#021: Analytics in Sports with Ben Gaines

In this episode, we’ve simulated a lobby bar at the end of Adobe Summit, with Ben Gaines dropping by and everyone temporarily tapped out on talk of eVars, s.Props, derived metrics, and classifications for a bit. The result? A conversation that quickly turns to an adjacent passion of many digital analysts: sports analytics. Baseball, basketball, football, e-sports, the CFL, and even a fairly obscure game played on ice with a stick. Surprisingly, the discussion loops back to the parallels of sports analytics to digital analytics time and time again. This Power Hour clocks in almost 10 minutes shorter than a regulation NBA game.

People, places, and things referenced in this episode include:


Episode Transcript

The following is a straight-up machine translation. It has not been human-reviewed or human-corrected. 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.”

[00:00:25] Hello everyone. Welcome to the digital analytics power hour.

[00:00:29] 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 Kane CEO of napkins and Babbage systems I know today we have a great show. We’re talking about analytics but analytics in a new context analytics in sports but we need 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 if so of course we got the number one guy we think of when analytics in sports is mentioned. That’s right. Ben Gades you might know him as the senior product manager at Adobe to answer 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.

[00:01:38] Ben thanks for having me. That introduction I certainly cannot live up to our staff.

[00:01:46] Nobody’s going to research. You can just make out. Make up numbers you know. Exactly.

[00:01:51] Yeah that’s Centera all crow. Ben Gaines is with us tonight. That’s right.

[00:01:56] But 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] Hey it worked as promised. Always good information coming out early and early and often in the power hour.

[00:02:11] That’s right. That’s awesome. Well I’m excited about this I think ever since Moneyball 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 are you seeing out there in the field of analytics in sports and what are people doing.

[00:02:42] That’s a that’s a great question a broad question I think yeah I’ll let you take it wherever you want to take it. Yeah.

[00:02:49] So I think the the emergence of Sports Analytics and the emergence of digital analytics have really followed sort of that same timeline right. It was sort of digital analytics started to really explode a little more than a decade ago with with organizations adopting various forms of web analytics and 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 can inform decisions at every level of the organization and I think it would if you fast forward to today of 2015. I think what you’re seeing in the world of sports is sort of almost to borrow like the the hype cycle from Gartner that I think Sports Analytics has come through the peak of inflated expectations or whatever whatever that’s called. And it’s 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 see brought up Moneyball and Billy Beane 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 Beane was so maniacal about the data that there were some obvious flaws with his. With his strategy and now you’ve got teams like the San Antonio Spurs in the NBA. They’re kind of the first ones that come to mind.

[00:04:33] 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 has he’s taken that data and he’s blended it with his sort of wisdom from from having a career in the game and turn that into really a revolutionary team that just swept swept through the NBA. You know I think like I said I think in a lot of ways it sort of parallels the emergence and sort of that’s sort of the different seasons of digital analytics over the last 10 years.

[00:05:08] Maybe I actually got to the plateau of productivity maybe a little faster and more mature there faster than 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 join only in marketing. But sometimes we still run into the data is just going to tell us the answer as opposed to you know you’d still need to have creativity in marketing. You need to have an idea for a strategy and smart questions to ask where it seems like with Moneyball and it first came out everybody hadn’t read it and was just trying to give the soundbite it was just plug. Jonah Hill when the movie came out and they spit out the answers as opposed to No 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 valuable.

[00:06:06] Right exactly.

[00:06:08] If I ever meet Jonah Hill I’m going to buy that guy a bear you know how much money that guy made me. I easily closed in my career five or six deals by someone going. I understand what your analytics company does and I’d like Moneyball you want jonah hill like yeah like scientists like OK.

[00:06:24] Has anybody made you wear a festoons such as Jonah Hill. I’m like what’s the deal. I’m unversed Jonah Hill and Jonah Hill snack that is.

[00:06:33] That is fantastic. I’m going to I’m going to try that sometime. It works I’m going to I’ve never acted as Jonah Hill to explain what you know what we do.

