Effectively Wild: A FanGraphs Baseball Podcast - Effectively Wild Episode 1794: Play Up and Pay Up

Episode Date: January 7, 2022

Ben Lindbergh and Meg Rowley continue their “Measuring the Unmeasurable” series about studying difficult-to-quantify aspects of the sport by talking to Patrick Brennan about his studies on assessing player development at the major and minor league levels, the challenges of evaluating player development, the data he wishes he had, the most and least successful player […]

🎵 It's just a small consolation I just define it as a matter of variation Hello and welcome to episode 1794 of Effectively Wild, a baseball podcast from Fangraphs presented by our Patreon supporters. I'm Benjamin Berg of The Ringer, joined by Meg Rowley of Fangraphs. Hello, Meg. Hello. So just like last time, we are devoting today's episode to talking about measuring the unmeasurable, talking to some authors of recent research about

difficult to quantify aspects of baseball that's caught our eye. So later on in this episode, we'll be talking to Grant Washburn of PitcherList about quantifying owner performance and ownership groups. But first, we want to talk a little bit about player development with Patrick Brennan. Patrick has written for various sites over the years, Beyond the Boxscore, Hardball Times, etc. But he wrote a piece for his own site just last week about player development in the minor leagues, kind of building off some previous work he had done about player development in the major leagues. And he is also the director of analytics for the Kansas State baseball team, which we will maybe ask him about as well.

Patrick, welcome to the podcast. Yeah, first I want to start off by thanking you guys for having me. I've listened to this podcast as much as I could for the past couple of years. So I'm thrilled to be on. But yeah, Ben, you gave a pretty good summary of what I've done the past few years and I'm happy to get into the specifics of the article and anything else you guys might want to talk about. Great. So what has drawn you to this topic? Because as I mentioned, you did a piece a couple of years ago that was looking at this at the major league level and which teams have managed to outperform their projections over the years, which you could chalk up to player development at that level. Now you've gone even deeper into the minor leagues and there's just not a ton of research into this topic.

And I co-wrote a book about it and still would love to see more research about player development in general. wrote a book about it and still would love to see more research about player development in general. It's certainly something I'm interested in and obviously something that's pretty important in baseball and in any sport. So what drew your attention to this topic? Oh, yeah. Just really, your book covered a lot of it and I read it. The growing importance and focus on player development within the major league baseball organizations. I know player development has always been a thing, obviously, throughout the history of baseball, but anyone that pays close attention to the game, I think, can see whether you want to look at the past three years, five years, 10 years, the focus on it, I think, has grown, I think, a lot due to

the added technology we have within the game has just given teams more data points, more insights into their players, which has, I think, allowed more areas to look at with each player, which in turn leads to more areas to a bit over two years ago, that project actually spurred from a tweet by Kyle Bode, who, as you know, has been very involved with the innovations tweet was, but along the lines of how we can use projections as baselines to evaluate players and factored into evaluation of player development. And that tweet really just sparked my interest. So I started looking into it on my own. First thing I thought of, well, let's just use a public projection system. So I, you know, like Steamer, went with that and just started looking at, you know, obviously just the raw differences in performance versus expected performance for each player and just how that looked when you grouped it by each major league organization. And I didn't know how the results would turn out with it, but it was good to see a lot

of it matched with intuition, I think. I broke it down by hitting and pitching and then also combined those two. And just, you know, a lot of the teams you would think that would come to your head when you ask, you know, the question of what teams are good at developing players. They were at the top. Astros, Rays, Dodgers, Cleveland, you know. So, yeah. And then after I I published that article the project kind of always just stuck around my head the question and uh obviously that one was focused on major league player development but I felt that you know we I could look at you know minor leagues uh because I feel like that's where you know the bulk of actual baseball player development takes place

I said in the article you know you're gonna have more areas to develop when you're dealing with a, you know, 2021 year old pitcher that was just drafted in the 20th round or something. Then, you know, 30 year old starting pitcher in the major leagues that already has hundreds of innings under his belt. So yeah, there's just more, you know, player development that goes on in the minor leagues and teams allocate their player development resources accordingly to that. So yeah, I felt that was definitely an area to look at. Obviously, there were some harder things to deal with. It's not just as straightforward as taking a projection system at the major league level and comparing it to performance.

So I had to do some added steps by myself. But, again, I was pretty satisfied with how the results matched with what we see with our eyes so that was again good to see and yeah you know I had a lot of fun doing the project. And maybe we can start there what were some of the challenges you had in creating your own minor league projections and how did you go about constructing those because as you said last time you relied on steamer and I know that there have been various other attempts some of which are you know more public than others to come up with good major league equivalencies and sort of minor league projections but a lot of that stuff isn't open the hood is closed so how did you go about the process oh yeah i'll start off by uh saying that the goal of this project wasn't

necessarily to build the most like accurate projection system i validated it and made sure like it was better than just like a baseline of like say the previous year performance. And it was, so that was good enough for me to use, I felt like. So yeah, I wasn't like trying to, I didn't go too deep into the projection part, but I just used just a lot of the projection, I think basics, if you're trying to build a projection system, which is just regressing to the mean, waiting past years. I think I went three years back and adjusting for things like if you're trying to build a projection system, which is, you know, just regressing to the mean, waiting past years. I think I went three years back and adjusting for, you know, things like I made an aging curve. That was one thing I didn't have available publicly. As for the MLEs, I used Clay Davenport's numbers. He has available on his site and just applied those to the data I

had. And so that was the way, yeah, you had to adjust for, you know, level played at. Obviously, a person who hits for league average in AAA is not going to be the same as a player that hits for league average in low A. So you had to adjust for that. And I think another big challenge, I don't know if I really got into this much in the article, but was the 2021 season. That was a very different season to what we've seen in the minors from you know the other day that i was working with which was 2007 to 2019 and i think a lot of that's obvious uh obviously you know the restructuring of the minor leagues and canceled season last year caused a lot of things to kind of be a little bit whack compared to past years. So that kind of threw off

the numbers a little bit for this past year. So I had to make some adjustments for that and kind of normalize the numbers a bit. But yeah, those were the three, I think, biggest difficulties I had to work around. And so what form did your results take? How do you deem a system either good or bad or successful or unsuccessful at player development in any given season or a range of seasons? So yeah, I just, you take the projection and you compare it to their actual performance. And then just the simple delta, you can do a couple different things, I felt like. You could weight it based off plate appearances. So so that way players in the organization with higher plate appearances would be weighted higher than you know players would say someone with like

