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First Man

Last night I got to see First Man, the biography of Neil Armstrong, in IMAX. I have been excited about this movie ever since it was announced. I will run to see any movie by director Damien Chazelle. The first moon landing? How can you not see that in IMAX?

This movie continues Chazelle’s theme of protagonists relentlessly in pursuit of their goals, particularly at the cost of their personal relationships. His work fleshing out Andrew Neiman’s drumming obsession and the doomed relationship of LA dreamers Sebastian Wilder & Mia Dolan was excellent practice for portraying the real life Neil Armstrong. I have to admit, I don’t know nearly enough about Armstrong to know if the portrayal was accurate.

Another theme Chazelle continued is his excellent use of music. Music was central to Whiplash and La La Land, two movies about musicians. In First Man, there were two striking musical moments. As they fly to the moon, Armstrong plays a tape that brings us back to an earlier scene with his wife. When Armstrong steps out onto the moon everything becomes haltingly silent. 

Again, I don’t know enough about Armstrong to say the portrayal was accurate, but Ryan Gosling’s performance was excellent. His “more fuel” quip harnessed Armstrong’s solemnity for the funniest moment of the movie. The real star of the show was Claire Foy as his wife Janet Shearon. While Neil puts his head down and drives at his goals, Janet brings to life the conflicts around them; the risks he is taking, the never-ending funerals for his colleagues, his refusal to talk about their lost daughter or the chance he may not return. 

First Man is the weakest of Chazelle’s three films, but that’s not intended as a strong criticism. The biggest problem was handling nearly a decade of events, jumping multiple years a few times. I have read some other reviews describing the non-Armstrong characters as flat. There might be some truth to that, but I think those reviewers are missing the point. This isn’t a movie about NASA, it’s about Neil. 

As I watched First Man I was in genuine awe of NASA’s achievements in putting men on the moon. And yet, I found myself agreeing with the hippies. Was it a wise use of resources? Did we gain much more than bragging rights over the Soviets? I’d like to read up on what we have gained from our research on the moon. But I’m skeptical it was worthwhile, even while recognizing the greatness of the achievement.

The gravity of their achievements was really brought home by how, well, 1960s everything was. You really felt like they were shot up to the moon in a bucket full of bolts. Apollo 1 was a fatal disaster before they even left the surface! 

On a personal note, I loved the bits of celestial mechanics. I was never too interested in physics in school, focusing more on social sciences, but I have become more interested in spaceflight because of the video game Kerbal Space Program. Playing that game has taught me a lot about orbital mechanics and lunar theory. I loved the Gemini 8 scene where Armstrong and David Scott docked with another spacecraft for the first time. I’ve done that! On a, uh computer game…

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Yoga

Everyone has regrets about high school. Maybe they should have studied harder. Maybe they should have spent more (or less) time with their friends. Maybe they passed up an opportunity they never got again. 

I wish I had done yoga.

I played football in high school. I lifted weights. I was in great shape, except I had lower back pain. It was most severe during football season, but hurt pretty much year round. 

I didn’t think much of it. It wasn’t severe and I really loved playing football. I thought back pain was just part of being a linebacker. 

People told me to stretch. I stretched with the team before practice, so I thought I was following this advice.

Some people told me to do yoga. I laughed at them. Me, do yoga? Isn’t that for girls? Don’t you have to convert to Buddhism? 

When I graduated high school and hung up my shoulder pads for the last time, the back pain softened. But it never went away. Throughout most of college I was still active, mostly playing basketball. While not as bad as football season, my back pain would flare up the day after a game of basketball. 

Three years ago I found something that really helps. Yoga. 

My wife Kelly was going to yoga classes here and there. While I had ignored previous suggestions to do yoga, the continued back pain five years after my last football game pushed me to consider joining her. And so I did.

The first class was exactly what I expected. I was really bad, inflexible and with poor balance. We had a moment of meditation at the end (which I hated at the time, but like yoga, I now have a more positive attitude). The class was nearly all female.

And yet, after about four classes, my back felt better! 