[00:06:41] Senior executives wannabe Billy Beane they want to be. What’s his name. Brad Pitt. Thank you. I wouldn’t want to be Brad Pitt. Right. And they want someone to just feed them. The decision support. That’s literally what we do for a living.

[00:06:55] So like I made me a lot of money but it’s overly simplistic representation of reality. Yeah.

[00:07:03] So that 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 the guy and says you play baseball right. He says I think he says you can play in college or something. He says are the Scout now and that’s idiocy. Like that’s just 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 only a person of analytics if his only impression of analytics is that Billy Beane fired the scouts get rid of all the sort of tacit knowledge and wisdom and just you know go purely by the data. And 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 it produces.

[00:08:11] When you’re talking you know thinking Michael Lewis who was one of the fantastic speakers at Summit and then was Nate Silver the same one it was last year one was this year last year. But if you look it you know he does take the sense he has. Well Michael is journalist trying to tell a really good story that is accurate read on the Internet. 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

[00:08:41] 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. His approach is I mean 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 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] He makes it really approachable. He’s so he speaks every year at the Sloan Sports Analytics Conference. And it’s interesting at that conference generally and I know 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 have to communicate it to them not like in the signal in the noise but more like a 538 article that I think does it the ones that at least the articles I’ve read have done a pretty good job putting the data into com into the context of the problem that the data’s trying to solve or that is the study is trying to solve and in communicating it in a way that for a reader is intelligible and relatable.

[00:10:12] I don’t know.

[00:10:13] I’ve talked to some pretty old school brand marketers who you know I think that the analytics guy on the Cowboys. Sure.

[00:10:21] Well or it may be like analytics with creative people but it 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 percent of those at bats you’re doing this you know we can train that out of you and you can get this much more out of your swing.

[00:10:48] 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] It’s kind of the conception of the athlete not being interested. You’ve got Charles Barkley maybe mis defining analytics but if you watch what athletes are doing in 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 you know and be creative and have things that make you unique they’re complimentary.

[00:11:28] I think the thing as well though is that again I get the parallels are uncanny here than I thought they’d be between again kind of senior old school brand marketers and people who are 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 where we’re gonna 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 data is thinking before the conference because I actually am pretty nerdy for sports analytics myself because I’m Canadian it’s one particular sport. Brian Burke went in front of the Sloan conference as a hockey panel for five years ago and he he’s got in front of a roomful of brilliant people and said everything you do is bullshit we’re never going to do it. Trump believes he’s now like an assistant something for the Calgary Flames. And Toronto has been hiring all the staff 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 of hockey in particular the adoption of advanced analysis just in the last two years was no team had every anybody. Every team has somebody all the top bloggers in the advanced adspace or hockey have all been picked up by a team.

[00:12:52] 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 starting to get into things like Coursey 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 last two it will be interesting to see where it goes.

[00:13:15] Last I think it was last year. Nate Silver gets up at the Sloan conference and was the last session as the conference and he says I’m trying to remember how many people were in the room. It was a few thousands. You know 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 know they’re all vying for the same positions for a small handful. To your point Jim Hawkey hiring all these kids. There’s way more supply of interested young talented kids than there is demand there just simply aren’t that many professional teams that they can hire someone. 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 which is a whole other sports marketing analytics is I assume there’s probably a higher proportion of people like any conference I go to.

[00:14:33] In kind of a mid-market.

[00:14:35] I wind up with people who are in marketing and marketing analytics for a major league team at the Neelix Wednesdays we have the our NHL team.

[00:14:48] The blue jacket is the mind body. So it’s sort of awesome actually know.

[00:14:57] We’re going to go on this is in talking to students and there occasionally. One thing I want to get into sports analytics and I kind of say well wait what do you mean there’s 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 playing college sports marketing that isn’t necessarily easier.

