Thaler, Massey, and Losers

Well before he won The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, Richard Thaler wrote The Loser’s Curse. Along with co-author Cade Massey (well before he hosted the Wharton Moneyball podcast), they found that NFL teams tend to trade too many assets to choose higher in the draft.

With the idea that it’s not what you buy, it’s what you pay we’ll revisit the paper. (Here’s a related 2018 work, also a gated 2020 analysis)

Also, Thaler spoke at SSAC20 about the paper in a panel with Bill James.

Thaler and Massey noticed that in-practice, NFL draft picks declined steeply in value. Top picks were worth a lot. Low picks were worth much less. The chart looked like a roller coaster’s first hill.

What they found was what’s known in the league as ‘The Chart’. The rule-of-thumb systems born in Dallas in 1991, and spread through the league. Thaler and Massey wrote that the chart standardized trades and created the norm to ‘gain a round waiting a year.'” It was the way things had always been done and few teams at the time considered why we’ve always done it that way. 

“What our analysis shows is that while this chart is widely used, it has the ‘wrong’ prices.”

The chart suggested that the first pick of the first round in the draft delivered less value than the last pick of the first round.

Thaler and Massey found the ‘right’ prices by comparing draft slot against games started and pro bowls awarded. Lower drafted players scored higher.

Thaler and Massey wondered if there was a ‘star premium’. “Over their first five years, first-round draft picks have more seasons with zero starts than with selections to the Pro Bowl.” Busting was as likely as breaking out.

Thaler and Massey wondered how often one pick was ‘better than the next guy’ at the same position. “Across all rounds, all positions, all years, the chance that a player proves to be better than the next best alternative is only slightly better than a coin-flip.”

In the paper Thaler and Massey lay out a variety of reasons why ‘The Chart’ was so different from the results. Let’s add four more.

Possible explanation 1: Measurement error. Quarterbacks are tremendously important and the stats underrate their impact. On the Wharton Moneyball podcast Massey brings this up and hints at it on Twitter. In the paper Thaler and Massey do boost performance scores by 50% without seeing value returns shift.

However maybe there was a trend they didn’t or couldn’t quite measure. More and more quarterbacks throw for more than 4,000 yards.

Possible explanation 2: Ownership incentives. The NFL—or any sport—isn’t just about winning. Though Massey and Thaler write that people don’t tune in to see their team lose, they don’t address whether people view interesting as different from winning. We think there’s only one honest sport.

If owners see values rise, share revenues, watch mediocre play, and they themselves face little (social) cost, how strong is the incentive to ‘just win baby’?

Possible explanation 3: Luck matters a lot . Michael Mauboussin writes about guidelines for situations that are more dependent on skill and ones more dependent on luck. For situations with more randomness (and luck) people should trust the base rates more and give more weight to environmental rather than personal factors. By thinking they can find a diamond in the rough, teams are operating like drafting players is more skill than luck based.

However, there’s always a chance to develop better talent evaluation, incorporate new technologies, or coach players better. Those are all skills that could improve the 52% ‘better than the next guy’ success rate.

Possible explanation 4: Culture is king. The effect that Thaler and Massey find could be partially driven by bad organizations picking at the top of the draft. Imagine these were not football franchises but restaurant franchises.

The best chefs keep their jobs and the talent pool for the open positions is a mix of unproven leaders, bad situations, or people who have already failed ‘but learned the right lessons’. The ownership of these franchises are people who have already proved they themselves are bad talent evaluators, or else they wouldn’t be looking for a new coach/chef.

What’s great is that while the data is old the ideas from Thaler and Massey are still present. They’ve taken new forms and changed in many ways but good decision making is still something worth thinking about.


Thank you for reading and supporting.


Three differences between hurricanes and viruses

Worth noting, this is only based on one hurricane season (2019) and one viral pandemic (CoVid19). 

