Effectively Wild: A FanGraphs Baseball Podcast - Effectively Wild Episode 1482: Multisport Sabermetrics Exchange (Diversity and Inclusion)

Episode Date: January 3, 2020

In the final (for now) installment of a special, seven-episode series on the past, present, and future of advanced analysis in non-baseball sports, Ben Lindbergh talks to sabermetric pioneer Sherri Nichols about her trailblazing work in baseball analysis and then data scientist and sports entrepreneur Tiffany Kelly (41:02) about her experience in the sports analytics […]

You've got your lights turned so they can see it The very best of what you've got to offer Tell them what your hands were made for Tell them who your mouth was made for You've got your prophets and your mathematicians The vocal fuel of a generation. Tell me what my hands were made for. Tell me who my mouth was made for.

Hello and welcome to episode 1482 of Effectively Wild, a baseball podcast from FanCrafts presented by our Patreon supporters. I am Ben Lindberg of The Ringer, and you are listening to the final installment of our seven-part multi-sport sabermetrics exchange series in which we have provided a primer on the past, present, and future of advanced analytics in a dozen different non-baseball sports. If you're just joining us now, we've talked about American football, Thanks for watching. Over the course of these interviews, I've definitely learned a lot and I've enjoyed talking to people from each of these fields. We've had a lot of great guests.

But one thing you may also have noticed is that we've had a lot of white guy guests. And that's something that's historically tended to be true about the sports analytics industry in general. If you delve into the history of sabermetrics and other sports analytical movements, as we have with some of their longstanding proponents in this series, As we have with some of their longstanding proponents in this series, you notice that it has not tended to be a very diverse group of researchers and writers and analysts. And fortunately, that's changing. And on previous episodes of the podcast, we've talked to some of the women who are working in MLB front offices today in R&D roles. That's becoming more common belatedly. But today, I wanted to explore some of the reasons why, historically speaking, women and people of color have been underrepresented in research and development departments inside sports teams, and also in analytically oriented roles in sports media, in addition to sports media more broadly, and to try to talk about some of the ways that might change some of the people who are trying to change it, and why it's so important to change it. Later in the episode, I'll be talking to Tiffany Kelly about her experience in the sports analytics field. But before I bring on Tiffany, I have another guest lined up. And unlike a lot of the segments in this series, this one will really be about baseball because my first guest was intimately involved in the origins of the

sabermetrics-infused landscape we enjoy or mostly enjoy today. I am joined now by Sherry Nichols, who is one of the formative figures in sabermetrics in baseball. And I had the pleasure of talking to her and telling her story at The Ringer early in 2018. And I am overdue to have her on the podcast to tell her story herself. So hi, Sherry. Hi, Ben. So tell me a little bit about your childhood and growing up in Clarksville, Tennessee, which I think you told me was about equidistant from Atlanta and St. Louis and Cincinnati. So you had your choice of major league teams.

You grew up as a baseball lover. So how did that come to be? I don't really remember not being a baseball fan. My dad's a baseball fan. So just always baseball was always around. I remember, you know, as a kid, you know, I'm old enough that we had recess more often than we had PE in school, and I remember playing baseball with all the boys when I was in like, you know, first and second grade. And I remember being very upset when I found out that I couldn't play Little League. You know, all the boys were going to go play Little League,

and I was told I couldn't because I was a girl, and I didn't understand that. But that was when Little League didn't allow girls. So I grew up in Clarksville. This was in the 70s. So the big red machine was going along. We would listen to Reds games on the radio. There weren't as many games televised back then. We'd get Reds games and Braves games on the radio. The Braves weren't as good, of course, so my brother and I became more Reds fans, and we would occasionally make trips up to Cincinnati to see games. We did that a few times.

And were you interested in the statistical side of baseball at that early age, or did that not come until later? Well, my brother, of course, played Little League, and so he was a couple of years younger. When he started playing Little League one day, his coach came over with a scorebook and needed someone to score games for the team. And he handed the scorebook to me and games and eventually, you know, made spending money scoring as working as a scorekeeper for the league. So I did that in my teens and that was fun. So that's sort of how I got into statistics in that sense and baseball. I was always interested in math. It's always good math. So I was always good in math,

so it was sort of a natural fit. And did that experience of keeping score make you think about what's valuable in baseball games in any unorthodox way? Or at that time, were you just thinking, yeah, batting average and RBI, that's all we need? I don't think it really made me think about it. It was just, yeah, it was more fun than babysitting for picking up spending money.

And I guess at that time, I mean, there wasn that brought you back to baseball in an even deeper way. But were you aware before you found the online community while you were at Carnegie Mellon that anyone had really done any baseball analysis and research of a statistical nature? When I was in college, I remember that was when the Sports Illustrated article about Bill James came out. So, I mean, I had read that and thought, oh, that's interesting. He's really thinking about it in a different way. Yeah, I was drawn to that, but I didn't know anybody doing that kind of work. And I was in college at the time. So you had gotten your degree in physics at Tennessee Tech, and then you went to study computer science.

So how did that lead you to baseball? Well, I went up to Pittsburgh pretty early on, met David, who eventually became my husband. And he was also a baseball fan, and I'd always been a baseball fan. And there was a community within the CS department who were all baseball fans. And we found the abstract, the Bill James Baseball abstract, and read it and learned about Project Scoresheet and got involved with that. And then started going to Sabre conventions. Then I got involved on RecSport Baseball, the Usenet group.

And everything just sort of flowed out of all of those various things. I met all these people and, you know, sort of meshed a lot of interests. I was interested in baseball. I think analytically anyway, computer programmer. I like to write, so Rick Sport Baseball was an interesting outlet for all of that. And was it very heartening to discover this like-minded community of people who were looking at baseball in a different way? And were your eyes opened by that community? I mean, I know that you opened eyes in that community too. Yeah, it was a lot of fun. Gary Huckabee was entertaining. He really sort of set a tone on

there. And it was just a fun place to hang out. I met a number of people on that community in person and just had a lot of fun. And the project was a lot of work and a lot of fun, met a number of people on that community in person and just had a lot of fun. And, you know, the project was a lot of work and a lot of fun, met a lot of interesting people. Sabre conventions were a lot of fun. Made friends there that, you know, I'm still really good friends with, like David Smith and Tom Tippett. Just, it was a cool time. Yeah. So Gary Huckabee, of course, one of the founders of Baseball Prospectus and many of the other eventual founders of BP were also on Rexport Baseball at the time. And for people who were not around and haven't read about all this, Usenet was essentially like a precursor to Reddit, but in the 80s. And it was, you know, forums or bulletin boards and all of it is archived now at Google Groups. So you can actually go back and read all of the Rex Ward baseball

posts from the 80s, which is entertaining. I do that sometimes. But you became kind of one of the leading lights in that community from the people that I spoke to and remembered fondly reading what you wrote about at that time. And do you remember, I mean, what sort of topics animated you or what kind of research was most interesting to you at the time? Just sort of taking a whole analytical approach and sort of looking at, you know, what do we really know and how can we look at things, you know, if this is true, then what would be, what would it look like is sort of the way I think about it. So if it is true that, you know, sacrifice months are important, then what would be the result of that?