[00:15:26] They’re also having to reinvent the rules of what is mobile inside of a stadium. I mean you know how do you. Whatever only the morning and all this stuff you know you were at ESPN I assume you were saying there’s a little before you got there.

[00:15:38] Watch 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 iPad’s and we’re not sure exactly what that’s going to mean and how we’re going to instrument for. So that’s a whole other I don’t know if that falls under Sports Analytics it’s consumer behavior.

[00:16:00] Yeah I mean it does at the Sloan conference. There are always a handful of sessions you know 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 was I want to say. David Halberstam one of the giants of sports writing it at one point said that when he gets approached similarly to him when he gets approached by a college kid who says I want to be a great sportswriter what do I need to do. He would say he would say he loves sports and 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 in sports because like you said the imbalance between supply and demand is so great that you know if you 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 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 you’re probably going to attend some games.

[00:17:20] So you know I would I would hope so. I have never been in that role.

[00:17:24] But I mean 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] We haven’t really narrowed it out on sports before. Did you guys have a favorite sport and have you ever sat back and thought I would like measurement this way because I know I have. I was wondering if you guys have ever sat there at the pub with your buddies and nerd it out on your favorite team your favorite sport and what was it was curious.

[00:17:49] I’m an 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 the just the standard baseball stats I can’t even follow the VOR. 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 there in a little bit of a lull. So non-professional baseball is kind of my weird little quirk but I enjoyed watching almost anything.

[00:18:33] 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 could be construed that way. Esports has been really fascinating me. I cannot I cannot fathom it.

[00:18:51] I’ve got two teenage sons and I mean videogame sports.

[00:18:55] Yes. Eastport they just drive scholarships to schools. Yeah that’s starting to happen. There’s a game called League of Legends that just in 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 you don’t mean other 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. So Ben what about you.

[00:19:37] Do you have a favorite sport. For me it kind of goes with the seasons. I’m 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 leagues for analytics right now. A lot of the best new research seems to be happening there baseball. There’s tons of stuff going on but it 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 analysts podcasts that you can just you know you could just drown yourself in 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 you know I’m a Utah Jazz fan. They live in Salt Lake City so people were always ripping the general manager of the youth such as Kevin O’Connor for being terrible at drafting because he’s had a handful of major misses. He had a chance of drafting Tony Parker who’s you know future Hall of Famer and he went with a total bust of a point guard. He was out of the league and a couple of years and no one’s ever heard of them. And a few others like that and so I I wanted to look and see you factor in players who were productive in the NBA but after they left the team that drafted them.

[00:21:06] 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 and it was 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 town was there and that you know just for coaching was terrible.

[00:21:30] Well yeah.

[00:21:32] So that’s not likely to be the case although Sloane 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 right about in the middle of current general managers in terms of downstream wins. The NBA has a debt called Win Shares 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 the ones above are pretty smooth wins above replacement equivalent is that it’s. It’s basically the NBA version of what is placement. So although I’m I’m not sure it’s as well-developed as wins above replacement anyway so I looked at that and found that I think the worst general manager I could find in terms of draft picks was Gregg Popovich. No it wasn’t. They actually so you have to factor in for the analysis you to factor in like where the team was drafting because you can’t honestly expect the Spurs who are always draft toward the end of the first round to produce as many wins shares out of out of a draft as a team that’s drafting in the top 3 where they’re liable they’re likely to pick a future superstar. But it was it was the Lakers.

[00:22:49] It was Mitch Kupchak 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 he didn’t get much credit when I did the study for drafting Mark Casal 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 I think that’s the only thing I’ve ever done to contribute anything to NBA analysis is with me.

[00:23:24] I realize that helping is not actually his not reference. We’ve talked about Moneyball which was the book and then a movie and helping hasn’t said anything about draft day in his beloved Cleveland Browns scene which is a scam.

[00:23:37] I also have not seen that movie and I feel as a fan. We’ve moved past that point in time.

[00:23:45] It was a bit of a timelike movie. Also you didn’t really miss anything.

