A close look at the Colorado Rockies and the rest of Major League Baseball, from a statistical perspective.
Saturday, April 24, 2010
Rain Out
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.
Sunday, April 18, 2010
U-baldo!
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.
Saturday, April 17, 2010
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.
Thursday, November 5, 2009
The Best Bandbox
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.
Thursday, October 22, 2009
My Thoughts on Sabermetrics
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.
Sunday, October 18, 2009
Franklin Morales, LOOGY
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.
Wednesday, October 14, 2009
Rocktober is Over
A few observations about the playoffs in general so far:
Three pretty good closers blew saves, while one lousy one managed to get two and blow zero. It just goes to show how anything can happen in a short series. Fair or not, Joe Nathan, Jonathan Papelbon, and Huston Street are all now rumored to be with new teams next year. Of course there was probably a chance all three would be gone anyway.
The umpiring was horrible around the league. While it's impossible to say that any team would have or wouldn't have won if the calls had been made correctly, it's reasonable to say that we shouldn't have to wonder. It should be up to the players to win or lose games, not umps. Now is the time to expand instant replay. Before that can happen, a few questions about the procedures must be answered:
Can replay happen quick enough not to slow down games?
What types of plays can be reviewed?
How will the plays be reviewed? (I.e. 5th ump in booth)
How will the Replays be initiated? (Personally, I think it should be up to the umps, although managers should have some way to ask for them. However, I do not think there should be any punishment for a failed review, like in football. I don't want to see anyone lose a game because they asked for a review, and was forced to give up an out. I also would not want to see a play not be reviewed that should, because a manager is afraid of being punished. If you do that you are changing the game too much.)
What will be done if continuity of a play is interrupted and how can you prevent that from happening? (My suggestion is that an ump can give a signal on a close play to "play it out" and that it will be reviewed when the play is over. If the review shows a fair ball, for example, then everyone stays where they ended up. If you do not have this, then a foul call that is over turned will require judgement by the umps to figure out where each runner should be.)
Where does the burden of proof lie? (In football, if a play is inconclusive then the ruling on the field stands. That may be logical, but in some cases, I don't think that would be the best way to handle it. For example if an ump says a fielder came off the base, or a runner missed a base, I feel that a replay should have to clearly show that happened, regardless of what the play was called on the field.)
Hopefully the league will spend some time this winter figuring out these questions and implement replay for next season, before something like this or this happens again.