50 plate appearances or you can just uh take a like make a qualifier like say 200 250 pas whatever you feel good with and just look at the raw average um i thought about it a little i couldn't decide which one was better uh i think i went with a weighted plate appearance so yeah just uh the average of the deltas weighted or unweighted and then um adjusting that to basically the seasonal environments of so what really caused me to adjust for seasonal environments again was the 2021 season i'm adjusting for that and then um you know applying it on a scale of 100, just like, you know, a lot of baseball stats, WRC plus OPS plus. And yeah, so if you were if an organization was like at 103, that means they were their hitters were 3%. They were hitters were over

performing 3%. If they were at 95, they're underperforming 5% 100 average. So yeah, that's how the numbers were displayed for the organizations. And were there any organizational surprises for you as you were working through your results? Yeah. Again, at the top, there was a lot of non-surprises, which was really what I was looking for to kind of validate it with the eye test. I did two tables. I looked back three years, and then I looked back at this past year. So on the three-year one, Blue Jays being at the top was a little bit surprising, I think. I think they're pretty well-regarded in player development, but they were ahead of the Astros and Rays, which I wouldn't have guessed to be true. Another one was the Pirates being up there.

I know they've gotten a lot of recent flack, especially at the major league level with their player development department. But I think they've made some changes in the past years. And their minor league, at least the data for their minor leaguers, they perform pretty well for both hitters and pitchers. And then for the 2021 one, the Royals were at the top, which I thought was a bit surprising. They were number three for hitters and number three for pitchers,

number one overall. Watching back in 2019, they had like all of their top prospects underperformed severely. I think actually in the, so I think I had 390 organizations going back to 2007 organization seasons. And the 2019 Royals were 390th out of 390 teams in hitting development and the score I had. And then this year they were number three overall in hitting development. They made, and that coincided with a lot of changes they made in their player development organization. I know they switched some guys around in some roles and then brought in Drew Saylor from the Dodgers organization to help with their hitting development. And all the prospects that struggled for them last year, they all had amazing years at higher levels, which was kind of amazing to see.

But then again, yeah, it was good to see a lot of the non-surprises at the top, you know, the Dodgers, Astros, Rays. So I felt like that at least semi-validated what I was doing. But yeah, there were some surprises mixed in for sure. Yeah. Do you know anything about the year-to-year consistency of this metric? I mean, it's hard to judge what a single season means, especially in this era where you have so much overhaul and turnover and expansion in player development and teams can just really rejigger their entire approach to player development in a year or two or three. So even if you were good at this three years ago, it doesn't necessarily mean you

are now. But do you know if that tends to be the case? I mean, I guess you looked over three years and maybe it's almost useless to go back much further than that. But I wonder what the consistency is. Yeah. In the minor league one, I didn't really dive too deep into that. In the major league one, I think I found a low level of correlation, like small relationship. I don't know if that was just noise or if there was something to that. But yeah, that was part of the reason I did two tables. I

wanted to give an insight into what was going on in 2021, but I felt like one season of sample size maybe wasn't fair to make 100% drawn out conclusions. But going back three years also has issues. It does improve your sample and I think it gives your metric a bigger chance to stabilize. But there are issues, as you mentioned, player development is constantly changing the landscape within baseball overall, just between all 30 teams. And then, you know, teams are constantly making changes with their departments, philosophy changes, you know, it's constantly evolving so uh that was you know why i wanted to give those you know two different insights but yeah with the minor league i with the minor league project i didn't really dive too much into year-to-year correlation but i would be shocked

if there was some for sure i'm curious if there's other data that you would be interested in incorporating into this model because obviously obviously performance is one good indicator, but I would imagine that when it comes to evaluating player development, that you might also be able to glean something interesting from, say, how many prospects see their hard hit rate improve or the average launch angle change or for a pitching prospect, if you're looking at differences in horizontal or vertical break year to year. So are there other pieces of information that you'd like

to incorporate to further sort of tease out which of these organizations is doing the best by their guys? Oh, yeah, I'd say both with publicly and private data. For public data, I think, yeah, like you said, you could break it down further from just overall performance like WRC+. You could look at what organizations are developing contact hitters better. So look at like K percentage, or you could look at ISO for power. And yeah, same thing with pitchers. You could look at strikeout rate. And then with privately available data, and I think a few teams I know I heard they do evaluate player development trends within baseball like this. So and obviously have loads more data than what is publicly available. But, yeah, you could definitely look at, you know, if a team has a pitch rating based off like pitch characteristics,

you could look at what organizations are better at developing stuff or command, you know, breaking that down into velocity, horizontal break, vertical break, things like that. So yeah, you could expand this a lot with other data that is available publicly. And if you had access to private data, you could look at, I think, a lot of different avenues. Yeah, and I guess another challenge with this is park adjustments, let's say, which are much more easily available at the major league level than the minor league level, right? So you're using FIP for pitchers and you're using WRC plus for hitters, which is league adjusted, but not park adjusted, I believe. And so I guess there could be some cases if a player is going from an extreme minor league pitchers park to an extreme minor league hitters park, that sort of thing, it could look like maybe they were outperforming or underperforming projections.

So I guess the framework is useful here, but maybe some of those inputs, just because it's minor league data and they're not quite as high quality or adjusting for all the same factors that we're used to with some of their major league equivalents. Yeah, for sure. That was one of the biggest caveats to the minor league project. And that wasn't really something I could adjust for with minor league data. I think teams have access to a good amount of that information, but publicly available. Yeah. And especially too, with all the affiliates changing in 2021, it makes it harder. So yeah, that was one of the biggest caveats to this project for sure. Yeah. But like you said, if there's a case where maybe if an organization has, you know,

going up the ranks of the minor leagues, low eight, a triple a if their parks, you know, become more pitcher friendly, that's going to make their hitter scores look bad and their pitcher scores look good. So for sure, that was one of the biggest caveats I hoped with a big enough sample size, at least someone that stuff could be eliminated. But yeah, that is something to be cognizant of when looking over the numbers for sure. I'm also curious, and Patrick, you tell me if this is a stupid question. And if it is, then you can tell me that. But I also wonder how you're accounting for sort of the baseline quality of the player involved here because obviously

player development you know it isn't linear and they're going to be you know mike trout might not vary very much from his projections as a minor leaguer but those projections might be in themselves very good because he's pretty close to cooked right and he's a great player so i'm curious what sort of quality adjustment there might have been to try to identify what is a real change from a player development perspective? What is an expression of underlying sort of innate talent relative to the player? Is that a dumb question? to totally eliminate like non-prospects from this project. Could, you know, how you wanna go about that, I don't know, but you could maybe take like just all prospects listed on MLB pipeline or fan graphs and look at that and just eliminate non-prospects totally.

