Doc would probably be a pretty good "fit" for Coors
As Dan O’Dowd set out to acquire pitching this offseason, one of the refrains I kept noticing was discussion (and mostly criticism) of how the pitchers would “fit in at Coors”. After noticing several different suggestions of what that fit would be I decided to pursue it on my own.
In my quest to figure out just what type of pitching staff would be best in Coors, my suspicion was that despite all of the chatter, at the end of the day if the Rockies are to succeed, it would be because they assembled a staff in the same way other successful teams do it: with good pitchers. As odd as that sounds, my hypothesis was that seeking a pitcher of a “particular Coors profile” would be a fool’s errand, as I assume the things that make any of the league’s good pitchers good, would make for a good pitcher in Coors.
To do that, I had to first establish exactly what makes a good pitcher. To do this I separated pitchers into groups. One group of pitchers with Fangraphs WAR above 7, one between 6-7, 5-6,4-5,3-4, 2-3, and 1-2 WAR respectively. First I will share some initial data to clarify what I am talking about. Pitchers that had over 7 WAR (3 pitchers) averaged 240.4 innings pitched (avg of 33 games started). Pitchers with a WAR between 2-3 (23 pitchers) averaged 192.7 innings pitched (avg of 31.1 games started). 7+ WAR pitchers averaged 8.72 K/9 while 1-2 WAR pitchers averaged 6.16 K/9.
What I was seeking was what made an excellent pitcher, not what made for decent. So I looked for statistical categories which had the largest variance from the average pitchers and the excellent pitchers. Examining which categories had little variance between good pitchers and bad pitchers and which categories were glaring differences would show exactly what separated good and average pitchers in terms of statistics.
Let’s start with little variance. For example, you may (or not) be surprised to hear that there was zero difference in BABIP between the studs and the duds. The BABIP for the 7+ WAR pitchers and the 1-2 WAR pitchers were both .284. Another category with little variation was ground ball %. This was very surprising to me. 7+ WAR pitchers had a GB% of 45.9% while 1-2 WAR pitchers had a rate of 45.6% (and this is not a fluke of the 3 studs at 7+, the group of 9 guys between 5-7 WAR had an even lower groundball rate). This means that in a given at bat, Roy Halladay, CC Sabathia, and Justin Verlander had balls go onto the ground at the same rate as the group of guys that included Jeff Karstens, Chris Volstad, and Brett Myers. The point is not that pitchers cannot control ground ball %, but this shows that creating a lot of ground balls does not necessarily lead to success, per se. For example John Lannan (1.3 WAR in 2011) had a GB% that was a whopping 13.9 percentage points higher than Justin Verlander (7 WAR in 2011) last year, 54.10% to 40.20%.
On to the differences. The largest variance in statistics from the top of the heap to the very average in 2011 were, in order of % variance: HR/9, BB/9, HR/FB, and then K/9. The average pitchers had a HR/9 of 1.13 while the best had 0.63. See the table below.
| HR/9 | BB/9 | HR/FB | K/9 | |
| 7+ WAR Pitchers | 0.63 | 1.90 | 7.4% |
8.72 |
|
1-2 WAR Pitchers |
1.13 | 2.80 | 11.8% |
6.16 |
The moral of this story is that bad pitchers give up HR’s and don’t walk people. Not too big of a surprise. The best pitchers keep batters from reaching base (low BB/9 and high K/9), and keep batters from putting the ball in play (K/9). And when batters do put the ball in play they keep the ball from traveling as far (HR/FB), which when combined with not allowing batters to put the ball in play (K/9), results in less total HR’s (HR/9).
Now let’s do some quick thinking on how pitchers achieve these stats to help us decide what makes an excellent pitcher:
- K/9 is from having good stuff (high velocity included) and command, as well as deception in the pitching motion.
- HR/FB is a result of batters making softer contact. This probably comes from good stuff which is commanded (not being able to zero in on a particular pitch type, i.e. batter not swinging as hard) as well as the movement on that stuff making it difficult to hit the sweet spot on the bat. Certainly a deceptive motion will contribute to this as well.
- BB/9 is achieved by having good stuff and commanding it. Good stuff because the pitcher is more comfortable attacking the zone (as well as more movement fooling the batter into swinging at balls) and command because of not missing the strike zone.
- HR/9 is achieved by combining all of these. If you strike out more batters (K/9) there are less balls hit in play that could become HR’s. If you generate softer contact (HR/FB) the balls that are put in play will be less likely to turn into HR’s. I would also argue that a low BB/9 would contribute to a better HR/9 rate, however the connection is less obvious. If a batter knows that a pitcher is likely not going to walk him than he is unable to “zero in on a pitch” in a way that Mark Reynolds may zero in on an AJ Burnett (1.5 WAR, 1.47 HR/9 in 2011) fastball. Because Reynolds knows that Burnett will likely not throw well commanded balls at the edges of the strike zone (imperative to having high BB/9 without getting hit hard), Reynolds will not be as likely to go after balls on the margins of the zone as he would against CC Sabathia (7.1 WAR, 0.64 HR/9 in 2011). Sabbathia’s good stuff leads to his low BB/9 rate (2.31 compared to Burnett’s 3.92 in 2011).
