#021: Analytics in Sports with Ben Gaines

The following is a straight-up machine translation. It has not been human-reviewed or human-corrected. However, we did replace the original transcription, produced in 2017, with an updated one produced using OpenAI’s WhisperX in 2025, which, trust us, is much, much better than the original. Still, we apologize on behalf of the machines for any text that winds up being incorrect, nonsensical, or offensive. We have asked the machine to do better, but it simply responds with, “I’m sorry, Dave. I’m afraid I can’t do that.”

00:00:04.89 [Announcer]: Welcome to the Digital Analytics Power Hour. Three analytics pros and the occasional guest discussing digital analytics issues of the day. Find them on Facebook at facebook.com forward slash analytics hour. And now, the Digital Analytics Power Hour.

00:00:25.63 [Michael Helbling]: Hello everyone, welcome to the Digital Analytics Power Hour. This is episode 21. As always, I’m joined tonight by the estimable Tim Wilson, who is a partner at Analytics Demystified. Hey Michael! And of course, by Jim Cain, CEO of Napkyn and Babbage Systems. Hello! Today, we have a great show. We’re talking about analytics, but analytics in a new context. Analytics in sports. But we needed an expert. We needed someone who could tell us all the stats from every minor league baseball team ever west of the Wasatch range. And so of course we got the number one guy we think of when analytics and sports is mentioned. That’s right, Ben Gaines. You might know him as the senior product manager at Adobe who answers all your questions on Twitter about how Adobe Analytics works. But he’s actually kind of a knowledgeable guy about the whole field of sports and analytics. Welcome to the podcast, Ben.

00:01:39.66 [Ben Gaines]: Thanks for having me. That introduction I certainly cannot live up to.

00:01:44.67 [Michael Helbling]: Oh, stop.

00:01:46.61 [Ben Gaines]: That’s OK.

00:01:46.93 [Tim Wilson]: Nobody’s going to research. You can just make up numbers, you know? Yeah, exactly.

00:01:51.76 [Jim Cain]: Yeah, that’s good. Inventor of Vilcro, Ben Gaines is with us tonight. That’s right.

00:01:56.66 [Ben Gaines]: Well, there’s anything that analytics has taught us. It’s that making up numbers to build up one’s own image is totally acceptable.

00:02:04.45 [Michael Helbling]: Hey, it works for trial purposes.

00:02:05.71 [Tim Wilson]: Oh, there’s your, as promised, always good information coming out early and often in the digital analytics power hour.

00:02:12.18 [Michael Helbling]: That’s right. So, awesome. Well, I’m excited about this. I think ever since Moeneyball, analytics and sports has started to become a more intriguing and ever-present topic. And that, coupled with fantasy sports and things like that, really is bringing it to the forefront. So, Ben, let me start with you. Where do you see out there in the fields of analytics, in sports, and what are people doing?

00:02:42.30 [Ben Gaines]: That’s a great question, a broad question, I think.

00:02:46.46 [Michael Helbling]: Yeah, I’ll let you take it wherever you want to take it.

00:02:49.01 [Ben Gaines]: Yeah, so I think the emergence of sports analytics and the emergence of digital analytics have really followed sort of the same timeline, right? It was sort of digital analytics started to really explode a little more than a decade ago with organizations adopting various forms of web analytics. And it was about that time that moneyball came out and the world of sports started to really pay attention to data and how data can inform decisions at every level of the organization. And I think what if you fast forward to today, to 2015, I think what you’re seeing in the world of sports is sort of a almost to borrow like the hype cycle from Gartner that I think sports analytics has come through the peak of inflated expectations or whatever that’s called. And I think it’s coming through the other side to the plateau of productiveness where you’re starting to see a good balance in decision making in sports organizations where data is informing decisions, but not driving decisions. And I think we’ve moved past, you know, you brought up Moeneyball and Billy Bean deserves all the credit in the world for really sort of kicking off this movement in sports. But if Mr. Lewis were to rewrite that book today, I think he would point to other organizations in other sports as finding that right blend where Billy Bean was so maniacal about the data. that there were some obvious flaws with his strategy, and now you’ve got teams like the San Antonio Spurs and the NBA. They’re kind of the first ones that come to mind, but the Golden State Warriors as well just this last year did a really good job. Steve Kerr, head coach of the Warriors, is if you listen to him talk, there’s data in everything he’s saying, and it’s clear that he’s he’s taken that data and he’s blended it with his wisdom from having a career in the game and turn that into really a revolutionary team that just swept through the NBA. I think in a lot of ways it’s sort of paralleled the emergence and the different phases of digital analytics over the last 10 years.