What I did was eliminated anyone over the age of 28, as I figured, you know, those, you know, there's anyone in their thirties playing in the minors, they're probably in AAA and, you know, probably there aren't much uh at least on the organizational side there aren't much major league ambitions uh with that player um in most cases so i wanted to eliminate that from the analysis but yeah i did think about just looking at prospects uh because obviously uh the majority of the players that you're going to have data on are not going to be major leaguers. They're not going to really even be prospects. So a lot of that was in the data, but I didn't

want to totally eliminate that too, as I felt like each major league organization, whether it's a prospect or a non-prospect is still trying to get, you know, the top end performance out of that player. And, you know, we've seen plenty of stories of non-prospects turning into something. So I didn't want to totally eliminate those players, but yeah, that was actually an idea I had. And I did take some steps to eliminate players that, you know, I felt weren't really reflective of a developmental process of an organization. Yeah. That's one of the things that makes this fit into our measuring the unmeasurable theme, because it's just hard to isolate these things. If you try to quantify how well a team has scouted or drafted, for instance, well, how do you do that without

accounting for how well they've developed those players, which is a separate department, or at least historically has been. They're a little bit more integrated these days, but it's hard to isolate those factors. And if you're going to assess the team's development too, then, well, it maybe matters how well you drafted and scouted. And it's kind of, it's like separating, you know, pitching from defense almost. It's just, it's hard to isolate some of those things.

One thing that stood out to me as I'm looking at the list, particularly the list since 2018, it seems like there isn't a very strong correlation between a team's rank or performanceter score for organizations over that period. So it's a fairly weak correlation, although it does seem like, you know, there aren't a lot of teams that are like close to last in one and close to the very top in others. There are some teams that seem to excel at both or be, you know, top five, top 10 in both certainly. And you, you mentioned the Astros seem to be up there and the Rays and the Yankees and the Blue Jays. And again, these are sort of the usual suspects when it comes to, oh, which teams are good at player development, but I guess it makes sense, right? That you would probably not be terrible at one and great at the other, but that there would be some

variability. I mean, it's like, you know, certain scouts are good at evaluating pitchers more so than they are at evaluating hitters. And certain systems, I guess, could be really good at developing a pitching program and not so great at developing a hitting program because those things have been kind of decoupled or pitching was ahead of hitting when it came to development. But also, like if you have the right people in place and you have sort of good communication and a pipeline and all of that, then you'd think probably you shouldn't be completely incompetent at one if you're pretty good at the other. Yeah, I agree. I think, yeah, intuition would suggest that you would expect to see a small relationship, I think. Not perfect organizations, those hitting and pitching developments. Departments don't really work together, but they have a lot, I think, of the same

processes and philosophies because I think they all take direction from what's going on in the Major League front office. And those are the people making those hires. So yeah, you could definitely expect to see some sort of relationship. It was also a good thing too. I didn't want it to be a perfect relationship too, because I think that would signify some of, you know, the, you know, the park factor issues we were talking about. If the hitter and pitcher scores are lined up, that would probably be some signal of that.

But yeah, again, I, yeah, I wouldn't expect to see a perfect correlation, but definitely some small relationship for sure. I know that it's extremely irritating to do a lot of work and then have someone say, have you considered doing all of this other work that I'm about to suggest to you? But I would be interested, and I know that it would be difficult to sort of track this and ascertain it because it would require very specific knowledge of not only the movements of team personnel but also who in organizations they ended up working with but i i wonder if some version of this could point us to sort of tracing more precisely a player development lineage through baseball right because teams hire away from one another all the time right like you know, Seattle hired guys from Cleveland, and then some of those guys went other places. And

you know, there's, there's a lot of shifting around every couple of years of org members. And so you would expect that some of that DNA transplants into new organizations. And I wonder if there would be a way for us to try to track that. Cause I would be curious as another way of sort of backtesting the reputations that some of these orgs have when we see how their former personnel maybe impart that wisdom to new teams. And then, you know, all of a sudden their pitching ranks go up because lo and behold, you know, Tampa is really good at developing pitchers or what have you. Oh yeah, for sure. That was something I thought about briefly was, you know, looking to see if I could group the, you know, these data points, you know, by, you know, whether you want to look at certain employees or departments or like you said, lineage from organization to organization. That was definitely something

that came to mind. I think it would be a little bit tough to group and quantify accurately, but if you could do it, I think it would be very interesting for sure. Since you published the study, have you seen particular fan bases either celebrate it or boom on it if their team didn't do well according to your rankings here? Who's sort of generated the most discussion when it comes to your findings? your rankings here? Who's sort of generated the most discussion when it comes to your findings? Yeah, I think it would be exactly that. The top team and the bottom team, Blue Jays and Rockies fans. Poor Rockies fans. You had to pile on those Rockies fans on top of all of their other woes. It is sort of surprising to see them down there, if only because it seems

like, if anything, they've been better at player development and developing players internally than they have been at, say, signing them via free agency. But I guess it's not news to Rockies fans that the Rockies are bad at something. So I'm glad, even if you saddened some Rockies fans, that you took a stab at this subject, thorny as it is. I know that the folks at Driveline have done some research at their blog, valuing the difference between teams in player development, but I think it's good that you did your own version of it and at least provided a template here. And even if there are things that we don't know about minor league players that teams do, and of course teams know even more about their own minor league players than they do about other teams, they might have access to their workout information and nutrition and sleep and who knows what else.

But we can't do it perfectly from the outside. But I think it's still valuable at least to put it out there. And I'm sure that you have gotten some firsthand experience in player development yourself working with the Kansas State baseball team. And I know that we have a lot of students who listen to the show and want to know how to get involved in baseball and what they can do. And you have done it so tell us a little bit about how that relationship started and what you have done with the team yeah so i'll go back a bit i think with a lot of people currently working in baseball and currently seeking to work in baseball um and you know when i was younger you know the movie moneyball came out and, you know, I saw that. And, yeah, that basically spurred my interest in, you know, this field, this industry.

And since then, you know, I've been working all I can do to try to achieve that. So when I went to school at Kansas State, I heard about some other schools that were doing things with volunteer assistants or student managers working on their staff particularly in analytics that had been something that I had been working on my own you know you mentioned a couple sites I wrote at that was all you know public research and I was that helped me refine my skills and sort of gave me a portfolio you know so when I reached out to the coaches when I got there there, there was this online blogger reaching out to coaches asking if they could help. And I was surprised when they responded.

