## Healthcare Economist

Unbiased Analysis of Today's Healthcare Issues

## The Brewers, Baseball and Statistics

Written By: Jason Shafrin - Aug• 14•08

My favorite team, the Milwaukee Brewers, is in town and I have gone to the first two games of the series (both wins). Unlike the recent dreadful history, this year the Brewers have the 2nd best record in the National League and are in the lead for the NL Wild Card. In honor of the Brewers visit to San Diego, today I will write a brief post of how statistics and baseball have intertwined.

Introduction

Baseball is a game where players a generally judged on a statistical basis. How many homeruns does a player hit? What is his batting average? What is the pitcher’s earned run average (ERA)?

The book Moneyball showed how the Oakland A’s were able to use advanced statistical analysis to put together a winning team despite having much lower financial resources compared to teams such as the Yankees, Red Sox and Cubs. While most fans are familiar with statistics such as ERA and on-base percentage (OBP), other, lesser-known statistics may help to reveal how good a player really is.

Lesser-known baseball statistics (from Hardball Times)

• BABIPBatting Average on Balls in Play. This is a measure of the number of batted balls that safely fall in for a hit (not including home runs). The exact formula we use is (H-HR)/(AB-K-HR+SF). If a pitcher has a low BABIP , this indicates that they are have been “lucky” since most of the balls that have been hit have been caught and their actual ERA may be lower then their talent would suggest. If they have high BABIP, this generally means the pitcher is “unlucky” since most of the balls in play have been hits, so their ERA may inflated compared to their actual talent level.
• FIP – Fielding Independent Pitching. a measure of all those things for which a pitcher is specifically responsible. The formula is (HR*13+(BB+HBP-IBB)*3-K*2)/IP, plus a league-specific factor (usually around 3.2) to round out the number to an equivalent ERA number. FIP helps you understand how well a pitcher pitched, regardless of how well his fielders fielded.
• GPA – Gross Production Average. This is a variation of OPS, but more accurate and easier to interpret. The exact formula is (OBP*1.8+SLG)/4, adjusted for ballpark factor. The scale of GPA is similar to BA: .200 is lousy, .265 is around average and .300 is a star
• K/9; BB/9; K/BB. These statistics are strikeouts/9 innings, walks/9 innings, and the ratio of strikeouts to walks. Since strikeouts and walks are wholely under the control of the pitcher, these statistics measure how good the pitcher’s stuff is (based on strikeouts) compared to how good his control is (based on the walks statistics).
• OPSOn Base plus Slugging Percentage. A crude but quick measure of a batter’s true contribution to his team’s offense. On base percentage measure how often the player is able to reach base safely and slugging percentage takes into account the players power numbers (doubles, triples, HRs).
• Pythagorean Record. A formula for converting a team’s Run Differential into a projected Won/Loss record. The formula is RS2/(RS2+RA2). Teams’ actual won/loss records tend to mirror their Pythagorean records, and variances can usually be attributed to luck. The Brewers record is currently 70-51, but their Pythagorean Record is 66-55, indicating that they have been somewhat lucky this year.
• WHIP – Walks and Hits Per Inning Pitched. A variant of OBP for pitchers. This is a popular stat in rotisserie baseball circles.

Statistically Oriented Baseball Blogs and Websites

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