WSJ: Marchman: A Computer Cracks the Cooperstown Code

I guess this is good news for all you Andres Galarraga fan out there.

Now that Rickey Henderson and Jim Rice have been inducted into the National Baseball Hall of Fame, fans the country over can return to the only thing they like as much as watching games: Arguing over who should join them in Cooperstown. Sadly, machine learning may have just taken much of the steam out of such arguments.

According to research by Lloyd Smith, a professor of computer science at Missouri State University, and James Downey, an assistant professor of management information systems at the University of Central Arkansas, whether a player is elected to the Hall of Fame by veteran baseball writers is an entirely predictable outcome based on a few statistics.

...Of the 1,592 players considered by their study—anyone who retired between 1950 and 2002 and met several other criteria such as having played 10 years in the majors—the model was able to accurately identify whether they had been elected 98.7% of the time. Before the 2009 class was voted in, the model gave Mr. Henderson a 97.2% chance of being elected. On the flip side, Mo Vaughn had a 1.3% chance.

There is, though, good news for fans in the upcoming elections. Just as the public does, the model sees such borderline cases as Edgar Martinez and Mike Mussina as having essentially 50/50 chances of making Cooperstown. So let barroom debates commence.