Let me run you through my take on Moneyball, with two personal notes to start.  First, I’ve been a member of SABR – Society for American Baseball Research – since the mid ‘90s.  Sabermetrics in practice is generally just some relatively simple statistical techniques applied to baseball performance data.  Not exactly rocket science and not at the cutting edge of statistical techniques, but definitely a quantum leap ahead of the standard tools typically used to evaluate baseball performance statistics through the 1980’s. 

Second, I haven’t seen the movie and am highly unlikely to see it.  Despite my interests in the economics of sports, I read the book with reluctance because it billed Billy Beane as “the smartest man in baseball,” which seemed like hyperbole, given the legion of brilliant men who have played and managed the game in its storied history. Beane also was a baseball player with exceptional playing skills who never took advantage of those skills, which strikes the heart of a fan who values hard work and humility.

The fundamental point of the book, and I presume the movie, was that there were inefficiencies in evaluating players.  Beane was able to hire people with the statistical skills to identify the qualities that were undervalued and then identify the players that possessed those skills.  By hiring or drafting the undervalued players, Beane was able to build a successful team with a modest payroll.

All that is true and readily documented and some of the players named in the book, e.g. Kevin Youkilis and Nick Swisher, have taken those skills and performed very successfully.  What is also is easily documented is that Beane’s team has not been particularly successful of late, missing the playoffs for the past five years. 

As a business lesson, what Moneyball misses is one crucial point:  You can exploit a market inefficiency for a while – as long as you are the only one or one of only a few who know about the inefficiency.  Once everyone knows, the game is over.  Publishing Moneyball was effectively the kiss of death for the success of Beane’s strategy.  (In fact, that’s why I was reluctant to read the book. I thought it incredibly arrogant – or in retrospect stupid – to publish your strategy and think that you would still be successful.)

Now, the most interesting point about the book is that there really was an inefficiency.  In that sense, Beane was entirely correct.  He and his staff identified factors that were undervalued and underpriced and he was very successful in exploiting that – in the short term!  In the long term, everyone caught on and that inefficiency disappeared.  In fact, after the book was published, the inefficiency disappeared virtually immediately – within a year – and Beane’s comparative advantage was lost.  The A’s no longer were the underfunded winners; they were simply one more underfunded franchise.

In the 10 years or so since the book came out, there has been substantial research done on the metrics that really contribute to a team’s success, and there’s been much work done on trying to come up with better measures than have been used historically.  Going back a decade, statistics such as batting average or slugging average was considered the most important.  Now, they have been supplanted by a measure called OPS which is on-base percentage plus slugging percentage. 

That is, Beane’s preferred metric of on-base percentage itself no longer is the best measure of potential success. Now, there’s an even better one. 

Amusingly, a recent Wall Street Journal article about the team’s strategy notes that the stats guys now clam up and won’t share any information.  No surprise there!  If there’s any metric that’s even better and they know it, they also recognize the advantage that they have if others don’t know it.  In other words, it’s not enough to know about a better way of doing things.  In a competitive environment, you need to be the only one that knows that better way!  (That was Beane’s critical mistake – effectively sharing knowledge of the market inefficiency.)

One last point, on the big market versus small market franchises:  A team such as Oakland could compete by having a comparative advantage in statistics as long as the big market franchises didn’t recognize the value of those statistics.  Once the big market franchises recognize the benefits of statistics, they also have the financial resources to be able to buy the best statisticians to exploit whatever information the statistics might contain.  Thus, the Red Sox has GM Theo Epstein and stats whiz Bill James, and Oakland effectively has the “B” team. 

Notre Dame Finance Professor Richard Sheehan conducts research on banking and the economics of sports. In recent papers, he has investigated the determinants of bank deposit pricing, the valuation of financial institutions’ core deposits, and market rates. He also has examined the relationship between collegiate athletics and academics.