It was actually a yes. So that was great. And I've been working there since finishing up school. Currently, my title is Director of Analytics. So that upstarted the analytics program at K-State. We were the first one there for the baseball team. So we've really, you know, been getting off the ground with a lot of the technological innovations that teams have been making throughout the years. So we got TrackMan, Rapsido, Edgertronic, and we've really just been introducing those

technologies and I've overseen a lot of that. And we operate and we manage all the operations of that. And then, of course, we help out with, you know, your other basic analytical operations, whether that's, you know, hitter reports, pitcher reports, advanced scouting reports for opponents. So, yeah, that's been a great experience. And I really felt that it's helped prepare me for what I goal is, what I want to do, exiting college. And I've really enjoyed it overall. I'm curious what the sort of baseline experience level with those varying technologies and

sort of core analytics concepts is among the players who you've worked with. And you don't have to name names or anything. But as guys are coming in, sort of how much do they already know about viewing the game through that lens and how receptive are they to incorporating that kind of information into their preparation and training yeah so i'd say when we introduced that technology at k-state across the players there was a varying amount of um past experience or knowledge with it and, it was pretty new to baseball at the time we got it. I don't think Rapsdale was more than a few years old. And colleges at that time were really starting to get involved,

you know, with just baseball technology in general. But I think around the time we got TrackMan was when there was just a huge spike in TrackMan being installed at college baseball stadiums. I think now in Division I, I don't know the exact numbers, but I want to say like there's probably near 100 schools that have radars now and are all involved in, most of them are involved in the sharing network. So that's when you share your data.

So yeah, I'd say with the players, you know, outside of the team, you know, they all train at different facilities that have, you know, varying amounts of technology. And just with different players, I think there's different interest within the game. Some actually did have interest on the analytical side and some don't really, not that that's wrong,

but they just prefer to play and not pay attention to that stuff, which is totally fine. So yeah, I think I'm not a coach or anything, but I think when you're a coach, trying to implement technology with that stuff, you have totally fine. So yeah, I think I'm not a coach or anything, but I think when you're a coach trying to implement technology with that stuff, you have to keep that in mind that, you know, some players are going to be really smart on this stuff because that's what interests them and they have past experience with it. And then some players are going to be new to it. It's going to be pretty foreign to them. So yeah, when you,

when you're a team implementing a bunch of new tools like that, you have to keep that in mind. And for those who don't know, the amateur level in college, especially the big programs, has really been a hotbed of player development in recent years. I mean, major league teams are hiring coaches from the college level often, although sometimes coaches will go from major league teams back to college because it might be a better working environment or they might make even more money there than they would with a major league organization. So I'm sure that you have seen that. the time they get drafted, if they do, I think often they're entering those player development systems, really having been steeped and seasoned in that stuff because of their college experience. Yeah, obviously with college, there's going to be more restrictions in a major league team with budgeting and stuff. But for the top tier programs, that'll be less so. Yeah. And a lot of them you've seen a lot more, I want to say, you know, changing positions between the NCAA and Major League Baseball organizations. Whether, like you said, jumping from NCAA to the professional level or professional down to college.

And I think that will only increase, too. I think I wouldn't be surprised if you see college teams here within the next few years start hiring their own analysts, at least the top tier programs, I think. And I think, you know, a few colleges are starting to work into full time staff members responsibilities. And again, with the top tier programs, you're going to see less of those, you know, budget restrictions. So they can invest more into the resources that may allow for them to hire an employee that is devoted to that full-time. So whether it's technology like TrackMan, Rapsido, all that, or actual labor of an employee, I think you're only going to see that increase for sure. And I think some schools have gone way into it. I know,

you know, Wake Forest is famous for their pitching lab, which I think is probably one of the best in the country. But yeah, I think you're only going to see this trend not slow down. Yeah. So last thing before we let you go, you did do one other article at your blog in October, I believe, called entropy and and Pitch Sequencing. And this is another subject that's proven a tough nut to crack for analysts. And I guess you were looking at it more in terms of pitch mix and variation and predictability more so than, say, what the effect one pitch would have on the subsequent pitch, for instance. what the effect one pitch would have on the subsequent pitch, for instance, but what was the approach that you took here and what kind of advantages do you think could be gained by studying that subject? Yeah. So in the article with the actual pitch type sequencing, I just

calculated entropy bits, which was, I believe, research done in the past. It hadn't been done in a while, so that's why I was interested in it. I think Rob Arthur did it at Baseball Prospectus maybe about like 10 years ago or so. So yeah, I remember that article. I looked over it a few times. I hadn't seen anything like it in the public sphere in the past couple of years, so I was just interested in looking at my own. Yeah, and I think with pitch sequencing, you can look at it and you can attempt to quantify it in a variety of ways. Actual predictability is one thing, as I did in that article, but you can look to quantify it in a variety of ways. You know, actual predictability is one thing, as I did in that article, but you can look at it like actual like sequencing

between like maybe two pitch types. So what's the effect of throwing a fastball changeup compared to a changeup fastball with a pitcher? So sequencing, it's a very broad term within baseball. And, you know, that makes it even, you know, harder to quantify. It's very complex, but that makes it all the more interesting, I think. And I still think And, you know, that makes it even, you know, harder to quantify. It's very complex, but that makes it all the more interesting, I think. And I still think that, you know,

can be, there's a lot of room for improvement within that area of study. And, you know, some things that could possibly be cracked in the future that really help us understand the game more. All right. Well, you can find Patrick on Twitter at Painting Corner, and I will link to all the work that we discussed today. And I know that you worked for the Reds and did some track man operation and baseball analytics work for them last year. Are you expecting slash hoping to be going into baseball full time as soon as you're done with school? Oh, yeah, that's the goal. Always looking for work, you know, when school's not in the way. So over the summer too, but after I graduate next year, that will definitely be a goal.

Whether I have to intern, you know, one or two more times, ideally. Yeah, for sure. That is my goal. That has not, nothing's gotten in the way of that yet. And that's what I'm focused on. And I'm doing anything to set myself up the best I can for that. Yep. Seems like you're doing a pretty good job to me.