00:05:08.45 [Tim Wilson]: maybe actually got to the plateau of productivity maybe a little faster and more is it matured there faster than in digital analytics where you actually said Steve Kerr took his expertise from having played the game been deeply immersed in the game his creativity and blended it with data and not to pivot to digital analytics and marketing but sometimes we still run into the data is just going to tell us the answer as opposed to you know you still need to have creativity and marketing you need to have an idea for a strategy and smart questions to ask where it seems like with with moneyball when it first came out everybody who hadn’t read it and was just trying to give the sound by it was just plug in, you know, Jonah Hill when the movie came out and spit out the answers as opposed to no, it’s, it’s complimentary. It’s not, it’s not a replacement. You’ve got to change. You’ve got to adopt this new thing and you have to keep the parts of the old that were, were valuable. Right.

00:06:07.13 [Ben Gaines]: Exactly.

00:06:08.21 [Jim Cain]: If I ever meet Jonah Hill, I’m going to buy that guy a beer. You know how much money that guy made me? I’ve easily closed in my career five or six deals by someone going, I don’t understand what your analytics company does. And I was like, you see Moeneyball, you want Jonah Hill? And they’re like, yeah, like sign this. They’re like, okay.

00:06:24.46 [Tim Wilson]: Has anybody made you wear a fat suit and dress up as Jonah Hill to actually close the deal?

00:06:29.01 [Jim Cain]: I’m reversed Jonah Hill. I’m the size of a Jonah Hill snack.

00:06:33.64 [Ben Gaines]: That is fantastic. I’m going to try that sometime. It works. I’ve never actually used Jonah Hill to explain what we do.

00:06:41.52 [Jim Cain]: Senior executives want to be Billy Bean. They want to be, what’s his name? It’s your Brad Pitt.

00:06:47.73 [Ben Gaines]: Who wouldn’t want to be Brad Pitt?

00:06:49.21 [Jim Cain]: Right? And they want someone to just feed them the decision support. That’s literally what we do for a living. So that guy made me a lot of money.

00:06:57.41 [Tim Wilson]: But it’s an overly simplistic representation of reality. Yeah.

00:07:03.62 [Ben Gaines]: So there’s that scene where Brad Pitt has the angry confrontation with the head scout and fires him. And then he walks into the room. He points to the guy and says, you played baseball, right? And he says, I think he says he played in college or something. And he says, all right, you’re the head scout now. And that’s idiocy. That’s just total idiocy. I don’t know if you guys saw that the sports analytics world was up in arms last NBA season when Charles Barkley basically said that analytics is stupid. He would be right if his only impression of analytics and maybe this is his only impression of analytics. If his only impression of analytics is the Billy Bean, you know, fire the scouts, get rid of all the sort of tacit knowledge and wisdom and just, you know, go purely by the data, then yeah, he’s right. That is stupid. And no one is, it seems unlikely that anyone’s ever going to win. a championship in a major sport doing it that way but you know as with digital analytics it’s the blend of marketing creativity and tacit understanding of your space and your customers and your marketing programs and so on and so forth with data that produces winter.

00:08:11.53 [Tim Wilson]: Is your talking and I’m thinking Michael Lewis who was one of the fantastic speakers at Summit and then was Nate Silver the same one was last year one was this year.

00:08:20.74 [Ben Gaines]: I think Nate was last year.

00:08:23.20 [Tim Wilson]: Last year. But if you look at, you know, he does take the, in a sense, he has, well, Michael Lewis, journalist, trying to tell a really good story that’s accurate, right? I mean, fantastic. Whereas you take when you have the analyst from reading the signal and the noise, which frankly, I couldn’t follow all of it. Like that’s a book that I will need to reread several times because he takes a much, much more nuanced view. And even when he had 538, he kind of got a little irked that people kind of wanted to oversimplify it and say, punch, punch the magic button and it’s going to spit this stuff out. But that his approach to me, I love 538 sports coverage because it does seem like he tries to really come at it in a way that says this isn’t, let’s put all the uncertainty in there. The machine’s not going to kick out the answer at the end of the day. It’s a bunch of guys on a field playing a game and they’re all human.

