SABERMETRICS

Popularised by Michael Lewis’s book Moneyball: The Art of Winning an Unfair Game, and more recently, in the film Moneyball and the Simpsons episode MoneyBart, sabermetrics is the collecting and analysing of baseball information. Defined in 1980 by Bill James, sabermetrics is “the search for objective knowledge about baseball”. This definition reflects the primary function of probability and statistics: to make sense of the random and

unpredictable world we live in. The word sabermetrics comes from the acronym of SABR, the Society of American Baseball Research, and the word metric, associated with measurements.

Sabermetrics is used to measure performances of individuals or teams and predict likelihoods of specific events in baseball occurring. The beauty and success of sabermetrics comes from the objectivity of statistics. Players and teams that were previously under-valued by traditional baseball scouts and traditional baseball statistics, now have their full potential on display through the lens of sabermetrics.

The Traditional Way of Thinking

Before Bill James and the success of sabermetrics, scouts searching for players have always judged them based on their ‘gut feelings’ and appearances from watching the players a handful of times. These ‘gut feelings’ and perceptions about a player’s appearance tend to cloud a scout’s decision on whether or not to draft

Sabermetrics has shifted the focus on what stats make up a good player. Previously, runs batted in, or RBIs, were believed to be an important statistic in evaluating a player, however to sabermetricians, this statistic is meaningless. For a player to have a high number of RBIs, they must consistently have runners on base when they are stepping up to bat. However, having runners on base is completely outside of the batter’s control. Sabermetricians favour statistics like on base percentage (OBS) and slugging to analyse a player’s value as a run and hit producer.

Success on a Budget

Sabermetrics was brought into the mainstream by Michael Lewis’s book Moneyball. The book follows the success of the Oakland Athletics baseball team under the general management of Billy Beane. Billy Beane was a devoted reader of Bill James and was a true sabermetrician, he felt that scouts overvalued certain statistics and felt that many players were undervalued due to their appearance or their unorthodox style of playing. He used his knowledge of sabermetrics to create a team that was consistently successful and ended up winning the 2002 World Series with a budget a fraction of a size of their opponents, the San Francisco Giants. This disparity in finances is especially clear in the chart below comparing the salaries of the two teams below:

However, even after the success of the A’s, the tide of success has not turned in favour of lower budget teams. Many high budget teams have adopted the ‘Moneyball’ approach, and since these teams have mofinancialial freedom, they can buy the players with their desired statistics. Sabermetrics is still evolving and many of the statistics considered as gospel by the A’s are now being disputed. Since 2012, there has been an annual SABR analytics meeting which showcases all the latest developments in baseball analysis, where there is great debate on the weight of certain statistics on the value of a good player. In the end, even as these sabermetricians climb closer to objectively analysing baseball, it becomes even more clear that baseball unpredictable and often unquantifiable, much like the world we live in.

Cian Rellis