The Ultimate Data Mining Sport

A few days ago, I came across a show on ESPN on the concept of Sabermetrics. According to Wikipedia, "Sabermetrics is the analysis of baseball through objective evidence, especially baseball statistics." The sport of baseball is a unique sport since it is dominated by statistics. As many of you, hitting a ball, which is the size of a tennis ball, with a stick is an not easy task. Now imagine if the ball is coming at you around eighty to ninety miles per hour. What makes it even more hard is that the ball velocity, location and the trajectory of the ball may be different from one pitch to another pitch. The hitter has to decide to hit the ball if it goes through or touches the strike zone. The hitter has to guess what the pitcher's tendencies are and where and what type of pitch he, the pitcher, will throw. As you can see, statistics are the core of any baseball game. Lineups and pitching match-ups maybe altered depending on the pitcher, hitter, weather, ballpark and the time of the game. As an avid fantasy baseball player, I am aware of some of the stats and I alter my fantasy line up everyday.

What does this all mean? Since baseball is game of stats, Major League Baseball (MLB) general managers are relying more on analytical systems like Sabermetrics which give quantitative data on whether a player is valuable to the team or not. Sabermetrics captures statistics which are usually overlooked by regular stats. For example, Sabermetrics does not put alot of value in a player who hits for a .320 average. It does, however, give the player a higher rank if the player hits .320 average compared to a player who is hitting .098 average when the bases are loaded in a tie game at the bottom of the ninth. Yes the Runs Batted In (RBI) stat would say this however the player's RBI stat might be inflated if the player bats in a lot of runs when the games are not close. This might indicate that the player does not do well in pressure.

Even though folks in baseball have figured out on how to quantitatively score their assets to put a better product on their field, IT folks have been struggling with this for number of years. IT folks have a grand vision called Enterprise Architecture where they can map every asset, process, system and other IT variables and start seeing the gaps in their IT enterprises. AS IT business managers look at EA as their panacea for monitoring their enterprises, computers scientists are looking to fields like ontologies and referential systems to capture "inferred relationships" in the IT domain. I believe the IT people, including myself and all of the architects, developers, testers, program managers, project managers, CIO, etc., etc, should take a step back and learn from the baseball folks before we all strike out and head back to the dugout shaking our heads and pondering, "How did I miss that?"