And if you don't see the result, then maybe those aren't as important, you know, and so you start looking at it from that approach, then you can sort of start backing out and going, okay, what really does matter? And you can, you know, you start learning that getting on base is important. Outs are really bad. Errors bad errors yeah they're just another way that outs aren't made yeah yeah just sort of looking at at the results and backing down to the yeah it's like if this is true then what must be true as a result and if you don't see the result, then that's not true. Right. And this was obviously before all of this started to actually bleed into the game and before Internet analysts started to sort of a snarky tone to it, which I think was appropriate because, you know, it was sort of this outsider voice that no one was listening to. And if they were listening, they were making fun of it. So I guess you had to sort of fight fire with fire.

Yeah, I mean, baseball for respect definitely had a snarky tone. Rec sport baseball had a snarky tone. You know, we were definitely outsiders. I mean, Bill James was an outsider back then. He, you know, he started Project Score Sheet because he couldn't get the data. I mean, you know, there was no other way to get the data but to collect it yourself. And I think that's one of the things that people today don't realize is that there was no data we had to collect you know there was you know i talked to i went to cardi mullen last

year to the sports analytics conference and i'm talking to the to them and it's like i had to step back and realize that they don't understand that there was no data to scrape off the internet there was barely an internet yeah i mean it was uh difficult to impossible to answer even the most basic questions i mean you you know you couldn't even look up how someone had hit i mean you have to lug around a baseball encyclopedia or something and and even that had just the most basic stats and and mlb and and the elias sports bureau at the time was very protective of of the data that it had so that they wouldn't share anything yes they wouldn't share no elias wouldn't share anything that's that's why bill started the project was elias wouldn't share

so yeah i mean it's really crazy that the project worked as well as it did i mean it's all volunteer organization trying to score every single game as it happens yeah it's ridiculous and it sort of worked for a number of years. Yeah. So that was, what, 84 or so, I think it started, maybe? Yeah. And yeah, so how were, I mean, I know that you weren't giving out the assignments, I guess, at that time, but how generally was it organized and what was the process of scoring a game like? Well, there were team captains in each major league city, then volunteers, and the team captains would try to assign games to everybody and pick up any games that weren't covered. And so people were scoring games both in the park and off of TV. And, you know, a lot of times at the end of the season, you know, trying to catch up on games that were missed

and recorded on VHS back in the day, you know, as we're trying to get all the games covered. It's amazing that it worked as well as it did. I mean, you just had some people who were doing it as a labor of love, and a few people were doing a lot of work, and a number of people were doing a little bit of work, like it is in any organization. And it sort of worked for a number of years. And what data was recorded? Because you were able to do some of your later defensive work because the trajectories of balls were recorded with some

precision. So how granular was it? Initially, it was just play-by-play data. Eventually, we started recording pitch-by-pitch and hit location. So it wasn't really trajectory, but each score recorded where the ball landed or was fielded. It wasn't perfect, but it was an idea of where the ball was. Nothing like you have today with StatCast. So that was the last few years of it. We had hit location. And once we had hit location, then you could start doing stuff with defensive data

you could start looking at that's when it became possible to do defensive average so the the field was divided into locations we just sort of arbitrarily divided it into a grid more or less and each hit was assigned to a each batted ball was put in a grid and then pete de courcy and i were talking about defensive average we sort of assigned each fielder an area of the field and looked at how many balls were hit into that area and how many balls they actually successfully turned into outs and computed defensive average. Right. And that is the same basic framework that many of the subsequent defensive stats used and continue to use, something like ultimate zone rating, for instance. And as i discovered as i was working on this article there's a direct lineage there to one of the defensive systems that is part of the input for the gold clubs now the the saber

defensive index that stat essentially just borrowed the design that you had come up with for defensive average so essentially the work that you were doing back in the late 80s is now indirectly or fairly directly reflected in who actually wins a Gold Glove Award, which is pretty amazing because I'd imagine at the time you probably exposed some players who were very much not deserving of Gold Gloves who were winning them and players who should have been winning them who were not.

Yeah, there were definitely differences between what perception and defensive average showed as what defensive average showed as reality. Anyway, I don't want to say what reality is because, you know, who knows. But yeah, there were definitely some striking differences differences because you know back then it was all about fielding percentage I mean that was basically what decided gold gloves back then was fielding percentage so it was all about errors and if I had my way we wouldn't even charge errors because I don't think errors tell us anything. It's just a play not made. Yeah. And do you remember any misconceptions that you helped overturn or that were sort of, I guess, the things that people at Rexport Baseball, whether it was defense or otherwise, things that were frequent subjects of of debate or maybe when you came up with defensive average you had some insights about the nature of defense or or certain players who people were surprised or you were surprised to

to find were more valuable or less valuable than generally believed well yeah the one the one that was most memorable was uh carney lansford who uh had a reputation of being a good defender because he was always diving for balls and all that. But he was diving for balls because he couldn't move. He had no range. So the defensive average showed that he had no range. So if he could get to it, he was good at fielding it, but he couldn't get to much.

Yeah, and if i look up his baseball reference page right now he has a negative 46 fielding runs so that that holds up total zone says the same thing that defensive average did so what was the process of calculating that stat because you'd get the the project score sheet data so all of these what would it be input via computer and then collated somehow and yeah how did you get from that to the output well there was all the games were input into a computer there were actually a library of programs for processing the data that dav and Tom Tippett had written. So, I mean, there was already some code for getting the data into a usable shape.

And I wrote C code to just take the data, pull out what I needed, and calculate from there. So, yeah, it wasn't as easy as just, you know, pulling data and putting it into a spreadsheet, but the project score sheet data was in a regular fashion. It, you know, it was play-by-play data, but there was a library of code that had the engine for pulling out the play-by-play data out of it in a reasonable fashion. I can't remember the exact details of everything now because it's been 30 years since I wrote that code, but yeah. So as you're going through the physics program and then the computer science program and then you're on rec sport baseball, what did the demographics of these groups typically

look like? And were you often the only woman or one of the very few uh yes uh often the only or very few my physics program in undergraduate was a little unusual there actually were a fair i mean it was a small program and it just happened that there were several women in it and graduate school when i entered i entered in 1984 and it was about 20 i want to say 25 percent women in my class which was i think sort of around the peak things sort of went downhill from there a little bit but it was mostly i mean you know the women were all graduate students there were only two women professors and one of them was a first year professor so i mean you didn't have a lot of role models right our mentors on rec sport

baseball there weren't very many women and there certainly weren't very many women as active and vocal as I was. There were some women in Sabre in the project. Again, not many women as active and vocal as I was. And was Rexport Baseball generally a welcoming community or was there resentment or bias or disparagement that would crop up from time to time? Definitely disparagement would crop up from time to time. But there was generally a group that kept it from getting out of hand. I mean, there were a strong group of men on there who just didn't let that, who would stand up and not let that go, like Gary and some others.

And was that under-representation either there or in the classes that you were taking, was that daunting to you, discouraging, or was it a challenge that you wanted to embrace? It was just like the air around me. I mean, it was what I had always been around. So I didn't really think about it that much then. I'm more aware of it now in a sense and I can see the impact of it more now looking back than I could then. It was just the way it was. I remember feeling it and being annoyed by it, but thinking, well, okay, at least I'll make it better for the people coming after me. And what's frustrating to me now is I'm not sure how much we did make it better for the people coming after us. Yeah, do you have theories about why it hasn't changed more quickly or, I guess, ideas about how it could?