[00:23:49] Yeah I know what happened in each of those drafts I was there. I was live tweeting. No I don’t usually live tweet the dress but I do I usually am glued to my computer or television during the draft. Watching all of that happen and seeing how disappointed the Jets and the Philly Eagles fans are with their picks because they always are. No matter what.

[00:24:11] But no it’s yeah it’s just draft Analytics a portable skill. 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. 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. Can I take that methodology and apply it to a different sport.

[00:24:34] I don’t see how you could even be difficult because of the measures and stuff are all different right.

[00:24:41] 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 or 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 you know 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 there’s I’m sure there are some models you could come up with.

[00:25:30] Well I mean the two sports that I think are closest actually are basketball and hockey because other than the 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 that scenario and that’s why whenever I’m out having a couple of pops and I started getting analytics nerd and we’re talking more 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 multi variant 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 that’s your draft profile potentially anyway. That’s the thing I nerd out about always testing and attribution.

[00:26:38] Well the NBA has that rate plus minus on the floor.

[00:26:44] Well even so even going beyond plus minus Kirk Goldsberry who does a lot of the spatial analysis he’s kind of the leading NBA spatial analyst that’s that’s out there and he I think he read for Grantland and he’s a professor at Harvard. He he’s come up with this with a way to quantify I mean it literally is attribution. He’ll take each movement of the basketball between players receive use of value based on a number of factors like that amount of time left on the shot clock and who the balls being passed to someone who shoots particularly well from that area of the floor. He’s he’s come up with these fairly advanced models for attributing success back to someone who made a pass maybe six passes ago in a possession which is wild you know stuff that you know even five years ago seemed to seemed impossible to an NBA fan. So yeah stuff exists if you want to trade a guy.

[00:27:39] And plus minus is the number one stat that you’re looking for. You weren’t afraid someone put them on the line with the best player in the league.

[00:27:45] So no know they tried that with Matthew Dellavedova and it almost worked.

[00:27:52] I don’t know what that is but he sounds very talented and not like a hockey player.

[00:27:56] You know he actually might be equally successful in hockey. I could tell he’d be an enforcer. Yeah. Oh for sure. Q Cleveland sports fans have it rough.

[00:28:07] That’s what I’m trying to say that least you have more than one team. If I didn’t like auto I would have to do hockey. We’ve got one team one sport. I just happen to like it so I win. There’s no CFL team. I don’t consider the CFL to be a sport. And I can see that lag so I don’t think any Canadians listen to this podcast. There were red flags. We just renamed the team the auto red blacks a couple of years ago and Tom Green said only in Ottawa could we be racist twice.

[00:28:33] We’re naming three Washington D.C. We’re tired of being the thought of country to the north.

[00:28:45] So he is down on our bigotry here in Ottawa.

[00:28:49] Here’s a quick question and we probably need to wrap things up. Ben gains a lot of our listeners or analytics folks and some of them may even be sports fans. What if they wanted to dig in and go beyond maybe the 538 stuff and get a little deeper into a topic where where would you send somebody. What resources are out there for people to get a little more information. So you mean in terms of like just getting your hands on the data or yeah or just what’s cutting edge I mean you’ve mentioned a bunch of folks you know in basketball analytics Craig Taspinar and so on like what other types of things or Web sites we think would be a good read or something like that. Okay.

[00:29:31] Yes so. So my sort of go to basketball analytics. I don’t actually I don’t think I have a baseball there. There are a ton. Take your pick. But for basketball there’s a site called nightlong calculus just nightlong calculus dot com basketball numbers for the people and it’s a blog. Ultimately it’s high level enough that you can you know you can dive into it and they have like tutorials on tutorials but just introductory material on different metrics that emerging NBA analysis but then they also have some very pointed studies on like I’m on there right now and there was a post the other day called more on the postscripts on the postscript to a shot block.

