Anti-Moneyball. How Poor Decision-Making Can Fail Organizations

Disclaimer: The author of this blog post is neither a fan nor a “hater” of the Washington Football Team. However, the author considers the Washington Football Team an interesting case study, which is worth of more in-depth analysis. Materials in this blog post summarize only one aspect of a potential failure of the Washington Football Team and are based on academic findings of world-class researches from the University of Chicago and the University of Pennsylvania. The author acknowledges that these materials were written 10-15 years ago and the situation might have changed, forcing NFL teams to make more rational decisions during the intense draft competition.


My interest in data science started with several things. One of them was a book Moneyball: The Art of Winning an Unfair Game, written by a brilliant author Michael Lewis. This book (and later a movie with Brad Pitt) became one of the most simple and vivid examples of how organizations can benefit from advanced data science solutions, combining it with the industry expertise.

Not everybody agreed with the concept of Michale Lewis. Some stated that it was an idealized version of what happened with Billy Beane and the Oakland A’s. This is a fair point because things should be always taken with a grain of salt. For instance, Alan Hirsch and Sheldon Hirsch published a book The Beauty of Short Hops: How Chance and Circumstance Confound the Moneyball Approach to Baseball, where they criticized the “Moneyball”, completely focused on sabermetrics (the empirical analysis of baseball, especially baseball statistics that measure in-game activity.)

However, “Moneyball” was not just a book. It became a phenomenon. Other books about the success in baseball due to sabermetrics were published too. For instance:

As usual, these stories have loyal supporters and harsh critics.

Moreover, the concept of “Moneyball” was used in other industries - for example, Moneyball for Government.

Okay, so what is the point of all this introduction? :)

The Failure of the Washington Football Team

Today (December 28, 2020) The Washington Football Team released its quarterback Dwayne Haskins.

From Wikipedia:

“Haskins was drafted by the Washington Redskins (now the Washington Football Team) in the first round of the 2019 NFL Draft, 15th overall and signed his four-year rookie contract on May 9, 2019. He played college football at Ohio State University, where he threw 50 touchdowns during his lone starting season in 2018, making him one of the few quarterbacks to ever accomplish that in a single NCAA season.”

Just after 18 months Haskins (the first round pick) was released by the team, which during the last years looks like an example of Anti-Moneyball.

Unfortunately, in recent years a DC football team became a disaster and its management was heavily criticized by fans and journalists. To name a few sports failures:

Besides the franchise was involved in a number of other scandals and controversies. Critics of the team did not even try to select proper words in their multiple articles, criticizing the team’s leadership. In this blog post, I summarized some information that data-driven decision making can improve the performance of organizations if leadership has understanding and needs for it.

Decision-making and NFL Draft

The Loser’s Curse: Decision Making and Market Efficiency in the National Football League Draft

In 2013 Richard Thaler, the Professor at the University of Chicago Booth School of Business together with the Professor from The Wharton School of the University of Pennsylvania Cade Massey published a very interesting paper - The Loser’s Curse: Decision Making and Market Efficiency in the National Football League Draft.

In this article authors tells about the behavioral aspects and the importance of good decision-making during the NFL draft:

"A question of increasing interest to researchers in a variety of fields is whether the biases found in judgment and decision-making research remain present in contexts in which experienced participants face strong economic incentives. To investigate this question, we analyze the decision making of National Football League teams during their annual player draft. This is a domain in which monetary stakes are exceedingly high and the opportunities for learning are rich. It is also a domain in which multiple psychological factors suggest that teams may overvalue the chance to pick early in the draft. Using archival data on draft-day trades, player performance, and compensation, we compare the market value of draft picks with the surplus value to teams provided by the drafted players. We find that top draft picks are significantly overvalued in a manner that is inconsistent with rational expectations and efficient markets, and consistent with psychological research."

In addition, authors previously worked on this topic, and in 2005 their working paper Overconfidence vs. Market Efficiency in the National Football League was published by the National Bureau of Economic Research.

