Alter Everything Podcast

MaddieJ · ‎06-04-2019

We're joined by Stan Van Gundy, former head coach and president of basketball operations for the Detroit Pistons and analyst for the NBA for a chat about the past, present, and future of basketball analytics.

Panelists

Neil Ryan - @NeilR LinkedIn

Stan Van Gundy

Topics

Community Picks

Stan:

Neil:

SprawlBall: A Visual Tour of the New Era of the NBA (excerpt)

Transcript

Episode Transcription

NEIL: 00:13	[music] Welcome to Alter Everything, a podcast about data science and analytics culture. I'm Neil Ryan, and I'll be your host. We're joined by Stan Van Gundy, legendary NBA coach and executive, for a chat about the past, present, and future of sports analytics. Let's get started. [music]
NEIL: 00:45	Stan, welcome to the show. Thanks so much for joining us.
STAN: 00:50	It's a pleasure to be here.
NEIL: 00:52	Yeah. Well, I'm a massive, lifelong NBA fan. So it's an honor for me to be able to talk to you at all. This is a data and analytics podcast, so we might actually have some listeners that don't know who you are. So for their benefit, could you just tell us a little bit about yourself.
STAN: 01:13	Yeah. Well, I'm not coaching right now, but my career has been as a basketball coach, 14 years in college basketball and a little over 20 years in the NBA, 11 of them as a head coach in Miami, Orlando, and Detroit.
NEIL: 01:35	So I think I first became a fan of yours back in those Orlando days. I was a big fan of Dwight Howard. And honing in on the theme of the show data and analytics, to me, that was one of the first times I had seen kind of that real emphasis on the inside-outside game. If you're not going to get a dunk, you might as well get a three-pointer. Was that how you were thinking about it, or was that just kind of a matter of the personnel you had at the time?
STAN: 02:13	Yeah. It's a little bit of both. I mean, it certainly was at the very beginning of the three-pointer becoming a bigger part of the game. We had a team with Dwight Howard, a great big guy, that defenses had to collapse into the paint to try to take away his scoring, which opened up three-point shooting. And then if you could make threes, then the paint would open back up for Dwight. And so things sort of worked in tandem. But that was the first time that I remember really starting to give some of the analytic type information to our players. And so we did talk about what the most efficient shots were. At least from a league-wide perspective is the way we started with the most efficient shot being the free throw.
STAN: 03:13	So if we can get fouled and get to the free throw line, we're going to get about a point and a half per position. If we can get a layup, which was anything inside three feet, that little arc you see near the basket, that was going to be a 61% shot at that time and pretty close to that now in the NBA. So we're going to get 1.2 points per one of those shots. And at that time, the three-point shot, overall, was about 37%. And so we were going to get about 1.1 points per possession. And we brought that out to guys but then also individualized it to what their abilities were and everything else to talk about the best shots that we could do-- that we could get as a team. So that was sort of the start of us using it with our players. I mean, we've used the analytics in the past in a player personnel type of area to try to decide which players you want on your team to trade or to sign as free agents, to draft, things like that. But my time in Orlando was the first time we sat down with the players and tried to get them to understand the analytics behind our offensive and defensive philosophies.
NEIL: 04:40	Cool. So that was kind of when you started first talking about it with your team. Do you think that's kind of league-wide; that's about when it started catching on like that as well?
STAN: 04:52	Yeah. I think it's only increased from there, and always there's people probably ahead of the game and behind the game. I'm not sure that we were ahead of the game. We were probably right there in the middle. But I think it started with most people with that whole shot efficiency type of analysis: what types of shots are best for us to get as a team; what do we need to prevent, in general, when we're developing a defensive system. That sort of thing I think is where it started.
NEIL: 05:32	Yeah. I'm trying to think-- I'm trying to compare in my head when that was compared to when Moneyball was written. I'm wondering if that's when analytics started catching on across all of professional sports, or that's just when it started getting big in basketball.
STAN: 05:49	Well, baseball's always been ahead of basketball. There's no question about that. I mean, you can go back to Bill James writing the Baseball Abstract, goes back many years, and he was probably the first guy to really get deep into the analytics. And baseball I think is far ahead of everyone even now in terms of what they do with analytics. Part of it is the structure of the game in that the game is a little easier to track. It starts always with a one-on-one matchup between the pitcher and the hitter. Every play is isolated. The game is not as fast and up and down. And so baseball's always been ahead. But I do think that Moneyball's emphasis on trying to find market inefficiencies and trying to find things that were important to winning and success that were not the things that, at least at that time, that are commanding big money would give you a chance to compete on a budget. And so I think the other sports have picked up on that, albeit a little bit slower.
NEIL: 07:09	What about in terms of--? You said baseball's always been ahead in the use of analytics. What sport do you think it's had the most impact on the game itself? I read something recently that home runs have gone up a lot since analytics have gotten bigger in baseball, but not nearly to the extent that three-pointers have gone up in the last few years in basketball.
STAN: 07:39	Yeah. I would still say it's probably-- I mean, it's affected basketball a lot, Neil, but I would still say probably baseball the most. Even beyond the home runs, now you see a lot of shifting of the infield in baseball, particularly against left-handed hitters. Every at bat, they pretty much are positioning the fielders based on their analytic information of where a guy hits certain pitches and things like that. We don't have it quite to that degree, but it has changed our game to the point of-- obviously, the three-pointers have increased. And what's really decreased is shots in the mid-range, everything from four feet to the three-point arc; shots that, quite honestly, when I was coming up playing the game, or anybody was at that time, shots that you used to work hard to try to get, and that teams and their execution try to get and individual players worked on, pull up jump shots from 15 feet. Those have become almost taboo on a lot of teams in the league.