Personal experience combined with Googling showed me what I would have already known had I paid attention in my high school anatomy class. My back pain wasn’t really the result of trauma to my back and it couldn’t be relieved with lower back stretches. It is largely caused by tight hamstrings. I have really tight hamstrings.

A yoga class does wonders for getting me to stretch my hamstrings and other tight spots, like my hips. I try to go once a week. Doing yoga regularly doesn’t necessarily make me feel better, it just makes my body not feel tight.  That’s a little frustrating. But it’s worth it. And I wish I could go back in time to convince my high school self of it. 

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Moneyball

If you’re wondering where I got my love for sports analytics, the answer is Moneyball. Published in 2003, Moneyball explains Sabermetrics through the story of Oakland Athletics General Manager Billy Beane. As defined by Wikipedia, Sabermetrics is the empirical analysis of baseball, especially baseball statistics that measure in-game activity“.

Moneyball generated a lot of controversy. These stats nerds were ruining the game with complicated algorithms. At the time, Beane thought players who excelled in on-base percentage were undervalued compared to those with a high batting average. Old school analysts like Joe Morgan mocked those who valued on-base percentage for wanting to clog up the basepaths.

The Oakland Athletics haven’t come within a 10-foot pole of a World Series. Why is Moneyball so lauded?

I evaluated whether on-base percentage is a better statistic than batting average. If you think that’s a poor way to evaluate the value of Sabermetrics, I agree. But it is probably the most popularized insight from Moneyball and makes for a simple test.

Using MLB data from 2003 to 2018, I calculated a multiple linear regression between batting average, on-base percentage, and wins. Here was the result:

Wins = (OBP * 560) – (BA * 204) – 49

This means to estimate how many games a team will win, you multiply their on-base percentage by 560, subtract their batting average multiplied by 204, and subtract 49. After controlling for OBP, having a higher BA is associated with a smaller chance of winning.

How could this be? Hits make you less likely to win? Not exactly. On-base percentage includes hits, walks, and hits by pitch. Since batting average includes hits, on-base percentage captures everything captured by batting average and then some.

To confirm this, I calculated two simple linear regressions, that between on-base percentage & winning and that between batting average & winning.

Wins = (OBP * 409) – 52
Mean Squared Error = 98

Wins = (BA * 340) – 7
Mean Squared Error = 113

First, we see the coefficient is stronger for on-base percentage than for batting average, 409 compared to 340. Second, we see the mean squared error is smaller for on-base percentage meaning the relationship is clearer. Conceptually, on-base percentage is more valuable to me than batting average. But if you’re skeptical and wanted the data, there it is.

The debate between on-base percentage and batting average is only one example between the statistics nerds and the old guard. Over a decade after Moneyball was published, on-base percentage is now properly valued. The promise of using statistics and economics to recognize undervalued assets in sports remains as alluring as ever.

Thanks to Kyle Safran for helping me prepare this post.

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Should we hate in-flight WiFi?

On Thursday and Sunday I flew to and from Chicago. I bought in-flight WiFi on both legs. I can’t do this without thinking of the famous Louis CK bit, everything is amazing and nobody is happy.

Is Louis right? Are we a bunch of whiners who should be grateful in-flight WiFi even exists? Or are we right to demand something more than the moderately functional yet expensive product we get today?

As someone who does a fair amount of programming I know it is no small feat to converse with a computer. They’re, well, not human. I do find the ability to surf the web while flying amazing.

On the other hand, it seems the hard part has already been done. Internet signal is being sent to and from a plane flying through the sky. How much more work is needed to ensure you can’t randomly end up on a flight where their WiFi is inexplicably inoperable that day? In an industry with minuscule profit margins, what will it take to get competitively priced internet?

During my Chicago trip I experienced the glory and the frustration of in-flight WiFi. On the way there, I was able to quickly turn around a report to my boss before I landed. On the return trip, I drafted my recent blog post evaluating my 2017-2018 NBA predictions. Well, I thought I did. You see, when I checked my drafts yesterday my work from the flight had not saved.

Maybe Louis would be okay with that. But paying $15 to lose an hour of work sure seemed like a raw deal to me.

