BtB Sabermetric Writing Awards: Voting for Best Novel Research Project

Update: Here are links to the other voting categories.

 

It is time to vote on the BtB Sabermetric Writing Awards!  As a reminder, the community vote has a 50% say in who gets the award (the other 50% being an internal vote among BtB writers as well as a few invited guests).

Here is our first category description.

Original sabermetric research that enhances our understanding of some general aspect of baseball. These studies should help establish new sabermetric principles, metrics, techniques, or perspectives. Think "breakthrough research" when nominating this category.

And here are your nominees, along with a description provided from the nomination thread.  They are sorted randomly, courtesy of excel's rand() function:

1. Mike Fast: Confessions of a Dips Apostate
http://www.hardballtimes.com/main/article/confessions-of-a-dips-apostate/
An amazing look at the outcome of batted balls by location.

2. Max Marchi: Chase-ing the FieldF/x
http://profpeppersassistant.blogspot.com/2009/02/chase-ing-fieldfx.html
The first time I’ve seen cluster analysis used with spray charts – Max located the ideal positioning again
st Chase Utley.

3. Matt Swartz: Improving BABIP Estimation
http://www.thegoodphight.com/2009/2/2/743228/improving-babip-estimation
It’s well-thought out, concise, and transparent on a subject that is very rarely tackled at that deep a level.

4. Colin Wyers: When Is A Fly Ball A Line Drive
http://www.hardballtimes.com/main/article/when-is-a-fly-ball-a-line-drive/
An investigation of whether press box location affects stringers' perceptions enough to alter how they classify batted balls.

5. Mitchel Lichtman (MGL): An Age Old Question
http://www.insidethebook.com/ee/index.php/site/comments/mgls_aging_study/ 
MGL addresses survivor bias in the delta method by using a conservative Marcel projection to include players who drop out of the sample in Year 2 in order to diminish the effects of false decline, which can improve any study which uses the popular delta method.

6. Greg Rybarczyk: 2009 Projections with Hit Tracker
http://baseballanalysts.com/archives/2009/02/2009_projection.php
Greg details a new method for doing projections for hitters involving information about batted balls. Eventually I believe this could be the way all projection systems work as we get more and more of this type of detailed batted ball data. It’s a fantastic concept.

7. Jeremy Greenhouse: Controlling the Zone
http://baseballanalysts.com/archives/2009/12/controlling_the.php
Jeremy’s writing and overall work is awesome, and this is a great example of it.

8. Dave Allen: PitchF/X Detective: Has Bradley's Strike Zone Been Widened
http://baseballanalysts.com/archives/2009/05/pitchfx_detecti.php
I know that it applies specifically to Bradley, but he’s done these contour maps for a few other players and I think they’re a great use of Pitch f/x, not only for analysis of player value but as a way to project future performance and assist players with their plate approach (if it gets in the hands of front offices).

9. Josh Kalk: The injury zone
http://www.hardballtimes.com/main/article/the-injury-zone/
A first look at a way of identifying injuries before they fully manifest themselves using Pitch f/x. The idea combined with the amazing tech ability it took to do the article makes this a legitimate advancement in research.

10. Adam Guttridge: Guttridge-Wang Trade Model
http://www.hardballtimes.com/main/article/the-guttridge-wang-trade-model/
I think this was one of my favorite pieces of the year.  Couples value-based trade analysis with recognition that wins have different values for different clubs.

11. Victor Wang: Valuing a Draft
http://www.hardballtimes.com/main/article/valuing-the-draft-part-one/
http://www.hardballtimes.com/main/article/valuing-the-draft-part-2/
These articles allow us to assign dollar values to different kinds of draft picks, which is important to help us understand the full impact of free agent compensation (and trading of draft picks, if that ever happens).

12. Brian Cartwright: Major League Equivalencies
http://www.baseballprospectus.com/article.php?articleid=8887
Challenges common assumptions on how to accurately model MLEs.

You may vote below the jump!


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