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Monday, August 14, 2006

The State of Statistical Analysis

Rany Jazayerli had an excellent two-part analysis of the Tigers last week on BP. The level of detail in analyzing the construction of the 2006 roster and the decisions made by Dave Dombrowski is enlightening to say the least. However, from a big picture standpoint I especially enjoyed these quotes from the second piece where he discusses the ever-decreasing benefit to statistical analysis as compared to the advantages to be gained by good scouting.

"When no one took statistical analysis seriously, a team that bucked the trend could find major inefficiencies in the market. But over the last decade the acceptance of statistical analysis throughout the game--there isn’t a major league team that doesn’t employ someone doing statistical work for them--has squeezed most of the inefficiencies out of the market. Statistical measures of offense were the first to catch on, because they were the most accurate. Using those measures before everyone else allowed the A’s to build an offense that ranked in the top four in the AL in runs scored between 1999 and 2001. But as other teams have caught on, their old tricks don’t work anymore. The A’s haven’t ranked higher than sixth in runs scored since, and this year rank dead last in the league."

"The best way to find inefficiencies in the numbers today is to have access to data other teams don’t have--which may explain why the A’s, with their own proprietary fielding numbers, have allowed the second-fewest runs (only the Tigers have allowed fewer) in the league. And certainly, combining the best of statistical analysis with the best in traditional scouting measures is always going to be a recipe for success, as it was for the Red Sox in 2004."

"The best way to find inefficiencies worth exploiting is to have better information than your competition. The beauty of data--that it is discrete and precise--is also its weakness. If everyone has the same numbers, then everyone has the same information. While there is such a thing as good data analysis vs. bad data analysis, anyone qualified to work for a major league team is unlikely to make any egregious errors on that front. Some writers might think it’s meaningful that Joe Shlabotnik has hit .320 in the #2 hole and .280 in the #5 hole in 100 plate appearances each; I doubt any professional analyst would make that kind of mistake. The very fact that statistical analysis is mainstream makes it that much more difficult for the very best analysts to hold much of an advantage on the second-tier guys chasing them."

Very well said and the reason that ever more granular data will be reauired in order to reap benefits. No more low hanging fruit.

1 comment:

Ron Stevens said...

After 30 years plus,the SABR method,has finaly been accepted throughout the MLB organization.Since this is a scientific field;i womder why it took the Majors so long into adopting it.
Perhaps in another 30 years or so,the baseball scribes will educate themselves in this .It is treated by most of them,as a esoteric,pointy headed intelectual excercise in futility.
In conclusion, the marriage of scouting and !SABR methodology,is the essence of the best way of selecting the best players