Definitely have ideas about how it could. I don't know why. Well, in tech anyway, I mean, I think if tech did more than just pay lip service to the idea of diversity, they could make it happen. I think if they treated it like a problem, like they treat any other problem, they would change the way they do things. But they keep doing things the same way, expecting different results. They keep talking about the pipeline, and the problem is not the pipeline. The problem is that women come into tech and they leave because it's not an environment that women want to stay in. Yeah, I think you told me when we spoke for the article, you said, I know how hard it is to be in a field where there's nobody like you. It's a constant, subtle message that maybe you don't belong,

that when you screw up, maybe it's more than just a mistake, which I guess is what you were alluding to as something that maybe you've realized almost in retrospect, more so than at the time. Yeah. So at that time, it really wasn't even an option to do stats for a baseball team. There were just a vanishingly small number of people doing that. So it wasn't something that you strongly considered as a career because it didn't seem like it could become one for anyone.

considered as a career because it didn't seem like it could become one for anyone. But you did have one close call or I guess one encounter with a major league team, which I thought was a great story while you were at Carnegie Mellon. So I will ask you to retell it for our audience. Yeah. So at one point, Carnegie Mellon had a small ownership stake in the Pirates. It was at one point when the Pirates were going to leave Pittsburgh and some group bought them and Carnegie Mellon had a small ownership stake. And so the GM at the time had some idea and wanted some people to come do some work for them to convince his field manager, who was Jim Leland at the time.

And so, you know, we got some VP at Carnegie Mellon, and it trickled down to David and I and a friend of ours who's also a baseball fan. And so we went and had a meeting with the GM, who was, I think, Larry Doty at the time. So we had a meeting with him, and I can't even remember what his idea was. It didn't make any sense. But he was convinced that he was right, and he just needed proof that he could beat Leland over the head with to convince him that this was right. And it was also clear that if we came up with data that didn't match his conclusion that

we would be worthless and and it was also clear that they weren't interested in you know paying us anything anything at all much less anything commensurance with the amount of work but we got a uh a meeting at the pirates and dinner in the in the press box then got to watch the game for a few innings from this is in three rivers and there was a right behind home plate there was a little window underneath the stands a little area underneath the stands behind home plate with a little window and that's where the grounds crew hung out and so we got to go down there and the grounds crew was really not very comfortable with me being down there because i was a woman and then they couldn't curse so then at one point jim got his picture for the pirates who was on the dl of time comes bouncing in there cursing up a storm and the grand secouz all going no no no stop stop there's a woman my other favorite uh pirates story is later when several years later when i was doing some stuff

with retro when i was on the board of the retro sheetet. And this was after I had moved away from Pittsburgh. But I was back in Pittsburgh for a Sabre meeting. And David Smith and I had a meeting with the pirates to talk with them about some pirate score sheets. And so we were meeting with this guy who's barely worked, who's new with the pirates, and he's like their PR person. And so we're meeting withates, and he's like their PR person. And so we're meeting with him, and he's like, I don't know.

The score sheets probably got lost in the move from Forbes Field to Three Rivers. I don't know where they would be. The only person who might know retired. So it's clear he doesn't know anything. So I'm sitting there and I'm bored because this guy knows nothing and is worthless. And so I'm just looking around his office because I'm bored. And I see these books, a bookcase on the lower shelf

and I'm going, those are interesting. Those look like they could be score sheets. So I was like, what are those? He goes, I don't know. And he goes and looks over through the score sheets. So he didn't know where they were, but I found them. And RetroSheet, we've had David Smith on the podcast to talk about the origins of RetroSheet. But you were the first vice president and treasurer of RetroSheet.

And you kept on in that capacity until 2003. And you kept on in that capacity until 2003. And you made what may have been your greatest contribution to Sabermetrics by insisting that everything RetroSheet do be free forever. And so that's why we have all of this great data available to us. So how did you come to be involved with RetroSheet? I guess it was a natural extension of Project Scoresheet, but how did you decide you wanted to take on a leadership role there? And then how did it come up that you wanted that to be the position of the organization? project so he had this crazy idea about retrofit and you know it sounded great having play-by-play data going back into the past would be marvelous and so he's forming this organization and once asked for david or i1 to serve on the board and so david and i discussed it, and I decided that he had served on the project board at the end, so I stepped up to serve on the retro board. And so then we were discussing, we had all been involved to some degree with Project Scoresheet, and seeing how trying to, there were people who were trying to make a career out of Project Score Sheet, especially at the end.

And trying to sell the data and people trying to have a volunteer organization with people who wanted to make a living doing this had created a lot of problems. And it was clear that to do RetroSheet was going to require a lot of volunteer time. It was also clear that the data did have some value. We could sell the data, but probably not enough to compensate everybody for the amount of time. And it was fortunate that, you know, David Smith wasn't interested in trying to make a living out of baseball. He was a tenured professor at the University of Delaware. I wasn't interested in trying to make a living out of baseball. I already at the time had a job. You know, the main people involved weren't trying to leverage this into a living in baseball.

And so I said, let's not try to sell the data. That just complicates our lives. It makes everybody unhappy. Let's give the data away, ask for credit. And if when we need money to run the organization, we'll ask for it. And that made it much easier to get score sheets from the major league teams because the major league teams didn't think those score sheets were valuable, but they don't like the idea of somebody making money off of their stuff.

I mean, now I think they understand the value of them. Back then, they didn't think they were valuable. It made it easy to get score sheets from retired sports writers, made it easier to do work with the Hall of Fame because we weren't trying to make money off of it. And so, you know, you look at what's come out of that, all the people who've been able to do stuff because the retro data is free. It's just incredible. Yes. Yeah, I'm grateful for that. I'm sure many people are grateful for that.

It's made so much of what this whole community has done in the past two decades possible. decades possible so it would have been i guess sad if if retro sheet had uh turned into the elias sports bureau and uh yeah walled off its its data too so i should also i think ask you about the aphorism the saying that bears your name because that is what uh originally you let me to you because i i kept reading about the Nichols Law of Catcher Defense and after I'd seen it enough times I started wondering who's Nichols and in fact I saw it just last month in the transaction analysis

at Fangrass when Yasmany Grundahl signed with the White Sox the Nichols Law of Catcher Defense was cited granted by Dan Simborski who was on Rexport Baseball back in the day. But it still shows up. So tell us about the Nichols Law.

Yeah, I never would have dreamed that it would still be being cited all these years later and in so many disparate contexts. So this was back in the 80s, I guess. This was back in the 80s, I guess. I had seen Mickey Tettleton play for the Oakland A's, where he had been a no-hit good defense catcher, or that had been the perception of him. And then I'd seen him sign with the Orioles, and suddenly he was hitting.

And he's a slugger catcher. And now I'm reading that, that well he's a good hitter but he's not a very good defensive catcher and i'm going wait a minute this is the same guy i had seen him play in oakland and i've been reading about how he was a good defensive catcher even though he couldn't hit i'm going what's the deal here? And as I thought more about it, I'm going, okay, I see this pattern here that, you know, we have no idea how to, especially back then, we have no idea who's a good defense. You know, we have no idea how to measure catcher defense.

