Winner’s Curse in Baseball (a look at sports economics)

This article regarding baseball raises a plethora of valid arguments regarding the auctioning system of free-agent baseball players. One thing I found particularly interesting about this article was the methodology used to value various free agent players, the author explains that a player’s value is measured by first statistically comparing a teams number of wins with their revenue and then multiplying that value by an individual’s marginal win value. Baseball and other team playing athletes are in that respect, difficult to value since we do not have perfect information and more importantly because it is nearly impossible to calculate precise monetary values of individual players because sports franchises earns more money based off of a team victory not based on individual contribution, or to put it more eloquently the whole is greater than the sum of it’s parts.

The article goes into the flaws of individual valuation more in depth and also discusses a few other potential pitfalls to trying to minimize the winner’s curse in this market. The reason I focus so heavily on the valuation aspect of this academic journal is for two reasons: one, because I believe that trying to accurately value an item (in this case a human being) is the most important step in minimizing an individuals winner’s curse, and two because the idea of trying to giving a human being a value in dollar terms or any numerical representation seems to me both a difficult process and also slightly disturbing one.


Evolutionary Game Theory Reevaluated

According to the basic models of evolutionary game theory that we studied, selfish strategies are more likely to prevail over cooperative strategies, even if they are not social optimal.  Biologists have previously believed that cooperative behaviors prevail only when they are also the best response for the individual, but there are new theories to suggest that animals engage in socially optimal behavior even if it is not in their immediate best interest.  It seems that some animals understand that it is in their long term best interest (and in the interest of their group) to engage in behaviors such as warning calls and sharing food, even if it leaves the giver slightly worse off.

Though a prisoner’s dilemma is traditionally a one-time game, cooperative decisions have to be made over and over.  Choosing to not make a warning call may be the best decision in an individual moment, but over time the optimal strategy changes to one of cooperation.  This type of repeated game where one player mimics the previous move of the other player is called ‘tit-for-tat’.

In the real animal world, these strategies look a little more complicated; fitness has to be measured on a gradation, and animals do occasionally forgive the betrayal of those in their group.  In this case, these researchers realized that one player can defect a certain percentage of the time and it is still in the other’s best interest to cooperate.  In these repeated games, the player who is a periodic extortionist has a strictly higher payoff than the cooperative player.  In the long run though, the generous strategy prevails because other members employ the ‘tit for tat’ idea and also generally play generous strategies, making each individual and the group as a whole better off.

Lotte may fall prey to ‘winner’s curse’

Recently in Incheon Airport new bids have been given to allow new businesses to operate in their ICN duty free zone, a popular shopping place for over fourteen million foreign tourists shopping that can bring as much as 8.3 trillion in revenue for duty free store operators together. Foreign conglomerate Lotte recently paid a ridiculous amount in total of 3.6 trillion dollars in the form of a bid for four out of the eight sections of the ICN. This is almost two and a half times what they bid last time for space in the ICN and will require over 720 billion annually to hold a profit. This exorbitant amount of money paid is expected to be a classic case of a winner’s curse; with a Lotte official admitting “It will take one or two years to know whether the bidding conditions were good or bad.” I believe this will be an example of winners curse because of the steep bidding seen by Lotte over what others considered to not be worth nearly as much. To put it in perspective, Hotel Shilla won three sections and paid a total of 1.32 trillion. This may never be an issue for Lotte but it certainly will remain to be seen for the coming years whether they made the right choice in bidding so high for the ICN duty free zone.

Auctioning Nobel Prizes

On February 24th it was announced that Simon Kuznet’s 1971 medal for the Nobel Prize in Economics will be put up for auction by his 83-year-old son Paul. The sale of Nobel prize medals has become a recent phenomena as both Francis Crick and James D. Watson’s medal sold for over 2 million and 4 million (dollars), respectfully, while Carlos Saavedra Lamas’ sold for $1.16 million and James Chadwick’s for $329,000 (both in 2014). The bidding will begin at $150,000 meaning that the auction will be an ascending bid auction, as potential buyers will successively bid higher and higher until no one will top the maximum offer. This is an interesting good to be selling as the actual worth of the 23-karat medallion is $8,700, this means that any of the astronomically large sums paid for the other medals, such as Crick’s and Watson’s, are valued as such based on the pure prestige of the recipients of the awards themselves. The fact that these medals have varied so widely in selling price makes it difficult to predict how much Kuznet’s medal will sell for. One of a kind collector goods such as a Nobel Prize medal often, due to their uniqueness, cause price wars to ensue, as typically these goods are pure luxury items and can only be acquired by people with a large disposable income. Because of the combined effects of these large incomes and the highly competitive markets that these goods create (due to their rarity), if the medal belonged to someone particularly noteworthy (and the bidding was appropriately competitive) then it seems that the ‘winner’s curse’ could be especially high, based on the nature of the good being auctioned.