00:09:14.15 [Ben Gaines]: He makes it really approachable and he speaks every year at the Sloan Sports Analytics Conference and it’s interesting at that conference generally and I know he’s made this point at that conference that it’s as much about the communication of the data as it is the data itself and more so when you’re talking to coaches and players who you know they’re not sitting in an office managing search keyword bids or or you know marketing campaigns they have they play a physical game you know you really you you have to communicate it to them not like in the signal in the noise but more like a five thirty eight article that I think at least the articles I’ve read have done a pretty good job putting the data into the context of the problem that the data is trying to solve or that the study is trying to solve and communicating it in a way that for a reader is intelligible and relatable.

00:10:12.87 [Jim Cain]: I don’t know. I’ve talked to some pretty old school brand marketers who, I think I’d rather sell analytics to the guy who owns the Cowboys.

00:10:21.36 [Michael Helbling]: Well, or it may be like analytics with creative people. What they do doesn’t seem like an actual fit for analytics. And much like being an athlete is not an analytical thing as much as it’s a physical muscle memory. But you can show somebody, hey, you go up and you take this many at bats a year and in 47% of those at bats, you’re doing this. and we can train that out of you and you can get this much more out of your swing. There’s still going to be, if you can present that in the right way, there’s going to be interest in a draw to be like, oh, I would like that.

00:10:55.42 [Tim Wilson]: It’s kind of the conception of the athlete not being interested. You’ve got Charles Barkley, maybe misdefining analytics, but if you watch what athletes are doing and the science, they’re getting told what to eat, when to eat, how much to eat, They’re getting their custom formulated drinks, so it’s not that big of a leap to go to them to say, the data is just the science of your body coming to life to give you that extra little edge. But it doesn’t mean you don’t still have to have heart and work your ass off and be creative and have things that make you unique. They’re complementary.

00:11:28.07 [Jim Cain]: Well, I think the thing as well, though, is that Again, the parallels are uncannier than I thought they’d be between, again, senior old school brand marketers and people who own sports teams. But when people think about advanced data and statistics and the panic of, again, a machine is going to take my job. A machine is going to tell me what decisions to make. And one of the things that I think we’ve covered quite extensively, I thought we’re going to have a show once we’re going to start bashing senior stakeholders. And then we had a three-man impassionate defense of the hippo. We do decision support. We make smart people win faster. And that’s all good analytics does in data. I was thinking before the conference, because I actually am pretty nerdy for sports analytics myself, but because I’m Canadian, it’s one particular sport. Brian Burke went in front of the Sloan conference. There was a hockey panel about four or five years ago. And he’s got in front of a room full of brilliant people and everything you do is bullshit. We’re never going to do it. Toronto Maple Leafs. He’s now like an assistant something for the Calgary Flames. And Toronto has been hiring all the stats people they can get their hands on right now because they’re the worst team in the history of the world. And I hate them also. But you know, if you look at the adoption, just hockey in particular, the adoption of advanced analysis just in the last two years was no team had everybody. Every team has somebody. All the top bloggers in the advanced stat space for hockey have all been picked up by a team. Actually, the Penguins were one of the first teams to pick somebody up. And we went from the best stat in the sport a few years ago being plus minus to starting to get into things like Corsi and Fenwick and advanced stats. I could nerd out about the hockey piece at length, but it’s just interesting because I really think hockey, and I can’t speak for other sports, but it’s been similar to what we’ve gone through in our industry in the last 10 years and the last two. And it’ll be interesting to see where it goes.

00:13:16.26 [Ben Gaines]: I think it was last year. Nate Silver gets up at the Sloan Conference. Well, I think it was the last session of the conference. And he says, I’m trying to remember how many people were in the room. It was a few thousands, the MIT kids, Harvard kids, representatives from every professional sports team in North America, bunch of colleges. And he starts out by saying, You guys all need to go learn omniture or google analytics if you want to always be employed which i just like i just leaned back in my chair put my hands behind my head and laughed he told a bunch of the smartest most well trained people who all you know they’re all vying for the same positions. for a small handful to your point, Jim, you know, the hockey, you know, hiring all these kids, there’s way more supply of interested young, talented kids than there is demand. You know, there just simply aren’t that many professional teams that can hire someone. And I thought how neat that was for our industry that, you know, you’ve got Nate Silver going and telling these guys to go learn the tools that, you know, for a large portion of our industry are the tools of the trade.