STAN: 08:59	I mean, the Houston Rockets is probably the biggest example. They've got two years in a row now where they've shot more threes than twos. They literally don't want those shots at all. They either want to lay up, or they want a three-pointer, or they want to get to the free throw line. And it's a failed possession for them if they end up with a mid-range jump shot, a short runner, or anything like that. So it's definitely changed the game. It's changed the way players work on their skill development and everything else. And I think it's only going to continue in that direction. I don't think we're going to turn back.
NEIL: 09:41	Well, speaking as a fan rather than a coach, is that good? Do you think that needs fixing, the loss of the mid-range? Is that hurting the game?
STAN: 09:52	Well, I do think it's hurting the game, not so much from losing the mid-range but with the emphasis on the three-pointer-- when I first came in the league in the mid '90s as an assistant, I remember the rules were different at the time too, but certainly so was the offensive approach and-- you'd have four, five, six plays a game with these great athletes challenging a shot blocker where it's going to end up in a dunk or a block shot, and we don't see much of that anymore. I mean, it's pretty rare. If you have a full slate of NBA games on a night in the regular season, the highlights the next day, you might get one or two of those because now, I drive the ball, and if I'm going to be challenged at all, I'm just throwing the ball out to somebody stationed behind the three-point line, and they're shooting a three. And so to me, as a fan, it's not exciting to watch guys stand around shooting long-range shots. What's exciting is the athleticism of these great players. And I think it's a better game when we're seeing more of that and less of the stationary shooters. But the analytics will show you that the way the game is being played now is the most efficient way to play. It gives you your best chance to win, and that's your job. So I don't know what could be done to change it, but I don't think our game is as exciting as it could be at this point.
NEIL: 11:30	What about a rule change? Do you think we'll have any of those--? I mean, the three-point shot wasn't always a thing, right? They implemented it around 1980. Is it time to move the three-point line back or make a four-point shot or something like that?
STAN: 11:45	Well, I don't think we want a four-point shot [laughter]. That's going to encourage more long-way shooting. There has been talk of moving the line back, or there has been talk of keeping the line at the same distance all the way around. Because of the width of our court and having to fit the line in, you get a shorter shot in the corner. If you see an NBA arc, it arcs around to just below the free throw line, and then you get a straight line down from there to the corner. And so the corner three-pointer is a more efficient shot because it's a shorter shot. There has been some talk of just keeping the line at 23 feet 9 inches all the way around would sort of make the corner shot almost an impossible shot to even get off from three. I think that could be a good thing for the league. But I don't think we're going to see a change anytime soon. I think the league tends to equate scoring with excitement, and scoring is up. They think that's exciting. I don't necessarily think the two correlate, but I think the people in charge do.
NEIL: 13:03	Okay. So which one do you like better, the making the distance the same all the way around or even extending the distance so that the value of the shot is about the same as the value of a two-point shot?
STAN: 13:16	Yeah. I think either one would be effective to at least reducing the role of three-pointers a little bit. I don't think it's a great game when we have one of our better teams that's taking more threes than twos. Look, I mean, this is an exaggeration, but if we go watch a bunch of middle-aged men play pickup games at the YMCA, we're going to see them stand around and shoot long-range set shots. I don't think that's what we want to watch when we get our best athletes on the floor. But again, Neil, I'm a little bit in the minority here. I think the people in charge like the way the game is now. There is no problem with TV ratings or attendance or anything else. And so I guess the old line about "If it's not broke, don't fix it" is applying to the NBA at this point.
NEIL: 14:21	I'm in that old-men YMCA game, by the way.
STAN: 14:24	Yeah. There you go. I mean, I don't play much anymore, but if I go down and shoot on my basket outside, I mean, that's what I'm going to do. I'm going to stand up there and fire long-range shots. Now, granted NBA players are going to do it at a high level, and you can certainly appreciate the skill involved. But I think that's different than the excitement of great athleticism, the quickness, the speed, the jumping ability, and everything else. So hopefully, it will all start to balance out, but I think that's going to take a lot of time and a lot of adjustment probably on the defensive end of things before we see more of that again.
NEIL: 15:10	Where do you think the players kind of stand on this right now? Obviously, to a good extent, they're buying in, right? Harden doesn't take those mid-range twos. Curry doesn't take many of them. But then at the same time, I think I saw LeBron took it at the end of the game last round. See, that's why I don't buy into the analytics. At the end of a game, a two-point shot is going to win you the game. So do you think they're wishing it was kind of going back to the old days a little bit too?
STAN: 15:44	Well, I think the players have a general understanding of the value of getting to the basket for layups and getting at the free throw line and having spacing on the floor and shooting threes. But they don't like hearing about the numbers all the time and the firm adherence to it. And look, I also think what we're seeing now in the playoffs-- I think the playoffs change things because you're playing against the best defenses who are also working hard to take away those high-efficiency shots. And so what you're left with a lot is a mid-range jump shot, and we're seeing great success from Kevin Durant, before he got hurt, shooting a lot of mid-range jump shots and Kawhi Leonard with Toronto, and they're the two highest-scoring players in the playoffs. So at the highest levels of our competition, the mid-range shot comes back to a level of importance. And that's why LeBron James and other players will point that out because I think they want to go out and play basketball, and I think that they look at some of the analytics as trying to make them almost robotic, and they fight it a little bit even though I think their generalized understanding of things is pretty good.
NEIL: 17:10	I want to switch gears a little bit and ask you about front offices because it's kind of mysterious to me. I know there are analytics departments in NBA teams now. But what are they like? How big are analytics departments? What kind of skills do these people have, and how do they work with the GMs and the coaches?