So good luck with that. And we'll be sorry to lose your work when it goes behind the mode of secrecy somewhere. But we will enjoy it until then, as we enjoyed having you on today. So thanks very much, Patrick. Yeah, thanks for having me. I appreciate it. All right. Let's take a quick break and we'll be back in just a moment

to talk with Grant Washburn of PitcherList about measuring ownership performance and unpurchased wins. In a symphony Just a simple melody Never longing to be And I just don't understand Things I've known this plan But this is how it should be How it should be How it should be

Just how it should be All right, we are joined now by Grant Washburn, who wrote a piece for Pitcher List last week called Measuring Ownership Performance, Unpurchased Wins. I believe this was his Pitcher List debut. So, Grant, you are one for one in writing something about baseball and getting invited on the podcast to talk about it. So hello. Hello. Thanks for having me. Yeah. So most of the interviews we're doing this week are about

player evaluation, and this is not, but I think it's a very important area and also maybe an understudied area and understandably understudied, I suppose, because it certainly fits into the measuring the unmeasurable idea, because this is a pretty tough one to actually put a value on. But what made you want to take a crack at this topic? Yeah, so I think a couple of things. One is that I think this time around when it comes to the union and the way that it's framing the argument in the public square is they've been doing it pretty effectively, I think, by kind of commanded how the public narrative was being told around particularly revenue sharing and competitive integrity in that respect. I think this time around, the players are doing a really good job of, you know, it seems pretty obvious, I think, to most people that the players at this are really on the side

of competitive integrity. that the players at this are really on the side of competitive integrity. And I think, well, what would it look like to incorporate wins into that kind of analysis? Because I think if we really want to talk about how teams are or are not competitive, we should really be talking. And if the MLB is willing to give us the kind of license to consider wins in terms of U.S. dollars based on this more recent proposal to replace arbitration with a war dollar figure, it just seemed like a good time to kind of put those things together and say, OK, well, what does unspent money look like in terms of wins? And there are a number of challenges here, not the least of which is that, you know, a detailed look into team finances is sort of beyond the purview of the public sphere.

But there are other concerns here in trying to come up with something that resembles what we might be familiar with on the war side when it comes to player evaluation. So what was your process here? What things did you try to measure and how did you go about doing that? Yeah. So my paper is not a Cameron Grove paper in terms of its analytic sophistication. This is very much, and as Ben referenced at the beginning, this is

my first piece. It's actually my first piece of baseball writing at all. So, you know, this was very much for me an attempt to kind of frame a question a particular way and take a stab at trying to answer it. But I think there's good reasons to do it the way that I did it. So the way I went about it was I kind of just take payroll as a percentage of revenue as kind of a fundamental ratio that can Forbes valuations that have been annually produced by Forbes magazine. Some of them are not currently on their website anymore. So I kind of just went through a bunch of old archives and found scanned documents of every previous publication, logged them, and then asked myself, okay, well, now that I have all this data, I have the payroll

numbers from the Lehman database, what would it look like to then ask, what's a sort of competitive baseline for spending payroll in proportion to revenue? What could basically become analogous to the replacement level player in a war calculation. And so I eventually came up with using the 90th percentile of payroll as a portion of revenue. And the reason I did that was because I had kind of played around with a few different ideas. The first was just to kind of base the calculation off of league averages. And I quickly started to realize that it wasn't really reflecting shifts in league-wide trends. And it wasn't really making those apparent. And that seemed problematic to me.

It also seemed just like in the case, I kind of addressed this in the piece, but whereas I think wins above replacement, an average player is generally pretty good already. Historically, as time has gone on, teams have been spending less and less of their revenue on payroll. So I wanted to be able to figure that in to the way I was presenting things. I decided that it was probably not in my best interest to just go with the highest proportion in a given year. And so I wanted to go with 90th percentile because it gave me some buffer space. We're dealing essentially with estimations from Forbes. These aren't published figures from teams. And so the idea is to take the 90th percentile in order to show kind

of an upper tier of spending, which teams have decided not to spend like, you know, teams below that percentile. And so after that, it's basically just adjusting payroll or presenting a kind of a hypothetical team payroll in proportion to that 90th percentile, subtracting actual payroll, and then dividing it by a war dollar figure based on some Van Graaff's articles. So the calculation is ultimately very simple, and it's very much a kind of a first step at taking a look at what do these figures tell us in terms of how much a team is willing to spend in order to win. And I think in a lot of ways, there are a number of things that I could have done to try to complexify that model, even with the data that we have available.

could have done to try to complexify that model, even with the data that we have available. But I actually think that there's something with payroll to revenue, there's something that is kind of fundamental about that ratio. And when you start to complexify things by trying to take into account other expenses, you quickly realize that there are a number of expenses that probably shouldn't be counted in this kind of analysis. And there are also a number of accounting tricks that make it difficult to really see where money is coming from and where it's going. So those two things made me want to take a simpler approach. And so that's the reason I went the way I did. any data that you wanted, then I guess you wouldn't have to rely on those outside estimates for one thing. But are there any other things that you wish you knew if you did want to make a more complex model and you actually had the data to do it? Yeah. So, I mean, one possibility

would be, of course, to just, I think a more fair look would include as much as we can know about expenses related to player development, expenses related to analytic departments, expenses. These are expenses that vary across teams. The differences are more marginal, so I don't think that it would ultimately affect the number two substantially, but they're there and they're real. The difficulty is, though, is that if we were to actually, we have had some examples of teams with open books. I mean, there was back in 2001, I think it was, there was the report to Congress where MLB tried to argue that it was losing millions every year.

And, you know, you can kind of look through those figures. There's some really interesting pieces in baseball perspectives. I think it's Doug Pappas. Pappas, I think. Yeah look through those figures. There's some really interesting pieces in Baseball Prospectus. I think it's Doug Pappas. Pappas, I think, yeah. Pappas, yes. And he's done a number of things in the past, I don't know, 20 years ago, to analyze those books. But you can also just look at teams like the Atlanta Braves, who have to give some kind of report annually because they are owned by, what is it, Liberty Media?

If you look at those books, you ultimately end up finding out a few things that are really interesting, which is that they have, in recent years, overshot Forbes estimates of their revenue. They include things like development revenue. Forbes also doesn't include TV stakes. So the Yankees make much more than Forbes reports, for example, having stakes in Yes Network. And then you also find various ways in which expenses are calculated that can really obscure the figures for the public and allow for a very legally honest way to say that teams are losing money. So there's a famous quote from Paul Beeston,

who was the president of the Blue Jays, where he said, with some basic accounting tricks, I can turn $4 million in revenue into $2 million in loss. And you can kind of see those on display in the Braves reports. They'll have things like based on roster depreciation allowance, They'll have things like based on roster depreciation allowance, which is something where teams are able to deduct or they're able to count as an expense toward taxes and in their financial reports. The entirety of a player's contract over the course of 15 years as a depreciating asset. And so if you look at the Braves, they'll say, oh, we're losing $74 million a year. Well, what that really means is that they're actually counting a player's contract twice. So you start seeing these kinds of things when you actually open the books and you realize maybe we could have a more complex model if we were to include competitive types of expenses. But there are also a number of ways in which the books are kind of obscuring

what I think is more fundamental, which is spending what you take in. And I think, you know, another important way, one thing that we could look at, it would be really nice to have figures of would be ownership salary numbers. One of the ways that teams talk about operational expenses, if you look at the Braves, they'll say that their team expenses are twice as much as their reported player payroll. And some of that's going to minor leagues, some of that's going to player development. They say that there are other things and we don't know what they are. But one thing that we do know is that owners often take a certain amount of profit and they count it as an expense in their books because they're taking it as a salary. So things like that would be nice to know. But unfortunately, we don't know anything about those things, except in these few instances. So except in these few instances. I'm curious where and how you think we should think about the luxury tax thresholds when we're thinking about this, because on the one hand, I'm reticent to use them the way that ownership seems keen to write as sort of a hard cap because they want there to be the tax threshold in these CBA negotiations. So I don't think that we should view it as sort of a constriction on their spending that they aren't asking for themselves.