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Revisiting 2017-2018 NBA Predictions

Around this time last year, I attempted to predict how many games each NBA team would win. I am hoping to do the same this year but before I do so I want to evaluate my predictions from last year. My model was primarily built using previous season win shares. One consistent flaw I found in my predictions was that I tended to underestimate the performance of team with promising young players. This makes sense because young players have the greatest potential to improve. A few other big misses were due to injuries, especially teams that choose to tank* after a star player was injured.

The number after each team is how the team fared compared to my prediction. For example, the Golden State Warriors won 9 fewer games than I predicted, 58 as compared to 67.

Golden State Warriors (-9) I don’t feel too bad about missing on this one. I think the Warriors could have won a handful more games, but they took their foot off the gas pedal to prioritize the playoffs. Given how the Rockets won more games but Chris Paul got hurt in the Western Conference finals, I can’t criticize that strategy.

Cleveland Cavaliers (-12) This prediction looks awful in retrospect. I did not expect much drop off from Isaiah Thomas but that was clearly a mistake. Not only did he miss much of the season recovering from injury, when he did return he was a much worse player. 

Minnesota Timberwolves (-13) I noted at the time this was probably showing a flaw in my model and I think that’s clear as day now. Andrew Wiggins regressed, which is a worrying sign that he played worse alongside Jimmy Butler. While Jeff Teague had a worse season than I expected, I think that was on me more than Teague. His year with Indiana the season before was clearly an aberration. For veteran players, my model could be improved by moving to a multi-year win shares average.

Houston Rockets (+2) Their big move was adding Chris Paul and he added about as much value as I expected. The question was would Harden & Paul be able to coexist without dropping off and it looks like they actually improved their individual production a bit. I wonder how much of this is due to their strategy of successfully playing lots of isolation basketball.

Oklahoma City Thunder (-5) This was an alright prediction. I thought it was the Knicks holding Carmelo back over the past few years, but he was a net negative even on the Thunder. I expect the Thunder to be a few games better with him off the roster this year.

San Antonio Spurs (-3) While my prediction looks close here, I’m shocked. My prediction certainly did not account for Kawhi Leonard missing most of the season. Where did they make up the production? A better season for LaMarcus Aldridge as well as a breakout year for Kyle Anderson. It also helps they continue to be the Spurs and put out the 3rd best defense in the league.

Washington Wizards (-5) I initially guessed I overestimated wins for the Wizards due to John Wall’s injury but they played fine without him. It was actually Marcin Gortat who under performed most severely and Bradley Beal was a bit worse than I expected.

Toronto Raptors (+11) One of many underestimates where I did not properly account for strong contributions from young players. For the Raptors that was Jakob Poeltl, Pascal Siakam, and Fred VanVleet.

Boston Celtics (+7) The accuracy of my prediction here is similar to the Raptors (underestimated young talent) and the Spurs (worse than it looks considering Gordon Hayward was hurt all season). The young players I underestimated the most were Jayson Tatum, Terry Rozier, and Jaylen Brown. Look for those players to get even better next year and they’ll add Hayward back in.

Denver Nuggets (-1) Nearly perfect!

Utah Jazz (+5) The main variable I missed here was Donovan Mitchell. I expected him to be your average rookie guard which is a slight negative but he was phenomenal for Utah.

Charlotte Hornets (-7) Dwight Howard was a disaster for the Hornets. I’ll need to keep an eye out for players who put up big stats in bad situations, like Howard did in the previous season.

Miami Heat (+1) Nearly perfect!

New Orleans Pelicans (+6) Two things happened here. First, the pairing of Anthony Davis and DeMarcus Cousins worked out better than I expected (and the Pelicans’ pickup of Nikola Mirotic when Cousins tore his Achilles tendon worked out nicely). Second, I did not factor in Jrue Holiday missing most of the previous season and he had a great bounce back year.

Milwaukee Bucks (+3) I had high expectations for Giannis Antetokounmpo which he met, but it was the mid-season trade for Eric Bledsoe that improved this team beyond my expectations. 

