A Baseball Weblog

Tuesday, December 28, 2010

Laying it down, part 1

I've been thinking a lot about bunting recently.  Considering all of the information we have about offensive statistics, it's surprising to me that we don't have more data on bunting readily available - Fangraphs has data for bunt hits and sacrifice bunts, but it's much more difficult to find information for bunts that aren't hit into play.  Certainly, one of the most important aspects of being a good bunter is being able to consistently get the ball in play, so I believe that it's just as important to look at foul and missed bunts as it is to look at fair bunts.  Combining the Fangraphs bunting splits leaderboard with PITCHf/x data can give us a more detailed look at who the league's better and worse bunters are.

There are three main things that I was able to quantify with the data I was working with - the frequency with which a batter attempts to lay down a bunt, the frequency of bunts put into play, and the overall quality of the bunt.  Before I get more in depth on the metrics I've been working with, I think it would be best to show some generic bunting benchmarks for the 2010 season.


Attempt%Fair%Foul%Missed%
League Average.019.505.416.080



Hit%Out%Sac%Double Play%
League Average.188.286.517.009

For the first table: attempt% is the number of bunt attempts (fair bunts, foul bunts, missed bunts) divided by the total number of swings; fair% is the number of fair bunts divided by bunt attempts; foul% is the number of foul bunts divided by bunt attempts; missed% is the number of missed bunts divided by bunt attempts.  For the second table: hit% is the number of bunt hits divided by fair bunts; out% is the number of bunt outs (in which a sacrifice is not involved) divided by fair bunts; sac% is the number of sacrifice bunts divided by fair bunts; double play% is the number of bunt double plays (there are very few of these) divided by fair bunts.  As you can see by the attempt percentage, it's not that common that a hitter decides to try to lay down a bunt - on average, only three or four pitches in a game result in a bunt attempt.  For the 2010 season, which is the data set that I'll be working with for this post, I have a total of 5,921 bunt attempts.



Who attempts to bunt the most?


The first metric I'd like to dig deeper into is attempt percentage.  The distribution below shows the attempt percentages for 573 hitters who took at least 75 swings last year.  
Of the qualified hitters, there were 138 without a single bunt attempt, and a few more with an attempt percentage between 0% and 1%.  Approximately 90% of the qualified players had rates under 10%, and the vast majority of the players over the number were pitchers, with Tim Lincecum (.252), Aaron Cook (.247), Livan Hernandez (.234), Zach Duke (.223), and Dave Bush (.218) leading the charge.  Raising the minimum number of swings to 200 (and thus eliminating pitchers) gives us these leaders:

RankNameTeamAttempt%
1Carlos GomezBrewers.107
2Julio BorbonRangers.105
3Peter BourjosAngels.102
4Juan PierreWhite Sox.098
5Erick AybarAngels.096
6Nyjer MorganNationals.095
7Emilio BonifacioMarlins.093
8Luis CastilloMets.083
9Gregor BlancoBraves/Royals.081
10Everth CabreraPadres.078
  
On a counting level, Juan Pierre was the clear champion of bunt attempts with 111; he was the only player with more than 100.  Next closest were Nyjer Morgan and Erick Aybar with 95 and 94, respectively.

One more thing on attempt percentages.  Common baseball sense would tell us that the guys who are less offensively adept would be the players resorting to bunting most often.  Based on these data, that would appear to be the case.  Keeping the 200 swing minimum, here is attempt percentage plotted against linear weight runs per 100 pitches (the numbers aren't exact, so don't consider 0 to be the exact 2010 league average).








For the most part, the frequent bunters are to the "below-average" side of the chart.  If you were wondering, the outlier with a bunt percentage of just over 6% and and an 0.69 runs per 100 is the Tigers' Will Rhymes.


Who gets it in fair territory?


As I showed in the benchmarks, the league average rate for fair bunts was just over 50%.  For the purpose of looking at season leaders and trailers, I've set a minimum of 20 bunt attempts, which leaves 70 bunters from last year.  The tables below show the fair bunt rates for the 10 leaders and trailers.

RankNameTeamAttemptsFair%
1Scott PodsednikRoyals/Dodgers33.818
2Ramon SantiagoTigers27.778
3Will RhymesTigers20.750
4Daric BartonAthletics20.750
5Clayton KershawDodgers27.741
6Ryan DempsterCubs26.731
7Barry ZitoGiants22.727
8Alexi CasillaTwins20.700
9Tony GwynnPadres30.700
10Elvis AndrusRangers56.679




1xRoy HalladayPhillies22.136
2xB.J. UptonRays23.174
3xRajai DavisAthletics36.222
4xAlcides EscobarBrewers37.270
5xChris CoghlanMarlins29.276
6xMike LeakeReds22.318
7xJon GarlandPadres22.364
8xAnibal SanchezMarlins22.364
9xNick PuntoTwins27.370
10xOrlando HudsonTwins27.370


Since this metric only judges whether the bunt was in play or not, its best use is probably to determine which players would be good in sacrifice situations.  There are plenty of pitchers sprinkled throughout the list (including three in the top 10 and four in the bottom 10), and the pitcher's role is almost exclusively to sacrifice.



Who does the most damage?