But on the other hand, I do think that it is useful to get a sense of what is their willingness to spend around those numbers, if only to understand how often they are willing to, say, go over one or two or even three of the luxury tax thresholds versus the years when they dip down. And I realize that might be hard to sort of figure in here, but I wonder if you've thought about future iterations of this that might sort of look at those numbers relative to the luxury tax, because even if we don't take those into consideration, there is sort of some sort of upper limit that we might envision for what teams are going to spend,

even if they have an extreme willingness to spend because they only have 26 roster spots, right? And there are only so many free agents. So I'm curious how we might think about that, even just theoretically for future iterations of this exercise, because our theme this week is to bring people on who have done good work and then ask them questions

about how they would change it in the future. Yeah. Yeah. So I think one way you could go about that would be, and this is not something I did in this model. You could look at kind of how, since we're talking about a war per dollar number, there is this assumption that that is the same across spending. And that's not the case because in years where you are meeting that threshold there's a higher tax and so technically even though the payroll is a certain amount teams are looking at

this as an investment that includes that tax so one way that you could do that would be you know to adjust that war dollar figure past that mark in the calculation of the hypothetical replacement level ownership spending number. So that would be one way to go about it. As far as how I think about the luxury tax threshold in general, I think it's an example of how teams are able to use competitive balance as a means to really just suppress wages. When you look at the previous iterations of the luxury tax, they used to be based on ranks, I think, up through 2002. And then for a couple of years, they didn't have them. And then they created this new threshold system. And once that happened, you quickly started to realize that really this old antagonism between large market teams and

small market teams became very different because the small market teams weren't just taking money from owners who had spent the most. They were taking money from owners who had decided to give it to them. And what we've seen in recent years is, you know, you look at, I mentioned this in the piece, how Steinbrenner in a recent proposal from the MLB had given, I just said the MLB, so we'll get to that. Don't worry. How Steinbrenner voted in favor or at least supported a proposal to lower the luxury tax just this past year, as reported by The Athletic. And what that tells us is essentially that this old antagonism between large market teams, the famous George Steinbrenner doesn't want to subsidize Bud Selig's brewers. You know, the famous George Steinbrenner doesn't want to subsidize Bud Selig's brewers. That kind of antagonism doesn't exist in the same way because by lowering the tax threshold, Hal is able to give an excuse for why he isn't spending more. to increase the competitive value of his team. So I think that's ultimately kind of the intellectual exercise that I'm trying to bring about with this piece is really just to reflect more explicitly

on how the very structure of team ownership as it currently stands is, I think, in many ways counter to the competitive nature of the game. I think if you talk to fans, you know, oftentimes fans, you know, you see people talk about different teams spending, they want competitive balance. people talk about different teams spending, they want competitive balance. Some of them are, you know, upset by teams that spend more. Others say, well, spending to win is good. I think one thing that most people agree on is that they want to see teams trying to win. I think that's one thing that they tend to agree on. And what we see when we start taking a deeper look is that owners have realized that spending on payroll is profitable up to a certain extent and then it's not much more profitable after that

and there are more profitable ways to spend revenue past a certain competitive level and so they choose to invest elsewhere. And if that's the case, then I think it actually is in the best interest of the sport to ask, well, how do we curb that? Because if we want to have this product, which is fundamentally a competition, shouldn't we have its participants being players in the game? And owners seem to be the incentives that structure ownership are kind of moving in the opposite direction. So yeah. And you went from 2000 to 2019 here. And I guess one thing that people might be a bit surprised to see is that almost every

team is below zero, is in negative numbers here for the most recent season that you looked at. And I guess, you know, usually if you're saying, well, replacement level, they can't all be below replacement level, right? Or maybe they should be, maybe owners should all be spending more, but clearly they are not. So the owner replacement level is what it is. So is it a problem that most of the numbers are negative, I guess, for 2019, except for the Nationals and the Rockies were the only ones who were in the black there. And then the Mariners were dead even, and then everyone else was

negative. Or does that just generally reflect the fact that across the board, teams are not investing what they could at this stage of the game? Yeah, so I think, and for listeners, if you want to look, I do have a Google sheet at the bottom of the piece that links to all of the figures for 2000 to 2019. So you can see, and they're all very negative, like you say. And the reason for that is really, I mean, it's kind of baked into the calculation,

but I think it makes good sense, which is that if you can see that potential spending toward putting together a team is higher than actual spending, then really the value that an owner adds is by meeting that potential. And otherwise, there's not many other ways for the owner to actually be adding value, if that makes sense. So if you look at someone like the Nationals, they're spending, I think it's a pretty high figure in 2019. I'm forgetting the exact percentage. I have to bring it up here. But they are spending way beyond what the rest of the league is, and they have a decent revenue. And it's suggestive that

if this is a possible way to spend at that level of revenue, then we might look at other teams and say, well, what are the reasons why this isn't being spent elsewhere? And usually we can come up with various reasons that may have to do with that money being placed elsewhere and not necessarily toward organizational expenses that are baseball related. Yeah. I was going to ask, is there any evidence in your analysis that teams might go through down periods of payroll relative to revenue to then ramp up to greater spending, perhaps when they think that they're closer to a viable competitive window relative to the rest of their division or even the league? Yeah. So if you look at the whole sheet from

2000 to 2019, you do see these kinds of periods of spending and then these periods where teams aren't spending. I want to spend more time trying to identify trends there. But one trend we don't see is any relation of that kind of volatility to the team's revenue. So teams with large revenues and teams with small revenues don't necessarily spend differently as time goes on. They eat both across the board. Some of them spend in a more volatile way or less volatile way, and there's really no correlation. And the reason I think that's significant is because I think in recent years, we've become very used to the idea that in order to be competitive, a small market team or

a low revenue team in general, they would have to tank for several years. Then they can build some kind of competitive base and then they can add to it in free agency. And then they have a window of being a viable team that may be able to compete for a pennant or a ring or a division or even just to get into the playoffs. And those windows are real. There's definitely, you know, if you do, they usually last. I think there's a piece in the Sabre Research Journal where it's usually on average about five years, but sometimes it's three and sometimes it's 10.