STAN: 17:33	Yeah. It varies; certainly the size does. I mean, I think you've got Philadelphia probably being the biggest analytics department in the league, and I think they have 10 or 11 people now, several of them with PhDs, highly, highly educated people. I mean, there's a real rush to hire people from the MITs of the world to come in and do these things. Some of the departments will be fairly small, two, three people. It's started out I think with what people did is they got a lot of kids right out of college, very bright people, but that they could get pretty cheaply, and they weren't spending a lot of money on it. Now, there's people running analytics departments making as much as $600,000 a year. So its importance in the league, and I think that they'll help with coaching decisions, but the real crux of the thing is trying to find the best players for your team.
STAN: 18:49	And so the two areas people are really working on now and have been for a long time is real predictive analysis on players. Certain types of players will maintain performance for a longer period of time. Let's say smaller players who rely on quickness, they tend to have their performance decrease pretty quickly when they hit about 30 years old because the quickness starts to go. Bigger players tend to be able to continue pretty consistent performance for longer because 7 feet is still 7 feet, and quickness isn't as big a deal. And those are just two of the extreme examples. But trying to predict, "We're going to sign this guy to a four-year contract. What's his performance going to look like in year four?"
STAN: 19:56	And then the second thing I think that is really big is are there things we can do to prevent injuries to players. And you hear a lot of talk now in the NBA throughout the regular season. You see teams resting their best players even when they're fully healthy. The term that comes up all the time is load management. And they're literally tracking-- we can't do it in games, but in practice, they're literally wearing GPS devices and everything else to track the amount of work: how far they run, at what speed; how high they jump. All of these things to calculate the load they're putting on their bodies and trying to find what are the optimal loads. When are we getting so far into too much work where a guy needs some rest, or he is in danger of being hurt? But we've got to do enough work to optimize conditioning, so he doesn't get hurt from being out of shape. That's sort of the holy grail right now-- I think of the analytics, at least in the NBA, is the whole injury prevention, load management type of stuff.
NEIL: 21:18	What about when you were-- we didn't get to this in the intro but-- I think you introduced yourself as a coach. But with the Pistons, you were president. You were running things as well, right? What was your analytics department like then?
STAN: 21:34	We came into, basically, having one person. We increased to three before we left and raised salaries and things. And look, I think that most of our use and probably the biggest use in the NBA is in terms of player personnel selection: who you're going to draft; who you want to trade for; who do you want to sign as free agent; what's the best cost of players and things like that. And so what you're really looking for is predictive analytics. Can we take individual players and predict based on their size, position, age, wear and tear, what they've done previously-- can we predict what they will be like, the performance we'll get not only at the beginning of their contract, but if it's a four-five year contract, what it will look like at the end? That's one of the important uses.
STAN: 22:33	And then really now I think in the NBA, the holy grail of analytics departments is trying to figure out how we minimize injury because, obviously, your greatest assets are your best players, and having them on the floor for more games and more minutes is going to go a long way in determining your success. And what we're trying to do is players wear-- a lot of them do wear GPS monitors actually during practice, and you're monitoring how far they run in a given practice, how fast they run, how much acceleration, deceleration, how high are they jumping, how often are they at maximum effort and calculating within that what is the total load that these players are taking on, and how much is too much. If you get too much, you're more susceptible to injury. At the same time, if you do too little, now you're not conditioned highly enough, and you're also vulnerable to injury. So where does the line-- where is the line of where you want to be in terms of how much work you give these players to do? Everybody is trying to figure that out at this point.
NEIL: 24:06	So the past of analytics in NBA franchises was kind of two-point versus three-point shot. The present is figuring out the best players to draft. And the future is player health. Am I getting that right?
STAN: 24:23	I think you're right on that. I mean, it's still all of the other stuff because it's also which lineups work best together, which five person units work best together so you know who you need to put out there among your stars. I mean, it's a little bit of everything. The amount of information is overwhelming. Every NBA arena now required-- every NBA arena has a system of cameras in them that are-- it's automatic. There's no camera operators. There's small cameras. And so every movement in an NBA game is tracked. So at the end of any NBA game, a coach can get a printout on how many miles a certain guy ran, at what speed. You know every shot how close the nearest defender was. So was it an open shot, or was there somebody close to him? When it was somebody close to him, which defender was the closest? Are there certain defenders that are tougher to score on than others? I mean, the amount of information that is available to coaches and executives in the NBA is phenomenal. And the real challenge is figuring out what's most important, what can be most helpful to you in terms of winning and losing games and finding the best players and keeping them healthy and all of that because every team is privy to a lot of information.
NEIL: 25:59	Yeah. I guess, yeah, there's so much data out there. You have to know what questions to ask. I wanted to ask about your time at the Pistons. I believe when you were with the Pistons, you were one of only five people coaching and being responsible for player personnel. What is that like? I mean, I guess at a high level, you're talking about balancing long-term strategy versus short-term tactics, and I guess there can be some give and pull there. But how did you get around that potential conflict of interest?
