Archive for 24 March 2012

FAQ

Eight months ago, on this blog, I described with excitement my decision to leave Adobe and join ESPN as an analytics manager. At the time, I knew that I was embarking on a tremendous learning experience, and I thought I even knew how everything would go. Sports, analytics, and New England; how could I lose? Call it a youthful sense of invincibility, if you will.

Well, as of this past Monday, I have rejoined Adobe, and I am thrilled, excited, and grateful for the entire turn of events. The Adobe Digital Marketing Summit took place this past week in Salt Lake City, and as I wandered the halls of the Salt Palace among colleagues, customers, and industry folks, a few things happened.

First, I felt like I was home, immediately. Second, I answered a barrage of questions about the past eight months. I took mental note of these questions and I’m going to answer them here, in good old FAQ form. So here we go.

FREQUENTLY ASKED QUESTIONS ABOUT BEN’S RETURN TO ADOBE

Q: So. . . what happened?

A: This is actually a tremendously complicated question, but I will simplify it by saying that once I started at ESPN, I quickly started to realize that making software is what gets me out of bed in the morning. When one of the engineers at Adobe asked me this question, I told him that I was sure he could go be a fantastic analyst, but he probably wouldn’t enjoy it—he needs to be programming and solving problems using code. That’s just in his DNA. I certainly could have stuck it out—and, in fact, tried to stick it out—but it wasn’t for me. If I needed to spend this time in order to learn that lesson, I can’t say that it wasn’t worth it. I’ve got a strong sense of direction for the foreseeable future, and that’s valuable.

Q: How were the people at ESPN?

A: They were great, and I consider many of them friends. In fact, I saw them at Summit and it wasn’t weird. . . well, it wasn’t too weird, at least. I’m so grateful that they gave me a chance. They’re brilliant and they are doing cutting-edge things with digital analytics. If you ever have a chance to them talk about cross-platform analysis, as my former VP Dave Coletti did at eMetrics NYC last October, you will know what I mean.

Q: What will you be doing at Adobe?

A: I’m returning to the Product Management team, working on analytics products—SiteCatalyst and more. When I originally joined that team almost two years ago, I wrote that I felt like a minor-league baseball player getting the call-up to the majors to play with his heroes. I still feel that way, and am excited to be part of such a bright and talented group. It seems that Adobe’s recent acquisitions have only added to the brainpower and passion. I hope that I now bring at least a little bit of unique insight having been an analytics practitioner for most of the past year.

Q: Are you staying in Connecticut, or moving back to Utah?

A: Actually, we have really enjoyed our time in Connecticut. The area is beautiful and our neighborhood is full of kids who want to play with our daughters almost constantly. But we still own our home in Utah, and rented in Connecticut, and it’s time to get back to the family and friends that we’ve missed so badly. But we had a great quality of life in both Utah and Connecticut. We will definitely miss Connecticut and hope to visit our friends there in the future.

Q: Why did you go back to Adobe?

A: First, as I mentioned above, I need to be in tech/software. That’s a given. Second, I believe in what Adobe is doing in digital marketing and I want to be a part of it. Third, there is a reason that Adobe consistently appears on Fortune’s “top places to work” list. It really is a fantastic company in too many ways to list here, but I especially love the way Adobe trusts its employees and values input from all over the organization. At least, that has been my experience, and I hope it will be again.

A personal appeal to Jazz fans

I loved this quote from Bill Simmons’ recent 2012 NBA Trade Value column:

On TV a few weeks ago, Chris Webber said something that made me say, “I wish I had thought of that first.”They were talking about trades, and C-Webb pointed out that championship teams are always stubborn. In other words, instead of caving to the whims of their fans, the pressure of the media, the ebbs and flows of a season (or even someone’s career) or especially conventional wisdom, they say to themselves, “Screw this, I know what I have, I’m sticking with it.”

So, Jazz fans, you want a GM with a championship mentality, or one who wavers and waffles?

I know you hate Kevin O’Connor’s strategy: get very young, develop talent, suffer through a few seasons in the lower half of the conference, then emerge with a core that can contend for a top spot in out west. You want to win now. If you could trade Paul Millsap or Derrick Favors for a wing who can shoot, you would do it in a heartbeat, even though it would only make the Jazz a seventh or eighth seed in the playoffs, right? It’s almost like you expect not to be alive in two or three years, and all you want to do before the heart attack comes is see one more Jazz playoff series, at any cost.