And it really just depends on how a team builds itself for longevity. That's the issue is that I have a pretty small sample here and finding trends among 30 teams over the course of 20 years is probably going to be less. It's probably not going to yield anything definitive. I do think it's the case though that you see these periods of spending. So if you look on those sheets, you see George Steinbrenner from 2004, I think, to 2006. He's spending so astronomically that he's actually putting up very high positive win numbers. And this is when the team is, it doesn't end up winning a championship during these years, but this is when the team is very built out and there's every reason to think they'll be competitive every year. But then it fizzles out and starts up again and fizzles out.

So, yeah, I think they're there. I'm not sure what I can make out of the data that I have. But it's something that I want to explore more, try to identify trends within the data where possible. So looking at one of your leaderboards or laggard boards here of the bottom 10 current principal owners or managing partners from this 2000 to 2019 period, these are the active ones. And there are some names that almost have to be on there, or you wonder, I mean, does this method actually telling us anything, right? So to no one's surprise, I think you will see Tom Ricketts of the Cubs is on there and Bob Nutting of the Pirates is on there and Larry Dolan of Cleveland is on there and Stu Sternberg of the metric. But it's not all that. I mean, it's not just the teams with the lowest payrolls generally.

And if it were, then this would not be very useful. And there's actually a pretty good range here of payrolls and even some teams that we think of as spending more. But once you take the revenue into account, proportionally speaking, maybe it's not all that impressive. So what were some of the notable results or surprises for you? Yeah. So I think, well, I think this wasn't surprising to me. So I grew up a Yankee fan, so I definitely am very familiar with the way that the Yankees run. But I do think it's at least notable that Hal Steinbrenner during his tenure, on average, according to the metric, WBRO or WBRO, whatever you want to call it, he's been on average worth negative 17.8 wins per year.

Yeah, that's the worst. Yes, it's the worst by a lot. And over the course of the last 20 years, it's unprecedented. And the reason why is because the team's revenue has continued to increase to the point where I think at this point it's twice the league average and yet they don't always carry the highest payroll in the league and yes we can talk about organizational expenses but fundamentally that doesn't add up and and I think it's pretty obvious once you start realizing just how high that revenue is. And as I said, the Forbes estimate doesn't even include their stakes in

the TV network. So, you know, you see something like that, that stands out to me, obviously. But another is something like Jim Crane in Houston. I mean, clearly a team that's been very effective in recent years. But I think what surprised me most was just how much revenue the Astros have pulled in, given the way that they posture with regard to payroll. They're not a team that anyone expects to spend at a high level, but they could afford a lot more than they do. And so I think seeing Jim Crane as high as he is, negative 11.3 wins per year on average, that was pretty startling to me. I don't think I expected that. So, but maybe that's just because I'm, you know, not an Astros fan.

I'm sure Astros fans have been complaining for a while. Right. Yeah. I mean, the Yankees is interesting because you do still hear that refrain from Yankees fans. Oh, you know, if George were still around, et cetera, et cetera. And things weren't always great when George was around either. And it's almost like if you could combine Hal's lack of meddling with baseball operations and just lack of, you know, firing people constantly. Although some Yankees fans would like him to fire people more often. But, you, but just not

introducing that mayhem and chaos and meddling aspect with his dad's willingness to spend. Like when people say, oh, if George were still around, I mean, they are maybe taking a rosy view of what George was actually like, but they're onto something really, because there is more of a conservatism seemingly in spending and breaking the competitive balance tax threshold and all those things in the younger Steinbrenner than there was in the elder. That's right. And I think that's a really important point to emphasize here. this at the beginning of the piece, but the basic idea behind the piece is to isolate ownership as essentially looking at ownership performance essentially as a willingness to spend revenue. And that abstracts intentionally from the effectiveness of how that money is spent. So you look at someone like Stu Sternberg, who is on average negative 9.4. And you think, well, maybe that's

true, but I would expect the Rays to do a lot better with that money than anyone else in the league. Because they just, you know, organizationally, their decision making is kind of next to none. And so you'd expect that really the R raise would be more effective if given a higher payroll at spending that money. Or you look at some of the examples of teams. I think you mentioned in 2019, the Rockies are at the very top and they remain bigger spenders proportionately or pretty consistently from 2000 to 2019. But I wouldn't say that they're an effectively run organization.

2000 to 2019, but I wouldn't say that they're an effectively run organization. So this is really not a leaderboard of who's best at spending money. It's very much who's most willing to spend money. Right. Exactly. Right. And sometimes if you are unwilling to spend money and yet you hire the right people who are good at winning without spending a lot of money, then you're the race, which if you're a race fan, maybe that works out

fine for you in that respect. But all else being equal, of course, you'd rather have an owner who was willing to invest in the team. But you're right, it's not a perfect correlation there. But I think it is important to even just have a rough approximation of this because we talk all the time about little edges in game tactics or player evaluation. And really, all of that can be completely overshadowed by your ownership. If you have terrible ownership, then it's going to be tough for you to go far, even if they are willing to spend if they do other things, if they hire the wrong people, which again is not really covered. That's not in the purview of your study here. But ownership quality matters as much as or more than anything. It's just harder to assess and I guess

also maybe less productive to assess because if the study shows that you have a lousy owner, well, what are you going to do about it? They own the team. So you can't necessarily replace them, unfortunately, for Pirates fans. Right, right. And I think it's interesting you mentioned this kind of combining the sort of efficiency of spending with someone who's willing to spend. And I think in many ways, people have been talking about the Dodgers this way for the last few years. They've talked about the Dodgers as, you know, the new Yankees or something. And though I think that the Dodgers spend their money far more effectively than George Steinbrenner would. And, you know, that's partially the case. I mean, we can see that they, you know, they consistently post very high payrolls compared to the league. They're often going over the luxury tax. Sometimes you think, oh, they have such a high payroll currently, there's no way they

sign the next big free agent, and then they do. But if you look from 2017 to 2019, for example, you see that they're dropping 7.8 wins, 11.6 wins, 8 wins. And that's because in recent years, partially due to them being an effective organization, they've increased revenue by quite a bit. So really, are they anything like the Yankees 15 years ago in terms of their willingness to spend? No, not at all. Are they much more efficient at it? Yes. Do they show what's possible for a team with that kind of revenue stream? Somewhat, but they could do a lot more. And I think if anything, they just kind of shed light on the fact that at this point, there's such a low demand for spending high in free agency across the entire league that these figures can get as big as they do.