00:14:22.31 [Tim Wilson]: Which is a whole other, I mean, sports marketing analytics is, I assume there’s probably a higher proportion of people I feel like any conference I go to that’s in kind of a mid-market, I wind up with people who are in marketing and marketing analytics for a major league team at the, I mean, WebUnit is Wednesdays. We have the, what’s our NHL team? The Bluejacket. Come on, buddy. That’s terrible.

00:14:54.28 [Michael Helbling]: So, sort of awesome, actually.

00:14:56.46 [Tim Wilson]: No, I knew who were. So when I go on campuses and talk to students, and they’re occasionally one saying, I’d love to get into sports analytics. And I kind of say, well, wait, what do you mean? There’s a ton of innovation going on. If you’re really, really passionate about the sport itself, keep in mind that that’s going to be highly competitive with people who potentially played the game, got a degree in math, played in college. You know sports marketing not that it’s necessarily easier there also having to reinvent the rules of like what is mobile inside of a stadium mean you know how do you know you were at ESPN I assume you were here I was seeing there’s a little before you got there I watched somebody you know talk about somebody from ESPN talking about how We have no idea how we’re going to handle the next international sporting event because we know there are these things called iPads and we’re not sure exactly what that’s going to mean and how we’re going to instrument for them. So that’s a whole other. I don’t know if that falls under sports analytics. It’s consumer behavior.

00:16:00.74 [Ben Gaines]: Yeah, I mean, it does at the Sloan Conference. There are always a handful of sessions, usually like StubHub will get up or Ticketmaster will get up and talk about how they do marketing. And that’s obviously that’s a little different than if you’re in marketing for a team, but they’re talking about a lot of the tools and practices that I think, you know, that you all and your listeners would be really familiar with. I think it was, I’m trying to remember who it was, I want to say David Halberstam, one of the giants of sports writing at one point said that when he gets approached similarly, Tim, when he gets approached by a college kid who says, I want to be a great sports writer, what do I need to do? He would say, do you love sports? And the kid would say, of course, and he would say, do you love to write? And that was the thing that would separate the ones that had potential from those that didn’t. It’s not enough to be into sports because like you said, the imbalance between supply and demand is so great that if what you love is analytics and you love sports, then sports marketing is a great place to end up. You may not be impacting the on-field or on-court performance as much, but you play as integral a role in the health of the organization financially because you’re reaching out to fans and you’re getting fans involved and keeping them buying season tickets and things.

00:17:18.53 [Tim Wilson]: And you’re probably getting to attend some games.

00:17:20.83 [Ben Gaines]: So, you know, I would, I would hope so. I’ve never been in that role, but I, man, I, if you, if you were in sports marketing for a team and you didn’t get to go to the games for free, that would suck.

00:17:31.55 [Jim Cain]: We haven’t really nerded out on sports before. Did you guys have a favorite sport? And have you ever sat back and thought. I would like to use measurement this way, because I know I have. I’m just wondering if you guys have ever sat there at the pub with your buddies and nerded out on your favorite team or your favorite sport and kind of what was it? I’m just curious.

00:17:48.99 [Tim Wilson]: So yeah, I’m an amateur baseball guy. I mean, to the point that I invented a stat for young kids and built a spreadsheet with pivot tables to generate just the standard baseball stats. I can’t even follow the, you know, VORP and all the advanced stats, but the basics just from a way to I think I would think baseball is a boring game to watch if I wasn’t actually scoring it, and that’s not something that goes back to my youth of, you know, doing this with my father. I came to that well after college for my beloved Texas Longhorns that have had a fantastic baseball team off and on over the years. They’re in a little bit of a lull. So non-professional baseball is kind of my weird little quirk, but I enjoy watching almost anything.

00:18:33.44 [Michael Helbling]: Yeah, I would say I’m a NFL fan, first and foremost. I do a lot of fantasy football leagues, so that’s probably my thing. But lately, most recently, this is super nerdy, or it could be construed that way, eSports has been really fascinating me.

00:18:49.42 [Tim Wilson]: I cannot, I cannot, still can’t fathom it. I’ve got two teenage sons, and I can’t fathom it. Wait, does that mean video game sports?

00:18:55.65 [Michael Helbling]: Yes, eSports.