In their “The Loser’s Curse” paper Professors Thaler and Massey investigated how did rational expectations and market efficiency play out in the NFL labor market.

“To determine whether the market values of picks are “correct,” we compare them to the surplus value (to the team) of the players chosen with the draft picks. We define surplus value as the player’s performance value—estimated from the labor market for NFL veterans—less his compensation."

According to the authors, their findings

"strongly reject the hypothesis of market efficiency. Although the market prices of picks decline sharply initially, we find surplus value of the picks during the first round actually increases throughout most of the round: the player selected with the final pick in the first round, on average, produces more surplus to his team than the first pick!"

So, what did Thaler and Massey do?

  • For the initial step in their analysis, they used a data set of 407 draft-day trades to estimate the market value of draft picks (trades of these draft picks from 1983–2008)

  • Authors asked whether the highest picks were too expensive, as the relevant psychology predicts, and used a non-parametric approach, comparing the benefit of using a pick to the opportunity cost of foregone trades

  • Finally, they performed a more detailed cost-benefit analysis of each player selected in the draft, by calculating the surplus value that the player provided to the team, namely, the performance value (estimated by the price of an equivalent veteran player) minus the salary paid

In particular, authors predicted that

“teams will overvalue the right to choose early in the draft. Specifically, we believe teams will systematically pay too much for the right to draft one player over another. This will be reflected in the relative price for draft picks as observed in draft-day trades.”

The results of the research were surprising even for the authors of the study.

The authors highlighted the following:

“A striking feature of these data is how steep the curve is. The drop in value from the 1st pick to the 10th is roughly 50%, and values fall another 50% from there to the end of the first round. As we report in the following section, compensation costs follow a very similar pattern. Although the curve is not as steep as it used to be, this flattening has slowed over time. In an efficient market the curve’s steepness would imply both that player performance falls sharply at the top of the draft, and that teams are highly skilled in their ability to identify these performance differences.”

Moreover, the authors noted that:

“Another notable feature is the remarkably high discount rate, which we estimate to be 136% per year. Although this finding is not the focus of the paper, it is clear that teams who “borrow” picks on these terms are displaying highly impatient behavior."

Besides Thaler and Massey highlighted that teams were not doing a very good job, estimating the likelihood that a player is better than the next player chosen at his position:

"The very steep curve we document in this section suggests that teams believe they have the ability to distinguish great players from the merely good. Before moving to full cost-benefit analyses, let us consider a simple question: What is the likelihood that a player is better than the next player chosen at his position (e.g., linebacker) by some reasonable measure of performance, such as games started in his first five seasons? After all, this is the question teams face as they decide whether to trade up to acquire a specific player. The answer is 52%. 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."

And that is exactly what the “Moneyball” was about - the inability of “industry experts” without a proper data analysis to distinguish and select the most valuable players on the market due to own biases.

In addition, the authors explored the opportunity costs and conducted the cost-benefit analysis of the NFL draft.

First, Thaler and Massey evaluated that

“the benefit of using a draft pick relative to the opportunity cost of trading it for two lesser picks”. They found overwhelming evidence that “that a team would do better in the draft by trading down (this gain to be reliably positive for 31 of the 32 draft-pick positions in the first round.” Moreover, “For 74% of the trades, a team would have acquired more starts by trading down than by using a pick.” Hence, teams would be much better off, exchanging their current first round pick with two future picks later in the draft.

Second, authors identified and later picks are more beneficial for the team financially.

“Consequently, surplus value increases at the top of the order, rising to its maximum of approximately $1,200,000 near the beginning of the second round before declining through the rest of the draft. That treasured first pick in the draft is, according to this analysis, actually the least valuable pick in the first round! To be clear, the player taken with the first pick does have the highest expected performance (that is, the performance value curve is monotonically decreasing), but he also has the highest salary, and in terms of performance per dollar, is less valuable than most players taken in the second round.”

