FanGraphs Baseball


RSS feed for comments on this post.

  1. It appears the dollar values may be incorrect for pitchers. Perhaps you didn’t account for inflation in the same way you did on position looks like all the dollars for pitchers are in 2002 dollars. Or is there some other explanation why Sabathia and Chipper Jones would have the same Value Wins in 2008 (7.6), but dollar values of $19.7 and $34+ million, respectively?

    Comment by Jeff — January 12, 2009 @ 4:05 pm

  2. Good catch – David will get that fixed shortly.

    Comment by Dave Cameron — January 12, 2009 @ 4:09 pm

  3. Is the reason that win values are only shown from 2002 on also relating to the dollar values that have been previously calculated? Or is there certain information used in the run calculations that are not available prior to 2002? But this is great, another fun thing to play around with on Fangraphs

    Comment by Rahul — January 12, 2009 @ 4:19 pm

  4. Fixed!

    Comment by David Appelman — January 12, 2009 @ 4:21 pm

  5. Yep, there’s certain information that I have only going back to 2002, mainly for the batter win values. UZR only going back to 2002 is the main reason.

    We could do pitcher values going back to 1974 right now, and possibly 1954 later on, but there is a leverage index component in the pitcher values which makes going back before that not possible.

    Comment by David Appelman — January 12, 2009 @ 4:25 pm

  6. First impressions -

    Man, Roy Halladay is grossly underpaid.

    Comment by Evan — January 12, 2009 @ 4:43 pm

  7. It’s strange living in a world where Javy Vasquez is worth more than Jake Peavy, but I’m sure grateful that such a world exists.

    Comment by Mark R — January 12, 2009 @ 4:59 pm

  8. Not possible for now. If Retrosheet is able to get all of the play-by-plays then you guys go and get the LI’s.

    Comment by Samg — January 12, 2009 @ 5:15 pm

  9. I’m sure you’ll get lots of questions about the use of FIP in this.

    I’m personally more interested in what you’re using for park factors.

    Comment by joser — January 12, 2009 @ 5:25 pm

  10. How do you guys adjust for a pitcher having a huge impact on his own run environment?

    Comment by Samg — January 12, 2009 @ 5:53 pm

  11. And any chance of putting a wRAA next to FIP for pitchers?

    Comment by Samg — January 12, 2009 @ 5:55 pm

  12. I wonder… do the pitchers receive the same amount spent per win that hitters do? If so, should that be the case? We’ve seen baseball teams more often grossly overpay for pitching then we have for hitting. In that regard, pitcher values should be subject to their own sample size.

    Comment by The Typical Idiot Fan — January 12, 2009 @ 5:57 pm

  13. We’ve seen that, but does it make any sense? A win is a win is a win, right?

    Though, I suppose that would impact the market for pitching vs. the market for hitting, so perhaps pitchers simply can’t be had for the same $/win rate.

    Then again, the actual salaries paid to players suggest that no player can be had for the actual $/win rate – it’s just that some are grossly underpaid (like Halladay) and some are grossly overpaid (like Jose Guillen).

    We’d need to measure it to be sure.

    Comment by Evan — January 12, 2009 @ 7:35 pm

  14. Tim Lincecum is very good at baseball.

    Comment by Graham — January 12, 2009 @ 9:52 pm

  15. Am I reading it right that Javier Vazquez was worth more $ in 2008 than in 2007???

    Comment by Gen. Bonkers — January 12, 2009 @ 11:06 pm

  16. Why didn’t you guys use a more advanced stat like tRA? Sorry, but FIP is not by any stretch of the imagination the best pitching metric out there. So why did you stick with FIP?

    Comment by David — January 13, 2009 @ 12:44 am

  17. Also, why use FIP when looking at past value? Zito was a bad value because of the runs allowed, not the FIP runs allowed.

    Comment by dan — January 13, 2009 @ 1:16 am

  18. I see FIP as sort of a middle ground between ERA and tRA. I think that works out nicely for a stat like this. Basically we’ll give a pitcher the benefit of the doubt on the LOB% and BABIP, but a home run problem (which is typically the main culprit for ERA), we’re not willing to ignore.

    Last time I checked FIP and tRA were at least similar with about a .75 r^2, or something like that.

    Comment by David Appelman — January 13, 2009 @ 3:33 am

  19. David, isn’t tRA a middle-ground between ERA and FIP? FIP assumes all balls in play are the same. tERA gives different credit/blame for liners and fly balls for example. Now, there may not be much of a year-to-hear correlation for LD%, but if a pitcher gave them up, one could argue that’s part of his value. Taken a step further, you’d use PZR, which is the pitcher’s half of UZR. With the UZR methodology, you know the expected run value of each batted ball. Assign that to each pitcher. (Fielders get the difference of the expected run value of the batted ball given up by the pitcher and the actual outcome of the batted ball.)

    Comment by Sky — January 13, 2009 @ 10:30 am

  20. It’s my understanding that tRA regresses LD%, so players aren’t getting fully docked for their LD% in tRA and they’re not getting docked for HRs at all.

    Anwyay, upon further research, the 2008 tRA to FIP r^2 for “qualified players” is about .82, so in practice they’re still pretty close.

    Maybe middle ground isn’t quite right. There are differences on both ends, but tRA for qualified players doing a straight average is about .4-.5 points higher than FIP, which does match up with ERA.

    Out of curiosity, has anyone done a study on tRA that shows it to be more useful than FIP/DIPS/whatever else is out there? I’d be curious to see one.

    Comment by David Appelman — January 13, 2009 @ 12:17 pm

  21. Great work on this.

    Two quick questions:
    1)Any chance you will be adding a 2009 projection for value? Using either Marcel or BJames, or combination of both?

    2)Is there a “leaderboard” function that we can sort through values by position, by team, etc?

    Combining 1 and 2, it would be interesting to see projections for teams, both in terms of wins and $ value.

    Comment by A.M. — January 13, 2009 @ 12:58 pm

  22. It’s a good point, and I agree, that FIP/tRA/xFIP/etc are strongly correlated. And are better measures than ERA.

    Graham has done some preliminary work with tRA/ERA/FIP correlations and they’re promising for tRA. He hasn’t published it or finished it, yet, though.

    Any possibility of PZR for the site, David? You already have the UZR methodology implemented…

    Comment by Sky — January 13, 2009 @ 3:04 pm

Leave a comment

Line and paragraph breaks automatic, e-mail address never displayed, HTML allowed: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>

Current ye@r *

Close this window.

0.076 Powered by WordPress