I should have known that any team that could have beaten my mighty Mets would go on to win the World Series, but I, like many of you, figured wrong by picking the Detroit Tigers to take the St. Louis Cardinals. Not that many people noticed, as it drew the lowest TV ratings of any World Series in history! Meanwhile, for those of you already eager to move on to the Hot Stove League, click below to read about how an actuary is thriving in major league baseball–which is almost as dependent on statistics as are those in the insurance industry.
***Posted by the Casualty Actuarial Society on Oct. 25:
New actuarial techniques such as data mining and predictive modeling are increasingly being used by Major League Baseball teams to help them gain a competitive edge on the field, according to John Dewan, an actuary who owns Baseball Info Solutions.
When the output from such models is combined with traditional scouting, baseball teams have the potential to achieve better results, Mr. Dewan said in a speech before the CAS Seminar on Predictive Modeling attendees in Boston.
There are more things you can do with data than you imagine. Our job is to find the nuggets of data that are interesting and relevant, and that reveal tendencies, he said.
He explained that a number of teams now employ statisticians in addition to scouts, to help determine the best prospects who can turn around a teams performance.
Statistics in baseball is like apple pie–they go hand-in-hand. You think of a sport where numbers mean something and its baseball, but were tracking things that in the past no one ever tracked, Mr. Dewan said.
He explained that his company collects data on every play of every MLB game and enters it into a computer. The data collected is then analyzed in great depth–for example, each pitch is charted by type, location, and velocity.
Such a granular analysis using actuarial approaches can yield strong correlations, according to Mr. Dewan, who cited the example of comparing fastball velocity with earned run average. His analysis showed that pitchers who throw harder (based on their average fastball speed) perform better.
He noted that a velocity of 94 miles per hour or more yielded an ERA of 3.84 in the regular season, compared to an ERA of 4.58 for a velocity of less than 90 MPH. The correlation was even stronger in the playoffs, with ERA improving to 3.42 for those pitchers who throw 94 MPH or harder.
Mr. Dewan urged actuaries to search out the unexpected and the new when collecting data. The data has to be interesting to get the attention of management you are trying to impress or win over to your side.
He pointed out that as for sports statisticians, one of the key challenges facing actuaries is to get management to invest in and support the use of predictive modeling.
Management in insurance doesnt always want to use the data or spend the money to collect the data. Thats the challenge, he said.
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