You’re being ridiculous. Here are two people who are on record saying that they see O’Connor’s vision and they like it: John Hollinger and Chad Ford. It’s cute that you have 1,300 Twitter followers, but you don’t know the NBA as well as those two men do. I’m sorry, but you don’t. (I certainly don’t, either.) When they want to understand what the Jazz are trying to do, they can actually pick up the phone and call people around the league to discuss. Or they use (or invent!) advanced statistical measures that give us more an accurate, data-driven sense of what is really going on. In most ways, we can’t compete with that. We see C.J. Miles jacking up threes early in the shot clock and we cannot understand why that guy is on the Jazz roster, without bothering to understand that C.J. has actually been a more efficient offensive player this season than Kyle Korver. (I’m not defending wasted possessions, just pointing out that our view of the world is heavily skewed sometimes. It’s confirmation bias: we tend to see evidence that supports our position. We see the worst in C.J. because we’ve already decided that we dislike him.) This is all that Hollinger and Ford do. (Well, Ford also teaches at BYU-Hawaii, actually.) This is their life! They’re certainly not always right, but are any of us? I’ll take my chances with two smart, accomplished, respected NBA analysts, and they’re taking their chances with a stubborn Kevin O’Connor.

Look, if we were talking about a perennial bottom-dweller then I would say sure, let’s talk about firing KOC. You’re so used to winning that you have no idea how weird life could be under David Kahn or Bryan Colangelo. Growing up in Boston during the M.L. Carr and Rick Pitino eras, let me tell you: I know what a franchise devoid of direction looks like. Stubbornness is most definitely a positive trait.

You’re welcome to hate this team, hate the coach, hate the GM. But by ignoring your persistent whining and demands that KOC mortgage the farm for Rajon Rondo (who, by the way, is a HORRIFIC outside shooter) or Wesley Matthews (he’s not coming through that door, to borrow a line from the aforementioned Pitino era in Boston), O’Connor is actually displaying a trait that demonstrates one reason why he is general manager and we work elsewhere.

So here’s hoping that KOC ignores us all and sticks to the plan.

(I will now record a YouTube video in the style Chris Crocker called “LEAVE KEVIN O’CONNOR ALONE!” Where did I put my blonde wig?)

Sloan Sports Analytics Conference: Day Two

As I have been tweeting, blogging, and updating Facebook about the Sloan Sports Analytics Conference, I keep hearing comments like: “I wish I could go, but I will never be able to” and “this is definitely on my bucket list now.” A few things about this. First, at $500 for non-student admission, it’s a bargain; even with hotel and airfare I’ll bet most of you could do this conference for well under $1,500, and it will be a truly memorable experience. So start saving a few dollars a week in a cookie jar today. Second—and I don’t think people realize this—anyone can attend. You don’t need to work for ESPN or an NBA franchise. My sister has a friend who does Account Management for Google, but he loves sports and analytics so he pays his own way to fly out every year from the Bay Area. All are welcome.

The other thing which pleasantly surprised me (I touched on it yesterday) is that you do not need to be a Ph.D. candidate in advanced statistical modeling or econometrics to thoroughly enjoy the conference. There were some sessions that really stretched that area of my brain, and others that were accessible even to non-sports fans, let alone non-academics. So don’t let that scare you away.

Highlights and thoughts from day two:

  • There was a request on Facebook to hear more about Bill James. As the godfather of the Sloan Sports Analytics Conference, he was definitely one of the stars of the show. Unfortunately, I didn’t feel like he shared much new information about himself or his work. Simmons did a live BS Report with James at the end of day one, during which they rehashed his rise from unheralded part-time stats geek to patron saint of sports nerds, but it’s all stuff we read about in Moneyball. Day two featured a “Boxscore Rebooted” panel with James, John Thorn (MLB historian), and John Dewan (baseball info solutions), but most of it is so widely accepted in these circles at this point (“Wins for a pitcher is too arbitrary! The Internet makes analytics easier!”) that I barely took notes. To be honest, it felt really strange to be so nonplussed by this guy who quite literally invented advanced baseball analytics. In talking to a few other attendees, I got the sense that I’m not the only one. We all have tremendous deference for what Bill James has given the world, but he does not seem to be on the bleeding edge of sports analytics anymore.
  • The conference (at least this year) leaned heavily toward basketball, probably because the millennials who dominated the conference are in a demographic where the NBA is excelling, whereas I believe I heard that the average baseball fan is between 45 and 55 years old.
  • I reviewed three basketball-themed research papers in yesterday’s post, but the best was yet to come. The two best research papers by far (in my mind) dealt with “spacial analytics” in the NBA, meaning the study of where the 10 players and the basketball are placed on the floor (or in the air) when key events occur, as opposed to pouring over isolated numbers to obtain insight. Jared Dubin of Hardwood Paroxysm did an excellent job reviewing these two presentations (he even has screen captures), so I won’t go into too much detail.
  • I will add that I thought the rebounding study was not fully matured—it presented a ton of potential to help teams understand how to position players in rebounding situations, but it wasn’t quite there yet. Key Insight: Teams’ offensive rebounding percentage decreases significantly the farther the shooter is from the basket, until you get to the three point line. Behind the three point line, offensive rebounds are more common than for mid-range jumpers. Especially considering that neither a mid-range jumper nor a three is likely to generate a lot of free throws, it stands to reason that mid-range jumpers are the least effective shot on the floor (which we’ve all kind of known for some time, but it’s nice to have data to back up the theory).
  • My absolute favorite research paper was Kirk Goldsberry’s creation of the “Range %” number, a statistic which tells us the percentage of spots on the floor where players are effective scorers (defining “effective scorer” as “one point per FGA”). The average NBA player is effective from 17.2% of the 1,284 spots on the floor that Goldsberry measured by breaking the floor into a grid. Even though Tyson Chandler leads the NBA in FG%, he is far below average in Range %, scoring effectively from just 4.3% of the floor (not that anybody thinks Chandler’s high FG% means he is a great shooter). Dubin recaps the top few players in Range %. I was mildly surprised that Steve Nash beat out Ray Allen for the top spot (using data from 2006-2011), but mostly the data confirmed what you would expect in terms of the most comfortable shooters and least comfortable shooters. Key Insight: I can’t express this in terms of a specific recommendation, but Goldsberry’s most immediately applicable contributions are “heat maps” which show exactly where players are effective scores, as well as where they are less effective but still love to try. If I were a coach, I would buy Goldsberry’s technology (he did have a chance to share his methods with Mark Cuban at the end of the conference, so I assume the Mavs will be employing it shortly) and try to get my defense to force opposing scorers to the spots on the floor where they can be coaxed into shooting despite low effectiveness. Similarly, I would design plays that put my players in the best position to score from spots on the floor where they shoot well. It’s not rocket science, but I believe it would work. Isn’t this the kind of thing that Shane Battier has been doing for years? (And where has he been getting his data? Presumably just from video scouting. Goldsberry’s method is more complete.)
  • Best panel of the entire conference in my mind was Saturday’s “Fanalytics” featuring Bill Simmons, Jonathan Kraft, Tim Brosnan (EVP Business, MLB), Nathan Hubbard (CEO of Ticketmaster), and John Walsh (EVP, ESPN). It was supposed to have Mark Cuban on it as well, which would have been even better, but Cubes was running late. The whole thing was about improving the fan experience through technology. This one deserves sub-bullets:
    • The NFL is improving in every possible metric except for fan attendance. Today’s fan needs to be able to use the Internet on mobile devices (for Twitter, fantasy football, live video of other games, etc.) or they won’t come to the game. Mark Cuban doesn’t want people using their cell phones at NBA games, but the NFL recognizes that its whole fan experience model is different because of the pace of the game (frequent stops and starts) as well as the nature of the NFL (everything is happening all at once, on the same day of the week).
    • Kraft: “We’ve spent $2-3 million [to upgrade WiFi infrastructure at Gillette Stadium] in the last couple of years.” He continued, saying that to allow 70,000 people to stream video over WiFi at Gillette would cost “literally tens of millions of dollars.”
    • Simmons asked whether it would be feasible to charge different prices for tickets not just by section, but by individual seat. For example, one section at an NBA game might stretch from the baseline to almost mid-court, and why are those tickets priced the same? I had wondered this, since obviously the technology to price tickets on a seat-by-seat level exists. The answer is that if a fan sees that the guy next to him has a different face value on his ticket, he is likely to get resentful and angry. So they do it by section and live with the fact that this isn’t fully optimized pricing.
    • On the night of the AFC Championship Game, when Kraft wanted to relive Billy Cundiff’s missed FG, he went not to NFL.com, but to YouTube. This is surprising since the NFL maintains strict media rights, and the video was available on NFL.com. Why YouTube? Because a guy sitting in the endzone had the perfect angle to film the kick sailing wide left, and had uploaded the video. It was the best angle Kraft had seen. The lesson regarding NFL media rights and fan-shot video? “You can’t stop it, so you better start learning how to use it.”
    • TicketMaster operates both a primary ticket vendor and a secondary market vendor (TicketsNow), so they can use Omniture (nice shout out for my friends) to analyze ticket re-selling and compare with original sales. According to Hubbard, “Technology is showing us that our tickets are worth more than what we’re selling them for.”
  • Weird recurring theme of the conference was presenters’ inability to pronounce player names. The professionals did not have this problem, but the student researchers did. The two most egregious (and there were others) were the old classic “Da-RON” Williams instead of “DARE-in” and the even-less-excusable Kevin “Dur-ONT” instead of “Dur-ANT.” I mean, Kevin Durant is a top-three player. How can you be presenting on the NBA at a conference of sports nerds and not pronounce his name correctly?