STAN: 26:40	Yea. Well, I mean, I think I went out and hired a very good general manager, Jeff Bower, who had actually done both jobs simultaneously when he was in New Orleans. He held about every job in the league but had been a general manager and a successful one with New Orleans. And he really ran the front office on a day-to-day basis. If there was a decision to be made on a trade or a free agent signing-- he compiled all the scouting information, all the analytic information, made his recommendations, and I just had to give a final yes or no, and I don't think he and I very often disagreed. So I wasn't really doing both jobs. I just had final say. I think the advantage to it-- and it's not really in vogue. In fact, I don't think anybody is doing it now that Tom Thibodeau got fired in Minnesota during the season. I don't think any team has somebody doing both. It's not in vogue. I thought it was good because at least we had an overall philosophy, and we were all on the same page. What you have in a lot of situations is you have different philosophies. There's not a lot of synergy between the front office and the coaching staff. And then what happens is when things don't go well, it's basically the front office wanting to blame the coaches, the coaches wanting to blame the front office. When you have one person in charge of everything, you don't have any of that going on. So I think there are advantages to it also.
NEIL: 28:27	And then since then, did I read correctly? Did you just finish teaching a semester at Stetson University?
STAN: 28:33	I did. I taught one class one night a week for three hours on just contemporary issues in sports, and we did a couple of weeks on analytics, salary cap, those types of things when we did the actual sports side of the business, looking at all the different leagues. And the feedback was from the students that that was their favorite part of the course because it was new information for a lot of them.
NEIL: 29:06	Nice. So you've done a lot of stuff. Now, you've been coaching for a long time. You did the GM thing. You taught a course. What's the proudest moment of your career so far?
STAN: 29:17	Oh, you know what? That's really hard. I've been at this a long time. And it would probably go back to actual college coaching and-- my wife and I had gone to a reunion of a small college team that I coached back in the early '80s. We went there a year and a half ago and had all those guys come back. And to be honest, the proudest is when you see all the people that played for you there and how well they are doing. That's the proudest moment.
NEIL: 29:54	All right. Stan, I can't let you go before I ask you to make a prediction here. So as we're recording right now, the Raptors and the Bucks are locked up two to two. Who do you got for that series?
STAN: 30:11	I've got the Bucks winning it in seven games. I've been on the Bucks all year, so I'll stick with them now even though they had two tough ones in Toronto.
NEIL: 30:23	They're just going to-- both teams are just going to keep winning on their home court until it's over.
STAN: 30:27	I think so. Yeah. I think so. I think Milwaukee will win their two home games and win it. I think whoever wins it will beat Golden State in the finals, and I've been making that prediction for a couple of months.
NEIL: 30:40	You think they're going to beat Golden State?
STAN: 30:42	I do. I just don't think Golden State is the best team. Now, they have done some phenomenal things since Kevin Durant got hurt that make you sort of second guess yourself when you make that prediction. But I'll stick with it because I really do believe that Milwaukee is the best team out there, and I think Toronto is the second best team out there.
NEIL: 31:03	Wow. Okay. That's a bold one. I'm glad I got you-- I'm glad I asked the question. All right. All right. Here we got the last segment of the show, the community picks. What's your pick, Stan?
STAN: 31:18	Well, look. At this time of the year, with college graduations going on, and I just had a daughter graduate, I love to go on and listen to commencement speeches. Nobody remembers who actually gave their own commencement speech, but I like listening to them. And so I'll give you two real quick. One from this year that I thought was really, really good was Savannah Guthrie from the Today show at George Washington University. But my all time favorite, and I listen to it every year when it comes this time of the year, Michael Lewis at Princeton University, 2012. You can get it on YouTube. It's about 13 minutes long, and it's him talking about the role of luck in both life and careers. And Michael Lewis, of course, you know is the guy who wrote Moneyball that you mentioned earlier; the best commencement speech I have ever heard.
NEIL: 32:15	Oh, wow. Cool. I'll check that out. I was actually just at GW. I'll give a shot at-- my little brother graduated from law school there, but I did not get a chance to watch the commencement speech because my toddlers were going nuts, and I had to take them outside, so [laughter]. My pick for the week is a new book on the NBA out pretty recently, SprawlBall by Kirk Goldsberry. So we were talking at length earlier about the evolution of the three-point shot. And so Kirk Goldsberry, long-time writer, professor, geographer [laughter], he's got a cool new book with a lot of cool illustrations talking about that evolution. So we'll put these links in the show notes. Stan, thanks again. I really can't thank you enough for joining the show. I'd love to talk about basketball with anybody, but I think this is definitely the best basketball conversation I've ever had. So thanks again.
STAN: 33:21	Thank you, Neil. Appreciate it. [music]
S3: 33:35	Thanks for tuning in to Alter Everything. To share your thoughts and ideas for future episodes, join us at community.alteryx.com/podcast or reach us on Twitter using the #AlterEverythingPodcast. Have a unique story to tell? Send us an email at podcast@alteryx.com. Catch you next time. [music]
NEIL: 34:06	Well, Stan. You are by far the highest profile guest we've had on the show so far. But it was through Libby, my boss's boss that we got you on here. So what's your relationship with her?
STAN: 34:24	Okay. Well, I coached at Castleton State College in Vermont and met my wife there. My wife was working at admissions. My wife and Libby both graduated from Castleton State and were best friends in college. And I met Libby through my wife, and Libby was in our wedding 31 years ago.
NEIL: 34:50	Do you have any funny stories about Libby? Libby is pretty, I'll say, serious at work. I'd like to know what she's like at a wedding.
STAN: 35:02	Yeah. You know what? I don't have any funny stories. And I'm going to be honest, Neil. If I had one, I would not [laughter] do that to her on this podcast. So yes. I would not do that to her, and I would hope she would not do it to me, so. And you never want to mess with the boss. That's something I think we all need to learn in our careers.
NEIL: 35:25	All right. I guess you've probably just saved my job.
STAN: 35:28	Yes. Probably.
NEIL: 35:29	All right [laughter]. Thanks again, Stan.
STAN: 35:31	No problem.

