Understanding Sabermetrics by Gabriel B. Costa, Michael R. Huber, John T. Saccoma Read Free Book Online Page B
the EC concept would be applied in a similar way to that of Dizzy Dean ERA projection above. We will revisit the concept of the EC in subsequent chapters (for example, see Inning 9: Creating Measures and Doing Sabermetrics — Some Examples).
Easy Tosses
1. In his career, Hank Greenberg hit 331 HR in 5193 AB. He also walked 852 times, giving him a PA total of 6045. If Greenberg had 11,000 PA, and if we assume that he would have been 2 percent better for the additional PA, find his EC and project his career HR total.
2. Don Mattingly batted .307 over a 14-year career in which he had 7003 AB while drawing 588 BB. If we assume 12,000 PA, with Mattingly 1 percent better for the additional PA, project his career hit total.
3. Sandy Koufax pitched 2324.3 innings and gave up 713 earned runs. Project his ERA given an additional 1200 IP, assuming that he would have been 4 percent better during the additional IP.
4. J. R. Richards, a first-round draft pick by the Houston Astros, was one of the most feared pitchers of his era in the National League. In his shortened career, he pitched 1606 innings and allowed 562 earned runs. Project his ERA and strikeouts given an additional 1000 innings pitched, assuming he would have been 5 percent better.
Hard Sliders
1. Consider the following “split” statistics for Ted Williams:
Give Williams an additional 1500 PA during the years 1939-1951 and assume that he was 8 percent better for the additional PA; furthermore, give him an additional 1000 PA for the remainder of his career while assuming that he was 3 percent better. Project his career totals for H, HR and BA.
2. Warren Spahn is considered to be one of the greatest left-handed starting pitchers of all time. He missed three years of playing ball from 1943 through 1945, due to his military service during World War II. Despite that, he still managed to win more games (363) than any other left-handed starting pitcher. Project his win total, given an additional 750 innings pitched, assuming he would have been 5 percent worse (it was the beginning of his career).
Inning 4: The Linear Weights School — Offense
Since the mid-1980s, there has been an explosion of new statistics, many commonly accepted by fans, players, writers, and official scorekeepers. Pete Palmer and John Thorn developed a statistic based on a formula known as “linear weights,” in order to view the numbers of the game “as a means of encapsulating and comprehending experience.” They went on to note that the tendency to scrutinize statistics is truly at the heart of baseball’s hidden game. They recognized that there is an essential relationship between scoring runs and winning games. When the linear-weights model was developed, that relationship was analyzed using raw data in major league baseball’s official records.
As a precursor to Thorn and Palmer’s Linear Weights statistic, we must mention the works of F. C. Lane and George Lindsey. Ferdinand Cole Lane was a biologist who spent 27 years working for Baseball Magazine (he was editor from 1912 to 1937), analyzing baseball through statistics that were decades ahead of their time. Well before 1920, Lane conducted a study of exactly 1000 base hits, which occurred in 62 major league games. His goal was to assign a value to each hit and then study the probability of each hit producing a run. He started with a single being one-quarter, a double being one half, etc., and then added a few adjustments for runners on base. After a lengthy study, he developed the run value of a particular hit:
Runs = (0.30 × 1B) + (0.60 × 2B) + (0.90 × 3B) + (1.15 × HR)
A single was worth 30 percent of a run, a double was worth 60 percent of a run, a triple was worth 90 percent of a run, and a home run was worth 115 percent of a run. Lane used his formula to compare various type of hitters: singles hitters versus sluggers, for example. According to his relationship, a double was twice as good as a single, and
Easy Tosses
1. In his career, Hank Greenberg hit 331 HR in 5193 AB. He also walked 852 times, giving him a PA total of 6045. If Greenberg had 11,000 PA, and if we assume that he would have been 2 percent better for the additional PA, find his EC and project his career HR total.
2. Don Mattingly batted .307 over a 14-year career in which he had 7003 AB while drawing 588 BB. If we assume 12,000 PA, with Mattingly 1 percent better for the additional PA, project his career hit total.
3. Sandy Koufax pitched 2324.3 innings and gave up 713 earned runs. Project his ERA given an additional 1200 IP, assuming that he would have been 4 percent better during the additional IP.
4. J. R. Richards, a first-round draft pick by the Houston Astros, was one of the most feared pitchers of his era in the National League. In his shortened career, he pitched 1606 innings and allowed 562 earned runs. Project his ERA and strikeouts given an additional 1000 innings pitched, assuming he would have been 5 percent better.
Hard Sliders
1. Consider the following “split” statistics for Ted Williams:
Give Williams an additional 1500 PA during the years 1939-1951 and assume that he was 8 percent better for the additional PA; furthermore, give him an additional 1000 PA for the remainder of his career while assuming that he was 3 percent better. Project his career totals for H, HR and BA.
2. Warren Spahn is considered to be one of the greatest left-handed starting pitchers of all time. He missed three years of playing ball from 1943 through 1945, due to his military service during World War II. Despite that, he still managed to win more games (363) than any other left-handed starting pitcher. Project his win total, given an additional 750 innings pitched, assuming he would have been 5 percent worse (it was the beginning of his career).
Inning 4: The Linear Weights School — Offense
Since the mid-1980s, there has been an explosion of new statistics, many commonly accepted by fans, players, writers, and official scorekeepers. Pete Palmer and John Thorn developed a statistic based on a formula known as “linear weights,” in order to view the numbers of the game “as a means of encapsulating and comprehending experience.” They went on to note that the tendency to scrutinize statistics is truly at the heart of baseball’s hidden game. They recognized that there is an essential relationship between scoring runs and winning games. When the linear-weights model was developed, that relationship was analyzed using raw data in major league baseball’s official records.
As a precursor to Thorn and Palmer’s Linear Weights statistic, we must mention the works of F. C. Lane and George Lindsey. Ferdinand Cole Lane was a biologist who spent 27 years working for Baseball Magazine (he was editor from 1912 to 1937), analyzing baseball through statistics that were decades ahead of their time. Well before 1920, Lane conducted a study of exactly 1000 base hits, which occurred in 62 major league games. His goal was to assign a value to each hit and then study the probability of each hit producing a run. He started with a single being one-quarter, a double being one half, etc., and then added a few adjustments for runners on base. After a lengthy study, he developed the run value of a particular hit:
Runs = (0.30 × 1B) + (0.60 × 2B) + (0.90 × 3B) + (1.15 × HR)
A single was worth 30 percent of a run, a double was worth 60 percent of a run, a triple was worth 90 percent of a run, and a home run was worth 115 percent of a run. Lane used his formula to compare various type of hitters: singles hitters versus sluggers, for example. According to his relationship, a double was twice as good as a single, and
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