FanGraphs Baseball


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  1. Interesting bit – although it appears that this data in measuring “luck” can really only be applied to relievers. Almost all the outliers from the mean xouts were short men, while most starters appear to have fairly normalized xouts due to more innings logged. It would be interesting to use SPSS to analyze what correlation exists between xouts and FIP, because most of the data is not as cut and dry as your examples of Rhodes and Qualls.

    Comment by M T K — June 17, 2010 @ 6:02 pm

  2. When are you guys going to realize that “Non-predictive across the entire sample” does not mean “Luck”

    Comment by Rich — June 18, 2010 @ 10:52 am

  3. Also, why is it always assumed here that K’s are a non-luck based event?

    Qualls has the highest K/9 rate of his career while having the lowest swinging strike percentage of his career. Isn’t it entirely possible that LUCK is inflating his k/9, and hence his FIP?

    He’s also throwing less first strikes than he ever has in his career, walking more guys, and giving up 23% line drives.

    Sometimes BABIP isn’t pointing to luck; sometimes its pointing to a guy who is getting himself into bad counts, and getting crushed.

    Comment by Rich — June 18, 2010 @ 11:00 am

  4. is there a way to get the UZR expected outs, for these pitchers. it would also be cool to see the expected outs for different batters to see who is lucky, it would be better the BABIP or line drive percentage

    Comment by GWR — June 18, 2010 @ 3:27 pm

  5. I think the k/9 rate going up is directly tied to the amount of batters he’s facing.

    Think of it this way, if everything that goes in play is a hit — I’m pretty sure his babip against is 1.000 — then the number of batters he’ll have an opportunity to strikeout goes up, eh?

    Comment by Matt — July 4, 2010 @ 6:40 pm

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