NEIL: 00:13 [music] Welcome to Alter Everything, a podcast about data science and analytics culture. I'm Neil Ryan, and I'll be your host. We're joined by Stan Van Gundy, legendary NBA coach and executive, for a chat about the past, present, and future of sports analytics. Let's get started. [music] NEIL: 00:45 Stan, welcome to the show. Thanks so much for joining us. STAN: 00:50 It's a pleasure to be here. NEIL: 00:52 Yeah. Well, I'm a massive, lifelong NBA fan. So it's an honor for me to be able to talk to you at all. This is a data and analytics podcast, so we might actually have some listeners that don't know who you are. So for their benefit, could you just tell us a little bit about yourself. STAN: 01:13 Yeah. Well, I'm not coaching right now, but my career has been as a basketball coach, 14 years in college basketball and a little over 20 years in the NBA, 11 of them as a head coach in Miami, Orlando, and Detroit. NEIL: 01:35 So I think I first became a fan of yours back in those Orlando days. I was a big fan of Dwight Howard. And honing in on the theme of the show data and analytics, to me, that was one of the first times I had seen kind of that real emphasis on the inside-outside game. If you're not going to get a dunk, you might as well get a three-pointer. Was that how you were thinking about it, or was that just kind of a matter of the personnel you had at the time? STAN: 02:13 Yeah. It's a little bit of both. I mean, it certainly was at the very beginning of the three-pointer becoming a bigger part of the game. We had a team with Dwight Howard, a great big guy, that defenses had to collapse into the paint to try to take away his scoring, which opened up three-point shooting. And then if you could make threes, then the paint would open back up for Dwight. And so things sort of worked in tandem. But that was the first time that I remember really starting to give some of the analytic type information to our players. And so we did talk about what the most efficient shots were. At least from a league-wide perspective is the way we started with the most efficient shot being the free throw. STAN: 03:13 So if we can get fouled and get to the free throw line, we're going to get about a point and a half per position. If we can get a layup, which was anything inside three feet, that little arc you see near the basket, that was going to be a 61% shot at that time and pretty close to that now in the NBA. So we're going to get 1.2 points per one of those shots. And at that time, the three-point shot, overall, was about 37%. And so we were going to get about 1.1 points per possession. And we brought that out to guys but then also individualized it to what their abilities were and everything else to talk about the best shots that we could do-- that we could get as a team. So that was sort of the start of us using it with our players. I mean, we've used the analytics in the past in a player personnel type of area to try to decide which players you want on your team to trade or to sign as free agents, to draft, things like that. But my time in Orlando was the first time we sat down with the players and tried to get them to understand the analytics behind our offensive and defensive philosophies. NEIL: 04:40 Cool. So that was kind of when you started first talking about it with your team. Do you think that's kind of league-wide; that's about when it started catching on like that as well? STAN: 04:52 Yeah. I think it's only increased from there, and always there's people probably ahead of the game and behind the game. I'm not sure that we were ahead of the game. We were probably right there in the middle. But I think it started with most people with that whole shot efficiency type of analysis: what types of shots are best for us to get as a team; what do we need to prevent, in general, when we're developing a defensive system. That sort of thing I think is where it started. NEIL: 05:32 Yeah. I'm trying to think-- I'm trying to compare in my head when that was compared to when Moneyball was written. I'm wondering if that's when analytics started catching on across all of professional sports, or that's just when it started getting big in basketball. STAN: 05:49 Well, baseball's always been ahead of basketball. There's no question about that. I mean, you can go back to Bill James writing the Baseball Abstract, goes back many years, and he was probably the first guy to really get deep into the analytics. And baseball I think is far ahead of everyone even now in terms of what they do with analytics. Part of it is the structure of the game in that the game is a little easier to track. It starts always with a one-on-one matchup between the pitcher and the hitter. Every play is isolated. The game is not as fast and up and down. And so baseball's always been ahead. But I do think that Moneyball's emphasis on trying to find market inefficiencies and trying to find things that were important to winning and success that were not the things that, at least at that time, that are commanding big money would give you a chance to compete on a budget. And so I think the other sports have picked up on that, albeit a little bit slower. NEIL: 07:09 What about in terms of--? You said baseball's always been ahead in the use of analytics. What sport do you think it's had the most impact on the game itself? I read something recently that home runs have gone up a lot since analytics have gotten bigger in baseball, but not nearly to the extent that three-pointers have gone up in the last few years in basketball. STAN: 07:39 Yeah. I would still say it's probably-- I mean, it's affected basketball a lot, Neil, but I would still say probably baseball the most. Even beyond the home runs, now you see a lot of shifting of the infield in baseball, particularly against left-handed hitters. Every at bat, they pretty much are positioning the fielders based on their analytic information of where a guy hits certain pitches and things like that. We don't have it quite to that degree, but it has changed our game to the point of-- obviously, the three-pointers have increased. And what's really decreased is shots in the mid-range, everything from four feet to the three-point arc; shots that, quite honestly, when I was coming up playing the game, or anybody was at that time, shots that you used to work hard to try to get, and that teams and their execution try to get and individual players worked on, pull up jump shots from 15 feet. Those have become almost taboo on a lot of teams in the league. STAN: 08:59 I mean, the Houston Rockets is probably the biggest example. They've got two years in a row now where they've shot more threes than twos. They literally don't want those shots at all. They either want to lay up, or they want a three-pointer, or they want to get to the free throw line. And it's a failed possession for them if they end up with a mid-range jump shot, a short runner, or anything like that. So it's definitely