Weighted Runs Above Average (wRAA) — Player Analysis
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Stat of the Week
by Peter Liubicich
Weighted Runs Above Average (wRAA) — Player Analysis
This post was written by Peter Liubicich on February 18, 2013
Posted Under: Stat of the Week

Last week we began to look at Weighted Runs Above Average (wRAA), which along with Weighted Runs Created (wRC), On-Base Plus Slugging Plus (OPS+) and Weighted On-Base Average (wOBA), are the most useful statistics to evaluate the offensive production of a hitter in my opinion.

What wRAA tells us according to FanGraphs is “the amount of “offensive runs a player contributes to their team compared to the average player” over the course of a season.”

The formula to calculate wRAA is:

wRAA = ((wOBA - league wOBA) / wOBA scale) × PA

The scale for evaluating a player based on their wRAA is:

Rating

wRAA

Excellent

40

Great

20

Above Average

10

Average

0

Below Average

-5

Poor

-10

Awful

-20

This past season, AL MVP Miguel Cabrera had the highest wRAA in MLB at 57.3, with Ryan Braun coming in second at 53.4 and AL MVP runner up Mike Trout coming in third with a wRAA of 48.2.  NL MVP Buster Posey finished sixth this season in terms of wRAA with 44.7.

Now the MVP race stereotypically hinges on a player’s offensive production and their team’s performance (especially reaching the playoffs), which explains why Cabrera and Posey won their league’s MVP Award.  There is no doubt that Trout was the more dynamic defensive player than Cabrera and that Braun was more productive at the dish than Posey, but Cabrera and Posey were the leaders of their team’s offenses during the season and both won their division’s title, likely giving them the edge in MVP voting in the minds of the Baseball Writers’ Association of America (BBWAA).

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Reader Comments

“This past season, AL MVP Miguel Cabrera had the highest wRAA in MLB at 57.3, with Ryan Braun coming in second at 53.4 and AL MVP runner up Mike Trout coming in third with a wRAA of 48.2. NL MVP Buster Posey finished sixth this season in terms of wRAA with 44.7.”

Linear weights provide a reasonable way to compare players of different generations. I would like to suggest, however, that, when comparing contemporary players, their actual contributions are more accurately measured by non-linear models, specifically WPA or RE24. In that case one finds Trout, for example, to have contributed more to both winning and runs: (Trout; WPA=5.3, RE24=54. M Cabrera; 4.8, 47).

More generally, I do not understand the appeal of wRAA, or any linear attempt to approximate productivity, in preference to non-linear models. I’m interested in your thoughts and response. Thanks. Zack

#1 
Written By Zack sf on June 11th, 2013 @ 12:44 am

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