Was Chris Iannetta Afraid to Swing the Bat?

Before Chris Iannetta’s surprising demotion earlier this season, he had come under fire for not being aggressive enough. In particular, by one the Rockies’ tv commentators in a game about a week before being sent down. As a fan of patient hitting, I was pretty ok with Chris not chasing a low fast ball on the outside corner, that would have surely turned into a 4-6-3 double play if he had offered at it. The commentator was a lot quieter when Chris ended up with a base hit.

Having seen a lot of criticism about Chris being too patient, it got me wondering if the perception was true. Was he afraid to swing the bat? Looking at the following tables from Fangraphs, the answer up to this year was clearly NO.

Season	O-Swing%	Z-Swing%	Swing%	Outside	Zone	Total
2006	17.30%	75.90%	48.80%	175	203	378
2007	17.90%	70.60%	46.20%	432	502	934
2008	16.20%	72.30%	44.00%	853	836	1689
2009	16.70%	72.30%	45.60%	709	765	1474
2010	18.80%	68.70%	44.30%	69	72	141
Total *	16.80%	72.20%	45.30%	2239	2377	4616

 

Season	O-Swing%	Z-Swing%	Swing%
2006	23.50%	66.60%	46.10%
2007	25.00%	66.60%	45.90%
2008	25.40%	65.40%	45.90%
2009	25.10%	65.90%	45.20%
2010	28.30%	63.90%	45.10%

 

The first of these tables shows Chris’s swing percentage outside and inside the zone (noted by O-Swing% and Z-Swing% respectively) as well as the total percentage of pitches swung at. The second part of the first table shows the number of pitches seen outside, inside, and total. This is all based on data up to Chris’s demotion.

Compare the first table to the second, which contains Major League averages of swing percentages over each year of Chris’s career. You’ll notice that Chris has been consistently good at not chasing pitches out of the strike zone, which shouldn’t surprise anyone. What me be surprising to some is that Chris is more aggressive on balls in the zone than the average major leaguer. It should be noted there was a slight decrease in pitches swung at in the zone. However, because of the sample size this means that he swung at only two fewer pitches than he normally would have. From Jim Tracy’s view that may have been all he needed to see, even if the stats don’t show the same urgency.

The next question we have to ask is “Has Chris become more aggressive since his recall?” The following table shows Chris’s swing rates since his recall.

O-Swing%	Z-Swing%	Swing%	Outside	Zone	Total
30.07%	68.87%	46.19%	55	104	159

It practically jumps off the page. That outside zone swing percentage has gone up to over 30%. So Chris has become more aggressive, but not in a a good way. Strangely enough, his walk rate has been higher than usual at 21%. His K rate since then, also at 21%, is close to his career norm. Coincidentally or not, the one thing missing is the power. Chris has only 1 double in 36 pa’s since being recalled. Of course it’s probably too early to make any real conclusions out of that.

This is something worth following over the course of the year. Something tells me Chris won’t develop from a guy who has been criticized for being too patient, to someone who doesn’t see any pitches he doesn’t like.

Rain Out

First off, I want to say how unfortunate it is that Rockies President, Keli McGregor, passed away earlier this past week. From what I know of him, he was very nice and sincere person. All the best to his family and friends.

It is somewhat fitting that we have dreary weather in the forecast for this weekend. Tonight's game got postponed due to rain/cold and will be made up tomorrow as part of a true doubleheader. I must say that I was disappointed to have the game called right I was getting to my seat, but I am pretty excited to go to the doubleheader tomorrow. I don't recall ever going to a doubleheader before, so this will be my first. I only hope neither of the games get rained out. Otherwise, I'll look forward to watching 'em play two.

U-baldo!