changed the game. It's changed the way players work on their skill development and everything else. And I think it's only going to continue in that direction. I don't think we're going to turn back. NEIL: 09:41 Well, speaking as a fan rather than a coach, is that good? Do you think that needs fixing, the loss of the mid-range? Is that hurting the game? STAN: 09:52 Well, I do think it's hurting the game, not so much from losing the mid-range but with the emphasis on the three-pointer-- when I first came in the league in the mid '90s as an assistant, I remember the rules were different at the time too, but certainly so was the offensive approach and-- you'd have four, five, six plays a game with these great athletes challenging a shot blocker where it's going to end up in a dunk or a block shot, and we don't see much of that anymore. I mean, it's pretty rare. If you have a full slate of NBA games on a night in the regular season, the highlights the next day, you might get one or two of those because now, I drive the ball, and if I'm going to be challenged at all, I'm just throwing the ball out to somebody stationed behind the three-point line, and they're shooting a three. And so to me, as a fan, it's not exciting to watch guys stand around shooting long-range shots. What's exciting is the athleticism of these great players. And I think it's a better game when we're seeing more of that and less of the stationary shooters. But the analytics will show you that the way the game is being played now is the most efficient way to play. It gives you your best chance to win, and that's your job. So I don't know what could be done to change it, but I don't think our game is as exciting as it could be at this point. NEIL: 11:30 What about a rule change? Do you think we'll have any of those--? I mean, the three-point shot wasn't always a thing, right? They implemented it around 1980. Is it time to move the three-point line back or make a four-point shot or something like that? STAN: 11:45 Well, I don't think we want a four-point shot [laughter]. That's going to encourage more long-way shooting. There has been talk of moving the line back, or there has been talk of keeping the line at the same distance all the way around. Because of the width of our court and having to fit the line in, you get a shorter shot in the corner. If you see an NBA arc, it arcs around to just below the free throw line, and then you get a straight line down from there to the corner. And so the corner three-pointer is a more efficient shot because it's a shorter shot. There has been some talk of just keeping the line at 23 feet 9 inches all the way around would sort of make the corner shot almost an impossible shot to even get off from three. I think that could be a good thing for the league. But I don't think we're going to see a change anytime soon. I think the league tends to equate scoring with excitement, and scoring is up. They think that's exciting. I don't necessarily think the two correlate, but I think the people in charge do. NEIL: 13:03 Okay. So which one do you like better, the making the distance the same all the way around or even extending the distance so that the value of the shot is about the same as the value of a two-point shot? STAN: 13:16 Yeah. I think either one would be effective to at least reducing the role of three-pointers a little bit. I don't think it's a great game when we have one of our better teams that's taking more threes than twos. Look, I mean, this is an exaggeration, but if we go watch a bunch of middle-aged men play pickup games at the YMCA, we're going to see them stand around and shoot long-range set shots. I don't think that's what we want to watch when we get our best athletes on the floor. But again, Neil, I'm a little bit in the minority here. I think the people in charge like the way the game is now. There is no problem with TV ratings or attendance or anything else. And so I guess the old line about "If it's not broke, don't fix it" is applying to the NBA at this point. NEIL: 14:21 I'm in that old-men YMCA game, by the way. STAN: 14:24 Yeah. There you go. I mean, I don't play much anymore, but if I go down and shoot on my basket outside, I mean, that's what I'm going to do. I'm going to stand up there and fire long-range shots. Now, granted NBA players are going to do it at a high level, and you can certainly appreciate the skill involved. But I think that's different than the excitement of great athleticism, the quickness, the speed, the jumping ability, and everything else. So hopefully, it will all start to balance out, but I think that's going to take a lot of time and a lot of adjustment probably on the defensive end of things before we see more of that again. NEIL: 15:10 Where do you think the players kind of stand on this right now? Obviously, to a good extent, they're buying in, right? Harden doesn't take those mid-range twos. Curry doesn't take many of them. But then at the same time, I think I saw LeBron took it at the end of the game last round. See, that's why I don't buy into the analytics. At the end of a game, a two-point shot is going to win you the game. So do you think they're wishing it was kind of going back to the old days a little bit too? STAN: 15:44 Well, I think the players have a general understanding of the value of getting to the basket for layups and getting at the free throw line and having spacing on the floor and shooting threes. But they don't like hearing about the numbers all the time and the firm adherence to it. And look, I also think what we're seeing now in the playoffs-- I think the playoffs change things because you're playing against the best defenses who are also working hard to take away those high-efficiency shots. And so what you're left with a lot is a mid-range jump shot, and we're seeing great success from Kevin Durant, before he got hurt, shooting a lot of mid-range jump shots and Kawhi Leonard with Toronto, and they're the two highest-scoring players in the playoffs. So at the highest levels of our competition, the mid-range shot comes back to a level of importance. And that's why LeBron James and other players will point that out because I think they want to go out and play basketball, and I think that they look at some of the analytics as trying to make them almost robotic, and they fight it a little bit even though I think their generalized understanding of things is pretty good. NEIL: 17:10 I want to switch gears a little bit and ask you about front offices because it's kind of mysterious to me. I know there are analytics departments in NBA teams now. But what are they like? How big are analytics departments? What kind of skills do these people have, and how do they work with the GMs and the coaches? STAN: 17:33 Yeah. It varies; certainly the size does. I mean, I think you've got Philadelphia probably being the biggest analytics department in the league, and I think they have 10 or 11 people now, several