Nylon Q&A: Jordan Sperber of Hoop Vision Coaching Analytics

Last week Jordan Sperber of Hoop Vision and the Video Coordinator for the New Mexico State University men’s basketball team shared his first edition of his Hoop Vision Coaching Analytics newsletter. Although it is aimed for Division I coaches and programs in mind, here at Nylon we love everything about basketball especially when it comes to analytics. Jordan brings a great background and perspective to the conversation about the combined use of basketball analytics with traditional non-analytics to make the best basketball decisions and we recently were able to catch up with him for some questions about his work. Check out his first newsletter here, subscribe here and follow him on twitter!

Nylon Calculus: First off, thank you for taking time to answer some questions. I know many of us at Nylon Calculus and those who follow are excited about your new newsletter series Hoop Vision Coaching Analytics. Before we jump into your first newsletter, for those who are not too familiar with your background, you started Hoop Vision while you were a junior in high school. As far as my research goes, not a lot of juniors in high school are starting their own basketball analytics website. What was the inspiration of putting that together?

Jordan Sperber: So early on in high school I read Moneyball, I was into baseball, sabermetrics and Fangraphs especially, but I played basketball and it was always my favorite sport, so it was a matter of time until I discovered Basketball on Paper by Dean Oliver. At the time sports blogs were popular and there were about 5 to 10 really good college basketball ones with analytics slants, but it was a little bit different back then without Twitter. I started Hoop Vision my junior year but I put it aside senior year because my varsity season was pretty hectic, but in college I pretty much went full swing at it.

NC: So what did your parents think about it?

JS: My parents were supportive, they definitely read everything (laughs). The funny thing is when I started the blog I wanted my name to be absolutely nowhere, because I didn’t want anyone to know that I was in high school. By the time I was in college and was planning on making a career out of basketball analytics, it was the complete opposite and I wanted to get my name out there and network. So my parents might have been one of the few that knew about it at first.

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NC: You kind of touched on my next question here, but you mentioned there was a time when you wanted to get into basketball analytics as a profession. How did your experience and work with Hoop Vision open up opportunities and angle you into that direction?

JS: I think it was my sophomore year of college when I got emails from Coach [Eric] Musselman who was an associate head coach at Arizona State at the time and Coach [Paul] Weir who was an associate head coach at New Mexico State after they read Hoop Vision. Those two coaches ended up giving me my first two jobs a few years later. It definitely opened up doors, coaches were interested and would get on the phone with me to talk more about certain topics. From there it was just staying in touch with them. Working in college basketball as someone who wasn’t a college player or manager is not easy. Most entry level guys were either managers or players for a program. So the website was my way in, which was a little unconventional.

NC: I think what is most interesting is that often times those who are into the analytics side generally tend to gravitate towards more of a front office type of role, but you seem to be more involved in the day-to-day operations of the basketball programs you’ve worked with (now currently at New Mexico State). What led you to want to work more at that level as opposed to a more front office type of role?

JS: Well, another thing I was doing during high school was working in player development. I spent time working out younger players that went to my high school my senior year, helped coach an AAU team, and obviously played too. I guess maybe people who are trying to make a career out of analytics don’t normally have those interests too or maybe that’s wrong, but it was something that made me a little more unique. I would like to think that even without basketball analytics I would still be working in basketball, probably coaching in some capacity. I’ve been obsessed with all areas of the game – from shooting mechanics to X’s & O’s to analytics – for as long as I can remember. I even have a YouTube video with over a million views about the Shammgod crossover.

NC: Basketball analytics is growing in general, but has really taken off in the NBA, so what made you want to stay in college basketball as opposed to trying something with an NBA team?

JS: I don’t know if there is a bigger college basketball fan than me. Growing up I didn’t just watch my favorite college team, I’ve always been someone who has wanted to watch all 351 teams. I watch a lot of NBA too and I am a big fan, but college has been the priority. However I don’t think I ever consciously chose college over NBA, it was somewhat more about the luck and opportunities I had. It’s different though, the NBA is all basketball all of the time, where college has a lot more of a variety in terms of day-to-day workload.

NC: So getting into your first newsletter, you mention that it is kind of the first of its kind in terms of “coach analytics”, what do you mean by coaching analytics?

JS: First and foremost, the newsletter is aware of its target audience. Communicating analytics to coaches requires different language and terminology than communicating with a stats professor. So that’s the first distinction I’m making when I say coaching analytics. The other part is that theoretically the newsletter is aimed to cover the “profession of basketball coaching”, not necessarily the “sport of basketball”. That might just be semantics and clearly there is a lot of overlap between the two, but future newsletters should shed some light on the distinction. For example, I have a rough outline for a full newsletter on different ways of using analytics to better evaluate yourself as a coach, evaluate your program, and look towards the future as well.