There has been a huge contrast in preparation for CoVid19 and for hurricane Dorian. Though both had the potential to do serious economic, physical, and life-threatening damage, people reacted in different ways. Why? I think there are three aspects. 


Hurricanes generate a lot of data that’s not too difficult to collect and we’ve been collecting it since the 1870’s by Catholic missionaries in Cuba. With time and tech we’ve become more precise and practiced. Hurricane forecasts include when the winds will arrive. It’s also easier to share hurricane information with the people who need it most. 

Rarely do economists and virologists have these conditions. On the Bloomberg Odd Lots podcast, Claudia Sahm bemoaned that in this case they had good data, “This started overseas and it’s different because we don’t need the unemployment rate to tell us that something bad is working its way through the global economy.” 

With ample tests, this is a different kind of problem. But no tests, no data and no data, no action. 


Floridians have a clear understanding of what hurricanes can do. The twenty-one million people who live in the state know someone or have themselves, lived through a storm. If culture is “what people do when you don’t tell them what to do,” then Florida has a pretty good preparation appreciation.

Part-of-the-reason for this culture is the cause-and-effect relationship. Storm comes through, storm destroys lives, storm leaves. Post hoc ergo propter hoc. This is harder to see with someone’s health. People look fine until they aren’t.


It’s clear what needs to be done for hurricanes. Bring things inside. Have food and water for some number of days for some number of people. Close shutters. Collect medicines. Pump gas. Pack a bug-out-bag. There’s even a tax-free weekend of shopping, where the state government encourages people to prepare. Planning for a hurricane is socially, economically, and timely easily done.

It’s hard to do anything for the virus besides take zinc. Sometimes the best action is to do nothing but that never really feels like enough, does it? Investors often say to ‘don’t just do something, sit there’ and that might be the best idea yet. 

So what? 

More tests solves the data problem. Experience affects the culture. Here we’ll focus on the actions and use the EAST framework to make choices easy, attractive, social, and timely. How would you get people to self-quarantine and practice social distancing? 

In my local area, Retirementville, Central Florida, residents should have been told how deadly this disease is to their age cohort (fifteen-percent for those seventy and older). Newspapers and radio could have emphasized the even elevated rates for people with conditions health conditions. In China it was men who smoked, but in the states it will be anyone with high blood pressure and cardiovascular conditions. 

Along with this public service announcement, we should have appealed to the patriotism of this particular part of Florida. We’d come together to defeat this microbial adversary. We could pass out stickers. It’s not Rosie the Riveter poster material, but it’s still a common foe.

Further, there’s enough technology to have virtual meetups. Let card games be on computers. Let people Facetime friends. With the right framing this would have been fun. People already have hurricane parties.

Had this been shared at the right time, things would be different.

Postscript, there’s probably something here too about distributions of outcomes. For the worst storms of the past thirty years, the median normalized damage is $26B and the average damage is $33B. How that data fits all hurricanes and compares to viruses is TBD.


Tim Harford’s Arguing Advice

Tim Harford joined Tyler Cowen to speak about his career, production function, and why dice are something he couldn’t live without. Harford said this about debates:

“I still think debating is underrated. People think that it’s a very elite thing, practiced by elite people from very posh schools and very privileged backgrounds and favors a certain kind of education. Those things are all true. At the same time, in a debate you are protected by certain rules, given space and time, and people are not allowed to interupt you except in certain formalized ways.

“Once I became an adult, and entered certain corporate spaces and corporate meetings, I became aware that all the old men were talking all over the young women. They’d interupt and wouldn’t let these younger people get a word in edgewise. I realized that debating protects anyone.”

Tim Harford

A contest has explicit rules. A culture has implicit rules.

For organizations to ‘argue Zell‘, they must have leaders willing to be challenged and leaders who communicate that. Career risk depends on the culture.

Like strategy, marketing, or ethics, culture is something organziations do. “Unless you set it, it’ll just be what it is.” The easiest way to create a specific culture is to hire well. After that, incentives matter.