Nobody really knows. And so there seemed to be this assumption that if a catcher couldn't hit, he must be good defensively because else why would he be on the team? But if he could hit, it's probably not very good defensive, unless you're Johnny Bench. If you're Johnny Bench, then you can do everything. So that's how I came up with Nichols' Law of Catcher Defense,

that a catcher's defensive prowess is inversely proportional to his offensive prowess. Yeah, I think that perception probably still exists to some extent. Now that we have better stats for catchers and can quantify defense much more accurately, I guess it's harder to have that misconception. But still, I think there's some inclination to that. So I think that probably accounts for why that saying still pops up after 20 years or more. So I also wanted to ask, so when I spoke to Gary Huckabee,

you know, he complimented you and what an impression you made on him at the time. And in the very first forwards to a baseball prospectus Annual in 1996. He thanked you immediately after the other BP co-founders who had helped him write the book. And he wrote, Sherry has taught me more about baseball than anyone else in the entire world. So it is certainly possible that Baseball Prospectus would not have existed or existed in the way that it did if you had not made that impression on Gary. But did you consider writing about baseball, pursuing some sort of career in baseball? You eventually went on to work on software at Adobe, but was there any temptation to stay in that sabermetrics world? Not really. By the time Gary did Baseball Prospectus, my daughter had been born. I was

really starting to fade out of baseball at that point. I did some writing for, you know, the project did the Great American Baseball Statbook. I did some writing for that. I never really was that strongly tempted to try to do anything professionally baseball related money was too good in software yeah well can you explain the major addition you you made to software too because that's a another thing that i know has been sort of brought up again after some passage of time and and appreciated for the impact that it made. So after I left graduate school, I dropped out of graduate school, dropped out of a PhD program. I went to work on campus at Carnegie Mellon at the Information Technology Center, which was a joint Carnegie Mellon-IBM project to sort of build the campus computing environment of the future.

project to sort of build the campus computing environment of the future and the thing i worked on was the andrew file system which was a uh distributive file system so this is back in the 80s so this is i mean one of the things ibm did was wire the entire campus for internet so this was you know this is before wi-fi this is you know this was unusual, you know, this is before Wi-Fi. This is, you know, this was unusual that, you know, all the dorm rooms, everything was on the internet. And so we built a file system so that you could walk up to any computer on campus and log in and see your files. So things like Dropbox today, where the Dropbox founder cites the Andrew file system as one of his influences. So we built that back in the 80s when this was just unheard of, and wrote a paper about it that was in one of the big operating systems journals. And just a couple of years ago, we won an ACM award,

the Software Systems Award for Influential Software Systems. So that was pretty cool. Yeah. So as you've kind of, I guess, drifted a little bit back into the baseball world over the last couple of years, just through articles and speaking at CMU and making the cover of the Carnegie Mellon magazine. Have you dabbled at all into the current state of sabermetrics and StatCast and all of that? If anything, it must just inspire envy of the people working with that now, as opposed to what you had to work with 30 years ago.

Yeah, a little bit of indie. I haven't really gotten into it. I'm pretty busy with stuff I'm doing now. But it's pretty cool. I look at all the defensive shifts and go, well, defensive average doesn't really fit anymore. All these shifts break it. Yes. That's true.

Yeah. The systems are trying to account for that now. So Project Scoresheet would have had to record the starting position of all the fielders too. Yeah. And have you made any connections because of this? Have you talked to any maybe young women who are trying to get into the field now who've heard your story? who I hadn't connected with in a long time, and Keith Wollner. Keith Wollner came to Carnegie Mellon, talked to him in ages. But it's interesting.

A friend of mine worked on AFS with me on the Andrew Files system. His daughter found out I was having dinner with him, and his daughter found out that he was having dinner with me, and she had read the Rear article, and she's a sports fan. She's going, you're having dinner with Sherry Nichols which is just strange well it's uh it's nice that that the stories come to the attention of some people and I know just from having worked on it that when I was speaking to some of the women who are working in front offices today and they weren't aware of it, I think they thought it was somewhat inspirational to know that that had through the gold glove voting, for instance. That was something I was happy to turn up. No, I had no idea about that. And yeah, you talked to some people who are in front offices today who had read me on

Rexford Baseball that I had no idea about. It's like, wow. Yeah, you've got to be careful what you write on the internet. It's out there forever. That's right. All right. Indeed. Well, I'm glad we could have this conversation.

And I know you are very busy now with your work with the ACLU and powerlifting and all the things that are keeping you busy. But you made a huge contribution to baseball analysis that I think is continuing to have an impact. So thank you for that. And thanks again for your time. Thank you, Ben. All right, let's take a quick break and we'll be right back with Tiffany Kelly to talk about her experience breaking into the sports analytics field.

So I'm joined now by Tiffany Kelly, a sports entrepreneur and data scientist who studied sports analytics in school and then went on to work as an analytics consultant for the Miami Heat and then joined ESPN as a sports analytics associate, where she was the first woman of color on ESPN's sports analytics team. She has also written for The Undefeated and she's involved in many other projects, which maybe we will touch on. Tiffany, welcome. Thanks so much for having me. Yeah, happy to. So give me your backstory. Tell me how you decided that you wanted to become involved in sports and then how you set about acquiring the skills to get involved in sports analytics? Yeah. So sports is definitely kind of this way for my family to bond growing up. So I knew that I wanted to work in sports.

I just didn't know what capacity yet whenever I was in high school and growing up. And so we had this thing, it was career day where we job shadowed people that we eventually wanted to become my senior year of high school. And so one of my friends actually was connected with the PR staff at the Hornets at the time, not the Pelicans, down in New Orleans. So I signed up to job shadow for two game nights, the public relations team. But like that entire night kind of changed the entire trajectory of my career because it was the PR staff was super busy that night. So because Will Ferrell was there. So makes total sense. So they stuck me with the

stats guys. And they're like, Hey, hang out with them for a while. And we'll come back and get you. But during I think it was three quarters that they stuck me with them, I just started noticing that, I mean, their job was so cool. They were running the stats to personnel. They were inputting it into the NBA.com website after every quarter. And they stayed for press conferences at the end of the game as well. And the coolest thing was during halftime. So we were handing out stat sheets to Monty Williams, who was a coach at the time, and to the front office staff. So we were handing out stat sheets to Monty Williams, who was a coach at the time, and to the front office staff. So I actually poked my head and I peeked my head into the president's suite because they were delivering stats to the president's suite. So it was kind of like this golden ticket moment, like, oh my God, these guys are awesome. They literally,

they talked to everyone in the front office and just, not even just the front office, marketing, public relations, everyone, right? Like everyone knew them. So I was just like, this is what I want to do with my life, right? As like a 17 year old. So when you described this in your undefeated article, you said they look tired and they were manually inputting stats until 1am with an empty potato chip bag which sounds so glamorous you just gotta get in on that no they were so and that's what's so funny because they were kind of put in this makeshift closet like act like an office kind of thing so i was just like oh okay and i had to leave because it was a school night so i didn't even stay for the press conference but you definitely kind of got to notice that what they were doing, you come super early game day, and you stay 2am, 3am, depending on how late the game is. And so, but besides that, I didn't just I didn't just fully focus on every job has its its tough points. But I just, as a 17 year old senior in high school,

I just was super intrigued just that they got to go everywhere within the entire arena. So I just was focused on that. I was like, this is amazing. Yeah. So then how did you decide how to get to that exalted position in the closet? Yeah. So I knew that I wanted to do it. So I made sure that my, what I focused on in college just kind of fully surrounded that, but aha, there were not sports analytics degrees. Right.