NC: You also mentioned that it is a “conversation starter” for coaches, so what type of conversation are you hoping to start? I know the NBA is warming up to the use of analytics, but is college still more traditional in their approach or are they warming up to the use of analytics in their programs too?

JS: With 351 teams and a head coach and three assistants for every team, there are bound to be plenty with interest in analytics. Generally I think the younger the coach the more they have been exposed to analytics and more specifically exposed to Kenpom. Almost all colleges have a Kenpom subscription, so many understand why rebounding margin is bad, to use offense and defensive rebounding percentage and the rest of the four factors. I don’t think many of these coaches would even consider themselves analytics people. But their scouting reports and when they watch film, they kind of have those basic concepts in mind, it’s almost not analytics anymore, it’s just basketball thought, so I think it bleeds in a little bit. On the other hand, I have definitely talked to different director of ops or grad assistants from other programs that have said their head coach is not open to analytics. Drew Cannon broke in at Butler as an analytics specialist in 2012. I would’ve thought we would see more of that by now, but it is slowly growing.

NC: How much do you think that is a result of the limitation in available data? The NBA is fortunate enough to have access to finer detail such as SportVU data, but on the college side that seems to be overall lacking.

JS: Yes and just resources in general. Especially at a mid-major school it would potentially be hard to justify someone who is going to solely do analytics with no other responsibility. At the college level you just have to be able to wear many different hats: academics, skill development, X’s and O’s, video, player relationships. In the NBA it is more setup to specialize because of the resources and the data.

NC: One of the many great points you brought up in the first newsletter was the dynamic between understanding basketball through film and on paper through analytics, especially with how a great scout and a great analyst can take their respective information and both maximize its usefulness while discarding unimportant information. You introduce concept of the “new-age” basketball thinker who can incorporate both of these types of information to make better decisions, which is a point I think is often overlooked within the basketball analytics community. Through all of your experience, where do you see basketball analytics ideally fitting in the decision making process from your perspective?

JS: Mmm . . . yeah . . .

NC: I realize I just asked a deep philosophical question. . .(laughs)

JS: I think at least working in college basketball as an analytics guy you have to understand your role in the decision making process. So I would say that it definitely works in tandem. A scouting report is probably the best example, you can have a page for the opposing team with key things that numbers are telling you and incorporate that into the rest of your traditional scouting report. Kind of like that part of the newsletter said, you can use both types of information to make the best decisions. One of the goals of the first newsletter from a college coach’s perspective was try and show some things that coaches haven’t thought about from analytics, like in recruiting. I do think, just because of how many kids you have to recruit and just the scope of it, that potentially analytics could be a solution. Now I did get some feedback that AAU stats aren’t quite reliable enough yet. But if we assume valid data, then there might be some areas where it can have an even bigger role.

NC: Out of that first newsletter, what type of reception did you get from it?

JS: I was probably most surprised by the reception received by the NBA. Whether it was with you guys at Nylon Calculus, subscribers who work for NBA teams, or other NBA writers. So that was pretty neat because I definitely set out thinking about college coaches. From college coaches, they were also interested and asking questions. The goal to start a conversation was pretty successful, a handful of coaches reached out to either ask questions or give me their take. Newsletters in basketball are very common whether it’s X’s and O’s or motivational, I do think most of them are started with the purpose of networking and that’s also a goal moving forward.

NC: Lastly, without giving away any secrets, how do you plan on carrying this conversation forward in future newsletters?

JS: College coaches haven’t fully embraced analytics, but one thing a large majority have embraced fully is lineup data. Meaning how each lineup combination does while on the floor together. And believe it or not I think they actually overuse lineup data. So I don’t know if I’ll have to do a newsletter on how analytics can be bad (laughs) or a full newsletter literally on lineup data because I feel I have a lot to say about that. I think lineup data has a lot of value, but it kind of goes back to the first article in the newsletter about predictive versus descriptive. I think college basketball lineup data is entirely descriptive and I know plenty of head coaches who use it as predictive. In other words, they are willing to change their substitutions based off of extremely small samples. So that is in the future. A lot will largely be dictated by feedback from coaches. This morning I was texting a D1 coach who had a bunch of great questions and ideas that weren’t necessarily in my plans. There certainly won’t be a shortage of topics going forward.

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