of them with PhDs, highly, highly educated people. I mean, there's a real rush to hire people from the MITs of the world to come in and do these things. Some of the departments will be fairly small, two, three people. It's started out I think with what people did is they got a lot of kids right out of college, very bright people, but that they could get pretty cheaply, and they weren't spending a lot of money on it. Now, there's people running analytics departments making as much as $600,000 a year. So its importance in the league, and I think that they'll help with coaching decisions, but the real crux of the thing is trying to find the best players for your team. STAN: 18:49 And so the two areas people are really working on now and have been for a long time is real predictive analysis on players. Certain types of players will maintain performance for a longer period of time. Let's say smaller players who rely on quickness, they tend to have their performance decrease pretty quickly when they hit about 30 years old because the quickness starts to go. Bigger players tend to be able to continue pretty consistent performance for longer because 7 feet is still 7 feet, and quickness isn't as big a deal. And those are just two of the extreme examples. But trying to predict, "We're going to sign this guy to a four-year contract. What's his performance going to look like in year four?" STAN: 19:56 And then the second thing I think that is really big is are there things we can do to prevent injuries to players. And you hear a lot of talk now in the NBA throughout the regular season. You see teams resting their best players even when they're fully healthy. The term that comes up all the time is load management. And they're literally tracking-- we can't do it in games, but in practice, they're literally wearing GPS devices and everything else to track the amount of work: how far they run, at what speed; how high they jump. All of these things to calculate the load they're putting on their bodies and trying to find what are the optimal loads. When are we getting so far into too much work where a guy needs some rest, or he is in danger of being hurt? But we've got to do enough work to optimize conditioning, so he doesn't get hurt from being out of shape. That's sort of the holy grail right now-- I think of the analytics, at least in the NBA, is the whole injury prevention, load management type of stuff. NEIL: 21:18 What about when you were-- we didn't get to this in the intro but-- I think you introduced yourself as a coach. But with the Pistons, you were president. You were running things as well, right? What was your analytics department like then? STAN: 21:34 We came into, basically, having one person. We increased to three before we left and raised salaries and things. And look, I think that most of our use and probably the biggest use in the NBA is in terms of player personnel selection: who you're going to draft; who you want to trade for; who do you want to sign as free agent; what's the best cost of players and things like that. And so what you're really looking for is predictive analytics. Can we take individual players and predict based on their size, position, age, wear and tear, what they've done previously-- can we predict what they will be like, the performance we'll get not only at the beginning of their contract, but if it's a four-five year contract, what it will look like at the end? That's one of the important uses. STAN: 22:33 And then really now I think in the NBA, the holy grail of analytics departments is trying to figure out how we minimize injury because, obviously, your greatest assets are your best players, and having them on the floor for more games and more minutes is going to go a long way in determining your success. And what we're trying to do is players wear-- a lot of them do wear GPS monitors actually during practice, and you're monitoring how far they run in a given practice, how fast they run, how much acceleration, deceleration, how high are they jumping, how often are they at maximum effort and calculating within that what is the total load that these players are taking on, and how much is too much. If you get too much, you're more susceptible to injury. At the same time, if you do too little, now you're not conditioned highly enough, and you're also vulnerable to injury. So where does the line-- where is the line of where you want to be in terms of how much work you give these players to do? Everybody is trying to figure that out at this point. NEIL: 24:06 So the past of analytics in NBA franchises was kind of two-point versus three-point shot. The present is figuring out the best players to draft. And the future is player health. Am I getting that right? STAN: 24:23 I think you're right on that. I mean, it's still all of the other stuff because it's also which lineups work best together, which five person units work best together so you know who you need to put out there among your stars. I mean, it's a little bit of everything. The amount of information is overwhelming. Every NBA arena now required-- every NBA arena has a system of cameras in them that are-- it's automatic. There's no camera operators. There's small cameras. And so every movement in an NBA game is tracked. So at the end of any NBA game, a coach can get a printout on how many miles a certain guy ran, at what speed. You know every shot how close the nearest defender was. So was it an open shot, or was there somebody close to him? When it was somebody close to him, which defender was the closest? Are there certain defenders that are tougher to score on than others? I mean, the amount of information that is available to coaches and executives in the NBA is phenomenal. And the real challenge is figuring out what's most important, what can be most helpful to you in terms of winning and losing games and finding the best players and keeping them healthy and all of that because every team is privy to a lot of information. NEIL: 25:59 Yeah. I guess, yeah, there's so much data out there. You have to know what questions to ask. I wanted to ask about your time at the Pistons. I believe when you were with the Pistons, you were one of only five people coaching and being responsible for player personnel. What is that like? I mean, I guess at a high level, you're talking about balancing long-term strategy versus short-term tactics, and I guess there can be some give and pull there. But how did you get around that potential conflict of interest? STAN: 26:40 Yea. Well, I mean, I think I went out and hired a very good general manager, Jeff Bower, who had actually done both jobs simultaneously when he was in New Orleans. He held about every job in the league but had been a general manager and a successful one with New Orleans. And he really ran the front office on a day-to-day basis. If there was a decision to be made on a trade or a free agent signing-- he compiled all the scouting information, all