The last pick in the first round is worth only 25% of the first pick even though the last pick will command a much smaller salary than the first pick. These simple facts are incontrovertible. In a rational market, such high prices would forecast high returns; in this context, stellar performance on the field. And, teams do show skill in selecting players: Using any performance measure, the players taken at the top of the draft perform better than those taken later. In fact, performance declines steadily throughout the draft. Still, performance does not decline steeply enough to be consistent with the very high prices of top picks. Indeed, we find that the expected surplus to the team declines throughout the first round. The first pick, in fact, has an expected surplus lower than any pick in the second round and is riskier as well. Furthermore, the risk associated with very high picks is mostly on the downside. Because top picks are paid so much, there is little room for a player to greatly exceed expectations, but when top picks turn out to be complete busts, tens of millions of dollars are wasted.

As a result, Thaler and Massey concluded the following:

A conclusion from our analysis is that teams should trade down, not up. A possible objection to this conclusion is that when teams trade up, they might have a special need at the position and/or believe they have particularly good information about the acquired player. … Our modest claim in this paper is that the owners and managers of National Football League teams are subject to the same biased judgments found in countless other domains. Furthermore, market forces have not been strong enough to overcome these human failings. The task of picking players, as we have described in this paper, is an extremely difficult one, much more difficult than the tasks psychologists typically pose to their subjects.”

The final thoughts of the authors:

"Our findings are strikingly strong. Rather than a treasure, the right to pick first appears to be a curse. If picks are valued by the surplus they produce, then the first pick in the first round is the worst pick in the round, not the best. In paying a steep price to trade up, teams are paying a lot to acquire a pick that is worth less than the ones they are giving up. The implications of this study extend beyond the gridiron. At its most general, these findings stand as a reminder that decision makers often know less than they think they know. This lesson has been implicated in disaster after disaster, from financial markets to international affairs. Closer to the topic at hand, football players are surely not the only employees whose future performance is difficult to predict. In fact, football teams almost certainly are in a better position to predict performance than most employers choosing workers, whether newly minted MBAs or the next CEO. In our judgment, there is little reason to think that the market for CEOs is more efficient than the market for football players. The problem is not that future performance is difficult to predict, but that decision makers do not appreciate how difficult it is."

Overconfidence vs. Market Efficiency in the National Football

There are also several more interesting points in the NBER working paper, written by authors in 2005. This paper used a smaller dataset, have similar conclusions, and provide some additional interesting ideas.

For instance, analyzing the data, Thaler and Massey found out the chance to be failed in the league for first round picks are similar to the chance to play in a Super Bowl:

“For example, over their first five years, players drafted in the first round spend about as many seasons out of the league (8%) or not starting a single game (8%) as in the Pro Bowl (9%).”

Authors also refer to Michael Lewis:

As Michael Lewis, author of Moneyball, said of another sport, “If professional baseball players, whose achievements are endlessly watched, discussed and analyzed by tens of millions of people, can be radically misvalued, who can’t be? If such a putatively meritocratic culture as professional baseball can be so sloppy and inefficient, what can’t be?”

Finally, Thaler and Massey provide some specific examples:

“We began this study with the strong intuition that teams were putting too high a value on choosing early in the draft. We thought it crazy for the Giants to give up so many picks for the opportunity to move up from the fourth pick to the first one (regardless of which player they chose). But we concede that we did not expect the findings to be as strong as those we report. Rather than a treasure, the right to pick first appears to be a curse. If picks are valued by the surplus they produce, then the first pick in the first round is the worst pick in the round, not the best! In paying a steep price to trade up, teams seem to be getting the sign wrong! We have done numerous “reality checks” to see whether these surprising conclusions are robust, and every analysis gives qualitatively similar results. So, suppose our analyses are taken at face value. Can they be right? This is a big market, after all, with franchises worth perhaps $1 billion or more. We think that while our results are surprising, they are plausible. We suspect that some teams have not fully come to grips with the implications of the salary cap, a relatively new innovation. Buying expensive players, even if they turn out to be great performers, imposes opportunity costs elsewhere on the roster. Spending $10 million on a star quarterback instead of $5 million on a journeyman implies having $5 million less to spend on offensive linemen to block or linebackers to tackle. Some of the successful franchises seem to understand these concepts, most notably the New England Patriots, but others do not. Whether because they are smart about these ideas or others, the Patriots have been doing well recently, and so have not had high draft picks to use. We can only speculate about whether they would trade down if they somehow ended up with one of the earliest and most overvalued picks. But notice that if a few teams do learn and have winning records, there is no market action they can take to make the implied value of draft picks rational. Indeed, the irony of our results is that the supposed benefit bestowed on the worst team in the league, the right to pick first in the draft, is really not a benefit at all, unless the team trades it away. The first pick in the draft is the loser’s curse."


In 2015 Professor Thaler published a wonderful book - Misbehaving: The Making of Behavioral Economics.

Thaler describes his experience and their work on this article in his book:

"Before we started this project, Cade and I had a strong hunch that there was some serious misbehaving going on in this environment. Specifically, we thought that teams were putting too high a value on the right to pick early in the draft.

Five findings from the psychology of decision-making supported our hypothesis that early picks will be too expensive:

1. People are overconfident. They are likely to think their ability to discriminate between the ability of two players is greater than it is.

2. People make forecasts that are too extreme. In this case, the people whose job it is to assess the quality of prospective players—scouts—are too willing to say that a particular player is likely to be a superstar, when by definition superstars do not come along very often.

3. The winner’s curse. When many bidders compete for the same object, the winner of the auction is often the bidder who most overvalues the object being sold. The same will be true for players, especially the highly touted players picked early in the first round. The winner’s curse says that those players will be good, but not as good as the teams picking them think.

4. The false consensus effect. Put basically, people tend to think that other people share their preferences. For instance, when the iPhone was new I asked the students in my class two anonymous questions: do you own an iPhone, and what percentage of the class do you think owns an iPhone? Those who owned an iPhone thought that a majority of their classmates did as well, while those who didn’t thought iPhone ownership uncommon. Likewise in the draft, when a team falls in love with a certain player they are just sure that every other team shares their view. They try to jump to the head of the line before another team steals their guy.

5. Present bias. Team owners, coaches, and general managers all want to win now. For the players selected at the top of the draft, there is always the possibility, often illusory, as in the case of Ricky Williams, that the player will immediately turn a losing team into a winner or a winning team into a Super Bowl champion. Teams want to win now!

Finally, Thaler remembers his short collaboration on this topic with the management of the current Washington Football Team:

"Before we even had our first draft of this paper, we had some interest from one of the NFL teams, and by now we have now worked informally with three teams (one at a time, of course). The first interaction we had was with Daniel Snyder, the owner of the Washington Redskins. Mr. Snyder had been invited by the entrepreneurship club at the Booth School of Business to give a talk, and one of the organizers asked me to moderate a discussion for the audience. I agreed, knowing I would have some time to talk to Snyder one-on-one during lunch.

Dan Snyder is a self-made man. He dropped out of college to start a company that chartered jets to sell cheap spring break vacation trips to university students. He later went into the direct mail advertising business and had the good fortune or wisdom to sell the company in 2000, at the peak of the market. He used the money from that sale, plus a lot of debt, to buy the Redskins, his favorite team when he was a kid. (Unsurprisingly, many consider the name of the team to be a slur, but Snyder defends keeping it.) He had only been an owner for a brief period when we met.