So I had to kind of create my own. So I went to Nova South Eastern university down in Fort Lauderdale, which is actually where the dolphins train. But they're, they're moving to the hard rock stadium. I think they moved, they're either moving next year or they moved this year. So I went to school there and my degree was actually my bachelor's is officially in sports management, but I added a computer science and statistics minor.

So I was kind of like basically creating my own sports analytics degree because I knew that I needed the statistical foundations, the mathematical modeling, and then I also needed to know how to program those models as well, right? But I also wanted to have the sports management background. Like I wanted to just understand how to run a team and just things that matter, salary cap, like finances, all that good stuff that you cover within sports management. I also knew that I needed that. So I kind of just created this melting pot of information that I noticed when I was young that would kind of embed me and get me into the career.

And did you have any mentors in that process or were there people in your family or your community who had done something similar or were you sort in your family or your community who had done something similar or were you sort of just blazing your own trail? Great question. I actually, my statistics professor was my mentor. So funny enough, I actually thought my stats classes were going to kind of be boring. That's what everyone tells you. But first day he starts talking about sports examples And I was just like, Oh, okay,

I'm definitely gonna like this class. And so, so right, so like hypothesis testing, all that good stuff, every single example, majority of them use sports. And that kind of just started our relationship. And yeah, so my statistics professor, Dr. Gershman down in Florida, he was kind of the main mentor that I had growing up to even where I was also an honor student at my college. So we got to kind of either take honors classes or do a thesis, which, of course, I took the thesis route. So we had a lot of one on one classes where it's literally just me and him scripting in our my thesis project, which was on the, it was on the triangle offense, which was really interesting. But, but yeah, so that I would say he was my mentor growing up.

And so as you were going through this program, were you very much in the minority? I mean, was this a male oriented, white oriented kind of class, I guess, at the time? oriented white oriented kind of class i guess at the time a hundred percent so i in all of my computer science classes like programming so javascript c++ i was definitely the only like minority when it comes to being an ethnicity for sure there were three other gender minorities so there were three other women within the classes, but then those programming classes, database statistics, not so much because you, those are more of the, I don't, I want to say flagship.

Those are more of the courses that a larger audience took, but yeah, it's definitely been a reoccurring theme my entire life. I mean, also just, I went to a predominantly white high school growing up in the South as well. It's, it's, it's an amazing high school. It's one of the best high schools. We have a blue ribbon school of excellence for four years, which I think is a cap, but yeah, so that's, that's kind of just been a norm for me. Yeah. So, I mean, it's daunting for anyone to try to break into the sports world or sports analytics, but that maybe adds an extra challenge where, you know, when I'm trying to get into this line of work and I'm thinking, gee, maybe I want to try to do something with sabermetrics.

I didn't have to wonder, have any white guys ever done anything with sabermetrics? sabermetrics. And so was that something that weighed on you as you were going through this process that there were few people that you could point to to say, yes, someone who looks like me has done this and succeeded? Yeah, no. So my parents are amazing because they raised me to understand, obviously, just history, but they also raised me to not focus on it so much. So to kind of, I don't want to say be in the middle area, but just to balance. Like if something does happen to me that does feel racially motivated or of prejudice, then understanding that that's what that is. But also not just being so obsessed with it. Like,'s what that is, but also not just being so obsessed with it. Like, oh my God, is this going to happen to me everywhere that

I walk? But so kind of growing up and being raised with that mentality, going back to that night in New Orleans, working with the stats guys and the PR staff, it is something that I noticed. So I, first thing I guess I noticed more so was gender diversity, how a lot of the women kind of all had, I don't want to say similar roles, but they all kind of fit a certain mold, whether they kind of worked within marketing or PR, or they were in front of the camera. And it wasn't until I got moved with the stats guys that I was the only woman. And I mean, Monty Williams was a person of color, but I was definitely the only woman of color maneuvering around the hallways within the arena

and near the locker rooms and actually like poking my head in the president's suite. So that's when it definitely dawned on me that I was just like, ooh. But it didn't dawn on me in a negative way. It dawned on me like, oh, like, why is this like this? I definitely want to figure out a way to change this. And on the way back home to Baton Rouge, it was like a 45-minute drive with my dad.

I, like, mentioned it to him. And he was just like, okay, like, what are you going to do about it? And I was just like, you know, I'm going to work in a front office. And I'm going to change that and front office and I'm going to, I'm going to change that and, and kind of figure out what's, what's going on. So yeah, I, I noticed it early on, but I think that's because I was raised that way. And how did you end up at ESPN and what sort of work did you do there? Yes. So I went a year, which actually kind of goes into what we're talking about. I went a year without being hired. So when I finished up my degree at Nova, I was actually interviewing

with an NFL team for six months, which didn't end up happening because one of their top personnel left last minute. So they had to kind of halt the position. And they're just like, Hey, Tiff, like, you're amazing. We're gonna hire you. But this happened. We can kind of connect you to people that we know, because we know you want to work in the NBA. That was actually really funny. Because like an NFL team is like, we know you want to work in the NBA. So we'll connect you with someone up at the league office can kind of get you going. And so that's what they

did. I honestly think I interviewed with about five to 10 NBA teams within a year. And I know that seems so small, but obviously there's not that many. There's a handful. So it was just super tough. And interviewing for an entire year, it's, I mean, it kind of dawned on me, like this is not going to be easy. And not that I thought that it would but i think interviewing for a full year and also understanding like i was kind of the only i don't say only but one of the main um women of color like doing sports analytics that also was in the back of my mind yeah were

there moments where i mean you don't always know, why a team says no or doesn't respond. But were there moments where you thought that it might be because of a bias? Or was it just something that when it keeps going on and on and maybe you see other people with similar training get jobs, then you start to wonder? It started to dawn on me, I think maybe halfway through the year of that year when I was interviewing because two teams actually. So I was referred by one of the top people within basketball analytics who kind of became my mentor during that year. And he referred me to a lot of teams at the time. And I talked about in my article a little bit, there was one team they were hiring and a handful of people were referred obviously you don't just

refer one person and so it was tough though because send an email radio silence followed up maybe a few days after that radio silence again and it wasn't until I was at work I was working with LSU athletics during that year so while I was at work I get this text from one of my friends within the industry saying, Hey, Tiff, like, can you help me with some methodology? Because you when you're interviewing for front office or just any technical job, you have an interview process that's technical. And so he wanted me to help him with some methodology. And I was like, Oh, yeah, for sure. What is it for? And he was just like, Oh, oh it's for this job and it was the job that I was waiting to hear back from and the job was you needed a bachelor's degree and my my friend my colleague did not have a bachelor's degree and I did so I that was the first time where I was like, okay, this is actually happening. And the second time was an NBA team told me I was second tier in their candidates, which is, okay, cool. Like you rank your candidates. I don't know what you're ranking them on.