I'm pretty wound up right now, but who could blame me after this happened. Looking back I wonder if people realize how special this is. Obviously, anyone should realize that it any no hitter is a big deal. It gets even bigger to throw the first in the history of your team, for any club. What really makes this special, is how miserable the Rockies pitching staff had been through most of the team's history. Until the past few years, the pitching staff was notoriously awful. Part of the improvement may be due to bringing in the humidor, but a large part of that was simply lack of pitching talent. Who can forget the immortal Jamey Wright or David Nied, and that legendary bullpen crew of Steve Reed, Darren Holmes, and Mike "Moonshot" Munoz? I certainly can't.

We've come a long way. We've gone from hoping the starter could hold the other team to less than 5 runs, to expecting quality starts every time out, and believing that a few members of the staff could throw a no-hitter. Now, it's actually happened. I for one won't forget Ubaldo's performance. More than that I won't forget the road the Rockies organization has traveled to have a starting pitcher who is even capable of throwing a no hitter, let alone actually doing it.

Panic Time?!?!

This is always sort of a frustrating time for me to be a baseball fan. Every year it seems people get hysterical when someone gets off to a slow start, when they just need to relax and let things develop. There are a lot of examples of people jumping to conclusions base on small samples. Your centerfielder is hitting .190? Bench him? After 37 AB’s, probably not. Your team is playing .500 ball after 10 games, so turn the whole roster over? No. The team has scored 51 runs in those 10 games, and has scored at least 4 runs in 9 of those 10 games, so make drastic changes to the lineup? I don’t think so! The solution is to have some patience and let everything settle, if you will.

Earlier I read Dexter Fowler was a “liability” in the lineup, because of his .189 batting average, so I’ll use him as an example. Dex’s batting average has come in 37 at bats, which is pretty obviously not very many. So how many is enough to actually worry? We can build a simple hypothesis test for a player’s batting average based on his current average, and his number of at bats. Given Dex’s ability to get on base (which is the real thing we care about, and deserves more analysis later), he needs to bat at least .250 to be a useful part of the lineup. If I’m Dan O’Dowd/Jim Tracy I’m going to want strong evidence that he’s not before I hit the panic button. Assuming at bats follow a typical binomial pattern, we test the hypothesis that the player is a .250 hitter after n at bats. It turns out that the number of AB’s that a player batting .189 can have before we feel truly confident that he’s not at least a .250 hitter is 111. (I’m more than willing to explain my math, if anyone asks.) That means Dexter only has 74 more AB's to get his average above .190. Don’t worry, something tells me he’ll do it.

The Best Bandbox

Recently I was downloading some data for a project that I have planned relating to park factor, when I had a moment of inspiration. It occurred to me that one could get a rough idea of how easy it is to hit a home run, at a given stadium, simply by finding the percentage of batted balls that were home runs. In other words, dividing the number of home runs by the number of AB's where the batter did not strike out would yield a home run rate. The higher the rate, the easier it is to hit home runs. The equation is simple and looks like this:

R=HR/(AB-K)

Before doing this, my belief was that Coors field would not ave the highest rate. I also had a suspicion that a certain stadium would have the highest rate. So I ran the numbers, looking at both the home team's and away teams' home run rate for each stadium in 2009. Here are the results:

Club	Stadium	Team	Opponents	Total
NYY	Yankee Stadium III	5.96%	4.61%	5.30%
TEX	Rangers Ballpark in Arlington	5.80%	4.02%	4.87%
PHI	Citizens Bank Park	5.02%	4.42%	4.71%
MIL	Miller Park	4.83%	4.55%	4.69%
CHA	Comiskey Park II	4.77%	4.03%	4.40%
TOR	SkyDome	4.67%	4.07%	4.37%
CIN	Great American Ballpark	4.46%	4.20%	4.33%
TAM	Tropicana Field	4.97%	3.70%	4.31%
BOS	Fenway Park	5.38%	3.26%	4.30%
BAL	Oriole Park at Camden Yards	4.15%	4.42%	4.29%
LAA	Angel Stadium of Anaheim	4.01%	4.53%	4.27%
DET	Comerica Park	4.26%	3.98%	4.12%
MIN	Hubert H. Humphrey Metrodome	4.22%	3.87%	4.04%
ARI	Chase Field	4.07%	3.82%	3.94%
COL	Coors Field	4.59%	3.30%	3.93%
FLA	Dolphin Stadium	3.99%	3.74%	3.87%
MLB Average		4.00%	3.63%	3.81%
CHN	Wrigley Field	3.87%	3.74%	3.80%
HOU	Minute Maid Park	3.57%	3.84%	3.71%
WAS	Nationals Park	3.57%	3.57%	3.57%
SEA	Safeco Field	3.50%	3.51%	3.51%
OAK	Network Associates Coliseum	3.25%	3.07%	3.16%
PIT	PNC Park	3.39%	2.92%	3.15%
SDG	PetCo Park	3.05%	3.16%	3.11%
SFG	AT&T Park	3.11%	3.07%	3.09%
CLE	Jacobs Field	3.10%	3.05%	3.07%
KAN	Kauffman Stadium	2.87%	3.01%	2.94%
LAD	Dodger Stadium	3.18%	2.68%	2.94%
NYM	Citi Field	2.22%	3.61%	2.92%
ATL	Turner Field	3.18%	2.55%	2.87%
STL	Busch Stadium II	3.06%	2.41%	2.73%

As you can see, the new Yankee Stadium comes out on top, with 5.3% of batted balls hit here turning into home runs. So that's it, the new Yankee Stadium is the easiest place to hit it out. Coors Field, as I guessed, was not really an easy place to hit home home runs. Unfortunately it's not that simple. These results may have more to do with each team's ability to hit home runs, and of their pitching staff's inability to keep the ball in the yard. So a team with lot of power and poor pitching is likely to score high on this list.

So in order to adjust for a team's ability, a new value must be found. The first step that I took was to recalculate the above table for each team while on the road. The following table shows these rates:

Club	Team	Opponents	Total
PHI	5.10%	4.09%	4.61%
CLE	4.27%	4.89%	4.58%
TAM	4.45%	4.62%	4.54%
BOS	4.25%	4.40%	4.32%
NYY	4.57%	3.86%	4.23%
TOR	4.30%	4.13%	4.22%
MIL	3.71%	4.69%	4.21%
DET	4.02%	4.27%	4.14%
TEX	4.70%	3.58%	4.14%
KAN	3.63%	4.65%	4.13%
SDG	3.56%	4.55%	4.05%
SEA	3.69%	4.23%	3.95%
COL	4.63%	3.24%	3.92%
ARI	4.04%	3.76%	3.89%
WAS	3.71%	3.90%	3.80%
BAL	2.79%	4.79%	3.78%
MLB Average	3.63%	3.83%	3.73%
MIN	3.28%	4.17%	3.72%
STL	4.15%	3.18%	3.67%
CHA	3.55%	3.66%	3.60%
CIN	2.88%	4.27%	3.57%
FLA	3.33%	3.72%	3.52%
LAA	3.57%	3.45%	3.51%
HOU	2.83%	4.21%	3.50%
CHN	3.62%	4.01%	3.39%
LAD	3.23%	3.45%	3.33%
OAK	2.72%	3.90%	3.29%
ATL	3.47%	3.02%	3.25%
PIT	2.42%	3.89%	3.17%
SFG	2.54%	3.83%	3.14%
NYM	1.98%	3.47%	2.71%

In this table it can be seen that the Phillies had the highest rate of batted balls becoming home runs. This was largely due to their ability to hit home runs at a high rate. While on the road, 5.1% of batted balls by the Phillies became home runs. While at home, only 5.02% of their batted balls were home runs. Their opponenets did benefit by playing in Philly, with 4.42% of batted balls at the Bank becoming home runs and only 4.09% becoming home runs in Phillies' away games.

