MIT Sports Analytics Conference: Random Ramblings on “Revenge of the Nerds.”

I took notes on the “Revenge of the Nerds”  session at the MIT Sloan Sports analytics Conference. .    Here are my random ramblings.   It’s incomplete, possibly wrong, and certainly has typos.   Deal with it.

Panel Leader:  Michael Lewis, Author of Moneyball.

Mark Cuban, Owner, Dallas Mavericks.
Paraag Marathe, COO, 49ers.
Daryl Morey, GM, Houston Rockets.
and returning champion,
Nate Silver:  Statistician, Psephologist, and Author, fiverthirtyeight.com.

Paraag:   Each pick has a currency value:  what’s the right value for each pick?   Started 2001 to negotiate contracts, personnel decisions. Were in Salary Cap Hell for a while.  12 years later, almost Super Bowl

ML:  Were you shock there was a career in this?

PM:  Yeah:  To get in, it’s about who you know.   Insular.  Cracking the world is hard.  Opportunity is not always fair in sports.

ML:  Is the work meaningful enough that you’re satisfied? Or will something new come along ?

PM:  Seeing how people reconnected at the SuperBowl was very uniting, brought team families together. That may keep me here.

ML:  Darryl, You?

Darryl:  2nd grade:  Bill James’ Abstracts.   Get a Commodore 64 when you’re young.  Playing Fantasy BB, got depressed at Northwestern.  StatsInc:   applied there, made myself nuisance,  until they hired me.   (Don’t do that, It worked once).

ML:   Is this a career endpoint?

Darryl:  Yes.  I think it’s a miracle I got this job pre FB era.  I have lots to thank.

Nate:   MY athletics career ended in grade 6.   Studied Econ a U Chicago.  Stat nerd as a kid. Consultant in 2000.  Bored as shit.  PECOTA sold to Baseball Prospectus.  played poker.  It bubbled.

ML:   There’s so much young intellectual energy crashing this party. Exportable? Sports is a great lab.  The kind of thinking here applies outside of sports.   Nate: you’re a good example.   You left sports, and had this huge effect in our political life.  Are you special?

NS:  Playing Fantasy, etc. is a good way to learn applied statistics.  Sports has great data sets.   Good criteria for success.  Very testable.   In politics, you can be wrong for four years at a time.  In spots, there’s “justice,”  I guess.  Great way to get your training wheels.

ML –  but your path is ODD.  Are there others?

NS:   Sabermetrics is light years ahead of anything I did.  Amazing what’s being done in sports.

ML:   Mark Cuban:  What’s your sports resume?

MC:   I was an all star player in HS.   In Basketball,  a JCC AllStar (LOL).   I was a fan, always an entrepreneur.

In 90s being a Mavs Fan was hard.  Sitting in the empty stadium when the Mavs undefeated, I got … “As a businessman, I can do a better job.”  Always from a business perspective. Paraag said, “12 years to get within 5 yards of a title.” That’s how I feel.  But when a sports team wins, the whole city changes.  The entire city .  I have a losing team right now. It’s really painful.

ML  were you aware of the data revolution?

MC      Yes:   I took grad Stats at Univ Indiana:  Wayne Winston used Sports as a foundation for problem solving.  I buy the team,  and then I turn on Jeopardy…  My professor Wayne is there, kicking ass!  I contact him: let’s start evaluating teams.  We started digging heavily into analytics.  Most teams didn’t know what it was.

ML:  Once you went down this path,  did you see  clear misevaluations of talent?

MC:  Yes! …and owners were pissed. They told me,  keep your mouth shut.  Other owners going Mr T on me.

ML:   When Moneyball came out,  I was shocked how controversial/angry people got… but I was costing people jobs, so I get it.   Status is big in sports. Your pecking order matters and you’re dealing with high testosterone males.  The Moneyball argument disrupted his structure.  It revelas that the GM is more important than the coach, perhaps.  That was troublin I’m wondering:  when you first hit the sports world:  what kind of friction did you encounter?  Now, what’s it like?

Mark:   Now,  no friction, I own it.  Now, I have years of data. Then, I didn’t know how well it would work.  Don Nelson, our old Manager, was still there. Trying to strike a balance.  #1 job is to keep your job.  They will take huge risks.  Incentives are screwed up.  As a decision maker:  talent evaluation vs analytics.  BB doesn’t have great analytics yet.

ML:  Even as the owner, is it more/less easy to impose new ideas?

Mark:  Easier.  Now,  you need to look how they reverse engineer their thinking.

