Section 518

Where we endeavor to stay positive about the 2011 Mets…

Crow: I Eats It

Posted by JD on April 2, 2010

So, me being me, I retweeted a link from Bill Simmons today with an off the cuff comment:

The day we’ve all been waiting for! #sarcasm RT @sportsguy33: The sabermetric revolution finally wins me over http://bit.ly/8XbYmQ

While I typically enjoy all of Simmons’ work, he (by his own admission) has been a tad unfair to the sabermetric community over the years. So, I jumped on his tweet before actually reading the article. Which, you know, was not entirely fair in and of itself.

After reading it I’ve found that it’s an excellent primer. Not only for his summations, but for the links he provides (and the links within the links). I know that I rely too heavily on OPS+ in my own (limited) analysis and while I try to learn the new statistics and incorporate them here, I often take the lazy way out. In explaining his own conversion, Simmons clearly did not.

I wanted to post this here as a way to both atone for my own snark and to keep his article for my own future use. Kudos to Simmons for seeing the light and providing an easy-to-use guide to “average fans” like me to expand our knowledge. It’s far better to come late to the party than not to come at all, and Simmons deserves some praise for bringing a well-written guide with him.

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7 Responses to “Crow: I Eats It”

  1. Ceetar said

    I read up on these stats more and more, but they bug me. There is too much that seems like they’re guessing, and too much that they seem to ignore. Maybe one day i’ll have the chance to actually discuss them with someone that’s a real expert.

    • JD said

      I have to disagree with your comment about “guessing” when it comes to offensive stats (I can’t defend the defensive stats as they are less transparent). I think it’s fair to say that there’s room to grow and that it’s almost inevitable that they’ll be improved upon, but calling it “guessing” is unfair. It’s a process, taking known variables and sharpening their focus.

      As for discussing them with a real expert (I am MOST DEFINITELY not an expert), I highly recommend emailing Rob Neyer at ESPN with your questions. As long as you stay on topic, he’s typically diligent in replying to his emails (at least, he was to me) and I think he’s pretty good at breaking the stats down to basics. I’m sure there are other folks to contact, but he’s been very accessible in the past.

      • Ceetar said

        Maybe I don’t fully understand. But I feel like what they say is a ‘replacement player’ or ‘park factor’ is very heavily weight on things that are basically guesses (Maybe guesses is too strong a word). Line Drive %, for instance. At one point, that’s a judgment call. Then again, the entire game is a judgment call, since that’s basically how we call balls and strikes.

        I try not to get too into it, because I feel like I’m speaking from “a little knowledge is a dangerous thing” point of view, but I’ll try emailing Rob Neyer and/or write up a post on it myself with my concerns, at least to the point of getting it a little more thought out.

      • JD said

        Ok, now I understand. And I think I agree with you on some level. The advanced defensive stats are reliant on observers watching every play, charting the ball, and determining what an “average fielder” could get to. There’s very little transparency because they are trying (in some part) to make money off of it. That’s fair. If you can’t crunch the raw numbers and replicate the results on your own, you’re right to be skeptical.

        Same thing with the “replacement player” concept. It does seem slightly arbitrary. This might help: are you familiar with the concept of a “haircut”? In the financial industry, regulators force brokers to reduce the value of their inventory by a certain percentage based on the liquidity of the product. It varies: for listed stocks, it’s 15%, but for exotic products (like CMO’s) it can be as much as 85-100%. I view replacement player in the same light. The haircut is lower for a left fielder or first baseman than it is for a shortstop. It’s a way to discount the value of the average player. As Simmons said, it’s much more useful for the majority of players than it is for the extremes: we know Pujols is awesome and Ronny Cedeno isn’t, but how do we quantify an Angel Pagan or Rod Barajas?

        Anyway, I hope you do write that post because I’d love to keep this dialogue going. As I mentioned, I’m still learning the concepts myself, so any questions/comments/doubts that you have will only help me, too. It’s the journey, not the destination…

      • Ceetar said

        Not familiar with the haircut no, but I do somewhat understand that a 1B is easier to find a certain quality of than a SS. Something I also disagree with to an extent, in that the world is not equal, the ‘replacement’ level guy that the Mets have access to might not be the same as say the Royals, and then you go into the debate about how likely is a replacement level player actually going to perform at replacement level, or drop off. Because it’s all odds and statistics, it doesn’t actually work out that well when you do thinks like “eh, we can just cut Daniel Murphy, whatever we throw there will stick as a replacement level.” So while it might be a useful tool as a baseline for evaluations, it also isn’t necessarily a hard and fast rule you can apply to personnel moves either. On top of that, I believe it’s calculated based on the existing players, so Pujols and Cedeno are known to be good/bad, but the degree to which they are good/bad (especially as ends of the spectrum) actively affects how everyone else is perceived.

        Not to say that any of my points are completely accurate or can’t be debunked either. There is something that disturbs me about it being a ‘revolution’ and players being pigeon holed based on a statistical analysis as an absolute value. Especially young players. Which is why the “Daniel Murphy sucks” arguments annoy me, because I know statistical analysis does not take into account specific players or their ability to learn. A concrete example is a pitcher who suddenly decides he’s going to learn and throw a curveball. It basically makes him a different pitcher and throws all the previous statistics out of whack. That’s the extreme example but there are many shades of gray as well.

        Regardless, I do want to write that post, and I do want to find the time to do some more research into these stats as I’ve always been a mathematical person. Enjoy your evening. :-D

  2. Well, in the final analysis, we baseball fans are all in this together. It’s sort of ironic, not to mention pointless, that we seem to break up into two so-called “schools of thought.” That’s not to say that every fan needs to think the same way. But all that really matters is that we all love baseball. Nice post on your part, Bill

    • JD said

      Thanks Bill. You’re right about “schools of thought”. Divergent viewpoints are the spice of life, especially when it comes to watching the game of baseball. I’d love to take back that original tweet but I can’t because I feel like that would be dishonest. This was my mea culpa…probably won’t be my last! Thanks for reading.

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