Los Angeles Clippers (+4) There was no clear pattern to my under estimation here. As far as I can tell, Doc Rivers did a fine job coaching this team and getting a little bit more than expected out of each player.

New York Knicks (-8) The Knicks were exactly on pace to win my predicted 37 games until star Kristaps Porzingis tore his ACL on February 6th. After that, the Knicks accepted their fate and attempted to make a late entry into the tankathon.

Dallas Mavericks (-12) While I expected the Mavericks to be a middle of the road team, instead they embraced tanking to the fullest extent. This made it easy to play a rookie at point guard, always a losing option, and to not be too torn over the loss to injury of Seth Curry. 

Philadelphia 76ers (+17) This was my worst prediction (Chris Freiman if you’re reading this, you were right!) They had a few things going for them. First, Ben Simmons was a massive value-add player for them when merely being positive is an accomplishment for a rookie. Second, Joel Embiid played many more games than I expected. Third, some other young players like Dario Saric and Robert Covington took nice steps forward. Fourth, in a similar fashion to the Clippers, essentially everybody on this roster had a slightly better season than my model expected. Credit Brett Brown for that one. 

Portland Trailblazers (+14) I thought Evan Turner would be a negative for this team but he was (barely) a positive contributor. I thought Damian Lillard would be really, really good but he was really, really, really good. Ed Davis took a much larger step forward than I expected and Jusuf Nurkic seems to fit in much better in Portland than he did in Denver.

Detroit Pistons (+5) When the Pistons traded for Blake Griffin, it gave them a boost in the short term. They did a little bit better than expected but it still was not enough to make the playoffs. How much will the Griffin trade hurt them in the long term? 

Indiana Pacers (+15) I completely missed on this prediction but so did everybody else watching the NBA. The big story here was Victor Oladipio’s meteoric rise from alright backup in OKC to all-star in Indiana.

Memphis Grizzlies (-10) The Grizzlies’ season was similar to that of the Knicks. When star Mike Conley got hurt early in the season it became clear the team needed to tank. Conley played so few games I can’t really extrapolate based on the time he was healthy.

Orlando Magic (-6) This was a surprise for me: my model had very high expectations for Mo Speights. He had a steep drop off from one of his best seasons ever last year in Los Angeles. The Magic, unsurprisingly, were also tankathon competitors. 

Phoenix Suns (-8) I’m not too upset about missing on a team that won the tankathon, but I will note that trading Eric “I Dont wanna be here” Bledsoe was a significant contributing factor.

Atlanta Hawks (-3) The Hawks were bad, as expected.

Brooklyn Nets (+2) The Nets were bad, as expected.

Sacramento Kings (+2) The Kings were bad, as expected.

Chicago Bulls (+3) The Bulls were bad, as expected.

Los Angeles Lakers (+12) To close out this analysis, I really need to do a better job of projecting youth-heavy teams (see also 76ers, Raptors, Celtics). Kyle Kuzma and Josh Hart were much better than I expected. An interesting note is that I have Julius Randle as their most impactful player last year but they let him leave for New Orleans.
*If you are you are reading this but don’t follow the NBA closely, “tankathon” refers to how many NBA teams “tank” (not sure where the term came from, but it means purposefully put out a poor team to work towards a losing record). So many teams were doing this last season in the hopes of getting a better draft pick that it became a bit of a “tankathon”, a contest to see who could tank the strongest.
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Non-Profit Measurement

For-profit companies have it so easy. Maximize revenue, minimize expenses. Make a profit.

There are important steps to making a profit. Develop a product that provides value. Identify customers. Sell customers on your product. Bring in talent and keep them happy.

But at the end of the day, your balance sheet tells you how you are doing. It is not so clear for a non-profit.

I have worked for a few non-profits now. Here is a sample of their mission statements:

…to inspire, educate, and connect future leaders with the economic, ethical, and legal principles of a free society.

…to educate, develop, and empower the next generation of leaders of liberty.

 …to ensure higher education becomes a place where classical liberal ideas are regularly taught, discussed, challenged, and developed, and where free speech, intellectual diversity, and open inquiry flourish.

