Monday, October 17, 2005

Detroit Tigers Runs Created Analysis

How many runs does a player contribute to his team’s offense? One way to answer this question is the statistic “runs created”. Runs created (RC) is not the most popular sabermetric measure today but it was one of the statistics which made Bill James (the God father of modern sabermetrics) famous. There are many versions of the statistic but the basic formula is always

(A times B) divided by C

where A=times reached base, B=total bases and C=plate appearances

I used the version published in The Hardball Times . It is the most complex of all the RC formulas and includes the impact of every offensive stat available. This includes HBP, stolen bases, caught stealing, sac flies, sac bunts, strikeouts and double plays. It even includes hitting with runners in scoring position.
The specifics of the formula can be found at Wikipedia

The version found in The Hardball Times is also adjusted for ballpark effect. In the case of the Tigers, this means, the runs created is adjusted upward a little for each player to allow for fairer comparisons with players who play in more hitter friendly parks.

Does RC work? If you add up the individual RC (before making ballpark adjustments) for players on a team, it generally comes pretty close to the total runs scored for that team. This is an indication that it is doing a fairly good job of measuring what it is intended to measure: how much each player contributes to his team runs scored total.

Another statistic is runs created per game or runs created per 27 outs (RC/G). Theoretically, this statistics tells you how many runs scored your team would score per game if you had the same player bat in all line-up positions. For example, Brandon Inge had an RC/G of 5.2 so you would theoretically expect a team of 9 Brandon Inges to score 5.2 runs per game. That’s not a very practical or realistic use of the statistic. However, it’s a good statistic for comparing the offensive contribution of different players.

A player like Inge who played a lot of games will have more runs created than a player like Chris Shelton who came up at midseason. On the other hand Shelton hit better when he did play so he’ll have a higher runs created per game. Both stats are useful depending on the question being asked.

The Table below ranks the Tigers in RC.

Player         RC      Lg Rank
Inge           87      32
Monroe         82      38
Shelton        70      61
White          65      68
Polanco        64      70
Young          64      70
Ordonez        54      98
Rodriguez      47      111
Guillen        42      116
Pena           42      116
Infante        41      122
Logan          35      127
Granderson     27      142
Wilson         14      175
Thames         11      189
Martinez       7       205
McDonald       6       214
Smith          4       226
Giarratano     3       240
Gomez          1       265
Hooper         1       265
Higginson      0       291

The table shows that Inge contributed more runs (87) to the offense than any other player on the team. He was followed by Craig Monroe (82), Shelton (70), Rondell White (65), Placido Polanco (64) and Dmitri Young (64). The final column on the table shows where players ranked within the American League. No Tigers finished in the top 30 which helps to explain why they had trouble scoring runs this year.

The next table ranks the Tigers in RC/G

Player         RC/G    Lg Rank
Polanco        7.6     13
Shelton        6.9     18
Ordonez        6.9     19
White          6.8     23
Granderson     6.3     ***
Pena           5.7     51
Monroe         5.4     60
Inge           5.2     67
Young          5       80
Guillen        5       84
Martinez       4.9     ***
Hooper         4.3     ***
Logan          3.9     118
Rodriguez      3.5     127
Infante        3.5     129
Thames         3.4     ***
Wilson         3.1     ***
McDonald       3.1     ***
Gomez          2.7     ***
Smith          2.2     ***
Giarratano     2.1     ***
Higginson      0       ***

This table looks a lot different because the players who contributed the most over the course of the full season were not the best hitters. Polanco tops the list at 7.6. Would a team of 9 Polancos score 7.6 runs per game? If the 9 Polancos performed exactly the same as the one Polanco did, then the answer would be yes. That’s a fun way to interpret the stat but it’s impossible to know what would really happen with such a line-up. Whatever way you look at it, Polanco was good ! He was followed by Shelton (6.9), Ordonez (6.9), White (6.8) and Granderson (6.3). Note that Monroe and Inge are much lower on this list (7th and 8th respectively).

The League rank column only has a value for players with 295 or more late appearances. I was going to use a 300 limit but Pena missed by just 5 PA so I decided on the 295 limit. Only 133 AL players reached 295 PA. For this measure, the Tigers did have 4 players in the top 30. This might bode well for 2006.

No comments:

Post a Comment


Blog Archive


My Sabermetrics Book

My Sabermetrics Book
One of Baseball America's top ten books of 2010

Other Sabermetrics Books

Stat Counter