00:18:56.83 [Tim Wilson]: They’re just full-right scholarships to schools.

00:19:00.05 [Michael Helbling]: Yeah, that’s starting to happen. There’s a game called League of Legends that just had their North America finals at Madison Square Garden. They’re starting to become a really big deal. It’s interesting to see that grow. And obviously, because it’s primarily digital, it’s built with analytics from the ground up. And so that’s just fascinating in its own right, much less so than all the other sports out there. I mean, are there sports that haven’t even Embraced analytics how much does rugby use analytics is it a thing or is it not a thing and maybe we don’t know as Americans because we Don’t follow rugby closely enough.

00:19:35.81 [Ben Gaines]: No, so Ben.

00:19:36.23 [Michael Helbling]: What about you? Do you have a favorite sport?

00:19:39.05 [Ben Gaines]: I for me it kind of goes with the seasons I’m a baseball basketball football guy, but at the end of the day if I had to stick with one I think it would be basketball and the NBA is kind of the hot league for analytics right now and A lot of the best new research seems to be happening there. Baseball, there’s tons of stuff going on, but it kind of feels like that had its kind of heyday with analytics in the last decade, and now people are kind of focused on the NBA. There are just tons of phenomenal blogs out there and podcasts, basketball analytics podcasts that you can just drown yourself in data and analytics in the NBA. To Tim’s point about creating a metric, I think the only original analysis that I’ve ever done, the only sort of statistical analysis I’ve ever done for the NBA was I looked at, I’m a Utah Jazz fan, live in Salt Lake City. So people were always ripping the general manager of the Utah Jazz, Kevin O’Connor, for being terrible at drafting. Because he’s had a handful of major misses, he had a chance at drafting Tony Parker who’s, you know, future Hall of Famer and he went with a total bust of a point guard who was, you know, out of the league in a couple of years and no one’s ever heard of him. And a few others like that. And so I wanted to look and see if you factor in players who were productive in the NBA, but after they left the team that drafted them, does that change the picture? Because obviously, you know, Kevin O’Connor had some picks that when they were with the Jazz, they were mediocre or terrible. And then they caught on somewhere else and they turned into, if not NBA stars, they at least turned into serviceable NBA players. And should he get credit for that? I kind of think he should get at least partial credit for recognizing that the talent was there. And the coaching was terrible then. Well, yeah. So that’s not likely to be the case, although Sloan tended to not play rookies very much. So you could actually make a case that maybe Sloan was holding some of them back. But anyway, what I found was he was he was actually sort of right about in the middle of current general managers in terms of downstream wins. The NBA has a stat called WinShares, which is sort of a, it’s the kind of metric that probably a lot of digital analysts would turn their noses up at. It’s an attempt to be a single metric to quantify a player’s value, which has its issues and I don’t think- So wins above replacement, wins above replacement equivalent? It’s basically the NBA’s version of wins above replacement. Although i’m not sure it’s as well developed as winds above replacement anyway so i looked at that and and found that i think the worst general manager i could find in terms of draft picks was great pop of it no it wasn’t they actually so you had to factor in for the analysis you had to factor in like where the team was drafting because You can’t honestly expect the Spurs who are always drafting toward the end of the first round to produce as many win shares out of a draft as a team that’s drafting in the top three where they’re likely to pick a future superstar. But it was the Lakers. It was Mitch Kupczyk of the Lakers. And they just, if you look at their draft history, since he’s been general manager, it’s just awful. And he’s gotten better. And this was several years ago, and he didn’t get much credit when I did the study for drafting Mark Gasol, who’s turned into like the best center in the NBA. But at the time he was just kind of a decent center, but hadn’t really sprouted yet. Now he’s in Memphis and he’s doing great. So I could go back and update the study, but that’s, I think that’s the only thing I’ve ever done to contribute anything to NBA analysis.

00:23:23.71 [Tim Wilson]: This makes me realize that Helbling is not actually his not referenced. We’ve talked about Moeney Ball, which was the book and then a movie and Helbling hasn’t said anything about Draft Day and his beloved Cleveland Brown.

00:23:34.80 [Ben Gaines]: I have seen which is a scandal.

00:23:37.43 [Michael Helbling]: I also have not seen that movie and I feel as a fan we’ve moved past that point in time.

