, digest every single moment. But when you cover the FIFA World Cup, it is different. It's only one game, you know, you could really digest that moment and the great goal, and you'll be happy about it. You can watch the replay multiple times, but you just don't have the opportunity when you cover the Olympic Games.

John Bailer
You're listening to Stats and Stories. Our guest today is Bo Li. You know, it seems like your research now can continue elements of sports reporting. You know, although the reporting is now touching on how audiences respond to and interact with sports and with other fans. So, can you talk a little bit about, kind of, some of your interests now, as a researcher into sports?

Bo Li
Yes, speaking of my research, at the very beginning, my research was focusing on media, because I'm very familiar with the film, but also when I start really looking at how fans started to watch it, consume sports, and also realized there's a trend that social media, digital media, really change how we watch sport. Right? In the past, we just turned on the TV and watched it. But right now, you have streaming services like the past Olympic Games. I know a lot of people may subscribe to Peacock. You can watch any sport you like on Peacock, anytime, right? That's very convenient. And also, if you're not big Olympic fans, you can also just go to Twitter, or go to other social media platforms. You can watch the highlights. You can go to YouTube to watch the highlights. Interesting thing, like when I watch when we started in 2024, the Olympic Games, we find a lot of people go to YouTube to watch these, like highlight videos, that one minute, two minute video, but they consider that is a lie. So you see a lot of comments there. They say, hey, NBC, don't spoil the result. Just don't say who won the medals. We just want to pretend that we're watching live in this video. It's interesting to see how fans like watching sports. Like in the past, we prefer watching live right now. Like, you know, you got it very easily for you to get resolved, but people will still like to have that atmosphere. So you can also see the athletes and also the sports organization take social media and digital media very seriously. Because in the past, if any big news they wanted to break, they usually would go through the media, but right now, they have the power to control the information. So if you look at all these well known athletes in the last few years, when they announced retirement, right? So they will never talk to the media directly, right? In the past, they were just like, let's have a sit down interview, talk to the media. Let the media break this news. Now this is like, Okay, I found out a particular time I want to break this news to the entire world, let everyone know that I'm retired from the sport. So I think that's a big change, and it also made my research start to look at more about how they use things like this, digital media, social media, to develop their brand and control that information and also enhance the interaction between them and the followers and the fans.

Rosemary Pennington
It's interesting because, as you were saying that, I was thinking back on that, I think the last big sit down sports breaking news interview that I can remember is LeBron James saying he was leaving Cleveland, yeah, and going to the Lakers. And I don't remember since then. You know, as a Cavs fan, that was heartbreaking. But I can't remember another moment where an athlete did something like that with a journalist and I, and again, had not recognized that until you just now brought it up. I wonder, how else are our athletes using social media? Because, I mean, I'm now on Tiktok, and sometimes they show up in Tiktok in interesting ways. How are athletes sort of using that space? Are they? Is it about branding? Is it about connecting to fans?

Bo Li
That's a very good question, because one of the recent research projects that we're working on is to study the top 100 athletes at the Paralympic Games. How do they use different types of social media, including Twitter, including Instagram, and including tea talks and Facebook? And not surprised that not many of them are using Facebook, right? Because Facebook, it just takes longer for them to really create those contents. You cannot just create short content right now. On Facebook, you have groups, you passively need to write long things over there to create good videos in order to target audiences. So like a lot of athletes, you know, you find out interestingly when they're using Twitter, they're more likely to share their opinion, right? So I support these athletes, great performances. I've made a lot of comments on Twitter, but when they're using Instagram, they use more about branding, right? So I have sponsors. We just had a great, you know, TV interview with NBC. So for instance, I would like to share the same stories with my audiences on Instagram and to talk more about entertaining, right? So you look at some of us when she won the Olympic gold and she recorded multiple different very entertaining content that mainly shared it on Tiktok. Obviously the content has also been shared on Instagram, because of the Instagram story function, but you see, finding out a lot more content on Tiktok is very entertaining. Is spontaneous content they usually create. So you find out they're using social media very differently and strategically, and they understand, you know, what kind of thing the audience is looking for on this platform. So they started to create that content, particularly for that platform.

John Bailer
You know, in one of the papers that you shared with us before we chatted, you mentioned the magic bullet technology, yeah, and this idea that there is an over the top service that allows for the audience to be engaged with each other while they're also engaged with viewing this sport. Can you talk a little bit about that? And then what kind of questions were you trying to answer when you looked at these types of interactions?

Bo Li
Yeah, that's a very interesting one. So the bullet is very popular in China and Japan. So how this whole thing started was, like in Japan, there are many people watching animation at home. So when you watch animation at home, you should always feel lonely, right? So you want to have that communication with someone who's also have a similar interest. So that created that technology where people were able to share the comments and then you'll be able to interact with each other with the content. So now, more and more sports have been broadcasting live on streaming services we call over the top service, and then the same service, same technology has also been applied in these kinds of contents as well. So for instance, when we watch NBA games, so when we, three of us, watch NBA games, we might all be at home. We don't know each other at all, but we all have an interest in watching these games a lot of the time. We might have a lot of questions. So for instance, it's my first time watching this game. So there are a lot of players. I don't know if the Lakers will get a new player to play. I would say, Hey, who is this player? I've never seen him before, as someone like John, possibly pretty knowledgeable about it, John would just say, okay, these players, blah, blah, blah, provide some inside information about it. So like, when we're watching the game, we don't feel like we're alone. We feel like, Oh, we've got company from so many people together, right? So when, but when we look at these contents, some of them, a lot of them, there's a charge to talk, right? So I support a certain team. I hold this team lost. So they will come in a lot of these, right? Because of this comment, you won't be able to see the user's ID. So basically, give them bigger freedom. They're able to talk more about things they want on that platform. So I think that it is an interesting technology to definitely enhance the engagement. So like, for instance, that's the same game that is also available on TV, available on this platform. People will say, Oh, before watching from this platform, because I can talk with someone who is also watching this game. So I think that's a cool technology that we'd be able to do. It's actually interesting to study too.