I told Mr. Snyder about the project with Cade and he immediately said he was going to send “his guys” to see us right away, even though they were in the midst of the season. He said, “We want to be the best at everything.” Apparently when Mr. Snyder wants something he gets it. That Monday I got a call from his chief operating officer, who wanted to talk to Cade and me ASAP. We met Friday of that week with two of his associates and had a mutually beneficial discussion. We gave them the basic lessons of our analysis, and they were able to confirm some institutional details for us.

After the season ended, we had further discussions with Snyder’s staff. By then, we were pretty sure they had mastered our two takeaways: trade down and trade picks this year for better picks next year. Cade and I watched the draft on television that year with special interest that turned into deep disappointment. The team did exactly the opposite of what we had suggested! They moved up in the draft, and then traded away a high draft pick next year to get a lesser one this year. When we asked our contacts what happened we got a short answer. “Mr. Snyder wanted to win now.”

The Winner’s Curse

In the articles and the book above, Thaler and Massey mention one more phenomenon - “The Winner’s Curse”. Professor Thaler wrote an article and a book about this topic:

But what is the winner’s curse?

Thaler provides the following example:

"The winner’s curse is a concept that was first discussed in the literature by three Atlantic Richfield engineers, Capen, Clapp, and Campbell (1971). The idea is simple. Suppose many oil companies are interested in purchasing the drilling rights to a particular parcel of land. Let’s assume that the rights are worth the same amount to all bidders, that is, the auction is what is called a common value auction. Further, suppose that each bidding firm obtains an estimate of the value of the rights from its experts. Assume that the estimates are unbiased, so the mean of the estimates is equal to the common value of the tract. What is likely to happen in the auction? Given the difficulty of estimating the amount of oil in a given location, the estimates of the experts will vary substantially, some far too high and some too low. Even if companies bid somewhat less than the estimate their expert provided, the firms whose experts provided high estimates will tend to bid more than the firms whose experts guessed lower. Indeed, it may occur that the firm that wins the auction will be the one whose experts provided the highest estimates. If this happens, the winner of the auction is likely to be a loser. The winner can be said to be “cursed” in one of two ways: (1) the winning bid exceeds the value of the tract, so the firm loses money; or (2) the value of the tract is less than the expert’s estimate so the winning firm is disappointed. Call these winner’s curse versions 1 and 2 respectively. Notice that the milder version 2 can apply even if the winning bidder makes a profit, as long as the profit is less than expected at the time the bid was made. In either version the winner is unhappy about the outcome, so both definitions seem appropriate.

The winner’s curse cannot occur if all the bidders are rational (see Cox and Isaac, 1984), so evidence of a winner’s curse in market settings would constitute an anomaly. However, acting rationally in a common value auction can be difficult. Rational bidding requires first distinguishing between the expected value of the object for sale, conditioned only on the prior information available, and the expected value conditioned on winning the auction. Even if a bidder grasps this basic concept, version 2 of the winner’s curse can occur if the bidder underestimates the magnitude of the adjustment necessary to compensate for the presence of other bidders".

The winner’s curse in a prototype for the type of problem that is amenable to investigation using modern behavioral economics, a combination of cognitive psy- chology and microeconomics. The key ingredient is the existence of a cognitive illusion, a mental task that induces a substantial majority of subjects to make a systematic error."

As we can see, this concept is extremely relevant for the NFL draft and other similar events, where teams overvalue their potential assets and frequently do not receive expected returns.


The story of Dwayne Haskins might be clear evidence of the poor management performance at the Washington Football Team. Or might be just a coincidence. Plus these articles and books were written a while ago and the situation can be very different now in terms of rational decisions by NFL teams. However, this story is just an element of the process, which might be poorly designed due to some systemic errors in the decision-making. Scientific research in this field by world-class professionals demonstrates that the management of NFL teams also makes mistakes which are common in many other situations. High NFL draft picks are frequently overvalued and become not a blessing, but a “winner’s curse” for many NFL teams, which make irrational decisions. In turn, it brings a lot of frustration to loyal fans, sports journalists, and franchise members.