- Of course, the big kicker here is that these key stats compound on each other. Good pitchers give up less HR’s per fly ball (which is nice enough) but when they do give up a home run there will be less likelihood of other players being on base to score due to K/9 and BB/9. That means that the 10 home runs Roy Halladay gave up in 2011 are even less harmless than 10 of the total 31 that AJ Burnett gave up (kind of feels good to pile on to AJ, admit it) because Halladay’s bases were much cleaner due to a whip of 1.04 compared to AJ’s 1.43. And of course WHIP is due to having both good K/9 and BB/9.
Let’s recap here. Statistically speaking, a pitcher becomes excellent by striking batters out, creating soft contact, not walking batters, and not allowing home runs. These are the main stats that separate the excellent from the average. Skill wise a pitcher achieves these statistics by possessing good stuff and by commanding that good stuff. A deceptive motion would contribute as well. While this all seems a bit obvious it is important to establish before we look at exactly how a Coors field staff should be constructed. Should Coors alter which statistics Dan O’Dowd evaluates when acquiring a pitcher?
In part two I will attempt to examine if any of these findings shed light on building a pitching staff that plays 81 games in Coors Field. Is there a formula? Can a fly ball pitcher survive in Coors? Would a staff of the 5 finest sinker ballers in the game be successful? What can we learn from the specific findings about how a baseball behaves at one mile above sea level? This and more soon.
Brandon was born and raised in Colorado and Montana and now resides in Annapolis, MD.
Brandon’s love for the Rockies growing up was cemented in the fall of 2007 while living in London. No, the seven hour time difference from Denver did not keep him from watching every game of that wonderful September and October. He may still be catching up from that sleep deprivation.
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5 comments
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Brendan Giles
February 22, 2012 at 2:55 PM (UTC -6)
I am surprised by the BABIP finding. Your proposal that low HR/FB indicates “softer” contact is sound, but the implication of softer contact should also result in fewer hits and therefore a lower BABIP. All of the reasons you put forth for low HR/FB are good points, but again, should result in fewer total hits, not just homeruns. Command, stuff and keeping hitters off balance prevents solid contact and it is solid contact that leads to both homeruns and hits. Of course, defense is essential to turning soft contact into outs and it is possible that defense is reponsible for the similar BABIP although I have hard time believing bloops and seeing eye groundballs make up the difference. Anyway, looking forward to part 2!
Logan Burdine
February 22, 2012 at 3:35 PM (UTC -6)
We went through this with Felipe Paulino last year. Dave Cameron predicted that he’d be a nice pickup for the Royals, to which I about lost it. Turns out he was right. However, I think where the Rockies screwed up was letting him rely too much on his fastball. As a starter with the Royals, he did a much better job of mixing it up. In Colorado he definitely was not a soft contact guy, but now it seems like that was probably because he wasn’t keeping hitters off balance. It’s easier to make solid contact when you know what’s coming. Also looking forward to Part II.
Brandon Cloud
February 22, 2012 at 4:15 PM (UTC -6)
I was a bit surprised about the BABIP as well. I thought that the best pitchers would have a slightly better BABIP. I figured that batters would take less nice, confident hacks at a Roy Halladay pitch and tend to put balls in play that turned into outs at a higher clip. But he had a BABIP of .298, and CC Sabathia’s was .318. Here is the breakdown from 2011 (hope it formats):
war over 7 0.284
war between 6 -7 0.277
war between 5-6 0.283
war between 4-5 0.283
war between 3-4 0.294
war between 2-3 0.291
war between 1-2 0.284
So one odd thing there is that the 3-4 WAR pitchers had worst BABIP than the 1-2 group. It is odd to me. BUT, I do still feel like it shows that you cannot hunt for quality pitchers by looking at that stat, per se.
Also, an interesting thing is that Jeremy Guthrie’s BABIP in 2011 was exactly .284 as well (including .280 on the road)
CodenameDuchess
February 22, 2012 at 6:48 PM (UTC -6)
Really cool post. However, when I see things like “3 guys” and “9 guys” my small sample size alarm goes off. Would this data hold up over 10 years?
Brandon Cloud
February 23, 2012 at 7:27 AM (UTC -6)
Well yes and no. By nature of the study, there are guys that had “career years”. Roy Halladay’s stats referenced above are far better than his career averages. For example, below are the average stats of the top 15 pitchers in WAR from 2000-2009:
HR/9: 0.90
BB/9: 2.2.
HR/FB: 10.10%
K/9: 7.70
So while the peaks of these few guys wont hold up even for their own careers I believe that it does still represent the differences between excellent and average pitchers. Compare them to these pitchers (2000-2009 WAR leaders #100-125):
HR/9: 1.04
BB/9: 2.99
HR/FB: 9.84%
K/9: 7.14
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