00:23:45.10 [Jim Cain]: You know, it was a bit of a time life movie. Also, you didn’t really miss anything. Yeah.

00:23:49.66 [Michael Helbling]: Yeah, and I know what happened in each of those drafts. I was there. I was live tweeting. No, I don’t usually live tweet the drafts, but I do. I usually am glued to my computer and or television during the draft, watching all of that happen and seeing how disappointed the Jets and the Philly and the Eagles fans are with their picks because they always are no matter what. But no, it’s yeah, it’s draft analytics, a portable skill.

00:24:15.95 [Jim Cain]: But could you go because I never really thought about using measurement for the draft before because that’s just not the part that I think is interesting. But I do now, I think it’s interesting. I got really good at helping predict a set of metrics for the Ottawa Senators to kick ass in the draft. Could I take that methodology and apply it to a different sport?

00:24:34.70 [Ben Gaines]: I don’t see how you could.

00:24:35.88 [Michael Helbling]: It would be very difficult because the measures and stuff are all different, right?

00:24:41.08 [Ben Gaines]: It depends. I suppose there are some metrics that are going to be more or less common or convertible, metrics like speed or agility or strength that, you know, if you can bench press 400 pounds in the NFL, you can bench press 400 pounds in the NHL. But I can’t think of a good two sports that are similar enough that the skills and any of the data that would come out of the amateur ranks, whether that’s, you know, amateur hockey or college football or college basketball, like they’re just, they’re so, so different. And the competition is. is all over the map at the amateur levels. Some guy who has incredible numbers playing for a small school against mediocre competition, how do you compare that to a guy with lesser numbers who did it against much better talent? I mean, I’m sure there are some models that you could come up with.

00:25:30.69 [Jim Cain]: Well, I mean, the two sports that I think are closest actually are basketball and hockey. because other than line changes in hockey, which make that very, very different, you’re looking at a high level of dynamism and individual play, but team contribution. It’s not set like a football or a baseball would be. It’s not set scenario. Um, and that’s why whenever I’m out having a couple of pops and I started getting analytics nerd and we’re talking about hockey, the two things that I do all the time right now are around attribution and multivariate testing. I think, and I’m not smart enough to do this, but maybe someday I can afford someone who is. really understanding attribution and being able to apply it to multivariant testing at the segment level. So that’s your team and what do I do on my team in terms of individual contributions? I think there’s something in there that carries through because basketball and hockey are very much team sports. I think in ways that maybe other sports aren’t. So if you can say, I’m missing a piece that needs to have these exact characteristics to be able to complete that on the court picture, that’s your draft profile potentially. Anyways, that’s the thing I nerd out about. I was testing an attribution.

00:26:38.92 [Michael Helbling]: Well, and the NBA has that, right? The plus minus on the floor.

00:26:43.59 [Ben Gaines]: They have well even so even going beyond plus minus Kirk Goldsbury who does a lot of the spatial analysis is kind of the leading NBA spatial analyst that’s that’s out there and he I think he writes for Grant Lund and he’s a professor at Harvard he he’s come up with this. with a way to quantify it literally is attribution he’ll take each movement of the basketball between players receives a value based on a number of factors like the amount of time left on the shot clock and who the balls being passed to is it someone who shoots particularly well from that area of the floor he’s come up with these fairly advanced models for attributing success back to someone who made a pass maybe you know six passes ago in a possession which is wild. You know stuff that you know even five years ago seemed impossible to an NBA fan. So yeah that stuff exists.

00:27:38.03 [Jim Cain]: If you want to trade a guy and plus minus is the number one stat that you’re looking for and you want to trade someone put them on the line with the best player in the league.

00:27:46.76 [Michael Helbling]: They tried that with Matthew de la Vadova and it almost worked.

00:27:52.15 [Jim Cain]: I don’t know who that is but he sounds very talented and not like a hockey player.

00:27:56.84 [Michael Helbling]: he actually might be equally successful in hockey as he I could see that he’d be an enforcer yeah oh for sure he would cleavage sports fans have it rough that’s what I’m trying to do at least you have more than one team if I didn’t like Ottawa I would have to or hockey we’ve got one team one sport

00:28:16.22 [Jim Cain]: I just happen to like it. So I win.

00:28:17.88 [Ben Gaines]: There’s no CFL team.

00:28:19.36 [Jim Cain]: I don’t, I don’t consider the CFL to be a sport and I can spit out lags. I don’t think any Canadians listen to this podcast.