Valuations and the NFL Draft

While the article attached doesn’t specifically mention economics or markets, as I read to procrastinate doing actual work, the article reminded me a bit of the topics from Chapter 10 in which we discussed valuations, optimal assignments, prices and payoffs, and market clearing prices. While the NFL Draft does not take place until late April and concludes in early May; the process of evaluating prospects and team needs begins shortly after the conclusion of the NFL season and amplifies as the NFL Draft Combine and as colleges host “pro days” to showcase their draft eligible players in front of college scouts.

From these workouts and pro days, draft analysts begin to create “Big Boards” or rankings of draft prospects from best to worst. Interestingly, quite often we see teams not draft based off of which player is the “best,” but rather search to find the best player at the position in which they need the most help. For example, there are some analysts who rate quarterback prospect Jameis Winston as the best quarterback prospect in the last ten years of the draft and coincidentally the Tampa Bay Buccaneers who have the first overall pick are weak at the quarterback position will more than likely draft Winston. Still, three years ago, when there were two highly rated quarterbacks Andrew Luck and Robert Griffin III, the team holding the second pick, the St. Louis Rams, did not “need” a quarterback as they drafted one with the first overall pick in a draft two years before. Consequently, they did not value RGIII as highly as other teams and traded the pick away for a collection of picks in the same draft and future drafts to the Washington Redskins who not only thought Griffin would be a future superstar, but also valued the position to pick second more than the Rams, as the team selecting third also could potentially select Griffin before Washington had the opportunity to.

To connect this to valuations and optimal assignments depending on how a values a draft prospect in relation to other teams value of the same prospect and relative to their draft position, a team may decide to pick the player or trade the draft pick. In the event that multiple teams have similar aspirations for a pick, the team holding the desired draft slot will continue to raise the price (or combination of players and picks needed to attain the pick) until there is only one buyer willing to pay for the pick and thus the market is cleared and a perfect match of one seller and one buyer. The defending Super Bowl Champion New England Patriots have a reputation for stockpiling draft picks by trading their highest pick to gain a collection of lower picks and thus draft more players. Attached is an article on both team needs for the upcoming draft and how teams should value the top prospects and a sheet which displays a trade formula and assigns a point value to each pick in the draft. The sheet shows the combination of picks a team usually has to trade in order to gain a desired higher draft position.

A Nice Piece of that American Pie

If you know the song “American Pie”, then you may know that the singer/songwriter is Don McLean. The hit song came out in 1971, and even I know a part of the song very well “bye-bye Miss American pie”. On April, the original 16-page manuscript will go up for auction by Christie’s auction in New York and is expected to sell for up to $1.5 million! That is a substantial amount of cash for a document, but I guess there are buyers who want their hands on the draft that generated this musical masterpiece. I’ve always wondered how and why anyone would purchase art (or cars, handbags, etc.) for in insane amount of loot. I believe that this will be an ascending-bid auction. Here the auction house has an idea of what McLean’s piece may go for. We can assume that there are a number of people who really appreciates his creation, and the rational bidder (who in my opinion is not so rational) may pay close (if not more) to the expected value of Christie’s estimate. I can picture the winner’s curse here, but at the same time the payoff of winning this piece is infinite. It must be absolutely superb to someone, somewhere to be able to basically own the sweat, tears, and energy invested to create this hit, and on top of it all, this treasure has good potential resale value.

Mixed Strategies in Soccer

Hello Class- This is my blog post on an example of two teams in soccer using mixed strategies in a real world scenario. Below you will find a YouTube link that shows “Manchester United – Chelsea London Champions League Final 2008”. In this video you can fast forward  to 2:55 of the video and at this point we can see that there is some type of confusion between the goalie and the kickers. This confusion is due to a mixed strategy of Manchester’s goalie responding to the actions of the other teams players. The goalie is adjusting his strategy due to what he expects the other players strategies to be. Manchester United’s goalkeeper learns of Chelsea’s kicking strategy. This strategy is of the kickers kicking to their natural side. Due to this the Chelsea players begin kicking to the opposite side- hence their unnatural side. Ex: If the kicking players natural side is right, they would kick the soccer ball to their left side. Manchester’s goal keeper notices this unnatural strategy, so on the last kick he points to the unnatural side of the kicker. This causes the kicker (Nicolas Anelka), to see that the goalie has learned of their strategy. Nicolas kicks to the natural side to confuse the goalkeeper. The problem is that the goalkeeper on Manchester (Van Der Sar) dives to the natural side and blocks the kicker. The reason why he was able to block the kick is because he increased his probability of the kicker kicking to the natural side. Through this example mixed strategy can be seen  by each player playing a strategy that will take advantage of the expected probability of the other players strategy.