Rosemary Pennington
It's interesting because during, you know, big sporting events, I am a terminally online person, and I'm, you know, I'm often, like, bouncing between, like Twitter and Reddit, sometimes they will have, like, live threads of sporting events to kind of see, because I love sports, and people in my house do not love sports, and so it's nice to be with people who are enjoying the sport too. And I am trying to imagine what that would be like to sort of experience that overlay of sort of being with these people as I'm watching the screen, having it all be on the screen together at the same time, and having to toggle back and forth.

Bo Li
Yeah, it's interesting. But also sometimes could be very frustrating, because you will see a lot of negative comments as well, right? Because you can see users ID, so they give them the freedom to have a lot of, like, worst chat talk over there. You know, maybe you're supporting one team and someone else really doesn't like the team, and you could have tons of trash talk over there that can really impact your experience watching that as well.

John Bailer
Yeah, you can build and destroy a community depending on the tone that you take. Yeah. So you also talked about, in another piece, that we were looking at the attitudes towards naturalized athletes competing for, you know, yeah, their home country, yeah, where the home country might be their parents, country of birth, or some other other connection, yeah. And I thought that it was interesting as you did. Part of this, you did a sentiment analysis and a thematic analysis of this kind of experience. Can you talk a little bit about some of the things that you did and some of the insights that maybe emerged from that?

Bo Li
Yeah, definitely. One of the studies during the 2022 winter Beijing Olympic Games was to study how Chinese audiences actually look at so many athletes. They were born and raised outside of China, but they have Chinese citizenship right before the Winter Olympic Games to compete for China, and how they react to that changes, because that's very uncommon in Asian countries. Because most of the Asian countries, including China, Japan, Korea, we barely have the athlete who were born race outside of the country and compete the country at the most important sports events in the world, at the Olympic Games, and also in 2022 Olympic Games happened to taking place in Beijing. So that means the attention of the Winter Games are much, much, much higher compared to previous winter games. So one example is Alin Gu who was born and raised in the United States when she was 15 years old, changed citizenship to China, competed for China and won three medals for China at the Olympic Games. So we'd like to see how people comment on this athlete, because it's very different, because in the past, you see only athletes that were born and raised in China speak foreign Chinese. Obviously, compete for China and talk about it, but now you're totally seeing a foreigner. But they also wear Chinese team jerseys and barely speak some Chinese, but compete for your country house. The people's reaction to it was interesting to study about this. But obviously every country is very, very different from the US, but you see very, very common efforts to change citizenship but compete for the United States. But in China, it's very different because we got only one nation, one nation, everyone should look the same so that they can represent China and compete. So it was interesting. You could see, when athletes win medals, they have great success. People recognize that, right? You met from a different country, but at this time, as you compete for China, you win a medal for China, that's the most important thing, but if the athlete did not have a very good performance. So people start a question of, why are we spending money to, you know, ask this athlete to change that nationality to compete for us? So because people will say, Well, we have our own athlete as well. When we use this athlete to compete, basically just jeopardize opportunity for our own athletes, right? It's not going to be good for the future. So a lot of debate on that as well. So actually, it's a very interesting study for us to look at.

Rosemary Pennington
I have one last question. I'm going to pull the John and ask the question, the last question before we wrap up, John mentioned this in the introduction to the episode, but talked about some sort of thing. Snoop Dogg was kind of everywhere at the Olympics, and then, you know, Leslie Jones has been sort of involved, officially, unofficially, for NBC, sort of commenting and social media. And then you had Flava Flav this Olympics, who was like, propping up a lot of women's sports. How important is it for celebrities to sort of be in that space to sort of, how do they impact the profile of particular sports, are they and are we going to see more of this moving forward and related to other sports, perhaps down the road?

Bo Li
Yeah, I think that's one very interesting thing about how you see the Olympic Games, because we conducted a study in the last three Olympic Games to see how the American audience sees the Olympic Games. What is the biggest motivation for you to watch the Olympic Games? Interestingly, entertainment is actually the number one motivation for American audiences to watch the Olympic Games. In the last three Olympic Games, right? In other countries they show different motivation, like China, patriotism the number one motivation. So when people think about the Olympic Games, it's like, a great festival for you know, 816 days we'll be able to watch so many different sports but you'll be able to, you know, feature so many celebrities. And in the Olympic Games, the coverage can really trigger people's interest, right? People, a lot of them. Maybe you never watched the sports before, but because celebrities come here and watch the game, have interaction with athletes, and suddenly people were just like, oh, this is interesting. I want to learn more about it, right? So I think we could see that happen again more often in the future, particularly in Olympic coverages or other sports coverages.

John Bailer
Well, I'm afraid that's all the time we have for this conversation today. Thank you so much for joining us today.

Bo Li
Yeah, thank you so much for the opportunity. And had also talked with you guys about sports and statistics.

John Bailer
Stats and Stories is a partnership between Miami University’s Departments of Statistics, and Media, Journalism and Film, and the American Statistical Association. You can follow us on Twitter, Apple podcasts, or other places you can find podcasts. If you’d like to share your thoughts on the program send your email to statsandstories@miamioh.edu or check us out at statsandstories.net, and be sure to listen for future editions of Stats and Stories, where we discuss the statistics behind the stories and the stories behind the statistics.

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