the analytic information, made his recommendations, and I just had to give a final yes or no, and I don't think he and I very often disagreed. So I wasn't really doing both jobs. I just had final say. I think the advantage to it-- and it's not really in vogue. In fact, I don't think anybody is doing it now that Tom Thibodeau got fired in Minnesota during the season. I don't think any team has somebody doing both. It's not in vogue. I thought it was good because at least we had an overall philosophy, and we were all on the same page. What you have in a lot of situations is you have different philosophies. There's not a lot of synergy between the front office and the coaching staff. And then what happens is when things don't go well, it's basically the front office wanting to blame the coaches, the coaches wanting to blame the front office. When you have one person in charge of everything, you don't have any of that going on. So I think there are advantages to it also. NEIL: 28:27 And then since then, did I read correctly? Did you just finish teaching a semester at Stetson University? STAN: 28:33 I did. I taught one class one night a week for three hours on just contemporary issues in sports, and we did a couple of weeks on analytics, salary cap, those types of things when we did the actual sports side of the business, looking at all the different leagues. And the feedback was from the students that that was their favorite part of the course because it was new information for a lot of them. NEIL: 29:06 Nice. So you've done a lot of stuff. Now, you've been coaching for a long time. You did the GM thing. You taught a course. What's the proudest moment of your career so far? STAN: 29:17 Oh, you know what? That's really hard. I've been at this a long time. And it would probably go back to actual college coaching and-- my wife and I had gone to a reunion of a small college team that I coached back in the early '80s. We went there a year and a half ago and had all those guys come back. And to be honest, the proudest is when you see all the people that played for you there and how well they are doing. That's the proudest moment. NEIL: 29:54 All right. Stan, I can't let you go before I ask you to make a prediction here. So as we're recording right now, the Raptors and the Bucks are locked up two to two. Who do you got for that series? STAN: 30:11 I've got the Bucks winning it in seven games. I've been on the Bucks all year, so I'll stick with them now even though they had two tough ones in Toronto. NEIL: 30:23 They're just going to-- both teams are just going to keep winning on their home court until it's over. STAN: 30:27 I think so. Yeah. I think so. I think Milwaukee will win their two home games and win it. I think whoever wins it will beat Golden State in the finals, and I've been making that prediction for a couple of months. NEIL: 30:40 You think they're going to beat Golden State? STAN: 30:42 I do. I just don't think Golden State is the best team. Now, they have done some phenomenal things since Kevin Durant got hurt that make you sort of second guess yourself when you make that prediction. But I'll stick with it because I really do believe that Milwaukee is the best team out there, and I think Toronto is the second best team out there. NEIL: 31:03 Wow. Okay. That's a bold one. I'm glad I got you-- I'm glad I asked the question. All right. All right. Here we got the last segment of the show, the community picks. What's your pick, Stan? STAN: 31:18 Well, look. At this time of the year, with college graduations going on, and I just had a daughter graduate, I love to go on and listen to commencement speeches. Nobody remembers who actually gave their own commencement speech, but I like listening to them. And so I'll give you two real quick. One from this year that I thought was really, really good was Savannah Guthrie from the Today show at George Washington University. But my all time favorite, and I listen to it every year when it comes this time of the year, Michael Lewis at Princeton University, 2012. You can get it on YouTube. It's about 13 minutes long, and it's him talking about the role of luck in both life and careers. And Michael Lewis, of course, you know is the guy who wrote Moneyball that you mentioned earlier; the best commencement speech I have ever heard. NEIL: 32:15 Oh, wow. Cool. I'll check that out. I was actually just at GW. I'll give a shot at-- my little brother graduated from law school there, but I did not get a chance to watch the commencement speech because my toddlers were going nuts, and I had to take them outside, so [laughter]. My pick for the week is a new book on the NBA out pretty recently, SprawlBall by Kirk Goldsberry. So we were talking at length earlier about the evolution of the three-point shot. And so Kirk Goldsberry, long-time writer, professor, geographer [laughter], he's got a cool new book with a lot of cool illustrations talking about that evolution. So we'll put these links in the show notes. Stan, thanks again. I really can't thank you enough for joining the show. I'd love to talk about basketball with anybody, but I think this is definitely the best basketball conversation I've ever had. So thanks again. STAN: 33:21 Thank you, Neil. Appreciate it. [music] S3: 33:35 Thanks for tuning in to Alter Everything. To share your thoughts and ideas for future episodes, join us at community.alteryx.com/podcast or reach us on Twitter using the #AlterEverythingPodcast. Have a unique story to tell? Send us an email at podcast@alteryx.com. Catch you next time. [music] NEIL: 34:06 Well, Stan. You are by far the highest profile guest we've had on the show so far. But it was through Libby, my boss's boss that we got you on here. So what's your relationship with her? STAN: 34:24 Okay. Well, I coached at Castleton State College in Vermont and met my wife there. My wife was working at admissions. My wife and Libby both graduated from Castleton State and were best friends in college. And I met Libby through my wife, and Libby was in our wedding 31 years ago. NEIL: 34:50 Do you have any funny stories about Libby? Libby is pretty, I'll say, serious at work. I'd like to know what she's like at a wedding. STAN: 35:02 Yeah. You know what? I don't have any funny stories. And I'm going to be honest, Neil. If I had one, I would not [laughter] do that to her on this podcast. So yes. I would not do that to her, and I would hope she would not do it to me, so. And you never want to mess with the boss. That's something I think we all need to learn in our careers. NEIL: 35:25 All right. I guess you've probably just saved my job. STAN: 35:28 Yes. Probably. NEIL: 35:29 All right [laughter]. Thanks again, Stan. STAN: 35:31 No problem.

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).

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34: Efficiency vs. athleticism in basketball with Stan Van Gundy

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