00:28:25.98 [Ben Gaines]: They’re Ottawa Red Blacks.

00:28:27.10 [Jim Cain]: We just renamed the team the Ottawa Red Blacks a couple of years ago and Tom Green said, only in Ottawa could we be racist twice when we’re naming it.

00:28:36.46 [Tim Wilson]: That’s fantastic.

00:28:37.68 [Michael Helbling]: Oh, man.

00:28:38.71 [Tim Wilson]: We’ll see you, Washington, DC. That’s right. We’re tired of being the unthought of country to the north.

00:28:46.09 [Jim Cain]: So here’s a double down on our bigotry here in Ottawa.

00:28:49.16 [Michael Helbling]: Here’s a quick question, and then we probably need to wrap things up. But Ben Gaines, a lot of our listeners are analytics folks, and some of them may even be sports fans. But what if they wanted to dig in and go beyond maybe the 538 stuff and get a little deeper into a topic? Where would you send somebody? What resources are out there for people to get a little more information?

00:29:13.51 [Ben Gaines]: So do you mean in terms of like just getting your hands on the data or?

00:29:17.72 [Michael Helbling]: Yeah, or just what’s cutting edge. I mean, you’ve mentioned a bunch of folks, you know, in basketball analytics, and so on, like what other types of things or websites we think would be a good read or something like that.

00:29:30.50 [Ben Gaines]: Okay. Yeah. So my sort of go to basketball analytics. I don’t actually don’t think I have one for baseball. They’re a ton. Take your pick. But for basketball, there’s a site called Nylon Calculus. Just nyloncalculus.com. Basketball members for the people. And it’s a blog, ultimately. It’s high level enough that you can dive into it, and they have tutorials on, or not tutorials, but just introductory material on different metrics that are emerging in NBA analysis. But then they also have very pointed studies on, so I’m on there right now, and there was a post the other day called more on the post script to a shot block. So like talking about what analysis into what happens after a shot is blocked and how certain players are better at blocking a shot in bounds as opposed to out of bounds so that their team can get possession of the ball. just a bunch of this stuff. And they’ve got a handful of really good writers. Seth Partnell, he’s written on sort of the theory and practice of analytics and said some really great things that I think I’ve tweeted out to the digital analytics crowd because it is so similar in a lot of ways to what I think a lot of us in the industry deal with when it comes to getting our conclusions accepted and our recommendations taken seriously and getting invited to the right meetings and all of that stuff. that we deal with. So I would start with nylon calculus. That’s the one I find myself going back to over and over again. And in terms of the data, nba.com is really, really, I think forward thinking in the amount of data they provide and access to it. If you go to, I think it’s stats.nba.com, there is this whole application for doing your own analysis and tons of data that’s made available for free. It’s powered by SAP and it’s just fantastic. And the other thing is for really for any of the major sports, I think they even have one for hockey gym, the dashreference.com franchises. So basketball-reference.com, baseball-reference.com, tons of data there. You can do custom queries, you can compare players across eras and It’s the kind of site where if you’re a data nerd, if you love playing around in data, you can easily find yourself up at 3 a.m. not realizing that you’ve stayed up three hours later than you intended to, because you’re just playing around with data and analysis on that site. So those are kind of my go-to sort of must-have. And then there’s some more nuanced databases available that are things like player salaries and things. But for the most part, those are my go-to sites.

00:32:10.66 [Tim Wilson]: So the hyper-motivated analyst who wants to learn R and dig into data, you can go to a dashreference.com, get a nice big data set, and then throw it into R and go to town.

00:32:22.34 [Jim Cain]: They have all the major sports. Also hockey, Jim.

00:32:27.22 [Ben Gaines]: I counted that. They have hockey-reference.com. It exists.

00:32:33.31 [Tim Wilson]: You can get all the history of the Calder Trophy, because that’s what you’ve always wanted.

00:32:37.46 [Jim Cain]: The Calder Cup, the rookie of the year trophy. We’re talking after the show.

00:32:41.59 [Michael Helbling]: So I think that’s one of the great things about the show is that we learn from each other about things like the Calder Cup.

00:32:49.59 [Tim Wilson]: Lady Bing Memorial Trophy, the player who displays gentlemanly conduct in the NHL.

00:32:58.72 [Michael Helbling]: Oh, that’s a good one. Don’t make me hate you.