But I kind of introduced myself to them at MIT Sloan, which is our huge conference. And I just sent them my code. Like I sent them a snippet of code. And I was just like, hey, this is just something that I've done. And they were like, actually, could we interview you within the next few weeks? And I was like, cool, let's totally do that. And what's crazy is on the interview, the GM was on the phone, which after I had the interview, I had texted one of my friends

that was affiliated with that front office. And I was just like, hey, is this normal? He's like, was it your second interview or third interview? I was like, no, it was the first one. He's like, yeah, no, that's definitely not normal. So I think those two instances, which are which are a few months apart, and before I kind of made my way to ESPN is when it kind of dawned on me like, okay, like, this is actually really tough to where I was even kind of second guessing, like, do I even tough to where I was even kind of second guessing. Like, do I even want to continue in this profession or stay on this trajectory? But I applied for the ESPN hackathon.

To make a long story short, I applied for the ESPN hackathon and was accepted and presented my findings, which I think within that year it was on measuring the immeasurable. So I did the NBA hustle difficulty complex. If any of you have read Basketball on Paper by Dean Oliver, it's fantastic. But he essentially has this crazy, crazy, these formulas that are quantifying individual points allowed and individual points produced on both the offensive and defensive end. So I basically took that and I just added in hustle for that because the NBA came out with hustle metrics, those five hustle metrics. So I presented that at MIT and then ESPN started the interview process like that day and I got hired within a month.

So I think Sloan that year was March. I believe it was in March. Interview process started in March. And then I was going up to ESPN like June 5th. And beautiful Bristol. Yeah, beautiful Bristol. Yeah, there was a story in the Times last month about Rachel Belkovic, who was hired by the Yankees. And she's going to be the first woman to be a full-time hitting coach hired by a major league organization.

And there was an anecdote she told in there about how she was trying to get a full-time position in affiliated baseball, and she wasn't getting callbacks when she was applying for strength and conditioning jobs at that time. And so she changed her name on her resume from Rachel to Ray, which is, you know, sort of indeterminate. And then she said she started getting calls and the callers were surprised to hear a woman's voice on the other end. And she said some of them wouldn't call back. One team told her it would not hire a woman, which you wouldn't normally expect it to be so explicit, even if it is implicit, but that experience is out there. So you end up at ESPN and what sort of work were you doing? Yeah. So I was our sports analytics team within our stats and information

group. So our stats and information group is the entire brain when it comes to all the numbers you see throughout programming. So on ESPN, the channels throughout games, everything that you see on programming, digital, what have you, it comes from stats and info. And so there are four arms within stats and info, the sports analytics team, which was a team of eight people, the research team, the bottom line team. So just the ticker that you see at the bottom. And then I think the stats team, which kind of focuses on play by play data. So there are four teams and I was on our sports analytics team as an associate. So I wasn't actually supposed to be just like building metrics by myself.

But of course, in Tiffany fashion, when I got there, my manager gave me a project two hours into my first day. It was just like, hey, the magazine wants us to quantify the happiest college football fan bases. And from Baton Rouge Louisiana this was like heaven because go Tigers so I was so excited he's like hey don't spend too much time on this we just want you get your feet wet see what you can do so of course I mean I spent about like three months actually kind of working through the methodology and and building a. And it was launched, it got over a million views within a couple of days, which is huge. So a lot of people

kind of started to notice and started to notice our team more, which was definitely very interesting. And were you able to do a lot of other independent projects like that during your time there? And were you able to do a lot of other independent projects like that during your time there? Yeah, so there was another one. And our team was pretty, like we all kind of worked together and kind of build metrics with each other. Like if one of us was building metric and we needed some help with one methodology, we'd help each other. So I also worked on our fantasy soccer projections with one of our sports analytics specialists on the team. And I also worked on the, I don't want to say problematic, but the problematic top 20 college football champions in the past 20 years, which was actually on Fox Sports 1.

Like they were actually talking about it, which was hilarious. But yeah, so I got to actually do the methodology for that list and create that list. So there were definitely a lot of, a lot of projects that I worked on. I got to kind of get into a win probability a little bit more. I looked at some different sports, so baseball and all that good stuff. So definitely at a company like ESPN, where it's all sports, you kind of get to work on a lot and just building metrics for all of this. So you were at ESPN until early in 2019. And then at least looking at your LinkedIn, it looks like you've moved on and you've started some other things and you're involved in a few projects. So what are you working on these days?

Yeah, so I quit Eastman in January. And I do want to say like with the, just focusing on diversity and within sports analytics, just the reason for why I left was essentially kind of surrounding that. Because I was first female of color on the team, the only female of color in in like 200 300 person department so definitely super lonely and kind of when the trajectory that was happening for

the team which was awesome once I created the the happiness metric they essentially wanted someone to be the face of the metric and it was a pretty tough time where I didn't have the support from my team and my department, even from and having the support from producers and wanting that to be me. But kind of having it be told to me that we don't feel comfortable with you representing us on TV, super tough. And I think it's like being a woman and a female of color just within sports analytics it's like since I started just always having to have this tough exterior so that was one of the main

reasons why I left and why I quit in January and yeah so I quit for startup world but I'm building my own entertainment sports entertainment media tech startup now with athlete driven media and individual driven media being just such a norm now. And now with NCAA student athletes being able to monetize name and like this, I knew that something needed to exist for them to be able to easily create their own media and easily monetize separate from the current options that are currently out there in the market. So that's what I'm doing now. So it launches end of quarter one next year. Cool, well good luck with it.

Thank you. That ESPN experience sort of sour you on your original goal of working for a team or for an organization? And did you feel like you needed to start something of your own or would you still be interested in doing that down the road? Potentially, if the right opportunity presents itself for me to go back and within a front office, maybe.

But I do think it's super interesting, just the thoughts and opinions surrounding minorities within sports analytics, right? And we both mentioned, like, just some comments that commentators at ESPN have had. And so Jalen Rose mentioned something in the summer, but also, like, Stephen A has the exact same thought process too, right? Like, that there's kind of this evil specific, like only focusing on a subset and a subgroup of people within sports analytics.

And those comments like yes and no, I do believe that some sourcing is going on. No, that I don't believe that it's purposeful. I don't believe that GMs are sitting in a room and like deliberating saying, okay, let's not hire this black person or let's not hire this woman just from the experience that I've had. But human psychology 101, we gravitate towards what we're comfortable with and what we have experienced and what's normal to us and what's our social group, right? Which is why HR

exists. And I think that specifically in front offices, just when I've worked with the front office, HR actually doesn't really touch a lot of front offices, which is extremely problematic, which that needs to change in every single front office. And that's kind of what happened with the Dallas Mavericks incident. So I do think if the right opportunity comes along, maybe, but I think that that needs to change. It needs to stop being looked at as a pipeline issue that we're kind of just like not out here because we are like we're, we're, there are technical African Americans and there are very technical women that that can do the job and it's not a coincidence that i got hired within a month to go work at espn right like within three months of getting hired i john skipper asked me the

former president of espn to meet with him in his office. And he was super intrigued by my hiring process and forever grateful at that meeting because he was just, I made it a point that HR purposely hired people that were competent, but also people of color and diversity that were competent. And so just that was amazing for me. He's like, so it's me. He's like, it's not a coincidence that you were hired so quickly. I wanted it to be that way because it needs to be that way. If every corporation, if every front office had this mindset, I think we would definitely be far better off. Yeah. For people who didn't see Jalen's comments, I'll just read a bit of his quote. This was something he told The New Yorker back in June. He said, Also an opportunity to funnel people to jobs, analytics that is, by saying that I am smarter than you because the numbers back up what I say and I am more read.