The next step is to divide the data in the two tables to determine the increase (or decrease) in rate of home runs to batted balls when a team is in it's home park. If there is an increase in thee ratios when playing at home, then playing in that stadium is beneficial to hitting home runs. The following table shows the ratios:

Club	Stadium	Team	Opponents	Total
NYY	Yankee Stadium III	1.3056	1.1962	1.2519
CHA	Comiskey Park II	1.3416	1.1034	1.2201
LAA	Angel Stadium of Anaheim	1.1240	1.3148	1.2180
CIN	Great American Ballpark	1.5495	0.9856	1.2118
TEX	Rangers Ballpark in Arlington	1.2330	1.1252	1.1769
BAL	Oriole Park at Camden Yards	1.4903	0.9230	1.1341
CHN	Wrigley Field	1.0678	0.9334	1.1240
MIL	Miller Park	1.3014	0.9704	1.1140
FLA	Dolphin Stadium	1.2000	1.0060	1.0988
MIN	Hubert H. Humphrey Metrodome	1.2859	0.9264	1.0865
NYM	Citi Field	1.1203	1.0393	1.0776
HOU	Minute Maid Park	1.2611	0.9129	1.0592
TOR	SkyDome	1.0866	0.9850	1.0360
PHI	Citizens Bank Park	0.9838	1.0789	1.0229
MLB Average		1.1026	0.9469	1.0220
ARI	Chase Field	1.0083	1.0166	1.0115
COL	Coors Field	0.9919	1.0183	1.0022
PIT	PNC Park	1.4016	0.7524	0.9945
BOS	Fenway Park	1.2665	0.7404	0.9943
DET	Comerica Park	1.0596	0.9325	0.9942
SFG	AT&T Park	1.2255	0.8025	0.9834
OAK	Network Associates Coliseum	1.1973	0.7875	0.9600
TAM	Tropicana Field	1.1169	0.8009	0.9511
WAS	Nationals Park	0.9643	0.9162	0.9393
SEA	Safeco Field	0.9481	0.8310	0.8870
LAD	Dodger Stadium	0.9851	0.7783	0.8815
ATL	Turner Field	0.9157	0.8462	0.8812
SDG	PetCo Park	0.8576	0.6942	0.7679
STL	Busch Stadium II	0.7373	0.7589	0.7429
KAN	Kauffman Stadium	0.7897	0.6460	0.7110
CLE	Jacobs Field	0.7257	0.6239	0.6706

As it turns out, new Yankee Stadium is the easiest stadium in the Major Leagues to hit a home run, with 25.19% more batted balls landing in the seats than in Yankee away games. Although Yankee Stadium provided the biggest increase in home run rate, the Yankees didn't benefit as much as some other teams. The rate of home runs was 55% higher at home for the Cincinnatti Reds than when they were on the road. Their opponents actually hit homeruns at a slightly lesser rate, when coming into Great American Ballpark. As it turns out, the Rockies had a tougher time in 2009 hitting home runs while on the road, than while at Coors. Their opponents did benefit slightly, but overall the rate was nearly the same as in away games.

This analysis provides a new look on whether or not a stadium really is a good home run park or not. Unlike park factor, which only considers the amount of homeruns per game, this method looks deeper and find the number of homeruns per batted ball. This is important since other factors may lead to increased number of plate appearances per game, in certain stadiums. The additional plate appearances add to the number of homeruns, thus slightly inflating the home run park factor. Like park factor, there is still a flaw which I will discuss further in a future post. Until then, hopefully I have shed some light on which ballparks really are home run friendly and which are not.

My Thoughts on Sabermetrics

Sabermetrics, if you've never heard of it, is the use of various statistical methods to evaluate baseball players and teams. It is actually somewhat controversial because many people in MLB like to stick to their traditions, and sabermetrics flies in the face of that. There are countless jokes about sabermetricians all living in their mom's basement and don't actually watch the games. In spite of the resistance, the use of sabermetrics has actually become more common in recent years. Several teams, most notably the Oakland A's, Tampa Bay Rays, and Boston Red Sox have used high level analysis to help build their teams.