[00:30:14] So like talking about what analysis into what happens after a shot is blocked and how you know certain players are better at blocking a shot in bounds as opposed to out of bounds 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 part no 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. And when it comes to getting our conclusions accepted and our recommendations are taken seriously and getting invited to the right meetings and all of that stuff that we deal with so I would start with my long calculus that’s the one I find myself going back to over and over again. And in terms of the data NBA dot com is really really I think forward thinking in the amount of data they provided access to it. If you go to I think it’s Stanstead and Gay.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 SFP 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 Jim. The dash reference dot com franchises so basketball Dasch reference dotcom baseball Dasch reference dotcom tons of data there you can do custom queries you can compare players across eras.

[00:31:42] It’s the kind of site where you’re a data nerd if you love playing around in data you can easily find yourself up at 3 am not realizing that you’ve stayed up no 3 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 nuance databases available that are things like player salaries and things. But you know for the most part those are my my go to sites.

[00:32:10] So the hyper motivated analyst who wants to learn are and dig into data. You can go to a dash reference dot com big data set and then throw it into our go to town.

[00:32:22] All the major sports also hockey.

[00:32:25] Jim I think I counted that they do have they have hockey that’s referenced dotcom that exists.

[00:32:33] You know all the history of the Calder Trophy because that’s what I’ve always wanted the Calder Cup rookie of the Year trophy.

[00:32:39] We’re talking after the show. 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 but the Bing Memorial Trophy the player who displays gentlemanly conduct.

[00:32:56] Is a good one. To make me hate you. Doesn’t look like an award.

[00:33:02] It’s 2010 11. Martin is going to have a lock on it for two years.

[00:33:07] Maybe it was Martin from St. Louis or he is French Canadian and as Martin said anybody who doesn’t matter who in St. Louis you can edit that out to you. You are a sexist the hell out of that guy’s name.

[00:33:24] They were defining Ugly American. 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 they want to share.

[00:33:40] 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 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 ram not taking your job in terms of getting people to listen and all that other kind of stuff. The other thing is I never thought about it before but you know there’s 10000 people that want to be the next assistant to Billy Beane and I have a hell of a time finding someone that wants to look at you know Panne session attributes data for a nonprofit organization. I read sports like people painstakingly for days of work build blogs doing analysis on hockey before they go back to their daytime job. 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 because actually the marketing analytics or digital analytics is equally awesome but you know if if you can find the same level of passion for your gig that some of these sports people have for the work they can do on evenings and weekends that I think is comparable in quality. You’re going to be a V.P. someday.

[00:34:59] I like it. Well again we would love to hear from all of you. So are your way into a sport and you’re digging in the analytic side of it. Let us know on Facebook dot com slash and next hour or on Twitter or on the measures like the instructions or 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 injured. 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 want to talk about which was a sneak peeks on Adobe analytics.

[00:35:40] I had a great time tonight if you want to have me back. I’m all about it. Well super gracious of you. All right.

[00:35:47] Well hey from my cohost Jim and Jim. Thanks everyone. Thanks again to ban and. Keep on analyzing. Rough go.

[00:36:00] Thanks for listening. And don’t forget to join the conversation on Facebook or Twitter. We welcome your comments and questions. Facebook dot com slash. And on this next hour. Now on Twitter.

[00:36:24] You’re trying to make that a thing. It is. 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 going to do live calls tonight people asking any question they want. I know you’re getting paid. I know you can afford a haircut. Who knew the Cleveland Browns would be sitting alone in a top to AFC north at this point. I think that battle it demystified as a strong highlight analytics practice. I’m still here and I am not good at sports. And then we end up drinking and making fun of how. Here is one. It’s just a giant. Pretty sure I could even hear people pausing the podcast in Jim’s whole NHL so little or no respect.

[00:37:21] It’s going to be this tension between like games I love I adore big games. Been fighting with I could give a shit about sports I could give it maybe. Oh and people that are just shit will get shut up when kids get tons of them or.

[00:37:39] There’s a payoff for everyone who’s willing to listen to them. Yeah.

[00:37:43] Nice. No not nice. Here is.

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