Economic Inefficiencies In Professional Athlete Valuation, Or Why Stanley Needs A Tan

Is this a sign of dysfunction? There I was in Aruba, Carribean climate and ocean all around, and I spend the better part of Saturday night (after cocktail hour, of course), in an island casino, drinking Balashi and smoking a Siglo V, watching our Flyers be out skated, out shot, and (gasp!) out hit, by the Tampa Bay Lightning.

Tampa Bay! Tampa!!! Land of beaches, palm trees, and hurricanes … land where ice shall not last!!

How could this happen?

Easy … they’re a better hockey team, just as Calgary is a better hockey team (at least this month) than anyone in the West.

But the location isn’t the kicker, this is: Calgary and Tampa do not pay a lot of money for their players. Indeed, a review of the statistics indicates that Calgary has the 20th-highest payroll in the league, at $35 million, and Tampa Bay has the 22nd-highest, at $34 million … both well below the league average of $44 million.

What’s more, the teams they beat, Calgary over Detroit and Tampa over the Flyguys, are first and fourth highest, respectively (Detroit: $78 million, Philly: $65 million).

So what gives?

Same thing that gives in the remarkable success of the Oakland A’s and Florida Marlins, which happen to have two of the lowest payrolls in baseball: Baseball and hockey coaches, scouts, and general managers do not know how to accurately evaluate the value of athletes in their leagues. If these guys were stock brokers, they’re consistently picking the wrong stocks.

But wait? They’re the experts, right? They know more about their sport and what it takes to win than anyone else, yes?

No.

Read Michael Lewis’ Moneyball, and you’ll understand. Moneyball is Lewis’ treatise on Billy Beane, manager of the Oakland A’s and architect of one of the most successful cheapskate franchises in sports history. His secret? Impassionate statistical analysis. Billy and his Harvard Law educated minions have nailed the statistical relationships between baseball statistics and the only statistics that matter in team performance: run production and wins. And their analysis indicates that many of the things scouts and GMs use to identify good “Baseball Men,” statistically, simply don’t have predictive relationships with run production or wins.

Like, for example, defense.

Beane knows that fielding percentage is meaningless in baseball … a Shortstop lines up two feet to the left, or a hit ball bounds two feet to the right, and an out becomes a hit or a hit becomes an out. Same with errors … meaningless. One error here or there simply means nothing across 162 games.

What does matter? On base percentage. The most important number in baseball is “3.” Outs are the only fixed quantity in baseball … three outs, and you can no longer score in an inning. 27 outs, and you can no longer score in a game. Burn your 27 outs and have fewer runs than the other guy, and you lose. So you need people who can get on base. A man on base is not an out. This also means that anything that risks outs … like hit-and-runs, sacrifice flies, or stealing bases … is foolish, as the odds of those gambits succeeding without an out are far lower than the odds of a man reaching base by working the count. Not coincidentally, the Oakland A’s do not hit-and-run, sacrifice, or steal.

Similarly, the statistic that matters in pitching is the production of outs. Strikes are good, but the ability to create outs … even if it’s on ground balls or flies … is most important.

What Beane knows, and why he’s succeeded, is that traditional Baseball Men don’t make impassionate, objective statistical player valuations … they make subjective ones. They look for other Baseball Men … guys who have “the look,” guys who might have one magic game that a scout sees, and that causes him, even in the face of poor statistics, to say “that guy’s a player … he just has ‘the look.’” Or, they believe mythology around baseball statistics that just don’t matter … like base stealing, or fielding percentage. Because that’s what Baseball Men have always done.

Beane believes none of that. He doesn’t care if a guy is fat or short or slow or old. If he has the right statistics … if he gets on base or gets outs … he’s an Oakland A. And because no Baseball Man wants to sign Mr. Fat Short Slow Old guy, Billy gets him for a steal. And then lo and behold, Mr. Fat Short Slow Old guy turns out to be Jason Giambi, at which point the A’s win lots of games, and once Jason’s a free agent, Billy trades him to the Yankess for a $120 million, thereby enriching the A’s and empowering Billy to continue investing in Harvard graduates, analyses, and the search for undervalued players.

The market for baseball talent is an inefficient market. Like any other market, it reflects personal biases and assumptions, many of which are founded in subjectivity, and many of which have become institutionalized as conventional wisdom. Bad wisdom, but conventional wisdom nonetheless.

There are two lessons here. The first that you shouldn’t kid yourself … the stock market is just as imperfect a market as is the baseball athlete market, so, yes, your suspicions are likely correct: your stock broker probably doesn’t know shit.

The second brings us to Stanley Needs a Tan. That’s a slogan many Tampa fans had on placards during game 7 of the Flyers series: “Stanley (as in the Stanley Cup) Needs a Tan.” And while the Flames scorched the Lightning in game 1 of the finals, those Tampa fans just might be right, because like Calgary, their team is damn good … good enough to beat everyone else in their division.

But I see more. I watched game 7 and I saw Billy Beane. I saw a team that was uglier, shorter, fatter, and less-famous than the Flyers, and they were skating rings around the Black and Orange. Tampa and Calgary have proved for hockey what Billy has proved for baseball: there are inefficiencies in the pricing of hockey players. I don’t know what those are, but I wager some Harvard grad, working in the depths of Tampa’s stadium, is huddled over a laptop at this very moment, running his latest predictive model of hockey success. Maybe it’s penalty minutes, maybe it’s shots on goal, maybe it’s plus/minus … but whatever it is, it would be great if the Flyers figured it out, too.

Until then, the city’s hopes ride with Smarty.