I could keep going, but I need to stop somewhere. Suffice it to say, SSAC was an absolute blast. I can already see myself looking at certain aspects of game action and the sports world at large a little differently, in a good way. As I said to people numerous times during the conference, I will definitely be coming back, even if I have to plunk down my own money to do it. Sports and data, together at last. I think it’s a beautiful thing.

Sloan Sports Analytics Conference: Day One

It’s time for a different sort of analytics conference. The eMetrics festivities may not start until Monday on the west coast, but 2,200 sports dorks gathered in Boston this weekend to talk about sports analytics in the annual MIT Sloan Sports Analytics Conference.

What does this mean? Well, the sports world is full of data. Every dribble in basketball, every pitch in baseball, every snap in football generates new data points that we can analyze to understand the games we love. Last season, the Dallas Mavericks used advanced analysis to determine that their best starting lineup included J.J. Barea. They made the change. . . and won the NBA title. Analytics isn’t just for business anymore. That is what this conference is all about.

I won’t give a travelogue. Instead, some general, brief highlights and observations, from the perspective of a sports fan and digital analyst.

  • I know I just said that the conference is about analyzing the game and the players, but I was surprised at the amount of a.) sports strategy discussion devoid of data, and b.) sports business analytics (e.g., StubHub discussion ticket sales analytics; ESPN, NBC, and others discussing the world of media rights). There really is something for just about everyone.
  • There is a LOT of crossover between digital analytics and sports analytics. Maybe the tools are different, but the principles and challenges are the same. The basketball analytics panel featured a bunch of quotes that could have occurred at eMetrics or Omniture Summit:
    • “There is ‘counting things’ and there is ‘analyzing the things you count.” -Dean Oliver, ESPN Stats & Info
    • “Statistics do two things as a coach: they allow you to figure stuff out, and they allow you to communicate.” Jeff Van Gundy, ESPN analyst and former NBA coach
    • “”A lot of times in analytics, you don’t want to come out with a single number.” -Oliver
    • Oliver also talked about preparing insights for coaches, and said that he used “very few numbers” in these reports, instead translating everything into words that coaches (i.e., executives) could understand.
  • The people at this conference are crazy smart. 73 professional teams and something like 175 colleges are represented. I couldn’t even follow a lot of the math/statistics in the research papers. Unlike some conferences I’ve attended, I was mentally worn out by the end of the day. Great feeling.
  • This conference is a tremendous value. Admission was less than $500, in exchange for which you get to see the greatest minds in sports debate cutting edge strategy and analytics, and they are all accessible. If you ever wanted to ask ESPN’s John Hollinger a question about NBA analytics, this is the place to do it. People like Bill James wander the halls just like anybody else.
  • Jeff Van Gundy was a revelation today. Everything he touched was comedic gold. We’ve become familiar with his wit during the ESPN NBA broadcasts, but he was in fine form today, tossing out sardonic commentary at every opportunity. Everyone I’ve talked to has agreed that we all need more Jeff Van Gundy in our lives.
  • Just a few sports insights and possible recommendations, if you’ll indulge me. The great thing about sports analytics (for me) is that it’s REALLY easy for me to see the kinds of recommendations you might make based on the data.
    • One study of performance under pressure showed that the home team shoots free throws worse than usual in late-game, high-pressure situations, whereas the away team is unaffected. The reason, they hypothesized, is that the crowd tries to avoid distracting its own team in these situations by getting very quiet, which inadvertently allows the player to focus on the action of shooting, causing them to “overthink” the shooting motion. The away team has fans yelling and jumping during their free throws throughout the game, so there’s no real difference. Recommendation: Fans shouldn’t get silent during home team free throws late in the game.
    • Another study took the concept of plus-minus and broke it out by individual skills, making it possible to see how players impact their teams in very specific ways beyond top-level stats. They also demonstrated that some skills are synergistic, meaning that putting two players who excel in a certain area on the floor together make both players (and other team members) better in that area than they would be otherwise. The whole ends up greater than the sum of its parts. Recommendations: Find synergies and build rotations to maximize plus-minus in key areas. For example, put players who create turnovers on the floor together to get even more bonus turnovers.
    • Finally, a study attempted to show the relationship between  experience and playoff success; do teams require experience in order to succeed in the postseason, as is often assumed? The answer was no. Experience does not matter among players. Young teams fare as well in the postseason as experienced teams. However, coaches who have coached in the postseason before perform better in subsequent playoffs. Recommendations: Depending on your team’s situation, consider not overvaluing veteran leadership. Also, look for head coaches who have coached in the postseason (even if they haven’t won titles).

It was a very full day, but tomorrow looks great as well. Time for bed so I can fill my brain with more sports analytics tomorrow.