Wolfram Alpha's baseball info just a bit outside

On the eve of Major League Baseball's All-Star game, Wolfram Alpha decided to promote its ability to process baseball queries. Strike one.

Tom Krazit Former Staff writer, CNET News
Tom Krazit writes about the ever-expanding world of Google, as the most prominent company on the Internet defends its search juggernaut while expanding into nearly anything it thinks possible. He has previously written about Apple, the traditional PC industry, and chip companies. E-mail Tom.
Tom Krazit
2 min read
Bill James--the father of the modern approach to baseball statistics--probably wouldn't like the results produced by Wolfram Alpha. CBS News

It's been two months since Wolfram Alpha launched, and in some ways, the "computation knowledge engine" is still fouling off pitches.

Wolfram used the occasion of Major League Baseball's 2009 All-Star Game--otherwise known as the three most boring days of the baseball season--to highlight the ability of Wolfram Alpha to process baseball-related queries. "...what we at Wolfram Alpha love about baseball are all of the fast statistics that can be quickly computed and returned as easy-to-read graphs," the company said in a blog post.

A few examples were provided, such as the ability to see whether the New York Yankees or Boston Red Sox had more wins last year, as well as a graph showing how many wins each club has had for all the seasons since 1960. Likewise, you can see which team had more home runs last year.

But for the most part, Wolfram Alpha is unable to deliver a shocking amount of baseball-related data. Baseball--easily the most statistically obsessed sport of the four major American professional sports--should be right in Wolfram Alpha's wheelhouse.

It's not. While the ability to settle arguments about wins and home runs among teams could avert as many as 27 percent of all baseball-related bar fights (statistic possibly made up), both the casual fan and the fantasy baseball junkie need far more information.

Wolfram Alpha was unable to determine which team or player had the most home runs in 2008. It was unable to tell me what Alex Rodriguez's batting average is for 2009, or for his entire career. Nor did it have any information about the modern baseball statistics that are a mathematician's dream, such as win shares or VORP--value over replacement player.

Google, on the other hand, was unable to tell me at first glance who led the league in home runs last year (Ryan Howard) in the first 10 results for "most home runs 2008," but was able to tell me A-Rod's batting average and define the terms win shares and VORP in the first few search results. Yahoo and Bing had similar trouble with identifying Ryan Howard's performance last year, but nailed the other queries, with Bing even providing A-Rod's up-to-date 2009 statistics.

Baseball's embrace of statistic information over the past decade is one of the most important non-pharmaceutical related trends the game has seen in quite some time. "Sabermetrics," as it's called, has prompted several baseball teams to employ at least one mathematician/statistical guru to assess the performance of its players as well as potential players the team might want to acquire.

Wolfram Alpha--backed by a powerful statistical engine--has the potential to be the tool for those devotees of the game, but does not understand enough query input terms at the moment to be a viable option. Wolfram Alpha is flirting with the Mendoza Line when it comes to baseball statistics; although, of course, it's a little confused about the definition of the Mendoza Line.