Measure the impact on pitchers and hitters from each major league park.
Unlike other sports, baseball is not played on identically sized fields. Some parks are built at different elevations (most notably Coors Field in Colorado), some have large amounts of foul territory (such as McAfee Coliseum in Oakland), and some have odd-shaped outfields (such as Wrigley Field in Chicago). Most fans notice the short right-field porch at Yankee Stadium or the huge green wall in left field at Fenway Park. Many web sites adjust statistics to compensate for park effects. But how do you measure these?
We want to come up with a “fudge factor” that tells us how well a batter or a pitcher is expected to perform in a particular park. If a player’s home park is a hitter’s park (a park where more runs are scored than normal), we might want to discount his stats appropriately. Similarly, if a batter plays in a pitcher’s park (where fewer runs than average are scored), we might want to boost his stats. We’re looking for a simple number that we can multiply by a batter’s AVG, a pitcher’s ERA, or other ballpark-dependent statistics to compare players’ performances fairly.
We’re looking for a few characteristics in an ideal park factor:
If the park doesn’t change, the park effect shouldn’t change. This means park effects should be the same from year to year.
A park factor should measure the park’s effect on an average ...