If you are an organizational leader or a financial supporter, how do you know if a non-profit is successfully advancing such a mission?
This is where non-profit measurement comes in. 
Non-profit measurement is the attempt to measure an organization’s impact. This means attempting to answer questions such as: 
  • What does success look like? 
  • Is our organization moving us closer to success? 
  • How do we know? 
  • If we are working towards long-term results, what short-term indicators can reasonably suggest long-term success?
In my experience, effective measurement provides a common language and clear (if inexact) answers to these questions. These are guidelines to steer team members in making decisions that move the organization in a unified direction. 
If you wonder what I do for a living, I attempt to help the Institute for Humane Studies measure success and make better decisions towards furthering our vision. 
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Real Estate

While on a run the other day, I saw an advertisement for a real estate agent that said “buyers pay no agent fees”. This got me thinking. In American home sales, sellers pay fees to real estate agents but buyers do not. It seems to me that these fees will be baked into the price that the buyer pays to the seller. The buyer is not off the hook after all. If this is the case, why do we frame it as the seller, but not the buyer, paying agent fees?

Am I missing something here?

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NBA game log tool online!

Last week I wrote about a few projects I want to tackle in my spare time. Friday night I started work on an NBA game log tool. Last night, I successfully deployed my initial app to Heroku! You can check it out here.

The goal of this tool is to easily log and recall notes about NBA teams and players. As I wrote previously, I think the “eye test” of watching games is just as important as studying player statistics. To use the eye test effectively I think you need to keep notes as systematized as possible.

When you log in, you see all existing notes. You can add an entry for a game you watched which includes the teams playing, the date, how much of the game you watched, and your notes on the game. Log entries can be edited or deleted. There is also a functioning registration and login system for users.

I have a long list of features to keep adding, here are my top priorities:

  1. Differentiate notes of different users
  2. Search notes for a specific team
  3. Associate notes with specific players
  4. Better visual layout
  5. Possibly, related Android and iOS apps
  6. A snappier name (NBAeyeTest?)
For now, I’m thrilled to say this project is already online! This is my most successful javascript project to date. I built this app using the MEAN stack: MongoDB, Express, Angular, and Node. This is also my first time using Heroku. 
Again, if you are interested, please check it out here. I’m aware of a few bugs, in particular the footer doesn’t always load properly. Please let me know what other bugs you run into! 
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The Future of Football

I think football has two major problems that will require change.

First, football is a dangerous sport. There is mounting evidence that football, particularly at the highest level, causes brain damage.

This could become a hit to popularity if fans lose interest in watching concussions. As parents grow concerned, fewer youth football players likely means fewer lifelong fans.

Second, college football is a financially lucrative business built upon players restricted from earning salaries. Division I football players receive scholarships covering tuition, housing, meals, etc. For most, this is a good deal. But some players are vastly underpaid. After being drafted first this year, Baker Mayfield will earn upwards of $8 million per year in the NFL. How does that compare to his scholarship just a few months ago at the University of Oklahoma?

At some point I believe this will be widely regarded as unacceptable. Players like Mayfield bring in significant revenue to their universities and to the NCAA. While student-athletes are not allowed to bring home any of the cash directly, one devastating injury could take away their future as professional athletes.

A related criticism of this arrangement is that college football (and basketball) have become so big they are major distractions to universities. In some cases, star student-athletes are treated differently in the classroom and in university discipline systems. Football coaches are some of the highest paid government employees in many states.

Where is this all headed? First, I think we will see professional football careers shorten. Long-lasting head trauma is a result of repeated blows, which can be minimized by playing football for fewer years. Second, I think we will see an uncoupling of major sports from universities. Most major football programs have enough brand loyalty to continue on divorced from their (now former) university. Third, I think these two trends will merge towards a unified system of professional football. Most players will play from the ages of 18 to 25 and we could see a future matchup between the Oklahoma Sooners and the Cleveland Browns.

There are obviously other common grievances with football. Many fans think the football rulebook has become too complex. Some fans think the NFL is anti-patriotic. Cord-cutting could be a financial risk for football. But I think only the high risk of concussions and the student-athlete arrangements are existential risks to the current football system.