I decided to start blogging with the hopes I can add something to the science. If nothing else, I could provide a unique perspective to my hometown team, the Colorado Rockies. Before I go further with my work there are a few thoughts on the science I would like to share.

First of all, I actually believe that sabermetrics backs up a lot of what traditional baseball thinking has always taught. For example, the old saying "Don't make the first or third out at third base" can be supported using sabermetrics. Of course you shouldn't be willing to make any outs, but the 1st and third are especially damaging. I also think that things that happen on the field can be explained using sabermetrics, such as a player who seems to always find the hole may indeed have a high batting average on balls in play (BABIP).

I don't necessarily agree with everything that sabermetrics tends to support. For one thing I don't believe there is a tell all statistic. Every stat tells you something about a different player's ability. Even though, on-base percentage (OBP) is more valuable than batting average (AVG), I don't think it's totally useless. I do think that it can show the likelihood of a batter driving in a runner in "scoring position." Of course a high slugging percentage (SLG) will indicate a batter is more likely to drive in a runner who is NOT in scoring position. There is also the notion that sabermetrics is only about walks and home runs. I would disagree and feel that it is also about singles, doubles, and the occasional triple. Another common belief among stat guys, that I don't really believe, is that pitchers have no control over their BABIP.

I am doing this for the fun of it and to hopefully gain more insight to the game. But if any team's GM reads this and wants to hire me, please send me a message. I'll get back to you right away. I also welcome any constructive comments about my work. However, if you're going to drop a "momma's basement" joke on me, you can get lost.

There are a number of projects that I plan to work on as I write. I plan to look closer at park factors, BABIP from the hitter's and the pitchers perspective, and would even like to do some work with Pitch F/X data. I am really excited about all of this. I only wish I had started doing this sooner. There's a lot of discoveries to be made, so I had better get to work.

Franklin Morales, LOOGY

It's funny how a bad outings (or a streak of them) can affect people's perception of a player. Case in point, is Franklin Morales who had a breakout season in a relief role. He pitched well enough that when Huston Street was injured, he took over the closer role. He recorded saves in his first 6 opportunities, then began to struggle. His struggles, highlighted by a 5 run, 7th inning in Los Angeles left many fans feeling that he should have been left off the roster. There was one good reason he made it: he had been very tough against left handed batters. With Philly's lineup of left handed, the move to include Morales, only made sense.

The move paid off, with Franklin pitching 2 and 1/3 perfect innings in the first three games of the series. All of that good work was quickly forgotten, however, thanks to his 3 walk (1 intentional) performance in game 4. Of course he did do one very important thing that inning - get Ryan Howard out. Many fans were again ready to show Morales the door, but I say hold on.

First off, I am never one to judge a player based on one stretch. It's much more telling to look at the player's body of work. One thing that pops out about Morales' career is how good he has been against lefty batters. I feel the Rockies should keep him since he has a great chance to be an outstanding left handed one out guy (a LOOGY).

Over his 3 year career, Morales has given up an AVG/SLG/OBP of .185/.276/.277 vs left handers (.175/.247/.275 in 2009). His numbers vs. righties are .274/.373/.396 in his career and .277/.366./405 in 2009. While facing righties he has clearly been hittable, although they have not hit him for much power. Against lefties he has been flat out dominant. That kind of arm is not easily replaced.

One of the big criticisms of Morales has been his tendency to walk too many batters. This is certainly justified, since has was walked 12.4% of the batters he has faced in his career. Interestingly, his splits again tell a deeper story. While walking 13.3% of right handed batters, Morales has walked only 9.2% of lefties, a more acceptable rate.

Hopefully the Rockies can take a close look at his effectiveness vs left handers and keep him around. More importantly, I hope they know to use him vs lefty bats and limit his work vs righties. After all, a misused reliever can do as much damage as a bad one.