Right. Yeah. I mean, player development was the subject of our first interview today. And if you're really good at player development, the way the Dodgers have been with hitters, especially, well, then you're going to get productive players who aren't making much money. And you could just spend even more in other areas. I mean, you could go load up on free agents, but it's almost like you have fewer roster spots to improve. I mean, if you do a good enough job at player development, then it's almost hard to spend as much as you quote unquote should, because the returns will be so diminishing beyond a certain point. If you're the Dodgers, of course, there aren't that many teams that do that as well as

the Dodgers do. But that's one reason why teams are so interested in player development these days is because if you're good at that, then you can win without actually spending, which is what all owners want to do, I think. So this is a good start at measuring this, I think, as well as we can from the public perspective. And you have the full results in a spreadsheet linked from the piece, and I will link to the piece itself as well as that spreadsheet on our show page. So before we let you go, you have said the MLB a couple times during this segment, and I don't think there were any the MLBs in the article, so I suppose I can thank your picture list editor for that maybe, but I saw

after I had invited you on to talk about this piece that your Twitter bio says that you are a historian of late antique religion who loves numbers and defends saying the MLB, and when I saw that I had second thoughts about this whole segment. I'm giving a platform

to someone with dangerous ideas. Do you have an actual defense? Is this based on some theory here? Because this has been a pet peeve of ours, people who say the MLB instead of MLB. So I will say as a caveat, I don't trouble my editors. So I do think I do believe in editorial practice and standardization. And so I'm not saying I wouldn't write this way necessarily, but I do find that there's oftentimes these tweets where people are dunking on people for using the phrase the MLB. depending on what you're expecting. But for me, it's really based off of a familiarity with a lot of languages that I, you know, have to use in my day job. And just the sort of orientation that I have toward language in general, which is that, you know, linguistic rules are really just attempts to standardize a nonstandard system of communication that develops organically.

And those rules are more logical than the actual phenomenon they're trying to evaluate. And so, you know, you're talking about something like saying the MLB. Well, in general, when it comes to initialisms, in many instances anyway, we do use the before, regardless necessarily of whether or not it makes sense if we were to spell out the initials. And so, you know, there are exceptions to this, certainly, and Major League Baseball does not speak this way about itself. But I do think that it's something you can expect that that kind of usage would develop, given the fact that you have, for example, other leagues, other major sports leagues that use the end for good reason. So, yeah, it's really just based on general orientation towards language, which is that I take usage first rather than rules or logic. And then I ask myself why they developed the way that they did.

And, you know, from a personal place, like this is how I talked. And there was reason that I talked that way. So I might as well continue. reason that I talked that way. So I might as well continue. I think in general, when it comes to grammatical things like this, yeah, I guess I just tend toward defending how people speak in general. And yeah, that's how it goes. Yeah. That's a very reasonable argument. And while I do not, I will not use the MLB, I am in favor of people not being overly fussy about language just to be overly fussy. So yeah. Yeah. It's still nails on a chalkboard for me personally, but I don't want to be too much of a linguistic prescriptivist when it comes to these things. So I do understand why it happens

and everyone knows what you mean when you say it, but still just don't say it. But all right. So I read the first part of your bio there that you're a historian of late antique religion, and I'm always interested in the day jobs that baseball analysts have. And we talked to an astrophysicist earlier this week who does baseball analysis sometimes, and you're a historian of late antique religion who does baseball analysis sometimes. And your Twitter header is an image of what looks like a late religious text with a fan graphs player page superimposed over it, which I'm sure is not what it is actually like to be a historian of late antique religion. Maybe that's what you wish it were like, but what does that actually entail?

Yeah. So yeah, I study second and third century, largely Christian texts as the primary objects of kind of my historical work. But a lot of what I do is kind of in relation to or adjacent to the field of comparative religion. So what that means is basically just the kind of comparative analysis of how different religious thought, practice, worship, et cetera, how're related to each other, or how we can put them in relation to each other. And what I do is I look at these kind of second and third century texts, and I try to ask how these texts are trying to orient themselves in relation to

other cultural practices, and find commonality, find differentiation and all sorts of things like that. What it looks like on the day-to-day is, you know, trying to reconstruct a bunch of things that don't exist anymore. So I spend a lot of time, you know, reading texts in Latin that are translations of texts that originally were written in Greek, and then just kind of cross-referencing what we have and what we don't have, and looking at old, largely medieval, copied manuscripts of all of these texts and trying to see whether or not the decisions of scholars in the 18th or 19th century about how they print those manuscripts on paper, whether or not they

hold up to scrutiny. So in many ways, I guess I do identify with my banner on my Twitter page, which is, you know, throughout the day, I'm looking at either digitized manuscripts or fan graphs pages. And in either case, it's kind of my sacred text so well we appreciate that and uh are glad we can give you a little distraction during your day so thank you very much for coming on and you can find grant on twitter at throwing gas underscore g-a-s-s-E. And we will link to this study as well. Thank you very much, Grant. Thank you. Really appreciate being on.

All right. By the way, one thing that I didn't mention in the first segment about player development, I'm interested in trying to quantify the improvement in player development in recent years. That was sort of outside the scope of Patrick's study, which was about comparing teams. I'm interested in comparing eras. And I did ask Patrick to take a look at that, and he did. And he couldn't find anything that seemed super significant to him in terms of recent improvement in the 2007 to 2021 data set he was using. It should be there.

I think it's just tough to detect because, of course, sports is sort of a zero-sum game. If you're improving pitcher development and improving hitter development it might not be obvious that both are developing better than they used to because they're playing each other so he looked at raw mean and 90th percentile outcomes and standard deviations and rate of over performers and nothing really jumped out i don't know what the best way to look for an era effect in player development would be. It would be surprising, I think, if you did not see some improvement in player development given the total overhaul in methods and the improvements in technology

and the greater investments that teams have made. I think it's just teasing out the signal there. Maybe you could look for more breakouts, for instance, the rates of large improvements. But then again, if everyone is improving at player development, then you might not see huge leaps because people would just be making slow and steady gains or would not be going zero to 60. So if anyone sees any studies on quantifying the improvement in player development across the sport in recent years, I would be very interested in any work along those lines. It's just all relative, which is

the problem. It's like looking relative, which is the problem. It's like looking at stats at the major league level. Obviously players are more athletic and skilled and talented and better at baseball today than they were a long time ago, but they're also playing opponents who are better, and so the stat lines might look similar. You have to do more complex analyses to try to track that improvement over time. And that kind of thing has been done, and I've written about that before. But player development's a bit stickier.

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on Reddit at r slash Effectively Wild. Thanks to Dylan Higgins for his editing and production assistance. And we will be back with one more episode before the end of the week. Talk to you then. Outro Music