As we continue our trip through the year's best in sabermetrics as voted internally by Beyond the Box Score and by its loyal readers and fans, we arrive today at the Best Applied Research Article/Project category. Before we move into the voting, let's once again define the category in question.
Research that takes established sabermetric principles and applies them to help understand a specific case (typically a player, a team, a transaction, etc). The difference between novel and applied research is newness of approach and scope of impact.
You'll find that the pieces that follow will work out quite well with regards to this criterion. Keep in mind also how the voting was tabulated, as explained by JinAZ in the first post. Without further ado, let us unveil the top four spots in our inaugural voting for the Best Applied Research Article/Project!
Going back to our original project -- measuring the little things -- we can see that WPA/LI definitely includes small things not included even in wOBA/wRAA. Moving a runner over at the cost of an out does advance a team's cause (in some situations), even if wOBA just sees it as another out. On the negative side of the ledger, wOBA/wRAA also doesn't recognize that grounding into a double play makes two outs -- it's just another failed plaet apperance like any other. WPA/LI recognizes proportionally how much that hurts a team by making two outs and taking a baserunner off of the base.
wRAA is better at measuring a player's raw offensive value, since it eliminates the game-state, base-state, and out state from the equation, things that the player has no control over (in the immediate sense). WPA/LI on the other hand, is very context-sensitive, only equalizing the importance of each PA.
This is the thought process that went into the idea of the "Little Things" that Matt then measures by taking the difference between the approach-sensitive WPA/LI and the entirely context-neutral wRAA. The result is the value of the "Little Things" the player does on the field to help his team win, such as "productive outs," avoiding double plays, and other such factors ignored by context-neutral linear weights. It was a simple, yet elegant design for determining something that is often discussed by sports pundits as being critically important to how the game is played. The 2008 winner was none other than Jack Hannahan, and in this year's rendition, the very bearded Casey Blake took home the award, which is now under the purview of FanGraphs.
So what did we learn today with this obnoxiously long article? Well I took a pitcher's 10 best and worst starts of the year, in which you'll remember there was an ERA difference of about 8, and found no meaningful differences in terms of what he threw, the velocity/movement of his pitches, where he threw them and when he threw them. I think I've established that there was practically no difference in how he pitched in his good starts compared to his bad starts.
Of course, I hope you read Nick's obnoxiously long article to view what he analyzed via Pitch f/x data about this pitcher's (A.J. Burnett) ten best and worst starts. Nick breaks down Burnett's pitches in terms of stuff, location, selection, and approach, attempting to see the differences between those marvelous and disastrous starts that have made the name "Burnett" synonymous with "inconsistent." Though the conclusion here is not wide-ranging, it is studied fairly thoroughly and has led to more work that suggests, in Nick's opinion, that pitchers may have even less control than DIPS has commonly assumed.
You can see very distinct sections in Bay's graphs where he excels against both LHPs and RHPs. These pitches have the same velocity and movement as your league average fastball (about 85-95 miles per hour with 5-10 inches of horizontal and vertical movement), which meshes with Bay's reputation as a fastball hitter. Over the past two seasons, Bay has been the fourth best hitter in baseball against the fastball. He’s not as good against curveballs, especially slower breaking pitches. I didn’t note anything remarkable in Holliday’s release point graphs nor his velocity/movement graphs, but Holliday does have interesting pitch splits. He saw 65% fastballs with the A’s and 55% with the Cardinals. In exchange, he saw his slider rate nearly double in St. Louis. The increase in slider percentage might have been part of the reason Holliday found renewed success, as he has been the top hitter in the Majors against the slider over the last two years.
To fully grasp why this paragraph itself was so awesome, one would have to click on the link and view the corresponding graphs. The graphs Jeremy puts together to display the "Visual Scouting Report" are astounding, revealing a treasure trove of information in a format easy to digest (providing you know a little bit about Pitch f/x charts). The analysis of these two premium hitters' tendencies at the plate provided us a more in-depth look at each player's plate discipline, performance against pitch types and platoon splits, and their spray of balls in play. Indeed, this could and should be the future of in-depth hitter analysis, and just the sort of information major league clubs could use in analyzing their own players.
(drum roll please)
And your winner of the 2010 (2009? I can never get the convention for award years correct) "Saber" for Best Applied Research Article/Project goes to:
1. Dave Allen - Run Value by Pitch Type and Location
This four-part "series" (really, it's not defined a series per se, but each article was tied together by common themes and was worth its merit in telling the story) done by Dave over at Baseball Analysts revealed a lot of information using Pitch f/x regarding the run value of pitches based on location and pitch type. Dave unleashes the full use of his heat map graphs in this set of articles, displaying heat maps of run values for overall location and location broken down by pitch type and batter/pitcher handedness. Within these charts lies information which Dave deciphers, information that generally follows with our general understanding of how pitches work. At the end of the series, Dave summarizes run values for each pitch type for each set of batter/pitcher handedness combination.
Congratulation to Dave Allen, who is personally one of my favorite writers in the business today. And of course, congrats to everyone else who was nominated. The following are the remaining nominees, in alphabetical order by author:
Again, congratulations to everyone who was nominated, each article was worth every minute of reading we spent on it in 2009 (and beyond). And congratulations to Dave Allen again for winning! Here's your Saber award!
It's also available in "light" form if necessary.
Hope to see more exciting applied research in 2010!