But what about what happens once the ball is in play?  There are a number of possible ways to quantify this; Fangraphs has bunt average, which is a good way to show how productive non-sacrifice bunts were.  In this post, I will use hits over all fair bunts as opposed to non-sacrifices (detailed in the glossary).  Below are the 10 leaders for hit%, out%, and sac%, with 10 fair bunts as the minimum. 

RankNameTeamFair BuntsHit%
1Adam JonesOrioles12.583
2Gregor BlancoBraves/Royals21.571
3Cameron MaybinMarlins11.545
4Jose ReyesMets17.529
5Ichiro SuzukiMariners14.500
6Angel PaganMets25.480
7Ben ZobristRays15.467
8Kevin FransdenAngels11.455
9Sean RodriguezRays16.438
10Cesar IzturisOrioles17.412


RankNameTeamFair BuntsOut%
1Emilio BonifacioMarlins14.786
2Koyie HillCubs10.600
3Rafael FurcalDodgers11.545
4Reggie WillitsAngels13.538
5Trevor CroweIndians13.538
6Roger BernadinaNationals17.529
7Juan PierreWhite Sox55.527
8Michael SaundersMariners14.500
9Drew StubbsReds14.500
10Orlando HudsonTwins10.500


Rank NameTeamFair BuntsSac%
1Darnell McDonaldRed Sox13.923
2Brett MyersAstros12.917
3Clayton KershawDodgers20.900
4Barry ZitoGiants16.875
5Roy OswaltAstros/Phillies13.846
6Ryan DempsterCubs19.842
7Bud NorrisAstros12.833
8Chris CarpenterCardinals12.833
9Chris VolstadMarlins11.818
t-10Mat LatosPadres11.818
t-10Wandy RodriguezAstros11.818
t-10Livan HernandezNationals11.818


The sacrifice column is interesting because it is composed entirely of pitchers except for the leader, Red Sox outfielder Darnell McDonald.
The last thing I'd like to look at in this post is a way to tie in all of the facets of bunt attempts into one metric.  Using run values is typically the best way to do this.  For bunts in play, I'm using the following weights (with "0" representing a neutral outcome):


Bunt Double Play - -0.78
Bunt Out - -0.28
Sac Bunt - -0.03
Bunt Single - +0.50
Bunt Double - +0.83 (there was only one bunt double last year, courtesy of Cliff Pennington)


In the overall value, I'll also include failed bunt attempts.  The run values for these pitches are dependent on the count and should be similar to the ones shown here.

There will be two sets of leaders and trailers for this metric, which for now I'll refer to as bunting runs - there's bunting runs as a counting stat, and there's bunting runs per 100 attempts.  I don't really like using 100 because it doesn't really have much meaning when it comes to bunting, but it's a nice, round number and is commonly used for rate stats.  According to my numbers, the league average bunt runs/100 in 2010 was -3.46 (-2.95 for bunts not in play and -0.51 for bunts in play), which would mean that overall, attempting to bunt leads to a below-average outcome.
 The top table shows bunting runs, and the bottom table shows bunting runs / 100 (minimum 20 attempts for both).  Both lists include pretty much the same players, but I've included both metrics anyway.

RankNameTeamBunt Runs
1Gregor BlancoBraves/Royals3.27
2Angel PaganMets2.76
3Ben ZobristRays2.26
4Adam JonesOrioles2.00
5Elvis AndrusRangers1.99
6Jose ReyesMets1.93
7Cesar IzturisOrioles1.59
8Julio BorbonRangers1.56
9Ichiro SuzukiMariners1.55
10Cliff PenningtonAthletics1.19




1xJuan PierreWhite Sox-6.27
2xNyjer MorganNationals-3.92
3xChone FigginsMariners-3.79
4xJoe BlantonPhillies-3.48
5xDenard SpanTwins-3.06
6xEmilio BonifacioMarlins-3.04
7xLivan HernandezNationals-2.89
8xMike PelfreyMets-2.81
9xDerek LoweBraves-2.56
10xOrlando HudsonTwins-2.47


RankNameTeamBunt Runs / 100
1Gregor BlancoBraves/Royals9.35
2Adam JonesOrioles8.35
3Ben ZobristRays7.52
4Angel PaganMets5.75
5Ichiro SuzukiMariners5.73
6Jose ReyesMets4.71
7Cesar IzturisOrioles4.55
8Cameron MaybinMarlins3.66
9Elvis AndrusRangers3.56
10Alexi CasillaTwins3.39




1xJoe BlantonPhillies-15.82
2xMike PelfreyMets-12.79
3xZach DukePirates-11.54
4xDerek LoweBraves-11.13
5xLivan HernandezNationals-9.97
6xTrevor CroweIndians-9.87
7xHiroki KurodaDodgers-9.40
8xOrlando HudsonTwins-9.13
9xRoy HalladayPhillies-8.99
10xEmilio BonifacioMarlins-8.94

I think it's fair to say that Gregor Blanco was the majors' best bunter in 2010.  As notable is Juan Pierre's number of bunting runs, which shows that lots of mediocre bunting might not be a good idea.

Hopefully, this post provided some answers about bunting; in addition, it certainly raises some more questions.  Next week, I will expand to data from 2008 and 2009 in order to look at larger sample sizes and year-to-year correlations.