00:33:01.14 [Tim Wilson]: Doesn’t look like it’s an award. It seems 2010-11. Martin St. Louis kind of had a lock on it for two years. Maybe it was Martin from St. Louis.

00:33:09.63 [Jim Cain]: Or he’s French Canadian and his name is Martin St. Louis, but it doesn’t matter. Oh, St.

00:33:13.56 [Ben Gaines]: Louis. St. Louis. You can edit that out, Tim.

00:33:16.68 [Jim Cain]: You just text the hell out of that guy’s name.

00:33:24.15 [Michael Helbling]: Today we’re defining ugly American. All right. So in conclusion and in summary, this has been great. Ben, thank you so much for coming on. Anybody got any big takeaways? Anything really blow open in their minds you want to share?

00:33:40.40 [Jim Cain]: I could do this episode again next week. I mean, I like the analytics piece. Obviously, I nerd out in a very specific area of it. I really feel that everything that we’re going through the sports analytics business, maybe not baseball, but all the other leagues, are just getting started now dealing with the bullshit we had to deal with six years ago in terms of stakeholder buying in terms of don’t worry, I’m not taking your job in terms of getting people to listen and all that other kind of stuff. The other thing is, and I never thought about it before, but you know, there’s 10,000 people that want to be the next assistant to Billy Bean. And I have a hell of a time finding someone that wants to look at, you know, pan session attribution data for a nonprofit organization. I read sports books, like people painstakingly for days of work build blogs doing analysis on hockey before they go back to their daytime job. But if they did that with marketing data for me, I would pay for their house, you know what I mean? And a level of passion that, and I’m not exactly, they marketing analytics or digital analytics is equally awesome. But if you can find the same level of passion for your gig that some of these sports people have for the work they again do on evenings and weekends that I think is comparable in quality, you’re going to be a VP someday.

00:34:59.31 [Michael Helbling]: I like it. Well, again, we would love to hear from all of you. So are you way into a sport and you’re digging the analytics side of it? Let us know on Facebook at facebook.com slash analytics hour or on Twitter or on the measure slack. So the instructions are on our Facebook page. So you can find it there. It’s a great community, great place to talk some sports analytics. with Ben Gaines and other folks who are interested in that. And once again, Ben, thank you so much. It’s been a pleasure having you on. And I hope you come back and do a show about what we all really wanted to talk about, which was sneak peeks on Adobe Analytics.

00:35:40.95 [Ben Gaines]: I had a great time tonight. If you want to have me back, I’m all about it.

00:35:44.61 [Michael Helbling]: Well, that’s super gracious of you. All right. Well, hey, for my co-host, Tim and Jim. Thanks, everyone. Thanks again to Ben and keep on analysing.

00:36:02.37 [Announcer]: Rock flag and here you go!

00:36:14.96 [Tim Wilson]: You’re trying to make that a thing.

00:36:26.31 [Michael Helbling]: It is a it’s already been a thing. I think it’s a good thing don’t get me wrong Oh, you didn’t know we’re just gonna do live calls tonight people asking any adobe question they want I Know you’re getting paid.

00:36:39.93 [Ben Gaines]: I know you can afford a haircut

00:36:43.28 [Michael Helbling]: Who knew that Cleveland Browns would be sitting alone atop the AFC North at this point in the season?

00:36:52.03 [Jim Cain]: I think that web analytics demystified has a strong high ally analytics practice.

00:36:58.16 [Michael Helbling]: I’m still here and I am not good at sports.

00:37:03.20 [Jim Cain]: And then we end up drinking and making fun of helplings.

00:37:07.19 [Michael Helbling]: I’m pretty sure I could even hear people pausing the podcast in Jim’s whole NHL soliloquy.

00:37:21.60 [Tim Wilson]: It’s gonna be this tension between like, it’s Ben Gaines, I love I adore Ben Gaines, I wanna listen to Ben Gaines fighting with it. I could give a shit about sports, I could give it, maybe he’ll, oh, and people, they’re just, people can be driven and true.

00:37:34.66 [Michael Helbling]: Shut up, Ben Gaines could talk some more. There’s a payoff for everyone who’s willing to listen to him, but yeah.

00:37:44.27 [Jim Cain]: Nice. No, not nice.

00:37:47.12 [Michael Helbling]: Cheers.

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