Guess Who’s Back

You can all stop holding your breath now- that’s right, I have returned from my nearly two-year blogging hiatus.  So much has happened since my last post, in the baseball world and in my own.  I’m now close to completing my freshman year at Boston University and the New York Yankees are now reigning world champions.  Go figure.

No promises on how often I’ll update this time- but hopefully it won’t be two years until my next post.  I’d like to add a new spin to the blog as well.  Since my last post I’ve developed more of an affinity for the number behind baseball- sabermetrics for those familiar with the term.  I spend much of my free time on http://www.baseball-reference.com which, by the way, is an incredible site for anyone with even the slightest interest in baseball or anyone trying to settle any baseball related argument.  They have an overwhelming amount of data over there, and one of these days I’m going to get around to giving back to them either via donation or volunteer work.
One of my favorite features on the website has to be the similarity scores.  At least a few of my posts in the coming weeks will be about these specifically, because quite frankly I think they’re awesome.  To put it simply, similarity score is an advanced stat created by Sabermetrics God Bill James that is designed to show how similar two given players careers have been.  Every player has not only a list of his top 10 similar players for his career numbers, but also the top 10 most similar careers through a given age.  I encourage you to read the quick primer here if you’re interested at all: http://www.baseball-reference.com/about/similarity.shtml
Today I want to talk about Josh Beckett.  While perusing his page the other day I noticed that his most similar player is none other than brand new teammate, John Lackey.  The way similarity score works is it starts at 1000 and points are subtracted for each “unsimilar” thing. Lackey’s score is 971, so they actually have had remarkably similar careers.  Beckett has a record of 107-68 compared to Lackey’s 103-71, and a lifetime ERA of 3.81 compared to Lackey’s 3.79.  
One of the trends in baseball today is general managers and front offices leaning towards new age statistics such as WAR, UZR, and ERA+ to determine a player’s value.  This may be part of the reason why a Jermaine Dye who is coming off a 27 HR, 81 RBI season is still unemployed, but that’s a story for another post.  I only mention this trend because I wonder if any agent or GM has tried to use these similarity scores in negotiations.  Much was made this winter about John Lackey’s brand new 5 year, $82.5 million deal.  GM Theo Epstein had previously set a precedent of not signing starting pitchers to contracts longer than 4 years, but he broke that rule for Lackey.  When it came time to extend Josh Beckett this spring, he told Beckett that he would not do the same for him, and Beckett accepted a 4 year, $68 million extension.  Now of course similarity score does not take expected performance into account, which is at the forefront of contract negotiations.  Beckett has more injury questions than Lackey, which is the reason Theo & Co. are reluctant to sign starting pitchers to long-term deals in the first place.  But it seems to me like Beckett and his agent Michael Moye could have pushed harder for a 5 year deal, given its proximity to Lackey’s and the near identical careers of the two pitchers.  
From here on out, you can assume all data is coming from either http://www.baseball-reference.com or Cot’s Contracts at http://mlbcontracts.blogspot.com.  Both are fabulous resources and I am forever indebted to them.  So credit to them.  Drop me a comment if you enjoyed this post and I’ll try to post again soon.
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