I study more. I am able to take these numbers and manipulate my point. And so he was saying that players with experience, ex-players, are not making it into analytics departments because their numbers backgrounds are kind of trumping the experience when it comes to that kind of work. And in a follow-up interview with NPR, he said a lot of times the numbers become a catalyst to say, here's an opportunity. Oh, and by the way, since you know analytics, you get pushed to the front of the line. And if you look in the NBA and in many professional sports, there isn't a lot of diversity among those who get their position based on the fact that they were really good at crunching the numbers and doing analytics, which is inarguable.

Obviously, if you look at analytics departments, there is not a lot of diversity, as he said. So that sort of, I don't want to say started a discussion, but amplified a discussion that had been going on and brought some attention to that imbalance. So are you aware of programs, initiatives that are out there that are doing a good job or a better job of trying to increase the representation? Yeah. So I'm on the board of one, not to plug here, but it's called the Sports Analytics Club Program. And it's a nonprofit that's essentially helping inner city high schools get students of color just more interested within

sports analytics and having them complete projects and just getting them really interested within STEM and sport. And also another one for family. Amazing. They travel around the country and kind of host these STEM workshops, but they're like in basketball gyms, which is amazing. So programs like this, I think obviously it starts really early, but retaining talent is super, super important. Like I think having the pipeline to give them the resources is amazing. And I think that's what a lot of people focus on. to give them the resources is amazing. And I think that's what a lot of people focus on. But once someone's in a front office,

once someone was in a corporation and they're there and they're diverse and they're kind of contributing to the organization, how do you keep them there? Right? Like, because if you are saying that, like you said, it's inaudible, it's not diverse. And then once you do have someone diverse, how do you keep them there? Are they lonely?

Like, is it just them? Are you giving them opportunities to be included in projects and everything that you're doing as an organization? That's super important. And I want more resources to be focused on retaining and just making sure that we kind of like our voices aren't lost essentially. And that's kind of what I've noticed throughout my entire career. Yeah. So do you think that any of the sports leagues does a particularly good job at promoting this type of hiring? I know baseball just because that's usually what we talk about, and they have started a diversity pipeline program and a diversity fellowship, and we've talked about that on the show.

And there's an organization, the Institute for Diversity and Ethics in Sports, that gives sports leagues and baseball a report card every year on gender hiring and racial hiring, and I don't know exactly how they determined that. I know MLB's grades used to be terrible and now are slightly less terrible. I think they got an A- for racial hiring and a C for gender hiring in the most recent report. So there are efforts to change there. But I guess that basketball has probably done a better job of that than baseball has the NBA. And maybe there are more people in positions of power in the NBA who are diverse than in baseball, certainly. Yeah, I think so. I actually recently gave a talk at Facebook and it was an analytics conference.

And A, people are super interested that sports analytics is a thing they're just like wait what and then b they're just like oh that's that's like really technical right it's like you're doing analytics but it's also sports right so I whenever I was there I kind of had this screen on my slideshow that kind of had numbers of women within the front office for all of the different leagues. And yes, of course, the MBA is the leader when it comes to hiring both gender minorities and racial minorities. But there's still so much work to do because I wanted to go into the MBA and I wanted to work with the front office and work with a team but even I kind of had my own just my own experience even I had to

kind of go through all of those hoops that I mentioned earlier so even though it is the best like still the fact that that's the best is still kind of sad? Like there's so much work that essentially needs to be done. And I think it's done through HR, like having HR embedded in front offices. Like that needs to happen. Like it can't be separate anymore. Like I remember when I was working with the Heat down in Florida,

like front office, one side, business office, other side. And it was so interesting. No one can meet, like you don't communicate with the front office, one side, business office, other side. And it was so interesting, no one, like you don't communicate with the front office. And so obviously I think that's changed a little bit, but that shouldn't be the norm anymore. Like HR and business needs to be plugged right in with the front office,

because even though you're running the team, even though you're talking to the athletes, even though you're focusing on super important personnel to get the business running, I mean, you still have to follow the rules and you still have to kind of focus on all the things that are super important. Well, we appreciate your coming on and sharing your experience. I wish you luck with your ongoing ventures. And you can find Tiffany on Twitter at TiffMKell. You can also find her website at TiffanyKelley.co.

She does speaking engagements if you would like to have her come talk to your organization. So thank you very much for your time, Tiffany. Thanks, Ben. All right. Thanks to Sherry and Tiffany for sharing their experiences I've linked to some of the programs And initiatives that we discussed On the show page at Fangraphs

And in our Facebook group It's obviously important that people not be barred or discouraged From doing things that they want to do And it also just makes sense that you would want to have A diverse group of analysts Because increased diversity and demographics May lead to increased diversity in demographics may lead to increased diversity in thought and a little less groupthink. Not to mention the fact that since

historically speaking, teams have tended to hire interns who don't make much money or any money, which really restricts the pool of potential applicants to a limited socioeconomic group that can actually afford to do those jobs. You're really narrowing the sample of people who can potentially work for you. Fortunately, that is changing, but it's taken too long. This is the last episode in our Multisport Sabermetrics Exchange series, but it seems like a lot of you have liked it and learned from it, so maybe we'll bring it back during the holidays next year in these slow news weeks for baseball when people are traveling and on vacation and we're looking for things to pre-record. We covered a lot of the most popular sports in the world in this initial run, but there are many more we could get into in the future. We could talk

about other racing sports, combat sports, curling, lacrosse, roller derby, Australian rules football, some of the other Olympic sports, even board games or card games or individual video games. If there's a sport with interesting analytics that you'd like to hear us talk about in the future, please let us know. And as we've worked our way through these dozen different non-baseball sports, some things have stood out to me, some common themes. For one thing, there's no stopping sabermetrics once it starts. You can't put the analytical genie back in the bottle. That's not to say that data analysis is the only way to succeed in sports.

But if you're using those tools and your competitors aren't, you're going to have an advantage. We started this series off with football, and you can hear what I'm talking about with football just this week, where Dave Gettleman, the New York Giants GM, who's been anti-analytics in the past and called the analytically driven idea that running backs are less valuable than previously believed a crock. And he said, if that makes me a hater of analytics because the analytic people say you can plug and play whoever you want at running back, you can't. If that's the reasoning that I've become a doddering old fool that hates analytics, that's okay, etc. Well, now Gettleman's job is in jeopardy. So he's saying, I'm going to learn from my mistakes. He's saying we hired four computer folks, software, that he recently met with a big analytics guy now okay someone who's

describing analysts as computer folks maybe not actually going to change his ways but the point is that he now at least has to pay it lip service and if he doesn't change his ways then the giants will probably find someone else who actually means what he says there's just no way to be anti-analytics anymore and keep your job. And of course, as tracking information has become common, the lines between what we used to think of as statistical information and scouting information have really blurred, and those things have become almost indistinguishable.