Parag:   It’s amazing:  same work.  If they win you’re brilliant.  If not, you’re an idiot. It’s about outcome, not process.  I was a youngster telling the brass stuff with analysis / stats, and they felt threatened, especially if they aren’t stats folks.  It’s not about the analytics:  The majority is communication and representing your work that gets buy in from the scouts, the GM, the owner.  .  When I figured that out, things changed for me.  Heling shape ideas so it was the collective group’s idea.

ML  did you hide the fact you were the smart guy?

Paraag:  It’s an organization’s decision.  It’s got to be communicated well.  … Today, things are much better even 3-5 years ago, b/c the market is embracing outsiders coming into the industry.  The sports marketplace is more open to people coming to new people. Football is last,

Darryl:   In Basketball, analysis matches what coaches suspected.

ML: Are the incentives of coaches different than those from general managers?

Darryl:  Coaches are treated poorly,  and rationally look at the short term. As GM’s we look longer term.

Mark:   Coaches and GM’s don’t evaluate talent in the same was. Coaches think they can fix everybody.

Darryl:  Coaches have a plan –  some players don’t execute that but produce collateral benefits.  GM’s see that, and coaches look too micro about “his plan.”

And you have to balance all these issues.

Nate:  In Baseball,  2003, There was certainly a Sharks vs. Jets kind of vibe.  But return on investment comes from young players who nurture potential talent.  The Best scouts use data analytics as a baseline upon which you improve.   Knowing your place in the constellation is helpful.   Less  moves of the “two back. one forward” kind.  In sports, eventually harmony emerges. In politics, a lot is total bullshit that has no value to society. 

For example.  At TED conference.  Some  of it is great, and all of it sounds great, until you ask an expert. the look deeper and realize that  some is total bullshit.  Once you get below the surface, you can get discouraged.

ML:  What will you pay $$ for in analytics?   Where are the important fields of ignorance? Are there diminishing returns on going further? 

Nate:  Diminishing returns, but not there yet in baseball. Not exhausted .  New data with codified scouting info. If I did PECOTA today with new data:  movement of players/ object on field.  New info, little low hanging fruit though, but plenty for new creativity.  Can we quantify a good curveball?  That would be cool.

Paraag:   In Football, a lot of unchartered territory:  Especially  #1:  Mental Aptitude. In FB, this has  a lot of impact  on competitiveness.  Physical differences are small.   Mental differences are vast.  #2: injury prevention – one player destroys a season in FB.  Soft tissue injury prevention, endurance.  Projecting their susceptibility to injury.  #3:  In-game management in its nascent stages .   In game strategy what formations are succesfful? Starting.

ML:   50 years from now,   will people think in-game  FB strategy was barbaric?

Paraag:  Currently, we’re not  using what we know.  If you have a good outcome, the process doesn’t matter. A few (Belichick, Payton)  are applying it during the game.

Darryl:   Potential is huge: We’re not getting “XYZ data:”  realtime data  of all players and the ball  captured at 30FPS.  That’s where the action is.  Multiple killer apps there.  We’re nowhere on the court in basketball.  I think offenses/ defenses will be completely different  in 10 years.  This data should allow us to exploit inefficiencies,  create synergies within skill sets.  Lot’s of innovation.

Mark Cuban:  XYZ data capture is the tip of a big iceberg.  Also in practice/ training.  We have a hard time developing talent:  what can we learn there.  Medical is incredibly important:  We’re doing genetic testing to pick the best anti-inflammatory. We’re locking in our medical staff longer contracts than our players.  Team psychology. Why?  In BB, we can project who the best will be. WE knew LeBron would be great.  He top 10 were known.  Is there a way to develop / nurture folks into the top 10,  like Baseball often does?

ML:   What’s hard to measure? 

  • Team psychology
  • Nate:  coaching.   Are there coaches that can bring out talent? 
  • Parag:  coaching. Making sure O and D have complementary skill sets.  The sum create a good team.   The styles often don’t  match. 
  • Darryl:  Medical staff: finding/ getting the best.  Do clinical trials on Yao Ming’s foot?  It can’t happen. 
  • Mark:  Organizational Dynamics.  The decision must be in the mix so a decision can be made. It’s hard to be a decision maker and be removed.  I do what I do because there are organizational dynamics to observe.  If there’s conflicts, we’ve got issues to address. 

 

About roughlynormal

I have been a math/statistics teacher for 20 years. I currently teach at a college prep school in southern California. I also coach teaching fellows for Math for America - Los Angeles chapter. I love my career, my colleagues, and my friends & family.
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