So it really doesn't go backward. Once this stuff starts to break into a sport, you can kind of forecast where it's going to go from there. And that's not necessarily a bad thing from a spectator perspective. As we've seen, it really varies by sport. In baseball, arguably, it has been a negative in some ways, maybe even a net negative. But in other sports, it hasn't hurt the entertainment value. Maybe it's even improved it in some cases. I think we've seen the importance of public data. You can't have a thriving analytical community surrounding a sport unless

the data is out there. And so we've seen in sport after sport how in the early stages of these movements, people really had to put some sweat in and do the grunt work to gather this data themselves. And over time, it has become more available, but not in every sport. In some sports, it's still really restricted to teams and certain data providers. And so those sports may have people working for teams who can slice and dice that data, but not so much out here in the public sphere. And when there are fewer people doing this work in the public sphere, that leads to fewer qualified people who can really move into a role with a team and help right away and just spot check and quality check and uncover biases in the data. That's an ongoing concern in baseball and other sports who will have access to this information. And will there be a gap between private and public analysts. I think we've also heard over and over about the importance of

Moneyball. We know what impact it had in baseball, but in baseball there was already a sabermetric movement underway. I think Moneyball certainly helped accelerate it, but it was proceeding along that path already. In other sports, though, Moneyball really helped jumpstart things because people looked at what Michael Lewis wrote about and what Billy Bean and the A's were doing and thought, can we apply this to our sport? And it really just reduced some of the resistance because if it had already worked in one sport and produced a bestselling book, then there was less resistance to it. People wanted to jump on the bandwagon instead of circling the wagons and preventing it from happening. But you still do see the same clashes and the same backlash and the same arguments playing out over and over and over again.

But if you've been following baseball, you kind of know where they're going to go and where they'll end, which is in greater acceptance. That said, there's still a lot of uncertainty, still a lot of concerns about tracking data and biometric data and wearables and privacy and how much is too much

and whether it becomes invasive at a certain point. And I think more and more all sports are really grappling with what Travis Sochik and I wrote about in baseball in the MVP machine, which is, okay, there's some baseline level of acceptance of analytics. There's some rich data out there. Teams or pros are employing people to analyze that data and produce insights. But then the key becomes translating it to the field, to the court, to the pitch, and figuring out how to get players to internalize and apply that information and how to get it in the hands of coaches who will actually use it. Otherwise, there's sort of a bottleneck preventing that information from actually being useful. So clearly a lot of parallels here,

even though the sports we discussed, according to our experts, ranged from a 2 to a 9 on the 1 to 10 ease of analysis scale. And I think it is helpful to have people from each of these fields talk to each other because there are a lot of concepts that extend across sports and some statistical frameworks that can be repurposed and concepts that have some universal value. So again, thank you to all of our guests and thanks to all of you for listening. It's easy to enjoy sports without looking at them through an analytical lens, but there can be something compelling about trying to solve them or understand them in a new way. And it is something that has enriched my enjoyment of sports.

It's sort of a puzzle that we can all try to tackle while we're marveling at the athletic feats that we know we could never recreate. Before I leave you a follow-up to a follow-up on the outro to yesterday's episode, I brought up the idea of the most famous non-walk-off, non-milestone homers in history, which is something that Sam Miller and Meg Rowley and I talked about a couple episodes ago. We were trying to come up with examples of home runs that fit those conditions and not coming up with a lot off the top of our heads. Of course, as I mentioned on the last episode, Bucky Dent's home run is a very famous non-walk-off, non-milestone homer.

And James N. Gannon, another one of our Patreon supporters, wrote in to suggest a few others. George Brett's pine tar game home run, Ted Williams' home run in his last at-bat, Reggie Jackson's third home run in Game 6 of the 1977 series, and Derek Jeter's Jeffrey Mayer-assisted home run over Tony Tarasco's outstretched glove in game one of the 1996 ALCS. All good suggestions. Thank you, James. And one last thing from the Scott Boris verbal gyrations department. I was reading an article at The Athletic by Richard Deitch and Daniel Kaplan and Bill Shea, headlined 2020 predictions and thoughts from sports industry figures. This was just surveying a lot of prominent sports people, commissioners and executives and analysts and network presidents and so on about what will

happen in their respective sports in 2020. And every entry but one here is just written in regular language, people writing in complete sentences, mostly pretty bland language, just business-like, professional. The one exception is, of course, Scott Boris, everyone's favorite inscrutable super agent, and he actually leads off the article. So here's what Scott Boris writes. 2020, it's the beginning of a new decade. The MLB roaring 20s, dot, dot, dot.

And then he has a bullet point list of five things that will happen. A jazzy new CBA will play new tunes. Sign bootleggers will be fined and suspended. Sign bootleggers, that's hyphenated, as in sign stealers. Three, reliever prohibitions will be enforced. Four, flappers will crowd the Clevelander in Miami

and double attendance. Five, the great luxury tax depression will occur. And then he closes with, it's deja roaring all over again. Deja roaring. That's hyphenated too. So he's really embracing the Roaring Twenties theme here. He's trying to tie this into jazz and bootleggers and prohibition and flappers and the Great

Depression. No one asked for this. No one. They just wanted some predictions for what will happen in 2020. Everyone else obliged in the completely predictable way. And here's Scott Boris coming up with catchphrases and what he thinks is witty wordplay. And you can kind of understand what he's going for,

but you don't really understand why he's going for it. And I scrolled down to the comments just to see if anyone else had remarked upon Boris's response here. The very first comment says, For baseball, all you have is some nonsensical drivel from Scott Boris. Deeply disappointed. Expected much more from you.

That has 147 likes. Someone else says, I was going to say the same. Another person says, yeah, that guy needs to put the pipe down. Someone else, and it led this piece. What a waste. Someone else calls it utter trash by Boris. Another person asks, anyone care to translate Boris's word salad? Another notes, as others have previously written, Boris's comments are a waste of time.

It goes on and on. Anyway, this is one of the weirdest examples of Scott Boris torturing the English language that I've ever come across. I get the metaphors and the analogies he's trying to get people talking and tweeting fine. But here he is given a platform, the spotlight is on him and many other prominent people from the sports world. And he just fully embraces this bit about the 2020s being like the roaring 20s in baseball. Boris just can't help but be himself. All right, that will do it for today and for this week. Thanks again for listening.

You can support the podcast on Patreon by going to patreon.com slash effectively wild. The following five listeners have already signed up and pledged some small monthly amount to help keep the podcast going and get themselves access to some perks. Matt Fogelson, Chad Post, Nathaniel Siegler, Nishant Menon, and Sarah Luthi. Thanks to all of you. You can join our Facebook group at facebook.com slash group slash effectively wild. You can rate, review, and subscribe to Effectively Wild on iTunes and other podcast platforms. Keep your questions and comments for me and Meg and Sam coming via email at podcast at fangraphs.com or via the Patreon messaging system if you are already a supporter. Thanks to Dylan Higgins for his editing assistance.

And we'll be back to business as usual next week. Have a wonderful weekend and we will talk to you soon.